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Master of Business Administration317 21
RESEARCH METHODSII - Semester
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ALAGAPPA UNIVERSITY [Accredited with ’A+’ Grade by NAAC (CGPA:3.64) in the Third Cycle
and Graded as Category–I University by MHRD-UGC]
KARAIKUDI – 630 003 DIRECTORATE OF DISTANCE EDUCATION
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ALAGAPPA UNIVERSITY [Accredited with ’A+’ Grade by NAAC (CGPA:3.64) in the Third Cycle
and Graded as Category–I University by MHRD-UGC]
KARAIKUDI – 630 003 DIRECTORATE OF DISTANCE EDUCATION
Master of Business Administration317 21
RESEARCH METHODSII - Semester
You are instructed to update the cover page as mentioned below:
1. Increase the font size of the Course Name.
2. use the following as a header in the Cover Page.
ALAGAPPA UNIVERSITY [Accredited with ’A+’ Grade by NAAC (CGPA:3.64) in the Third Cycle
and Graded as Category–I University by MHRD-UGC]
KARAIKUDI – 630 003 DIRECTORATE OF DISTANCE EDUCATION
You are instructed to update the cover page as mentioned below:
1. Increase the font size of the Course Name.
2. use the following as a header in the Cover Page.
ALAGAPPA UNIVERSITY [Accredited with ’A+’ Grade by NAAC (CGPA:3.64) in the Third Cycle
and Graded as Category–I University by MHRD-UGC]
KARAIKUDI – 630 003 DIRECTORATE OF DISTANCE EDUCATION
RESEA
RC
H M
ETHO
DS
Master of Business Adm
inistration
Master of Business AdministrationII - Semester
317 21
Directorate of Distance Education
RESEARCH METHODS
ALAGAPPA UNIVERSITY[Accredited with ‘A+’ Grade by NAAC (CGPA:3.64) in the Third Cycle
and Graded as Category–I University by MHRD-UGC]
(A State University Established by the Government of Tamil Nadu)
KARAIKUDI – 630 003
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Authors:Naseem Abidi, Associate Professor, Jaypee Business School, Jaypee Institute of Information Technology, NoidaUnits (1.0-1.2, 1.3, 1.4, 1.5-1.9, 4, 5.3-5.9, 6.2-6.2.1)Dr Deepak Chawla, Distinguished Professor, Dean (Research & Fellow Programme), International Management Institute (IMI), New DelhiDr Neena Sondhi, Professor, International Management Institute (IMI), New DelhiUnits (1.2.1, 1.4.1, 2, 5.0-5.2, 6.0-6.1, 6.2.2-6.9, 7, 10.2.1, 12.0-12.2, 12.3-12.3.1, 13.0-13.1, 13.2.2-13.3.4, 13.5-13.9)Vikas® Publishing House: Units (3, 8, 9, 10.0-10.2, 10.3-10.10, 11, 12.2.1, 12.3.2-12.5, 12.6-12.10, 13.2-13.2.1, 13.4-13.4.1, 14)
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SYLLABI-BOOK MAPPING TABLE Research Methods
BLOCK I: FUNDAMENTALS OF RESEARCHUNIT 1: ResearchBasis:Definitionandapplicationsofbusinessresearch;
Types of research – descriptive, exploratory, correlational,explanatory,quantitative,qualitative;Stepsintheresearchprocess;establishingoperationaldefinitions.
UNIT 2: Research scope -Recent advancements in research.DistinctionbetweenPure&Applied,Historical&Futuristic,Analytical&Synthetic,Descriptive&Prescriptive,Survey&ExperimentalandCase&GenericResearches.
UNIT 3: PlanningofResearch:Researchproblem–Identification,selectionandformulationofresearchproblem–Reviewofliteratureinthefieldofbusiness-Identifyingobjectivesoftheresearch.
UNIT 4: Economicmanagement:Use in identifyingResearchGaps andTechniques –Hypothesis –Meaning – Sources andTypes ofHypothesis–HypothesisFormulationfortesting–Researchdesign–Factorsaffectingresearchdesign–Evaluationofresearchdesign.
BLOCK II: SAMPLING AND ITS TYPESUNIT 5: Variables construction forHypothesis: Identifying variables -
Constructing hypotheses – functions, characteristics, types ofhypotheses-Significanceofresearchinsocialsciences–Inductionanddeduction.
UNIT 6: SamplingDesign: Censusmethod and samplingmethod forinvestigation –Principle of sampling – Essentials of a goodsampling – sampling frame;Methods of sampling: Probability,non-probability,mixedsamplingdesigns.
UNIT 7: ConstructionofsamplingforFiniteandInfinitepopulations–Samplesizedetermination–Calculations-Factorsaffectingthesizeofthesample–Biasedsample–Samplingandnon-samplingerrors.
UNIT 8: Sources andCollection ofData:Sources of data –Primary andsecondarydata–Modesofdatacollection–Observation:TypesandTechniques–Interview:Typesandconduct–Preparationforan interview –Effective interview techniques –Limitations ofinterview.
BLOCK III: TOOLS OF DATA COLLECTIONUNIT 9: Schedule:Meaning and kinds –Essentials of a good schedule
–Procedure for the formulation of a schedule –Questionnaire:Meaningandtypes–Formatofagoodquestionnaire–SchedulesVs.Questionnaires.
UNIT 10:Scalingtechniques:Meaning,Importance,Typesofmeasurementscales –Nominal, Ordinal, Interval, Ratio;Methods of theirconstructionofQuestionnairesorSchedules–Pre-testingofDataCollectionTools-ValidityandReliability–Methods.
UNIT 11:ProcessingandAnalysisofData:Meaning–Importance–Processof data analysis –Editing–Coding–Tabulation–Diagrams–Univariate,BivariateandMulti-variantanalysis.
Syllabi Mapping in Book
Unit 1: Research Basis (Pages 1-20);
Unit 2:ResearchScope (Pages 21-36);
Unit 3:PlanningofResearch (Pages 37-51);
Unit 4:EconomicManagement (Pages 52-67)
Unit 5:VariablesConstructionforHypothesis (Pages 68-82);
Unit 6:SamplingDesign (Pages 83-104);
Unit 7:Constructionof SamplingforFiniteand
InfinitePopulations (Pages 105-116);
Unit 8:Sourcesand CollectionofData-I
(Pages 117-127)
Unit 9:Sourcesand CollectionofData-II
(Pages 128-143);Unit 10:Sourcesand CollectionofData-III
(Pages 144-174);Unit 11:Processingand
AnalysisofData (Pages 175-191)
BLOCK IV: HYPOTHESIS AND REPORT WRITINGUNIT 12:TestofSignificance:FundamentalsonTestProcedure-Testing
for significance ofMean/Proportion anddifferencebetweenMeans/Proportions- FTest forMeans andChi-square testContingencyTable-ParametricTest:Ttest,FTestandZtest.
UNIT 13:Non-parametricTest: Concept andTypes:MannWhitneyTest-Test,KruskalWallis, sign test.Multivariate analysis-factor, cluster,MDS,Discriminant analysis -Theprocessofinterpretation ofTestResults–Guidelines formaking validinterpretation
UNIT 14:ReportWriting : Role and types of reports –Contents ofresearchreport–Stepsinvolvedindraftingreports–Principlesof good reportwriting –GrammaticalQuality –Languageflow-DataSupport-DiagrammaticElucidation-ReferencesandAnnotations–ClarityandBrevityofexpressions-FeaturesofagoodReport-Criteriaforevaluatingresearchreports/researchfindings.
Unit 12:TestofSignificance (Pages 192-215);
Unit 13:Overviewof Non-ParametricTests
(Pages 216-239);Unit 14:ReportWriting
(Pages 240-270)
CONTENTS
INTRODUCTION
BLOCK I: FUNDAMENTALS OF RESEARCHUNIT 1 RESEARCH BASIS 1-20 1.0 Introduction 1.1 Objectives 1.2 DefinitionofBusinessResearch
1.2.1 ApplicationsofBusinessResearch 1.3 TypesofResearch 1.4 StepsintheResearchProcess
1.4.1 EstablishingOperationalDefinitions 1.5 AnswerstoCheckYourProgressQuestions 1.6 Summary 1.7 KeyWords 1.8 SelfAssessmentQuestionsandExercises 1.9 FurtherReadings
UNIT 2 RESEARCH SCOPE 21-36 2.0 Introduction 2.1 Objectives 2.2 RecentAdvancementsinResearch:OnlineResearch 2.3 DistinctionbetweenDifferentTypesofResearches 2.4 AnswerstoCheckYourProgressQuestions 2.5 Summary 2.6 KeyWords 2.7 SelfAssessmentQuestionsandExercises 2.8 FurtherReadings
UNIT 3 PLANNING OF RESEARCH 37-51 3.0 Introduction 3.1 Objectives 3.2 ResearchProblem
3.2.1 Identification,SelectionandFormulationofResearchProblem 3.2.2 IdentificationofObjectivesoftheResearch 3.2.3 StatementofResearchProblemandCostandValueInformation
3.3 ReviewofLiteratureintheFieldofBusiness 3.4 AnswerstoCheckYourProgressQuestions 3.5 Summary 3.6 KeyWords 3.7 SelfAssessmentQuestionsandExercises 3.8 FurtherReadings
UNIT 4 ECONOMIC MANAGEMENT 52-67 4.0 Introduction 4.1 Objectives 4.2 UseinIdentifyingResearchGapsandTechniques 4.3 Hypothesis:Meaning,Sources,TypesofHypothesis,andHypothesisTesting 4.4 ResearchDesign
4.4.1 FactorsAffectingResearchDesign 4.4.2 EvaluationofResearchDesign
4.5 AnswerstoCheckYourProgressQuestions 4.6 Summary 4.7 KeyWords 4.8 SelfAssessmentQuestionsandExercises 4.9 FurtherReadings
BLOCK II: SAMPLING AND ITS TYPES
UNIT 5 VARIABLES CONSTRUCTION FOR HYPOTHESIS 68-82 5.0 Introduction 5.1 Objectives 5.2 ConstructingHypothesis
5.2.1 IdentifyingVariables 5.2.2 CharacteristicsandFunctions 5.2.3 TypesofHypotheses
5.3 SignificanceofResearchinSocialSciences 5.4 ScientificMethod:InductionandDeduction 5.5 AnswerstoCheckYourProgressQuestions 5.6 Summary 5.7 KeyWords 5.8 SelfAssessmentQuestionsandExercises 5.9 FurtherReadings
UNIT 6 SAMPLING DESIGN 83-104 6.0 Introduction 6.1 Objectives 6.2 MeaningofSamplingDesign
6.2.1 PrincipleofSamplingandEssentialsofGoodSampling 6.2.2 SamplingConceptsandSamplingFrame
6.3 CensusMethodandSamplingMethodforInvestigation 6.4 MethodsofSampling:Probability,Non-ProbabilityandMixedSamplingDesignorSystematic
Sampling 6.5 AnswerstoCheckYourProgressQuestions 6.6 Summary 6.7 KeyWords 6.8 SelfAssessmentQuestionsandExercises 6.9 FurtherReadings
UNIT 7 CONSTRUCTION OF SAMPLING FOR FINITE AND INFINITE POPULATIONS 105-116
7.0 Introduction 7.1 Objectives 7.2 SampleSizeDetermination,CalculationandFactorsAffectingtheSizeoftheSample 7.3 SamplingandNon-SamplingErrors
7.3.1 BiasedSample 7.4 AnswerstoCheckYourProgressQuestions 7.5 Summary 7.6 KeyWords 7.7 SelfAssessmentQuestionsandExercises 7.8 FurtherReadings
UNIT 8 SOURCES AND COLLECTION OF DATA-I 117-127 8.0 Introduction 8.1 Objectives 8.2 SourcesofData:PrimaryDataandSecondaryData 8.3 ModesofDataCollection
8.3.1 Interview:Types,Conduct,Preparation,EffectiveTechniquesandLimitation 8.3.2 Observation:TypesandTechniques
8.4 AnswerstoCheckYourProgressQuestions 8.5 Summary 8.6 KeyWords 8.7 SelfAssessmentQuestionsandExercises 8.8 FurtherReadings
BLOCK III: TOOLS OF DATA COLLECTION
UNIT 9 SOURCES AND COLLECTION OF DATA-II 128-143 9.0 Introduction 9.1 Objectives 9.2 Questionnaire:Meaning,TypesandFormatofaGoodQuestionnaire 9.3 Schedule:Meaning,Kinds,Essentials,ProcedurefortheFormulationofaSchedule
9.3.1 SchedulesVs.Questionnaires 9.4 AnswerstoCheckYourProgressQuestions 9.5 Summary 9.6 KeyWords 9.7 SelfAssessmentQuestionsandExercises 9.8 FurtherReadings
UNIT 10 SOURCES AND COLLECTION OF DATA-III 144-174 10.0 Introduction 10.1 Objectives 10.2 ScalingTechniques:Meaning,Importance,andClassification
10.2.1 TypesofMeasurementScales:Nominal,Ordinal,IntervalandRatio 10.3 MethodsoftheirConstructionofQuestionnairesorSchedules 10.4 Pre-TestingofDataCollectionTools 10.5 ValidityandReliabilityMethods
10.6 AnswerstoCheckYourProgressQuestions 10.7 Summary 10.8 KeyWords 10.9 SelfAssessmentQuestionsandExercises 10.10 FurtherReadings
UNIT 11 PROCESSING AND ANALYSIS OF DATA 175-191 11.0 Introduction 11.1 Objectives 11.2 Meaning,ImportanceandProcessofDataAnalysis:Editing,Coding,TabulationandDiagrams 11.3 TypesofAnalysis 11.4 AnswerstoCheckYourProgressQuestions 11.5 Summary 11.6 KeyWords 11.7 SelfAssessmentQuestionsandExercises 11.8 FurtherReadings
BLOCK IV: HYPOTHESIS AND REPORT WRITING
UNIT 12 TEST OF SIGNIFICANCE 192-215 12.0 Introduction 12.1 Objectives 12.2 FundamentalsofTestProcedure
12.2.1 TypesofHypothesisTesting 12.3 ParametricTests
12.3.1 TestsConcerningMeansinCaseofSingleandTwoPopulationMeans-Z-test 12.3.2 HypothesisTestingforComparingTwoRelatedTerms:T-test 12.3.3 HypothesisTestingofProportions,DifferencebetweenProportionsandComparingVariance 12.3.4 TestingtheEqualityofVariancesofTwoNormalPopulations:F-test
12.4 StatisticalTechniquesofHypothesisTesting 12.5 Chi-SquareTestandContingencyTable 12.6 AnswerstoCheckYourProgressQuestions 12.7 Summary 12.8 KeyWords 12.9 SelfAssessmentQuestionsandExercises 12.10 FurtherReadings
UNIT 13 OVERVIEW OF NON-PARAMETRIC TESTS 216-239 13.0 Introduction 13.1 Objectives 13.2 Non-ParametricTest:ConceptandTypes
13.2.1 Mann-WhitneyTest 13.2.2 KruskalWallis 13.2.3 SignTest
13.3 MultivariateAnalysis 13.3.1 FactorAnalysis 13.3.2 Cluster 13.3.3 MultidimensionalScaling(MDS) 13.3.4 DiscriminantAnalysis
13.4 TheProcessofInterpretationofTestResults 13.4.1 GuidelinesforMakingValidInterpretation
13.5 AnswerstoCheckYourProgressQuestions 13.6 Summary 13.7 KeyWords 13.8 SelfAssessmentQuestionsandExercises 13.9 FurtherReadings
UNIT 14 REPORT WRITING 240-270 14.0 Introduction 14.1 Objectives 14.2 RoleandTypesofResearchReports 14.3 StepsInvolvedinDraftingResearchReports 14.4 ContentsofResearchReport 14.5 ReportWriting:Principles,FeaturesandCriteria
14.5.1 PrinciplesofaGoodReportWriting 14.5.2 FeaturesofaGoodResearchReport 14.5.3 CriteriaforEvaluatingResearchReports/Findings
14.6 ResearchReport:LanguageFlowandGrammaticalQuality 14.6.1 ClarityandBrevityofExpressions 14.6.2 ReferencesandAnnotations
14.7 DataSupportandDiagrammaticElucidation 14.8 AnswerstoCheckYourProgressQuestions 14.9 Summary 14.10 KeyWords 14.11 SelfAssessmentQuestionsandExercises 14.12 FurtherReadings
Introduction
NOTES
Self-Instructional Material
INTRODUCTION
Research is the quest for knowledge or a systematic investigation in order to establish facts. It helps to solve problems and to increase knowledge. The basic aim of research is to discover, interpret and develop methods and systems to advance human knowledge on diverse scientific matters. There are different types of research, such as exploratory, descriptive and experimental. Exploratory research is done when few or no previous studies of the subject exist. Descriptive research is used to classify and identify the characteristics of a subject. Experimental research suggests or explains why or how something happens. Thus, one of the primary aims of research is to explain new phenomena and generate new knowledge. Before conducting any research, a specific approach is to be decided; this is called research methodology. Research methodology refers to the way research can be conducted. It is also known as the process of collecting data for various research projects and helps to understand both the products as well as the process of scientific enquiry. A research process involves selection and formulation of a research problem, research design, sample strategy or sample design, as well as the interpretation and preparation of research report.
A few important factors in research methodology include the validity and reliability of research data and the level of ethics. A job is considered half done if the data analysis is conducted improperly. Formulation of appropriate research questions and sampling probable or non-probable factors are followed by measurement using survey and scaling techniques. A research design is a systematic plan for collecting and utilizing data so that the desired information can be obtained with sufficient accuracy. Therefore, research design is the means of obtaining reliable, authentic and generalized data. Research methodology is a very important function in today’s business environment. There are many new trends in research methodology through which an organization can function in this dynamic environment.
This book, Research Methods, has been designed keeping in mind the self-instruction mode (SIM) format and follows a simple pattern, wherein each unit of the book begins with the Introduction followed by the Objectives for the topic. The content is then presented in a simple and easy-to-understand manner, and is interspersed with Check Your Progress questions to reinforce the student’s understanding of the topic. A list of Self-Assessment Questions and Exercises is also provided at the end of each unit. The Summary and Key Words further act as useful tools for students and are meant for effective recapitulation of the text.
NOTES
Self-InstructionalMaterial 1
Research BasisBLOCK - I
FUNDAMENTALS OF RESEARCH
UNIT 1 RESEARCH BASISStructure 1.0 Introduction 1.1 Objectives 1.2 DefinitionofBusinessResearch
1.2.1 ApplicationsofBusinessResearch 1.3 TypesofResearch 1.4 StepsintheResearchProcess
1.4.1 EstablishingOperationalDefinitions 1.5 AnswerstoCheckYourProgressQuestions 1.6 Summary 1.7 Key Words 1.8 SelfAssessmentQuestionsandExercises 1.9 FurtherReadings
1.0 INTRODUCTION
Broadly speaking, the search for knowledge is referred to as research.Researchcanalsobedefinedasanartofscientificinvestigation.Withintheacademic scenario, researchcomprisesdefiningand redefiningproblems,formulatinghypothesisor suggestedsolutions;collecting,organisingandevaluatingdata;makingdeductionsandreachingconclusions;andintheendcarefullytestingtheconclusionstodeterminewhethertheyfittheformulatinghypothesis.Thisunitwillprovideanoverviewofresearch.Itwilldiscusstheapplicationandtypesofresearch.Itwillthengoontodiscussthestepsintheresearchprocess.
1.1 OBJECTIVES
Aftergoingthroughthisunit,youwillbeableto: •Defineresearch •Describetheapplicationofresearchinvariousfields •Explainthedifferenttypesofresearch •Examinethevariousstepsintheresearchprocess
Research Basis
NOTES
Self-Instructional 2 Material
1.2 DEFINITION OF BUSINESS RESEARCH
A research generally beginswith a question or a problem.The purposeof research is tofindsolutions through theapplicationof systematicandscientificmethods.
Meaning and Definitions
Researchisatoolthatisabuildingblockandasustainingpillarofeverydiscipline—scientificorotherwise—thatoneknowsof.Beforecomprehendingthetruemeaningoftheterm,wewouldliketomakeitclearthatthisbookprimarilyfocusesontheprocessofbusinessresearch.Thepremiseofthisdecision-orientedenquiryisvastandmayrangefromthesimplisticview,whichinvolvescompilationandvalidationofinformation,toanexhaustivetheoryandmodelconstruction.Todistinguishbetweennon-scientificandscientificmethod,wewouldliketoconsiderafewdefinitionsofresearch.
OneoftheearliestdistinctionswasmadebyLundberg(1942)whostated‘Scientificmethodsconsistofsystematicobservation,classification,andinterpretationofdata.Nowobviously,thisprocessisoneinwhichnearlyallpeopleengageintheirdailylife.Themaindifferencebetweenourday-to-daygeneralizationsandtheconclusionsusuallyrecognizedasthescientificmethodliesinthedegreeofformality,rigorousness,verifiability,andgeneralvalidityofthelatter.’
FredKerlinger (1986) also validated the thought and stated that‘Scientificresearchisasystematic,controlledandcriticalinvestigationofpropositionsaboutvariousphenomena.’Grinnell(1993)hassimplifiedthedebateandstated‘Thewordresearchiscomposedoftwosyllables,reandsearch.Thedictionarydefinestheformerasaprefixmeaningagain,aneworoveragainandthelatterasaverbmeaningtoexaminecloselyandcarefully,totestandtry,ortoprobe.Togethertheyformanoundescribingacareful,systematic, patient study and investigation in somefield of knowledge,undertakentoestablishfactsorprinciples.’
Thus,drawingfromthecommonthreadsoftheabovedefinitions,wederivethatmanagementresearchisanunbiased,structured,andsequentialmethodof enquiry, directed towards a clear implicit or explicit businessobjective.Thisenquirymightleadtovalidatingexistingpostulatesorarrivingatnewtheoriesandmodels.
Themostimportantanddifficulttaskofaresearcheristobeasobjectiveandneutralaspossible.Thetemptationtoskewtheresultsinthehypothesizeddirectionhastobeavoidedatallcosts.MagazinearticlesandnewspapersurveyswhichwanttoproveapointmightwanttoskewtheopinionpollsinfavouroftheCapitalistsortheRepublicans,orontheneedforreservationversusnoreservationineducationalinstitutesbutaresearcherhastocollectanddisplaythefindingsoftheresearchasobjectivelyaspossible.
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Self-InstructionalMaterial 3
Research BasisThe lastmost important aspect of our definition that needs to becarefullyconsidered is thedecision-assistingnatureofbusiness research.Thus,asEasterby-Smithet al.(2002)state,businessresearchmusthavesomepracticalconsequences,eitherimmediately,whenitisconductedforsolvinganimmediatebusinessproblemorwhenthetheoryormodeldevelopedcanbeimplementedandtestedinabusinesssetting.Theworldofbusinessdemandsthatmanagersandresearchersworktowardsagoal—whetherimmediateorfuturistic,elsetheresearchlosesitssignificanceinthefieldofmanagement.
Someoftheproposeddefinitionsofresearchareasfollows:• RedmanandMoryhavedefinedresearchasasystematizedeffort
togainknowledge.• In thewords of renowned researcherCliffordWoody, research
involvesdefiningandredefiningproblems;formulatingsuggestedsolutionsorhypotheses;collecting,evaluatingandorganizingdata,reachingconclusionsandmakingdeductionsandcarefullytestingtheconclusionstofindoutiftheyfittheformulatinghypothesisornot.
• D.SlesingerandM.Stephenson in theEncyclopaedia of Social Sciencesdefineresearchasthemanipulationofthings,conceptsorsymbolsforthepurposeofgeneralizingtoextend,correctorverifyknowledge,whetherthatknowledgeaidsintheconstructionofatheoryorinthepracticeofanart.
Purpose of research
The principal purpose of research is to find solutions to problemssystematically.Ingeneral,thepurposeofresearchcanbespecifiedasfollows: •Toacquirefamiliaritywithaphenomenon •Tostudythefrequencyofconnectionorindependenceofanyactivity
or occurrence •Todeterminethecharacteristicsofanindividualoragroupofactivities
andthefrequencyoftheoccurrenceoftheseactivities •Totestahypothesisaboutacausalrelationship thatexistsbetween
variables
Characteristics of research
Theprocessofresearchhelpsincreasethecreativeabilityofadecision-maker.Thevariouscharacteristicsofresearchareasfollows: • Interdisciplinary team approach:This approach is based on the
principleofusingtheexpertiseandexperienceofdifferentpersonnelworkingindifferentdisciplineswithinanorganization.Anindividualcannotbeanexpertinalltheareasofoperation.So,researcherstakehelpfromotherexperts,whoarespecialistsintheirrespectivefields.
Research Basis
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Self-Instructional 4 Material
Underinterdisciplinaryteamapproach,anexpertmayuseoldsolutions,whichareusedinthepastasaresearchmaterialforfindingthemostappropriatesolutiontotheproblem.
• Methodological process:Researchers use scientificmethods andtechniques to provide an optimum solution to the problems.Thescientificmethods include observing and defining a problem andformulatingahypothesisrelatedtotheresultsofthescientificmethodsandtechniques.Ifthehypothesisisaccepted,thenitsresultsshouldbeexecutedinanorganization,butifthehypothesisisnotaccepted,thenanotherhypothesisisformulated.
• Objectivistic approach:The aimof an organization is to provideoptimalsolutionstovariousproblems.Itisessentialtomeasurethedesirabilityofasolutionforachievingtheorganizationalobjective.Thismeasureddesirabilityhelpsincomparingthealternativecoursesofactionwithrespecttotheiroutcomes.
• Economical in nature:Inanuncertainandcomplexsituation,researchhelpsinreducingthecostsofinventoryandthereby,improvingtheprofits. For example, in inventory control, research can providescientificrulesforreducingacquisitioncostsandinventory-carryingcosts.
Nature of Research
Goodandeffectiveresearchisidentifiedbyitsnature,whichsignifiesitsfocusontheresearchtopic,asystematicwayofimplementation,controloverthevariablesandsoon.Thenatureofagoodandeffectiveresearchisasfollows: • Objectivity:Agoodresearchisobjectiveintermsofofferingsolutions
totheresearchquestions.Thiscallsforplanningandcreationofsuitablehypothesistoavoidlackofrelationshipbetweentheresearchquestionsandhypothesis.
• Control:Agoodresearchiscapableofcontrollingallthevariables.Thisnecessitatesrandomizationatallstagesandascertainssufficientcontrolovertheindependentvariables.
• Universality:Agoodresearchwillalmosthavethesameresultbyusingidenticalmethodologysothattheresultcanbeappliedtosimilarsituations.
• Free from personal biases:A good research is free from theresearcher’spersonalbiasesandmustbebasedonobjectivityandnotsubjectivity.
• Systematic:Agoodresearchhasseveralwell-plannedstepsthatareinter-connectedandlogical.
• Reproductivity:A researcher,while conducting the research, isabletoobtainapproximatelythesameresultsbyusinganidenticalmethodologyforconductinginvestigation.
NOTES
Self-InstructionalMaterial 5
Research Basis1.2.1 Applications of Business Research
Thediscussion so far points out the role and significanceof research in aidingbusiness decisions.Thequestiononemight ask here is about thecriticalimportanceofresearchindifferentareasofmanagement.Isitmostrelevant inmarketing?Dofinancialandproductiondecisions reallyneedresearchassistance?Doesthemethodorprocessofresearchchangewiththefunctionalarea?
TheanswertoalltheabovequestionsisNO.Businessmanagersineachfield—whetherhumanresourcesorproduction,marketingorfinance—areconstantlybeingconfrontedbyproblemsituationsthatrequireeffectiveandactionabledecisionmaking.Mostofthesedecisionsrequireadditionalinformation or information evaluation,which can be best addressed byresearch.While the nature of the decision problemmight be singularlyuniquetothemanager,organizationandsituation,broadlyforthesakeofunderstanding,itispossibletocategorizethemunderdifferentheads.
Fig 1.1 The Process of Research
Research Basis
NOTES
Self-Instructional 6 Material
Marketing function
Thisisoneareaofbusinesswhereresearchisthelifelineandiscarriedoutonavastarrayoftopicsandisconductedbothin-housebytheorganizationitself andoutsourced to external agencies.Broader industry- or product-category-specificstudiesarealsocarriedoutbymarketresearchagenciesandsoldasreportsforassistinginbusinessdecisions.Studieslikethesecouldbe: •Marketpotentialanalysis;marketsegmentationanalysisanddemand
estimation •Market structure analysiswhich includesmarket size, players and
marketshareofthekeyplayers • Salesandretailauditsofproductcategoriesbyplayersandregions
aswell as national sales; consumer and business trend analysis—sometimesincludingshort/longtermforecastingHowever,itistobeunderstoodthattheabovementionedareasneed
notalwaysbeoutsourced;sometimestheymightbehandledbyadedicatedresearchornewproductdevelopmentdepartmentintheorganizations.Otherthanthese,anorganizationalsocarriesoutresearchesrelatedtoallfourPsofmarketingsuchas: • Productresearch:Thiswouldincludenewproductresearch;product
testing and development; product differentiation and positioning;testingandevaluatingnewproductsandpackagingresearch;brandresearch—includingequitytotracksandimagingstudies.
• Pricingresearch:Pricedeterminationresearch;evaluatingcustomervalue;competitorpricingstrategies;alternativepricingmodelsandimplications.
• PromotionalResearch: Includes everything fromdesigning of thecommunicationmix to design of advertisements, copy testing,measuring the impact of alternativemedia vehicles, impact ofcompetitors’strategy.
• Placeresearch:Includeslocationalanalysis,designandplanningofdistributionchannelsandmeasuringtheeffectivenessofthedistributionnetwork.These days,with the onset of increased competition and the need
to convert customers into committed customers, customer relationshipmanagement (CRM), customer satisfaction, loyalty studies and leaduseranalysisarealsoareasinwhichsignificantresearchisbeingcarriedout.
Personnel and human resource management
Humanresources(HR)andorganizationalbehaviourisanareawhichinvolvesbasicorfundamental researchasa lotofacademic,macro level researchmaybeadaptedandimplementedbyorganizationsintotheirpoliciesand
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Self-InstructionalMaterial 7
Research Basisprogrammes.AppliedHRresearchbycontrastismorepredictiveandsolutionoriented.Thoughthereareanumberofacademicandorganizationalareasinwhichresearchisconducted,yetsomekeycontemporaryareaswhichseemtoattractmoreresearchareasfollows: • Performancemanagement; leadership analysis development and
evaluation; organizational climate andwork environment studies;talentandaptitudeanalysisandmanagement;organizationalchangeimplementation,managementandeffectivenessanalysis
•Employee selection and staffing:This includes pre and on-the-jobemployeeassessmentandanalysis;staffingstudies
•Organizational planning and development:Culture assessment—either organization specific or the studyof individual andmergedcultureanalysisformergersandacquisitions;manpowerplanninganddevelopment
• Incentive and benefit studies: These include job analysis andperformance appraisal studies; recognition and reward studies,hierarchical compensation analysis; employee benefits and rewardanalysis,bothwithintheorganizationandindustrybestpractices
•Traininganddevelopment:Theseincludetrainingneedgapanalysis;trainingdevelopmentmodules;monitoringandassessingimpactandeffectivenessoftraining
•Other areas include employee relationship analysis; labour studies;negotiation andwage settlement studies; absenteeism and accidentanalysis;turnoverandattritionstudiesandwork-lifebalanceanalysisCritical success factor analysis and employer branding are some
emerging areas inwhichHR research is being carriedout.Thefirst is aparticipativeformofmanagementtechnique,developedbyRockart(1981)inwhichtheemployeesofanorganizationidentifytheircriticalsuccessfactorsandhelpincustomizingandincorporatingthemindevelopingthemissionandvisionoftheirorganization.Theideaisthatasynchronizedobjectivewillbenefitboththeindividualandtheorganization,andwhichwillleadtoacommitmentandownershiponthepartoftheemployees.Employerbrandingisanotherareawhichisbeingactivelyinvestigatedasthecustomerperception(inthiscaseitistheinternalcustomer,i.e.,theemployee)abouttheemployerortheemployingorganizationhasastronganddirectimpactonhisintentionstostayorleave.Thus,thisisasubjectivequalitativeconstructwhichcanhavehazardouseffectonorganizationaleffectivenessandefficiency.
Financial and accounting research
Theareaoffinancialandaccountingresearchissovastthatitisdifficulttoprovideapensketchoftheresearchareas.Inthissection,weareprovidingjustabriefoverviewofsomeresearchtopics:
Research Basis
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•Assetpricing,corporatefinanceandcapitalmarkets:Thefocushereisonstockmarketresponsetocorporateactions(IPOs,takeoversandmergers),financialreporting(earningsandfirmspecificannouncements)andtheimpactoffactorsonreturns,e.g.,liquidityandvolume;
• Financialderivativesandinterestrateandcreditriskmodelling:Thisincludesanalysinginterestratederivatives,developmentandvalidationofcorporatecreditratingmodelsandassociatedderivatives;analysingcorporatedecisionmakingandinvestmentriskappraisal;
•Market based accounting research:Analysis of corporatefinancialreportingbehaviour;accounting-basedvaluations;evaluationandusageofaccountinginformationbyinvestorsandevaluationofmanagementcompensationschemes;
•Auditing and accountability:This includes bothprivate andpublicsector accounting studies, analysisof audit regulations; analysisofdifferentauditmethodologies;governanceandaccountabilityofauditcommittees;
• Financialeconometrics:This includesmodellingandforecastinginvolatility,riskestimationandanalysis;
•Other related areas of investigation are inmerchant banking andinsurancesectorandbusinesspolicyandeconomicsareas.Consideringthenatureofthedecisionrequiredinthisarea,theresearch
isamixofhistoricalandempiricalresearch.Behaviouralfinanceisanewandcontemporaryareainwhich,probably,forthefirsttimesubjectiveandperceptualvariablesarebeingstudiedfortheirpredictivevalueindeterminingconsumer sentiments.
Production and operation management
Thisareaofmanagement isone inwhichquantifiable implementationoftheresearchresultstakesonhugecostandprocessimplications.Researchinthisareaishighlyfocusedandproblemspecific.Thedecisionareasinwhichresearchstudiesarecarriedoutareasfollows: •Operation planning:These include product/service design and
development;resourceallocationandcapacityplanning •Demandforecastinganddecisionanalysis • Process planning:Production scheduling andmaterial requirement
management;workdesignplanningandmonitoring • Projectmanagementandmaintenancemanagementstudies •Logisticsandsupplychainandinventorymanagementanalysis •Qualityestimationandassurancestudies:Theseincludetotalquality
management(TQM)andqualitycertificationanalysis
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Research BasisThisareaofmanagementalsoinvitesacademicresearchwhichmightbemacro and general but helps in developing technologies such as JIT(just-in-timetechnology)andEOQ(economyorderquantity—aninventorymanagementmodel)whicharethenadaptedbyorganizationsforoptimizingoperations.
Cross-functional research
Businessmanagementbeingan integratedamalgamationofall theseandotherareassometimesrequiresaunifiedthoughtandapproachtoresearch.These studies require anopenorientationwhere experts fromacross thedisciplinescontributetoandgainfromthestudy.Forexample,anareasuchas newproduct development requires the commitment of themarketing,productionandconsumerinsightsteamtoexploitnewopportunities.Otherareasrequiringcrossfunctionaleffortsare: •Corporategovernanceandethics—theroleofsocialvaluesandethics
andtheirintegrationintoacompany’sworkingisanareathatisofcriticalsignificancetoanyorganization.
•Technical support systems, enterprise resource planning systems,knowledgemanagement, and datamining andwarehousing areintegratedareasrequiringresearchonmanagingcoordinatedeffortsacrossdivisions
•Ecologicalandenvironmentalanalysis;legalanalysisofmanagerialactions;humanrightsanddiscriminationstudies
Check Your Progress
1.Whatistheprincipalpurposeofresearch? 2.What are someof the areaswhich involve basic or fundamental
research?
1.3 TYPES OF RESEARCH
Thetypesofresearchdependonthefieldinwhichthespecificresearchstudyisperformed.Thedifferenttypesofresearchareasfollows: • Pure research:This type of research ismainly concernedwith
identifyingcertainimportantprinciplesinaspecificfield.Itintendstofindoutinformationthathasabroadbaseofapplication.ExamplesoffundamentalresearchareJohnRobinson’simperfectcompetitiontheoryinEconomicsandMaslow’shierarchyofneedstheoryinmotivationandsoon.
• Applied research:Thistypeofresearchaimsatfindingasolutiontoanimmediateproblem,facedbyasocietyoranindustrialorganization.
Research Basis
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Itissupposedtodiscoverasolutiontosomebasicpracticalproblems.Appliedresearchsuggestscorrectivemethodstominimizeasocialorbusiness problem.
• Historical research: It is theprocessofsystematicexaminationofpasteventstobeabletopresentanaccountofwhathashappenedinthepast.Mostpeoplebelievethatitisasimplyaccumulationofdatesandfactsofpastevents.Actually,itisnotso.Itisaflowing,dynamicaccountofpasteventsinvolvinganinterpretationoftheseeventstounderstandthefactors,personalitiesandideasthat influencedtheseevents.Oneofthegoalsofhistoricalresearchistocommunicateanunderstandingofpastevents.Historicalresearchisimportantbecauseit:
(i)Helpsuncovertheunknownorunrecordedfacts/events (ii)Answersquestions (iii)Facilitatesidentificationoftherelationshipofthepasthaswith
thepresent (iv)Records and evaluates the accomplishments of individuals,
agencies,orinstitutions. (v)Assistsinunderstandingthecultureinwhichwelive It is not possible to identify any single approach that is used in
conductinghistoricalresearch.Somegeneralstepsthataretypicallyfollowed,whichincludethefollowing:
(i) Identifyingtheresearchtopic (ii)Formulatingtheresearchproblem (iii)Collectingdataandreviewingliterature (iv)Evaluatingmaterials. (v)Synthesizingdata (vi)Preparingreport • Futuristic research: This type of research does not really predict
thefutureasthenamemayseemtosuggest.Itisactuallyabranchofoperationsresearchaimedatconductinglong-rangeplanningbasedonforecastingusingmathematicalmodels,cross-disciplinarytreatmentofthesubject,systematicuseofexpertjudgementsoropinionsandasystemsanalyticalapproach.
• Analytical research: Analytical research is concernedwith cause-effectrelationships.Forexample,examiningthefluctuationsinIndia’sinternational tradeduringaparticularperiodof timewouldrequiredescriptiveresearch.However,toexplainwhyandhowIndiantradebalancemovesinaspecificwayoveraperiodoftimeisanexampleofanalyticalresearch.
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Research Basis • Synthetic research:Syntheticresearchdealswithbasicmechanismsorrelationshipsofthedifferentmechanismswithintheentireorganism.Thistypeofinvestigationdependsneitheronthemethodsusednoronthesubjectofinvestigations.
• Descriptive research: Descriptive research attempts to determine,describe, or identifywhat is unlike analytical research aimed atestablishingwhy it is thatway or how it came to be thatway.Descriptiveresearchusesdescriptions,classifications,measurements,andcomparisonstodescribevariousphenomena.
• Prescriptive research:Thistypeofresearchencompassesboththedescriptiveandexplicativedimensionsof research.Thedescriptivelevelaimstodescribetheresearchobjectwhereastheexplicativelevelinterprets the observed phenomena. Prescriptive research tests therelevanceofbothexplicativeandprescriptivehypotheses.Itsupposesaninteractionbetweentheresearcherandthefieldofstudysoastoimplementrecommendationsorpropositionsandthenmeasuretheirimpact.
• Survey research:Itisacollectionofquantifieddatafromasectionofthepopulationfordescribingoridentifyingbetweenvariablesthatmaypointtocausalrelationshipsorpredictivepatternsofinfluence.Acensuscanbeconsideredasurveythatmeasuresthenatureofhumanresourceavailable,theirlevelofeducation,theirprofessions,etc.
• Experimental:The experimental type of research enables you tocalculatethefindings,employthestatisticalandmathematicaldevicesandmeasuretheresultsthusquantified.
• Case study:Thismethodundertakesintensiveresearchthatrequiresathoroughstudyofaparticularunit;forexample,industrialorbanking,fordatacollection.
• Generic research:Itisresearchexistsbetweenappliedresearchandbasicresearch.Itisconsideredtobealessacademicwayofresearchingusedwhenresearchhastobeconductedwithinashortframeoftime.It results in a qualitativedescription showinghowparticipantsnotonlyunderstandbutalsomakesenseoftheirexperiences.Theverylackofaspecificmethodistheadvantageofthisresearch.Insteadofbeingobsessedwithoneparticularmethod,researchersusevariousproceduresandstrategiesofdatacollectionwithoutbeingboundbytoomanytechnicalandphilosophicalissues.
• Formulative or exploratory:Ithelpsexamineaproblemwithsuitablehypothesis.This research, on social science, ismainly significantfor clarifying concepts and innovations for further researches.Theresearchersaremainlyconcernedwith theprinciplesofdevelopinghypothesisandtestingwithstatisticaltools.
Research Basis
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• Ex post facto:This type of research is the same as experimentalresearch,whichisconductedtodealwiththesituationsthatoccurinoraroundanorganization.Examplesofsucharesearcharemarketfailureofanorganization’sproductbeingresearchedlaterandresearchintothecausesforalandslideinthecountry.
• Disciplinary research:Thisresearchaimedatimprovingadiscipline.Itisconcernedwiththetheories,relationships,andanalyticalproceduresandtechniqueswithinthediscipline,forexample,economicresearchorsocialresearch.
• Subject-matter research:Thisisresearchonanysubjectofinterestwithinaspecificdiscipline.
• Problem-Solving research:Itisresearchdesignedtosolveaspecificproblemforaspecificdecision-maker.Itisoftenmultidisciplinary,forexample,amultidisciplinarystudyofanewdrugforcancerinvolvingmedicaldoctors,engineers,andaneconomist.Besidesthese,thereareseveralothertypesofresearchlikeevaluation
research,surveyresearch,assessmentresearchandcomparativeresearch.The researchers in quantitative research classify features of the
researchandthenbuildthestatisticalmodelstoexplainwhatheobserves.Theresearcherinquantitativeresearchmustknowclearlyinadvancewhathewants to researchbeforehestarts the research.Focus in this researchisconciseandnarrow.Thus,quantitativeresearchisconclusive.Thedatacollectedinthisresearchismeasurableandcanbeanalysedeasilybytheresearcher.Unlikequalitativeresearch,quantitativeresearchdealswithwhat,whereandwhentoresearch.Thistypeofresearchisusedinlaterphasesofresearchcycle.Quantitativeresearchisbasicallythestudyofnumbersandstatistics.Theresearchercanusedifferenttypesoftoolslikequestionnairesor equipment togather thisnumerical information.Thedatacollected inquantitative research ismoreeffective thanqualitativedataandcanhelptheresearchermore.Thistypeofresearchisnotconcernedwithprocess.Itonlydealswithwhatwillbetheoutcomeorproduct.Thus,theresearcherin quantitative research tends to be objective; therefore, it is also calledobjectiveresearch.
Itshouldbekeptinmindthatitisdifficulttocategoriseaparticularresearchunderanymajorheads.Thisisbecause,nomatterwhatthenatureormethod of research, the research problem is essentially treated in aninterdisciplinarymanner.Interdisciplinarytreatmentmeanstheborrowingof an idea from relateddisciplines connectedwith the research topic formoreauthenticity.Forexample;managementisnotanindividualdisciplineinitsownrightandrequiresanintegralapproachofvariousdisciplineslikefinanceandhumanresources,etc.
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Research Basis1.4 STEPS IN THE RESEARCH PROCESS
Theprocessofresearchisimplementedasaseriesofactionsorstepsthatareessentiallyperformedinaspecificorder.Theseactionsoractivitiesusuallyoverlapeachotherratherthanpursuingaspecificsequence.Abriefdescriptionofthestepsisgivenasfollows: •Selecting the topic:Thefirststepofaresearcheristoselectatopicof
research.Whiledoingso,heshouldrestricthimselftothemostpotentialtopicthatisopenforextensiveresearchoutofseveralalternatives.Thefactorstobeconsideredfortopicselectionare:o Relevanceo Scopeforresearch,i.e.therequireddatashouldbeavailableand
accessibleo Contributiontoknowledgeinthespecificfieldo Requiredcooperationfromtheresearchguide
•Define the research problem:There are two types of researchproblems:o Problemsrelatedtothestateofnatureo Problemsrelatedtotherelationshipofvariables
In defining the research problem, the researcher should study theexistingliteraturelikebooksandjournals,availableinthefieldwithan interdisciplinaryperspective to basehis research topicon somereliablebackground.Heshouldalsoconcentrateontherelevanceofthepresentresearchwiththepastworks.
•Mention the objective of research:After selecting the topic anddefining the research problem, the researcher shouldmention theobjectiveofresearch.Thismeansthatheshouldexplainwhatheaimstoachievethroughtheresearch.Hisobjectiveshouldalsoexplaintheextenttowhichtheresearchworkisrelatedtothespecificfield.
•Survey existing literature:Tounderstand the basis of research, itisimportantfortheresearchertoreviewtheexistingliterature.Thisinvolves:o Surveyingtheexistingbooksavailableinthefieldo Reviewingotherpublishedliteraturelikearticles,journals,reports,
conferenceproceedingsetc. The researcher should thenpreparehis own index for a period, in
chronologicalorder,inadditiontohisconsultationofvariousindices. • Development of working hypothesis:Ahypothesisisanuncertain
statement that involves the proposed answer to the problem.The
Research Basis
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hypothesis statement provides high priority to accountability andresponsibilityofresearchprocedure.Thesolutionproposedbyworkinghypothesiscannotbeconsideredastheonlysolutiontotheresearchproblem.Itonlyactsasthechainorinterfacebetweenthetheoryandtheresearchproblem.Itcanalsobeconsideredasthepointofdeparture.Hypothesesarethusthetentativestatementsthatcaneitherbyrejectedor accepted after the research process.Hypothesis also provides astructureandguidestheresearcherinthedirectionheshouldmovetoreach thesolutionof theproblem.Theresearchermustkeep thefollowingthingsinmindwhileformulatingaworkinghypothesis:o Hypothesiscanonlybedevelopedaftertheresearcheriscertain
aboutthenature,extentandintensityoftheproblem. o Hypothesisshouldbefiguredoutthroughouttheresearchprocess
whichprovidesappropriatestructuretotheproblem.o Theresearchershouldkeepitinmindthathypothesisisonlythe
tentativestatements/solutionsoftheproblemandthishypothesisshouldnotbegeneralisedmuch.
o Aresearchproblemdoesnotneedtohaveonlyonehypothesis.Itonlydependsontheresearchproposalthathowmanyhypothesesarerequiredtosolvetheproblem.
• Preparing the research design:Oncetheresearcherhasgainedenoughknowledgeabouttheproblemstatement,heneedstopreparetheplanthatwillactastheoutlineoftheinvestigationinresearchprocess.Theresearchdesignconsistsofaseriesofstepsthathastobecarriedoutduringresearch.
Therearetwotypesofresearchdesign:o Exploratoryresearcho Conclusiveresearcho Descriptiveresearcho Causalresearch
• Exploratory research:Theresearcherconductsexploratoryresearchwhentheproblemhasnotbeendefinedorhehasnotgainedmuchknowledgeabouttheresearchproblem.Exploratoryresearchallowstheresearchertobecomefamiliarwiththeproblemortheconcepttobe studied.The researcher candetermine the best researchdesign,datacollectionmethodandselectionofsubjectswith thisresearch.Sometimes, this research can also conclude that the problemdoesnotexist.Exploratoryresearchcanbequiteinformalandcanrelyonsecondaryresearchandqualitativeresearch.
• Conclusive research: As specifiedby its name is used to provideinformation that can help the researcher to reach to conclusionor
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Research Basisdecision-making.Thissearchislikelytobequantitativeinnature.Itdependsonbothsecondarydata,whichisalsocalledexistingdata,andprimaryresearch,ordatathatiscollectedforthecurrentstudyonly.o Descriptive research:Descriptiveresearch,alsocalledstatistical
research, provides data about the population or universe thathas tobestudiedduringresearch.Descriptiveresearchprovidesinformationabout‘who,what,when,whereandhow’ofasituationbutitdoesnotprovideinformationaboutwhocausedtheproblem.Theresearchercanusethedescriptiveresearchwhentheobjectiveistoprovidesystematic,accurateandfactualdescription.Therearetwotypesofdescriptiveresearchdesign:
-Observations - Surveys
o Causal research: Itisusedtofindoutthevariablecausingcertainbehaviour.Thisresearchisapplicablewhentheresearcherhastheknowledgeofvariablesthatarecausingtheproblemandthatareaffectedby theproblem.This typeof research tends tobeverycomplexandtheresearchermaysometimesbeunabletodeterminetheattitudeofanindividualbythisresearch.Therearetwotypesofcausalresearchdesign:
-Experimentation -Simulation •Determine the sample design:Oftenonlyafewitemsareselected
foruniversalstudypurposes,forexample,bloodtestingonasamplebasis toperformcensus inquiry.The items selectedare technicallyknownasasample.Theresearchermustdecidethewayofselectingasampleordecideaboutsampledesign.Asampledesignisadefiniteplandeterminedfordatacollectiontoobtainasamplefromagivenpopulation.Thevarioustypesofsampledesignsareasfollows:o Deliberatesamplingo Simplerandomsamplingo Systematicsamplingo Stratifiedsamplingo Quotasamplingo Clustersamplingo Multi-stagesamplingo Sequentialsampling
Theresearchershoulddecidethesampledesignafterconsideringthenatureofinquiryandotherrelatedfactors.Sometimesseveralabove-
Research Basis
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mentionedmethodsofsamplingareusedinthesamestudy,whichiscalledmixedsampling.
• Data collection:Thereareavarietyofwaystocollectdata.Primarydatacanbecollectedthroughexperimentsorthroughsurveys.Iftheresearcher performs an experiment, he observes somequantitativemeasurements.Thishelpshimexaminethevalidityofhishypothesis.Inthecaseofsurveys,however,theresearchercanadoptoneormoreofthefollowingwaystocollectdata:o Byobservationo Throughpersonalinterviewso Throughtelephoneinterviewso Bymailingofquestionnaireso Throughschedules
• Execution of project:Thisisthemostimportantstepintheresearchprocess.Theresearchershouldensurethattheprojectisperformedinalogicalwayandintime.Ifasurveyistobecarriedout,stepsshouldbetakentoensurethatitisunderstatisticalcontrol,sothatthecollecteddataisinaccordancewiththepre-determinedstandardofaccuracy.
• Analysis of data:Afterdata collection, the researcher turns to thetaskofanalysingit.Thebulkdatashouldbecompressedintoafewmanageablegroupsandtablesforfurtheranalysis.Theresearchercanthenanalysethecollecteddatabyusingvariousstatisticalmeasures.
• Hypothesis testing:Afteranalysingthedata, theresearchershouldtest thehypothesis, ifany.Heshouldcheckif thefactssupport thehypothesisorarecontrary.StatisticianshavedevelopedtestslikeChisquaretest,t-testandF-testforhypothesistesting.Thistestingfurtherresultsineitheracceptanceorrejectionofhypothesis.
• Generalisations and interpretations:Therealvalueofresearchliesinitsabilitytoarriveatcertaingeneralisations.Iftheresearchercannotfindahypothesistostartwith,hemightseektoexplainhisfindingsonthebasisofsometheory.Thisiscalledinterpretation.Thismaygiverisetonewquestionsandleadtofurtherresearch.
• Preparation of report or thesis:Thisistheconcludingstepofresearch,wheretheresearcherhastoprepareareportofwhathasbeendonebyhim.Generally,thereportshouldbedesignedinaccordancetothefollowinglayout:o The preliminary pages:Herethetitle,date,acknowledgements
andforewordwiththetableofcontents,shouldbementioned.o The main text:Thisshouldbedividedintointroduction,summary,
mainreportandconclusion.
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Research Basiso End matter:This should contain appendices, bibliography andindex.
Areportshouldbewritteninapreciseandobjectivestyleinsimplelanguage.Chartsandillustrationsshouldbeincludedtolayemphasisonthestudyofresearch.
1.4.1 Establishing Operational Definitions
Havingidentifiedanddefinedthevariablesunderstudy,thenextsteprequiresoperationalizingthestatedrelationshipintheformofatheoreticalframework.This is anoutcomeof theproblemaudit conductedprior todefining theresearchproblem;itcanbebestunderstoodasaschemaornetworkoftheprobablerelationshipbetweentheidentifiedvariables.Anotheradvantageof themodel is that it clearlydemonstrates theexpecteddirectionof therelationshipsbetweentheconcepts.Thereisalsoanindicationofwhethertherelationshipwouldbepositiveornegative.
Thisstephoweverisnotmandatoryassometimestheobjectiveoftheresearchistoexploretheprobablevariablesthatmightexplaintheobservedphenomena(DV)andtheoutcomeofthestudyhelpstotheorizeandproposeaconceptualmodel.
Thetheoreticalframework,onceformulated,isapowerfuldrivingforcebehindtheresearchprocessandoughttobecomprehensivelydeveloped.Itrequiresathoroughunderstandingofboththeoryandopinion.
‘The specificway inwhich a variable ismeasured in a particularstudyiscalledtheoperationaldefinition.Itiscriticaltooperationallydefineavariableinordertolendcredibilitytothemethodologyandtoensurethereproducibilityoftheresults.Anotherstudymaymeasurethesamevariabledifferently.Theoperationaldefinitionalsohelpstocontrolthevariablebymakingthemeasurementconstant.Therefore,whenitcomestooperationaldefinitionsofavariable,themoredetailedthedefinitionis,thebetter.’
Check Your Progress
3.Whatispureresearchconcernedwith? 4.Whenisexploratoryresearchconducted? 5.Listthewaysofcollectingdata.
1.5 ANSWERS TO CHECK YOUR PROGRESS QUESTIONS
1.The principal purpose of research is tofind solutions to problemssystematically.
Research Basis
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2.Humanresources(HR)andorganizationalbehaviourareareaswhichinvolvebasicorfundamentalresearchasalotofacademic,macrolevelresearchmaybeadaptedandimplementedbyorganizationsintotheirpoliciesandprogrammes.
3.Pureresearchismainlyconcernedwithidentifyingcertainimportantprinciplesinaspecificfield.
4.Theresearcherconductsexploratoryresearchwhentheproblemhasnotbeendefinedorhehasnotgainedmuchknowledgeabouttheresearchproblem.
5.Theresearchercanadoptoneormoreofthefollowingwaystocollectdata:o Byobservationo Throughpersonalinterviewso Throughtelephoneinterviewso Bymailingofquestionnaireso Throughschedules
1.6 SUMMARY
•Thepurposeofresearchistofindsolutionsthroughtheapplicationofsystematicandscientificmethods.
•Themostimportantanddifficulttaskofaresearcheristobeasobjectiveandneutralaspossible.
•Goodandeffectiveresearchisidentifiedbyitsnature,whichsignifiesitsfocusontheresearchtopic,asystematicwayofimplementation,controloverthevariablesandsoon.
•Businessmanagers in each field—whether human resources orproduction,marketingorfinance—are constantly being confrontedbyproblemsituationsthatrequireeffectiveandactionabledecisionmaking.Most of these decisions require additional informationorinformationevaluation,whichcanbebestaddressedbyresearch.
•Thetypesofresearchdependonthefieldinwhichthespecificresearchstudyisperformed.
•Theresearchersinquantitativeresearchclassifyfeaturesoftheresearchandthenbuildthestatisticalmodelstoexplainwhatheobserves.
•Theprocessofresearchisimplementedasaseriesofactionsorstepsthat are essentially performed in a specificorder.These actions oractivitiesusuallyoverlapeachotherrather thanpursuingaspecificsequence.
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Research Basis •Ahypothesis is an uncertain statement that involves the proposedanswertotheproblem.Thehypothesisstatementprovideshighprioritytoaccountabilityandresponsibilityofresearchprocedure.
•Having identified and defined the variables under study, the nextstep requiresoperationalizing thestated relationship in the formofa theoretical framework.This is an outcomeof the problem auditconductedpriortodefiningtheresearchproblem.
•The theoretical framework, once formulated, is a powerful drivingforcebehindtheresearchprocessandoughttobecomprehensivelydeveloped.
1.7 KEY WORDS
• Fundamental Research: It focusesonfindinggeneralizations andformulatingtheories.
• Applied Research: It aims atfinding a solution for an immediateproblemfacingasocietyorabusiness/industrialorganization.
• Empirical Research: Itreliesonlyonrealexperiencesandobservations. • Social Research:Thisreferstoresearchconductedbysocialscientists
inordertoanalyseavastbreadthofsocialphenomena. • Quantifiable: Itmeans something that is able to be expressed or
measuredasaquantity.
1.8 SELF ASSESSMENT QUESTIONS AND EXERCISES
Short Answer Questions
1. Distinguishbetweennon-scientificandscientificmethod. 2.Whatarethecharacteristicsofresearch? 3.Howisthetheoreticalframeworkformulated?
Long Answer Questions
1. Describetheapplicationofbusinessresearchinvariousfields. 2.Explainthedifferenttypesofresearch. 3.Examinethevariousstepsintheresearchprocess.
Research Basis
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1.9 FURTHER READINGS
Creswell,JohnW.2002.Research Design: Qualitative, Quantitative, and Mixed Methods Approaches.London:SagePublicationsInc.
Booth,Wayne,GregoryG.ColombandJosephM.Williams.1995.The Craft of Research.Chicago:UniversityofChicagoPress.
Bryman,AlanandEmmaBell.2015.Business Research Methods.4thEdition.UnitedKingdom:OxfordUniversityPress.
Gupta,S.L.andHiteshGupta. 2012. Business Research Methods. NewDelhi: TataMcGrawHillEducationPrivateLimited.
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Research Scope
UNIT 2 RESEARCH SCOPEStructure 2.0 Introduction 2.1 Objectives 2.2 RecentAdvancementsinResearch:OnlineResearch 2.3 DistinctionbetweenDifferentTypesofResearches 2.4 AnswerstoCheckYourProgressQuestions 2.5 Summary 2.6 Key Words 2.7 SelfAssessmentQuestionsandExercises 2.8 FurtherReadings
2.0 INTRODUCTION
In the previousunit, youwere introduced to various aspects of businessresearch.Herewewilldiscusstheadvancementsmadeinresearchinrecentyears.Businessresearch,likeallotherdomains,hasbeengreatlyinfluencedbytechnologicaladvancementsinrecentyears.Researchthatiscarriedouttodaybearsnoresemblancetobusinessresearchofearliertimes.OneofthenotableadvanceshasbeentheadventoftheInternet.Wewilldiscussthisaspectindetail.Theunitwillalsodiscussthedifferencesbetweendifferenttypesofresearch.
2.1 OBJECTIVES
Aftergoingthroughthisunit,youwillbeableto: •Describeonlineresearchanditsdatacollectionmethods •Discussthedifferencesbetweenvarioustypesofresearch
2.2 RECENT ADVANCEMENTS IN RESEARCH: ONLINE RESEARCH
Ifthe1960swastheeraofrationalityandthesearchforuniversalparadigmsandabsolutetruthswhichcouldstandthetestoftimeandboundaries;the1990s saw turmoil and uncertainty.As the aftermath of nuclearwarfareand environmental calamities likepollution, globalwarming andgeneticmalformationsledtopost-modernismandaquestioningmindsetcharacterizedbyhostilityanddespairwiththestateofthings.Thisresultedinhyperrealities,wheremoreandmorepeopleacrosstheworldsoughtaworldthatwassurrealandthusfreefromthechaosanddisappointmentsaswellasthreatsofthereal
Research Scope
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world.Theneedwasablysupportedbytheextremelyfastdigitalgrowththatwashappeningacrosstheworld.Today,almosttwodecadeslater,morethanonemillionpeopleacrossphysicalboundariesstandconnectedthroughonlinecommunities,networks,groups,forumsandpodcasts.ThehugesuccessofvirtualsocialworldssuchasSecondlifeisadefiniteproofofthefactthatmoreandmoreconsumersaretakingonanalternativeidentity(oravatar),whichhasnoconstraintsorrules.Thisisonlyonepartofit—thesuccessofsocialcommunities(Facebook),virtualproductsales(onforumssuchasFlipkartandSnapdeal)gaming(WorldofWarfare)andknowledge/opinionsharing(TwitterandWikipedia)allpointtowardstherelevanceofseekingtimeandinformationfromdatasourcesthatareavailable(secondary)andcanbesought(primary)inavirtualenvironment.
The Relevance and Domain of Online Research
Inthelastdecade,whatwesawwastherecognitionoftheInternetasausefulsourceofsecondaryinformation,suchasdatabasesandonlineresources.However,todayitisbeingrecognizedasaseparatemethodasitinvolvesuniquechallengesandprocesses related to sampling,data collectionandmeasurementmetricswhicharenotprevalentintraditionalresearchasweknowit.Thus,itiscriticaltounderstandtheseissuesfromtheperspectiveofusingthemediumeffectivelyforconductingaresearchstudy.
Atypicalphenomenonofvirtualspaceisthatcompaniesnowhavetofacethetrueaspectsofdesigningconsumercentricstrategies.Thus,fortheneweraofco-creationbyconsumersandbusinessmanagers,thebusinessresearcherneedstobe“listening”towhatthebrandcommunitiesaresaying;“talking”with them for co creation; “energizing” and “supporting” tocompletetheengagementwiththeconsumer.Themediumisexcitingandhashugepotential,yetitisinanevolvingstageasitfacesconstantchallengesofchangesintermsofbusiness-customerinterfaceaswellasethicalconstraints.Thus,bothperspectivesonrecognizingthevalueoftheprocessaswellasseriousconcernsexistaboutit.Thus,beforewegoontothespecificsoftheonlineresearchprocess,letusbrieflyexaminestheprosandconsofusingthemethod.
Advantages and Disadvantages of Online Research
Justlikethetraditionalresearchprocesswehavegonethroughinthetextbookthisalsohasstrengthsandweaknessesassociatedwithit.Someofthesearelistedbelow:
Advantages
Theadvantagesareasfollows: • Low cost: Themostsupportiveargumentisthecostofconductingthe
onlineresearch.Researchershavefoundittobealmost30%cheaperto
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Research Scopeconductastudyonline.Theonlysignificantcosttheinvestigatormayincurisintheuseofthesoftwaretogeneratethestudyquestionnaire.Thishasalsobeenresolvedtoacertainextentasanumberoffreesitesareavailablethatcanbeusedfordesigninganduploadingtheinstrument.Thesecondisthesavinginthenegligibletozerocostofreachingthesamplerespondents.
• Quick response time: Thisisbothintermsofsecondarydataaswellascollectingdatathatisprimaryinnaturefromthesamplegroup.
• Better respondent engagement: Withtheinnovationindesignandtoolsavailableonthenetthequestionnaireandtheinformationseekingcanbemadeveryengagingandinterestingfortherespondent.
• Extensive reach: Theadvantageofthevirtualmediumisthattherearenodistancesintermsofapproachingthesamplegroup.Also,withadvancedsoftwareavailableitispossibletoenableanalmostinstanttranslationofthequestionsintothelanguageoftherespondent.
• Anonymity and answering: Since the researcher/investigator is inmostinstancesnotthere,therespondentfeelsfreertoanswerandtherelativeanonymitygivesthemtheassurancetoanswer,sensitiveandopenendedquestions
• Accuracy in data entry: Sincetheresponsecategoriesfortheclosedendedquestionsisdoneinthebeginningthereisnolikelihoodofhumanerrorinfillingtheanswersinthespreadsheet.Theotherrecordsintermsoftimeoffaccessandtimetakentocompletethequestionnaire,etc.,arepreciselyrecordedandagainthisensureszeroerror.
• Authentic data sources: Withmoreandmorecompaniesandresearchagenciesrealizingthemeritofthemedium,reputedcompanieslikeNielsen,ForresterandEuromonitorareestablishingonlinedivisionstocatertotheneedsofthebusinessandacademicresearcher.
Disadvantages
Thedisadvantagesareasfollows: • Skewed sample: Theconstraintofthemethodisthatthedatacollected,
especiallyprimary,canonlybeconductedonpeoplewhoareInternet-savvy.Thus,thereistheissueofgeneralizability.
• Representativeness and authenticity: The anonymity of therespondentisalsoaproblemasonedoesnotknowwhoisontheothersideasthepersonmightnotrevealhis/hertrueidentity,ageorgender.Thus,onemayconductandformulateconclusionbasedonasamplegroupthatwasnotmatchingthepopulationunderstudy.
• Significant cues: Alotofphysicalcuesthatcomefrombodylanguageandvoicemodulationsislostinanonlinesurvey.Thoughthisissueis
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beingresolvedtoacertainextentbyaudioandvideointerviewsandalsoanalysisofemoticons(smileyfaceandpunctuationandwordforms)inthetextisbeingresearchedtotryandovercomethisweakness.
• Malicious responses: Oncethequestionnaireispostedforresponseonehasnocontroloverwhoresponds.Itmighthappenthatadisgruntledemployee or customermight be extremely negative and fill thequestionnairenotoncebutmultipletimesandthusdeformtheoutput.
• Design problems: Theonlinesurveysaremoreengagingprovidedoneknowshowtomakeeffectiveuseofthesoftwarefeatures.Thus,theyarealsodifficulttodesignandtheaverageonlineresearchermightnotbeproficientindoingso.Theonlineresearchprocessisbyandlargethesameintermsofsteps
involved.However,specialmentionneedstobemadeof threeimportantissues-sampling;datacollectionanddatametrics.
Sampling For Online Research Studies
Oneof themajor challenges in online studies is designing an effectivesamplingplan andobtaining a representative sample.Since no concretesamplingframeexistsofinternetusers,obtainingaprobabilitysampleisadifficulttask.Asaresultofnon-representativenessinsamplingthesamplingerrorbecomesconsiderableand thusraisingdoubtswithreference to theresultsofthestudy.Incasetheresearchstudyisbeingconductedonafinitegroupasamongstemployeesinacompanyorevenstudentsinuniversities,thepopulationisfiniteandthuschancesoferrorareminimized.Henceintheabsenceofsamplingframeoneshoulddispersethequestionnaireonallrelevantplatforms,mailinglists,chatroom,newsgroupetc.However,thereisstillnowayofknowingwhetherthesamplewhorespondedisrepresentativeofthepopulationonewantedtostudy.
Addedtothechallengeisthefactthatthesameusermayhavemultipleaccounts.Andupdatingandcomprehending theaccountsonwhichhe isactive/inactive isdifficult toobtain.Toacertainextent therearevariouscompaniesacrosstheGlobethathaverecognizedtheweb-opportunityinthegapandprovidetheserviceofsamplingusersdirectlyfromvariouswebsites.NetzeroisonesuchfreeInternetserviceprovider.Thecompanyhasabarterstrategyandinexchangeofcompleteprofilingandtrackingrightsofuser’ssitebehaviour,itofferstheuseoffreeinternetaccess.Despitetheinvasionofprivacy,thecompanyhasmorethan8millionusers.Thusthefirmhasadatabaseofconsumersandcantoacertainextentassistinimprovingtherepresentativenatureofthesampleandalsobasedontheprofileofconsumersmanageanexperimentaldesignofexperimentalandcontrolgroup,better.
AnothercompanyutilizingthisbarterstrategyisKnowledgeNetworks.ThiscompanyusesRDD(randomdigitdialling)methodstorecruitindividuals
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Research Scopeforahouseholdpanelsurvey.Thiswouldneedtobelongitudinalinnature.TherecruitedandscreenedpanellistisprovidedfreeWebTVreceiverandinternetaccessinexchangeforagreeingtoparticipateintheonlinepanels/surveys.
Therearesometypicalwaysofsamplingonthenet.Open–Internet samples: Thissampleincludespeoplewho,forwhateverreasonvolunteeredtocompletetheonlinequestionnairesurvey.Somealsooptforbeingpartofonlinepanels.Thismethodsuffersfromtheproblemofself-selection.Thesecondproblemisthatifthesurveyistoolongtheymightgetboreorloseinterestandquitwithoutcompletingthesurvey.Also,thesearesometimesmailedandsometimestheymightberolledoutaspop-upsurveys.Thechallengewithexecutingpop-upsurveys,beingthatmostInternetusersthesedayshaveapop-upblocker.Sometimes,theresearcheralso does Internet–intercept survey,which involves interjecting into anInternetuser’sactivityonatypicalhomepageofanysite.Screened–Internet samples: Thisscreenedsamplecouldbefromtheopen-samplegrouportheymightbepartofaparticulardatabaseorserviceproviderlikeNetzero.Theyarefirstadministeredascreeningquestionnaireandthenrequestedbasedonthestudyrequirementtocompletethesurvey.Sometimesusingthescreeneritisalsopossibletoclassifythemintoseparatesegments.Inthiscaseitispossibletodirectthemtowardsseparatequestionsbasedontheircharacteristics.Forexampleinastudyoncompensationandrewards,theremightbegroupsofPublicsectorworkersaswellasprivate,sotheyaredirectedtowardsdifferentsections.Recruited sample: These arememberswho are generally accessed likethetraditionalmethodthatisoncetheyarerepresentativeofthepopulationunderstudytheyarecontactedthroughmail,email,telephoneorinperson.Andaftertheyagreetoanswerthesurveytheyaresentthequestionnaireorthelinktothequestionnaire,withapasswordtocompleteit.
Data Collection Methods for Online Research
Asisthecasewithtraditionalresearchprocess,onlineresearchalsohasthesamebasictwobroadcategoriesofdatacollection—primaryandsecondary.
I. Secondary Methods
Letusdiscussthesecondarydatacollectionmethodsindetail.
Search engines
Today, one of themost powerful andmost frequently used sources ofsecondarydataistheInternet.AnumberofcompanieslikeGoogle,Wikipedia,MSN search, andYahoo search have recognized themerit of having afull-fledgeddivisiondedicatedtothis.Thesearchengineshavetheirown
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programmedwebcrawlers,webspiders(thesearelikewebrobotsandtheysystematically“crawl”theInternettosearchandindexsites/information)oftakingthe“searcher”tovarioussites.Somepopularmethodsarebasedonkeywordsandtheirdensity,afterwhichtheylookatthelinkpopularity—intermsofhowmanytimesithasbeenaccessed—andtodaywithmonetizationofsites,howmuchdoesoneneedtopayperclick.ThereareagaingeneralsearchengineslikeGoogleandYahooandmorespecificintermsof,say,whenyouarelookingforspecificsintermsoflet’ssaystatisticaldatarelatedtoIndiandemographics,onegoes to www.censusindia.gov.in.Becauseofthehugenumberofwebsitesavailablewithasinglekeytermonemayget1000or10000optionsanditisnearimpossibletotackleallofthem,theotherchallengeisthatalotofsites,especiallyscholarlysearchsiteslikewww.hbsp.harvard.edu (HarvardBusiness School publishing) require apasswordandcannotbeaccessednormally.Thus,theresearchersmayliketomovetofocusedandreliablesiteslikePathfinders.Pathfindersarebasicallysitesthattaketheusertoalimitedportfolioofsitesthatareprovidedbycredible sources. www.pathfinderhealth.in is a pathfinder that is focusedon informational sites related to health and relevant to the Indian user/practitioner.Thesesiteshavewhatareknownas intelligentcrawlers thatindexspecifictopic-relatedresults.
Newsgroups
These are quite similar to other socialmedia platforms.They are callednewsgroups because they are a primarymethod of communication in avirtualworldwithlikemindedprofessionals(e.g.marketingacademicians—www.marketingpower.com) or special interest groups (e.g.managementaspirants—www.pagalguy.com).The “Internet reader” can view threads(conversationhistories);posequestionstoothergroupmembersorrebukeordisagreewithpointsofviewsmoreorlessasinaface-to-faceargument.Atypicalnewsgroupmessagelooksverysimilartoanemail.Thereisasender,asubjecttitleandtheactualmessage.Thesethreadsarepowerfulsourcesofinformationasyouasaresearchercanbrowsethroughanentirethreadandgetafirsthandqualitativeinsightintowhattherespondentpopulationisthinkinganddoing.
Blogs
Blogs originated in the late 1990swhen theywere usuallymanaged byanenthusiastwhogaveachronologicalindexofsitesofinterestandalsoprovidedapersonalcommentaryonthelinksorsites.However,laterpeoplecreatedtheirownprivateblogs,whichwerelikepublicsharingofprivate,personalviewsandthoughts.Thefact that theyare in thepublicdomainmeanstheyareaccessibleandsometimesonesexpressionofdiscontentordespairthatreflectsapersonalmiserycreatesareactionandsometimescanleadtoanuprising,ascanbeseeninanumberofcasesofrebellioninthe
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Research Scopeyears2011–12.Marketingresearchersfindblogsasveryinterestingastheyareabletounderstandthelifestyleandbeliefsaboutanyconsumersegmentrather thanmerely the product or the brand, thusmaking targeting andpositioningstrategiesmorefocusedandmeaningful.Infacttherearesearchengineslikewww.blogsearch.comthatcanhelparesearcherconductablogsearchonanytopicofinterest.
II. Primary Methods
Thepremiseof using theprimarymethods and thebasic nuances of thetechniquesremainthesame.Inthissection,wewillhighlighttheaspectsthataredifferentandthusneedtobetakencareofwhilemakinguseofanyofthese.Therearealsosomeprimarymethods–netnography—thatareuniquetothismediumandwillbedealtwithintheendinsomedetail.
Beforewe proceed further, let us examine some categorization ofonlineprimarymethods.Oneisbetweenaweb-basedmethodinwhichtheresearchercouldmakeuseofawebdesignedquestionnaireandcollectthedatafromtherespondent.Theotherisacommunicationmethod,whichismorepersonalizedandtargetedtowardscollectingspecificinformationfromidentified samplegroup.This involvesusing the email as a personalizedplatformforcollectinginformation.
Theothermethodissynchronizedvsnon-synchronized.Inthefirsttheresearcher/interviewerasksquestionsandtherespondentanswersinrealtimewhileinthesecondcasethequestionnaireissenttotherespondentandhe/sheanswersasperherconvenienceatalatertimeslot.
Online focus groups
Thefocusgroupisasrichinitsconductandusefulnessasitistherealworld.Herethefocuscroupcouldbebothintheformofchatordiscussionforums—wherethegroupmembersarealreadyfamiliarwitheachotherorelsetheyareselectedthroughtheInternet.Themethodcouldalsobesynchronizedwhereallmembersandthemoderatorarediscussingatasinglemomentintime.However,therecouldalsobenon-synchronizedfocusgroupswherethemembersmightposttheircommentsandthenmoveoutofthegrouptoconductotheractivitiesandsomeoneelsemayrespondmuchlaterandtheuserwhenhe returns then responds to the comment.These are typicallycalledbulletinboards.
Asthemethodinvolvesusuallytypingonesresponseitisrecommendedthatsincetherecouldbesimultaneousresponsefromthegroupmembersratherthan8-10asisthepracticeinaregularfocusgrouponeshouldlimitoneselfto6-8members.Secondly,themoderatormustbefastintypingonthekeyboardandbeveryfamiliarwithhandlingdiversionsandinterjectionsonthesoftwareplatform.Atypicalonlinefocusgrouplastforabouttwohours.Whilesomegroupmembersmightbekeyingintheirresponseothers
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mightreactwithemoticonslikesmileys,etc.,toexpresstheirfeelingsforthestatementorcomment.Sincetherecouldbemultiplepeoplewhorespondatthesametime,itmightbeprudenttousetwomoderatorssothatmultiplereactionscanbehandledatthesametime.Justlikethetraditionalmethodtheonlinemethodshavetheirownchallengesandadvantages.Theadvantageprimarilybeingintermsofcost,geographicreachandtoacertainextenttheydonotinvolvefacingagroup.Thedisadvantagesarethattherichnessofnon-verbalcuesarelosthere.
Social network analysis
ThismethodhasitsorigininSociometry.Here,essentiallyonetriestostudysocialorvirtualsocialties.Thisinvolvesstudyingthestructure—hierarchyandpatternsofnetworksthatemergebetweensocialorvirtualactors.Thereareessentiallytwoaspectsoneisanalyzing—nodes(thenetusers)andtheties(theirrelationshipwitheachother).Thetiescouldbeasharingofideas,information a business transactionor an emotional transaction.One cando things inasocialnetwork—eitherobserve theway the information isflowing—intermsofwhoisthecentreofthenetwork(opinionleader),whoistheloner,aretheirtwopeoplewhocommunicatemorewitheachother(dyads).Thesecondmethod is toaskquestionsandfindoutwithwhomthegroupmemberswouldinteractforemotionalproblemsorinformation/knowledgeseeking.Basically, theideabeingtoassesshowdecisionsaretaken in group settings andhowgroupdynamics influence individual orgroupbehaviourinaparticularnetwork.
Online surveys
Theonlinesurveymaybeconductedinbothrealtimeandnon-synchronized.Thesurveycouldinvolveeitherofthefollowingtwomethods: • E-mail-based surveys: These are generally conducted after the
sampling has been done and the email address of the respondenthas beenmade available.Postwhich the study instrumentmaybeattachedwiththemailorbeembeddedinthemail.inthiscasetherewouldbeashortintroductiontothestudyandtherespondentanswersthequestionsandthencarryoutthesimpleactionofreply,thefilledquestionnairereturnsbacktotheresearcher.Theothermethodisthatthereisanattachmentwhichneedstobedownloadedandthenfilledin.Thiscanbeeithersentbackasanattachmentorthephysicalcopycanbemailedbacktotheresearcher.
• Web-based surveys: Theseinvolveusingsoftwareoraprogramtogenerateaquestionnaire.Thismethodhasahugeadvantageintermsofdesigncapabilities.Onecanmakethequestionnaireengagingandinterestingbymakinguseofcomputerprograms.Secondly,theoptionoffilter andbranching question that are tediouswhendone in the
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Research Scopetraditionalmannerarehandledveryefficientlyhere.Inmostinstancesthe instrument requires the respondent to punch/key in the buttonindicating their response.There aremultipleweb surveypackagesavailabletodaythatcanhelptheresearchertoefficientlydesignawebsurvey,e.g.Websurveyor;PerseusSurveyMonkey;Zoomerang,etc.Thesoftwarefurthersegregateandcategorizedatabytabulatingtheresponses.Thusthetaskofmakingadataentryandcodingthedataissavedasthehumanerrorindataentryiseliminatedhere.Thebasicchallenge liesnot indesigningbut ingetting the respondent to theinstrumentandmotivatingthemtocompletethesurvey.
Netnography
RobertZ.Kozinets (2010) came upwith an onlinemethod that has itsrootsinethnographicanalysis.Ethnographyisbasicallyananthropologicaltechniqueusedquiteactivelytodayinthefieldofmarketingandconsumerresearchtoday.Themethodisdistinguishedfromotherprimarymethodsasitusesmultiplemethodsinconjunctionwitheachothertoarriveatarichandholisticpictureaboutacultureoracommunity.Themethodspopularlyusedaretheobservationmethod,semiotics,films,documentaries,conversationalanddiscourseanalysis,videography.Theideabeingtouseeverypossiblepieceofcommunication/informationthathasbeenspouted/createdbytheuserofthatcommunitytounderstandtheapparentandlatentaspectsaboutthecommunity.
Kozinet took the participant-observationmethod to understanddiscourseandconversationsonthecomputerasthesourceofdata.Thusthepremiseisthatalongwithitsothermethods,ethnographicanalysismusttakeintoaccountthedataobtainedfromanetnographicanalysis.
Ethnographytonetnographicanalysiscanbeviewedasacontinuum.At the one end is a face to face interaction-observation, dialogue, datacollection,whichisanethnographicanalysis.Letussaywewanttostudytheworldorchallengesfacebysinglemothersofautisticchildren.Now,letussaythatthesesinglemothersspendconsiderabletimeonline,thusatthenextstagewestudythesecommunitiesonlineandboththefacetofaceandonlinemethodsprovideusarichunderstandingoftheirgroupinitsentirety.Thelaststageiswhenwestudyonlyonlinecommunities—secondlife—andourobservationarelimitedtoonlytheironlineinteraction.Thismethodiscallednetnography.Themethodhasitsownsetofpeculiaritiesthatneedtobeunderstoodbeforewediscussthemethodofnetnographicanalysis.Thefirst isalteration—thetechnology-basedmediuminwhichthe interactionis happening is different from the traditional interaction as peoplemoveinandoutoftheplatform,comebacksometimesinstantlyandsometimesafterdays to respond toamessageorcommunication.Thesecond is theanonymousnatureofthemediumthatletsthecommunitymembergivevent
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tobehavior,feelingsandexpression,thatmayneverbepossibleintheactualworld,howeverthiscanalsobeachallengeasitbecomesextremelydifficulttoidentifythecommunityorevengenderthispersonbelongsto.Thethirdaspect isaccessibility,oncepartofanonlinecommunity,one isprivy toeverythingandanythingthatthepersonisdoingintheirvirtualworldandthelastisthatbecauseofitsverynatureofstorage,historicalarchivingofactivityandcommunicationisextremelyeasy.
A typical netnographic analysis involves adopting a structuredapproach. • Step 1- Identifying the research question and objectives: Once done
andyouhaveidentifiedwhatkindofinformationorknowledgethatyouseekaboutthecommunity.Youfirstneedtovisitsitesfrequentedbythecommunities(secondarydata)tounderstandtheirtypicallingos,theirconcernsandpatternsofcommunicatingwitheachother.
• Step 2- Identifying and approaching the communities: Once you haveunderstoodthemtoacertaindegree,thenextthingistoidentifythe forumsor groups onwhich they interact- these could be chatforums,bulletinboard,andsocialnetworkingsites.Nextoneneedstoshortlistthecommunitiesthatonewantstoenter.Itissuggestedthatoneentersthegroupsthatareinteractive,active,heterogeneousandalsothecommunicationcontentisrich.
• Step 3- Ethical immersion and participation in the communities: Ateverystageinthestudytheresearchermustfollowanethicalpathtotheintroductionandparticipationinacommunity.Thusthetimewhen the researcher enters the community, explains the academicpurposeofthedesiretoenterthecommunity.Thedatacollectionhereis alsomulti fold. It involvespostingcomments,posingquestions,gettingfeedback,takingonlineinitiativeandtakingleadershiproles.Theresearcherhastodecideabouthowthecommunicationandonlinebehaviouristoberecorded.Itisadvisedhowever,thattheresearchermaintainsobservationalfieldnotesonthesecommunicationpieces.
• Step 4- Data analysis and interpretation: Likeanyotherqualitativemethod, researcher needs tomake sense of the huge amount ofconversationpieces thathehasgatheredand triesanddiscerns theunderlyingorcommonpatternsofideasorbehaviour.Thiscanbedonemanually,wheretheresearcherattemptstodrawcategoriesandtriestoestablishpossiblerelationshipsorlinksbetweenobservedattitudeorbehaviour.Pleaseunderstandthisisnotinterpretationbutanalysisthatisverysimilartocontentanalysis.TherearealsosoftwareprogramssuchasCAQDAS(computerassistedqualitativedataanalysis)thatdo thesameanalysis in termsof lookingat identifyingandcodingrecurrentthemes.
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Research Scope • Step 5- Evaluating and interpreting netnographic data:Kozinetshas identified10criteria thatanetnographicanalysismustmeet inordertoconsiderthefindingsoftheanalysisasanaccurategroundforestablishingaccuratelyanycharacterizationaboutthecommunityorcultureunderstudy.Thepremiseessentiallybeingthatthedevelopedideasandconstructsmustbedistinct fromeachother.Theyshouldbegroundedinsometheoreticalframework,allowforflexibilityofinterpretationbyotherresearchersandbeabletoinspiresomekindofappliedsocialactionwithreferencetothecommunity.Today,netnographyisatechniquethatisbeingappliedtoblogs,tweets,
and socialnetworking sites like facebook,podcasts andvideocasts.Thetechniquebecomesincreasinglyimportantasitisabletoprovideinsightsintohowpeoplethinkandreact.Thecompaniesareabletoconnectwiththeircustomers/stakeholdersbetteriftheyunderstandtheperson’sinnerworld.Thethirduseisthattheresearchcanprovidevaluablemeansofcommunicatingwiththesecommunitiesinamannerandlanguagethattheyunderstandandbelieve in.
Online data metrics
Theresearchprocessinvolvedinanonlineresearchstudyisverysimilartothatconductedotherwise.Howevertherearecertainvariablemeasurementsthatareuniquetoonlineresearch.Itisnotpossibletodiscusseachoneofthematlength;however,anattemptismadetogivethereaderasubstantiveideaaboutwhattolookforandhowtomeasureit. 1. Cookie: Isthehistoricalrecordonyourcomputerofyourvisitingany
website.EverycookiehasanIDnumber,adomainnameandanexpirydate,thusbecomesusefulintrackinguserbehaviour.
2. Webserver log files: Mostwebhostswhocreate thewebsitehaveaninbuiltmechanismofstoringanyrequestmadethere.Thusdetailsabouttheuserwhoaccessedyoursiteareavailabletoyou.Onecanprogramthewebanalyticsoftwaretorecordthevisitorinformationinthemanneryouwishto.
3. Page tagging: Besidesthewebsiteonecantagindividualpagesonthewebsiteandrecorddetailsofthosewhovisitedthepage.Asthisisrelatedtowhatwereferredtoasintelligentcrawlingwheretheusermight be looking for specific information.There are free analyticserviceslikeGoogleanalyticsthatcanassistinthisformoftracking.
Key performance indicator
Keyperformanceindicators(KPIs)areessentiallymeasuresofoutcomeorthedependentvariableandtheresearchercandecidewhathe/shewantstoassessdependingontheobjectiveoftheresearchstudy.SomePopularKPIsare:
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1. Ad impression: ThisisameasureofthenumberoftimesanadbannerisdisplayedontheInternet.
2. Cost per thousand impressions (CPM): Thismodel based onimpressionsoressentiallyawarenesswas themodelused till1997.Postthatthewebmarketerwasmoreconcernedabouttheviewerandthecompanypaidforbeingseenbytheuser.
3. CTR: Click through rate is a percentagefigurewhich is the ratiobetweenthenumbersofimpressionsanadgetsuponthenumberoftimestheadwasshown.
4. Bounce rate: Bouncerateindicatesthenumberofpeoplewhovisitawebsite’slandingpageandbouncebackwithoutbrowsingfurther.
5. Open rate: Incasesomeinformationorlinkwassentbye-mail.Thentheopenrateis thenumberofpeoplewhoopenedthee-mail.ThisrequirestheHTMLorimagetoopenandincasethishasbeendisabledbytherecipientitcannotbeusedasametrics
6. CTOR (click to open rate): IncasealinkwassentonanemailthentheCTORmeasures thenumberofpeoplewhoopened the linkvsthosewhoopenedthee-mail.
7. Conversion rate: Thisistheproportionofpeoplewhovisityoursitevsthosewhocarryoutaspecificaction,say,purchase.
8. Abandonment rate: Thosewho start an action but quit beforecompletingtherequiredactivity.Saymakingapaymentatthepaymentgateway.
9. Page views: thenumberofpagesonyoursiteviewedbyasitevisitor. 10. Absolute unique visitor: Thedetailsofthevisitorwhovisitedyour
websiteatauniquetimeperiod-sayanonlinepromotion. 11. New vs returning visitors: Thosewhoarriveatthepageforthefirst
timevsthosewhohavevisitedthesiteearlier. 12. Cost per click (CPC): Theratiooftheadvertisingspendvsthenumber
ofclicksthesponsoredsearchorbanneradvertisementgot.ThiswasmoreimportantthanCPMasaclickwouldmeanahigherprobabilitythattheuserwouldconvertintoapurchaseatthesite.
13. Transaction conversion rate (TCR): Thisistheratioofthefixedcostofadvertisingvsthenumbersofconversionsposttheadvertisement.
14. Take rate = CTR X TCR: Isthenumberoftimesavisitorclicksandthenconvertsintoatransaction.
15. Return on ad dollars (ROA): Isameasureof totalrevenuemade(TCR)/costofinternetmarketing.
16. Word of mouth (WOM): thisisanimportantmetricsforevaluatingsocialmediaeffectiveness=
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Research ScopeNumberofdirectclicks+NumberofclicksbasedonrecommendationNumberofdirectclicks
Theseareexamplesoftheoutputintermsofwhatistheobjectiveofanonlinestrategy.Thebusinessresearchermightstudyeitherthepatternofthesematricesacrosssegmentsorcommunitiesoralternativelytrytoestablishtheantecedentsoftheseastheseinsightsarewhatarenecessaryforthebusinessmanagerwhowantstobettermanagehis/here-commerceactivities.
2.3 DISTINCTION BETWEEN DIFFERENT TYPES OF RESEARCHES
WehavealreadylearnedthemeaningofdifferenttypesofresearchinUnit1. Letusrecapitulatethedistinctionsbetweendifferentmajortypesofresearches: • Pure vs Applied Research:Pureresearchisalsoknownasfundamental
research. It is exploratory in nature and is conductedwithout anypracticalend-useinmind.Pureresearchdrivenbyinterest,curiosityorintuition,anditsobjectiveistoadvanceknowledgeandtoidentify/explainrelationshipsbetweenvariables.Ingeneral,appliedresearchisnotcarriedoutforitsownsakebutinordertosolvespecific,practicalquestionsorproblems.Ittendstobedescriptive,ratherthanexploratoryandisoftenbaseduponpureresearch.
•Historical vs Futuristic Research: Historical research entailsunderstandingpasteventstopredictfutureones.Ontheotherhand,futuresresearchcanbedefinedasasystematicstudyofpossiblefutureeventsandcircumstances.
•Synthetic vs Analytical Research:Asyntheticapproachtoresearchlooksattheresearchquestionortopicfromaholisticpointofview.Here,theresearchertriestocomprehendthepartsoftheproblembylookingat thewhole.Ananalyticapproach to researchwould lookat a topic froma constituent point of view.The researcher tries tocomprehendthewholephenomenonbylookingattheseparateparts.
•Descriptive vs Prescriptive Research: Descriptive research isemployedtodescribecharacteristicsofapopulationorphenomenonbeingstudied.Itdoesnotanswerquestionsabouthow/when/whythecharacteristicsoccurred.Prescriptiveresearch,likeEvaluativeresearch,isappliedratherthantheoretical.Itisdifferentfromevaluativeresearchinthatitgoesastepfurther,beyondidentifyingsuccessorperformanceoroutcomes,andactuallyrecommendssolutionsornewideas.
•Experimental vs Survey Research:Experimentandsurveymethodsishighlycriticalindatagathering.Bothtypesofresearchisemployedtotesthypothesesandcomeupwithconclusions.Researchthrough
Research Scope
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experiments entails themanipulation of an independent variableandmeasuringitseffectonadependentvariable.Ontheotherhand,conducting surveys often entails the use of questionnaires and/orinterviews.While experimentalmethod is a type of experimentalresearch,surveyisatypeofdescriptiveresearch.
•Case vs Generic Researches:Casestudiesareatypeofdescriptiveresearchwhichencompassesdetailedanalysisofasingle(orlimitednumber) of peopleor events.Case studies are typically interestingbecauseof theunusualnessof thecase.On theotherhand,genericresearchorgenericqualitativeresearchispresumedtogobeyondtheobservableconstructsandvariablesthatarenotvisibleormeasurable;rathertheyhavetobededucedbydifferenttechniques.
Check Your Progress
1.Whatisthedisadvantageoftheskewedsamplemethod? 2.Listonechallengeofonlinestudies. 3.WhatareKPIs? 4.Whatispureresearchalsoknownas?
2.4 ANSWERS TO CHECK YOUR PROGRESS QUESTIONS
1.The disadvantage of the skewed samplemethod is that the datacollected,especiallyprimary,canonlybeconductedonpeoplewhoareInternet-savvy.
2.Oneofthemajorchallengesinonlinestudiesisdesigninganeffectivesamplingplanandobtainingarepresentativesample.
3.Keyperformanceindicators(KPIs)areessentiallymeasuresofoutcomeorthedependentvariableandtheresearchercandecidewhathe/shewantstoassessdependingontheobjectiveoftheresearchstudy.
4.Pureresearchisalsoknownasfundamentalresearch.
2.5 SUMMARY
• Inthelastdecade,whatwesawwastherecognitionoftheInternetasausefulsourceofsecondaryinformation,suchasdatabasesandonlineresources.
•Atypicalphenomenonofvirtualspaceisthatcompaniesnowhavetofacethetrueaspectsofdesigningconsumercentricstrategies.
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Research Scope •Oneofthemajorchallengesinonlinestudiesisdesigninganeffectivesamplingplanandobtainingarepresentativesample.
•Sincenoconcretesamplingframeexistsofinternetusers,obtainingaprobabilitysampleisadifficulttask.
•Asisthecasewithtraditionalresearchprocess,onlineresearchalsohasthesamebasictwobroadcategoriesofdatacollection—primaryandsecondary.
•Thepremiseofusingtheprimarymethodsandthebasicnuancesofthetechniquesremainthesame.
•Thefocusgroupisasrichinitsconductandusefulnessasit is therealworld.Herethefocuscroupcouldbebothintheformofchatordiscussion forums—where thegroupmembers are already familiarwitheachotherorelsetheyareselectedthroughtheInternet.
•The research process involved in an online research study is verysimilartothatconductedotherwise.Howevertherearecertainvariablemeasurementsthatareuniquetoonlineresearch.
•Transactionconversionrate(TCR):Thisistheratioofthefixedcostofadvertisingvsthenumbersofconversionsposttheadvertisement.
•Historicalresearchentailsunderstandingpasteventstopredictfutureones.Ontheotherhand,futuresresearchcanbedefinedasasystematicstudyofpossiblefutureeventsandcircumstances.
•Case studiesarea typeofdescriptive researchwhichencompassesdetailedanalysisofasingle(orlimitednumber)ofpeopleorevents.
2.6 KEY WORDS
• Questionnaire:Itreferstoasetofprintedorwrittenquestionswithachoiceofanswers,devisedforthepurposesofasurveyorstatisticalstudy.
• Case Studies: It refers to process or records of research into thedevelopmentofaparticularperson,group,orsituationoveraperiodoftime.
• Ethnography: It refers to the scientificdescriptionofpeoples andcultureswiththeircustoms,habits,andmutualdifferences.
• Focus Group: Itreferstoagroupofpeopleassembledtoparticipateinadiscussionaboutaproductbefore it is launched,or toprovidefeedbackonapoliticalcampaign,televisionseries,etc.
Research Scope
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2.7 SELF ASSESSMENT QUESTIONS AND EXERCISES
Short Answer Questions
1. Whatareblogs? 2.Writeashort-noteononlinesurveys. 3.Whatisprescriptiveresearch?
Long Answer Questions
1. Differentiatebetweenvarioustypesofresearch. 2.Whatisonlineresearch?Discussitsadvantagesanddisadvantages. 3.Examinethedatacollectionmethodsforonlineresearch.
2.8 FURTHER READINGS
Creswell,JohnW.2002.Research Design: Qualitative, Quantitative, and Mixed Methods Approaches.London:SagePublicationsInc.
Booth,Wayne,GregoryG.ColombandJosephM.Williams.1995.The Craft of Research.Chicago:UniversityofChicagoPress.
Bryman,AlanandEmmaBell.2015.Business Research Methods.4thEdition.UnitedKingdom:OxfordUniversityPress.
Gupta,S.L.andHiteshGupta. 2012. Business Research Methods. NewDelhi: TataMcGrawHillEducationPrivateLimited.
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Planning of Research
UNIT 3 PLANNING OF RESEARCHStructure 3.0 Introduction 3.1 Objectives 3.2 ResearchProblem
3.2.1 Identification,SelectionandFormulationofResearchProblem 3.2.2 IdentificationofObjectivesoftheResearch 3.2.3 StatementofResearchProblemandCostandValueInformation
3.3 ReviewofLiteratureintheFieldofBusiness 3.4 AnswerstoCheckYourProgressQuestions 3.5 Summary 3.6 Key Words 3.7 SelfAssessmentQuestionsandExercises 3.8 FurtherReadings
3.0 INTRODUCTION
Inthisunit,youwilllearnabouttheplanningofresearch.Beforearesearchworkiscarriedout,alotofplanningisrequired.Properplanninghelpsinperformingresearchworkwithmuchease.Thisunitfocussesonthebasicconceptofplanningaresearchwhichisessentialwhileconductingresearchforaspecificpurpose.Ideassuchasresearchproblemsarediscussed.Researchproblemsarequestionsthatindicategapsinthescopeorthecertaintyofourknowledge.Discoveringaproblemputstheresearchprocessintoactionandidentificationofthepurposeisthefirststeptowardsthesolution.
3.1 OBJECTIVES
Aftergoingthroughthisunit,youwillbeableto: •Definearesearchproblem •Describehowaresearchproblemisidentified,selectedandformulated •Discussreviewofliterature
3.2 RESEARCH PROBLEM
Research problems are questions that indicate gaps in the scope or thecertainityofourknowledge.Theypointeithertotheproblematicphenomena,observed events that are puzzling in terms of the accepted ideas, or toproblematictheories,currentideasthatarechallengedbynewhypothesis.
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Defining the Research Problem
Problemdiscoveryputstheresearchprocessintoactionandidentificationoftheproblemisthefirststeptowardsitssolution.Properlyandcompletelydefiningabusinessproblemiseasiersaidthandone.Actually,theresearchtaskmaybetodefineorevaluateanopportunityortoclarifyaproblem.Thedefinitionanddiscoveryoftheresearchproblemisviewedunderthisbroadercontext.Inresearch,often,onlysymptomsareapparenttobeginwith.Theadage‘aproblemwelldefinedisaproblemhalfsolved’isworthremembering.Theinvestigationgetsasenseofdirectionwithanorderlydefinitionoftheresearch problem.A careful attention to the problemdefinition allows aresearchertosettheproperresearchobjectives.Whenthepurposeofresearchisclear,thechancesofcollectingtherelevantandnecessaryinformationaregreater.(SeeAppendixgivenattheendofthisunit).However,justbecauseaproblemhasbeendiscoveredoranopportunityhasbeenrecognizeddoesnotmeanthattheproblemhasbeendefined.Aproblemdefinitionindicatesaspecificmanagerialdecisionareatobeclarifiedoraparticularproblemtobesolved.Itspecifiesresearchquestionstobeansweredandtheobjectivesoftheresearch.
3.2.1 Identification, Selection and Formulation of Research Problem
Thefirstandthemostimportantstepoftheresearchprocessistoidentifythepathofenquiryintheformofaresearchproblem.Itisliketheonsetofajourney,inthisinstancetheresearchjourney,andtheidentificationoftheproblemgivesanindicationoftheexpectedresultbeingsought.Aresearchproblem can be defined as a gap or uncertainty in the decisionmakers’existing body of knowledgewhich inhibits efficient decisionmaking.Sometimesitmaysohappenthattheremightbemultiplereasonsforthesegapsandidentifyingoneof theseandpursuingitssolution,mightbe theproblem.AsKerlinger(1986) states,‘Ifonewantstosolveaproblem,onemustgenerallyknowwhattheproblemis.Itcanbesaidthatalargepartoftheproblemliesinknowingwhatoneistryingtodo.’Thedefinedresearchproblemmightbeclassifiedassimpleorcomplex (Hicks,1991).Simpleproblemsarethosethatareeasytocomprehendandtheircomponentsandidentifiedrelationshipsarelinearandeasytounderstand,e.g.,therelationbetweencigarettesmokingandlungcancer.Complexproblemsontheotherhand, talksabout interrelationshipbetweenantecedentsandsubsequentlywiththeconsequentialcomponent.Sometimestherelationmightbefurtherimpactedbythemoderatingeffectofexternalvariablesaswell,e.g.,theeffectofjobautonomyandorganizationalcommitmentonworkexhaustion,atthesametimeconsideringtheinteracting(combined)effectofautonomyandcommitment.Thismightbefurtherdifferentformalesandfemales.These
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Planning of Researchkindsofproblemsrequireamodelorframeworktobedevelopedtodefinetheresearchapproach.
Thus, thesignificanceofaclearandwell-definedresearchproblemcannot be overemphasized, as an ambiguous andgeneral issue does notlend itself to scientific enquiry. Even though different researchers havetheirownmethodologyandperspectiveinformulatingtheresearchtopic,ageneralframeworkwhichmightassistinproblemformulationisgivenas follows:
Problem identification process
Theproblemrecognitionprocessinvariablystartswiththedecisionmakerandsomedifficultyordecisiondilemmathathe/shemightbefacing.Thisisanactionorientedproblemthataddressesthequestionofwhatthedecisionmakershoulddo.Sometimes,thismightberelatedtoactualandimmediatedifficultiesfacedbythemanager(appliedresearch)orgapsexperiencedintheexistingbodyofknowledge(basicresearch).Thebroaddecisionproblemhastobenarroweddownto informationorientedproblemwhichfocusesonthedataorinformationrequiredtoarriveatanymeaningfulconclusion.GiveninFigure3.1isasetofdecisionproblemsandthesubsequentresearchproblemsthatmightaddressthem.
Management decision problem
Theentireprocessexplainedabovebeginswiththeacknowledgementandidentificationofthedifficultyencounteredbythebusinessmanager/researcher.Ifthemanagerisskilledenoughandthenatureoftheproblemrequirestoberesolvedbyhimorheralone,theproblemidentificationprocessishandledbyhimorher,elseheorsheoutsourcesittoaresearcheroraresearchagency.Thissteprequirestheauthortocarryoutaproblemappraisal,whichwouldinvolveacomprehensiveauditoftheoriginandsymptomsofthediagnosedbusinessproblem.Forillustration,letustakethefirstproblemlistedintheFigure3.1.AnorganicfarmerandtraderinUttarakhand,Nirmalfarms,wantstosellhisorganicfoodproductsinthedomesticIndianmarket.However,heisnotawareifthisisaviablebusinessopportunityandsincehedoesnothavetheexpertiseortimetoundertakeanyresearchtoaidintheformulationofthemarketingstrategy,hedecidestooutsourcethestudy.
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Fig. 3.1 Converting Management Decision Problem into Research Problem
Discussion with subject experts
Thenextstepinvolvesgettingtheproblemintherightperspectivethroughdiscussionswith industry and subject experts.These individuals areknowledgeableabouttheindustryaswellastheorganization.Theycouldbefoundbothwithinandoutsidethecompany.Theinformationonthecurrentandprobablescenariorequiredisobtainedwith theassistanceofasemi-structuredinterview.Thus,theresearchermusthaveapredeterminedsetofquestionsrelatedtothedoubtsexperiencedinproblemformulation.Itshouldberememberedthatthepurposeoftheinterviewissimplytogainclarityontheproblemareaandnottoarriveatanykindofconclusionsorsolutionstotheproblem.Forexample,fortheorganicfoodstudy,theresearchermightdecide togo to foodexperts in theMinistry forFoodandAgricultureoragriculturaleconomistsorretailersstockinghealthfoodaswellasdoctorsanddieticians.Thisdatahowever isnotsufficient inmostcaseswhile inothercases,accessibilitytosubjectexpertsmightbeanextremelydifficult
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Planning of Researchtask as theymightnotbe available.The information should, inpractice,besupplementedwithsecondarydataintheformoftheoreticalaswellasorganizationalfacts.
Review of existing literature
Aliteraturereviewisacomprehensivecompilationoftheinformationobtainedfrompublishedandunpublishedsourcesofdatainthespecificareaofinteresttotheresearcher.Thismayincludejournals,newspapers,magazines,reports,governmentpublications,andalsocomputerizeddatabases.Theadvantageofthesurveyisthatitprovidesdifferentperspectivesandmethodologiestobeusedtoinvestigatetheproblem,aswellasidentifypossiblevariablesthatmayneedtobeinvestigated.Second,thesurveymightalsouncoverthefactthat theresearchproblembeingconsideredhasalreadybeeninvestigatedandthismightbeusefulinsolvingthedecisiondilemma.Italsohelpsinnarrowingthescopeofthestudyintoamanageableresearchproblemthatisrelevant,significantandtestable.
Oncethedatahasbeencollectedfromdifferentsources,theresearchermustcollateallinformationtogetherinacogentandlogicalmannerinsteadofjustlistingthepreviousfindings.Thisdocumentationmustavoidplagiarismandensurethatthelistofearlierstudiesispresentedintheresearcher’sownwords.Thelogicalandtheoreticalframeworkdevelopedonthebasisofpaststudiesshouldbeabletoprovidethefoundationfortheproblemstatement.
Thereportingshouldciteclearlytheauthorandtheyearofthestudy.There are several internationally accepted formsof citing references andquotingfrompublishedsources.ThePublication Manual of the American Psychological Association(2001)andtheChicago Manual of Style(1993)areacademicallyacceptedasreferencingstylesinmanagement.
Toillustratethesignificanceofaliteraturereview,givenbelowisasmallpartofaliteraturereviewdoneonorganicpurchase.
Researchindicatesorganicisbetterqualityfood.Thepesticideresidueinconventionalfoodisalmostthreetimestheamountfoundinorganicfood.Bakeret al.(2002)foundthatonanaverage,conventionalfoodismorethanfivetimeslikelytohavechemicalresiduethanorganicsamples.Pesticidestoxicity has been found to have detrimental effects on infants, pregnantwomenandgeneralpublic(NationalResearchCouncil,1993;Maet al.,2002;Guilleteetal.,1998)Majorfactorsthatpromotegrowthinorganicmarketareconsumerawarenessofhealth,environmentalissuesandfoodscandals(YossefiandWiller,2002).
Thisparagraphhelpsjustifytherelevanceandimportanceoforganicversusnonorganicfoodproductsaswellas identifyvariables thatmightcontributepositivelytothegrowthinconsumptionoforganicproducts.
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Organizational analysis
Anothersignificantsourceforderivingtheresearchproblemistheindustryandorganizationaldata.Incasetheresearcher/investigatoristhemanagerhimself/herself,thedatamightbeeasilyavailable.However,incasethestudyisoutsourced,thedetailedbackgroundinformationoftheorganizationmustbecompiled,asitservesastheenvironmentalcontextinwhichtheresearchproblemhastobedefined.Itistoberememberedatthisjuncturethattheorganizationalcontextmightnotbeessentialincaseofbasicresearch,wherethenatureofstudyismoregeneric.
Thisdataneedstoincludetheorganizationaldemographics—originandhistoryofthefirm;size,assets,natureofbusiness,locationandresources;managementphilosophyandpoliciesaswellasthedetailedorganizationalstructure,withthejobdescriptions.
Qualitative survey
Sometimes the expert interview, secondary data and organizationalinformationmightnotbeenoughtodefinetheproblem.Insuchacase,anexploratoryqualitativesurveymightberequiredtogetaninsightintothebehaviouralorperceptualaspectsoftheproblem.Thesemightbebasedonsmallsamplesandmightmakeuseoffocusgroupdiscussionsorpilotsurveyswiththerespondentpopulationtohelpuncoverrelevantandtopicalissueswhichmighthaveasignificantbearingontheproblemdefinition.
Intheorganicfoodresearch,focusedgroupdiscussionswithyoungandoldconsumersrevealedthelevelofawarenessaboutorganicfoodandconsumersentimentsrelatedtopurchaseofmoreexpensivebutahealthyalternativefoodproduct.
Management research problem
Oncetheauditprocessofsecondaryreviewandinterviewsandsurveyisover,theresearcherisreadytofocusanddefinetheissuesofconcern,thatneedtobeinvestigatedfurther,intheformofanunambiguousandclearly-definedresearchproblem.Onceagainitisessentialtorememberthatsimplyusingtheword‘problem’doesnotmeanthereissomethingwrongthathastobecorrected,itsimplyindicatesthegapsininformationorknowledgebaseavailabletotheresearcher.Thesemightbethereasonforhisinabilitytotakethecorrectdecision.Second,identifyingallpossibledimensionsoftheproblemmightbeamonumentalandimpossibletaskfortheresearcher.For example, the lackof sales of a newproduct launch couldbedue toconsumerperceptionsabouttheproduct,ineffectivesupplychain,gapsinthedistributionnetwork,competitorofferingsoradvertisingineffectiveness.It istheresearcherwhohastoidentifyandthenrefinethemostprobablecauseoftheproblemandformalizeitastheresearchproblem.Thiswouldbeachievedthroughthefourpreliminaryinvestigativestepsindicatedabove.
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Planning of Research3.2.2 Identification Objectives of the Research
Letusdiscusstheresearchobjectives.
Statement of research objectives
Next,theresearchquestion(s)thatwereformulatedneedtobebrokendownandspeltoutastasksorobjectivesthatneedtobemetinordertoanswertheresearchquestion.
Basedontheframeworkofthestudy,theresearcherhastonumericallylistthethrustareasofresearch.Thissectionmakesactiveuseofverbssuchas‘tofindout’,‘todetermine’,‘toestablish’,and‘tomeasure’soastospellouttheobjectivesofthestudy.Incertaincases,themainobjectivesofthestudymightneedtobebrokendownintosub-objectiveswhichclearlystatethetaskstobeaccomplished.
Intheorganicfoodresearch,theobjectivesandsub-objectivesofthestudywereasfollows: 1. To study the existing organic market:Thiswouldinvolve:
• TocategorizetheorganicproductsavailableinDelhiintograin,snacks,herbs,pickles,squashesandfruitsandvegetables;
• Toestimatethedemandpatternofvariousproductsforeachoftheabovecategories;
• Tounderstandthemarketingstrategiesadoptedbydifferentplayersforpromotingandpropagatingorganicproducts.
2. Consumer diagnostic research: Thiswouldentail:• To studytheexistingconsumerprofile,i.e.,perceptionandattitudes
towardsorganicproductsandpurchaseandconsumptionpatterns;• Tostudythepotentialcustomersintermsofconsumersegments,
level of awareness, perception and attitude towards health andorganicproducts;
3. Opinion survey: To assess the awareness and opinions of expertssuchasdoctors,dieticiansandchefsinordertounderstandorganicconsumptionandpropagation;
4. Retail market: Thiswouldinvolve:• To findthegapbetweendemandandsupplyforexistingretailers;• Toforecastdemandestimatesbyconsideringtheexistingaswell
aspotentialretailers.Thus, the research problem formulation involves the following
interrelatedsteps: •Ascertainingtheobjectivesofthedecision-maker •Understandingtheproblem’sbackground
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• Identifyingandisolatingtheproblem,ratherthanitssymptoms •Determiningtheunitofanalysis •Determiningtherelevantvariables •Statingtheresearchobjectivesandresearchquestions(hypotheses).
Theabove-mentionedprocessensuresthattherealresearchobjectives/questionsareidentifiedfortheproposedresearch.
3.2.3 Statement of Research Problem and Cost and Value Information
Boththedecision-makersandresearchersexpectthattheproblemdefinitionefforts should result in a statement of the research problemor researchobjectives.On completion of the exercise of formulating the researchproblem,theresearchermustprepareawrittenstatement(s)thatclarifiesanyambiguityaboutwhats/hehopetheresearchwillaccomplish.Writingaseriesofresearchquestionsandhypothesescanaddclaritytothestatementofthebusinessproblem.Theseresearchquestionsaretheresearcher’stranslationofthebusinessproblemintoaspecificneedforinquiry;andhypothesisisanunprovenpropositionthattentativelyexplainscertainfactsorphenomena,apropositionthatisempiricallytestable.Inotherwords,researchobjectives/hypothesesexplainthepurposeofresearchinmeasurabletermsanddefinestandardswhattheresearchshouldaccomplish.
Values and Cost of Information
Thevalueandcostofinformationplayanessentialroleinestimatingtheimportanceofinformationaswellasthetotalexpenditurebedoneforbuyingtheinformation.
Value of information
Humanbeingshaveevolvedinawaythattheycanappreciatetheroleofinformation in their lifewithoutmucheffort.The initialphase inhumancivilization, has taught us to appreciate instinctively the importance ofinformationandcommunication.Weareinstinctivelyalerttoinformation.However,thehumanbrainhasevolvedtounderstandthatinformationhasdifferentdegreesof‘value’(whichthebrainunconsciouslyrates).Informationcanbedefinedasprocesseddata,whichhelps indecision-makingand/orfacilitatescommunicationwithinanorganization.Moreoften,informationprovidesanswersto‘who’,‘what’,‘where’,and‘when’typeofquestions.Thehumanbrainprioritizesinformation,accordingtoitsperceivedvalue(mostoftenthisunconsciousvaluationmechanisminourbrainiscorrect,moresointhecaseofinstinct-basedinformation).
For example, let us assume that a driver notices a child suddenlycrossingtheroadandcalculatesthathewillhitthechildunlesshestopsandatthesametime,hefeelsanitchingsensationonhisforehead.Inthiscase,
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Planning of Researchthebrainofthedriverprioritizestwodifferentinformationreceivedfromdifferentsensoryinputs.Itreactsbysendingasignaltothedriver’srightfoottopressthebrakepedaltostopthecarandonlyafterthecarstopswillthebrainreacttotheitch.Weunconsciouslydothiseveryday.Evolutionhastaughtusthatinformationhasacontextandhencedifferentdegreesofvalue.
Theprincipalobjectiveof research is tofindsolutions toproblemssystematically.Ingeneral,theobjectivesofvalueofinformationwithrespecttoresearchcanbespecifiedasfollows: •Toextendtheknowledgeofhumanbeings,environment,andnatural
phenomenontoothers. •Tobringtheinformationwhichisnotdevelopedfullyduringordinary
courseoflife? •Toverifyexistingfactsandidentifythechangesintotheseexisting
facts. •Todevelopfactsforcriticalevaluation. •Toanalyseinter-relationshipsbetweenvariablesandderivingcasual
explanations. •Todevelopnewtoolsandtechniquesthatstudyunknownphenomenon. •Tohelpinplanninganddevelopment. •Toacquirefamiliaritywithaphenomenon. •Tostudythefrequencyofconnectionorindependenceofanyactivity
or occurrence. •Todeterminethecharacteristicsofanindividualoragroupofactivities
andthefrequencyofoccurrenceoftheseactivities. •Totestahypothesisaboutacasualrelationship thatexistsbetween
variables.Thevalueofinformationisdeterminedbasedonthebenefitsthatare
derivedfromtheinformation.ConsideranexamplewheretwoproductsAandBaredeveloped.ThebenefitsderivedfromproductAevaluatesto20andthebenefitsderivedfromproductBevaluatesto30.Thedifferencebetweenthebenefitsofthetwoproductsis10units.
If you add some information, the benefits derived fromproductAincreasesby20pointsfrom20to40.Theactualvalueofinformationneedstobecalculatedfromsimplemathematics.Thecostofinformationincreasesby20units.Youneedtosubtractthecostinvolvedinobtainingtheinformation,todeterminetheactualvalueoftheinformation.
Cost of information
The cost of information determines the cost involved in obtaining theinformation,whichincludes:
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•Costofacquiringthedata. •Costofmaintainingthedata. •Costofgeneratingtheinformation. •Costofcommunicatingtheinformation.
Thecostisestimatedfromthepointtheinformationisgenerated,tothepoint the informationisretrieved.Thecostofobtainingaccurateandcompleteinformationismoreascomparedtothecostgenerallyretrievedfromthesystem.
3.3 REVIEW OF LITERATURE IN THE FIELD OF BUSINESS
Aliteraturereviewisthepresentation,classificationandevaluationofwhatotherresearchershavewrittenonaparticularsubject.Aliteraturereviewmayformpartofaresearchthesis,ormaystandaloneasaseparatedocument.Althoughthesecondofthesetypesofliteraturereviewislessextensivethanthatexpectedforathesis,theskillsrequiredareidentical.Aliteraturereviewisnotsimplyashoppinglistofwhatothershavesaid.Itdoesnotandcannotrefertoeverypieceofliteratureinthefield.Rather,aliteraturereviewisorganizedaccordingtoaparticularresearchobjective.Itisaconceptuallyorganizedsynthesiswhichultimatelyprovidesarationaleforfurtherresearch,whetherbyyouorbyothers.Thefewbasicpurposesthatabusinessliteratureshouldfulfilarethefollowing, •Compareandcontrastdifferentauthors’viewsonanissue •Groupauthorswhodrawsimilarconclusions •Criticizeaspectsofmethodology •Noteareasinwhichauthorsareindisagreement •Highlightexemplarystudies •Highlightgapsinresearch
Twoessentialelementsofallliteraturereviews(thoughtheyarenotformallyidentifiedassuch)are: 1.Anoutlineonwhatothershavedoneinyourchosenarea 2.Aprogressivenarrowingtothegapintheresearch
Economic management areas covered under literature review
Thevariouseconomicareascoveredunderliteraturereviewareasfollows: •Economicgrowthanddevelopment •Economicsoforganizationsandindustries
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Planning of Research • Econometrics • Economic policy •Economictheory •Environmentalandagriculturaleconomics •Financialeconomics •Gametheoryandmathematicalmethods •Historyofeconomicthought • Internationaleconomics •Lawandeconomics •Monetaryeconomics • Industrialorganization •Publicfinance •R&Dandtechnologypolicy •Regionalandsocialpolicy •Laboureconomics •Populationeconomics •Politicaleconomy • Development economics •Managerialeconomics •Financialpsychology •Economicgeography •Realestateeconomics •Energyeconomics •Greeneconomics •Computationaleconomics •Behaviouraleconomics • Socioeconomics
Business management areas covered under literature review
Thevariouseconomicareascoveredunderliteraturereviewareasfollows: •Accounting •Finance •Strategicmanagement •Educationalmanagement •Operationsmanagement
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•Productionmanagement •Humanresourcemanagement •Marketing •Organizationalanalysisandplanning •Policymakinganddecisionmaking •Ethicsinbusiness •Motivation •Globalization •Traininganddevelopment •Recruitmentandselection • Industrialrelations •Virtualtechnology •Changemanagement •Entrepreneurship •Organizationalbehaviour •Sustainablebusinesspractices •Totalqualitymanagement •Supplychain •Projectmanagement •Politicalbusinessstrategy • Innovationmanagement
Ina literature review, theworkofothers isused tocast thegap inrelief(thatis,tomakeitclear).Theresearchquestionandthesisstatementarethenstatedpreciselybeforetheremainderoftheresearchproject(referseeAppendixgivenattheendofthisunit).
Searchingforpapersincludedtwodatabaseswithawealthofbusinessliterature:ABI/ProQuestandEBSCOhostBusinessSourceComplete.Theseincludepeer-reviewed academic journals but also other sources, such asnewspapers,magazinesandtradepublications.
Check Your Progress
1.Whatareresearchproblems? 2.Whatisaliteraturereview? 3.Howisthevalueofinformationdetermined? 4.Listthreeeconomicareascoveredunderliteraturereview.
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Planning of Research3.4 ANSWERS TO CHECK YOUR PROGRESS
QUESTIONS
1.Researchproblemsarequestionsthatindicategapsinthescopeorthecertainityofourknowledge.
2.Aliteraturereviewisacomprehensivecompilationoftheinformationobtainedfrompublishedandunpublishedsourcesofdatainthespecificareaofinteresttotheresearcher.
3.Thevalueofinformationisdeterminedbasedonthebenefitsthatarederivedfromtheinformation.
4.Threeeconomicareascoveredunderliteraturereviewareasfollows:• Economicgrowthanddevelopment• Economicsoforganizationsandindustries• Econometrics
3.5 SUMMARY
•Problem discovery puts the research process into action andidentificationoftheproblemisthefirststeptowardsitssolution.
•Thesignificanceofaclearandwell-definedresearchproblemcannotbeoveremphasized,asanambiguousandgeneralissuedoesnotlenditselftoscientificenquiry.
•Aproblemdefinitionindicatesaspecificmanagerialdecisionareatobeclarifiedoraparticularproblemtobesolved.Itspecifiesresearchquestionstobeansweredandtheobjectivesoftheresearch.
•Another significant source forderiving the researchproblem is theindustryandorganizationaldata.
•Sometimes the expert interview, secondarydata andorganizationalinformationmightnotbeenoughtodefinetheproblem.Insuchacase,anexploratoryqualitativesurveymightberequiredtogetaninsightintothebehaviouralorperceptualaspectsoftheproblem.
•Oncetheauditprocessofsecondaryreviewandinterviewsandsurveyisover,theresearcherisreadytofocusanddefinetheissuesofconcern,thatneedtobeinvestigatedfurther,intheformofanunambiguousandclearly-definedresearchproblem.
•Basedontheframeworkofthestudy,theresearcherhastonumericallylistthethrustareasofresearch.
•Thecostofinformationdeterminesthecostinvolvedinobtainingtheinformation.
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•Aliteraturereviewmayformpartofaresearchthesis,ormaystandaloneasaseparatedocument.Althoughthesecondofthesetypesofliteraturereviewislessextensivethanthatexpectedforathesis,theskillsrequiredareidentical.
•Thevariouseconomicareascoveredunder literature reviewareasfollows:o Accountingo Financeo Strategicmanagement
3.6 KEY WORDS
• Research Problem: It is a statement about an area of concern, aconditiontobeimproved,adifficultytobeeliminated,oratroublingquestion that exists in scholarly literature, in theory, or in practicethatpointstotheneedformeaningfulunderstandinganddeliberateinvestigation.
• Research Objectives:Theyrefertothedescriptionofwhatistobeachievedbythestudy.
• Audit:Itmeansanofficialinspectionofanorganization’saccounts,typicallybyanindependentbody.
• Hypothesis:Itreferstoasuppositionorproposedexplanationmadeonthebasisoflimitedevidenceasastartingpointforfurtherinvestigation.
• Thesis:Itisastatementortheorythatisputforwardasapremisetobemaintainedorproved.
3.7 SELF ASSESSMENT QUESTIONS AND EXERCISES
Short Answer Questions
1. Howdoestheresearcherdefinetheresearchproblem? 2.Whatdoesaliteraturereviewinclude? 3.Listtheeconomicareascoveredunderliteraturereview.
Long Answer Questions
1. Examine how the research problem is identified, selected andformulated.
2.Discussreviewofliteratureinbusiness. 3.Describehowresearchobjectivesareidentified.
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Planning of Research3.8 FURTHER READINGS
Creswell,JohnW.2002.Research Design: Qualitative, Quantitative, and Mixed Methods Approaches.London:SagePublicationsInc.
Booth,Wayne,GregoryG.ColombandJosephM.Williams.1995.The Craft of Research.Chicago:UniversityofChicagoPress.
Bryman,AlanandEmmaBell.2015.Business Research Methods.4thEdition.UnitedKingdom:OxfordUniversityPress.
Gupta,S.L.andHiteshGupta. 2012. Business Research Methods. NewDelhi: TataMcGrawHillEducationPrivateLimited.
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UNIT 4 ECONOMIC MANAGEMENTStructure 4.0 Introduction 4.1 Objectives 4.2 UseinIdentifyingResearchGapsandTechniques 4.3 Hypothesis:Meaning,Sources,TypesofHypothesis,andHypothesisTesting 4.4 ResearchDesign
4.4.1 FactorsAffectingResearchDesign 4.4.2 EvaluationofResearchDesign
4.5 AnswerstoCheckYourProgressQuestions 4.6 Summary 4.7 Key Words 4.8 SelfAssessmentQuestionsandExercises 4.9 FurtherReadings
4.0 INTRODUCTION
In thisunit, youwill learnabout economicmanagementandhypothesis.AccordingtoTheodorson,‘ahypothesisisatentativestatementassertingarelationshipbetweencertainfacts.’Kerlingerdescribesitas‘aconjecturalstatementoftherelationshipbetweentwoormorevariables’.Hypothesisismoreusefulwhen stated in precise and clearly defined terms.Agoodhypothesisimpliesthathypothesiswhichfulfilsitsintendedpurposesandisuptothemark.Theunitwillgoontodiscussresearchdesign.
Ithasbeenfoundbyresearchscholarsandmanagersalikethatmostresearchstudiesdonotresultinanysignificantfindingsbecauseofafaultyresearchdesign.Mostresearchersfeelthatoncetheproblemisdefinedandhypothesesaremade,onecangoaheadandcollectthedataonaspecifiedgroup,orsample,andthenanalyseitusingstatisticaltests.However,unlesstheformulatedresearchproblemandthestudyhypothesesistestedthroughawell-definedplan,answersaregoingtobebasedonhitandtrialratherthananysoundlogic.
Thedesignapproachesavailabletotheresearcheraremanyandwilldependonwhether the study is of descriptive or conclusive nature.Thedesigns range from very simple, loosely structured to highly scientificexperimentation.Justasexperimentsinscience,inbusinessresearchalsotherearechancesoferrorandthisneedstobeunderstoodandcontrolledformoreaccurateresultsforthedecision-maker.
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Economic Management4.1 OBJECTIVES
Aftergoingthroughthisunityouwillbeableto: •Discussresearchgaps •Describethedifferenttypesofhypothesistesting •Explainthevariousstepsinaresearchdesign
4.2 USE IN IDENTIFYING RESEARCH GAPS AND TECHNIQUES
Whenaresearcherisworkingonoriginalresearch,hewouldliketoidentifyaneedforhisresearchsomewhereclosetothebeginningofhispaper.Whyisitso?Becausehewouldliketoshowthereaderthatheisnotduplicatingexistingresearch.Hedoesthisbysurveyingthecurrentresearchandthenidentifyingagapthatheisgoingtofill.Theresearcheridentifiesthebroadproblemandstatesitsimportance.Healsostateswhatissignificantinwhathas alreadybeenwritten.Hedescribes thegapheproposes tofill in theexistingresearchliterature.Thisthencreatesanopportunityforhimtomakeacontributiontotheresearchinthearea.
Thus,theprocessofdevelopingaresearchproposalisultimatelyoneofestablishingagapincurrentresearchwhichtheresearcheraimstoaddress.Asaresult,thefunctionoftheresearcher’sresearchproposalandtheliteraturereviewchapterofhisthesisistoconvince theaudiencethatthisresearchgapdoesexist,andthathisresearchisvalidandsignificant.Theprincipleaimoftheresearcheristoassessthegapsinresearchwithrespecttohisareaofresearch,reviewcurrentworkbeingcarriedoutinrelationtothesegaps,andrecommendthemostfruitfulareasforhis.
Thecharacteristicsofresearchgapmaybesummarizedasfollows:• Itiswhatmakestheresearcher’smanuscriptpublishable.• Itisthemissingelementintheexistingresearchliterature.• Itisthegapthattheresearcherwillfillwithhisresearchapproach.
4.3 HYPOTHESIS: MEANING, SOURCES, TYPES OF HYPOTHESIS, AND HYPOTHESIS TESTING
Theterm‘hypothesis’isderivedfromtheancientGreektermhypotithenai whichmeanstoputunderortosuppose.Thereareseveralcharacteristicsofhypotheses,whichareasfollows:
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• Clear and accurate:Ahypothesisshouldbeclearandaccuratetobeabletodrawaconsistentconclusion.
• Statement of relationship between variables: If a hypothesisis relational, it should state the relationship between the differentvariables.
• Testability:A hypothesis should be open to testing so that otherdeductionscanbemadefromitandcanbeconfirmedordisprovedbyobservation.Theresearchershoulddosomepriorstudytomakethehypothesistestable.
• Specific with limited scope:Ahypothesiswhichisspecificwithlimitedscopeismoreeasilytestablethanahypothesiswithlimitlessscope.Therefore,aresearchershouldspendmoretimetoconductresearchonsuchakindofhypothesis.
• Simplicity: Ahypothesisshouldbestatedinthemostsimpleandcleartermstomakeitunderstandable.
• Consistency: Ahypothesis should be reliable and consistentwithestablishedfacts.
• Time limit: Ahypothesisshouldbecapableofbeing testedwithinareasonabletime.Inotherwords,theexcellenceofahypothesisisjudgedbythetimetakentocollectthedataneededforthetest.
• Empirical reference: Ahypothesisshouldexplainorsupportallthesufficientfactsneededtounderstandwhattheproblemisallabout.
Hypothesis Testing: Parametric and Non-Parametric Tests
Hypothesis testingmeans to determinewhether or not the hypothesis isappropriate.This involveseitheracceptingorrejectinganullhypothesis.Theresearcherhastopursuecertainactivitiescontainedintheprocedureofhypothesis.
Hypotheses: Null and Alternative
A hypothesisisanapproximateassumptionthataresearcherwantstotestforitslogicalorempiricalconsequences.Ahypothesisreferstoaprovisionalideawhosemeritneedsevaluation,buthasnospecificmeaning.Itisoftenreferredtoasaconvenientmathematicalapproachforsimplifyingacumbersomecalculations.Settingupandtestinghypothesesisanintegralartofstatisticalinference.Hypothesesareoftenstatementsaboutpopulationparameterslikevarianceandexpectedvalue.Duringthecourseofhypothesistesting,someinferencesabout thepopulation likemeanandproportionaremade.Anyusefulhypothesiswillenablepredictionsbyreasoning,includingdeductivereasoning.Ahypothesismightpredicttheoutcomeofanexperimentinalabsettinginvolvingtheobservationofaphenomenoninnature.Thus,a
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Economic Managementhypothesisisanexplanationofaphenomenonproposalsuggestingapossiblecorrelationbetweenmultiplephenomena.
Forthepurposeofdecision-making,ahypothesishastobeverifiedandthenacceptedorrejected.Thisisdonewiththehelpofobservations.Decision-makingplaysasignificantroleindifferentareassuchasmarketing,industryandmanagement.Testingastatisticalhypothesisonthebasisofasampleenablesustodecidewhetherthehypothesisshouldbeacceptedornot.Thesampledataenablesustoacceptorrejectthehypothesis.
Null Hypothesis and Alternative Hypothesis
Inthecontextofstatisticalanalysisandresearch,whilecomparinganytwomethods,thefollowingconceptsorassumptionsaretakenintoconsideration: • Null Hypothesis:Whilecomparingtwodifferentmethodsintermsof
theirsuperiority,whereintheassumptionisthatboththemethodsareequallygoodiscallednullhypothesis.ItisalsoknownasstatisticalhypothesisandissymbolizedasH0.
• Alternate Hypothesis:While comparing two differentmethodsregardingtheirsuperiority,wherein,statingaparticularmethodtobegoodorbadascomparedtotheotheroneiscalledalternatehypothesis.ItissymbolizedasH1.
Note 1:Atestprovidesevidence,ifany,againstahypothesis,usuallycalledanullhypothesis.Thetestcannotprovethehypothesistobecorrect.Itcangivesomeevidenceagainstit.
Thetestofhypothesisisaproceduretodecidewhethertoacceptorrejectahypothesis.Note 2: Theacceptanceofhypothesesimpliesthatifthereisnoevidencefromthesample,weshouldbelieveotherwise.
Therejectionofahypothesisleadsustoconcludethatitisfalse.Thiswayofputtingtheproblemisconvenientbecauseoftheuncertaintyinherentintheproblem.Inviewofthis,wemustalwaysbrieflystateahypothesisthatwe hope to reject. Ahypothesisstatedinthehopeofbeingrejectediscalledanull hypothesis andisdenotedbyH0.
IfH0 is rejected, itmay lead to the acceptance of an alternativehypothesisdenotedbyH1.
Totakeanexample,supposeanewfragrantsoapisintroducedinthemarket.ThenullhypothesisH0,whichmayberejected,isthatthenewsoapisnotbetterthananyexistingsoap.
Similarly,adiceissuspectedtoberolled.Rollthediceanumberoftimes to test.
BytheNullHypothesisH0,p=1/6forshowingsix.
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BytheAlternativeHypothesisH1,p ≠1/6.Ahypothesisisusuallyconsideredtheprincipalinstrumentinresearch.
Thebasicconceptsregardingthetestabilityofahypothesisarenowdiscussed.
Comparison of Null Hypothesis and Alternate Hypothesis
Followingare thepointsof comparisonbetween thenullhypothesis andalternatehypothesis: •Nullhypothesisisalwaysspecificwhilealternatehypothesisgivesan
approximatevalue. •Therejectionofnullhypothesisinvolvesgreatrisk,whichisnotthe
casewithalternatehypothesis. •Null hypothesis ismore frequently used in statistics than alternate
hypothesisbecauseitisspecificandisnotbasedonprobabilities.
Procedure for hypothesis testing
Theprocedureforhypothesistestingisasfollows: 1. Making formal statement: In thisstep, thenatureofahypothesis
isclearlystated,whichcouldbeeithernullhypothesisoralternatehypothesis. Stating a problem in hypothesis testing is of utmostimportance,whichshouldbedonewithpropercare,keepinginmindtheobjectandnatureoftheproblem.
2. Choosing a significance level: Inthisstep, ahypothesisistestedonthebasisofapresentsignificancelevel,whichhastobeadequateintermsofnatureandpurposeoftheproblem.
3. Sampling distribution: In this step, determining an appropriatesamplingdistributionandmakingachoicebetweennormaldistributionandt-distributionareincluded.
4. Random selection of a sample: In this step, a random sample isselectedfromthesampledatafordetermininganaptvalue.
5. Probability calculation: Inthisstep,theprobabilityregardingviabilityofthesampleresultismadedependentonthenullhypothesis.
6. Comparison:Inthisstep,thecalculatedprobabilityandthevalueofalphaincaseofone-tailedtestandalpha/2incaseoftwo-tailedtestiscompared.
Check Your Progress
1.Whatistheprocessofdevelopingaresearchproposal? 2.Whatisnullhypothesis?
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Economic Management4.4 RESEARCH DESIGN
Researchdesignisastructurethatgivesanoutlineoftheoverallresearchwork.Itistheresultofbetterplanningandimplementationofagoodstrategy.Different authors have given different definitions of a research design.AccordingtoKerlinger,researchdesignistheplan,structureandstrategyofinvestigationconceivedsoastoobtainanswerstoresearchquestionsandtocontrolvariance.BernardPhillipsdefinesresearchdesignastheblueprintforcollection,measurementandanalysisofdata.
Greenet al.(2008)definesresearchdesignsas‘thespecificationofmethods and procedures for acquiring the information needed. It is theoveralloperationalpatternorframeworkoftheprojectthatstipulateswhatinformationistobecollectedfromwhichsourcesbywhatprocedures.Ifitisagooddesign,itwillinsurethattheinformationobtainedisrelevanttotheresearchquestionsandthatitwascollectedbyobjectiveandeconomicalprocedures.’
Thedecisions thatyouneed to take to formulatea researchdesignshouldbebasedonthefollowingquestions: •Whatistheresearchallabout? •Whyistheresearchbeingdone? •Whatkindofdataisrequiredfortheresearch? •Fromwherecanthedatabeobtained? •Howmuchtimewilltheresearchtake? •Whatisasampleresearchdesign? •Howshouldthedatabeanalysed? •Whatisthestyleofreportpreparation?
A research design helps a researcher to organize ideas and checkforflawsandinadequaciesinthecollecteddata.Itinvolvesthefollowingelements: •Astatementthatclearlydefinestheproblemforwhichtheresearchis
beingdone •Proceduresandtechniquesforgatheringtheinformationrequiredfor
researchdesign •Methodsthatneedtobeimplementedforprocessingandanalysingthe
datarequiredforresearchdesignTheoverallresearchdesigncanbedividedintothefollowingfourparts: • Sampling part:Itincludesthemethodofselectingitemsthatareto
beobservedfortheresearchstudy.
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• Observational part:Itincludestheconditionsunderwhichyouneedtomakeobservations.
• Statistical part:Itisbasedonthenumberofitemsthatneedtobeobserved and the analysis technique to be used for the analysis ofgathereddata.
• Operational part:Itinvolvesthetechniquesthathelptoimplementtheitemsspecifiedinthesampling,statisticalandobservationaldesigns.
Need for research design
Before starting the research process, the formulationof an efficient andappropriateresearchdesignisimportant.Aresearchdesignissignificantasithasthefollowingadvantages: • Ithelpsinthesmoothfunctioningofvariousresearchoperations. • Itrequireslesseffort,timeandmoney. • Ithelpstodecidethemethodsandtechniquestobeusedforcollecting
andanalysingdata.Theresearcherneedstoconsiderthefollowingfactorsbeforecreating
aresearchdesign: •Sourceoftheinformation •Skillsoftheresearcherandhiscoordinatingstaff •Problemobjectives •Natureoftheproblem •Availabilityoftimeandmoneyfortheresearchwork
Features of a good research design
Agoodresearchdesignischaracterizedbyflexibility,efficiencyandlowcost,butithasmanyotherfeaturestoo.Onthebasisofthedescriptionofthedesign,aresearchdesignhasthefollowingfeatures: • Itstatesthesourcesandtypesofinformationrequiredforsolvingthe
problemforwhichtheresearchisbeingcarriedout. • Itisastrategyforindicatingtheapproachtobeadoptedforgathering
andanalysingdata. • It includesperformingresearchworkaccordingtotimeandbudget
constraints. • Itminimizespreconceptionandmaximizesthereliabilityofcollected
andanalyseddata. • Itminimizesexperimentalerrorsinaninvestigation. • Itprovidesvariousaspectsfordealingwithaproblem.
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Economic ManagementAresearchdesigndependstoalargeextentonthetypeofresearchstudythatyouareconducting.Iftheresearchstudyisexploratory,thenmajoremphasisisonthediscoveryofideas.So,aresearchdesignshouldbeflexibleto implement thedifferentaspectsofaphenomenon.However,when thepurposeistoobtainanaccuratedescriptionofaresearchstudy,thedesignthatmaximizesreliabilityofthecollecteddataisconsideredagooddesign.Theavailabilityoftime,money,skillsoftheresearchstaffandthemethodofobtaining informationmustbeconsideredwhilecreatingexperimentaldesign,surveydesignandsampledesign.
Steps in research design
Thestepsinaresearchdesignprimarilydependonthetypeofresearchbeingconducted.Thestepsinvolvedinaresearchprocessareasfollows: 1.Preparingtheresearchquestionorproblem 2.Assessingtheavailableliterature 3.Creatinghypotheses 4.Constructingtheresearchdesign 5.Collectingdata 6.Analysingthedata 7. Interpretingtheresults 8.Writingtheresearchreport
Thefourthstep,i.e.,constructingtheresearchdesign,involvesthreesubordinatesteps,whichincludetheprocessofcreatingaresearchdesign.Thethreesubordinatestepscanfurtherbeexplainedasfollows: (i) Identifying variables:This involves identifying the variables to
bestudiedanddeterminingtheirtypes.Themostcommontypesofvariablesaredependent,independent,controlledandothervariables.Dependent variables are items such as responses of subjects andoutcomesofsurveyorcriterionvariables.Independentvariables,ontheotherhand,arethose,whichareexplanatoryorpredictorvariables.
(ii) Formulating functional definitions:Here,theresearcherexploresthepossibilitiesandthewaysinwhichthevariablescanbeoperationalized.
(iii) Selecting design for data analysis:Thisisthepreliminarystepofdatacollection,andhence,involvesdeterminationofwhatdesignoptiontochooseforanalysingthedatabeingcollected.
Types of Research Design
Severalresearchdesignsareclassifiedonthebasisofthestudyperformedintheresearch.Theseresearchdesignscanbelistedasfollows:
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•Researchdesigninexploratoryresearchstudies •Researchdesignindescriptivestudies •Researchdesigninquantitativestudies •Researchdesigninqualitativestudies •Researchdesigninexperimentalresearchstudies
1. Exploratory Research Design
Exploratoryresearchdesignisalsoknownasformulativeresearchdesign.Inthisresearchdesign,aspecificsubjectisinvestigated.Ithelpstogenerateasetofhypothesesorresearch-basedquestionsthatcanbeusedatalaterstage.Thethreemethodsthatareappliedforexplorativeresearchstudiesareasfollows: • Surveying the literature:Itisthesimplestmethodforformulating
the researchproblem inwhich alongwith new literature, previoushypothesesarereviewedandevaluatedforfutureresearch.
• Experience survey:Itisatypeofresearchthatinvolvespracticallyexperiencedpersonsintheresearchwork.Forsuchasurvey,peoplewithmoreinnovativeideasarecarefullyselectedasrespondentsandthen the investigators interview the respondents.Thus, experiencesurveyenablestheresearchertoconciselydefinetheproblem.Thissurveyalsoprovidesinformationaboutthepracticalpossibilitiesfordifferentresearchworks.
• Analysis of insight-stimulating examples:Itincludesanintensivestudyofselectedinstancesofaphenomenon.Inthismethod,theattitudeoftheinvestigator,intensityofstudyandabilityoftheresearcherarerequiredtounifythediverseinformationoftheproblem.Thus,inexploratoryresearchstudy,theappliedmethodneedstobe
flexible,regardlessofthetypeofthemethod,sothatthedifferentaspectsoftheproblemcanbeconsidered.Inexploratoryresearchdesign,thefollowingconsiderationsarekeptinmind: •Asmallsamplesizeisused. •Datarequirementsareunclear. •Generalobjectivesareconsidered,ratherthanspecificobjectives. •Nodefinitesuggestionsaremadeafterresearchanalysis.
2. Descriptive Research Design
Adescriptive research studydescribes the characteristics of a particularproblemoran individualoragroup.Descriptivestudies includespecificpredictionsconcernedwith study, factsandcharacteristicsconcerninganindividual,agroupor situations.Mostof thesocial research isbasedon
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Economic Managementdescriptiveresearchstudies.Indescriptivestudies,thequestionsrelatedto‘what’,‘why’,‘where’and‘who’needtobeanswered.
Thefollowingstepsmustbefollowedwhiledesigningadescriptivestudy: 1. Formulating the objectives of the study:This step specifies the
objectives to ensure that the collected data is related to the study,otherwisetheresearchwillnotprovidethedesiredresult.
2. Designing the data collection methods:Thisstephelpstoselectthemethod,thatis,observation,questionnaires,intervieworexaminationofrecords,forcollectingthedata.
3. Processing and analysing the data:Thedatacollectedfortheresearchstudymustbeprocessedandanalysed.Thisincludesanalysingthedatacollectedthroughinterviewsandobservations,tabulatingthedataandperformingstatisticalcomputations.
4. Reporting the researched data:Forreportingthefindings,thelayoutshouldbewellplanned,andpresentedinasimpleandeffectivestyle.
Indescriptivestudies,thefollowingconsiderationsshouldbekeptinmind:• Thephenomenonunderstudyshouldbedescribed.• The datamay be related to the behavioural variables of the
respondent.• Therecommendationsaredefinite.• Theobjectivesshouldbespecific,datarequirementsshouldbeclear
andlargesamplesshouldbeused.Descriptiveresearchdesign requiresaclearspecificationof‘when’,
‘where’,‘who’,‘what’,‘why’,and‘how’oftheresearch.Itsmainpurposeistodescribethecharacteristicsorthefunction.Someoftheconditionsinwhichthisresearchcanberecommendedare:
• Tomakeaspecificforecast• Discoveryofassociationsamongvariables• Estimatesoftheproportionsofapopulationthathavesomespecific
characteristics.• Todescribethecharacteristicsofproduct,group,organizationor
market.Unlikeexploratoryresearch,thedescriptiveresearchdesignismarked
by a specific hypotheses, clear statement of the problem and detailedinformationneeds.Generally,descriptiveresearchfollowssurveys,panels,secondarydataanalysisandobservationmethodsandcanbeclassifiedintocross-sectionalandlongitudinalresearch.
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Cross-sectional research:Thisisthemostfrequentlyusedresearchdesigninbusinessresearchandinvolvesinformationcollectionfromagivensampleofpopulationelements,andthattooonlyonce.Theymaybeeithermultiplecross-sectionalorsinglecross-sectional.Insinglecross-sectionaldesigns,onlyonesampleofrespondents isdrawnfromthetargetpopulation,andtheinformationfromthissampleisobtainedonlyonce.Thisdesignisalsoreferredtoassamplesurveyresearchdesign.
Inmultiplecross-sectionaldesign,therearetwoormoresamplesofrespondents,andtheinformationfromeachofthesampleisobtainedonlyonce.Often,informationfromdifferentsamplesisobtainedatdifferenttimesoverlongintervals.Multiplecross-sectionaldesignsallowcomparisonsattheaggregatelevelbutnotattheindividualrespondentlevel.Becauseadifferentsampleistakeneachtime,asurveyisconducted,thereisnowaytocomparethemeasuresonanindividualrespondentacrosssurveys.Oneofthespecialinterest,multiplecross-sectionaldesigniscohortanalysis,whichconsistsofaseriesofsurveysconductedatappropriatetimeintervals,wherethecohortservesasthebasisunitofanalysis.Agroupofrespondentswhoexperiencethesameeventwithinthesametimeintervalisreferredtoasa‘cohort’.Longitudinal research design:Unlikecross-sectional researchdesign,afixedsample(s)ofpopulationelementsismeasuredrepeatedlyonthesamevariable. In otherwords, the sameobjects are studiedover time and thesamevariablesaremeasured.Incontrasttothecross-sectionaldesign,whichprovidesasnapshotofthevariablesofinterestatasinglepointintime,alongitudinalstudygivesaseriesofpicturesthatprovideanin-depthviewofthesituationandthechangesthathavetakenplaceovertime.Sometimes,thetermpanelisusedinterchangeablywiththetermlongitudinaldesign.Apanelconsistsofasampleofrespondentswhohaveagreedtogiveinformationatspecifiedintervalsoveranextendedperiod.Causal research design:Thisresearchdesignisusedtoobtaintheevidenceofcause-and-effect(causal)relationships.Likedescriptiveresearchdesign,causal research design also requires a plan and structure and ismoreappropriateforthefollowingpurposes: •Tounderstandcause(independent)variablesandeffect(dependent)
variablesofthephenomenon •Todeterminethenatureoftherelationshipbetweencauseandeffect
variablestomakepredictionsabouteffectIn this design, causal (independent) variables aremanipulated in a
relatively controlled environment, inwhich the other variables thatmayaffectthedependentvariablearecontrolledorcheckedasmuchaspossible.The effect of thismanipulation on one ormore dependent variables isthenmeasured to infer causality.Themainmethodof causal research isexperimentation.
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Economic Management3. Diagnostic/Conclusive Research Design
A conclusive research design ismore structured and formal than anexploratory research design. It is based on large representative samples,and the data obtained is subjected to quantitative analysis.The aim ofconclusive research is to examine specific relationships and test specifichypotheses.To achieve these objectives, the researcher needs to clearlyspecifytherequiredinformation.Inthisresearch,thefindingsareconsideredasconclusiveinnatureastheyareusedasinputsformanagerialdecision-making.Thetwocategoriesofconclusiveresearchdesignsaredescriptiveandcausal.Descriptiveresearchdesignscanfurtherbeeithercross-sectionalorlongitudinal.
4. Experimental Research Design
Experimentalresearchdesignisusuallyapplicablewhenwearedeterminingthecauseandeffectrelationshiporderivingthecauseandeffectinferencesinanyexperimentalresearchstudy.Experimentalresearchdesignisinstrumentalinansweringsomeoftheimportantpsychologicalquestionsthatarebasedontheconceptofwhatcauseswhat.
Theobjectiveofexperimentalresearchdesignistoestablishthecauseandeffectrelationshipbetweenvariables.Thefourtypesofvariablesrelatedtoexperimentalresearchdesignareasfollows: • Independent variables:Thesesignifyconditionsormeasuresinthe
experimentaldesignthatcanbechanged. • Dependent variables:Thesevariablescanbemeasuredandsignify
theeffectorresultintheexperimentaldesign. • Control variables:Theseremainconstantintheexperimentaldesign. • Random variables:Thesecanvarytheirvaluesindifferentconditions
intheexperimentaldesign.Therearemanyvariationsinexperimentaldesigns,whicharecreated
toachievedifferentresultsandresolvedifferentproblems.Wecandefinethesimplestformofexperimentaldesignbycreatingtwosimilargroups,whichareequivalenttoeachotherinallrespects,exceptforthefactthatonegroupwillreceivethetreatmentandanothergroupwillnotreceivethetreatment.Thegroupthatreceivesthetreatmentcanbetermedasthetreatmentgroupandthegroupthatdoesnotreceivethetreatmentcanbetermedasthecomparisonorcontrolgroup.
Theformationoftwosimilargroupsthatareequivalenttoeachotherisensuredbyrandomlyassigningpeopleorparticipantsintotwogroupsfromacommonpoolofpeopleorparticipants.Thesuccessoftheexperimentisbasedontheconceptofrandomassignmentofpeopleintotwogroups.However,astwopeoplecannotbeexactlysimilar,intheexperimentaldesign,wereferto
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theideaofprobabilityandsaythattwogroupsareprobabilisticallyequivalentorequivalentintheprobabilisticranges.
4.4.1 Factors Affecting Research Design
Someofthefactorsthataffectresearchdesignareasfollows: •Accessibilityofscientificinformation •Availabilityofsufficientdata,time,moneyandmanpower •Exposuretovarioussourcesofdata •Extentoftheproblemthatneedstoberesolvedwiththehelpofresearch • Supportofthetopmanagementofthecompanyororganization •Knowledge,skillsandabilityoftheresearcher
4.4.2 Evaluation of Research Design
Followingpointsneedtobeconsideredforevaluatingresearchdesign •Determiningthenatureoftheresearchthatneedstobeevaluated •Checkingtherelevanceandreliabilityofthesourcesthatarecitedin
theresearchproposal •Checkingwhethertheresearchdesignconformstothestandardsof
scientificresearch • Identifying whether the research design is semi-experimental,
experimental,descriptiveorcorrelational • Findingtheethicalproblemsthatmayariseintheresearchdesign •Reviewingexistingliteraturetofindoutifsimilarorsameresearch
hasbeendonebefore
Check Your Progress
3.HowdoesBernardPhillipsdefineresearchdesign? 4.Listthestepsintheresearchprocess. 5.Whatistheobjectiveofexperimentalresearchdesign? 6.Listtwofactorsthataffectresearchdesign.
4.5 ANSWERS TO CHECK YOUR PROGRESS QUESTIONS
1.Theprocessofdevelopinga researchproposal isultimatelyoneofestablishingagap incurrent researchwhich theresearcheraims toaddress.
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Economic Management 2.Whilecomparingtwodifferentmethodsintermsoftheirsuperiority,whereintheassumptionisthatboththemethodsareequallygoodiscallednullhypothesis.ItisalsoknownasstatisticalhypothesisandissymbolizedasH0.
3.BernardPhillipsdefinesresearchdesignastheblueprintforcollection,measurementandanalysisofdata.
4.Thestepsinvolvedinaresearchprocessareasfollows: (i)Preparingtheresearchquestionorproblem (ii)Assessingtheavailableliterature (iii)Creatinghypotheses (iv)Constructingtheresearchdesign (v)Collectingdata (vi)Analysingthedata (vii) Interpretingtheresults (viii)Writingtheresearchreport 5.Theobjectiveofexperimentalresearchdesignistoestablishthecause
andeffectrelationshipbetweenvariables. 6.Twofactorsthataffectresearchdesignareasfollows:
• Accessibilityofscientificinformation• Availabilityofsufficientdata,time,moneyandmanpower
4.6 SUMMARY
•Whenaresearcherisworkingonoriginalresearch,hewouldliketoidentifyaneedforhisresearchsomewhereclosetothebeginningofhispaper.
•Theresearcheridentifiesthebroadproblemandstatesitsimportance.Healsostateswhatissignificantinwhathasalreadybeenwritten.Hedescribesthegapheproposestofillintheexistingresearchliterature.
•The term ‘hypothesis’ is derived from the ancient Greek termhypotithenaiwhichmeanstoputunderortosuppose.
•Ahypothesisshouldbeopentotestingsothatotherdeductionscanbemadefromitandcanbeconfirmedordisprovedbyobservation.Theresearchershoulddosomepriorstudytomakethehypothesistestable.
•Ahypothesisreferstoaprovisionalideawhosemeritneedsevaluation,buthasnospecificmeaning.
•Therejectionofahypothesisleadsustoconcludethatitisfalse.Thiswayofputtingtheproblemisconvenientbecauseoftheuncertaintyinherentintheproblem.
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•Research design is a structure that gives an outline of the overallresearchwork.Itistheresultofbetterplanningandimplementationofagoodstrategy.
•Agoodresearchdesignischaracterizedbyflexibility,efficiencyandlowcost,butithasmanyotherfeaturestoo.
•Several research designs are classified on the basis of the studyperformed in the research.These research designs canbe listed asfollows:o Researchdesigninexploratoryresearchstudieso Researchdesignindescriptivestudieso Researchdesigninquantitativestudieso Researchdesigninqualitativestudieso Researchdesigninexperimentalresearchstudies
4.7 KEY WORDS
• Research Gap: It isaresearchquestionorproblemwhichhasnotbeenansweredappropriatelyoratallinagivenfieldofstudy.
• Random Selection: It refers to how sample members (studyparticipants)areselectedfromthepopulationforinclusioninthestudy.
• Sample Distribution: It is a probability distribution of a statisticobtained througha largenumberofsamplesdrawnfromaspecificpopulation.
• Research Design: It is the set ofmethods andprocedures used incollecting and analyzingmeasuresof thevariables specified in theresearchproblemresearch.
4.8 SELF ASSESSMENT QUESTIONS AND EXERCISES
Short Answer Questions
1. Whatarethecharacteristicsoftheresearchgap? 2. Discussthecharacteristicsofahypothesis. 3. Whatarethedifferentpartsoftheresearchdesign?
Long Answer Questions
1. Explainnullandalternativehypothesis. 2. Whatishypothesistesting?Discussitsprocedure. 3. Examinethevarioustypesofresearchdesign.
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Economic Management4.9 FURTHER READINGS
Creswell,JohnW.2002.Research Design: Qualitative, Quantitative, and Mixed Methods Approaches.London:SagePublicationsInc.
Booth,Wayne,GregoryG.ColombandJosephM.Williams.1995.The Craft of Research.Chicago:UniversityofChicagoPress.
Bryman,AlanandEmmaBell.2015.Business Research Methods.4thEdition.UnitedKingdom:OxfordUniversityPress.
Gupta,S.L.andHiteshGupta. 2012. Business Research Methods. NewDelhi: TataMcGrawHillEducationPrivateLimited.
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BLOCK - II
SAMPLING AND ITS TYPES
UNIT 5 VARIABLES CONSTRUCTION FOR HYPOTHESIS
Structure 5.0 Introduction 5.1 Objectives 5.2 ConstructingHypothesis
5.2.1 IdentifyingVariables 5.2.2 CharacteristicsandFunctions 5.2.3 TypesofHypotheses
5.3 SignificanceofResearchinSocialSciences 5.4 ScientificMethod:InductionandDeduction 5.5 AnswerstoCheckYourProgressQuestions 5.6 Summary 5.7 Key Words 5.8 SelfAssessmentQuestionsandExercises 5.9 FurtherReadings
5.0 INTRODUCTION
In thepreviousunit,youwere introduced tohypothesis. In thisunit, thediscussiononhypothesiswillcontinue.Youwilllearnabouthowtoconstructhypothesis.Ahypothesis is constructed after the preliminary research isconducted.Thehypothesisiswordedinsuchawaythatitcanbetestedintheexperiment(s)anditmustencompassbothindependentanddependentvariables.Theunitwillalsodiscussthesignificanceofresearchinthesocialsciencesandconceptsofinductionanddeduction.
5.1 OBJECTIVES
Aftergoingthroughthisunit,youwillbeableto: •Discussthedifferenttypesofvariables •Examineinductiveanddeductivereasoning •Describethefeaturesofagoodresearchstudy
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Variables Construction for Hypothesis5.2 CONSTRUCTING HYPOTHESIS
Letusbeginthediscussiononconstructingahypothesisbyexamininghowtoidentifyvariables.
5.2.1 Identifying Variables
Tocarryoutaninvestigation,itbecomesimperativetoconverttheconceptsandconstructstobestudiedintoempiricallytestableandobservablevariables.Avariable isgenerallyasymbol towhichweassignnumeralsorvalues.Avariablemaybedichotomousinnature,thatis,itcanpossessonlytwovaluessuchasmale–femaleorcustomer–non-customer.Valuesthatcanonlyfitintoprescribednumberofcategoriesarediscretevariables,forexample,occupationscanbe:Teacher(1),CivilServant(2),PrivateSectorProfessional(3)andSelf-employed(4).Therearestillothersthatpossessanindefiniteset,e.g.,age,incomeandproductiondata.
Variablescanbefurtherclassifiedintofivecategories,dependingontheroletheyplayintheproblemunderconsideration. •Dependent variable: Themostimportantvariabletobestudiedand
analysedinresearchstudyisthedependentvariable(DV).Theentireresearch process is involved in either describing this variable orinvestigatingtheprobablecausesoftheobservedeffect.Thus,thisinessencehastobereducedtoameasurableandquantifiablevariable.Forexample,intheorganicfoodstudy,theconsumer’spurchaseintentionsandtheretailersstockingintentionsaswellassalesoforganicfoodproducts in the domesticmarket, could all serve as the dependentvariable.
AfinancialresearchermightbeinterestedininvestigatingtheIndianconsumers’investmentbehaviour,posttherecentfinancialslowdown.Inanotherstudy,theHRheadatCognizantTechnologieswouldliketostudytheorganizationalcommitmentandturnoverintentionsofshortandlongtenureemployeesinthecompany.
Hence,ascanbeseenfromtheaboveexamples,itmightbepossiblethatinthesamestudytheremightbemorethanonedependentvariable.
• Independent variable: Anyvariablethatcanbestatedasinfluencingorimpactingthedependentvariableisreferredtoasanindependentvariable(IV).Moreoftenthannot,thetaskoftheresearchstudyistoestablishthecausalityoftherelationshipbetweentheindependentandthedependentvariable(s).Theproposedrelationsarethentestedthroughvariousresearchdesigns.In the organic food study, the consumers’ attitude towards healthy
lifestylecouldimpacttheirorganicpurchaseintention.Thus,attitudebecomes
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the independentandintentionthedependentvariable.Anotherresearchermightwant to assess the impact of job autonomyand role stress on theorganizationalcommitmentoftheemployees;herejobautonomyandrolestressareindependentvariables. •Moderating variables: Moderatingvariablesaretheonesthathavea
strongcontingenteffectontherelationshipbetweentheindependentanddependentvariables.Thesevariableshavetobeconsideredintheexpectedpatternofrelationshipastheymodifythedirectionaswellas themagnitudeof the independent–dependent association. In theorganicfoodstudy,thestrengthoftherelationbetweenattitudeandintentionmightbemodifiedbytheeducationandtheincomelevelofthebuyer.Here,educationandincomearethemoderatingvariables(MVs).In a consulting firm, themanagement is looking at the option of
introducingflexi-timeworkschedule.Thus,astudymightneedtobetakentoseewhethertherewillbeanincreaseinproductivityofeachindividualworker(DV)subsequenttotheintroductionofaflexi-time(IV)workschedule.
Inrealtimesituationsandactualworksettings,thispropositionmightneedtoberevisedtotakeintoaccountotherimpactingvariables.Thissecondindependentvariablemightneedtobeintroducedbecauseithasasignificantcontributiononthestatedrelationship.Thus,wemightliketomodifytheabovestatementasfollows:
Therewillbeanincreaseinproductivityofeachindividualworker(DV) subsequent to the introduction of aflexi-time (IV)work schedule,especiallyamongstwomenemployees(MV).
Theremight be instanceswhen confusionmight arise between amoderatingvariableandanindependentvariable.
Considerthefollowingsituation:• Proposition 1: Turnoverintention(DV)isaninversefunctionof
organizationalcommitment(IV),especiallyforworkerswhohaveahigherjobsatisfactionlevel(MV).
Whileanotherstudymighthavethefollowingpropositiontotest.• Proposition 2: Turnoverintention(DV)isaninversefunctionof
job satisfaction (IV), especially forworkerswhohave a higherorganizationalcommitment(MV).
Thus,thetwopropositionsarestudyingtherelationbetweenthesamethreevariables.Howeverthedecisiontoclassifyoneasindependentandtheotherasmoderatingdependsontheresearchinterestofthedecisionmaker.
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Variables Construction for Hypothesis
Tounderstandtheimpactandroleofthemoderatorvariableletusrepresenttherelationshipsgraphically(Figure5.1).Herearepresentstheeffectoftheindependentvariable(jobsatisfaction);brepresentstheeffectof the second variablemoderator variable (organizational commitment)andc represents themoderating effect,which is the combined effect ofthemoderating variable and the independent variable on the dependentvariable.Thus,theeffectofchastobelargeenoughandsignificantenough(statistically)toprovethemoderationhypotheses. • Intervening variables: Aninterveningvariable(IVV)hasatemporal
connotationtoit.Itgenerallyfollowstheoccurrenceoftheindependentvariableandprecedesthedependentvariable.Tuckman(1972)definesitas‘thatfactorwhichtheoreticallyaffectstheobservedphenomenabutcannotbeseen,measured,ormanipulated;itseffectsmustbeinferredfromtheeffectsoftheindependentvariableandmoderatorvariablesontheobservedphenomenon.’
Fig 5.1 Graphical representation of moderating variable: Proposition 2
Forexample,inthepreviouscase,Thereisanincreaseinjobsatisfaction(IVV)ofeachindividualworker,subsequenttotheintroductionofaflexi-time(IV)workschedule,whicheventuallyaffectstheIndividual’sproductivity(DV),especiallyamongstwomenemployees(MV).Anotherexamplewouldbe,theintroductionofanelectronicadvertisementforthenewdietdrink(IV)willresultinincreasedbrandawareness(IVV),whichinturnwillimpactthefirstquartersales(DV).Thiswouldbesignificantlyhigheramongsttheyoungerfemalepopulation(MV).
Fig 5.2 Graphical Representation of Mediating Variable
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Incurrentresearchterminology,theinterveningvariableisalsocalledamediatingvariable,asitmediatesthestrengthanddirectionoftherelationshipbetweentheindependentanddependentvariable(Figure5.2).Forexampleintheabovecase,thedirecteffectofthepredictorortheindependentvariableismeasuredbya; and themediating impactof themediatingvariable isrepresented by b.However, thepoint tobenoted is that the independentvariableactsonthemediatingvariableasrepresentedbyc.Thus,toproveamediatingrelationship,onewouldexpectthattheeffectofb would be more thantheeffectofaandthatthiscouldbeproventobesignificantlysignificant.Thebestcaseofmediationwouldbeifawaszeroorthepredictorhadnodirecteffectontheoutcomevariable.Theimpactofthemediatingvariableisassessedbythemethodofstructuralequationmodelling. • Extraneous variables: Besides themoderating and intervening
variables, theremight still exist a number of extraneous variables(EVs)which could affect the defined relationship butmight havebeenexcludedfromthestudy.Thesewouldmostoftenaccountforthechancevariationsobservedintheresearchinvestigation.Forexample,a tyrannical boss; family pressures or nature of the industry couldimpacttheflexi-timeimpact,butsincethesewouldbeapplicabletoindividualcases,theymightnotheavilyimpactthedirectionofthefindings.However,incasetheeffectissubstantial,theresearchermighttrytoblocktheireffectbyusinganexperimentalandacontrolgroup(Thisconceptwillbediscussedlaterinthesectiononexperimentaldesigns).At this stage, we can clearly distinguish between the different
kindsofvariablesdiscussedabove.Anindependentvariableis theprimeantecedent conditionwhich isqualifiedas explaining thevariance in thedependentvariable;theinterveningvariablefollowstheoccurrenceoftheindependentvariableandmay in turn impact thedependentvariable; themoderatingvariableisacontributingvariablewhichmightimpactthedefinedrelationship;theextraneousvariablesareoutsidethedomainofthestudyandresponsibleforchancevariations,butinsomeinstances,theireffectmightneed to be controlled.
5.2.2 Characteristics and Functions
Anyassumptionthattheresearchermakesontheprobabledirectionoftheresultsthatmightbeobtainedoncompletionoftheresearchprocessistermedasahypothesis.Unliketheresearchproblemthatgenerallytakesonaquestionform,thehypothesesisalwaysinadeclarativeform.Thestatementsthusformulatedcanlendthemselvestoempiricalenquiry.Kerlinger(1986)definesahypothesisas‘…aconjectualstatementoftherelationshipbetweentwoormorevariables.’AccordingtoGrinnell(1993),‘Ahypothesesiswrittenin
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suchawaythatitcanbeprovenordisprovenbyvalidandreliabledata—itisinordertoobtainthesedatathatweperformourstudy’.
While designing any hypotheses, there are a few criteria that theresearchermustfulfil.Theseare: •Ahypothesismustbeformulatedinsimple,clear,anddeclarativeform.
Abroadhypothesismightnotbeempiricallytestable.Thus,itmightbeadvisabletomakethehypothesisunidimensional,andtobetestingonlyonerelationshipbetweenonlytwovariablesatatime.o Consumerlikingfortheelectronicadvertisementforthenewdiet
drinkwillhavepositiveimpactonbrandawarenessofthedrink.o High organizational commitmentwill lead to lower turnover
intention. •Ahypothesismustbemeasurableandquantifiablesothatthestatistical
authenticityoftherelationshipcanbeestablished. •Ahypothesisisaconjectualstatementbasedontheexistingliterature
andtheoriesaboutthetopicandnotbasedonthegutfeelorsubjectivejudgementoftheresearcher.
•Thevalidationofthehypothesiswouldnecessarilyinvolvetestingthestatisticalsignificanceofthehypothesizedrelation.Forexample,theabovetwohypotheseswouldneedtousecorrelationandregressionanalysisrespectivelytotestthestatedrelationship.
5.2.3 Types of Hypotheses
Theformulatedhypothesiscouldbeoftwotypes: 1. Descriptive hypothesis: This is simply a statement about the
magnitude, trendor behaviour of a population under study.Basedonpastrecords,theresearchermakessomepresumptionsaboutthevariableunderstudy.Forexample:• Studentsfromthepuresciencebackgroundscore90–95percent
onacourseonQuantitativeMethods.• Thecurrentadvertisementforthedietdrinkwillhavea20–25per
centrecallrate.• TheattritionrateintheBPOsectorisalmost33percent.• TheliteracyrateinthecityofIndoreis100percent.
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Fig 5.3 Problem Identification Process
2. Relational hypothesis: Thesearethetypicalkindofhypotheseswhichstatetheexpectedrelationshipbetweentwovariables.Whilestatingtherelationiftheresearchermakesuseofwordssuchasincrease,decrease,less thanormore than, thehypothesis isstated tobedirectionalorone-tailedhypothesis.
Forexample,• Higherthelikeabilityoftheadvertisement,thehigheristherecall
rate.• HighertheworkexhaustionexperiencedbytheBPOprofessional,
higheristheturnoverintentionoftheperson. However, sometimes the researchermight not have reasonable
supportivedatatohypothesizetheexpecteddirectionoftherelationship.Inthiscase,heorshewouldleavethehypothesisasnon-directionalortwo-tailed.
Forexample,• There is a relation between quality ofworking life and job
satisfactionexperiencedbyemployees.• Banonsmokinghasanimpactonthecigarettesales.• Anxietyisrelatedtoperformance.
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Thehypothesesdiscussedinthissectionareinproseformandinaverbaldeclarativesentenceform.
Check Your Progress
1.Whatisavariable? 2.Whatisadescriptivehypothesis?
5.3 SIGNIFICANCE OF RESEARCH IN SOCIAL SCIENCES
Researchplaysanimportantroleinmanyapplicationareas.Someofthemareasfollows: • Finance, budgeting and investments:This includes the following
activities:o Cash flow analysis, long-range capital requirements analysis,
investmentpoliciesanddividendpoliciescreationo Creationofcreditpolicies,creditrisksandaccountproceduressuch
asdepositsandwithdrawals • Purchasing, procurement and exploration: This includes the
followingactivities:o Determiningthequantityandtimeofpurchaseofrawmaterials,
machineryandthelike.o Definingtherulesforbuyingandsupplyingproductsundervarying
priceso Determining thequantitiesand timingsofpurchasesoffinished
productso Formulating strategies for exploration and exploitation of new
materialsources • Production management:This includes physical distribution of
products,facilityplanningandmanufacturingplanning.o Physical distribution: It is further divided into the following
elements: –Locationandsizeofthewarehouses,distributioncentres,retail
outletsandsoon. –Distributionpolicy
o Facility planning:Itisfurtherdividedintothefollowingelements: –Productionschedulingandsequencingofavailableresources
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–Projectschedulingandallocationofresources –Determiningtheoptimumproductionmix
o Manufacturing planning:Itisfurtherdividedintomaintenancepoliciesandpreventivemaintenance
• Research and development:Itincludesthefollowingactivities:o Determiningtheareasofconcentrationofresearchanddevelopmento Reliabilityandevaluationofalternativedesignsofresearchand
developmento Controlofdevelopedprojectso Coordinationofmultipleresearchprojectso Determiningthetimeandcostrequirements
5.4 SCIENTIFIC METHOD: INDUCTION AND DEDUCTION
Goodbusinessresearchisbasedonsoundreasoningsuchasfindingpremisesthatarecorrect,testingtheconnectionsbetweentheirassumptionsandfacts,makingclaimsthatarebasedonadequateevidence.Inthereasoningprocess,inductionanddeduction,observationandhypothesistestingcanbecombinedinasystematicwayforproducingscientificresults.Scientificmethodsarepractised inbusiness research toguideourapproach toproblemsolving.Someoftheessentialtenetsofthescientificmethodsare: •Observationofphenomena •Clearly-definedprocedures,methodsandvariables •Empiricallytestablehypotheses •Abilitytoruleoutrivalhypotheses •Statisticaljustificationofconclusions •Theself-correctingprocess
Theresearcherusingthisapproachof‘empiricism’attemptstodescribe,explainandmakeapplicationsbyrelyingontheinformationgainedthroughobservation.Clearly, reasoning is pivotal tomuch of the researcher’ssuccess,whichcanbeconveyedthroughoneofthetwotypesofdiscourse:exposition or argument.Exposition consists of statements that describewithout attempting to explain.Argument allowsus to defend, challenge,explain,interpretandexploremeaning.Thetwotypesofargumentthatareofgreatimportancetoresearchare:deductivethoughtandinductivethought.
Thesecondconcerninformulatingbusinessresearchproblemsisthefact thatmoreoftenthannot,managersbecomeawareofproblems,seekinformationandarriveatdecisionsunderconditionsofbondedrationality.A
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conceptformalizedbyMarchandSimon(1958)whichimpliesthatmanagersdonotalwaysworkandtakedecisionsinaperfectlyrationalsequence.Themodelsaysthatinformationsearchorproblemrecognitionphaselikeanyotherbehaviourhastobemotivated.Unlessthemanagerisdrivenbypresentlevelsofdissatisfactionorbyhighexpectedvalueofoutcomes,theprocessdoesnotstart.Thenextimplicationofthemodelisthatinmostinstances,amanagerdoesnothaveaccesstocompleteandperfectinformation.Andfurther, themanagermight try to seek reasonably convenient and quickinformationthatmeetsminimalratherthanoptimalstandards.
Deductive thought
Deductivethought,alsocalleddeductivelogic,istheprocessofreasoningfromoneormoregeneralstatementsregardingwhatisknowntoreachalogicallycertainconclusion.Itinvolvesusinggiventruepremisestoreachaconclusionthatisalsotrue.Underdeductivelogic,aspecificconclusionisarrivedatfromageneralprinciple.Iftherulesandlogicofdeductionarefollowed,thisprocedureensuresanaccurateconclusion.Deductiveargumentsareevaluatedintermsoftheirvalidityandsoundness.Deductivelogicorreasoningisusuallyconsideredtobeaskillthatdevelopswithoutanyformalteachingortraining.
Usingdeductive reasoning, researchers comeupwith a conclusionbasedonfactsthathavealreadybeenshowntobetrue.Hence,theirconclusionisalwaystrue.Thefactstheyusetoprovetheirconclusiondeductivelymaycomefromaccepteddefinitions,postulatesoraxioms,orpreviouslyprovedtheorems.
Thiskindoflogicisaculmination,aconclusionoraninferencedrawnasaconsequenceofcertainreasonedfacts.Thereasonscitedhavetoberealandnotafigmentoftheresearcher’sjudgementandsecond,thedeductionsorconclusionsmustessentiallybeanoutcomeofthesamereasons.
Unlessallprobablereasonshavebeenisolatedandidentified,thenatureoftheinferenceisincomplete.
Inductive thought
Ontheotherendofthecontinuumisinductivethought.Herethereisnostrongandabsolutecauseandeffectbetweenthereasonsstatedandtheinferencedrawn.Inductivereasoningcallsforgeneratingaconclusionthatisbeyondthefactsorinformationstated.
Inductivethought,alsoknownasinductivelogicorinductivereasoning,constructsorevaluatespropositionsthatareabstractionsofobservationsofindividualinstances.Ininductivereasoning,ageneralconclusionisarrivedatbyspecificexamples.Inductivelogicistheprocessofcomingupwithaconclusionbasedonaseriesofeventsthatrepeat.Anexamplewouldbeto
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pushalightswitchupturnsonthelightandpushingitdownturnsthelightoff.Ifthisisdoneagainandagain,say100times,itmaybeconcludedthatthelightgoesonwhentheswitchisupanditisoffwhentheswitchisdown.However,theconclusionmaynotalwaysbetruebecauseothercircumstancesmaycausethelighttonotgoonwhentheswitchisup,suchasthelightmayburnout,theelectricitymaygooff,etc.
Thus,thefactofthematteristhatinductivethoughtdrawsassumptionsandhypothesiswhichcouldexplainthephenomenaobservedandyettherecouldbeotherpropositionswhichmightexplaintheeventaswellas theonegeneratedbythemanager/researcher.Eachoneofthemhasapotentialtruthinit.However,wehavemoreconfidenceinsomeovertheothers,soweselectthemandseekfurtherinformationinordertogetconfirmation.
Inpractice, scientific thought actuallymakesuseofboth inductiveanddeductivereasoning inachronologicalorder.Wemightquestion thephenomenabyaninductivehypothesisandthencollectmorefactsandreasonstodeductthatthehypothesizedconclusioniscorrect.
Features of a Good Research Study
Intheabovesectionwelearntthatonemethodofarrivingatsolutionstoourprofessionaldilemmasisthroughresearch.Thismethodofenquiry,wewillsubsequentlylearncanvaryfromthelooselystructuredmethodbasedonobservationsand impressions to thestrictlyscientificandquantifiablemethods.However,whateverbethemethodofenquiry,itmustadheretocertainhistoricallyestablishedcriteria tobe termedasbusiness research.Foraresearchtobeofvalueandtoauthenticateorcontributetothebodyofknowledge,wefeelthatitmustpossessthefollowingcharacteristics: (a) Itmusthaveaclearlystatedpurposethatisimplicitaswhenthepurpose
istodevelopanewsystemofinventorymanagementorexplicittoestablishqualitystandardsfortheservicedeliverymodelinourmobileeyecareunit. Thisnotonlyreferstotheobjectiveofthestudy,butalsoprecisedefinitionofthescopeanddomainofthestudy.Thevariablesandconstructs thatarebeinginvestigated—servicedeliverymodel,qualitystandards,inventorymanagement—needtobedefinedinclearandpreciseterms.
(b) Itmust follow a systematic and detailed plan for investigatingthe research problem.The source fromwhich information is to becollectedaboutqualitystandardsinventorymodelshastobelisted.Incasethedataistobecollectedfromasampleofsuppliers,retailersandpathologists for investigating thegaps in thecurrent inventorymodel,thedetailingofhowrepresentativenessofthesampletothetotalpopulationistobeensuredalongwithestimatederrorhastobespecified.Thesystematicconductionalsorequiresthatallthestepsintheresearchprocessareinterlinkedandsequentialinnature.
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(c)The selection of techniques of collecting information, samplingplans anddata analysis techniquesmust be supportedby a logicaljustification.Incaseyouareselectingasecondarydatasourceonlyorgoingforanonlinesurvey,orratherthangoingtopathologistsgoingtotheENTspecialistsforyourhearingaidstudy,thereasonfordoingso,alongwithacleardemonstrablelinktotheresearchpurposeisanabsolutemust.
(d)Theresultsofthestudymustbepresentedinanunbiased, objective and neutral manner.Thesignificantfindingscan,atbest,besupportedbypastresearches,researchapproachandlimitation,orbyexpertopinion.Theresearchers’ownjudgementsandbiasesshouldnotberevealedat any cost, evenwhen the scope of the studydemands providingrecommendations.
(e)Theresearchthatyouundertakecanneverbefruitfulifitcornersorifitexploitstherightsoftherespondents.Thus,theresearchateverystageandatanycostmustmaintainthehighest ethical standards. For example,forthehearingaidsstudy,ifthroughthesurveyweidentifythepivotalinfluenceofthepathologistinthehearingaidpurchasedecision;thepathologistscouldbegivenacommissionforbadmouthingthecompetitor’sproductstosteerthecustomerstowardsourproductevenwhenthereisadelayindelivery,thusimprovingourprofitswithoutanymajorchangesimplementedinthefaultyinventoryreporting.Butthiswouldbeunethical.
(f)Andlastly,thereasonforastructured,ethical,justifiableandobjectiveapproachisthefactthattheresearchcarriedoutbyusmustbereplicable. Thismeansthattheprocessfollowedbyusmustbe‘reliable’,i.e.,incasethestudyiscarriedoutundersimilarconstraintsandconditionsitshouldbeabletorevealsimilarresults.
Check Your Progress
3.Whatdoesproductionmanagementinclude? 4.Whatdoesexpositionconsistof? 5.Howshouldtheresultsofthestudybepresented?
5.5 ANSWERS TO CHECK YOUR PROGRESS QUESTIONS
1.Avariableisgenerallyasymboltowhichweassignnumeralsorvalues. 2.Descriptivehypothesis is simply a statement about themagnitude,
trendorbehaviourofapopulationunderstudy.
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3.Productionmanagement includesphysical distributionof products,facilityplanningandmanufacturingplanning.
4.Expositionconsistsofstatementsthatdescribewithoutattemptingtoexplain.
5.Theresultsofthestudymustbepresentedinanunbiased,objectiveandneutralmanner.
5.6 SUMMARY
•Tocarryoutan investigation, itbecomes imperative toconvert theconcepts andconstructs tobe studied into empirically testable andobservablevariables.
•Avariablemaybedichotomousinnature,thatis,itcanpossessonlytwovaluessuchasmale–femaleorcustomer–non-customer.
•Variablescanbefurtherclassifiedintofivecategories,dependingontheroletheyplayintheproblemunderconsideration.Theseinclude:o Dependentvariableo Independentvariableo Moderatingvariableso Interveningvariableso Extraneousvariables
•Anyassumptionthattheresearchermakesontheprobabledirectionof theresults thatmightbeobtainedoncompletionof theresearchprocessistermedasahypothesis.
•Unliketheresearchproblemthatgenerallytakesonaquestionform,thehypothesesisalwaysinadeclarativeform.Thestatementsthusformulatedcanlendthemselvestoempiricalenquiry.
•Ahypothesismustbemeasurableandquantifiablesothatthestatisticalauthenticityoftherelationshipcanbeestablished.
•Goodbusinessresearchisbasedonsoundreasoningsuchasfindingpremises that are correct, testing the connections between theirassumptions and facts,making claims that are based on adequateevidence.
•Scientificmethods are practised in business research to guide ourapproachtoproblemsolving.
•Argumentallowsustodefend,challenge,explain,interpretandexploremeaning.Thetwotypesofargumentthatareofgreatimportancetoresearchare:deductivethoughtandinductivethought.
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•Deductive thought, also called deductive logic, is the process ofreasoningfromoneormoregeneralstatementsregardingwhatisknowntoreachalogicallycertainconclusion.
•Ontheotherendofthecontinuumisinductivethought.Herethereisnostrongandabsolutecauseandeffectbetweenthereasonsstatedandtheinferencedrawn.
•Theresearchmusthaveaclearlystatedpurposethatisimplicitaswhenthepurposeistodevelopanewsystemofinventorymanagementorexplicittoestablishqualitystandardsfortheservicedeliverymodelinourmobileeyecareunit.
•Thereasonforastructured,ethical,justifiableandobjectiveapproachisthefactthattheresearchcarriedoutbyusmustbereplicable.Thismeansthattheprocessfollowedbyusmustbe‘reliable’,i.e.,incasethestudyiscarriedoutundersimilarconstraintsandconditionsitshouldbeabletorevealsimilarresults.
5.7 KEY WORDS
• Objective:Itreferstosomethingnotinfluencedbypersonalfeelingsoropinionsinconsideringandrepresentingfacts.
• Deductive Reasoning:Somethingthatischaracterizedbyorbasedontheinferenceofparticularinstancesfromagenerallaw.
• Inductive Reasoning:Itisamethodofreasoninginwhichthepremisesareviewedassupplyingsomeevidenceforthetruthoftheconclusion.Thetruthoftheconclusionofaninductiveargumentmaybeprobable,basedupontheevidencegiven.
• Proposition:Itisastatementorassertionthatexpressesajudgementor opinion.
5.8 SELF ASSESSMENT QUESTIONS AND EXERCISES
Short Answer Questions
1. Discussthesignificanceofresearchinthesocialsciences. 2.Whatisgoodbusinessresearchbasedon? 3.Listtheessentialtenetsofthescientificmethod. 4.Writeashort-noteoninductivereasoning.
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Long Answer Questions
1. Describethevariousclassificationofvariables. 2.Examinethedifferenttypesofhypothesis. 3.Explaininductiveanddeductivereasoningindetail. 4.Discussthefeaturesofagoodresearchstudy.
5.9 FURTHER READINGS
Creswell,JohnW.2002.Research Design: Qualitative, Quantitative, and Mixed Methods Approaches.London:SagePublicationsInc.
Booth,Wayne,GregoryG.ColombandJosephM.Williams.1995.The Craft of Research.Chicago:UniversityofChicagoPress.
Bryman,AlanandEmmaBell.2015.Business Research Methods.4thEdition.UnitedKingdom:OxfordUniversityPress.
Gupta,S.L.andHiteshGupta. 2012. Business Research Methods. NewDelhi: TataMcGrawHillEducationPrivateLimited.
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Sampling Design
UNIT 6 SAMPLING DESIGNStructure 6.0 Introduction 6.1 Objectives 6.2 MeaningofSamplingDesign
6.2.1 PrincipleofSamplingandEssentialsofGoodSampling 6.2.2 SamplingConceptsandSamplingFrame
6.3 CensusMethodandSamplingMethodforInvestigation 6.4 MethodsofSampling:Probability,Non-ProbabilityandMixedSampling
DesignorSystematicSampling 6.5 AnswerstoCheckYourProgressQuestions 6.6 Summary 6.7 Key Words 6.8 SelfAssessmentQuestionsandExercises 6.9 FurtherReadings
6.0 INTRODUCTION
Inthepreviousunit,youlearntabouttheconstructionofhypothesis.Inthisunit,wewillturntowardssamplingdesign.
While conducting a research, collecting a sample is of utmostimportance.However,simplycollectingasampleisnotenough.Thereisacertainplanforobtainingasamplefromthesamplingframe.Properplanninganddesigning isverymuchessential forcarryingoutasurvey.Thisunitfocusesontheimportanceofsampledesign;itsprinciples,essentialsofgoodsamplingandvariousmethodsinvolvedinaninvestigation.Samplingdesignreferstothetechniqueorprocedureadoptedbyaresearcherinselectingsomesamplesorsamplingunitsfromwhereinferencesaboutpopulationaredrawn.
6.1 OBJECTIVES
Aftergoingthroughthisunit,youwillbeableto: •Discusstheessentialsofgoodsampling •Evaluatetheneedforsampling •Analysethecensusmethodandsamplingmethod •Discussthedifferentmethodsofsampling
6.2 MEANING OF SAMPLING DESIGN
Samplingdesignreferstoadefiniteplanforobtainingasamplefromthesamplingframe.Itreferstothetechniqueorprocedure,whicharesearcher
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adopts in selecting some sampling units fromwhere inferences aboutpopulationaredrawn.Samplingdataisobtainedbeforecollectingthefinaldata.
Need for Sampling
Wecandefinesamplingastheprocessofobtaininginformationaboutanentirepopulationbyexaminingonlyapartofit.Samplingisrequiredforthefollowingreasons: • Itsavestimeandmoney.Asamplestudyisusuallylessexpensivethan
acensusstudy. • Itproducesresultsatafasterspeed. • It enablesmore accuratemeasurement for a sample study as it is
conductedbyexperiencedinvestigators. • Itistheonlymethodforaninfinitelylargepopulation. • It usually enables you to estimate sampling errors and thus assists
youinobtaininginformationconcerningsomecharacteristicsofthepopulationsuchasagegrouporgender.
Theadvantagesofsamplingareasfollows: •Thesolutiontoknowthetrueoractualvaluesofthevariousparameters
ofthepopulationwouldbetotakeintoaccounttheentirepopulation.This is not feasible due to the cost and time involved.Therefore,samplingseemsmoreeconomical.
•Asthemagnitudeofoperationinvolvedinasamplesurveyissmall,theexecutionofthefieldworkandtheanalysisofresultscanbecarriedoutatafasterrateandinalessertime.
•Onlyasmallstaffisrequiredforgatheringandanalysinginformationandpreparingreports.Therefore,samplingisaverycheapprocess.
•Aresearchercancollectdetailedinformationinalessertimethanispossibleinacensussurvey.
•Asthescaleofoperationinvolvedinasamplesurveyissmall, thequalityofinterviewssupervisionandotherrelatedactivitiesisbetterthanthecensussurvey.
• Samplingprovidesadequateinformationneededforthepurposeandissufficientlyreliableforsurveys.
Characteristics of Sampling
Usually, sampling involves determining a propertyor attribute to adheretoforthepurposeofdifferentiatingbetweenitemsofagivenpopulation.Theseattributes,whicharetheobjectsofstudy,arecalledcharacteristics.Theprocessofdistinguishingtheitemsisusuallyoftwotypes,quantitative
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Sampling Designorqualitative.Inquantitativesampling,characteristicspertainingtovariablesaredealtwith.Ontheotherhand,qualitativesamplingisconcernedwiththecharacteristicsrelatedtoattributes.
Thebasicideabehindsamplingistousethecommoncharacteristicsofaverageitemsassamplesforalargerentity.Thus,itinvolveschoosingasubsetofpopulationelementsforstudy.Thus,forexample,ifthepopulationtobedealtwithis,saythatofroads,thenthecharacteristicscouldbelength,duration,roughness,carriagecapacity,etc.Samplingprovestobeamuchcheaperandquickermodeofestimationwherethepopulationisabsolutelyhuge.
However,itisabsolutelynecessarytotakeamplecarewhiledeterminingwhichcharacteristicsshouldbesampled.Thosecharacteristics,whicharerare,shouldbeavoided.Similarly,eveniftherearecertainverycommoncharacteristics,which,however,donotcontributeinanywaytodrawreliableestimates,thensuchcharacteristicsshouldnotbesampled.
6.2.1 Principle of Sampling and Essentials of Good Sampling
After understanding various concepts related to sampling and samplingdesign,letusnowlookattheprinciplesandessentialsofsampling: • Unbiased:Oneoftheprimaryprinciplesofsamplingisthatitshould
notbebiased. • Adequate sampling size: Foraccuratesampling,itisimportantthat
thesizeofsampleisadequate. • Standardized samples:Samplesshouldbestandardizedsothatthey
canbecheckedforrelevanceandaccuracy. • Statistical Regularity:Accordingtothisprinciple, theunitsof the
samplemustbeselectedatrandom.
Uses of sampling in real life
Inourday-to-day lifewemakeuseof theconceptof sampling.There ishardlyanypersonwhohasnotmadeuseoftheconceptinareal-lifesituation.Considerthefollowingexamples: • Supposeyougotoagroceryshoptopurchaserice.Youhavebeen
instructedbyyourmothertopurchasegoodqualityrice.Onreachingthegroceryshopyouhavethechoiceofbuyingthericefromanyoneofthreebags.Whatisgenerallydoneisthatyoupickupahandfulofricefromeachbag,examineitsqualityandthendecideaboutwhichbag’sriceistobebought.Theconceptofsamplingisbeingusedhereasahandpickfromeachbagisasampleandexaminingthequalityisaprocessbywhichyouaretryingtoassessthequalityofallthericeinthebag.
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• Supposeyouhaveaguestfordinneratyourresidence.Yourmotherpreparesanumberofdishesandbeforetheguestarrives,shemaygiveyouatablespoonofeachofthedishtotasteandtellherwhetheralltheingredientsareintherightproportionornot.Again,asampleisbeingtakenfromeachofthedishtoknowhoweachofthemtastes.
•Yougotoabookshoptobuyamagazine.Beforeyoudecidetobuyit,youmayflipthroughitspagestoknowwhetherthecontentsofthemagazinesareofinteresttoyouornot.Again,asampleofpagesistakenfromthemagazine.
6.2.2 Sampling Concepts and Sampling Frame
Beforewegetintothedetailsofvariousissuespertainingtosampling,itwouldbeappropriatetodiscusssomeofthesamplingconcepts.Population: Populationreferstoanygroupofpeopleorobjectsthatformthesubjectofstudyinaparticularsurveyandaresimilarinoneormoreways.Forexample, thenumberof full-timeMBAstudents inabusinessschool could form one population. If there are 200 such students, thepopulationsizewouldbe200.Wemaybeinterestedinunderstandingtheirperceptionsaboutbusinesseducation.Ifthereare200classIVemployeesinanorganizationandweareinterestedinmeasuringtheirjobsatisfaction,allthe200classIVemployeeswouldformthepopulationofinterest.IfaTVmanufacturingcompanyproduces150TVsperweekandweareinterestedinestimating theproportionofdefectiveTVsproducedperweek,all the150TVswouldformourpopulation.If,inanorganizationthereare1000engineers,outofwhich350aremechanicalengineersandweareinterestedinexaminingtheproportionofmechanicalengineerswhointendtoleavetheorganizationwithinsixmonths,allthe350mechanicalengineerswouldformthepopulationofinterest.Iftheinterestisinstudyinghowthepatientsinahospitalarelookedafter,thenallthepatientsofthehospitalwouldfallunderthecategoryofpopulation.Element: Anelementcomprisesasinglememberofthepopulation.Outofthe350mechanicalengineersmentionedabove,eachmechanicalengineerwouldformanelementofthepopulation.IntheexampleofMBAstudentswhoseperceptionaboutthemanagementeducationisofinteresttous,eachofthe200MBAstudentswillbeanelementofthepopulation.Thismeansthattherewillbe200elementsofthepopulation.Sampling frame: Samplingframecomprisesalltheelementsofapopulationwithproperidentificationthatisavailabletousforselectionatanystageofsampling.Forexample,thelistofregisteredvotersinaconstituencycouldforma sampling frame; the telephonedirectory; the number of studentsregisteredwithauniversity;theattendancesheetofaparticularclassandthepayrollofanorganizationareexamplesofsamplingframes.Whenthe
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Sampling Designpopulation size is very large, it becomes virtually impossible to form asamplingframe.Weknowthatthereisalargenumberofconsumersofsoftdrinksand,therefore,itbecomesverydifficulttoformthesamplingframeforthesame.Sample: Itisasubsetofthepopulation.Itcomprisesonlysomeelementsof the population. If out of the 350mechanical engineers employed inan organization, 30 are surveyed regarding their intention to leave theorganizationinthenextsixmonths,these30memberswouldconstitutethesample.Sampling unit:A samplingunit is a singlemember of the sample. If asampleof50studentsistakenfromapopulationof200MBAstudentsinabusinessschool,theneachofthe50studentsisasamplingunit.Anotherexamplecouldbethatifasampleof50patientsistakenfromahospitaltounderstandtheirperceptionabouttheservicesofthehospital,eachofthe50patientsisasamplingunit.Sampling: It is a process of selecting an adequate number of elementsfromthepopulationsothat thestudyof thesamplewillnotonlyhelp inunderstandingthecharacteristicsofthepopulationbutwillalsoenableustogeneralizetheresults.Wewillseelaterthattherearetwotypesofsamplingdesigns—probabilitysamplingdesignandnon-probabilitysamplingdesign.Census (or complete enumeration): Anexaminationofeachandeveryelementofthepopulationiscalledcensusorcompleteenumeration.Censusis analternative to sampling.Wewilldiscuss the inherentadvantagesofsamplingoveracompleteenumerationlater.
Check Your Progress
1.Whatis‘sampledesign’? 2.Stateanyoneadvantageofsampling. 3.Whatisasamplingunit?
6.3 CENSUS METHOD AND SAMPLING METHOD FOR INVESTIGATION
Inaresearchstudy,wearegenerallyinterestedinstudyingthecharacteristicsofapopulation.Supposeinatownthereare2lakhhouseholdsandweareinterestedinestimatingtheproportionofthosehouseholdswhospendtheirsummervacationsinahillstation.Thisinformationcanbeobtainedbyaskingeveryhouseholdinthattown.Ifallthehouseholdsinapopulationareaskedtoprovideinformation,suchasurveyiscalledacensus.Thereisanalternativewayofobtainingthesameinformationbychoosingasubsetofallthetwo
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lakhhouseholdsandaskingthemforthesameinformation.Thissubsetiscalledasample.Basedupontheinformationobtainedfromthesample,ageneralizationaboutthepopulationcharacteristiccouldbemade.However,thatsamplehastoberepresentativeofthepopulation.Forasampletobearepresentativeofthepopulation,thedistributionofsamplingunitsinthesamplehastobeinthesameproportionastheelementsinthepopulation.Forexample,ifinatownthereare50,35and15percenthouseholdsinlower,middleandupperincomegroups,thenasampletakenfromthispopulationshouldhavethesameproportionsinforittoberepresentative.Thereareseveraladvantagesofsampleovercensus. • Sample saves time and cost.Consider as an example thatwe are
interestedinestimatingthemonthlyaveragehouseholdexpenditureonfooditemsbythepeopleofDelhi.ItisknownthatthepopulationofDelhi is approximately 1.2 crore.Now, ifwe assume that therearefivemembersperhousehold,itwouldmeanthatthepopulationcomprisesapproximately24lakhhouseholds.Collectingdataontheexpenditureofeachofthe24lakhhouseholdsonfooditemswouldbeaverytime-consumingandexpensiveexercise.Thisisbecauseyouwillneedtohireanumberofinvestigatorsandtrainthembeforeyouconductthesurveyonthe24lakhhouseholds.Instead,ifasampleof,say,2000householdsischosen,thetaskwouldnotonlybefinishedfasterbutwillbeinexpensive,too.
•Manytimesadecision-makermaynothavetoomuchoftimetowaittillalltheinformationisavailable.Therefore,asamplecouldcometohisrescue.
•Therearesituationswhereasampleistheonlyoption.Whenwewanttoestimatetheaveragelifeoffluorescentbulbs,whatisdoneisthattheyareburntoutcompletely.Ifwegoforacompleteenumerationtherewouldnotbeanythingleftforuse.Anotherexamplecouldbetestingthequalityofaphotographicfilm.Totestthequality,weneedtoexposeitcompletelyandthemomentitisexposeditgetsdestroyed.Therefore,sampleistheonlychoice.
•Thestudyofasampleinsteadofcompleteenumerationmay,attimes,producemorereliableresults.Thisisbecausebystudyingasample,fatigueisreducedandfewererrorsoccurwhilecollectingthedata,especiallywhenalargenumberofelementsareinvolved.Acensus isappropriatewhenthepopulationsize issmall,e.g., the
number of public sector banks in the country.Suppose the researcher isinterested in collecting information from the topmanagement of a bankregarding their viewson themonetarypolicy announcedby theReserveBankofIndia(RBI),inthiscase,acompleteenumerationmaybepossibleas the population size is not very large.As another example, consider abusinessschoolhavingafewstudentsfromEurope,EastAfrica,SouthEast
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Sampling DesignAsiaandtheMiddleEast.ThesestudentswouldhavetheirownproblemsinsettlingdownintheIndianenvironmentbecauseofthedifferencesinsocial,culturalandenvironmentalfactors.Tounderstandtheirconcerns,asurveyofpopulationmaybemoreappropriate.Therefore,asurveyofpopulationcouldbeusedwhenthereisalotofheterogeneityinthevariablesofinterestandthepopulationsizeissmall.
6.4 METHODS OF SAMPLING: PROBABILITY, NON-PROBABILITY AND MIXED SAMPLING DESIGN (OR SYSTEMATIC SAMPLING)
Samplingdesignreferstotheprocessofselectingsamplesfromapopulation.Therearetwotypesofsamplingdesigns—probabilitysamplingdesignandnon-probabilitysamplingdesign.Probabilitysamplingdesignsareusedinconclusiveresearch.Inaprobabilitysamplingdesign,eachandeveryelementofthepopulationhasaknownchanceofbeingselectedinthesample.Theknown chance does notmean equal chance.Simple random sampling isaspecialcaseofprobabilitysamplingdesignwhereeveryelementofthepopulationhasbothknownandequalchanceofbeingselectedinthesample.Incaseofnon-probabilitysamplingdesign,theelementsofthepopulationdonothaveanyknownchanceofbeingselectedinthesample.Thesesamplingdesignsareusedinexploratoryresearch.
Probability Sampling Design
Under this, the following sampling designswould be covered—simplerandom samplingwith replacement (SRSWR), simple random samplingwithout replacement (SRSWOR), systematic sampling, stratified randomsamplingandclustersampling.
Simple random sampling with replacement
Underthisscheme,alistofalltheelementsofthepopulationfromwherethesamplestobedrawnisprepared.Ifthereare1000elementsinthepopulation,wewritetheidentificationnumberorthenameofallthe1000elementson1000differentslips.Theseareputinaboxandshuffledproperly.Ifthereare 20 elements to be selected from the population, the simple randomsamplingprocedureinvolvesselectingaslipfromtheboxandreadingoftheidentificationnumber.Oncethisisdone,thechosenslipisputbacktotheboxandagainaslipispickedupandtheidentificationnumberisreadfromthatslip.Thisprocesscontinuestillasampleof20isselected.Pleasenotethatthefirstelementischosenwithaprobabilityof1/1000,thesecondoneisalsoselectedwiththesameprobabilityandsoareallthesubsequentelementsofthepopulation.
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Analternativewayofselectingthesamplesfromthepopulationisbyusingrandomnumbertables.Table6.1givesanillustrativeexampleofrandomnumbers.
Table 6.1 Select Four-digit Random Numbers
I II III IV V 2807 0495 6183 7871 9559 8016 5732 3448 0164 2367 1322 4678 8034 1139 1474 0843 4625 7407 9987 5734 2364 1187 4565 2343 9786 4885 8755 4355 5465 0575 3406 4678 5950 7222 8494 5927 6010 7545 8979 1041 4447 3476 9140 0736 2332 4968 7553 1073 2493 4251 7489 1630 2330 4250 6170 4010 2707 3925 6007 8089 6531 9784 5520 7764 0008 7052 3861 7115 9521 2192 6573 2793 8710 2127 3846 8094 3205 2030 3035 5765 8615 6092 1900 4792 7684 9136 4016 3495 6549 9603 9656 5246 5090 8306 1522
2017 8323 1685 3006 3441
Table6.1givesfour-digitrandomnumbersarrangedin20rowsandfive columns.These randomnumbers can be generated by a computerprogrammedtoscramblenumbers.Thelogicforgeneratingrandomnumberisthatanynumbercanbeconstructedfromnumbers0to9.Theprobabilitythatanyonedigitfrom0through9willappearisthesameasthatforanyotherdigitandtheappearanceofthenumbersisstatisticallyindependent.Further,theprobabilityofonesequenceofdigitsoccurringisthesameasthatforanyothersequenceofthesamelength.
The use of randomnumber table for selecting samples could beillustrated through an example.Suppose there are 75 students in a classanditisdecidedtoselect15outofthe75students.Thesestudentscanbenumberedfrom01to75.Now,topickup15studentsusingrandomnumbers
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Sampling Designandfollowingtheschemeofsimplerandomsamplingwithreplacement,weproceedasfollows: •Witheyesclosed,weplaceourfingeronanumberon the random
numbertable.Supposeitisonthefirstrowandthefirstcolumnofourtable.Now,wegodownthefirsttwocolumnsandchoosetwo-digitrandomnumbersrunningfrom01to75.Ifanynumbergreaterthan75appears,itgetsrejected.Thisway,thefirstnumbertobeselectedwouldbe28.Thesecondnumberis80,whichwouldberejectedaswearechoosingnumbersfrom01to75.Thenextselectednumberwouldbe13,followedby08,23,48,34,59,44,49,74,40,65,70and65.Notethat65hasappearedtwice.Sinceweareusingtheschemeofsimplerandomsamplingwithreplacement,wewouldretainit.Thiswaywehaveselected14samples.The15thnumberselectedwouldbe20.Inbrief,theschemeexplainedabovestatesthatanynumbergreaterthanthepopulationsize(inthiscase75)isrejectedandonlythenumbersfrom01to75areselected.Anumbermaygetrepeatedbecausesimplerandomsamplingschemeisdonewithreplacement.
Simple random sampling without replacement
Inthecaseofsimplerandomsamplewithoutreplacement,theprocedureisidenticaltowhatwasexplainedinthecaseofsimplerandomsamplingwithreplacement.Theonlydifferencehereisthatthechosenslipisnotplacedbackinthebox.Thisway,thefirstunitwouldbeselectedwiththeprobabilityof1/1000,secondunitwiththeprobabilityof1/999,thethirdwillbeselectedwithaprobabilityof1/998andsoon,tillweselecttherequirednumberofelements(inthiscase,15)inoursample.
Thesimplerandomsampling(withorwithoutreplacement)isnotusedinaconsumerresearch.Thisisbecauseinaconsumerresearchthepopulationsize isusuallyvery large,whichcreatesproblemsin thepreparationofasamplingframe.Forexample,thereisalargenumberofconsumersofsoftdrinks,pizza,shampoo,soap,chocolateandsoon.However,these(SRSWRandSRSWOR)designscouldbeusefulwhenthepopulationsizeisverysmall,forexample,thenumberofsteel/aluminium-producingcompaniesinIndiaandthenumberofbanksinIndia.Sincethepopulationsizeisquitesmall,thepreparationofasamplingframedoesnotcreateanyproblem.
Anotherproblemwiththese(SRSWRandSRSWOR)designsisthatwemaynotgetarepresentativesampleusingsuchascheme.Consideranexampleofalocalityhaving10,000households,outofwhich5,000belongtolow-incomegroup,3,500belongtomiddleincomegroupandtheremaining1,500belongtohigh-incomegroup.Supposeitisdecidedtotakeasampleof100householdsusingthesimplerandomsampling.Theselectedsamplemaynotcontainevenasinglehouseholdbelongingtothehigh-andmiddle-
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incomegroupandonlythelow-incomehouseholdsmaygetselected,thus,resultinginanon-representativesample.
Systematic sampling
Systematic sampling takes care of the limitation of the simple randomsamplingthatthesamplemaynotbearepresentativeone.Inthisdesign,theentirepopulationisarrangedinaparticularorder.Theordercouldbethecalendardatesortheelementsofapopulationarrangedinanascendingoradescendingorderofthemagnitudewhichmaybeassumedasrandom.Listofsubjectsarrangedinthealphabeticalordercouldalsobeusedandtheyareusuallyassumedtoberandominorder.Oncethisisdone,thestepsfollowedinthesystematicsamplingdesignareasfollows: • Firstofall,asamplingintervalgivenbyK=N/niscalculated,where
N=thesizeof thepopulationandn=thesizeof thesample.It isseenthatthesamplingintervalKshouldbeaninteger.Ifitisnot,itisroundedofftomakeitaninteger.
•Arandomnumberisselectedfrom1toK.LetuscallitC. •Thefirstelementtobeselectedfromtheorderedpopulationwouldbe
C,thenextelementwouldbeC+KandthesubsequentonewouldbeC+2Kandsoontillasampleofsizenisselected.Thiswaywecangetrepresentationfromalltheclassesinthepopulation
andovercomethe limitationsof thesimplerandomsampling.Totakeanexample,assumethatthereare1,000groceryshopsinasmalltown.Theseshopscouldbearrangedinanascendingorderoftheirsales,withthefirstshophavingthesmallestsalesandthelastshophavingthehighestsales.Ifitisdecidedtotakeasampleof50shops,thenoursamplingintervalKwillbeequalto1000÷50=20.Nowweselectarandomnumberfrom1to20.Supposethechosennumberis10.Thismeansthattheshopnumber10willbeselectedfirstandthenshopnumber
10+20=30andthenextonewouldbe10+2×20=50andsoontillallthe50shopsareselected.Thiswaywecangetarepresentativesampleinthesensethatitwillcontainsmall,mediumandlargeshops.
Itmaybenoted that inasystematicsamplingthefirstunitof thesampleisselectedatrandom(probabilitysamplingdesign)andhavingchosenthis,wehavenocontroloverthesubsequentunitsofsample(non-probabilitysampling).Becauseofthis,thisdesignattimesiscalledmixedsampling.
Themainadvantageofsystematicsamplingdesignisitssimplicity.Whensamplingfromalistofpopulationarrangedinaparticularorder,onecaneasilychoosearandomstartasdescribedearlier.Afterhavingchosenarandomstart,everyKthitemcanbeselectedinsteadofgoingforasimplerandomselection.Thisdesignisstatisticallymoreefficientthanasimple
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Sampling Designrandomsampling,providedtheconditionoforderingofthepopulationissatisfied.
Theuseofsystematicsamplingisquitecommonasitiseasyandcheaptoselectasystematicsample.Insystematicsamplingonedoesnothavetojumpbackandforthalloverthesamplingframewhereverrandomnumberleads, andneitherdoesonehave tocheck forduplicationofelementsascomparedtosimplerandomsampling.Anotheradvantageofasystematicsampling over simple random sampling is that one does not require acompletesamplingframetodrawasystematicsample.Theinvestigatormaybeinstructedtointerviewevery10thcustomerenteringamallwithoutalistofallcustomers.
Theremay be situationswhere itmay not be possible to get arepresentative sample.The design can create problems if the samplingintervalisawholenumbermultipleofsomecyclerelatedtotheproblem.Onthisdesigntheremaybeaproblemthatthereisahighprobabilityofsystematicbiascreepingintothesampleresultinginanon-representativesample.Consider,forexample,thecaseofacertainPVRcinemahallwheretheremaybeacoupleofsnackbars.WemaybeinterestedinestimatingtheaveragedailysalesofaparticularsnackbarinthatPVR.Now,usingthedailydatawiththepopulationandsamplesizeknown,wecomputeasamplingintervalwhichmaybeamultipleofseven.Usingthis,wemayselectourfirstelementwhichwouldreflectoneof thesevendaysof theweek,sayFriday.Thenext elementwould alsobeFriday, asour sampling intervalis amultipleof sevenandso the subsequentelementsof thepopulation.Therefore,oursamplewouldcompriseonlyFridaysandthesamplewouldnotreflectdayoftheweekvariationinthesalesdata,whichcouldresultinanon-representativesample.Therefore,whileusingdailydata,careshouldbetakenthatoursamplingintervalisnotamultipleofseven.
Stratified random sampling
Underthissamplingdesign,theentirepopulation(universe)isdividedintostrata(groups),whicharemutuallyexclusiveandcollectivelyexhaustive.Bymutuallyexclusive,itismeantthatifanelementbelongstoonestratum,itcannotbelongtoanyotherstratum.Strataarecollectivelyexhaustiveifalltheelementsofvariousstrataputtogethercompletelycoveralltheelementsofthepopulation.Theelementsareselectedusingasimplerandomsamplingindependentlyfromeachgroup.
Therearetworeasonsforusingastratifiedrandomsamplingratherthansimplerandomsampling.Oneisthattheresearchersareofteninterestedinobtainingdata about thecomponentpartsof auniverse.For example,theresearchermaybeinterestedinknowingtheaveragemonthlysalesofcellphonesin‘large’,‘medium’and‘small’stores.Insuchacase,separatesamplingfromwithineachstratumwouldbecalledfor.Thesecondreason
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forusingastratifiedrandomsamplingisthatitismoreefficientascomparedtoasimplerandomsampling.Thisisbecausedividingthepopulationintovariousstrataincreasestherepresentativnessofthesamplingastheelementsofeachstratumarehomogeneoustoeachother.
There are certain issues thatmaybe of interestwhile setting up astratifiedrandomsample.Theseare:What criteria should be used for stratifying the universe (population)?Thecriteriaforstratificationshouldberelatedtotheobjectivesofthestudy.Theentirepopulationshouldbestratifiedinsuchawaythattheelementsarehomogeneouswithinthestrata,whereasthereshouldbeheterogeneitybetweenstrata.Asanexample,iftheinterestistoestimatetheexpenditureofhouseholdsonentertainment,theappropriatecriteriaforstratificationwouldbethehouseholdincome.Thisisbecausetheexpenditureonentertainmentandhousehold income are highly correlated.As another example, if theobjectiveofthestudyistoestimatetheamountofmoneyspentoncosmetics,then,gendercouldbeusedasanappropriatecriteriaforstratification.Thisisbecauseitisknownthatthoughbothmenandwomenusecosmetics,theexpenditurebywomenismuchmorethanthatoftheirmalecounterparts.Someonemayargueoutthatgendermaynolongerremaintheappropriatecriteriaifitisnotbackedbyincome.Therefore,theresearchermighthavetouse twoormorecriteriaforstratificationdependingupontheprobleminhand.Thiswouldonlyincreasethenumberofstratatherebymakingthesamplingdifficult.
Generallystratificationisdoneonthebasisofdemographicvariableslike age, income, education andgender.Customers are usually stratifiedonthebasisoflifestagesandincomelevelstostudytheirbuyingpatterns.Companiesmaybestratifiedaccordingtosize,industry,profitsforanalysingthestockmarketreactions.How many strata should be constructed?Goingbycommonsense,asmanystrataaspossibleshouldbeusedsothattheelementsofeachstratumwillbeashomogeneousaspossible.However,itmaynotbepracticaltoincreasethenumberofstrataand,therefore,thenumbermayhavetobelimited.Toomanystratamaycomplicatethesurveyandmakepreparationandtabulationdifficult.Costsofaddingmorestratamaybemorethanthebenefitobtained.Further,theresearchermayendupthepracticaldifficultyofpreparingaseparatesamplingframeasthesimplerandomsamplesaretobedrawnfromeachstratum.What should be appropriate number of samples size to be taken in each stratum?Thisquestionpertainstothenumberofobservationstobetakenoutfromeachstratum.Attheoutset,oneneedstodeterminethetotalsamplesizefor
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Sampling Designtheuniverseandthenallocateitbetweeneachstratum.Thismaybeexplainedasfollows:
LettherebeapopulationofsizeN.Letthispopulationbedividedintothreestratabasedonacertaincriterion.LetN1,N2andN3denotethesizeofstrata1,2and3respectively,suchthatN=N1+N2+N3.Thesestrataaremutuallyexclusiveandcollectivelyexhaustive.Eachofthesethreestratacouldbetreatedasthreepopulations.Now,ifatotalsampleofsizenistobetakenfromthepopulation,thequestionarisesthathowmuchofthesampleshouldbetakenfromstrata1,2and3respectively,sothatthesumtotalofsamplesizesfromeachstrataaddsupton.
Letthesizeofthesamplefromfirst,secondandthirdstrataben1,n2,andn3respectivelysuchthatn=n1+n2+n3.Then,therearetwoschemesthatmaybeusedtodeterminethevaluesofni,(i=1,2,3)fromeachstrata.Theseareproportionateanddisproportionateallocationschemes.
Proportionate allocation scheme: In this scheme, the size of thesampleineachstratumisproportionaltothesizeofthepopulationofthestrata.Asanexample,ifabankwantstoconductasurveytounderstandtheproblemsthatitscustomersarefacing,itmaybeappropriatetodividethemintothreestratabaseduponthesizeoftheirdepositswiththebank.Ifwehave10,000customersofabankinsuchawaythat1,500ofthemarebigaccountholders(havingdepositsmorethan`10lakh),3,500ofthemaremediumsizedaccountholders(havingdepositsofmorethan`2lakhbutlessthan`10lakh),theremaining5,000aresmallaccountholders(havingdepositsoflessthan 2lakh).Supposethetotalbudgetforsamplingisfixedat`20,000andthecostofsamplingaunit(customer)is`20.Ifasampleof100istobechosenfromallthethreestrata,thesizeofthesamplefromstrata1wouldbe:
11
N 1500n n 100 15N 10000
= × = × =
Thesizeofsamplefromstrata3wouldbe:2
2N 3500n n 100 35N 10000
= × = × =
Thesizeofsamplefromstrata3wouldbe:3
3N 5000n n 100 50N 10000
= × = × =
Thiswaythesizeofthesamplechosenfromeachstratumisproportionaltothesizeofthestratum.Oncewehavedeterminedthesamplesizefromeachstratum,onemayusethesimplerandomsamplingorthesystematicsamplingoranyothersamplingdesigntotakeoutsamplesfromeachofthestrata.Disproportionate allocation:Aspertheproportionateallocationexplainedabove, thesizesof thesamples fromstrata1,2and3are15,35and50
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respectively.As it is known that the cost of sampling of a unit is` 20 irrespectiveofthestratafromwherethesampleisdrawn,thebankwouldnaturallybemoreinterestedindrawingalargesamplefromstratum1,whichhasthebigcustomers,asitgetsmostofitsbusinessfromstrata1.Inotherwords,thebankmayfollowadisproportionateallocationofsampleastheimportanceofeachstratumisnotthesamefromthepointofviewofthebank.Thebankmayliketotakeasampleof45fromstrata1and40and15fromstrata2and3respectively.Also,alargesamplemaybedesiredfromthestratahavingmorevariability.
Cluster sampling
Intheclustersampling,theentirepopulationisdividedintovariousclustersinsuchawaythattheelementswithintheclustersareheterogeneous.However,thereishomogeneitybetweentheclusters.Thisdesign,therefore,isjusttheoppositeof the stratified samplingdesign,where therewashomogeneitywithin the strata and heterogeneity between the strata.To illustrate theexampleofacluster sampling,onemayassume that there is acompanyhavingitscorporateofficeinamulti-storeybuilding.Inthefirstfloor,wemayassumethatthereisamarketingdepartmentwheretheofficesofthepresident(marketing),vicepresident(marketing)andsoontothelevelofmanagementtrainee(marketing)arethere.Naturally,therewouldbealotofvariation(heterogeneity)intheamountofsalariestheydrawandhenceahighamountofvariationintheamountofmoneyspentonentertainment.Similarly,ifthefinancedepartmentishousedonthesecondfloor,wemayfindalmostasimilarpattern.Samecouldbeassumedforthird,fourthandotherfloors.Now,ifeachofthefloorscouldbetreatedasacluster,wefindthatthereishomogeneitybetweentheclustersbutthereisalotofheterogeneitywithintheclusters.Now,asampleof,say,2to3clustersischosenatrandomandoncehavingdoneso,eachoftheclusterisenumeratedcompletelytobeabletomakeanestimateoftheamountofmoneytheentirepopulationspendsonentertainment.
Examplesofclustersamplingcouldincludead-hocorganizationalcommitteesdrawnfromvariousdepartmentstoadvisetheCEOofacompanyonproductdevelopment,newproductideas,evaluatingalternativeadvertisingprogrammes,budgetallocationsandmarketingstrategies.Eachoftheclusterscomprisesaheterogeneouscollectionofmemberswithdifferentinterests,background, experience, value system and philosophy.TheCEOof thecompanymaybeabletotakestrategicdecisionsbasedupontheircombinedadvice.
Althoughtheperunitcostsofclustersamplingaremuchlowerthanthoseofotherprobabilitysampling,theapplicabilityofclustersamplingtoanorganizationalcontextmaybequestionedasaclustermaynotcontainheterogeneouselements.Theconditionofheterogeneitywithinthecluster
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Sampling Designandhomogeneitybetweentheclustersmaynotbemet.Asanotherexample,thehouseholdsinablockaretobesimilarratherthandissimilarandasaresult,itmaybedifficulttoformheterogeneousclusters.
Althoughtheperunitcostsofclustersamplingaremuchlowerthanthoseofotherprobabilitysampling,theapplicabilityofclustersamplingtoanorganizationalcontextmaybequestionedasaclustermaynotcontainheterogeneouselements.Theconditionofheterogeneitywithintheclusterandhomogeneitybetweentheclustersmaynotbemet.Asanotherexample,thehouseholdsinablockaretobesimilarratherthandissimilarandasaresult,itmaybedifficulttoformheterogeneousclusters.
Clustersamplingisusefulwhenpopulationsunderasurveyarewidelydispersedanddrawingasimplerandomsamplemaybeimpractical.
Non-probability Sampling Designs
Under the non-probability sampling, the following designswould beconsidered—conveniencesampling,purposivesampling,snowballsamplingandquotasampling.
Convenience sampling
Convenience sampling is used to obtain information quickly andinexpensively.Theonlycriterionforselectingsamplingunitsinthisschemeistheconvenienceoftheresearcherortheinvestigator.Mostly,theconveniencesamples used are neighbours, friends, familymembers, colleagues and‘passers-by’.Thissamplingdesignisoftenusedinthepre-testphaseofaresearchstudysuchasthepre-testingofaquestionnaire.Someoftheexamplesofconveniencesamplingare: • Peopleinterviewedinashoppingcentrefortheirpoliticalopinionfor
aTVprogramme. •Monitoring the price level in a grocery shopwith the objective of
inferringthetrendsininflationintheeconomy. •Requestingpeopletovolunteertotestproducts. •Using students or employees of an organization for conducting an
experiment. • InterviewsconductedbyaTVchannelofpeoplecomingoutofacinema
hall,toseektheiropinionaboutthemovie. •Aresearchervisitingafewshopsnearhisresidencetoobservewhich
brandofaparticularproductpeoplearebuying,soastodrawaroughestimateofthemarketshareofthebrand.Inalltheabovesituations,thesamplingunitmayeitherbeself-selected
orselectedbecauseofeaseofavailability.Noeffort ismadetochoosearepresentativesample.Therefore,inthisdesignthedifferencebetweenthe
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populationvalue(parameters)ofinterestandthesamplevalue(statistic)isunknownbothintermsofthemagnitudeanddirection.Therefore,itisnotpossibletomakeanestimateofthesamplingerrorandresearcherswon’tbeabletomakeaconclusivestatementabouttheresultsfromsuchasample.Itisbecauseofthis,conveniencesamplingshouldnotbeusedinconclusiveresearch(descriptiveandcausalresearch).
Conveniencesamplingiscommonlyusedinexploratoryresearch.Thisisbecausethepurposeofanexploratoryresearchistogainaninsightintotheproblemandgenerateasetofhypotheseswhichcouldbetestedwiththehelpofaconclusiveresearch.Whenverylittleisknownaboutasubject,asmall-scaleconveniencesamplingcanbeofuseintheexploratoryworktohelpunderstandtherangeofvariabilityofresponsesinasubjectarea.
Judgemental sampling
Under judgemental sampling, experts in a particular field choosewhattheybelievetobethebestsampleforthestudyinquestion.Thejudgementsamplingcallsforspecialeffortstolocateandgainaccesstotheindividualswhohavetherequiredinformation.Here,thejudgementofanexpertisusedtoidentifyarepresentativesample.Forexample,theshoppersatashoppingcentremayservetorepresenttheresidentsofacityorsomeofthecitiesmaybeselectedtorepresentacountry.Judgementalsamplingdesignisusedwhentherequiredinformationispossessedbyalimitednumber/categoryofpeople.Thisapproachmaynotempiricallyproducesatisfactoryresultsand,may,therefore,curtailgeneralizabilityofthefindingsduetothefactthatweareusingasampleofexperts(respondents) thatareusuallyconvenientlyavailabletous.Further,thereisnoobjectivewaytoevaluatetheprecisionoftheresults.Acompanywantingtolaunchanewproductmayusejudgementalsamplingforselecting‘experts’whohavepriorknowledgeorexperienceofsimilarproducts.Afocusgroupofsuchexpertsmaybeconductedtogetvaluableinsights.Opinionleaderswhoareknowledgeableareincludedinthe organizational context.Enlightenedopinions (views andknowledge)constitutearichdatasource.Averyspecialeffortisneededtolocateandhaveaccesstoindividualswhopossesstherequiredinformation.
Themostcommonapplicationofjudgementalsamplingisinbusiness-to-business(BtoB)marketing.Here,averysmallsampleofleadusers,keyaccountsortechnologicallysophisticatedfirmsorindividualsisregularlyusedtotestnewproductconcepts,producingprogrammes,etc.
Snowball sampling
Snowball sampling is generally usedwhen it is difficult to identify themembers of the desired population, e.g., deep-sea divers, familieswithtriplets, people usingwalking sticks, doctors specializing in a particularailment,etc.Underthisdesigneachrespondent,afterbeinginterviewed,is
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Sampling Designaskedtoidentifyoneormoreinthefield.Thiscouldresultinaveryusefulsample.Themainproblemisinmakingtheinitialcontact.Oncethisisdone,thesecasesidentifymoremembersofthepopulation,whothenidentifyfurthermembersandsoon.Itmaybedifficulttogetarepresentativesample.Oneplausiblereasonforthiscouldbethattheinitialrespondentsmayidentifyotherpotentialrespondentswhoaresimilartothemselves.Thenextproblemistoidentifynewcases.
Quota sampling
In quota sampling, the sample includes aminimumnumber from eachspecifiedsubgroupinthepopulation.Thesampleisselectedonthebasisof certain demographic characteristics such as age, gender, occupation,education, income,etc.Theinvestigator isaskedtochooseasamplethatconformstotheseparameters.Fieldworkersareassignedquotasofthesampletobeselectedsatisfyingthesecharacteristics.
Aresearcherwants tomeasure the jobsatisfaction levelamongtheemployeesofalargeorganizationandbelievesthatthejobsatisfactionlevelvariesacrossdifferenttypesofemployees.Theorganizationishaving10percent,15percent,35percentand40percent,classI,classII,classIIIandclassIV,employees,respectively.Ifasampleof200employeesistobeselectedfromtheorganization,then20,30,70and80employeesfromclassI,classII,classIIIandclassIVrespectivelyshouldbeselectedfromthepopulation.Now,variousinvestigatorsmaybeassignedquotasfromeachclassinsuchawaythatasampleof200employeesisselectedfromvariousclassesinthesameproportionasmentionedinthepopulation.Forexample,thefirstfieldworkermaybeassignedaquotaof10employeesfromclassI,15fromclassII,20fromclassIIIand30fromclassIV.Similarly,asecondinvestigatormaybeassignedadifferentquotasuchthatatotalsampleof200isselectedinthesameproportionasthepopulationisdistributed.Pleasenotethattheinvestigatorsmaychoose theemployees fromeachclassasconvenientlyavailabletothem.Therefore,thesamplemaynotbetotallyrepresentativeofthepopulation,hencethefindingsoftheresearchcannotbegeneralized.However,thereasonforchoosingthissamplingdesignistheconvenienceitoffersintermsofeffort,costandtime.
Intheexamplegivenabove,itmaybearguedthatjobsatisfactionisalsoinfluencedbyeducationlevel,categorizedashighersecondaryorbelow,graduation,andpostgraduationandabove.Byincorporatingthisvariable,thedistributionofpopulationmaylookasgiveninTable6.2.Fromthetable,wemaynotethatthereare8percentclassIemployeeswhoarepostgraduateandabove,thereare35percentclassIVemployeeswithahighersecondaryeducation and below and so on.Now, suppose a sample of size 200 isagainproposed.Inthiscase,thedistributionofsamplesatisfyingthesetwoconditionsinthesameproportioninthepopulationisgiveninTable6.3.
Sampling Design
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Table 6.2 Distribution of Population (percentage)
Table 6.3 Distribution of Sample (numbers)
Table6.3 indicates thatasampleof20classIIemployeeswhoaregraduates should be selected.Likewise, a sample of 10 employeeswhopossesspostgraduateandaboveeducationshouldbeselected.Intheabovetable,thesampletobetakenfromeachofthe12cellshasbeenspecified.Having done so, each of the investigators is assigned a quota to collectinformationfromtheemployeesconformingtotheabovenormssothatasampleof200isselected.
Quota sampling designmay look similar to the stratified randomsamplingdesign.However, therearedifferencesbetween the two. In thestratified sampling design, the selection of sample fromeach stratum israndombut in thequotasampling, therespondentsmaybechosenat theconvenienceorjudgementoftheresearchers.Further,asalreadystated,theresultsofstratifiedrandomsamplingcouldbegeneralized,whereasitmaynotbepossible in thecaseofquotasampling.Quotasamplinghassomeadvantagesovertheprobabilistictechniques.Thisdesignisveryeconomicalanditdoesnottaketoomuchtimetosetitup.Also,theuseofthisdesigndoesnotrequireasamplingframe.
However,quotasamplingalsohascertainweaknesseslike:• The total number of cells depends upon the number of control
characteristicsassociatedwiththeobjectivesof thestudy.If thecontrolcharacteristicsarelarge,thetotalnumberofcellsincreases,whichmayresultinmakingthetaskoftheinvestigatordifficult.
• Thechosencontrolcharacteristicsshouldberelatedtotheobjectivesofthestudy.Thefindingsofthestudycouldbemisleadingifanyrelevantparameterisomittedforonereasonortheother.
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Sampling Design• Theinvestigatormayvisitthoseplaceswherethechancesofgettingtherespondentswiththerequiredcontrolcharacteristicsarehigh.Theinvestigatorcouldalsoavoidsomeresponsesthatappeartobeunfriendly.Allthiscouldresultinmakingthefindingsofthestudylessreliable.
Check Your Progress
4.Stateanyoneadvantageofsampleovercensus. 5.Wheniscensusappropriate? 6.Whatisprobabilitysamplingdesign? 7.Definesystematicsampling. 8.Whatistheimportanceofclustersampling?
6.5 ANSWERS TO CHECK YOUR PROGRESS QUESTIONS
1.Adefinite plan for obtaining a sample from the sampling frame isknownassampledesign.Italsoencompassesthetechnique,adoptedby a researcher in selecting some sampling units to carry out aninvestigation.
2.Anyoneadvantageofsamplingisthatthesolutiontoknowthetrueoractualvaluesofthevariousparametersofthepopulationwouldbetotakeintoaccounttheentirepopulation.Thisisnotfeasibleduetothecostandtimeinvolved.Therefore,samplingseemsmoreeconomical.
3.Asamplingunitisasinglememberofthesample. 4.Samplesavestimeandcost.Therearesituationswhereasampleis
theonlyoption.Ifwewanttoestimatetheaveragelifeoffluorescentbulbs,theyareburntoutcompletely.Insuchcases,samplingscoresover census.
5.Acensusisappropriatewhenthepopulationsizeissmall.Forexample,onewantstocalculatethenumberofpublicsectorsbanksinthecountry.
6.Underprobabilitysamplingdesign,simplerandomsamplingwillbereplacedandsamplingdesignswouldbecovered.
7.Systematicsamplingtakescareofthelimitationofthesimplerandomsamplingthatthesamplemaynotbearepresentativeone.
8.Whenpopulationsunderasurveyarewidelydispersedanddrawingasimplerandomsample is required,clustersamplingcomes to therescue.
Sampling Design
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6.6 SUMMARY
•Adefinite plan for obtaining a sample from the sampling frame istermedassamplingdesign. It refers to the techniqueorprocedure,whicharesearcheradoptsinselectingsomesamplingunitsfromwhereinferencesaboutpopulationaredrawn.
•Samplingisrequiredforobtaininginformationbecauseitsavestimeandmoney.Itislessexpensiveandproducesresultsatafasterspeed.
•Samplinginvolvesdeterminingapropertyorattributetoadheretoforthepurposeofdifferentiatingbetweenitemsofagivenpopulation.Thebasicideabehindsamplingistousethecommoncharacteristicsofaverageitemsassamplesforalargerentity.
•Populationreferstoanygroupofpeopleorobjectsthatformthesubjectofstudyinaparticularsurveyandaresimilarinoneormoreways.
•Anelement comprises a singlemember of the populationwhile asampleisasubsetofthepopulation.Itcomprisesonlysomeelementsofthepopulation.
•Samplingisaprocessofselectinganadequatenumberofelementsfromthepopulationsothatthestudyofthesamplewillnotonlyhelpin understanding the characteristics of the populationbutwill alsoenableustogeneralizetheresults.
•Censusisanexaminationofeachandeveryelementofthepopulationiscalledcensusorcompleteenumeration.
•Acensusisappropriatewhenthepopulationsizeissmall,forexample,thenumberofpublicsectorbanksinthecountry.
•The process of selecting samples from a population is termed assampling design.Two types of sampling designs are probabilitysamplingdesignandnon-probabilitysamplingdesign.
• Intheproportionateallocationscheme,thesizeofthesampleineachstratumisproportionaltothesizeofthepopulationofthestrata.
• Inclustersampling,theentirepopulationisdividedintovariousclustersinsuchawaythattheelementswithintheclustersareheterogeneous.
•Convenience sampling is used to obtain information quickly andinexpensively.Theonlycriterionforselectingsamplingunitsinthisschemeistheconvenienceoftheresearcherortheinvestigator.
•Snowballsamplingisgenerallyusedwhenitisdifficulttoidentifythemembersofthedesiredpopulation,e.g.,deep-seadivers,familieswithtriplets,peopleusingwalkingsticks,doctorsspecializinginaparticularailment,etc.
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Sampling Design • Inquotasampling,thesampleincludesaminimumnumberfromeachspecifiedsubgroupinthepopulation.Thesampleisselectedonthebasisofcertaindemographiccharacteristicssuchasage,gender,occupation,education,income,etc.
6.7 KEY WORDS
• Quota Sampling:Itisasamplewhichincludesaminimumnumberfromeachspecifiedsubgroupinthepopulation.
• Sampling Design:Itreferstoadefiniteplanforobtainingasamplefromthesamplingframe.
• Stratified Random Sampling:Itisamethodofsamplingthatinvolvesthedivisionofapopulationintosmallergroupsknownasstrata.Instratifiedrandomsampling,orstratification,thestrataareformedbasedonmembers’sharedattributesorcharacteristics.
• Sampling Frame:Itcomprisesalltheelementsofapopulationwithproperidentificationthatisavailabletousforselectionatanystageofsampling.
6.8 SELF ASSESSMENT QUESTIONS AND EXERCISES
Short Answer Questions
1.Definesampledesign.Whydoweneedsampledesign? 2.Stateanyonecharacteristicofsampling. 3.Whatisthecensusmethod? 4.Whatdoyouunderstandbysamplingframe?
Long Answer Questions
1.Differentiatebetweencensusmethodandsamplingmethod. 2.Whatarethemethodsofsampling?Discussanytwoindetail. 3.Explainclustersampling. 4.Analysejudgementalsampling.
6.9 FURTHER READINGS
Creswell,JohnW.2002.Research Design: Qualitative, Quantitative, and Mixed Methods Approaches.London:SagePublicationsInc.
Sampling Design
NOTES
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Booth,Wayne,GregoryG.ColombandJosephM.Williams.1995.The Craft of Research.Chicago:UniversityofChicagoPress.
Bryman,AlanandEmmaBell.2015.Business Research Methods.4thEdition.UnitedKingdom:OxfordUniversityPress.
Gupta,S.L.andHiteshGupta. 2012. Business Research Methods. NewDelhi: TataMcGrawHillEducationPrivateLimited.
NOTES
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Construction of Sampling for Finite and Infinite
PopulationsUNIT 7 CONSTRUCTION OF SAMPLING FOR FINITE AND INFINITE POPULATIONS
Structure 7.0 Introduction 7.1 Objectives 7.2 SampleSizeDetermination,CalculationandFactorsAffectingtheSizeof
theSample 7.3 SamplingandNon-SamplingErrors
7.3.1 BiasedSample 7.4 AnswerstoCheckYourProgressQuestions 7.5 Summary 7.6 Key Words 7.7 SelfAssessmentQuestionsandExercises 7.8 FurtherReadings
7.0 INTRODUCTION
Inthepreviousunit,youwereintroducedtotheconceptofsamplingdesign.Asampledesignismadeupoftwoelements,thatis,asamplingmethodandanestimator.Inthisunit,thediscussionwillturntowardshowtodeterminesamplesize,thefactorsaffectingthesizeofasampleaswellassamplingandnon-samplingerrors.
7.1 OBJECTIVES
Aftergoingthroughthisunit,youwillbeableto: •Describehowtodeterminesamplesize •Examinesamplingandnon-samplingerrors •Discussbiasedsample
7.2 SAMPLE SIZE DETERMINATION, CALCULATION AND FACTORS AFFECTING THE SIZE OF THE SAMPLE
Thesizeofasampledependsuponthebasiccharacteristicsofthepopulation,the type of information required from the survey and the cost involved.
Construction of Sampling for Finite and Infinite Populations
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Self-Instructional 106 Material
Therefore,asamplemayvaryinsizeforseveralreasons.Thesizeofthepopulationdoesnotinfluencethesizeofthesample.
Therearevariousmethodsofdeterminingthesamplesizeinpractice:• Researchersmayarbitrarydecidethesizeofsamplewithoutgiving
anyexplicitconsiderationtotheaccuracyofthesampleresultsorthecostofsampling.Thisarbitraryapproachshouldbeavoided.
• Forsomeoftheprojects,thetotalbudgetforthefieldsurvey(usuallymentioned)inaprojectproposalisallocated.Ifthecostofsamplingpersampleunitisknown,onecaneasilyobtainthesamplesizebydividingthetotalbudgetallocationbythecostofsamplingperunit.Thismethodconcentratesonlyonthecostaspectofsampling,ratherthanthevalueofinformationobtainedfromsuchasample.
• Thereareotherresearcherswhodecideonthesamplesizebasedonwhatwasdonebytheotherresearchersinsimilarstudies.Again,thisapproachcannotbeasubstitutefortheformalscientificapproach.
• Themost commonlyused approach for determining the sizeofsampleistheconfidenceintervalapproachcoveredunderinferentialstatistics.Belowwillbediscussedthisapproachwhiledeterminingthesizeofasampleforestimatingpopulationmeanandpopulationproportion.Inaconfidenceintervalapproach,thefollowingpointsaretakenintoaccountfordeterminingthesamplesizeinestimationofproblemsinvolvingmeans:
(a)The variability of the population:Itwouldbeseenthatthehigherthevariabilityasmeasuredbythepopulationstandarddeviation,largerwillbethesizeofthesample.Ifthestandarddeviationofthepopulationisunknown,aresearchermayusetheestimatesofthestandarddeviationfrompreviousstudies.Alternatively,theestimatesofthepopulationstandarddeviationcanbecomputedfromthesampledata.
(b)The confidence attached to the estimate:Itisamatterofjudgement,howmuch confidence youwant to attach to your estimate.Assuminganormaldistribution, thehigher theconfidencetheresearcherwantsfortheestimate,largerwillbesamplesize.Thisisbecausethevalueofthestandardnormalordinate‘Z’willvaryaccordingly.Fora90percentconfidence,thevalueof‘Z’wouldbe1.645andfora95percentconfidence,thecorresponding‘Z’valuewouldbe1.96andsoon(seeAppendix1attheendofthebook).Itwouldbeseenlaterthatahigherconfidencewouldleadtoalarger‘Z’value.
(c)The allowable error or margin of error:Howaccuratedowewantourestimate tobe isagainamatterof judgementof theresearcher.Itwillofcoursedependupontheobjectivesofthe
NOTES
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Construction of Sampling for Finite and Infinite
Populations
studyandtheconsequenceresultingfromthehigherinaccuracy.Iftheresearcherseeksgreaterprecision,theresultingsamplesizewouldbelarge.
Sample size for estimating population mean
Wehavelearntinthecentrallimittheoremthatthesamplingdistributionofthesamplemeanfollowsanormaldistributionwithameanandastandarderrorirrespectiveoftheshapeofpopulationdistributionwheneverthesamplesizeislarge.Symbolically,itmaybewrittenas:
xX N( , )s∩ µ
n×30Theabovealsoholdstruewheneversamplesaredrawnfromnormal
population.However,inthatcase,therequirementofalargesampleisnotthere.Thevariousnotationsareexplainedasunder:
X = Samplemean µ = Populationmean
Xs = Standarderrorofmean
n = Samplesize N = Populationsize s = PopulationstandarddeviationThevalueof:
/ nXs = s = / n
Xs = s (whensamplesaredrawnfromaninfinitepopulation)
= N nN 1n
s −=−
(whensamplesaredrawnfromafinitepopulation)
Theexpression N nN 1
−−
iscalledthefinitepopulationmultiplierand
neednotbeusedwhilesamplingfromafinitepopulation provided n 0.05.N
<
ThestandardnormalvariateZmaybewrittenas:
Z =X
x
− µs
Z= X
n
− µs
Z = X n− µs
Z =e n
s
Construction of Sampling for Finite and Infinite Populations
NOTES
Self-Instructional 108 Material
WhereX − µ=e=Marginoferror
∴ n=2 2
2Z
es
Itmaybenoted fromabove that the size of the sample is directlyproportional to thevariability in thepopulationand thevalueofZ for aconfidence interval. It varies inverselywith the size of the error. Itmayalsobenoted that thesizeofasampledoesnotdependupon thesizeofpopulation.Belowaregivensomeworkedoutexamplesforthedeterminationofasamplesize.Example 7.1: Aneconomistisinterestedinestimatingtheaveragemonthlyhouseholdexpenditureonfooditemsbythehouseholdsofatown.Basedonpastdata,itisestimatedthatthestandarddeviationofthepopulationonthemonthlyexpenditureonfooditemis`30.Withallowableerrorsetat`7, estimatethesamplesizerequiredata90percentconfidence.Solution:
90percentconfidence ⇒Z=1.645 e = ` 7 s = ` 30
n =2 2
2Z
es
=2 2
2(1.645) (30)
(7)
= 49.7025 = 50(approx.)
Example 7.2:Youaregivenapopulationwithastandarddeviationof8.6.Determinethesamplesizeneededtoestimatethemeanofthepopulationwithin±0.5witha99percentconfidence.Solution:
99percentconfidence ⇒Z=2.575 e = ±0.5 s = 8.6
n =2 2
2Z
es
=2 2
2(2.575) (8.6)
(0.5) = 1961.60 = 1962(approx.)
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Construction of Sampling for Finite and Infinite
Populations
Example 7.3: Itisdesiredtoestimatethemeanlifetimeofacertainkindofvacuumcleaner.Giventhatthepopulationstandarddeviations=320days,howlargeasampleisneededtobeabletoassertwithaconfidencelevelof96percentthatthemeanofthesamplewilldifferfromthepopulationmeanbylessthan45days?Solution:
96percentconfidence ⇒Z=2.055 e = 45 s = 320
n =2 2
2Z
es
=2 2
2(2.055) (320)
(45)
= 213.55 = 214(approx.)
Determination of sample size for estimating the population proportion
Ifthesampleproportionp isusedtoestimatethepopulationproportionp,
thestandarderrorof pp
s
would be pq ,n
whereq=1–p.Nowassuming
normaldistribution,wehave
p N
pqp,n
∩
Therefore, Z =p ppqn
−
Therefore,marginoferrore= p p Zpqn
− =
Z =epqn
Z =e npq
n =2
2Z pq
eTheaboveformulawillbeusedifthevalueofpopulationproportion
pisknown.If,however,pisunknown,wesubstitutethemaximumvalueofpqintheaboveformula.Itcanbeshownthatthemaximumvalueofpqis¼whenp=½andq=½.ThisisshowninFigure3.1.
Construction of Sampling for Finite and Infinite Populations
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Self-Instructional 110 Material
Therefore,2
2n1 Z4 e
=
Letusconsiderafewexamplesfordeterminingasamplesizewhileestimatingthepopulationproportion.Example 7.4: Amarketresearcherforaconsumerelectronicscompanywouldliketostudythetelevisionviewinghabitsoftheresidentsofaparticular,smallcity.Whatsamplesizeisneededifhewishestobe95percentconfidentofbeingwithin±0.035ofthetrueproportionwhowatchtheeveningnewsonatleastthreeweeknightsifnopreviousestimateisavailable?
Fig. 7.1 Graph of pq Corresponding to the Values of p
Solution:90percentconfidence ⇒Z=1.96 e = ±0.035
n =
2
2n1 Z4 e
=
=
2
21 (1.96)4 (0.035)
=784Example 7.5: Amanagerofadepartmentstorewouldliketostudywomen’sspendingperyearoncosmetics.Heisinterestedinknowingthepopulationproportionofwomenwhopurchasetheircosmeticsprimarilyfromhisstore.Ifhewantstohavea90percentconfidenceofestimatingthetrueproportiontobewithin±0.045,whatsamplesizeisneeded?
90percentconfidence ⇒Z=1.645 e = ±0.045
n =2
2n1 Z4 e
=
NOTES
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Construction of Sampling for Finite and Infinite
Populations =2
21 (1.645)4 (0.045)
= 334.0722 = 335(approx.)
Example 7.6: Aconsumerelectronicscompanywantstodeterminethejobsatisfaction levelsof itsemployees.For this, theyaska simplequestion,‘Areyousatisfiedwithyourjob?’Itwasestimatedthatnomorethan30percentoftheemployeeswouldansweryes.Whatshouldbethesamplesizeforthiscompanytoestimatethepopulationproportiontoensurea95percentconfidenceinresult,andtobewithin0.04ofthetruepopulationproportion?Solution:
95percentconfidence⇒Z=1.96 e = 0.04 p = 0.3 q = 0.7
n =
2
2Z pq
e
=
2
2(1.96) 0.3 0.7
(0.04)× ×
= 504.21 = 505(approx.)
Factors to be noted for sample size determination
Therearecertainissuestobekeptinmindbeforeapplyingtheformulasforthedeterminationofsamplesizeinthisunit.Firstofall,theseformulasareapplicableforsimplerandomsamplingonly.Further,theyrelatetothesamplesizeneededfortheestimationofaparticularcharacteristicofinterest.Inasurvey,aresearcherneedstoestimateseveralcharacteristicsofinterestsandeachoneofthemmayrequireadifferentsamplesize.Incasetheuniverseisdividedintodifferentstrata,theaccuracyrequiredfordeterminingthesamplesizeforeachstratamaybedifferent.However,thepresentmethodwillnotabletoservetherequirement.Lastly,theformulasforsamplesizemustbebaseduponadequateinformationabouttheuniverse.
7.3 SAMPLING AND NON-SAMPLING ERRORS
Therearetwotypesoferrorthatmayoccurwhilewearetryingtoestimatethepopulationparametersfromthesample.Thesearecalledsamplingandnon-samplingerrors.
Construction of Sampling for Finite and Infinite Populations
NOTES
Self-Instructional 112 Material
I. Sampling Error
Thiserrorariseswhenasampleisnotrepresentativeofthepopulation.Forexample,ifourpopulationcomprises200MBAstudentsinabusinessschoolandwewanttoestimatetheaverageheightofthese200studentsbytakingasampleof10(say).Letusassumeforthesakeofsimplicitythatthetruevalueofpopulationmean(parameter)isknown.Whenweestimatetheaverageheightofthesampledstudents,wemayfindthatthesamplemeanisfarawayfromthepopulationmean.Thedifferencebetweenthesamplemeanandthepopulationmeaniscalledsamplingerror,andthiscouldarisebecausethesampleof10studentsmaynotberepresentativeoftheentirepopulation.Supposenowweincreasethesamplesizefrom10to15,wemayfindthatthesamplingerrorreduces.Thisway,ifwekeepdoingso,wemaynotethatthesamplingerrorreduceswiththeincreaseinsamplesizeasanincreasedsamplemayresultinincreasingtherepresentativenessofthesample.
Reducing the sampling errors
Thefollowingmethodsareusefulinreducingsamplingerrors: (i) Increase in the size of the sample: As already mentioned, the
samplingerrorcanbereducedbyincreasingthesamplesize.Ifthesamplesizeequalsthepopulationsize,thenthesamplingerroriszero.
(ii) Stratification:Asimplerandomsampleislikelytoberepresentativeof the population if the population contains homogeneous units.However,whenthepopulationconsistsofdissimilarunits,asimplerandomsamplemaynotberepresentativeofalltypesofunitsinthepopulation.Inordertoimprovetheresultofthesample,thesampledesign ismodified.Thepopulation isdivided intodifferentgroupscomprisingsimilarunits.Thesegroupsarereferredtoasstrata.Fromeachgroup(stratum),asub-sampleisselectedinarandommanner.Asaresult,allthegroupshaverepresentationinthesample,reducingthesamplingerror.Itisknownasstratified-randomsampling.
II. Non-Sampling Error
Thiserrorarisesnotbecauseasampleisnotarepresentativeofthepopulationbutbecauseofotherreasons.Someofthesereasonsarelistedbelow: •Therespondentswhenaskedforinformationonaparticularvariable
maynotgivethecorrectanswers.Ifapersonaged48isaskedaquestionabouthisage,hemayindicatetheagetobe36,whichmayresultinanerrorandinestimatingthetruevalueofthevariableofinterest.
•Theerrorcanarisewhiletransferringthedatafromthequestionnairetothespreadsheetonthecomputer.
•Therecanbeerrorsatthetimeofcoding,tabulationandcomputation.
NOTES
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Construction of Sampling for Finite and Infinite
Populations
• Ifthepopulationofthestudyisnotproperlydefined,itcouldleadtoerrors.
•Thechosenrespondentmaynotbeavailabletoanswerthequestionsormayrefusetobepartofthestudy.
•Theremaybeasamplingframeerror.Supposethepopulationcompriseshouseholdswithlowincome,highincomeandmiddleclasscategory.The researchermight decide to ignore the low-income categoryrespondentsandmaytakethesampleonlyfromthemiddleandthehigh-incomecategorypeople.
Reducing non-sampling errors
Non-samplingerrorsareafractionofthetotalerrorarisingfromperforminga statistical analysis.Thebalanceof the total error arises fromsamplingerror.Unlikesamplingerror, increase in thesamplesizedoesnot reducenon-samplingerror. In fact, it is practically impossible to eliminatenon-samplingerrorsentirely.However,wecanreducenon-samplingerrors inthefollowingways: • Improving survey processes: Non-samplingerrorscanbereducedby
improvingsurveyprocesses.Thesurveyshouldrelyonthecollectionandanalysisofdatarelatingtoeditingperformanceaswellastothesources,typesanddistributionoferrorsinthedata.
• Systematic and orderly specification of edits: Formitigation ofnon-samplingerrors, there isaneed for thesystematicandorderlyspecificationofeditsand that theamendmentofdata shouldoccuronlyinresponsetoimportanterrors.Abalanceshouldessentiallybeachievedbetween:o Editsappliedinthefieldandthoseappliedintheofficeo Automatedandclericalapproachestoverificationandamendment
oferrorso Useofmicroandmacro-editingmethods
• Use of computer-assisted telephone interviewing (CATI) and computer-assisted personal interview (CAPI) systems: Thesesystemsallowforgreatercontrolthanthenormalpaperquestionnairedoes.Thereislessleewayforinterviewerstocommitmistakes.Further,theintegrationofdatacollection,dataentryandeditingbringsdownthechancesoferrorsinthesesystems.Thesesystemshavethetechnologyto provide immediate feedback of possible errors.This helps theinterviewerqueryduringtheinterview.
• Use of computer-assisted coding systems and automated coding systems:Thesecodingsystemshavethepotentialformoreaccurateandlessexpensivecodingsystems.Further,theyresultinmoreconsistentcoding.
Construction of Sampling for Finite and Infinite Populations
NOTES
Self-Instructional 114 Material
7.3.1 Biased Sample
Thepurposeofresearchistoestimateanunbiasedstatisticthatrepresentsthetrueparameterforapopulation.Biasisdefinedasapredispositiontooneparticularoutcomeoveranother.Biasinresearchleadstounrepresentativeoutcomes.Inotherwords,biascausesresearchers’estimatestobepredisposedtotheleftortotherightofthetruemark.
Statistical estimates rely on random error, and bias introducessystematicerror into theresearchdesignoranalysis, renderingoutcomesunreliableormeaningless.Randomerrorisunpredictable,whilesystematicerrorispredictable.Obtainingabiasedestimatecanbetheresultofoneormoremistakesmadebefore,during,orafterastudy.
Asamplethatisnotrepresentativeofthepopulationfromwhichitwasdrawniscalledabiasedsample.
Check Your Progress
1.Whatdoesasizeofasampledependupon? 2.Definesamplingerror. 3.Whatdoesbiasinresearchleadto?
7.4 ANSWERS TO CHECK YOUR PROGRESS QUESTIONS
1.The sizeof a sampledependsupon thebasiccharacteristicsof thepopulation,thetypeofinformationrequiredfromthesurveyandthecost involved.
2.Thedifferencebetweenthesamplemeanandthepopulationmeaniscalledsamplingerror.
3.Biasinresearchleadstounrepresentativeoutcomes.Inotherwords,biascausesresearchers’estimatestobepredisposedtotheleftortotherightofthetruemark.
7.5 SUMMARY
•Thesizeof a sampledependsupon thebasiccharacteristicsof thepopulation,thetypeofinformationrequiredfromthesurveyandthecostinvolved.Therefore,asamplemayvaryinsizeforseveralreasons.
•Researchersmayarbitrarydecidethesizeofsamplewithoutgivinganyexplicitconsiderationtotheaccuracyofthesampleresultsorthecostofsampling.
NOTES
Self-InstructionalMaterial 115
Construction of Sampling for Finite and Infinite
Populations
• Inasurvey,aresearcherneedstoestimateseveralcharacteristicsofinterestsandeachoneofthemmayrequireadifferentsamplesize.
•Thereare twotypesoferror thatmayoccurwhileweare tryingtoestimatethepopulationparametersfromthesample.Thesearecalledsamplingandnon-samplingerrors.
•Asamplingerrorariseswhena sample isnot representativeof thepopulation.
•Anon-samplingerrorarisesnotbecauseasampleisnotarepresentativeofthepopulationbutbecauseofotherreasons.
•Non-sampling errors are a fraction of the total error arising fromperformingastatisticalanalysis.Thebalanceofthetotalerrorarisesfromsamplingerror.
•Unlike samplingerror, increase in the sample sizedoesnot reducenon-samplingerror.
•The purpose of research is to estimate an unbiased statistic thatrepresentsthetrueparameterforapopulation.
•Asamplethatisnotrepresentativeofthepopulationfromwhichitwasdrawniscalledabiasedsample.
7.6 KEY WORDS
• Field Survey: Itisatypeoffieldresearchbywhicharchaeologistssearch for archaeological sites and collect information about thelocation,distributionandorganizationofpasthumanculturesacrossalargearea.
• Non-Sampling Error: It is a catch-all term for the deviations ofestimatesfromtheirtruevaluesthatarenotafunctionofthesamplechosen,includingvarioussystematicerrorsandrandomerrorsthatarenotduetosampling.
• Bias:Itisdisproportionateweightinfavouroforagainstonething,person,orgroupcomparedwithanother,usuallyinawayconsideredtobeunfair.
7.7 SELF ASSESSMENT QUESTIONS AND EXERCISES
Short Answer Questions
1. What are thepoints that need tobe taken into considerationwhiledeterminingsamplesize?
Construction of Sampling for Finite and Infinite Populations
NOTES
Self-Instructional 116 Material
2.Howdowereducenon-samplingerrors? 3.Writeashort-noteonbiasedsample.
Long Answer Questions
1. Describethemethodsfordeterminingsamplesize. 2.Whatissamplingerror?Howcanresearchersreducesamplingerrors? 3. Illustratehowtodeterminesamplesizeforestimatingpopulationmean.
7.8 FURTHER READINGS
Creswell,JohnW.2002.Research Design: Qualitative, Quantitative, and Mixed Methods Approaches.London:SagePublicationsInc.
Booth,Wayne,GregoryG.ColombandJosephM.Williams.1995.The Craft of Research.Chicago:UniversityofChicagoPress.
Bryman,AlanandEmmaBell.2015.Business Research Methods.4thEdition.UnitedKingdom:OxfordUniversityPress.
Gupta,S.L.andHiteshGupta. 2012. Business Research Methods. NewDelhi: TataMcGrawHillEducationPrivateLimited.
NOTES
Self-InstructionalMaterial 117
Sources and Collection of Data-IUNIT 8 SOURCES AND
COLLECTION OF DATA-IStructure 8.0 Introduction 8.1 Objectives 8.2 SourcesofData:PrimaryDataandSecondaryData 8.3 ModesofDataCollection
8.3.1 Interview:Types,Conduct,Preparation,EffectiveTechniquesandLimitation
8.3.2 Observation:TypesandTechniques 8.4 AnswerstoCheckYourProgressQuestions 8.5 Summary 8.6 Key Words 8.7 SelfAssessmentQuestionsandExercises 8.8 FurtherReadings
8.0 INTRODUCTION
Inthisunit,youwillbeintroducedtotheprocessofdatacollection.Primarydatacanbeobtainedthroughobservationsorthroughdirectcommunicationwiththepersonsassociatedwiththeselectedsubjectbyperformingsurveysordescriptiveresearch.Atelephonicinterviewisalsousuallylimitedtotwopersons.However,itisconductedoverthetelephone.Telephonicinterviewsaregenerallyconsideredastheinitialmethodsforscreeningthecandidatesforpersonalinterviews.Observationmethodscanbecategorizedintodifferenttypesdependingonvariousfactorssuchasstyleforrecordingtheobservedinformation,dataneededforobservationandactivityoftheobserver.Theinformationorthequestionsincludedinthescheduleshouldbeaccurateandshouldenabletherespondenttobetterunderstandthecontextinwhichthequestionsareasked.
8.1 OBJECTIVES
Aftergoingthroughthisunit,youwillbeableto; •Discussthedifferentsourcesofdata •Describethetypesandmethodsofobservation •Explainthetypesandlimitationsofinterview
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8.2 SOURCES OF DATA: PRIMARY DATA AND SECONDARY DATA
Therearevariousmethodsofdatacollectionwhichhelptheusertogatherandcompileinformationfromvariouslocations.
Tounderstandthemultitudeofchoicesavailabletoaresearcherforcollecting the project/study-specific information, one needs to be fullycognizantoftheresourcesavailableforthestudyandthelevelofaccuracyrequired.Toappreciatethetruthofthisstatement,oneneedstoexaminethegamutofmethodsavailabletotheresearcher.Thedatasourcescouldbeeithercontextualandprimaryorhistoricalandsecondaryinnature.
Primary data asthenamesuggestsisoriginal,problem-orproject-specificandcollectedforthespecificobjectivesandneedstobespeltoutbytheresearcher.Theauthenticityandrelevanceisreasonablyhigh.Themonetaryandresourceimplicationsofthisarequitehighandsometimesaresearchermightnothavetheresourcesorthetimeorbothtogoaheadwiththismethod.Inthiscase,theresearchercanlookatalternativesourcesofdatawhichareeconomicalandauthenticenoughtotakethestudyforward.Theseincludethesecondcategoryofdatasources—namelythesecondarydata.
Secondarydata asthenameimpliesisthatinformationwhichisnottopicalorresearchspecificandhasbeencollectedandcompiledbysomeotherresearcherorinvestigativebody.Thesaidinformationisrecordedandpublishedinastructuredformat,andthus,isquickertoaccessandmanage.Secondly,inmostinstances,unlessitisadataproduct,itisnottooexpensivetocollect.Assuggestedintheopeningvignette,thedatatotrackconsumerpreferences is readily available and the information required is readilyavailableasadataproductorastheauditinformationwhichtheresearcherortheorganizationcanprocure.
8.3 MODES OF DATA COLLECTION
Thereareseveralmethodsofcollectingprimarydata,whichareasfollows: (a) Interviewmethod (b)Observationmethod (c)Surveymethod (d)Questionnairemethod (e)Schedulemethod (f)Scalingtechnique
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(g)Othermethodsarewarrantycards,distributoraudits,pantryaudits,consumer panels, usingmechanical devices, through projectivetechniques,depthinterviewsandcontentanalysis.
8.3.1 Interview: Types, Conduct, Preparation, Effective Techniques and Limitation
Interviewis themethodofcollectingdata that involvesapresentationoforalandverbalstimuliandthereplyintermsoforalandverbalresponses.Interviewinvolvesbothpersonalinterviewaswellastelephonicinterview.
Personal interviews
Personalinterviewinvolvestwopeople:theinterviewerandtheinterviewee.Theintervieweristhepersonwhoquestionstheinterviewee.Thereisaface-to-facediscussionbetweenthem.Therecanbemorethanoneinterviewerwhiletakingapersonalinterview.Therearetwotypesofinterviews:directpersonalinterviewandindirectoralinterview.
In a direct personal interview, the interviewer collects informationfromtheconcernedsources.Heshouldbepresentat thesitefromwherethedatahastobecollected.Thismethodismostappropriateforintensiveinvestigationsbutthismethodmaynotbesuitableinthesituationswhereadirectcontactwiththeconcernedpersonisnotpossible.Insuchcases,anindirectoralexaminationorinvestigationtakesplacewheretheinterviewercross-examinestheintervieweetocheckhisknowledgeabouttheproblemunder investigation.The informationexchangedbetween the intervieweeandtheinterviewerisrecordedforfuturereference.
Personalinterviewscanbeofthefollowingtypes:• Structured interviews:Ifthepersonalinterviewtakesplaceina
structuredway,itiscalledastructuredinterview.Inthistypeofpersonalinterview,thesetofquestionstobeaskedarepredefinedand the techniques used to record the information are highlystandardized. Structured interviews are economical, as they donot requiremuch information from the interviewer. Structuredinterviewsareusedasamaintechniquetocollectinformationindescriptiveresearchstudies.
• Unstructured interviews: If thepersonal interview takesplaceinanunstructuredway, itmeans, that thequestions tobeaskedto the interviewee are decided at the timeof interview. In thistypeof personal interview, the set of questions to be asked arenotpredeterminedandtherearenostandardisedtechniquesused.Alistofadditionalquestionsisprovidedtotheintervieweranditdependsonhimtoaskthesequestionsornot.Thismethoddemandsdeepknowledgeandgreaterskillsoftheinterviewer.Youcanuse
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unstructuredinterviewasamaintechniquetocollectinformationintheexplorativeandformulativeresearchstudies.
Telephonic interview
Atelephonicinterviewisalsousuallylimitedtotwopersons;however,itisconductedoverthetelephone.Telephonicinterviewsaregenerallyconsideredastheinitialmethodsforscreeningthecandidatesforthepersonalinterviews.Thisinvolvestestingthevariousskillsoftheintervieweethatincludeverbalreasoningandoralcommunicationskills.Someoftheimportanttipsfortheintervieweeinatelephonicintervieware:
• Mustkeeptheresumeinfrontofhim/her.• Shouldkeeptheemployerresearchmaterialswithineasyreach.• Shouldkeepanotepadtohighlighttheimportantrationaleofthe
interview.• Shouldtalkinacalmandcoolmanner.• Shouldsoundprofessionalwhenansweringthequestions.
Limitations of interview method
• Thismethodistimeconsuming.• It isdifficult togeneralizethefindingsduetosmallsamplesize
usedinthismethod.• Theinterviewermaybebiased.Thiswouldmakehimaskclose-
endedquestions,whichaffectsthevalidityandreliabilityofinterview.Givenbelowisaninterviewguidecreatedforabeveragepurchase
andconsumptionstudy.
Interview guide: beverage purchase and consumption Introduction and Warm Up
Hi,Iamconductingashortsurveyonsoftdrinkconsumption.Thus,Iwouldjusttakesomeinsightsfromyouonyourpurchase.Therearenorightorwronganswers,however,sinceyouconsumesoftdrinks,youropinionisreallyimportantforunderstandingthepurchasebehaviour. 1. Tellmesomethingaboutyourselves…whatdoyoudo—asinoccupation…your
hobbies…yourinterests?Howwouldyoudescribeyourselfasaperson?Doyougenerallyplanandbuy….
2. PROBE FURTHER – PSYCHOGRAPHICS/LIFESTYLE 3. PURCHase behaviour : 4. Thissoftdrinkthatyouhavepurchased….howdoyougenerallyconsumeit….
Chilled/cool,can/bottle,standaloneormixedwithsomething. 5. IfIweretoaskyoutolistoccasionsforsoftdrinks’purchase,theywouldbe: ________________________________________ ________________________________________ ________________________________________
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Sources and Collection of Data-I 6. Sowhenyouaremakingthispurchase,whattriggersit:
•brand • price •deals •taste •packaging •anyother_____________
PROBEALLATTRIBUTESFORREASONS.For example, what kind of deals? Packaging? brand image?
7. Supposingyour favouritebrand isnot available forpurchase…..whatdoyoudo…….(PROBE)……do youmove on to another store or pick up anotherbrand……(PROBE)…….reason(s)
8. Supposingacompanychangesitspackagingsothatitisreallyeyecatching,whatisyourreactiontoit……(PROBE)……reason(s)
9. EXPOSE PICTURE Iamgoingtoshowyousomedisplaypictures.Pleasetellmewhichonedoyou
think looksattractive….. (let the respondent select)…….(PROBEreasons forliking)……wouldthismovecustomerstogoandlookaroundandpurchase…….(reason)……..woulditinfluenceyoutobuy…..(reasons)
10. EXPOSE PICTURE Iamgoingtoshowyouapictureofastore.Wherewouldyougenerallyexpect
thesoftdrinkstobeplaced…..inyouropinion,isthistherightplaceorcanitbeputsomewhereelse…..REASON
11. Buyonegetonefree,afreebie,coupons,prizes.Doyougetmovedtotryoutandbuysomeofthese?.......whichonesdidyoutry……REACTION
12. Softdrinkscompaniescomeupwithalotofads….canyoutellmesomethingaboutsomeads?Whatdoyourecall……..(note-degreeofrecallandifbrandrecalledwastherightmatch)……..diditinfluenceyourpurchaseofthedrink.PROBE
Thankyou.
8.3.2 Observation: Types and Techniques
Theobservationmethodisthemostcommonmethodtostudybehaviouralsciences.Observationisnotascientificmethodbutitbecomesascientifictoolwhenitisusedforformulatingthepurposeofresearch.Inthismethod,theinformationcollectedbytheresearcheristotallybasedonhisobservation.Forexample,iftheresearcherisstudyingaboutdifferentbrandsofshoes,hewillnotaskthepersonwearingshoesofaparticularbrand.Ratherhewillobserveitbyhimselfandcometosomeconclusion.Themainadvantageofthismethodisthattherearenochancesofpartialityiftheobservationisdoneaccurately.Secondly,theinformationorthedatacollectedthroughobservationisrelatedtowhatiscurrentlyhappening,itisnotaffectedbythepastbehaviourorfutureintentions.Thirdly,thismethodisindependentofaperson’swillingnesstorespondanddoesnotrequiremuchcooperationonthepartoftheperson,asithappenstobethecaseinintervieworquestionnairemethod.Observation
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methodissuitableinthosesituationswheretherespondentisnotcapableofexpressingthefeelingsverbally.
Types of observation method
Observationmethodscanbecategorizedintodifferenttypesdependingonvariousfactorssuchasstyleforrecordingtheobservedinformation,dataneededforobservationandactivityoftheobserver.Followingarethedifferenttypesofobservationmethods: • Structured observation: It isanobservationmethod inwhich the
followingpointsneedtobeconsidered:o Carefuldefinitionofthematterthatneedstobeobserved.o Identificationofthestylethatmustbeusedtorecordtheobserved
information.o Standardizationoftheconditionofobservation.o Selectionofthedatarequiredforobservation.
Thismethodismostappropriatewhereadescriptivestudyofthematterunderobservationisrequired.
• Unstructured observation:Itisanobservationmethodinwhichacarefuldefinitionofthemattertobeobserved,thestyletoberecorded,standardizedconditionofobservationandtheselectionoftherequireddata of observation are not properly known.Thismethod ismostappropriatewhereanexploredstudyofthematterunderobservationisrequired.
• Participant observation: It isanobservationmethodinwhichtheobserver isalsoamemberof thegrouphe isobserving inorder tounderstandtheneedsandtheproblemsfacedbythegroupinabetterway.Forexample,ateamleaderwhoobservesallhisteammembersandalsodoesthesameworkashisteammembers.Thereareseveraladvantagesofparticipantobservation,whichare:o Theresearcherisabletorecordthenaturalbehaviourofthegroup.o The researcher can even gather information,which could not
otherwise easily be obtained if he observes from an isolatedsituation.
o The researchercanevenverify the truthof statementsmadebyinformantsinthecontextofthequestionnairesoraschedule.
• Non-participant observation: Itisanobservationmethodinwhichtheobserver isnotamemberof thegroupunderobservation.Thismethodhasadisadvantagethattheobserverisunabletosensewhattheotherteammembersfeel.
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• Disguised observation: It is an observationmethod inwhich themembers of the group are unaware of the fact that they are beingobserved.
• Controlled observation: Theobservationthattakesplaceaccordingtodefinitepre-arrangedplans,involvingexperimentalproceduresiscalledcontrolledobservation.
• Uncontrolled observation: Theobservation that takesplace in thenaturalsettingiscalledtheuncontrolledobservation.Themainaimofthisobservationistohavespontaneouspictureofthesituationandforthistheprimerequirementissufficienttime.
Limitations of observation method
Though observationmethods provide differentways for studying thebehaviouralscience,therearesomelimitationswhileusingthesemethods.Followingarethelimitationsofobservationmethods: •Allobservationmethodsaregenerallyexpensive. • Itprovidesverylimitedinformationregardingtheobservedmatter. • Itmaybeaffectedbysomeunwantedfactors.Forexample,people
whoarenotinvolvedinthedirectobservationmightcreateaproblemwhilecollectingdatathroughobservationmethods.
Points to be considered while doing observation
Intheobservationmethods,researchersmustkeepinmindthefollowingpointsatthetimeofobservinganyinformation: •Whatshouldbeobserved? •Howtheobservationshouldberecorded? •Howtheaccuracyoftheobservationcanbeensured?Anexampleofobservationsheetisgivenbelow:
Observation Sheet: Organic RetailerNameofStore: Location: SizeofStore:Storepersonnel(number):Storepersonnel(attitude):Storeatmosphere:ApproximatefootfallsWeekdays: weekendsPercentageofconversionsWeekdays: weekends
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Please mark (•) the items in stock
Product Stock Product StockTea CEREALSOrganicTea AmaranthFlavoured AmaranthPoppedSnacks AmaranthBreakfastCerealCookies(Ragi/Ramdana) JhangaraBread RagiNamkins RagiAttaSpices MaizeChilliPowder MaizeAttaChilliRed WheatAttaDhaniaPowder WheatDaliaDhaniaSeeds WheatPuffedHaldiWhole PULSESHaldiPowder ArharDalMustardPowder BhattDalSesame/Til KulathDalZeera MasoorDalPRESERVES MoongSabutMangoPickle MoongDalGarlicPickle KabuliChannaMixedPickle NaurangiDalAmlaChutney Rajma(Brown/White)GingerAle Rajma(Chitkabra)BuransSquash Rajma(Mix)LemonSquash Rajma(RedSmall)MaltaSquash UradDalPudinaSquash UradWhole
RICEANYOTHER BasmatiDehradun
RiceKhandaRiceRikhwaRiceUnpolishedRiceHansraj
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Sources and Collection of Data-IRiceRed
RiceKasturiRiceKelasRicePunjabBasmatiRiceRamjavanRiceSela
Check Your Progress
1.Whatisprimarydata? 2.Whatisnon-participantobservation? 3.Whatisuncontrolledobservation?
8.4 ANSWERS TO CHECK YOUR PROGRESS QUESTIONS
1.Primarydataas thenamesuggests isoriginal,problem-orproject-specificandcollectedforthespecificobjectivesandneedstobespeltoutbytheresearcher.
2. Itisanobservationmethodinwhichtheobserverisnotamemberofthegroupunderobservation.
3.Theobservation that takesplace in thenatural setting is called theuncontrolledobservation.
8.5 SUMMARY
•Therearevariousmethodsofdatacollectionwhichhelptheusertogatherandcompileinformationfromvariouslocations.
•Primarydataas thenamesuggests isoriginal,problem-orproject-specificandcollectedforthespecificobjectivesandneedstobespeltoutbytheresearcher.
•Thereareseveralmethodsofcollectingprimarydata,whichareasfollows:
(a) Interviewmethod (b)Observationmethod (c)Surveymethod (d)Questionnairemethod (e)Schedulemethod
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(f)Scalingtechnique (g)Othermethodsarewarrantycards,distributoraudits,pantryaudits,
consumerpanels,usingmechanicaldevices,throughprojectivetechniques,depthinterviewsandcontentanalysis.
• Interviewisthemethodofcollectingdatathatinvolvesapresentationoforalandverbalstimuliandthereplyintermsoforalandverbalresponses. Interview involves both personal interview aswell astelephonicinterview.
•Personal interview involves two people: the interviewer and theinterviewee. The interviewer is the person who questions theinterviewee.
•The observationmethod is themost commonmethod to studybehavioural sciences.Observation is not a scientificmethodbut itbecomesascientifictoolwhenitisusedforformulatingthepurposeofresearch.
•Observationmethodscanbecategorizedintodifferenttypesdependingonvariousfactorssuchasstyleforrecordingtheobservedinformation,dataneededforobservationandactivityoftheobserver.
8.6 KEY WORDS
• Secondary Data: Itreferstodatawhichiscollectedbysomeonewhoissomeoneotherthantheuser.
• Interview: Itreferstoameetingofpeoplefacetoface,especiallyforconsultation.
• Observation: Itmeanstheactionorprocessofcloselyobservingormonitoringsomethingorsomeone.
8.7 SELF ASSESSMENT QUESTIONS AND EXERCISES
Short Answer Questions
1. Whatarethevariousmethodsofdatacollection? 2.Whatareunstructuredinterview?
Long Answer Questions
1. What is personal interview?Discuss the various types of personalinterview.
2.Examinethetypesandtechniquesoftheobservationmethod.
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Sources and Collection of Data-I8.8 FURTHER READINGS
Creswell,JohnW.2002.Research Design: Qualitative, Quantitative, and Mixed Methods Approaches.London:SagePublicationsInc.
Booth,Wayne,GregoryG.ColombandJosephM.Williams.1995.The Craft of Research.Chicago:UniversityofChicagoPress.
Bryman,AlanandEmmaBell.2015.Business Research Methods.4thEdition.UnitedKingdom:OxfordUniversityPress.
Gupta,S.L.andHiteshGupta. 2012. Business Research Methods. NewDelhi: TataMcGrawHillEducationPrivateLimited.
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BLOCK - III
TOOLS OF DATA COLLECTION
UNIT 9 SOURCES AND COLLECTION OF DATA-II
Structure 9.0 Introduction 9.1 Objectives 9.2 Questionnaire:Meaning,TypesandFormatofaGoodQuestionnaire 9.3 Schedule:Meaning,Kinds,Essentials,ProcedurefortheFormulationofa
Schedule 9.3.1 SchedulesVs.Questionnaires
9.4 AnswerstoCheckYourProgressQuestions 9.5 Summary 9.6 Key Words 9.7 SelfAssessmentQuestionsandExercises 9.8 FurtherReadings
9.0 INTRODUCTION
Inthepreviousunit,youwereintroducedtotheprocessofdatacollection.Inthisunit,thediscussiononthecollectionofdatawillcontinue.Asyoulearnt,thereareessentiallytwosourcesofdata,thatis,primaryandsecondarydata.Twooftheimportantmethodsofcollectingprimarydataareinterviewsandschedule.Wewilldiscusstheseindetailintheunit.
9.1 OBJECTIVES
Aftergoingthroughthisunit,youwillbeableto: •Discussthemeaningandtypesofquestionnaire •Explainthetypesandcharacteristicsofaschedule •Differentiatebetweenquestionnaireandschedule
9.2 QUESTIONNAIRE: MEANING, TYPES AND FORMAT OF A GOOD QUESTIONNAIRE
Thequestionnaireformisanimportantandcommonlyusedmethodofdatacollection.Itisusedmostlyincaseoflarge-scaleenquiries.Thecategoriesof
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enduserswhousethistechniqueincludeindividuals,researchworkers,privateandpublicorganisationsandgovernments.Aquestionnaireisadocumentthatcontainsasetofquestionsprintedortypedinapropersequence.Thequestionnaireissenttoeachindividualwhoissupposedtoanswerit.Thistechniqueofcollecting information throughquestionnaires is extensivelyusednowadays.Thefollowingaretheadvantagesofaquestionnaire: • Itiscost-effective. •Astherespondentsareallowedtoanswerthequestionsaccordingto
theirownviewsandunderstanding,thistechniqueofdatacollectionisnon-partial.
•Alltherespondentsofthequestionnaireareprovidedenoughtimetoanswerthequestions.
• Inthistechnique,alargesampleofquestionscanbeusedtomaketheresultsmorereliable.Inaddition to theadvantagesmentionedabove,questionnairesalso
havecertaindisadvantages.Thedisadvantagesareasfollows: •This technique has possibilities of no-response. Itmeans that the
respondentsmayormaynotprovideanswerstoallthequestionsasked. •This techniquecanbeusedonly if the respondents are skilledand
supportive. •Therearepossibilitiesofvaguerepliesbysomerespondents. • Itisnotpossibletodeterminewhetherornotaparticularcandidateis
appropriatetogiveinformationaboutaparticularsubject. • Itisatimeconsumingtechnique.
Inaquestionnaire,theuseofstandardizedquestionscanhelpcollectmoredatathatisreliable.Byusingquestionnaires,thesystemanalystcancollectvaluableinformationfromthepeopleintheorganisationwhomaybeaffectedbythecurrentandproposedsystem.
Thevarioustasksperformedduringthequestionnairemethodareasfollows: •Acquiring information before conducting the interviewwith the
questionnaire. •Gaininginformationinordertoprovefactsfoundintheinterview. •Acquiringinformationon‘Howusersfeelaboutthecurrentsystem?’ • Isthereanyproblemthatremainsunsolved? •Whatdopeopleexpectfromanewormodifiedsystem?
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Thefollowingarethesituationsduringwhichthequestionnairesshouldbeused: • If the people to be questioned belongs to different departments or
branchesofthesameorganisation. • Iftheprojectinvolvesalargenumberofpeopleandyouwanttoknow
whatproportionofagivengroupapprovesordisapprovesofaparticularfeatureoftheproposedsystem.
• Ifyouwanttodeterminetheoverallopinionbeforethesystemsprojectisgivenanyconsiderationforimplementation.Questionsincludedinaquestionnairecanbeeitherclosedendedor
open ended.
Open-ended questions
Openendedquestionsarequestionswhichdonotrequirespecificresponses.Examplesofthistypeofquestionsareasfollows: •Howwillyouevaluatethebenefitsofanewinstalledsystem? •HowwillyoudesigntheManagementInformationSystem? •Whatisyouropinionaboutthecurrentincometaxpolicy?
Closed-ended questions
Closedendedquestionsarethequestions,whichareusedwhenthesystemsanalystisabletoeffectivelylistallpossibleresponsestothequestion.Allpossibleresponsesoftheclosedquestionsshouldbemutuallyexclusive.Thistypeofquestionsarecategorizedintothefollowingtypes: • Fillintheblanksquestions •Dichotomousquestions •Rankingscalequestions •Multiplechoicequestions •Ratingscalequestions
Fill in the blanks questions
These are questionswhich require specific responses that are analysedstatistically.Theexamplesofthistypeofquestionsare: •Whatisyourname? •Whatisthenameofyourorganisation? •Howmanyemployeesarethereintheaccountsdepartmentofyour
organisation? •Howmanyautomatedsystemsareinstalledinyourorganisation?
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Dichotomous questions
Dichotomousquestionsarequestionswhichoffertwoanswers,YesorNo.Theexamplesofthistypeofquestionsare: •Areyouworkingwithmanualsystems? YesorNo • Ifyes,doyouneedtoswitchovertotheautomatedsystems? YesorNo • Ifno,areyousatisfiedwiththeperformanceofmanualsystems? YesorNo
Ranking scale questions
Rankingscalequestionsallowtheresearchertoarrangethelistofitemsintheorderoftheirimportanceandpreference.Considerthefollowingquestion:
Pleasearrangethefollowinginalphabeticalorder:• London• America• India• Italy
Multiple choice questions
Thesetypesofquestionsallowyoutoselectanoptionfromalistofoptions.Theexamplesofthistypeofquestionare: •Whatisthenumberofautomatedsystemsusedinyourorganisation?
o 0–9o 10–19o 20–29o Morethan29
•Whatisthetypeoforganisationyouareworkingwith?o Banko ManufacturingCompanyo Computer/ITSectoro Other
Rating scale questions
Inthistypeofquestions,auserisrequiredtoratetheoptionsaccordingtohisopinion.Theexamplesofthistypeofquestionareasfollows:Howskilledyouareinyourwork?(Helpsinratingyourskills)
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Once Twice Manytimes Never• Numberoftimesyougotpromotion. 1 2 3 4• Numberoftimesyoureceivedappreciation. 1 2 3 4
• Numberoftimesyouarecriticizedforwork. 1 2 3 4
Designing a questionnaire
Questionnaireprovidesadatacollectiontechniqueinwhichwrittenquestionsarepresentedthataretoansweredbythepeopleinwrittenform.Thepointsthatshouldbekeptinmindwhiledesigningaquestionnaireareasfollows: •Thegoalofthequestionnairemustspecifythepurposeofdetermining
whomyouwillsurveyandwhatwillyouaskthem. •Thequestionsinthequestionnairemustnotbeconfusingandunfamiliar.
Itshouldbeeasytounderstand,shortandsimplesothatitiseasytocomplete.
•Thequestionsinthequestionnairemustbeproperlystated.Itshouldnotcontainanyprivatequestionsregardingthesalary,age,etc.
•Thequestionsplacedoutoforderoroutofcontextshouldbeavoided.Thereshouldbespecificquestions,whichcanbefollowedbygeneraleasy-to-answerquestions.
•Theperiodortimemustbestatedinwhichthequestionnairecanbecompleted.
•The performance of the questionnaire should be determined bypretestingit.
•Thequestionnaireshouldbefinallyreviewedandeditedtoensurethatthequestionnaireisreadyforadministration.
•Thetypeofquestionnaireshouldbeproperlydefined.Reliable and valid questionnaires are designed using the scaling
construction technique.According to this technique, the researchermustfocusonthequestioncontent,questionwordingandquestionformat.Pleaserefertoappendicestoo.
A Specimen questionnaire
This hypothetical study is adapted from a study developed byDeepakMehendru*inIndia.Assumethatthisstudyinvolves200professorsinIndiaareacollegeswhoareaskedabouttheirinterestinbuyingautomobiles.ThebasicobjectiveofthissurveyistodeterminecertainmarketingtrendsamongthepopulationofprofessorsinIndiaarearegardingtheirautomobilebuyingpatternsandarebaseduponthefollowingfactors: •Theprofileofthedecision-makerwhofinallydecidestobuyaparticular
typeofcar.
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• Peoplearoundthedecision-makerwhoinfluencethedecision-makingprocess.
•Thefactorsaffectingtheselectionofaparticulardealerofcars. • People in the familywhomake or affect decisions regarding the
maximumbudgetthatcanbeallocatedforpurchasingacar. •Theeffectofvariousoptionsavailableinthecar. •Theimageandreliabilityofthecompanythatmakesthesecars. •Theeffectofheavypromotionontelevisionabouttheutilityofthecar
onthedecisionmaker.(Forthesakeofsimplicity,itisassumedthattheprofessorshaveonlyonecarinthefamily.)
The questionnaire
1.General Name................................................................................ Age................................................................................... Sex.........M..........F............................................................ MaritalStatus.......Married.......Unmarried................... Numberofmembersinthefamily 1–2................... 3–4................... 5–6................... Over 6.............. Yearlyincome Lessthan`30,000................... `30,000–`39,999...................... `40,000–`49,999...................... `50,000andmore................... 2.Whattypeofcardoyouownnow? .................American .................Japanese .................European 3.Whatsizeofcardoyouown? .................Luxury .................Mid-size .................Compact
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4.Didyoubuythiscarneworused? .................New....................Used 5. Ifyouboughtausedcar,didyoubuyit fromadealeroraprivate
party? .................Dealer.................Privateparty 6. Ifyouboughtanewcar,howlonghaveyouownedthiscar? .................Numberofyears 7. Ifyouboughtausedcar,howoldisthiscarnow? ..............Numberofyears 8.Pricepaidforthecar..........New..........Used 9.Who influencedyourdecision topurchase theabovebrandofcar?
Indicateifmorethanone. ...............Yourself ......................Yourwife ...............Yourchildren ......................Yourfriend ...............Yourneighbour ......................Yourcolleague Others................................................................................... 10. Indicateastowhodecidedaboutthebudgetallocationforthecar? ...............Yourself ...............Yourspouse ...............Familydecision 11. Ifyouboughtyourcarfromadealer,thenwhoinfluencedyourdecision
regardingtheselectionofaparticulardealer? ...............Yourself ...............Yourfriend ...............Yourcolleague ...............Familydecision 12.Howdidyoucometoknowaboutthisdealer? ...............TVcommercial ...............Newspapers ...............Personalreferences ...............Others 13.Rankthefollowingfactorsthataffectedthefinaldecisionatthetime
ofpurchasingthecar(Arankof1measuresthemostimportantfactor,arankof2measuresthesecondmostimportantfactor,andsoon).
...............Veryinconvenientwithoutthecar ...............Moneywasavailable
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...............Reputationofcarmanufacturer ...............Discountsoffered ...............Interestrateonfinancing ...............Guaranteesandwarrantiesoffered ...........................Others 14.Didyoumakeanextensivesurveyregardingpricecomparisonsafter
youdecidedtobuytheparticularcar?............Yes.........No. 15. Ifyouboughtausedcar,howdidyoulearnaboutit?............Newspapers ...............Friend...............Others 16. Inorderofpreference,whatwerethemajorreasonsforbuyingaused
car? ...............Unavailabilityofadequatefunds ...............Cheaperinsurance ...............Lackofparkinggarage ...............Conditionofthecar ...............Others 17.Whichofthefollowingmediayouthinkismosteffectiveincreating
animpactonthepotentialcustomerrelativetoaparticularbrandofthecar?
................TV ...............Newspapers ................Magazines ...............Favourablenewsreports ................Wordofmouth ...............Others
Theresponsestosuchquestionswouldformthebasisofanalysisinordertoachievethesetmarketingobjectives.
Questionnairedesigningisanimportantpartofresearchmethodologythus,wehavedealtwiththistopicingreatdetailintheappendixgivenattheendofthebook.
Characteristics of a good questionnaire
•Thequestionnaireisaveryimportantdocumentthatisthefirstinterfacebetweentherespondentandtheresearcher.Thus,theappearanceoftheinstrumentisveryimportant.Thefirstthingisthequalityofthepaperonwhichthequestionnaireisprinted.Incasethequestionnaireisprintedonapoor-qualitypaperorlookstatteredandunprofessional,therespondentsdonotvaluethestudyandthusarenotverysincereorcarefulinresponding.
• Incasethenumberofquestionsistoomany,insteadofjuststaplingthepaperstogether,itwouldbeagoodideatoputthemtogetherasa
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booklet.Theyareeasyfortheinvestigatorandthesubjecttoanswer.Secondly,onecanhaveadouble-pageformatforthequestionsandtheappearance,then,ismoresombreandprofessional.Theformat,spacingandpositioningofthequestionscanhaveasignificanteffectontheresults,especiallyinthecaseofself-administeredquestionnaires.
•The font style and spacing used in the entire document should beuniform.Onemustensurethateveryquestionanditsresponseoptionsareprintedonthesamepage.Infact,asfaraspossible,theresponsecategoriesshouldbeinthesamerowasthequestion.Thissavesspaceandatthesametime,ismoreresponsefriendly.
• Incase thequestionnaire is long,or theresearcher iseconomizing,onemustnotcrowdquestionstogetherwithnolinespacingtomakethequestionnaireseemshorter.Thisformatcouldresultinerrorwhilerecordingasthepersoncouldfilltheanswerinthewrongrow.Secondly,incasethereareopen-endedquestionsaswell,theresponseswouldbelessrevealingandshorter.Therespondentmightfeelthatthisisgoingtobeareallylongandcomplexadministrationandmayactuallyloseinterest.Thus, though it isadvisable tohaveshort instruments thatarenottootaxing,butincasehereisaresearchneedforwhichthequestionscannotbeshortened,onemustnotcluttertheappearanceofthemeasuringinstrument(questionnaire).
•Althoughtheuseofcolourdoesnotreallyimpactthequalityoftheresponse,sometimesitcanbeusedtodistinguishbetweenthegroupsorforbranchingquestions.Also,surveysfordifferentgroupscouldbeondifferentcolouredpaper.Thiswouldbehelpfulwhengroupingtheresponsesfromdifferentsegments. Forexample,ifDelhiisbeingstudiedasfivezones,thenthequestionnaireusedineachzonecouldbeprintedonadifferentlycolouredpaper.
•Aswe saw in the last section, the questionnaire is segregated intodifferentsectionstoaddressthevariousinformationneeds.ItisusefuliftheresearcherdividesthedataneededintoseparatesectionssuchasSectionsA,B,Candsoon.
•Thenthequestionsineachpartshouldbenumbered,especially,whenoneisusingbranchingquestions.Theotheradvantageofnumberingthequestions is that after the conduction coding, entering thedataobtainedbecomesmucheasier.Precodedquestionnairesareeasiertoadministerandrecord.
• Incasethereisanyresponseinstructionforanindividualquestion,itmust accompany thequestion. In case it is a schedule and thereare instructions for asking the question aswell as instructions forresponding,theresponseinstructionshouldbeplacedveryclosetothequestion.However,instructionsabouthowtorecordtheanswerand
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Sources and Collection of Data-II
anyprobingquestionthatneedstobeaskedshouldbeplacedafterthequestion.Todistinguishtheinstructionsfromquestions,oneshoulduseadifferentfontstyle.Forexample,overallhowsatisfied(are/were)youwithyour[Domino’s]experience?Wouldyousayyouare(READLIST)?
Verysatisfied..................................................................................5 Satisfied..........................................................................................4 Neithersatisfiednordissatisfied.....................................................3 Dissatisfied......................................................................................2 Or,Verydissatisfied.........................................................................1 INCASEOF2or1 (PROBE) Whatwasthereason(s)foryourexperience?Kindlyexplain.
9.3 SCHEDULE: MEANING, KINDS, ESSENTIALS, PROCEDURE FOR THE FORMULATION OF A SCHEDULE
A scheduleisaquestionnairecontainingasetofquestionsthatarerequiredtobeansweredtocollectthedataaboutaparticularitem.Aschedulegenerallytakesplaceinaface-to-facemanner.
Objectives of a schedule
Thefollowingarethemainobjectivesofaschedule: •Ascheduleiscreatedforadefiniteitemofenquiry.Theschedulesets
theboundariesforthesubjectunderstudy. •Ascheduleactsasanaidtomemorisetheinformationbeingcollected
by the interviewer. Since the interviewer collects the informationfromvariousrespondents,hemightgetconfusedwhileanalysingandtabulatingthedata.
•Aschedulehelpsintabulatingandanalysingthedatainasystematicandstandardisedmanner.
Types of schedules
Therearefivetypesofschedules,whichareasfollows: 1. Observation schedule:Itisthescheduleunderwhichtheobserver
observes all the activities and records all the responses of therespondentsundersomepredefinedconditions.Thechiefideabehindexaminingtheactivitiesistoverifytherequiredinformation.
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2. Rating schedule: It is the schedule used tomeasure and rate thethoughts,preferences,self-consciousness,perceptionsandothersimilarcharacteristicsoftherespondents.
3. Document schedule:Itisthescheduleusedforcollectingtheimportantdataandpreparingasourcelist.Thisscheduleismostlyusedtoattaindatafromautobiographies,diariesorrecordsofgovernmentsregardingwrittenfactsandcasehistories.
4. Institution survey schedule: It is the schedule used for studyingdifferentproblemsofinstitutions.
5. Interview schedule:Itisthescheduleunderwhichaninterviewerasksthequestionstotheintervieweeandrecordshisresponseinthegivenspaceofthequestionnaire.
Merits of the schedule method
Followingarethemeritsoftheschedulemethod: • Inthismethod,theresearcherisalwaystheretohelptherespondents.
So, theresponserate ishighascomparedtoothermethodsofdatacollection.
•Thepresenceof researchernotonly removes thedoubtspresent intheminds of the respondents but also avoid fake replies from therespondentsduetothefearofcrosschecking.
• Inthismethod,thereisapersonalcontactbetweentheresearcherandtherespondent.Thus,thedatacanbecollectedeasilyandcanbereliedupon.
•Thismethodhelpstobetterunderstandthepersonality,livingconditionsandthevaluesoftherespondents.
• It is easy for the researcher todetect and rectify thedefects in thescheduleduringsampling.
Limitations of schedule method
Followingarethelimitationsoftheschedulemethod: • Itisacostlyandtime-consumingmethod. •Thismethodrequireswell-trainedandexperiencedfieldworkersto
taketheinterviewoftherespondents. • Sometimes,therespondentmaynotbeabletotellcertainfactsdueto
thepersonalpresenceofsomeresearchersatthework. • Ifthefieldofresearchisdispersed,itbecomesdifficulttoorganisethe
variousactivitiesoftheresearch.
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Sources and Collection of Data-II
Characteristics of a good schedule
Theessentialcharacteristicsofagoodscheduleareasfollows: •Theinformationorthequestionsincludedinthescheduleshouldbe
accurateand shouldenable the respondent tobetterunderstand thecontextinwhichthequestionsareasked.
•Thescheduleshouldbepre-arrangedandstructuredinsuchamannerthattheinformationgatheredorcollectedisaccurateandtenable.Forthis,thefollowingpointsmustbeconsidered:o Thesizeofthescheduleshouldbeaccurate.o Thequestionsinthescheduleshouldbeunderstandableandshould
bedefinite.o Thequestionsshouldnotcontainanybiasedevaluation.o Allthequestionsofthescheduleshouldbeproperlyinterlinked.o Informationgatheredshouldbeorganisedinatablesothatitcan
beeasilyusedforstatisticalanalysis.
Suitability of schedule method
Theschedulemethodismostlyappliedinthefollowingsituations: •Whenthefieldofinvestigationiswideanddispersed. •Whentheresearcherrequiresquickresultsatlowercost. •Whentherespondentsarewelltrainedandeducated.
Organisation of schedule
Followingisthesequenceinwhichaschedulemustbeorganised: • Selection of respondents:Usuallysamplingmethodisusedforthe
selectionofrespondents.Thesampleshouldberepresentativeoftherespondentsandshouldcontainalltherelevantinformationabouttherespondents.
• Selection and training of field workers: Since thefieldworkerstake the interviewof the respondentsandcollect the requireddata,theselectionofthefieldworkersshouldbedonecarefullyandpropertrainingshouldbeprovidedtothem.
• Conducting interviews: Forasuccessfulinterviewandcorrectresult,thefollowingpointsmustbeconsidered:o Follow correct approach: Thefieldworkershouldapproachthe
respondentsinacorrectmannersothattherespondentscanclearlyunderstandthepurposeoftheinterview.
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o Generating accurate responses:Forproperandaccurateresponsefromtherespondents,therespondentsshouldnotbemisunderstoodintheirperspectiveandcontext.
Testing the validity of the gathered data
Aftertherespondentsfillintheschedule,thegathereddataissubjectedtocertaintestsinordertofindouttheircorrectness.Forthis,theresearchercanagainconducttheinterviewoftherespondentsandcheckforanyvariation.Ifthevariationsareenormous,thenthegathereddataisnotaccurateandthescheduleiseitherrejectedormodified.
9.3.1 Schedules Vs. Questionnaires
When youworkwith questionnaires and schedules, there are severalsimilarities between the two.However, there are prominent differences,whichdifferentiatesthetwo: •Thequestionnaireismostlysentbytheinterviewertotheinterviewee
bymailandisfilledbytheintervieweewhereas,ascheduleisfilledbytheintervieweratthetimeofinterview.
•Datacollectionthroughquestionnaireischeaperwhencomparedtoschedulesasmoneyisspentonlyinpreparingschedulesandmailingit.Inschedulemethod,extramoneyisspentonappointingtheinterviewersandimpartingtrainingtothem.
• Incaseofaquestionnaire,theresponseisgenerallylowbecausemostpeopledonotrespondtothequestions.Ontheotherhand,responseishighinthecaseofschedulessincetheinterviewerfillsthematthetimeofinterview.
• Identityoftherespondentisnotalwaysclearincaseofquestionnaire,whereas, in case of schedules the identity of the interviewee orrespondentisknown.
•Thequestionnairemethodistimeconsumingastherespondentmaynotreturnthequestionnaireintime.Thereisnosuchprobleminthescheduledmethodastheinterviewerfillstheschedulesatthetimeofinterview.
•Aquestionnairedoesnotallowpersonalcontactwiththerespondent.Schedulesestablishdirectcontactwiththeinterviewer.
•Questionnairemethodisusefulonlyincaseiftherespondentisliterate,whileincaseofscheduleitisnotnecessaryfortheintervieweetobeliterate.
•Riskofincompleteandincorrectinformationismoreinquestionnaire,whileinschedules, theinformationcollectediscompleteandmoreaccurate.
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Sources and Collection of Data-IICheck Your Progress
1.Whenisaquestionnaireformused? 2.Whatareopen-endedquestions? 3.Whatisanobservationschedule? 4.Whatmethodisusedfortheselectionofrespondents?
9.4 ANSWERS TO CHECK YOUR PROGRESS QUESTIONS
1.Thequestionnaireformisanimportantandcommonlyusedmethodofdatacollection.Itisusedmostlyincaseoflarge-scaleenquiries.
2.Open ended questions are questionswhich do not require specificresponses.
3.Anobservation schedule is the scheduleunderwhich theobserverobserves all the activities and records all the responses of therespondentsundersomepredefinedconditions.
4.Usuallysamplingmethodisusedfortheselectionofrespondents.
9.5 SUMMARY
•Thequestionnaireformisanimportantandcommonlyusedmethodofdatacollection.Itisusedmostlyincaseoflarge-scaleenquiries.
•Thequestionnaireissenttoeachindividualwhoissupposedtoanswerit.Thistechniqueofcollectinginformationthroughquestionnairesisextensivelyusednowadays.
• Inaquestionnaire,theuseofstandardizedquestionscanhelpcollectmoredatathatisreliable.Byusingquestionnaires,thesystemanalystcancollectvaluableinformationfromthepeopleintheorganisationwhomaybeaffectedbythecurrentandproposedsystem.
•Closedendedquestionsarethequestions,whichareusedwhenthesystemsanalystisabletoeffectivelylistallpossibleresponsestothequestion.
•Rankingscalequestionsallowtheresearchertoarrangethelistofitemsintheorderoftheirimportanceandpreference.
•Questionnaireprovidesadatacollectiontechniqueinwhichwrittenquestionsarepresentedthataretoansweredbythepeopleinwrittenform.
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• Incasethequestionnaireislong,ortheresearcheriseconomizing,onemustnotcrowdquestionstogetherwithnolinespacingtomakethequestionnaireseemshorter.
•Aschedule isaquestionnairecontainingasetofquestions thatarerequiredtobeansweredtocollectthedataaboutaparticularitem.
•Therearefivetypesofschedules,whichareasfollows: 1.Observationschedule 2.Ratingschedule 3.Documentschedule 4. Institutionsurveyschedule 5. Interviewschedule •Theinformationorthequestionsincludedinthescheduleshouldbe
accurateandshouldenable the respondent tobetterunderstand thecontextinwhichthequestionsareasked.
•Aftertherespondentsfillintheschedule,thegathereddataissubjectedtocertaintestsinordertofindouttheircorrectness.
•Whenyouworkwithquestionnairesandschedules,thereareseveralsimilaritiesbetweenthetwo.However,thereareprominentdifferences,whichdifferentiatesthetwo.
• Incaseofaquestionnaire,theresponseisgenerallylowbecausemostpeopledonotrespondtothequestions.Ontheotherhand,responseishighinthecaseofschedulessincetheinterviewerfillsthematthetimeofinterview.
•Riskofincompleteandincorrectinformationismoreinquestionnaire,whileinschedules, theinformationcollectediscompleteandmoreaccurate.
9.6 KEY WORDS
• Schedule:Itisaquestionnairecontainingasetofquestionsthatarerequiredtobeansweredtocollectthedataaboutaparticularitem.
• Rating Schedule: It is the schedule used tomeasure and rate thethoughts,preferences,self-consciousness,perceptionsandothersimilarcharacteristicsoftherespondents.
• Questionnaire: Itisasetofprintedorwrittenquestionswithachoiceofanswers,devisedforthepurposesofasurveyorstatisticalstudy.
• Institution Survey Schedule: It is the schedule used for studyingdifferentproblemsofinstitutions.
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Sources and Collection of Data-II9.7 SELF ASSESSMENT QUESTIONS AND
EXERCISES
Short Answer Questions
1. Listthetasksperformedduringthequestionnairemethod. 2.Whataredichotomousquestions? 3.Whataretheobjectivesofaschedule? 4.Differentiatebetweenquestionnairesandschedules.
Long Answer Questions
1. Whatisaquestionnaire?Discussitsadvantagesanddisadvantages. 2.Discusshowtodesignquestionnaires. 3.Describethecharacteristicsofschedules.Whatarethevarioustypes
ofschedules? 4.Discussthemeritsandlimitationsoftheschedulingmethod.
9.8 FURTHER READINGS
Creswell,JohnW.2002.Research Design: Qualitative, Quantitative, and Mixed Methods Approaches.London:SagePublicationsInc.
Booth,Wayne,GregoryG.ColombandJosephM.Williams.1995.The Craft of Research.Chicago:UniversityofChicagoPress.
Bryman,AlanandEmmaBell.2015.Business Research Methods.4thEdition.UnitedKingdom:OxfordUniversityPress.
Gupta,S.L.andHiteshGupta. 2012. Business Research Methods. NewDelhi: TataMcGrawHillEducationPrivateLimited.
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UNIT 10 SOURCES AND COLLECTION OF DATA-III
Structure 10.0 Introduction 10.1 Objectives 10.2 ScalingTechniques:Meaning,Importance,andClassification
10.2.1 TypesofMeasurementScales:Nominal,Ordinal,IntervalandRatio 10.3 MethodsoftheirConstructionofQuestionnairesorSchedules 10.4 Pre-TestingofDataCollectionTools 10.5 ValidityandReliabilityMethods 10.6 AnswerstoCheckYourProgressQuestions 10.7 Summary 10.8 Key Words 10.9 SelfAssessmentQuestionsandExercises 10.10 FurtherReadings
10.0 INTRODUCTION
In the previous units, you have been introduced to concepts related tocollectionofdata.Youhavelearntthatsourcesareprimaryandsecondaryinnature.Youhavealso learnedabout thequestionaries’ and schedulingmethodofcollectingdata.Inthisunit,wewilldiscussscalingtechniquesofcollectingdata.Scalingbasicallyistheprocessofgeneratingthecontinuum,acontinuoussequenceofvalues,uponwhichthemeasuredobjectsareplaced.Theunitwillalsodiscussthepre-testingofdataaswellastheconceptsofreliabilityandvalidity.
10.1 OBJECTIVES
Aftergoingthroughthisunit,youwillbeableto: •Describethevarioustechniquesofscaling •Discusspre-testingofdatacollectiontools •Examinetheconceptsofvalidityandreliability
10.2 SCALING TECHNIQUES: MEANING, IMPORTANCE, AND CLASSIFICATION
Thescalingtechniquesusedinresearchcanalsobeclassifiedintocomparativeandnon-comparativescales(Figure10.1).
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Fig. 10.1 Types of Scaling
Comparative scales
Incomparativescalesitisassumedthatrespondentsmakeuseofastandardframeofreferencebeforeansweringthequestion.Forexample:
Aquestionlike‘HowdoyourateBaristaincomparisontoCafeCoffeeDayonqualityofbeverages?’isanexampleofthecomparativeratingscale.Itinvolvesthedirectcomparisonofstimulusobjects.Forexample,respondentsmaybe askedwhether theypreferChinese or Indian food.Consider thefollowingsetofquestionsgenerallyusedtocomparevariousattributesofDomino’sPizzaandPizzaHut. • Please rateDomino’s in comparison to PizzaHut on the basis of
yoursatisfactionlevelonan11-pointscale,basedonthefollowingparameters:(1=Extremelypoor,6=Average,11=Extremelygood).Circleyourresponse:
a. Varietyofmenuoptions 1 2 3 4 5 6 7 8 9 10 11
b. Valueformoney 1 2 3 4 5 6 7 8 9 10 11
c. Speedofservice(deliverytime) 1 2 3 4 5 6 7 8 9 10 11
d. Promotionaloffers 1 2 3 4 5 6 7 8 9 10 11
e. Foodquality 1 2 3 4 5 6 7 8 9 10 11
f. Brandname 1 2 3 4 5 6 7 8 9 10 11
g. Qualityofservice 1 2 3 4 5 6 7 8 9 10 11
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h. Convenienceintermsoftakeawaylocation
1 2 3 4 5 6 7 8 9 10 11
i. Friendliness of the salespersononthephone
1 2 3 4 5 6 7 8 9 10 11
j. Qualityofpackaging 1 2 3 4 5 6 7 8 9 10 11
k. AdaptationofIndiantaste 1 2 3 4 5 6 7 8 9 10 11
l. Sideorders/appetizers 1 2 3 4 5 6 7 8 9 10 11
Comparativescaledataisinterpretedgenerallyinarelativekind.Thecomparativescaleincludespairedcomparison,rankorder,constantsumscaleandQ-sorttechniquetomentionafew.
Wewill discuss below eachof the scale under comparative ratingscalesindetailbelow:Paired comparison scales:Herearespondentispresentedwithtwoobjectsandisaskedtoselectoneaccordingtowhatevercriterionheorshewantstouse.Theresultingdatafromthisscaleisordinalinnature.Asanexample,supposeaparentwantstoofferoneofthefouritemstoachild—chocolate,burger,icecreamandpizza.Thechildisofferedtochooseoneoutofthetwofromthesixpossiblepairs,i.e.,chocolateorburger,chocolateoricecream,chocolateorpizza,burgeroricecream,burgerorpizzaandicecreamorpizza.Ingeneral,iftherearenitems,thenumberofpairedcomparisonwouldbe(n(n–1)/2).Pairedcomparisontechniqueisusefulwhenthenumberofitemsislimitedbecauseitrequiresadirectcomparisonandovertchoice.Incasethenumberofitemstobecomparedislarge(say10),itwouldresultin45pairedcomparisonswhichwouldfurtherresultinfatiguefortherespondents.Further,inrealityarespondentdoesnotmakethechoicefromtwoitemsatatime—therearemultiplealternativesavailabletohim.
Therearemanywaysofanalysingthepairedcomparisondata.Theanalysisofpairedcomparisondatawouldresultinanordinalscaleandalsoinanintervalscalemeasurement.Thiswillbeshownwiththehelpofanexample.Letusassumethattherearefivebrands—A,B,C,DandE—andapairedcomparisonwithtwobrandsatatimeispresentedtotherespondentwiththeoptiontochooseoneofthem.Astherearefivebrands,itwillresultin10pairedcomparisons.Supposethisisadministeredtoasampleof250respondentswiththeresultsaspresentedinTable10.1.
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Table 10.1 Paired Comparison Data
A B C D E
A – 0.60 0.30 0.60 0.35
B 0.40 – 0.28 0.70 0.40
C 0.70 0.72 – 0.65 0.10
D 0.40 0.30 0.35 – 0.42
E 0.65 0.60 0.90 0.58 –
Theabovetablemaybeinterpretedbyassumingthatthecellentryinthematrixrepresents theproportionofrespondentswhobelievethat‘thecolumnbrandispreferredovertherowbrand’.Forexample:
InbrandAversusbrandBcomparisonitcanbesaidthat60percentoftherespondentspreferbrandBtobrandA.Similarly,30percentoftherespondentspreferbrandCtobrandAandsoon.
Todeveloptheordinalscalefromthegivenpairedcomparisondataintheabovetable,wecanconverttheentriesinthetableto0–1scores.Thisistoshowwhetherthecolumnbranddominatestherowbrandandviceversa.Iftheproportionisgreaterthan0.5intheabovetable,anumberof‘1’isassignedtothatcell,whichmeansthatthecolumnbrandispreferredovertherowbrand.Whenevertheproportionislessthan0.5inabovetable,anumberof‘0’isassignedtothatcell,whichmeanscolumnbranddoesnotdominatetherowbrand.TheresultsareinTable10.2.
Togettheordinalrelationshipamongthebrands,wetotalthecolumns.HeretheordinalscaleofbrandsisD>B>A>C>E.ThismeansbrandDisthemostpreferredbrand,followedbyB,A,CandE.
Table 10.2 Conversion of Paired Comparison Data into 0 to 1 Form
A B C D E
A – 1 0 1 0
B 0 – 0 1 0
C 1 1 – 1 0
D 0 0 0 – 0
E 1 1 1 1 –
Total 2 3 1 4 0
Inordertoobtaintheintervalscaledatafromthepairedcomparison
dataaspresentedabove,theentriesinthetablecanbeanalysedbyusingatechniquecalledThurston’slawofcomparativejudgement,whichconvertsthe ordinal judgements into the interval data.Here the proportions are
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assumedasprobabilitiesandusingtheassumptionofnormality,Z-scorescanbecomputed.Z-valuehassymmetricdistributionwithameanof‘0’andvarianceof‘1’.Iftheproportionislessthan0.5,thecorrespondingZ-valuehasanegativesignandfortheproportionthatisgreaterthan0.5,theZ-scoretakesapositivevalue.TheZ-scoresforthepairedcomparisondataisgiveninTable10.3.
Table 10.3 Z-scores for Paired Comparison Data
A B C D E
A 0 0.255 –0.525 0.255 –0.38
B –0.255 0 –0.58 0.525 –0.255
C 0.525 0.58 0 0.385 –1.28
D –0.255 –0.525 –0.385 0 –0.2
E 0.38 0.255 1.28 0.2 0
Total Distance 0.395 0.565 –0.21 1.365 –2.115
Average Distance 0.079 0.113 –0.042 0.273 –0.423
Brand D B A C E
Interval scale value with change of origin
0.696 0.536 0.502 0.381 0
The entries inTable 10.4 show the distance between two brands.
Assumingthatthescorescanbeadded,thetotaldistanceiscomputed.Theaverage distance is computedbydividing the total score by the numberofbrands.Thiswayoneobtainstheabsolutepositionofeachbrand.Nowthehighestnegativevaluesamongall thecolumn isadded toeachentrycorrespondingtotheaveragevaluesothatbychangeoforigin,intervalscalevaluescanbeobtained.Thisisshowninthelastrowandthevaluesareofintervalscale,indicatingthedifferencebetweenbrands.BrandDisthemostpreferredbrandandEistheleastpreferredbrandandthedistancebetweenthetwois0.696.ThedistancebetweenbrandCandEequals0.381.
Rankorderscaling:Intherankorderscaling,respondentsarepresentedwithseveralobjectssimultaneouslyandaskedtoorderorrankthemaccordingtosomecriterion.Consider,forexamplethefollowingquestion: •Rankthefollowingsoftdrinksinorderofyourpreference,themost
preferredsoftdrinkshouldberankedone,thesecondmostpreferredshouldberankedtwoandsoon.
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Sources and Collection of Data-IIISoft Drinks Rank
CokePepsiLimcaSpriteMirinda
Seven UpFanta
Likepairedcomparison,thisapproachisalsocomparativeinnature.Theproblemwiththisscaleisthatifarespondentdoesnotlikeanyoftheabove-mentionedsoftdrinkandisforcedtorankthemintheorderofhischoice,then,thesoftdrinkwhichisrankedoneshouldbetreatedastheleastdislikedsoftdrinkandsimilarly,theotherrankingscanbeinterpreted.Thisscaleisverycommonlyusedtomeasurepreferencesforbrandsaswellasattributes.Therankorderscalingresultsintheordinaldata.Constant sum rating scaling:Inconstantsumratingscale,therespondentsareaskedtoallocateatotalof100pointsbetweenvariousobjectsandbrands.Therespondentdistributesthepointstothevariousobjectsintheorderofhispreference.Considerthefollowingexample: •Allocateatotalof100pointsamongthevariousschoolintowhich
youwouldliketoadmityourchild.Themorethepointsyouallocatetoaschool,morepreferreditisconsideredtobe.Thepointsshouldbeallocatedinsuchawaythatthesumtotalofthepointsallocatedtovariousschoolsaddsupto100.
Schools PointsDPS
ModernSchoolMother’s
InternationalAPEEJAY
DAVPublicSchoolLaxmanPublic
SchoolTagoreInternationalTOTAL POINTS 100
SupposeMother’sInternationalisawarded30points,whereasLaxmanPublic School is awarded 15 points, one canmake a statement that therespondent ratesMother’s International twice as high asLaxmanPublicSchool.Thistypeofdataisnotonlycomparativeinnaturebutcouldalsoresult
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inratioscalemeasurement.Thistypeofscaleiswidelyusedinallocatingweightswhichtheconsumermayassigntothevariousattributesofaproduct.
Q-sorttechnique:TheQ-sorttechniquewasdevelopedtodiscriminateamongalargenumberofobjectsquickly.Thistechniquemakesuseoftherankorderprocedureinwhichobjectsaresortedintodifferentpilesbasedontheirsimilaritywithrespecttocertaincriterion.Supposethereare100statementsandanindividualisaskedtopilethemintofivegroups,insuchaway,thatthestronglyagreedstatementscouldbeputinonepile,agreedstatementscouldbeputinanotherpile,neutralstatementformthethirdpile,disagreedstatementscomeinthefourthpileandstronglydisagreedstatementsformthefifthpile,andsoon.Thedatageneratedinthiswaywouldbeordinalinnature.Thedistributionofthenumberofstatementineachpileshouldbesuchthattheresultingdatamayfollowanormaldistribution.Thenumberofpilesneednotberestrictedto5.Itcouldbeaslargeas10ormoreasthelargenumberincreasesthereliabilityorprecisionoftheresults.
Non-comparative scales
Inthenon-comparativescales,therespondentsdonotmakeuseofanyframeofreferencebeforeansweringthequestions.Theresultingdataisgenerallyassumedtobeintervalorratioscale.Forexample:
The respondentmaybe asked to evaluate the quality of food in arestaurantonafivepointscale(1=verypoor,2=poorand5=verygood).Thenon-comparative scales aredivided into twocategories, namely, thegraphic rating scales and the itemized rating scales.The itemized ratingscalesarefurtherdividedintoLikertscale,semanticdifferentialscaleandStapelscale.Allthesecomeunderthecategoryofthemultipleitemscales.
Graphic rating scale
Thisisacontinuousscale,alsocalledgraphicratingscale.Inthegraphicratingscaletherespondentisaskedtotickhispreferenceonagraph.Considerforexamplethefollowingquestion: • Please put a tickmark (•) on the following line to indicate your
preferenceforfastfood.
1 7LeastPreferred
MostPreferred
Tomeasurethepreferenceofanindividualtowardsthefastfoodonehastomeasurethedistancefromtheextremelefttothepositionwhereatickmarkhasbeenput.Higherthedistance,higherwouldbetheindividualpreferenceforfastfood.Thisscalesuffersfromtwolimitations—one,ifarespondenthasputatickmarkataparticularpositionandaftertenminutes,heorsheisgivenanotherformtoputatickmark,itwillvirtuallybeimpossible
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toputatickatthesamepositionaswasdoneearlier.Doesitmeanthattherespondent’spreferenceforfastfoodhasundergoneachangein10minutes?Thebasicassumptioninthisscaleisthattherespondentscandistinguishthefineshadeindifferencesbetweenthepreference/attitudewhichneednotbethecase.Further,thecoding,editingandtabulationofdatageneratedthroughsuchaprocedureisaverytedioustaskandresearcherswouldtrytoavoidusingit.Anotherversionofgraphicscalecouldbethefollowing: • Please put a tickmark (•) on the following line to indicate your
preferenceforfastfood.
1 7LeastPreferred
MostPreferred
2 3 4 5 6
This is a slightly better version than the one discussed earlier. Itwillovercomethe limitationof thescale tosomeextent.Forexample, ifarespondenthadearliertickedbetween5and6,itislikelythathewouldrememberthesameandthesecondtime,hewouldtickveryclosetowherehedidearlier.Thismeansthatthedifferenceinthetworesponsescouldbenegligible.
Anotherwayofpresentingthegraphicratingscaleisthroughsmilingfacescale.Thefollowingexamplewouldillustratethesame. • Pleaseindicatehowmuchdoyoulikefastfoodbypointingtotheface
thatbestshowsyourattitudeandtaste.Ifyoudonotpreferitatall,youwouldpointtofaceone.Incaseyoupreferitthemost,youwouldpointtofaceseven.
Itemized rating scale
Intheitemizedratingscale,therespondentsareprovidedwithascalethathasanumberofbriefdescriptionsassociatedwitheachoftheresponsecategories.Theresponsecategoriesareorderedintermsofthescalepositionandtherespondentsaresupposedtoselectthespecifiedcategorythatdescribesinthebestpossiblewayanobjectisrated.Itemizedratingscalesarewidelyusedinsurveyresearch.Therearecertainissuesthatshouldbekeptinmindwhiledesigningtheitemizedratingscale.Theseissuesare:Number of categories to be used: Thereisnohardandfastruleastohowmanycategoriesshouldbeusedinanitemizedratingscale.However,itisapracticetousefiveorsixcategories.Someresearchersareoftheopinionthatmorethanfivecategoriesshouldbeusedinsituationswheresmallchangesin
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attitudesaretobemeasured.Thereareothersthatarguethattherespondentswouldfinditdifficulttodistinguishbetweenmorethanfivecategories.Itis,however,afactthattheadditionalcategoriesneednotincreasetheprecisionwiththeattitudebeingmeasured.Itisgenerallyseenthatresearchersusefive-categoryscalesandinspecialcases,mayincreaseordecreasethenumberofcategories.Odd or even number of categories: Ithasbeenamatterofdebateamongtheresearchersastowhetheroddorevennumberofcategoriesaretobeusedinsurveyresearch.Byusingevennumberofcategoriesthescalewouldnothaveaneutralcategoryandtherespondentwillbeforcedtochooseeitherthepositiveorthenegativesideoftheattitude.Ifoddnumbersofcategoriesareused,therespondenthasthefreedomtobeneutralifhewantstobeso.TheLikertscale(tobediscussedlater)isabalancedratingscalewithanoddnumberofcategoriesandaneutralpoint.Itisgenerallyseenthatifarespondentisnotawareofthesubjectmatterbeingmeasuredbythescale,hewouldprefertobeneutral.However,ifwehaveselectedourunitofanalysistobeonewhoisknowledgeableaboutthestudybeingconductedandifhepreferstobeneutral,weshouldnotdebarhimfromthisopportunity.Balanced versus unbalanced scales: Abalancedscale is theonewhichhasequalnumberoffavourableandunfavourablecategories.Examplesofbalancedandunbalancedscalearegivenbelow.Thefollowingistheexampleofabalancedscale: •Howimportantispricetoyouinbuyinganewcar? Veryimportant Relativelyimportant Neitherimportantnorunimportant Relativelyunimportant Veryunimportant
In this question, there are five response categories, two ofwhichemphasize the importance of price and two others that do not show itsimportance.Themiddlecategoryisneutral.Thefollowingistheexampleoftheunbalancedscale. •Howimportantispricetoyouinbuyinganewcar? Moreimportantthananyotherfactor Extremelyimportant Important Somewhatimportant Unimportant
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In this question there are four response categories that are skewedtowardstheimportancegiventotheprice,whereasonecategoryisfortheunimportantside.Therefore,thisquestionisanunbalancedquestion.Intheunbalancedscale,thenumbersoffavourableandunfavourablecategoriesarenotthesame.Onecoulduseanunbalancedscaledependinguponthenatureofattitudedistributiontobemeasured.Ifthedistributionisdominantlyfavourable, an unbalanced scalewithmore favourable categories thanunfavourable categories should be appropriate. If anunbalanced scale isused,thenatureanddegreeoftheunbalanceinthescaleshouldbetakenintoaccountduringthedataanalysis.Nature and degree of verbal description: Manyresearchersbelievethateachcategorymusthaveaverbal,numericalorpictorialdescription.Verbaldescriptionshouldbeclearlyandpreciselywordedsothattherespondentsareabletodifferentiatebetweenthem.Further,theresearchermustdecidewhethertolabeleveryscalecategory,somescalecategories,oronlyextremescalecategories.Itisarguedthataclearlydefinedresponsecategoryincreasesthereliabilityofthemeasurement.Forced versus non-forced scales: An important issue concerning theconstructionofanitemizedratingscaleistheuseofaforcedscaleversusnon-forcedscale.Intheforcedscale,therespondentisforcedtotakeastand,whereasinthenon-forcedscale,therespondentcanbeneutralifhe/shesodesires.Theargumentforaforcedscaleisthatthosewhoarereluctanttorevealtheirattitudeareencouragedtodosowiththeforcedscale.Pairedcomparison scale, rank order scale and constant sum rating scales areexamplesofforcedscales.Physical form: Therearemanyoptionsthatareavailableforthepresentationofthescales.Itcouldbepresentedverticallyorhorizontally.Thecategoriescouldbeexpressedinboxes,discretelinesorasunitsonacontinuum.Theymayormaynothavenumbersassignedtothem.Thenumericalvalues,ifused,maybepositive,negativeorboth.
SupposewewanttomeasuretheperceptionaboutJetAirwaysusingamulti-itemscale.Oneofthequestionsisaboutthebehaviourofthecrewmembers.Givenbelowisasetofscaleconfigurationsthatmaybeusedtomeasure theirbehaviour.The followingare someof theexampleswherevariousformsofpresentingthescalesareshown:
ThebehaviourofthecrewmembersofJetAirwaysis: 1.Verybad_____ _____ _____ _____ _____ Verygood 2.Verybad 1 2 3 4 5 Verygood 3. Verybad
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Neitherbadnorgood Verygood 4.Verybad Bad Neitherbadnorgood Good Verygood 5. –2 –1 0 1 2 Verybad Neitherbadnorgood Verygood
Belowwewilldescribesomeoftheitemizedratingscaleswhichareverycommonlyusedinsurveyresearch.Likert scale:Thisisamultipleitemagree–disagreefive-pointscale.Therespondentsaregivenacertainnumberofitems(statements)onwhichtheyareaskedtoexpresstheirdegreeofagreement/disagreement.Thisisalsocalledasummatedscalebecausethescoresonindividualitemscanbeaddedtogethertoproduceatotalscorefortherespondent.AnassumptionoftheLikertscaleisthateachoftheitems(statements)measuressomeaspectofasinglecommonfactor,otherwisethescoresontheitemscannotlegitimatelybesummedup.Inatypicalresearchstudy,therearegenerally25to30itemsonaLikertscale.
ToconstructaLikertscaletomeasureaparticularconstruct,alargenumberofstatementspertainingtotheconstructarelisted.Thesestatementscould range from80 to120.The identificationof the statements isdonethroughexploratory researchwhich is carriedout by conducting a focusgroup,unstructuredinterviewswithknowledgeablepeople,literaturesurvey,analysisofcasestudiesandsoon.Supposewewanttoassesstheimageofacompany.Asafirststep,anexploratoryresearchmaybeconductedbyhavinganinformalinterviewwiththecustomers,andemployeesofthecompany.Thegeneralpublicmayalsobecontacted.Asurveyoftheliteratureonthesubjectmayalsogiveasetofinformationthatcouldbeusefulforconstructingthestatements.Supposethenumberofstatementstomeasuretheconstructsis100innumber.Nowsamplesofrepresentativerespondentsareaskedtostatetheirdegreeofagreement/disagreementonthosestatements.Table10.4givesafewstatementstoassesstheimageofthecompany.
Itmaybenotedthatonlyanchorlabelsandnonumericalvaluesareassignedtotheresponsecategories.Oncethescaleisadministered,numericalvaluesareassignedtotheresponsecategories.Thescalecontainsstatements’someofwhicharefavourabletotheconstructwearetryingtomeasureandsomeareunfavourabletoit.
Forexample,outofthetenstatementsgiven,statementsnumbering1,2,4,6and9inTable10.4arefavourablestatements,whereastheremainingareunfavourablestatements.ThereasonforhavingamixtureoffavourableandunfavourablestatementsinaLikertscaleisthattheresponsesbytherespondentshouldnotbecomemonotonouswhileansweringthequestions.
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Generally, in aLikert scale, there is an approximately equal number offavourable andunfavourable statements.Once the scale is administered,numericalvaluesareassignedtotheresponses.Theruleisthata‘stronglyagree’responseforafavourablestatementshouldgetthesamenumericalvalue as the ‘strongly disagree’ response of the unfavourable statement.SupposeforafavourablestatementthenumberingisdoneasStronglydisagree=1,Disagree=2,Neitheragreenordisagree=3,Agree=4andStronglyagree=5.Accordingly,anunfavourablestatementwouldgetthenumericalvaluesasStronglydisagree=5,Disagree=4,Neitheragreenordisagree=3,Agree=2andStrongagree=1.Inordertomeasuretheimagethattherespondenthasaboutthecompany,thescoresareadded.
Table 10.4 Likert Scale Statements to Measure the Image of the Company
No. Statement Strongly disagree
Disagree Neither agree nor disagree
Agree Strongly agree
1. Thecompanymakesqualityproducts
√
2. Itisaleaderintechnology √
3. Itdoesn’tcareaboutthegeneralpublic.
√
4. ThecompanyleadsinR&Dtoimproveproducts
√
5. Thecompanyisnotagoodpaymaster.
√
6. Theproductsofthecompanygothroughstringentqualitytests.
√
7. Thecompanyhasnotdoneanythingtocurbpollution.
√
8. Itdoesnotcareaboutthecommunitynearitsplant.
√
9. Thecompany’sstocksaregoodtobuyorown.
√
10. Thecompanydoesnothavegoodlabourrelations.
√
Forexample,ifarespondenthasticked(√)statementsnumberingfrom
onetotenasshowninTable10.4,histotalscorewouldbe3+5+4+4+5+4+4+5+4+4=42outof50.Nowifthereare100respondentsand100statements,thescoreontheimageofthecompanycanbeworkedoutforeachrespondentbyaddinghis/herscoresonthe100statements.
Theminimum score for each respondentwill be 100,whereas themaximumscorewouldbe500.
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Asmentionedearlier,a typicalLikertscalecomprisesabout25–30statements.Inordertoselect25statementsfromthe100statements,weneedtodiscardsomeofthem.Therulebehinddiscardingthestatementsisthatthoseitemsthatarenon-discriminatingshouldberemoved.Theprocedureforchoosing25(saynumberofstatements)isshown.
Asmentionedearlier,thescoreforeachoftherespondentsoneachofthestatementscanbeusedtomeasurehis/hertotalscoreabouttheimageofthecompany.ThedatamaylookasgiveninTable10.5.
Table 10.5 shows that the total score for respondent no. 1 is 410,whereasforrespondentno.2itis209.Thismeansthatrespondentno.1hasamorefavourableimageforthecompanyascomparedtorespondentno.2.Now,inordertoselect25statements,letusconsiderstatementsnumberingiandj.Wenotethatthestatementno.jismorediscriminatingascomparedtostatementno.i.Thisisbecausethescoreonstatementjisveryhighlycorrelatedwith the total score as compared to the scoreson statement i.Therefore,ifwehavetochoosebetweeniandj,wewillchoosestatementno.j.Fromthiswecanconcludethatonlythosestatementswillbeselectedwhich have a very high correlationwith the total score.Therefore, the100correlationsare tobearrangedin theascendingorderofmagnitudescorrespondingtoeachstatementandonlytop25statementshavingahighcorrelationwiththetotalscoreneedtobeselected.Table 10.5 Total Score and Individual Score of each Respondent on Various Statements
Scores of Statements
Resp. No. 1 2 3 ........... i ........... j ........... 100 Total Score
1 - - - ........... 5 ........... 4 ........... - 410
2 - - - ........... 4 ........... 2 ........... - 209
3 - - - ........... - ........... - ........... - -
- - - - ........... - ........... - ........... - -
- - - - ........... - ........... - ........... - -
- - - - ........... - ........... - ........... - -
- - - - ........... - ........... - ........... - -
- - - - ........... - ........... - ........... - -
- - - - ........... - ........... - ........... - -
100 - - - ........... - ........... - ........... - -
Anothermethodofselectingthenumberofstatementsfromarelatively
largenumberofthemisthroughtheuseoffactoranalysis.Thisaspectwillbecoveredattheappropriatestageintheunitonfactoranalysis.
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Semanticdifferentialscale:Thisscaleiswidelyusedtocomparetheimagesofcompetingbrands,companiesorservices.Heretherespondentisrequiredtorateeachattitudeorobjectonanumberoffive-orseven-pointrating scales.This scale is bounded at each endbybipolar adjectives orphrases.ThedifferencebetweenLikertandSemanticdifferential scale isthat inLikert scale, a number of statements (items) are presented to therespondentstoexpresstheirdegreeofagreement/disagreement.However,inthesemanticdifferentialscale,bipolaradjectivesorphrasesareused.AsinthecaseofLikertscale,theinformationonthephrasesandadjectivesisobtainedthroughexploratoryresearch.Attimestheremaybeafavourableorunfavourabledescriptor(adjectives)ontheright-handsideandoncertainoccasions thesemay be presented on the left-hand side.This rotationbecomesnecessarytoavoidthehaloeffect.Thisisbecausethelocationofpreviousjudgmentsonthescalemayinfluencethesubsequentjudgementsbecauseofthecarelessnessoftherespondents.Themidpointofabipolarscaleisaneutralpoint.IntheLikertscale,tenstatementswereusedwhererespondentswereaskedtoexpresstheirdegreeofagreement/disagreementregardingtheimageofthecompany.Takingthesameexamplefurther,thesemanticdifferentialscalecorrespondingtothosetenstatementsinLikertscaleisshownbelowwherethebipolaradjectives/phrasesareseparatedbysevenpoints.Thesepointscanbenumberedas1,2,3,...,7or+3,+2,+1,0,–1,...,–3–forafavourabledescriptorpositionedonthelefthandside.Foranunfavourabledescriptorthenumberingswouldbereversed.Atypicalsemanticdifferentialscalewherebipolaradjectives/phrasesarepositionedatthetwoextremeendsisgiveninTable10.6.
Table 10.6 Select Bipolar Adjectives/Phrases of Semantic Differential Scale
1 Makesqualityproducts � � � � � � � Doesnotmakequalityproducts
2 Leaderintechnology � � � � � � � Backwardintechnology
3 Doesnotcareaboutgeneralpublic
� � � � � � � Caresaboutgeneralpublic
4 LeadsinR&D � � � � � � � LaggingbehindinR&D
5 Notagoodpaymaster � � � � � � � Agoodpaymaster
6 Productsgothroughstringentqualitytest
� � � � � � � Productsdon’tgothroughqualitytest
7 Doesnothingtocurbpollution
� � � � � � � Doesaremarkablejobincurbingpollution
8 Doesnotcareaboutcommunitynearplants
� � � � � � � Caresaboutcommunitynearplants
9 Companystocksgoodtobuy
� � � � � � � Notadvisabletoinvestincompanystock
10 Doesnothavegoodlabourrelations
� � � � � � � Hasgoodlabourrelations
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Oncethescaleisconstructedandadministeredtotherepresentativerespondents,themeanscoreforeachofthedescriptoriscalculated.Thescaleisadministeredundertheassumptionthatthenumericalvaluesassignedtotheresponsecategoriesareofintervalscaleinnature.Thisisgenerallythepracticeadoptedbymanyresearchers.However,iftheresponsecategoriesaretreatedasordinalscale,insteadofcomputingthearithmeticmean,medianmaybecomputed.Inthisexample,wearetreatingtheresponsesastheintervalscaleandhencethemeaniscomputed.Oncethemeanforallthebipolaradjectives/phrasesiscomputedweputtheresultintheformofapictorialprofilesoastomakethecomparisoneasy.Atthistime,allthefavourabledescriptors arekeptonone side andall theunfavourabledescriptors arepositionedattheother.Inourexample,wehavepositionedallthefavourabledescriptorsforthetwocompanieswhoseimagewewanttocompareonthelefthandside.ThisisshowninTable10.7.
Table 10.7 Pictorial Profile based on Semantic Differential Ratings
1 Makesqualityproducts Doesnotmakequalityproducts
2 Leaderintechnology Backwardintechnology
3 Caresaboutgeneralpublic
Doesnotcareaboutgeneralpublic
4 LeadsinR&D LaggingbehindinR&D
5 Agoodpaymaster Notagoodpaymaster
6 Productsgothroughstringentqualitytest
Productsdonotgothroughqualitytest
7 Doneremarkablejobincurbingpollution
Donenothingtocurbpollution
8 Caresaboutcommunitynearplants
Doesnotcareaboutcommunitynearplants
9 Companystocksgoodto buy
Notadvisabletoinvestincompanystock
10 Hasgoodlabourrelations
Doesnothavegoodlabourrelations
CompanyA___________________________________CompanyBAspertheresultspresentedinthepictorialprofile,CompanyAisbetter
thanCompanyBinthesensethatitmakesqualityproducts,leadsinR&D,itsproductsgothroughstringentqualitytests,itsstocksaregoodtobuyandithasgoodlabourrelations.CompanyBisaheadofCompanyAasitcaresaboutgeneralpublicandisagoodpaymaster.CompanyAisabetterthanCompanyBasitisleadsintechnologywhereasCompanyBisbetterthan
NOTES
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CompanyAasithasdonearemarkablejobincurbingpollution.However,thesedifferencesarenotstatisticallysignificant.Stapel scale: The Stapelscaleisusedtomeasurethedirectionandintensityofanattitude.Attimesit,maybedifficulttousesemanticdifferentialscalesbecause of the problem in creating bipolar adjectives.TheStapel scaleovercomesthisproblembyusingonlysingleadjectives.Thisscalegenerallyhas10categoriesinvolvingnumbering–5to+5withoutaneutralpointandisusuallypresentedinaverticalform.Thejoboftherespondentistoindicatehowaccuratelyorinaccuratelyeachtermdescribestheobjectbyselectinganappropriatenumericalresponsecategory.Ifapositivehighernumberisselectedbytherespondent,itmeanstherespondentisabletodescribeitmorefavourably.Supposearestaurantistobeevaluatedonqualityoffoodandqualityofservice,thentheStapelscalewouldbepresentedasshownbelow:
RESTAURANT +5 +5 +4 +4 +3 +3 +2* +2 +1 +1 Quality of Food Quality of Service –1 –1 –2 –2 –3 –3 –4 –4 –5 –5*Intheabovescale,therespondentsareaskedtoevaluatehowaccurately
eachwordorphrasedescribestherestaurantinquestion.Theywillchooseavalueof+5iftherestaurantveryaccuratelydescribestheattributeand–5ifitdoesnotdescribeatallcorrectlythewordinquestion.Supposearespondenthas chosenhis options as indicatedby*.This shows that the respondentslightlyprefersthequalityoffoodandisoftheopinionthatthequalityofserviceistotallyuseless.
10.2.1 Types of Measurement Scales: Nominal, Ordinal, Interval and Ratio
Therearefourtypesofmeasurementscales—nominal,ordinal,intervalandratioscales.Wewilldiscusseachoneofthemindetail.Thechoiceofthemeasurementscalehasimplicationsforthestatisticaltechniquetobeusedfordataanalysis.
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Nominal scale: This is the lowest levelofmeasurement.Here,numbersare assigned for the purpose of identification of the objects.Anyobjectwhichisassignedahighernumberisinnowaysuperiortotheonewhichisassigneda lowernumber. In thenominalscale there isastrictone-to-onecorrespondencebetweenthenumbersandtheobjects.Eachnumberisassignedtoonlyoneobjectandeachobjecthasonlyonenumberassignedtoit.Itmaybenotedthattheobjectsaredividedintomutuallyexclusiveandcollectivelyexhaustivecategories.
Examplesofnominalscale:• Whatisyourreligion?
(a) Hinduism (b) Sikhism (c) Christianity (d) Islam (e) Anyother,(pleasespecify) AHindumaybeassignedanumber1,aSikhmaybeassignedanumber
2,aChristianmaybeassignedanumber3andsoon.Anyreligionwhichisassignedahighernumberisinnowaysuperiortotheonewhichisassignedalowernumber.Theassignmentofnumbersisonlyfor thepurposeof identification.Wealsonote that all respondentshavebeendividedintomutuallyexclusiveandcollectivelyexhaustivecategories.Forexample:• Areyoumarried?
(a) Yes (b) No Ifapersonismarried,heorshemaybeassignedanumber101and
anunmarriedpersonmaybeassignedanumber102.• Inwhichofthefollowingdepartmentsdoyouwork?
(a) Marketing (b) HR (c) InformationTechnology (d) Operations (e) FinanceandAccounting (f) Anyother,(pleasespecify)Herealso,apersonworkingforthemarketingdepartmentmaybeassignedanumber1,theoneworkingforHRmaybeassignedanumber2andsoon.
Nominal scalemeasurements are used for identifying food habits(vegetarianornon-vegetarian), gender (male/female), caste, respondents,brands,attributes,stores,theplayersofahockeyteamandsoon.
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The assigned numbers cannot be added, subtracted,multiplied ordivided.Theonlyarithmeticoperationsthatcanbecarriedoutarethecountofeachcategory.Therefore,afrequencydistributiontablecanbepreparedforthenominalscalevariablesandmodeofthedistributioncanbeworkedout.Onecanalsousechi-squaretestandcomputecontingencycoefficientusingnominalscalevariables.Ordinal scale: Thisisthenexthigherlevelofmeasurementthanthenominalscalemeasurement.Oneofthelimitationsofthenominalscalemeasurementsisthatwecannotsaywhethertheassignednumbertoanobjectishigherorlowerthantheoneassignedtoanotheroption.Theordinalscalemeasurementtakescareofthislimitation.Anordinalscalemeasurementtellswhetheranobjecthasmoreorlessofcharacteristicsthansomeotherobjects.However,itcannotanswerhowmuchmoreorhowmuchless.Anordinalscaletellsustherelativepositionsoftheobjectsandnotthedifferencebetweenthemagnitudesoftheobjects.SupposeShashiscoresthehighestmarksinmarketingandisrankedno.1;Mohanscoresthesecondhighestmarksandisrankedno.2;andKrishnascoresthirdhighestmarksandisrankedno.3.However,fromthisstatementwecannotsaywhetherthedifferenceinthemarksscoredbyShashiandMohanisthesameasbetweenMohanandKrishna.TheonlystatementwhichcanbemadeunderordinalscaleisthatShashihasscoredhigherthanMohanandMohanhasscoredhigherthanKrishna.Thedifferencebetweentheranksdoesnothaveanymeaningfulinterpretationinthesensethatitcannottellthedifferenceinabsolutemarksbetweenthethreecandidates.AnotherexampleoftheordinalscalecouldbetheCATscoregiveninpercentileform.Supposeacandidate’sscoreis95percentileintheCATexam.Whatitmeansisthat95percentofthecandidatesthatappearedintheCATexaminationhaveascorebelowthiscandidate,whereasonly5percenthavescoredmorethanhim.Theactualscoreishowmuchlessormorecannotbeknownfromthisstatement.Examplesoftheordinalscaleincludequalityranking,rankingsoftheteamsinatournament,rankingofpreferenceforcolours,softdrinks,socio-economicclassandoccupationalstatus,tomentionafew.Someoftheexamplesofordinalscalesarelistedbelow: •Rankthefollowingattributeswhilechoosingarestaurantfordinner.
Themostimportantattributemayberankedone,thenextimportantmaybeassignedarankof2andsoon.
Attribute Rank
Foodquality
Prices
Menuvariety
Ambience
Service
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•Rankthefollowingbyplacinga1besidetheattributeyouthinkisthemostimportant,a2besidetheattributeyouthinkisthesecondmostimportantandsoonwhilepurchasingatwo-wheeler.
Attribute Rank
Aftersaleservice
Prices
Re-salevalue
Fuelefficiency
Aestheticappeal
Intheordinalscale,theassignedrankscannotbeadded,multiplied,subtractedordivided.Onecancomputemedian,percentilesandquartilesofthedistribution.Theothermajorstatisticalanalysiswhichcanbecarriedoutistherankordercorrelationcoefficient,signtest.Astheordinalscalemeasurementishigherthanthenominalscalemeasurement,allthestatisticaltechniqueswhichareapplicableinthecaseofnominalscalemeasurementcanalsobeusedfortheordinalscalemeasurement.However,thereverseisnottrue.Thisisbecauseordinalscaledatacanbeconvertedintonominalscaledatabutnottheotherwayround.Interval scale: Theintervalscalemeasurementisthenexthigherlevelofmeasurement.Ittakescareofthelimitationoftheordinalscalemeasurementwherethedifferencebetweenthescoreontheordinalscaledoesnothaveanymeaningfulinterpretation.Intheintervalscalethedifferenceofthescoreonthescalehasmeaningfulinterpretation.Itisassumedthattherespondentisabletoanswerthequestionsonacontinuumscale.Themathematicalformofthedataontheintervalscalemaybewrittenas Y=a+bX where a≠0
Theintervalscaledatahasanarbitraryorigin(non-zeroorigin).ThemostcommonexampleoftheintervalscaledataistherelationshipbetweenCelsiusandFarenheittemperature.Itisknownthat:
5C (F 32).9
° = ° −
Therefore, 160 5C F9 9
−° = + °
ThisisoftheformY=a+bX,wherea= 1609
− andb=59andhenceit
representstheintervalscalemeasurement.Intheintervalscale,thedifference inscorehasameaningfulinterpretationwhiletheratioofthescoreonthis
NOTES
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scaledoesnothaveameaningfulinterpretation.Thiscanbeseenfromthefollowingintervalscalequestion: •Howlikelyareyoutobuyanewdesignercarpetinthenextsixmonths?
Very unlikely Unlikely Neutral Likely Very likely
Scale A 1 2 3 4 5
Scale B 0 1 2 3 4
Scale C –2 –1 0 1 2
Supposearespondenttickstheresponsecategory‘likely’andanotherrespondentticksthecategory‘unlikely’.IfweuseanyofthescalesA,BorC,wenotethatthedifferencebetweenthescoresineachcaseis2.Whereas,whentheratioofthescoresistaken,itis2,3and–1forthescalesA,BandCrespectively.Therefore,theratioofthescoresonthescaledoesnothaveameaningfulinterpretation.Thefollowingaresomeexamplesofintervalscaledata. •Howimportantispricetoyouwhilebuyingacar?
Least Unimportant Neutral Important Mostimportant important 1 2 3 4 5
•Howdoyouratetheworkenvironmentofyourorganization?Verygood Good Neithergood Bad Verybad
norbad 5 4 3 2 1
•The counter-clerks at ICICIBank, (VasantKunjBranch) are veryfriendly.Strongly Disagree Neitheragree Agree Strongly
disagree nordisagree agree 1 2 3 4 5
•Ratethelifeofthebatteryofyourinverter.
• Indicate thedegreeof satisfactionwith theoverall performanceofWagonR.
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•Howexpensiveistherestaurant‘PunjabiByNature’?ExtremelyDefinitely Somewhat Somewhat Definitely Extremely expensive expensive expensive inexpensive inexpensive inexpensive 1 2 3 4 5 6 •Howlikelyareyoutobuyanewcarwithinthenextsixmonths? Definitely Probably Neutral Probablywill Definitelywill will buy will buy not buy not buy 1 2 3 4 5
Thenumbers on this scale canbe added, subtracted,multipliedordivided.Onecancomputearithmeticmean,standarddeviation,correlationcoefficientandconductat-test,Z-test,regressionanalysisandfactoranalysis.Astheintervalscaledatacanbeconvertedintotheordinalandthenominalscaledata, thereforeall the techniquesapplicable for theordinaland thenominalscaledatacanalsobeusedforintervalscaledata.Ratio scale: This is the highest level ofmeasurement and takes care ofthe limitations of the interval scalemeasurement,where the ratio of themeasurementsonthescaledoesnothaveameaningfulinterpretation.Theratioscalemeasurementcanbeconvertedintointerval,ordinalandnominalscale.Buttheotherwayroundisnotpossible.ThemathematicalformoftheratioscaledataisgivenbyY=bX.Inthiscase,thereisanaturalzero(origin),whereasintheintervalscalewehadanarbitraryzero.Examplesoftheratioscaledataareweight,distancetravelled,incomeandsalesofacompany,tomentionafew.
10.3 METHODS OF THEIR CONSTRUCTION OF QUESTIONNAIRES OR SCHEDULES
Wehave alreadydiscussed themethodof constructionof questionnairesandschedules inUnit9.Tobriefly recapitulatewhatwehavediscussed,the steps involved indesigningaquestionnaireencompass the followingsteps:(1)converttheresearchobjectivesintotheinformationneeded,(2)Methodofadministeringthequestionnaire,(3)Contentofthequestions,(4)Motivatingtherespondenttoanswer,(5)Determiningthetypesofquestions,(6)Questiondesigncriteria,(7)Determinethequestionnairestructure,(8)Physicalpresentationofthequestionnaire,(9)Pilottestingthequestionnaire,(10)Standardizingthequestionnaire.
Check Your Progress
1.Howcanscalingtechniquesusedinresearchbeclassified? 2.Listthefourtypesofmeasurementscales. 3.Whataresomeexamplesofratioscaledata?
NOTES
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Sources and Collection of Data-III10.4 PRE-TESTING OF DATA COLLECTION TOOLS
Pre-testisatrialtestofaspecificaspectofthestudy,suchasthecommonmethods of data collection or common data collection tools—schedule(used as tool for interviewing), questionnaire ormeasurement scale. Itis the administration of the data collection instrumentwith a small setof respondents from thepopulation for the full scale survey. Ifproblemshappeninthepre-test,theresearcherislikelytofacesimilarproblemsinfull-scaleadministration.Pre-testingaimsatidentifyingproblemswiththedatacollectioninstrumentandfindpossiblesolutions.Pre-testingneedstobecarriedoutincircumstancesthatareasakinaspossibletoactualdatacollectionandasidenticalaspossibletothosethatwillbesampled.
Survey sponsors have amajor role to play in developing the datacollectioninstrumentsbeingproposed,includinganytestingbeingcarriedout.Muchoftheaccuracyandinterpretabilityofthesurveyresultsdependsonpre-testing,whichshouldneverbeignored.
Need for pre-testing
An instrumentofdatacollection isdesigned inaccordancewith thedatarequirements of the study.However, any scrutiny by the designer andotherresearcherscannotmaketheinstrumentperfect.Itneedstobetestedempirically.AspointedbyGoodeandHatt:‘Noamountofthinking,nomatterhowlogicalthemindorbrillianttheinsight,islikelytotaketheplaceofcarefulempiricalchecking.’Thus,pre-testingofadraftinstrumentisessential.
Purpose of pre-testing
Pre-testingaimsat: •Testingwhethertheinstrumentwoulddrawoutresponsesneededto
achievetheresearchobjectives •Developing a suitable procedure to administer the instrumentwith
referencetofieldconditions •Testingwhetherwordingofquestionsisunambiguousandsuitedto
theunderstandingoftherespondents •Testingwhetherthecontentoftheinstrumentisapplicableandsufficient •Testingtheotherqualitativeaspectsoftheinstrument,suchasquestion
structureandquestionsequence
Pre-Testing of Questionnaire
• Pilottestingreferstotestingandadministeringthedesignedinstrumentonasmallgroupofpeoplefromthepopulationunderstudy.Thisistoessentiallycoveranyerrorsthatmighthavestillremainedevenaftertheearliereightsteps.
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•Everyaspectofthequestionnairehastobetestedandonemustrecordall the experiences of the conduction, including the time taken toadministerit.Iftherespondenthadaproblemunderstandingaquestionor response category, the investigator should verbatim record theinstructionhe/shegavetoclarifythepointasthisthenwouldneedtobeincorporatedinthefinalversionofthequestionnaire.
• Incaseaquestiongotnoanswers,thenitmightbeessentialtorephrasetheentirequestion.
•Evenwhen themodeof administration ismail or Internet or self-administeredtests,thepilottestsshouldalwaysbedoneinaface-to-face interaction.Here, the researcher is able toobserveand recordresponses,bothverbalandnon-verbal.
• Sometimes,theresearchermightalsogetthequestionnairevettedbyacademicorindustryexpertsfortheirinputs.
•Oncetheessentialchangeshavebeenmade,theresearchermightcarryoutoneshorttrialandthengoaheadwiththeactualadministration.
•Asfaraspossible,thepilotshouldbeasmallscalereplicaoftheactualsurveythatwouldbesubsequentlyconducted.
• Itisadvisabletousemultipleinvestigatorsforthepilotstudy. •Thegroupofinvestigatorsshouldbeamixofexperiencedandseasoned
fieldinvestigatorsandinexperiencedinvestigatorsaswell. •The inexperienced oneswould be able to reveal the problems
encounteredinadministeringthemeasure,whiletheexperiencedfieldworkerswouldbeabletoreportrespondentdifficultiesinansweringthequestions.
•Therespondent’sexperienceofthepilottestcanberecordedintwoways.One is protocol analysiswherehe is asked to speakout thereasoninginrespondingtothequestions.Thisisrecorded,asithelpstounderstandtheunderlyingfactorsormentalprocessinginvolvedingivinganswers.
•Theothermethodiscalleddebriefing,whereafterthequestionnairehasbeencompleted,thepersonisaskedtosummarizehisexperienceintermsofanyproblemsexperiencedinansweringorwhethertherewasanyconfusionorfatiguewhileansweringthequestionnaire.
•Theresearchermusttheneditthequestionnaireasrequiredandcarryoutanyfurtherpilottests.Oncethisisover,heentersthepilotdatatoexploreandseewhethertheinformationthatisbeingcollectedthroughthequestionnairewouldadequatelyfurnishtheinformationneedsforwhichtheinstrumentwasdesigned.
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Sources and Collection of Data-III
Methods of pre-testing questionnaires
Thevariousmethodsortechniquesofpre-testingquestionnairesarelistedanddiscussedasfollows: • Respondent focus groups: Focusgroups(referredtoasaformofin-
depthgroupinterviewing)arecarriedoutearlyinthequestionnairedevelopmentcycletoevaluatethequestion-answeringprocess. Suchgroupsmaycollectinformationrelatingtoatopicbeforethebeginningof questionnaire construction.They help in the identification ofdifferences in language, terminology, or interpretationof questionsandresponseoptions.Theyareespeciallyveryusefulinpre-testingself-administeredquestionnairesinordertolearnabouttheappearanceandformattingofthequestionnaire.Oneofthemajoradvantagesoffocusgroupsisthatitprovidestheopportunitytomonitoragreatdealofinteractiononatopicinalimitedtimespan.
• Behaviour coding: Behaviourcodingreferstoasystematiccodingoftheinteractionbetweeninterviewersandrespondentsfromliveortapedinterviews.Itemphasizesonspecificaspectsofhowtheintervieweraskedthequestionandhowtherespondentreacted.Whenusedforpre-testingaquestionnaire,thecodinghighlightsinterviewerorrespondentbehaviours indicativeof aproblemwith thequestion, the responsecategories,ortherespondent’sskilltoformasatisfactoryresponse.
• Cognitive laboratory interviews: Cognitive laboratory interviewscompriseone-on-one interviewsusingastructuredquestionnaire inwhichrespondentsdescribetheirthoughtswhilegivinganswerstothesurveyquestions.Theyprovideavitalmeansoffindingoutdirectlyfromrespondentswhattheirproblemsarewiththequestionnaire.Inaddition,smallnumbersofinterviewsmaygivevaluableinformationaboutmajorproblems,suchasrepetitionsofquestionsandambiguousconcepts.As sample sizes are not large in cognitive laboratoryinterviews,repeatedpre-testingofaninstrumentiscommon.
• Respondent and interviewer debriefings: Respondentdebriefingsinvolvetheincorporationofstructuredfollow-upquestionsattheendofafieldtestinterviewtogatherquantitativeandqualitativeinformationaboutrespondents’interpretationsofsurveyquestions.Forthepurposeof pre-testing, their primeobject is tofindoutwhether the surveyconceptsandquestionsarecomprehendedbyrespondentsinthesamewaythatthesurveysponsorsintended.Interviewerdebriefingshaveconventionallybeentheprimarymethod
forevaluatingfield tests. In thismethod, the interviewersconducting thesurveyfieldtestsarequeriedtousetheirdirectcontactwithrespondentssothatthequestionnairedesigner’sunderstandingofquestionnaireproblemsisenriched.
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• Analysis of item non-response rates: Analysisofitemnon-responserates from the data gathered during a field test provides usefulinformationabouthowwellthequestionnaireworks.Thisiscarriedoutbylookingathowoftenitemsaremissing(i.e.,itemnon-responserates).
• Split-panel tests: Split-panel tests are the controlled experimentaltesting among questionnaire variants or interviewingmodes fordeterminingwhich is ‘better’or formeasuringdifferencesbetweenthem.Inordertopre-testmultipleversionsofaquestionnaire,researchrequires a previously determined standard bywhich to judge thedifferences.Split-paneltestsarealsousefulinstandardizingtheeffectofchangingquestions,whichisparticularlysignificantintheredesignandtestingofsurveyswherethecomparabilityofthedatagatheredovertimeisaproblem.
• Analysis of response distributions: The analysis of responsedistributions for an item isuseful indeterminingwhetherdifferentquestionwordings or question sequences result different responsepatterns.Suchanalysisismostusefulwhentheresearcherhastopre-testmorethanoneversionofaquestionnaireorasinglequestionnaireinwhichsomeknowndistributionofcharacteristicsexistsforcomparativepurposes.
Pre-Testing of Interview Schedule
Thepre-testing of interview schedule involves contactwith respondentsdrawnfromthesamepopulationasfortheactualsurvey.Pre-testingincludesthetestingofquestioncontent,wording,sequence,formandlayout,difficulty,instructionsandacceptance.Onthecompletionofpre-testing,allnecessarychanges aremade tofix the identified problems.As in any high-qualityresearchplan,aresearcherneedstopre-testtheinterviewprotocol,orlistofinterviewquestions,beforecollectingdataforthemainstudy.Inotherwords,firstofall,theresearcherconductsapilotstudyofhislistofinterviewquestionswithagroupofpersonswhoaredemographicallysimilartohisultimatesampleprofile.Thishelpsinthedeterminationofthemostlogicalandsmooth-flowingorderofthequestions.Pre-testingalsoidentifieswordingissuesthatneedtobeaddressedforthesakeofclarity,whichwillenhancetheintegrityoftheresearcher’sdata.Lastbutnotthelist,apre-testshedsimportantlightontheamountoftimetobetakentoconducttheinterview,whichisoneofthefirstquestionstheresearcherwillbeaskedbypotentialparticipants.
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Sources and Collection of Data-III10.5 VALIDITY AND RELIABILITY METHODS
Therearethreecriteriaforgoodcollectionofdata:reliability,validityandsensitivity.
1. Reliability
Reliabilityisconcernedwithconsistency,accuracyandpredictabilityofthescale.Itreferstotheextenttowhichameasurementprocessisfreefromrandomerrors.Thereliabilityofascalecanbemeasuredusingthefollowingmethods:
Test–retestreliability:Inthismethod,repeatedmeasurementsofthesamepersonorgroupusingthesamescaleundersimilarconditionsaretaken.Averyhighcorrelationbetweenthetwoscoresindicatesthatthescaleisreliable.However,thefollowingissuesshouldbekeptinmindbeforearrivingatsuchaconclusion. •What should be the appropriate time difference between the two
observations is a questionwhich requires attention. If the timedifferencebetweentwoconsecutiveobservationsisverysmall(saytwoorthreeweeks)itisverylikelythattherespondentswouldrememberthepreviousanswerandmaygivethesameanswerwhentheinstrumentisadministeredthesecondtime.Thiswillmaketheinstrumentreliable,whichmaynotactuallybethecase.However,ifthedifferencebetweenthetwoobservationsisverylarge(saymorethanayear)itisquitelikelythattherespondent’sanswerstothevariousquestionsoftheinstrumentmighthaveactuallyundergoneachange,resultinginpoorreliabilityofthescale.Therefore,theresearcherhastobeverycarefulindecidinguponthetimedifferencebetweenthetwoobservations.Generally,itisthoughtthatatimedifferenceofaboutfivetosixmonthsisanidealperiod.
•Anotherprobleminthistestisthatthefirstmeasurementmaychangetheresponseofthesubjecttothesecondmeasurement.
•Thesituationalfactorsworkingontwodifferenttimeperiodsmaynotbethesame,whichmayresult indifferentmeasurementinthetwoperiods.
•Thesecondreadingonthesameinstrumentfromthesamesubjectmayproduceboredom,angerorattempttoremembertheanswersgiveninaninitialmeasurement.
•Afavourableresponsewithabrandduringtheperiodbetweenthetwotestsmightcauseashiftintheindividualratingbythesubject.
Split-half reliability method:Thismethodisusedinthecaseofmultipleitemscales.Herethenumberofitemsisrandomlydividedintotwoparts
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andacorrelationcoefficientbetweenthetwoisobtained.Ahighcorrelationindicates that the internal consistency of the construct leads to greaterreliability.Anothermeasurewhichisusedtotesttheinternalconsistencyofamultiple itemscale is thecoefficientalpha (±)commonlyknownascronbachalpha.Thecronbachalphacomputestheaverageofallpossiblesplit-halfreliabilitiesforamultipleitemscale.Thiscoefficientdemonstrateswhethertheaveragescoreofallsplit-halfofreliabilitiesconvergetoacertainpoint or not.
The coefficient alpha does not address validity.However,manyresearchers use this as a sole indicator of validity.The alpha coefficientcantakevaluesbetween0and1.Thefollowingvaluesofalphawiththeirinterpretationaresuggestedbelow:
±=0means Thereisnoconsistencybetweenthevariousitemsofamultipleitemscale
±=1means There iscompleteconsistencybetweenvariousitemsofamultipleitemscale
0.80 ≤ a ≤0.95implies Thereisverygoodreliabilitybetweenthevariousitemsofamultipleitemscale
0.70 ≤ a ≤0.80implies Thereisgoodreliabilitybetweenthevariousitemsofamultipleitemscale
0.60 ≤ a ≤0.70implies Thereisfairreliabilitybetweenthevariousitemsofamultipleitemscale
a<0.60means Thereispoorreliabilitybetweenthevariousitemsofamultipleitemscale
2. Validity
Thevalidityofascalereferstothequestionwhetherwearemeasuringwhatwewanttomeasure.Validityofthescalereferstotheextenttowhichthemeasurementprocessisfreefrombothsystematicandrandomerrors.Thevalidityofascaleisamoreseriousaissuethanreliability.TherearedifferentwaystomeasurevalidityContent validity:This isalsocalled facevalidity. It involves subjectivejudgementbyanexpertforassessingtheappropriatenessoftheconstruct.Forexample,tomeasuretheperceptionofacustomertowardsKingfisherAirlines,amultipleitemscaleisdeveloped.Asetof15itemsisproposed.TheseitemswhencombinedinanindexmeasuretheperceptionofKingfisherAirlines.Inordertojudgethecontentvalidityofthese15items,asetofexpertsmayberequestedtoexaminetherepresentativenessofthe15items.Theitemscoveredmaybelackinginthecontentvalidityifwehaveomittedbehaviourofthecrew,foodquality,andfoodquantity,etc.,fromthelist.In
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fact,conductingtheexploratoryresearchtoexhaustthelistofitemsmeasuringperceptionoftheairlinewouldbeofimmensehelpinsuchacase.Concurrent validity:Itisusedtomeasurethevalidityofthenewmeasuringtechniquesbycorrelatingthemwiththeestablishedtechniques.Itinvolvescomputingthecorrelationcoefficientoftwomeasuresofthesamephenomena(forexample,perceptionofanairlineandimageofacompany)whichareadministeredatthesametime.Wepreparea15itemscaletomeasuretheperceptionofKingfisherAirline,whichisassumedtobeavalidone.Supposearesearcherproposesanalternativeandshortertechnique.Theconcurrentvalidityofthenewtechniquewouldbeestablishedifthereisahighcorrelationbetweenthetwotechniqueswhenadministeredatthesametimeundersimilaroridenticalconditions.Predictive validity:Thisinvolvestheabilityofameasuredphenomenaatonepointoftimetopredictanotherphenomenonatafuturepointoftime.Ifthecorrelationcoefficientbetweenthetwoishigh,theinitialmeasureissaidtohaveahighpredictiveability.Asanexample,considertheuseofthecommonadmissiontest(CAT)toshortlistcandidatesforadmissiontotheMBAprogrammeinabusinessschool.TheCATscoresaresupposedtopredictthecandidate’saptitudeforstudiestowardsbusinesseducation.
3. Sensitivity
Thesensitivityofascaleisanimportantmeasurementconcept,particularlywhenchangesinattitudesareunderinvestigation.Sensitivityreferstoaninstrument’s ability to accuratelymeasure thevariability in a concept.Adichotomousresponsecategorysuchasagreeordisagreedoesnotallowtherecordingofanyattitudechanges.Amoresensitivemeasurewithnumerouscategoriesonthescalemayberequired.Forexample,addingstronglyagree,agree,neitheragreenordisagree,disagreeandstronglydisagreecategorieswillincreasethesensitivityofthescale.
Thesensitivityofscalebasedonasinglequestionorasingleitemcanbeincreasedbyaddingquestionsoritems.Inotherwords,becausecompositemeasuresallowforagreaterrangeofpossiblescores,theyaremoresensitivethanasingle-itemscale.Therefore,thesensitivityofthescaleisgenerallyincreasedbyaddingmoreresponsepointsorbyaddingscaleitems.
Check Your Progress
4.Whatisapre-test? 5.Howcanthesensitivityofscalebasedonasinglequestionoritem
beincreased?
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10.6 ANSWERS TO CHECK YOUR PROGRESS QUESTIONS
1.The scaling techniques used in research can be classified intocomparativeandnon-comparativescales.
2.Therearefourtypesofmeasurementscales—nominal,ordinal,intervalandratioscales.
3.Someexamplesoftheratioscaledataareweight,distancetravelled,incomeandsalesofacompany.
4.Pre-test is a trial test of a specific aspect of the study, such as thecommonmethodsofdatacollectionorcommondatacollectiontools—schedule(usedastoolforinterviewing),questionnaireormeasurementscale.
5.Thesensitivityofscalebasedonasinglequestionorasingleitemcanbeincreasedbyaddingquestionsoritems.
10.7 SUMMARY
• Incomparativescalesit isassumedthatrespondentsmakeuseofastandardframeofreferencebeforeansweringthequestion.
•Comparativescaledataisinterpretedgenerallyinarelativekind.Thecomparativescale includespairedcomparison, rankorder,constantsumscaleandQ-sorttechniquetomentionafew.
• Inthenon-comparativescales,therespondentsdonotmakeuseofanyframeofreferencebeforeansweringthequestions.Theresultingdataisgenerallyassumedtobeintervalorratioscale.
•Thenon-comparativescalesaredividedintotwocategories,namely,thegraphicratingscalesandtheitemizedratingscales.
• Inthegraphicratingscaletherespondentisaskedtotickhispreferenceonagraph.
• Intheitemizedratingscale,therespondentsareprovidedwithascalethathasanumberofbriefdescriptionsassociatedwitheachof theresponsecategories.
• Ifanunbalancedscaleisused,thenatureanddegreeoftheunbalanceinthescaleshouldbetakenintoaccountduringthedataanalysis.
•TheStapelscaleisusedtomeasurethedirectionandintensityofanattitude.Attimesit,maybedifficulttousesemanticdifferentialscalesbecauseoftheproblemincreatingbipolaradjectives.
•Therearefourtypesofmeasurementscales—nominal,ordinal,intervalandratioscales.Wewilldiscusseachoneofthemindetail.
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•Thechoiceofthemeasurementscalehasimplicationsforthestatisticaltechniquetobeusedfordataanalysis.
•Pre-test is a trial test of a specific aspect of the study, such as thecommonmethodsofdatacollectionorcommondatacollectiontools—schedule(usedastoolforinterviewing),questionnaireormeasurementscale.
•Pre-testistheadministrationofthedatacollectioninstrumentwithasmallsetofrespondentsfromthepopulationforthefullscalesurvey.
•Thepre-testingofinterviewscheduleinvolvescontactwithrespondentsdrawnfromthesamepopulationasfortheactualsurvey.
•Therearethreecriteriaforgoodcollectionofdata:reliability,validityandsensitivity.
•Reliabilityisconcernedwithconsistency,accuracyandpredictabilityofthescale.Itreferstotheextenttowhichameasurementprocessisfreefromrandomerrors.
•The sensitivity of a scale is an importantmeasurement concept,particularlywhenchangesinattitudesareunderinvestigation.
10.8 KEY WORDS
• Focus Groups:Itreferstoagroupofpeopleassembledtoparticipateinadiscussionaboutaproductbefore it is launched,or toprovidefeedbackonapoliticalcampaign,televisionseries,etc.
• Sensitivity: Itreferstoaninstrument’sabilitytoaccuratelymeasurethevariabilityinaconcept.
• Behaviour Coding:Itreferstoasystematiccodingoftheinteractionbetweeninterviewersandrespondentsfromliveortapedinterviews.
• Likert Scale:Itisascaleusedtorepresentpeople’sattitudestoatopic. • Split-Panel Tests:Theyarethecontrolledexperimentaltestingamong
questionnairevariantsorinterviewingmodesfordeterminingwhichis‘better’orformeasuringdifferencesbetweenthem.
10.9 SELF ASSESSMENT QUESTIONS AND EXERCISES
Short Answer Questions
1. Whatisgraphicratingscale? 2.Whatshouldbekeptinmindwhiledesigningitemizedratingscale? 3.Whatisthestaplescaleusedtomeasure?
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4.Liststhestepsinvolvedindesigningaquestionnaire. 5.Discussvalidity.
Long Answer Questions
1. Whatarecomparativeratingscales?Discussitsvarioustypes. 2.Describethevariousnon-comparativescales. 3.Examinethevarioustypesofmeasurementscales. 4.Whatispre-test?Discussitspurpose. 5.Describethemethodsofpre-testingaquestionnaire.
10.10 FURTHER READINGS
Creswell,JohnW.2002.Research Design: Qualitative, Quantitative, and Mixed Methods Approaches.London:SagePublicationsInc.
Booth,Wayne,GregoryG.ColombandJosephM.Williams.1995.The Craft of Research.Chicago:UniversityofChicagoPress.
Bryman,AlanandEmmaBell.2015.Business Research Methods.4thEdition.UnitedKingdom:OxfordUniversityPress.
Gupta,S.L.andHiteshGupta. 2012. Business Research Methods. NewDelhi: TataMcGrawHillEducationPrivateLimited.
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Processing and Analysis of DataUNIT 11 PROCESSING AND
ANALYSIS OF DATAStructure 11.0 Introduction 11.1 Objectives 11.2 Meaning,ImportanceandProcessofDataAnalysis:Editing,Coding,
TabulationandDiagrams 11.3 TypesofAnalysis 11.4 AnswerstoCheckYourProgressQuestions 11.5 Summary 11.6 Key Words 11.7 SelfAssessmentQuestionsandExercises 11.8 FurtherReadings
11.0 INTRODUCTION
Inthepreviousunit,youlearntaboutscalingtechniquesandpre-testing.Inthisunit,wewillbeginourdiscussionontheprocessingandanalysisofdata.Theprocessofinspecting,cleaning,transformingandmodellingdatawiththespecificpurposeofhighlightingusefulinformation,suggestingconclusionsand supportingdecisionmaking is termed as analysis of data.There aremultiplefacetsandapproachestodataanalysis.Thedatathatisacquiredmustbeidentifiedasamatterofutmostimportance.Thisisfollowedbytheprocessingandanalysisofthesameinordertoinferproperandaccurateresults.Thisunitfocusesonthemeaning,importanceandtheprocessofdataanalysis.
11.1 OBJECTIVES
Aftergoingthroughthisunit,youwillbeableto: •Discussthemeaningandimportanceofdataanalysis •Explaintheprocessofdataanalysis •Examinetheimportanceandsignificanceofcoding •Classifydataaccordingtothevariousclassintervals
11.2 MEANING, IMPORTANCE AND PROCESS OF DATA ANALYSIS: EDITING, CODING, TABULATION AND DIAGRAMS
Research does notmerely consist of data that is collected.Research isincompletewithoutproperanalysisofthecollecteddata.Processingofdata
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involves analysis andmanipulation of the collected data by performingvariousfunctions.Thedatahastobeprocessedinaccordancewiththeoutlinelaiddownatthetimeofdevelopingtheresearchplan.Processingofdataisessentialforensuringthatallrelevantdatahasbeencollectedtoperformcomparisonsandanalyses.Thefunctionsthatcanbeperformedondataareasfollows:
• Editing• Coding• Tabulation• ClassificationUsually,expertsareoftheopinionthattheexerciseofprocessingand
analysingofdataisinter-related.Therefore,thetwoshouldbethoughtasoneandthesamething.Itisarguedthatanalysisofdatagenerallyinvolvesanumberofclosely-relatedoperations,whicharecarriedoutwiththeobjectiveofsummarizingthecollecteddataandorganizingitinsuchawaythattheyareabletoanswertheresearchquestionsassociatedwithit.
However, in technical terms, processing of data involves datarepresentationinawaythatitisopentoanalysis.Similarly,analysisofdataisdefinedasthecomputationofcertainmeasuresalongwithsearchingforthepatternsofrelationshipthatmayexistamongdatagroups.
Editing of data
Editingofdatainvolvesthetestingofdatacollectioninstrumentsinordertoensuremaximumaccuracy.Thisincludescheckingthelegibility,consistencyand completeness of the data. The editing process aims at avoidingequivocationandambiguity.Thecollectedrawdataisalsoexaminedtodetecterrorsandomissions,ifany.Acarefulscrutinyisperformedonthecompletedquestionnairesandschedulestoassurethatthedatahasthefollowingfeatures:
• Accuracy• Consistency • Unity • Uniformity• EffectivearrangementThestagesatwhicheditingshouldbeperformedcanbeclassifiedas
follows: • Field editing:This involves reviewing the reporting forms,by the
investigator,thatarewritteninanabbreviatedorillegibleformbytheinformantatthetimeofrecordingtherespondent’sresponses.Suchtypeofeditingmustbedoneimmediatelyaftertheinterview.Ifperformedaftersometime,sucheditingbecomescomplicatedfortheresearcher,
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asitisdifficulttodecipheranyparticularindividual’swritingstyle.Theinvestigatorneedstobecarefulwhilefieldeditingandrestraintheresearcherfromcorrectingerrorsoromissionbyguesswork.
• Central editing: Thiskindofeditinginvolvesathorougheditingoftheentiredatabyasingleeditororateamofeditors.Ittakesplacewhenall theschedulescreatedaccording to the researchplanhavebeen completed and returned to the researcher.Editors correct theerrorssuchasdatarecordedinthewrongplaceorthedatarecordedinmonthswhenitshouldberecordedinweeks.Theycanprovideanappropriateanswertoincorrectormissingrepliesbyreviewingtheother information in the schedule.At times, the respondent canbecontactedforclarification.Insomecases,iftheanswerisinappropriateorincompleteandanaccurateanswercannotbedeterminedonanybasis, thentheeditorshoulddeleteorremovethatanswerfromthecollecteddata.He/Shecanputanoteas‘noanswer’inthiscase.Theanswers thatcanbeeasilydecipheredaswrongshouldbedroppedfromthefinalresults.Besidesusingtheabove-statedmethodsaccordingtothedatasource,
theresearchershouldalsokeepinmindthefollowingpointswhileediting: •Familiaritywiththeinstructionsgiventointerviewersandcoders •Know-howofeditinginstructions •Singlelinestrikingfordeletingofanoriginalentry •Standardizedanddistinctiveeditingofdata • Initializationofallanswersthatarechanged
Coding of data
Thecodingofdatacanbedefinedasrepresentingthedatasymbolicallyusingsomepredefinedrules.Oncedataiscodedandsummarized,theresearchercananalyseitandrelationshipscanbefoundamongitsvariouscategories.
Checklist for coding
This enables the researcher to classify the responses of the individualsaccordingtoalimitednumberofcategoriesorclasses.Suchclassesshouldpossessthefollowingimportantcharacteristics: •Classesshouldbeappropriateandinaccordancetotheresearchproblem
underconsideration. •Theymustincludeaclassforeverydataelement. •There shouldbe amutual exclusivity,whichmeans that a specific
answercanbeplacedinoneandonlyonecellofagivencategoryset. •Theclassesshouldbeone-dimensional.Thismeansthateveryclassis
definedintermsofonlyoneconcept.
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Significance of coding
Codingof data is necessary for its efficient analysis.Codiing facilitatesreductionofdatafromavarietytoasmallnumberofclasses.Thus,onlythatinformationwhichisimportantandcriticalforanalysisisretainedintheresearch.Codingdecisionsareusuallytakenatthedesigningstageofthequestionnaire.Thismakesitpossibletopre-codethequestionnairechoices,whichinturn,ishelpfulforcomputertabulation.
However, incaseofhandcoding,somestandardmethodshouldbeused.One suchmethod is to code in themarginwith a colouredpencil.Theothermethodistotranscribedatafromthequestionnairetoacodingsheet.Whatevermethodisadopted,youshouldensurethatcodingerrorsarealtogethereliminatedorreducedtoaminimumlevel.
Classification of data
Research studies involve extensive collection of rawdata and usage ofthedatatoimplementtheresearchplan.Tomaketheresearchplaneasier,the data needs to be classified in different groups for understanding therelationshipamongthedifferentphasesoftheresearchplan.Classificationofdatainvolvesarrangementofdataingroupsorclassesonthebasisofsomecommoncharacteristics.Themethodsofclassificationcanbedividedunderthefollowingtwoheadings: •Classificationaccordingtoattributes •Classificationaccordingtoclassintervals
Figure11.1showsthecategoriesofdata.Figure4.1showsthecategoriesofdata.
Fig. 4.1 DataClassificatio
CHECK YOUR PROGRESS 1. Whatdoyouunderstandby
fieldediting? 2. Whatpointsshouldthe
researcherkeepinmindwhileperformingeditingwork?
3. Howdoescodinghelpinretainingimportantinformationinresearch?
Data Classification
AccordingTo
Attributes
AccordingTo Class
Intervals
DESCRIPTIVECLASSIFICATION
SIMPLECLASSIFICATION
MANIFOLD CLASSIFICATION
EXCLUSIVE
CLASS-INTERVALS INCLUSIVE
CLASS-INTERVALS
Fig. 11.1 Data Classification
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Processing and Analysis of Data
Classification of data according to attributes
Dataisclassifiedonthebasisofsimilarfeaturesasfollows: • Descriptive classification:Thisclassificationisperformedaccording
to thequalitativefeaturesandattributeswhichcannotbemeasuredquantitatively.These features can be either present or absent inan individual or an element.The features related to descriptiveclassificationofattributescanbeliteracy,sex,honesty,solidarity,etc.
• Simple classification:Inthisclassificationtheelementsofdataarecategorizedonthebasisofthosethatpossesstheconcernedattributeandthosethatdonot.
• Manifold classification: Inthisclassificationtwoormoreattributesareconsideredsimultaneouslyandthedataiscategorizedintoanumberofclassesonthebasisofthoseattributes.Thetotalnumberofclassesoffinalorderisgivenby2n,wheren=numberofattributesconsidered.
Classification of data according to class intervals
Classifyingdataaccordingtotheclassintervalsisaquantitativephenomenon.Classintervalshelpcategorizethedatawithsimilarnumericalcharacteristics,suchasincome,production,age,weight,etc.Datacanbemeasuredthroughsomestatisticaltoolslikemean,mode,median,etc.Thedifferentcategoriesofdataaccordingtoclassintervalsareasfollows: • Statistics of variables:Thistermreferstothemeasurableattributes,as
thesetypicallyvaryovertimeorbetweenindividuals.Thevariablescanbediscrete,i.e.,takingvaluesfromacountableorfiniteset,continuous,i.e.,havingacontinuousdistributionfunction,orneither.Thisconceptofvariableiswidelyutilizedinthesocial,naturalandmedicalsciences.
• Class intervals:Theyrefertoarangeofvaluesofavariable.Thisintervalisusedtobreakupthescaleofthevariableinordertotabulatethe frequencydistributionofa sample.Asuitableexampleof suchdata classification canbegivenbymeansof categorizing thebirthrateofacountry.Inthiscase,babiesagedzerotooneyearwillformagroup;thoseagedtwotofiveyearswillformanothergroup,andsoon.Theentiredataisthuscategorizedintoseveralnumbersofgroupsorclassesorinotherwords,classintervals.Eachclassintervalhasanupperlimitaswellasalowerlimit,whichisdefinedas‘theclasslimit.’Thedifferencebetweentwoclasslimitsisknownasclassmagnitude.Classescanhaveequalorunequalclassmagnitudes.Thenumberofelements,whichcomeunderagivenclass,iscalledthe
frequencyofthegivenclassinterval.Allclassintervals,withtheirrespectivefrequencies,aretakentogetheranddescribedinatabularformcalledthefrequencydistribution.
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Problems related to classification of data
Theproblemsrelatedtoclassificationofdataonthebasisofclassintervalsaredividedintothefollowingthreecategories: (i)Number of classes and their magnitude:There are differences
regarding the numberof classes intowhichdata canbe classified.Assuch,therearenopre-definedrulesfortheclassificationofdata.It all dependsupon the skill andexperienceof the researcher.Theresearchershoulddisplaythedatainsuchawaythatitshouldbeclearandmeaningfultotheanalyst.
Asregardsthemagnitudeofclasses,itisusuallyheldthatclassintervalsshouldbeofequalmagnitude,butinsomecasesunequalmagnitudesmay result in abetter classification. It is the researcher’sobjectiveandjudgementthatplaysasignificantroleinthisregard.Ingeneral,multiplesoftwo,fiveandtenarepreferredwhiledeterminingclassmagnitudes.H.A.Sturgessuggestedthefollowingformulatodeterminethesizeofclassinterval:
where, i = sizeofclassinterval R = Range(differencebetweenthevaluesofthelargestelement
andsmallestelementamongthegivenelements) N = Numberofitemstobegrouped Sometimes,datamaycontainoneortwoorveryfewelementswith
veryhighorverylowvalues.Insuchcases,theresearchercanuseanopen-endedintervalintheoverallfrequencydistribution.Suchintervalscanbeexpressedbelowtwoyears;ortwelveyearsandabove.However,suchintervalsarenotdesirable,yetcannotbeavoided.
(ii)Choice of class limits:Whilechoosingclasslimits,theresearchermustdeterminethemid-pointofaclassinterval.Amid-pointis,generally,derivedbytakingthesumoftheupperandlowerlimitofaclassandthendividingitbytwo.Theactualaverageofelementsofthatclassintervalshouldremainasclosetoeachotheraspossible.Inaccordancewiththisprinciple,theclasslimitsshouldbelocatedatmultiplesoftwo,five,ten,twentyandhundredandsuchotherfigures.Theclasslimitscangenerallybestatedinanyofthefollowingforms:o Exclusive type class intervals:Theseintervalsareusuallystated
asfollows: • 10–20 • 20–30 • 30–40 • 40–50
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Theseintervalsshouldbereadinthefollowingway: • 10andunder20 • 20andunder30 • 30andunder40 • 40andunder50 Intheexclusivetypeofclassintervals,theelementswhosevaluesare
equaltotheupperlimitofaclassaregroupedinthenexthigherclass.Forexample,anitemwhosevalueisexactlythirtywouldbeputin30–40-classintervalandnotin20–30-classinterval.Inotherwords,anexclusivetypeofclassintervalisthatinwhichtheupperlimitofaclassintervalisexcludedanditemswithvalueslessthantheupperlimit,butnotlessthanthelowerlimit,areputinthegivenclassinterval.o Inclusive type class intervals:Theseintervalsarenormallystated
asfollows: • 11–20 • 21–30 • 31–40 • 41–50 Thisshouldbereadasfollows: • 11andunder21 • 21andunder31 • 31andunder41 • 41andunder51 Inthismethod,theupperlimitofaclassintervalisalsoincludedin
theconcerningclassinterval.Thus,anelementwhosevalueistwentywillbeputin11–20-classinterval.Thestatedupperlimitoftheclassinterval 11–20 is twentybut the real upper limit is 20.999999 andassuch11–20classintervalreallymeanselevenandundertwenty-one.Whendata tobe classifiedhappens tobe adiscreteone, thentheinclusivetypeofclassificationshouldbeapplied.Butwhendatahappenstobeacontinuousone,theexclusivetypeofclassintervalscanbeused.
(iii)Determining the frequency of each class:Thefrequencyofeachclasscanbedeterminedusingtallysheetsormechanicalaids.Intallysheets,theclassgroupsarewrittenonasheetofpaperandforeachitemastroke(asmallverticalline)ismarkedagainsttheclassgroupinwhichitfalls.Thegeneralpracticeisthataftereveryfoursmallverticallinesinaclassgroup,thefifthlinefortheelementfallinginthesamegroupisindicatedasadiagonallinethroughtheabovesaidfourlines.This
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enablestheresearchertoperformthecountingofelementsineachoneoftheclassgroups.Table11.1displaysahypotheticaltallysheet.
Table 11.1 A Tally Sheet
In case of large inquiries and surveys, class frequencies can bedeterminedbymeansofmechanicalaids,i.e.,withthehelpofmachines.Suchmachinesfunction,eithermanuallyorautomaticallyandrunonelectricity.Thesemachinescansortoutcardsataspeedofaround25,000cardsperhour.Althoughthismethodincreasesthespeed,itisanexpensivemethod.
Tabulation of data
Insimpleterms,tabulationmeansplacingtheresultsanddatacollectedfromresearchinatabularform.
Methods of tabulation
Tabulation can be done eithermanually ormechanically using variouselectronic devices. Several factors like the size and type of study, costconsiderations,timepressuresandavailabilityoftabulatingmachinesdecidethechoiceoftabulation.Relativelylargedatarequirescomputertabulation.Manualtabulationispreferredincaseofsmallinquiries,whenthenumberofquestionnairesissmallandtheyareofrelativelyshortlength.Thedifferentmethodsusedinhandtabulationareasfollows: • Direct tally method:Thismethodinvolvessimplecodes,whichthe
researchercanusetodirectlytallydatawiththequestionnaire.Thecodesarewrittenonasheetofpapercalledtallysheetandforeachresponse,astrokeismarkedagainstthecodeinwhichitfalls.Usually,aftereveryfourstrokesagainstaparticularcode,thefifthresponseisindicatedbydrawingadiagonalorhorizontallinethroughthestrokes.Thesegroupsareeasytocountandthedataissortedagainsteachcodeconveniently.
• List and tally method: In this method, code responses maybe transcribed into a largeworksheet, allowing a line for eachquestionnaire.Thisfacilitateslistingofalargenumberofquestionnairesinoneworksheet.Talliesarethenmadeforeachquestion.
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• Card sort method:Thisisthemostflexiblehandtabulationmethod,wherethedataisrecordedonspecialcardsthatareofconvenientsizesandshapesandhaveaseriesofholes.Eachholeinthecardstandsforacode.Whenthecardsarestacked,aneedlepassesthroughaparticularholerepresentingaparticularcode.Thesecardsarethenseparatedandcounted.Inthisway,frequenciesofvariouscodescanbefoundoutbytherepetitionofthistechnique.
Significance of tabulation
Tabulationenablestheresearchertoarrangedatainaconciseandlogicalorder.Itsummarizestherawdataanddisplaysthesameinacompactformforfurtheranalysis.Ithelpsintheorderlyarrangementofdatainrowsandcolumns.Thevariousadvantagesoftabulationofdataareasfollows: •Atablesavesspaceandreducesdescriptiveandexplanatorystatements
totheminimum. • Itfacilitatesandeasesthecomparisonprocess. • Summationofelementsanddetectionofomissionsanderrorsbecomes
easyinatabulardescription. •Atableprovidesabasisforvariousstatisticalcomputations.
Checklist for tables
Atableshouldcommunicatetherequiredinformationtothereaderinsuchawaythatitbecomeseasyforhim/hertoread,comprehendandrecallinformationwhen required.Certainconventionshavetobefollowedduringtabulationofdata.Theseareasfollows: •Alltablesshouldhaveaclear,preciseandadequatetitletomakethem
intelligibleenoughwithoutanyreferencetothetext. •Tablesshouldbefeaturedwithclarityandreadability. •Every table shouldbegivenadistinctnumber to facilitateaneasy
reference. •Thetableshouldbeofanappropriatesizeandtallywiththerequired
information. •Headingsforcolumnsandrowsshouldbeinboldfontletters.Itisa
generalruletoincludeanindependentvariableintheleftcolumnorthefirstrow.Thedependentvariableiscontainedinthebottomrowortherightcolumn.
•Numbersshouldbedisplayedsuchthattheyareneatandreadable. •Explanatory footnotes, if any, regarding the table shouldbeplaced
directlybeneaththetable,alongwiththereferencesymbolsusedinthetable.
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•Thesourceofthetableshouldbeindicatedjustbelowthetable. •Thetableshouldcontainthicklinestoseparatedataunderoneclass
fromthedataunderanotherclassandthinlinestoseparatethedifferentsubdivisionsoftheclasses.
•Allcolumnfiguresshouldbeproperlyaligned. •Abbreviationsshouldbeavoidedinatabletothebestpossibleextent. • Ifdatahappenstobelarge,thenitshouldnotbecrowdedinasingle
table.Itmakesthetableunwieldyandinconvenient.Tabulationcanalsobeclassifiedascomplexandsimple.Theformer
typeoftabulationgivesinformationaboutoneormoregroupsofindependentvariables,whereas, the latter shows the division of data in twoormorecategories.
Diagrams
Thedatawecollectcanoftenbemoreeasilyunderstoodforinterpretationifitispresentedgraphicallyorpictorially.Diagramsandgraphsgivevisualindicationsofmagnitudes,groupings,trendsandpatternsinthedata.Theseimportantfeaturesaremoresimplypresentedintheformofgraphs.Also,diagramsfacilitatecomparisonsbetweentwoormoresetsofdata.
Thediagramsshouldbeclearandeasytoreadandunderstand.Toomuchinformationshouldnotbeshowninthesamediagram;otherwise,itmaybecomecumbersomeandconfusing.Eachdiagramshouldincludeabriefandself-explanatorytitledealingwiththesubjectmatter.Thescaleofthepresentationshouldbechoseninsuchawaythattheresultingdiagramisofappropriatesize.Theintervalsontheverticalaswellasthehorizontalaxisshouldbeofequalsize;otherwise,distortionswouldoccur.
Diagramsaremore suitable to illustrate thedatawhich isdiscrete,whilecontinuousdataisbetterrepresentedbygraphs.Wewillstudyaboutdiagrammaticelucidationindetailinthenextunit.
11.3 TYPES OF ANALYSIS
Analysis of data is the process of transforming data for the purpose ofextractingusefulinformation,whichinturnfacilitatesthediscoveryofsomeusefulconclusions.Findingconclusionsfromtheanalyseddataisknownas interpretationofdata.However, if theanalysis isdone, in thecaseofexperimentaldataorsurvey,thenthevalueoftheunknownparametersofthepopulationandhypothesistestingisestimated.
Analysisofdatacanbeeitherdescriptiveor inferential. Inferentialanalysisisalsoknownasstatisticalanalysis.Thedescriptiveanalysisisusedtodescribethebasicfeaturesofthedatainastudysuchaspersons,work
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groupsandorganizations.Theinferentialanalysisisusedtomakeinferencesfromthedata,whichmeansthatwearetryingtounderstandsomeprocessandmakesomepossiblepredictionsbasedonthisunderstanding.Thethreetypesofanalysesareasfollows: (i)Multiple regression analysis:Thistypeofanalysisisusedtopredicta
singledependentvariablebyasetofindependentvariables.Inmultipleregressionanalysis,theindependentvariablesarenotcorrelatedtoeachother.
(ii)Multiple discriminant analysis: Inmultiplediscriminantanalysis,there is one single dependent variable,which is very difficult tomeasure.Oneof themain objectives of this type of analysis is tounderstand thegroupdifferencesandpredict the likelihood that anentity,i.e.,anindividualoranobject,belongstoaparticularclassorgroupbasedonseveralmetric-independentvariables.
(iii)Canonical correlation analysis: It is amethod for assessing therelationship between variables.This analysis also allows you toinvestigatetherelationshipbetweentwosetsofvariables.
Univariate, Bivariate and Multivariate Analysis
Manytypesofanalysesareperformedaccordingtothevariancethatexistsinthedata.Suchanalysesiscarriedouttocheckifthedifferencesbetweenthreeormorevariablesaresignificantenoughtoevaluatethemstatistically.There are three typesof such analyses; namely, univariate, bivariate andmultivariateanalyses.Thesetypesareexplainedbelow: (i)Univariate analysis:Inthisanalysis,onlyasinglevariableistaken
intoconsideration.Itisusuallythefirstactivitypursuedwhileanalysingthedata.Itisperformedwiththepurposeofdescribingeachvariableintermsofmean,medianormode,andvariability.Examplesofsuchanalysisareaveragesorasetofcasesthatmaycomeunderaspecificcategoryamidstawholesample.
(ii)Bivariate analysis:Thistypeofexaminestherelationshipbetweentwovariables.Ittriestofindtheextentofassociationthatexistsamongthesevariables.Thus,abivariateanalysismayhelpyou;forexample,tofindwhetherthevariablesofirregularmealsandmigraineheadachesare associate; and up towhat extent.Here, twovariables are thusstatisticallymeasuredsimultaneously.
(iii)Multivariate analysis:This type of analysis involves observationand analysis of three ormore than three statistical variables at atime.Suchananalysisisperformedusingstatisticaltestsoreveninatabularformat.Thus,forexample,youcanstudythevariablesofage,educationalqualificationandannualincomeofagivensetofpopulationatthesametimeusingthemultivariateanalysismethod.
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Usually,thesetypesofanalysesaremoreconvenientwhenperformedinatabularformat.Thisinvolves,usingacross-classificationorcontingencytable. Such a table ismade of two columns and two rows, showing thefrequenciesoftwovariablesthataredisplayedinrowsandcolumns.Thisismorepopularlyknownasconstructingthebivariatetable.Traditionally,theindependentvariableisdisplayedincolumnsandthedependentonesinrows.Amultivariatetable,ifrelatedtothesamedata,istheresultofcombiningthebivariatetables.Inthiscase,eachbivariatetableisknownaspartialtable.Usually,amultivariate table iscreatedwith thepurposeofexplainingorreplicatingtheprimaryrelationshipthatisfoundinthebivariatetable.Table11.2(a)and(b)showsanexampleofabivariatetableandamultivariatetable.
Table 11.2 (a) Bivariate Table
1991 1992 1993
Percentageofstudentsfailed 33 per cent 38 per cent 42 per centPercentageofstudentspassed 67 per cent 62 per cent 58 per cent
Table 11.2 (b) Multivariate Table
1991 1992 1993First Attempt Second Attempt ThirdAttempt
Percentageof studentswhopassedinMaths
27 per cent 35 per cent –
Percentageof studentswhopassedinEnglish
53 per cent 60 per cent 44 per cent
Although the data in both tables is related, except the variable of‘attempts’, themultivariate table has been displayed separately in thisexample.However,youshouldnotethatthetableshavedealtsimultaneouslywithtwoormorevariablesofthedata.
Data interpretation
Datainterpretationreferstotheidentificationoftrendsindifferentvariables.Theresearcherusesstatisticsforthispurpose.Theresearcherisrequiredtobefamiliarwiththeknowledgeofthescalesofmeasurement.Thisenableshim/her to choose the appropriate statisticalmethod for his/her researchproject.The scales ofmeasurement facilitate the allotment of numericalvaluestocharacteristicsadheringtoanyspecificrules.Thismeasurementisalsorelatedtosuchlevelsofmeasurementofdatalikenominal,ordinalandinternalandratiolevels.Theselevelscanbeexplainedasfollows:
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• Nominal measurement:Thenominalmeasurementassignsanumeralvalue to a specific characteristic. It is the fundamental form ofmeasurement.Thenominalmeasurementcalculatesthelowestlevelofdataavailableformeasurement.
• Ordinal measurement:Thistypeofmeasurementinvolvesallottingaspecificfeaturetonumeralvalueintermsofaspecificorder.Theordinalscaledisplaysthewayinwhichtheentityismeasured.Theordinalscaleofmeasurementisusedtocalculateandderivedatapertainingtothemedian,percentage,rankorder,correlationsandpercentile.
• Interval measurement:A researcher can depict the differencebetweenthefirstaspectofadataandanotheraspectusingthislevelofmeasurement.The interval scale ofmeasurement is useful forthe researcher in severalways. It canbe applied in the calculationof arithmeticmean, averages, standard deviations anddeterminingcorrelationbetweendifferentvariables.
• Ratio measurement:Inthismethod,therearefixedproportions(ratio)betweenthenumbernumericalandtheamountofthecharacteristicsthatitrepresents.Aresearchershouldrememberwhilemeasuringtheratiolevelsthat,afixedzeropointexists.Theratiolevelofmeasurementfacilitatesresearchersindetermining,iftheaspectspossessanycertaincharacteristic.Almost any type of arithmetical calculations can beexecutedusingthisscaleofmeasurement.Themostimportantfeatureofanymeasuringscaleisitsreliabilityand
validity,whichisexplainedasfollows: • Reliability: It is the term used to deal with accuracy.A scale
measurementcanbesaidtobereliable,whenitexactlymeasures,onlythatwhatitissupposedtomeasure.Inotherwords,whenthesameresearcherrepeatsatest,i.e.,withadifferentgroupbutresemblingtheoriginalgroup,he/sheshouldgetthesameresultsastheformer.
• Validity:According to Leedy, validity is the assessment of thesoundnessandtheeffectivenessofthemeasuringinstrument.Therearefourtypesofvalidity,whichcanbestatedasfollows:o Content validity: It dealswith the accuracywithwhich an
instrumentmeasuresthefactorsorcontentofthecourseorsituationsoftheresearchstudy.
o Prognostic validity: It depends on the possibility tomakejudgements from results obtained by the concernedmeasuringinstrument.Thejudgementisfutureoriented.
o Simultaneous validity:Thisinvolvescomparingofonemeasuringinstrumentwithanother;onethatmeasuresthesamecharacteristicandisavailableimmediately.
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Multiple regression analysis
Multiple regression analysisisastatisticaltoolthathelpstheresearcherstoevaluatetheeffectofdifferentfactorsontheconsequencesoccurringatthe same time. It analyzes the relationshipbetween several independentor predictor variables and a dependent variable. In research technology,regressionanalysisisusedtoinvestigateaparticularsetofpredictorsandtoshowdifferencesintheconsequencesthatoccur.Generally,regressionisusedtodeterminetheeffectofthespecificfactorsalongwiththeotherfactorsthatinfluencetheseconsequences.Theresearchersusealgebraicmethodstoanalyzetheresultbymakingagroupoffactorsassociatedwithaparticularphenomenonasaconstant.Accordingtothedictionarymeaning,themultipleregressionisastatisticaltechniquethatpredictsvaluesofonevariableonthebasisoftwoormoreothervariables.Multiple regression and statistics: Theterm‘multipleregression’wasfirstgivenbyPearson.Theregressionisoftwotypes,simpleandmultipleandboththeregressiontechniquesarerelatedtotheAnalysisOfVariance(ANOVA).Ofthese,multipleregressionisthesimplestmethodincomparisontoothermultivariatestatisticaltechniques.Multiple regression and mathematics: Themultipleregressiontechniqueis used inmathematics to formulate simple regression equations, and toevaluatethebestfittingcurveforastraightlinealongthedotsonanx-y plot orascattergram.
Check Your Progress
1.Whatdoyoumeanbyprocessingofdata? 2.Listthefunctionsthatcanbeperformedondata. 3.Whatis‘fieldediting’? 4.Datacanbeclassifiedintothreecategories.Whatarethey? 5.Listthreetypesofanalyses.
11.4 ANSWERS TO CHECK YOUR PROGRESS QUESTIONS
1.Researchisincompletewithoutproperanalysisofthecollecteddata.Processingofdatainvolvesanalysisandmanipulationofthecollecteddatabyperformingvariousfunctions.
2.Thefunctionsthatcanbeperformedondataare:• Editing• Coding
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• Tabulation• Classification
3.Themethodoffieldeditinginvolvesreviewingreportingformsbytheinvestigatorthatarewritteninanabbreviatedformbytheinformant.Thiskindofeditingisusuallydoneimmediatelyaftertheinterview.
4.Data can be classified into three categories, they are, descriptiveclassification,simpleclassificationandmanifoldclassification.
5.Threetypesofanalysisare:• Multipleregressionanalysis• Multiplediscriminantanalysis• Canonicalcorrelationanalysis
11.5 SUMMARY
•Researchdoesnotmerelyconsistofdatathatiscollected.Researchisincompletewithoutproperanalysisofthecollecteddata.
•Dataprocessinginvolvesanalysisandmanipulationofthecollecteddatabyperformingvariousfunctions.Thedatahastobeprocessedinaccordancewiththeoutlinelaiddownwhentheresearchplaninbeingdeveloped.
•Editingofdatainvolvesthetestingofdatacollectioninstrumentsinordertoensuremaximumaccuracy.
•Acollecteddatamusthavefivefeatures,suchasaccuracy,consistency,unity,uniformityandeffectivearrangement.
•Representingthedatasymbolicallybyusingsomepredefinedrulesistermedascodingofdata.Codingofdataisverymuchessentialforperformingefficientanalysis.
•Datacanbeclassifiedintothreecategoriesaccordingtoattributesandintotwoasperclassintervals.
•Tabulationmeansplacingtheresultsanddatacollectedfromresearchinatabularform.Tabulationcanbedoneeithermechanicallyormanuallyusingvariouselectronicdevices.
•Theprocessoftabulationenablestheresearchertoarrangedatainaconciseand logicalorder. It summarizes rawdataanddisplays thesameinacompactformforfurtheranalysis.
•Analysisofdataistheprocessoftransformingdataforthepurposeofextractingusefulinformation,whichinturnfacilitatesthediscoveryofsomeusefulconclusions.
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•Analysisofdatacanbeeitherdescriptiveor inferential. Inferentialanalysisisalsoknownasstatisticalanalysis.
•Thedescriptiveanalysisisusedtodescribethebasicfeaturesofthedatainastudysuchaspersons,workgroupsandorganizations.
•Theinferentialanalysisisusedtomakeinferencesfromthedata,whichmeansthatwearetryingtounderstandsomeprocessandmakesomepossiblepredictionsbasedonthisunderstanding.
•Manytypesofanalysesareperformedaccordingtothevariancethatexistsinthedata.Suchanalysesiscarriedouttocheckifthedifferencesbetweenthreeormorevariablesaresignificantenoughtoevaluatethemstatistically.
•Data interpretation refers to the identificationof trends indifferentvariables.Theresearcherusesstatisticsforthispurpose.
•Multipleregressionanalysisisastatisticaltoolthathelpstheresearcherstoevaluatetheeffectofdifferentfactorsontheconsequencesoccurringatthesametime.
•Multiple regression analyses the relationship between severalindependentorpredictorvariablesandadependentvariable.
11.6 KEY WORDS
• Coding of Data: Itreferstoasymbolicrepresentationofdateusingsomepredefinedrules.
• Analysis of Data:Itreferstotheprocessoftransformingdataforthepurposeofextractingusefulinformation.
• Multiple Regression Analysis: It is a statistical tool that helpsthe researchers to evaluate the effect of different factors on theconsequencesoccurringatthesametime.
11.7 SELF ASSESSMENT QUESTIONS AND EXERCISES
Short Answer Questions
1.Whatisprocessinganddataanalysis? 2.Whatiscentralediting? 3.Brieflydiscussthesignificanceofcoding. 4.Writeashortnoteontheclassificationofdataaccordingtoattributes.
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Long Answer Questions
1.Examinetheclassificationofdata. 2.Whataretheproblemsrelatedtoclassificationofdata?Discuss. 3.Definetabulationandexplainitsmethods.Whatisitssignificance?
11.8 FURTHER READINGS
Creswell,JohnW.2002.Research Design: Qualitative, Quantitative, and Mixed Methods Approaches.London:SagePublicationsInc.
Booth,Wayne,GregoryG.ColombandJosephM.Williams.1995.The Craft of Research.Chicago:UniversityofChicagoPress.
Bryman,AlanandEmmaBell.2015.Business Research Methods.4thEdition.UnitedKingdom:OxfordUniversityPress.
Gupta,S.L.andHiteshGupta. 2012. Business Research Methods. NewDelhi: TataMcGrawHillEducationPrivateLimited.
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BLOCK - IV
HYPOTHESIS AND REPORT WRITING
UNIT 12 TEST OF SIGNIFICANCEStructure 12.0 Introduction 12.1 Objectives 12.2 FundamentalsofTestProcedure
12.2.1 TypesofHypothesisTesting 12.3 ParametricTests
12.3.1 TestsConcerningMeansinCaseofSingleandTwoPopulationMeans-Z-test
12.3.2 HypothesisTestingforComparingTwoRelatedTerms:T-test 12.3.3 HypothesisTestingofProportions,DifferencebetweenProportionsand
ComparingVariance 12.3.4 TestingtheEqualityofVariancesofTwoNormalPopulations:F-test
12.4 StatisticalTechniquesofHypothesisTesting 12.5 Chi-SquareTestandContingencyTable 12.6 AnswerstoCheckYourProgressQuestions 12.7 Summary 12.8 Key Words 12.9 SelfAssessmentQuestionsandExercises 12.10 FurtherReadings
12.0 INTRODUCTION
Inthepreviousunit,youwereintroducedtotheprocessingandanalysisofdata.Inthisunit,thediscussionontheanalysisandprocessingofdatawillcontinue.ItwilldiscussvariousparametrictestssuchasTtest,FtestandZtest.Theunitwillbeginwithadiscussiononthefundamentalsoftestingprocedure,aswellasthevarioustypesofhypothesistesting.
12.1 OBJECTIVES
Aftergoingthroughthisunit,youwillbeableto: •Discussthefundamentalsofhypothesistestingprocedure •Examinethevarioustypesofparametrictests • Illustratethechi-squaretest,t-testandz-test
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Test of Significance12.2 FUNDAMENTALS OF TEST PROCEDURE
Thefollowingfundamentalstepsarefollowedintestingofahypothesis:Setting up of a hypothesis: Firststepistoestablishthehypothesistobetested.Asitisknown,thesestatisticalhypothesesaregenerallyassumptionsaboutthevalueofthepopulationparameter;thehypothesisspecifiesasinglevalueorarangeofvaluesfortwodifferenthypothesesratherthanconstructingasinglehypothesis.Thesetwohypothesesaregenerallyreferredtoasthe(1)nullhypothesesdenotedbyH0and(2)alternativehypothesisdenotedbyH1.
Thenull hypothesis is the hypothesis of the population parametertakingaspecifiedvalue.Incaseoftwopopulations,thenullhypothesisisofnodifferenceorthedifferencetakingaspecifiedvalue.Thehypothesisthatisdifferentfromthenullhypothesisisthealternativehypothesis.IfthenullhypothesisH0isrejectedbaseduponthesampleinformation,thealternativehypothesisH1isaccepted.Therefore,thetwohypothesesareconstructedinsuchawaythatifoneistrue,theotheroneisfalseandviceversa.Therecanalsobesituationswheretheresearcherisinterestedinestablishingtherelationshipbetweenanytwovariables.Insuchacase,anullhypothesisissetasthehypothesisofnorelationshipbetweenthosetwovariables;whereasthealternativehypothesisisthehypothesisoftherelationshipbetweenvariables.Therejectionofthenullhypothesisindicatesthatthedifferences/relationshiphaveastatisticalsignificanceandtheacceptanceofthenullhypothesismeansthatanydifference/relationshipisduetochance.Setting up of a suitable significance level: Thenextstepinthetestingofhypothesisexerciseistochooseasuitablelevelofsignificance.Thelevelofsignificancedenotedbyαischosenbeforedrawinganysample.Thelevelofsignificancedenotestheprobabilityofrejectingthenullhypothesiswhenitistrue.Thevalueofαvariesfromproblemtoproblem,butusuallyitistakenaseither5percentor1percent.A5percentlevelofsignificancemeansthatthereare5chancesoutofhundredthatanullhypothesiswillgetrejectedwhenitshouldbeaccepted.Thismeansthattheresearcheris95percentconfidentthatarightdecisionhasbeentaken.Therefore,itisseenthattheconfidencewithwhicharesearcherrejectsoracceptsanullhypothesisdependsuponthelevelofsignificance.Whenthenullhypothesisisrejectedatanylevelofsignificance,thetestresultissaidtobesignificant.Further,ifahypothesisisrejectedat1percentlevel,itmustalsoberejectedat5percentsignificancelevel.Determination of a test statistic: Thenextstepistodetermineasuitabletest statistic and itsdistribution.Aswouldbe seen later, the test statisticcouldbet,Z,χ2orF,dependinguponvariousassumptionstobediscussedlaterinthebook.
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Determination of critical region: Before a sample is drawn from thepopulation,itisveryimportanttospecifythevaluesofteststatisticthatwillleadtorejectionoracceptanceofthenullhypothesis.Theonethatleadstotherejectionofnullhypothesisiscalledthecriticalregion.Givenalevelofsignificance,α,theoptimalcriticalregionforatwo-tailedtestconsistsofthatα/2percentareaintherighthandtailofthedistributionplusthatα/2percentinthelefthandtailofthedistributionwherethatnullhypothesisisrejected.Therefore,establishingacriticalregionissimilartodetermininga100(1–α)percentconfidenceinterval.Computing the value of test-statistic: Thenextstepistocomputethevalueoftheteststatisticbaseduponarandomsampleofsizen.Oncethevalueofteststatisticiscomputed,oneneedstoexaminewhetherthesampleresultsfallinthecriticalregionorintheacceptanceregion.Making decision: Thehypothesismayberejectedoraccepteddependinguponwhether the value of the test statistic falls in the rejection or theacceptance region.Management decisions are based upon the statisticaldecisionofeitherrejectingoracceptingthenullhypothesis.
If thehypothesis isbeing testedat5percent levelofsignificance,itwouldberejectediftheobservedresultshaveaprobabilitylessthan5per cent. In such a case, the differencebetween the sample statistic andthehypothesizedpopulationparameterisconsideredtobesignificant.Ontheother hand, if thehypothesis is accepted, thedifferencebetween thesamplestatisticandthehypothesizedpopulationparameterisnotregardedassignificantandcanbeattributedtochance.
12.2.1 Types of Hypothesis Testing
Ahypothesis is tested to identify the errors that have occurred in thestatementsandconceptsusedinthathypothesis.Hypothesistestingcanbebroadlydividedintotwotypes,whichareasfollows: •Parametrictestsorstandardtestsofhypothesis •Non-parametrictestsordistribution-freetestsofhypothesis
Therearethetwogeneralclassesofstatisticaltests.Parametrictestsaremorepowerfulbecausetheirdataiseitherofintervalorratiolevelandbasedonthefollowingassumptions: (a)Theobservationsmustbeindependent. (b)Theobservationsneedtobedrawnfrompopulationsthatarenormally
distributed. (c)Thepopulationsshouldhaveequalvariances.
Itistheresearcher’sresponsibilitytochecktheassumptionsrelevanttothechosentest.Someofthepopularparametrictestsarez-testt-testandF-test.
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Test of SignificanceNon-parametrictests,ontheotherhand,havelessstringentandfewerassumptions.Theydonotspecifynormallydistributedpopulationsorequalityofvariances.Some tests require independenceof cases,whileothers aredesignedexpresslyforsituationswithrelatedcases.Non-parametrictestsaregenerallyusedforqualitativeanalysis(ordinalornominal-leveldata).Boththecategoriesoftestsprovideefficientresultsprovidedtheirselectionsareappropriate.Non-parametrictestsincludechi-square,run-test,Mann-Whitneytest,Kruskal-Wallistest,etc.
1. Parametric tests or standard tests of hypothesis
Parametric testsassumecertainpropertiesof thepopulationsample suchas observations fromanormal population, large sample size, populationparameterslikemeanandvariance.Thevariousparametrictestsofhypothesisarebasedontheassumptionofnormality.Inotherwords,thesourceofdataforthemisnormallydistributed.Theycanbelistedasfollows: •Z-test: Thiskindoftestisbasedonnormalprobabilitydistribution.It
ismostlyusedtojudgethesignificanceofmeanasastatisticalmeasure.Thisisthemostfrequentlyusedtestinresearchstudies.Itisgenerallyusedtocomparethemeanofasamplewiththehypothesizedmeanof thepopulation. It isalsoused incase thepopulationvariance isknown.Itishelpfulinjudgingthesignificanceofdifferencebetweenthemeansoftwoindependentlargesamples,tocomparethesampleproportiontoatheoreticalvalueofpopulationproportionandtojudgethesignificanceofmedian,modeandcoefficientofcorrelation.
•T-test:This test is basedon t-distributionand isused to judge thesignificanceofasamplemeanorthedifferencebetweenthemeansoftwosmallsampleswhenthepopulationvarianceisnotknown.
•χ2:This test is based on a chi-square distribution and is used forcomparingasamplevariancetoatheoreticalpopulationvariance.
•F-test:ThistestisbasedonF-distributionandisalsousedtocomparethevarianceoftwoindependentsamples.Itisalsousedtocomparethesignificanceofmultiplecorrelationcoefficients.
2. Non-parametric tests or distribution-free tests of hypothesis
Therearesituationsintestingwhereassumptionscannotbemade.Insuchsituations,non-parametricmethodsareemployed.Therearevarioustypesofnon-parametrictests.Theimportantonesareasfollows: •Sign test:Thisisoneoftheeasiesttestsinpracticebasedontheplus/
minussignofanobservationinasample.Thesignmaybeoneofthefollowingtwotypes:o One-sample sign test:Thisisaverysimpledistribution-freetest
andisappliedincaseofasamplefromacontinuoussymmetrical
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population,whereintheprobabilityofasampletobeeitherlessormorethanmeanishalf.Here,totestanullhypothesis,allthoseitems,whicharegreaterthanthealternatehypothesis,arereplacedbyaplussignandthose,whicharelessthanthealternatehypothesis,arereplacedbyaminussign.
o Two-sample sign test:Incaseofall theproblemsconsistingofpaireddata,two-samplesigntestisused.Here,eachpairofvaluescanbereplacedwithaplussigninthefirstvalueofthefirstsamplewiththefirstvalueofthesecondsample.Ifthefirstvalueisless,minussignisassigned.
•Fisher–Irwin test:Thisisappliedwherethereisnodifferencebetweentwosetsofdata.Inotherwords,itisusedwhereyoucanassumethattwodifferenttreatmentsaresupposedlydifferentintermsoftheresultsthattheyproduce.Itisappliedinallthosecaseswhereresultforeachiteminasamplecanbedividedintooneofthetwomutuallyexclusivecategories.
•McNamara test:Itisappliedwherethedataisnominalinnatureandisrelatedtotwointerrelatedsamples.Byusingthistest,youcanjudgethesignificanceofanyobservedchangesinthesamesubject.
•Wilcoxon matched-pairs test:This test isapplied in thecaseofamatched-pairsuchasoutputoftwosimilarmachines.Here,youcandetermineboththedirectionandthemagnitudebetweenthematchedvalues.ThistestisalsocalledSignedRankTest.
Check Your Progress
1.Whatarethetwotypesofhypothesistesting? 2.WhenistheFisher-Irwintestapplied?
12.3 PARAMETRIC TESTS
A parametric statistical test is one thatmakes assumptions about theparameters(definingproperties)ofthepopulationdistribution(s)fromwhichone’sdataaredrawn.Letusstudythesetestsindetail.
12.3.1 Tests Concerning Means in Case of Single and Two Population Means- Z-test
Incasethesamplesizenislargeorsmallbutthevalueofthepopulationstandarddeviationisknown,aZ-testisappropriate.Therecanbealternatecasesoftwo-tailedandone-tailedtestsofhypotheses.CorrespondingtothenullhypothesisH0:µ=µ0,thefollowingcriteriacouldbeusedasshowninTable12.1.
NOTES
Self-InstructionalMaterial 197
Test of Significance Theteststatisticisgivenby,
where,X = Samplemeanσ = PopulationstandarddeviationµH0 = Thevalueofµundertheassumptionthatthenullhypothesisis
truen = Sizeofsample
Table 12.1 Criteria for accepting or rejecting null hypothesis under different cases of alternative hypotheses
Ifthepopulationstandarddeviationσisunknown,thesamplestandarddeviation
isusedasanestimateofσ.ItmaybenotedthatZαandZα/2areZvaluessuchthattheareatotherightunderthestandardnormaldistributionisαandα/2respectively.Belowaresolvedexamplesusingtheaboveconcepts.Example 12.1Asampleof200bulbsmadebyacompanygivealifetimemeanof1540hourswithastandarddeviationof42hours.Isitlikelythatthesamplehasbeendrawnfromapopulationwithameanlifetimeof1500hours?Youmayuse5percentlevelofsignificance.Solution:Intheaboveexample,thesamplesizeislarge(n=200),samplemean(X )equals1540hoursandthesamplestandarddeviation(s)isequalto42hours.Thenullandalternativehypothesescanbewrittenas:
H0 : µ= 1500hrs H1 : µ≠ 1500hrs
Test of Significance
NOTES
Self-Instructional 198 Material
Itisatwo-tailedtestwithlevelofsignificance(α)tobeequalto0.05.Sincenislarge(n>30),thoughpopulationstandarddeviationσisunknown,onecanuseZ-test.Theteststatisticsaregivenby:
where,µH0=Valueofµundertheassumptionthatthenullhypothesisistrue
ˆXs =Estimatedstandarderrorofmean
Here,
(Note thatisestimatedvalueofσ.)
Thevalueofα=0.05andsinceitisatwo-tailedtest,thecriticalvalueZisgivenby–Zα/2andZα/2whichcanbeobtainedfromthestandardnormaltable.
Fig 12.1 Rejection regions for Example 12.1
SincethecomputedvalueofZ=13.47liesintherejectionregion,thenullhypothesisisrejected.Therefore,itcanbeconcludedthattheaveragelifeofthebulbissignificantlydifferentfrom1500hours.
Alternative Approach to the Test of Hypothesis
There is analternativeapproachcalledprobability approachor simplypvalueapproachtotestthehypothesis.Underthisapproach,theresearcherdoesnothavetorefertoZtabletodeterminethecriticalvalue.ReferringtoExample12.1,thepvaluecanbecalculatedasfollows:
p=P(Z>13.47)+P(Z<–13.47)Weknow that the problem is that of a two-sided test andZhas a
symmetricdistribution,therefore,
NOTES
Self-InstructionalMaterial 199
Test of Significancep=2P(Z>13.47)=2×0=0 Now,thedecisionruleis: Reject H0 if p≤α Accept H0 if p>αIn this example, α = 0.05 and p value is less than α, so the null
hypothesisisrejected.Therefore,itmaybenotedthatthesameconclusionisarrivedatandthereisnoneedtolookatthecriticalvalueofZasgiveninthestatisticaltable.Thesedays,mostcomputersoftwarelikeSPSS,EXCEL,SAS,MINITABprovideboththecomputedvalueofteststatisticandthecorrespondingpvalue.Pleasenotethatthepvalueprovidedthereisforthetwo-sidedtest.Incasetheproblemisofaone-sidedtest,thereportedpvalueisdividedby2toobtainthedesiredpvaluefortheproblemandthencomparedwithalpha(α),thelevelofsignificancesoastoeitheracceptorrejectthenullhypothesis.ThisispossiblesinceZ-distributionisasymmetricaldistribution.
Tests for Difference between Two Population Means
So farwe have been concernedwith the testing ofmeans of a singlepopulation.Wetookupthecasesofbothlargeandsmallsamples.Itwouldbeinterestingtoexaminethedifferencebetweenthetwopopulationmeans.Again,variouscaseswouldbeexaminedasdiscussedbelow:
Case of Large Sample
In case both the sample sizes are greater than 30, aZ-test is used.Thehypothesistobetestedmaybewrittenas:
H0 : µ1=µ2
H1 : µ1≠µ2
where, µ1=Meanofpopulation1 µ2=Meanofpopulation2Theaboveisacaseoftwo-tailedtest.Theteststatisticusedis:
1X =Meanofsampledrawnfrompopulation1
2X =Meanofsampledrawnfrompopulation2 n1=Sizeofsampledrawnfrompopulation1
Test of Significance
NOTES
Self-Instructional 200 Material
n2=Sizeofsampledrawnfrompopulation2Ifs1ands2areunknown,theirestimatesgivenby 1s and 1s 2areused.
TheZvaluefortheproblemcanbecomputedusingtheaboveformulaandcomparedwiththetablevaluetoeitheracceptorrejectthehypothesis.Letusconsiderthefollowingproblem.Example 12.2Astudyiscarriedout toexaminewhether themeanhourlywagesof theunskilledworkers in the twocities—AmbalaCanttandLucknoware thesame.TherandomsampleofhourlyearningsinboththecitiesistakenandtheresultsarepresentedintheTable12.2.
Table 12.2 Survey Data on Hourly Earnings in Two Cities
Usinga5percentlevelofsignificance,testthehypothesisofnodifferenceintheaveragewagesofunskilledworkersinthetwocities.Solution:Weusesubscripts1and2forAmbalaCanttandLucknowrespectively.
H0 : µ1=µ2 →µ1–µ2=0 H1 : µ1≠µ2 →µ1–µ2≠0
Thefollowingsurveydataisgiven:
1X =8.95, 2X =9.10, s1=0.40, s2=0.60, n1=200, n2=175, α=0.05Sincebothn1,n2aregreaterthan30andthesamplestandarddeviations
aregiven,aZ-testwouldbeappropriate. Theteststatisticisgivenby
NOTES
Self-InstructionalMaterial 201
Test of SignificanceAs s1,s2areunknown,theirestimateswouldbeused.
Astheproblemisofatwo-tailedtest,thecriticalvaluesofZat5percentlevelofsignificancearegivenby–Zα/2=–1.96andZα/2=1.96.ThesamplevalueofZ=–2.83liesintherejectionregionasshowninthefigurebelow:
Fig 12.2 Rejection regions for Example 12.2
Therefore,thenullhypothesisisrejectedanditmaybeconcludedthatthereisadifferenceintheaveragewagesofunskilledworkersinthetwocities.Letusreworkthesameproblemusingthepvalueapproach.Asitisknownthattheproblemisofatwo-tailedtest,thepvalueisgivenby:
p = P(Z<–2.83)+P(Z>2.83) = 2P(Z>2.83) = 2×(0.5–0.4977) = 2×0.0023 = 0.0046Asthevalueofpislessthanα(0.05),thenullhypothesisisrejected.
Similarly,theproblemsonone-tailedtestscanbesolved.
12.3.2 Hypothesis Testing for Comparing Two Related Terms: T-test
Themethodforcomparingtworelatedsamplesinhypothesistestingisthepairedt-test.Forthistest,itisnecessarythattheobservationsinthetwosamplesshouldbecollectedintheformofmatchedpairs.Itmeansthateachobservationinonesamplemustbepairedwithanobservationintheothersampleinsuchawaythattheyarematchedexcludingtheotherfactorswhichdonotfallwithintheareaofthistest.
Test of Significance
NOTES
Self-Instructional 202 Material
Animportantformulaforcalculatingthisis:
iDD=
n∑
Andtheformulaforcalculatingthevariancesofthedifferencesis:
(sdiff.)2 ( )22
i2diff.
D D ×n(ó ) =
n 1
−
−∑
Where,D =Meanofdifferences.Thet-testisbasedont-distribution,whichisaprobabilitydistribution
thatarisesintheproblemofestimatingthemeanofanormallydistributedpopulationwhen the sample size is small. t-distribution ariseswhen thepopulationstandarddeviationisunknownandhastobeestimatedfromthedata.
InStudent’st-distribution,therandomvariableisassumedasXwithmeanµandvariance 2s , xZ thestandardnormalstatisticisassumedas X
−
and 2X bearandomvariable,whichfollowschi-squaredistributionwitht degreesoffreedom.
If thevariablesarerelativelyindependentwitheachother, thenthet-distributionwillbe:
2
xZ
tXτ
−
=
Thestandardnormalstatisticofandchi-squarestatisticsare:
/x
XZns
−
−
=
and2
22
( 1)n SXs−= with(n–1)degreesoffreedom.
Aftersubstitutingthesetwostatisticsint,t-distributionisrepresentedas:
/XtS n
µ−= with(n–1)degreesoffreedom.
Thet-distributioncanbeusedonlywhenthesamplesizeisnotmorethan30;whenthesamplesizeismorethan30,thenitcanbeapproximatedtoanormaldistribution.
NOTES
Self-InstructionalMaterial 203
Test of Significance12.3.3 Hypothesis Testing of Proportions, Difference between Proportions and Comparing Variance
You can test proportions by using hypothesis testing.The formula forhypothesistestingofproportionsisasfollows:
Standarddeviationoftheproportionofsuccessesp×q= .
nIfnislarge,binomialdistributiontendstobecomenormaldistribution.
Forproportiontesting,youusestaticzasunder:
0
0 0
p pZp q
n
−=
(b) Hypothesis testing for differences between proportions
Iftwosamplesaredrawnfromdifferentpopulations,onemaybeinterestedinknowingwhetherthedifferencebetweentheproportionsissignificantornot.
Theformulafortestingthesignificanceofdifferenceisasunder:
1 2
1 1 2 2
1 2
p pz=p ×q p ×q+
n n
−
Where,p1=Proportionofsuccessinsampleone p2=Proportionofsuccessinsampletwoq1=1→ p1
q2=1→ p2
n1=Sizeofsmallonen2=Sizeofsampletwo
Hypothesis testing for comparing a variance: Chi-square test
This test is used to compare a sample variance to some theoretical orhypothesizedvarianceofpopulation. It isdifferent fromz-testand t-test.Thetestusedforthispurposeisknownaschi-squaretest.Itisusedtotestnullhypothesis.
Theformulaforthisisasfollows:2
2 s2p
σχ = (n 1)σ
−
orVarianceofthesample DegreeoffreedomVarianceofpopulation
×
Test of Significance
NOTES
Self-Instructional 204 Material
Wheren=numberofitemsinthesampleBycomparingthecalculatedvalueofchi-squaretestwithn–1degrees
offreedomatagivenlevelofsignificance,youcandeterminewhetherH0 isacceptedorrejected.
Thechi-squaretestisbasedontheconceptofchi-squaredistribution.Thistypeofdistributionisusedwhenyouaredealingwiththecollectionof values that include adding up squares.Chi-square distribution is notsymmetricalandallthevaluesarepositive.Youneedtoknowthedegreesoffreedomforusingthechi-squaredistribution.Thechi-squaretestisusedforjudgingthesignificanceofdifferencebetweenobserved(Oi)andexpected(Ei)frequencies.Thegeneralizedshapeofχ2distributiondependsonthedegreeoffreedomandtheχ2(chi)iswrittenas,
( )2ki i2
i=1 i
O Eχ =
E−∑
Thechi-squaretestthuscalculatestheprobabilitythatnosignificantdifferenceseemstoexistbetweentheexpectedfrequencyofanoccurrenceandtheobservedfrequencyofthesameoccurrence.Thechi-squaretestingcanbeclassifiedfurtherasfollows: •Chi-squaregoodness of fit test:Thistest isusedforperforminga
comparisonbetweenatheoreticaldistributionandtheobserveddatafromasample.Asthenameimplies,itteststhefitbetweenatheoreticalfrequencydistributionandafrequencydistributionofobserveddata.
•Chi-square test of association:The chi-square test of associationfacilitatescomparingtwoattributesinasampledata.Thecomparisonenablestheresearchertodeterminewhetherthereexistsanyrelationbetweenthetwoattributes.
•Chi-square test of homogeneity:Here, the test is concernedwithdeterminingwhether twopopulationshave the sameproportionofobservationswithacommoncharacteristic.Varianceofsamplesrequiresaddingacollectionofsquaredquantities
andthushavingdistributionthatisrelatedtochi-squaredistribution.TheChi-squaredistributionisamathematicaldistributionthatisuseddirectlyor indirectly inmany testsof significance.Themostcommonuseof thechi-squaredistributionistotestdifferencesamongproportions.Figure12.3showsthechi-squaredistribution.
NOTES
Self-InstructionalMaterial 205
Test of Significancedegreeoffreedom
5degreeoffreedomFrequency/probability
Chi-squarevariable
Fig. 12.3 Chi-square Distribution
Thevarianceofthechi-squaredistributionisrepresentedby:
212 ( )
1X X
Sn
−
−=
−∑
where
1X =observationofthesampleX−
=meanofthesamplen =sizeofthesampleThechi-squaredistributionisrepresentedas:
21 2
2 12 2
( )( 1)
n
iX X
n SXs s
−
=
−−= =
∑with(n–1)degreesoffreedom.
Intheformulaofchi-squaredistributionthevarianceofthedistributionisrepresentedass.Thisarandomsampleandfromthenormalpopulationthesizeistakenwiththevariancethatisknownaschi-square(χ2)distributionwith(n–1)degreesoffreedom.
12.3.4 Testing the Equality of Variances of Two Normal Populations: F-test
Totesttheequalityofvariancesoftwonormalpopulations,theF-testisused,whichisbasedonF-distribution.
Theformulaforthishypothesistestingisasfollows:
1
2
2s2s
σF=
σ
Test of Significance
NOTES
Self-Instructional 206 Material
Where,( )( )1
2
1i 12s
1
X Xσ =
n 1
−
−∑ and
( )( )2
2
2i 22s
2
X Xσ =
n 1
−
−∑
ThefollowingpresumptionsaremadewhileusingF-test:• Thepopulationsamplesarenormal.• Sampleshavebeendrawnrandomly.• Observationsareindependent.• Thereisnomeasurementerror.Totest thehypothesis,whether the twosamplesarefromthesame
normalpopulationwithequalvarianceorfromtwonormalpopulationswithequalvariances,theobjectsofF-testareused.Itisalsousedtoverifythehypothesisofequalitybetweentwovariances.But,thistestisnowmostlyusedintheanalysisofvariance.
The F-test depends on F distribution, which is an asymmetricdistributionthathasaminimumvalueof0,butnomaximumvalue.Thecurvereachesapeaknotfartotherightof0,andthenapproachesthehorizontalaxis.Figure12.4showstheFdistribution.
Freq
uenc
y/pr
obab
ility
F
Fig. 12.4 F Distribution
InFdistribution,(n1–1)and(n2–1)arethedegreesofthefreedomoftheFdistribution,whichisrepresentedas:
2 21 1
12 2
2 2 2
2
( 1) / - 1
( 1) / - 1
n SnF
n Sn
s
1− s
=−
with(n1–1)and(n2–1)arethedegreesoffreedom.
NOTES
Self-InstructionalMaterial 207
Test of SignificanceIf 1s = 2s ,thentheformulaofFdistributionwillberepresentedas:2
122
SF
S= with(n1–1)and(n2–1)arethedegreesofthefreedom.
Hypothesis testing of correlation coefficients
Toknowthesignificanceofcorrelationcoefficientbasedonsampledata,thefollowingformulaeareapplied:
•Forsimplecorrelationcoefficient: yx 2yx
n 2t = r1 r
−−
,nullhypothesisis
eitheracceptedorrejectedbasedonthevalueoft.
•Forpartial correlation coefficient: p 2p
(n k)t=r1 r
−−
, null hypothesis is
eitheracceptedorrejectedbasedonthevalueoft.
12.4 STATISTICAL TECHNIQUES OF HYPOTHESIS TESTING
Thestatisticaltechniquesofhypothesistestinginvolvesprovingastatementthat acts as an alternative for the hypothesis.There are several types ofstatisticaltechniquesemployedinhypothesistestingwhichcanbeexplainedwithsuitableexamples.
(a) Hypothesis testing of means
Therearedifferentsituationsunderhypothesistestingofmeans.Thetestingtechniqueisdifferentindifferentsituations,whichareasfollows: • Ifpopulation isnormal,population is infinite, samplesize thatcan
belargeorsmallandthevarianceofpopulationisknown,then,Hamaybeone-sidedortwo-sided.Insuchasituation,z-testisusedandformulaforthisisasfollows:
0H
p
X-μz=
σ / n
• Ifpopulationisnormal,populationisfinite,samplesizethatcanbelargeorsmallandthevarianceofpopulationisknown,then,Hamaybe one-sided or two-sided. Theformulaforthissituationisasfollows:
( )0H
p
X μz=
σ / n × (N n)/(N 1)
− − −
Test of Significance
NOTES
Self-Instructional 208 Material
· If population is normal, population is infinite, sample size is small and variance of the population is unknown, then, Ha may be one-sided or two-sided. The formula for this situation is as follows:
( )0H
p
X μz =
σ / n × (N n)/(N 1)
− − −
and · If population is normal, population is finite, sample size is small and
variance of the population is unknown, then, Ha may be one-sided or two-sided.The formula for this situation is as follows:
0H
s
X μt =
σ / n
− and
2i
s
(X X)σ =
(n 1)−
−∑
· If population is not normal but sample size is large, variance of the population is known or unknown, then, Ha may be one-sided or two-sided.The formula for this situation is as follows:
(b) Hypothesis testing for difference between means
There are situations where the significance of difference between the two means is examined. Such situations are stated along with their respective formulas: · Population variances are known or the samples happen to be large
samples. The formula used under this situation is as follows:
1 2
1 22 2p p
1 2
X Xz = σ σ
+ n n
−
In case sp1 and sp2 are not known, ss1 and ss2 are used in the same formula, which can be rewritten as:
( )1
2
1i 1s
1
X Xσ =
n 1
−
−∑
and ( )
2
2
2i 2s
2
X Xσ =
n 1
−
−∑
· Samples happen to be large but presumed to have been drawn from the same population whose variance is known.
NOTES
Self-InstructionalMaterial 209
Test of SignificanceThe formula used under this situation is as follows:
1 2
2p
1 2
X Xz = 1 1σ + n n
−
In case sp is not known, ss1.2 (combined standard deviation of both the samples) is used. The formula thus obtained after replacing it is as follows:
( ) ( )1 2
1,2
2 2 2 21 s 1 2 s 2
s1 2
n σ + D + n σ + Dσ =
n + n
Where D1= 1 1.2X X− and D2 = 2 1.2X X−
and 1 21 2
1,21 2
n X + n XX = n + n
· Samples happen to be small and population variances are not known but assumed to be equal.The formula for this situation is as under:
12.5 CHI-SQUARE TEST AND CONTINGENCY TABLE
From the observation (of data), different statistics are constructed to estimate the population parameters. In general (but not always) the sampling distribution of these statistics depends on the parameters and form of the parent population. The difference between distributions have been previously studied through constants like mean, standard deviation, etc., which are the estimates of the parameters, but generally these do not give all the features of these distributions. This caused the necessity to have some index which can measure the degrees of difference between the actual frequencies of the various groups and can thus compare all necessary features of them. An index of this type is “Karl Pearson’s χ2 (chi-square)” which is used to measure the deviations of observed frequencies in an experiment from the expected
Test of Significance
NOTES
Self-Instructional 210 Material
frequenciesobtainedfromsomehypotheticaluniverse.Here,wearegoingtostudyadistributioncalledχ2-distributionwhichenablesustocompareawholesetofsamplevalueswithacorrespondingsetofhypotheticalvalues.
χ2 distributionwas discovered in 1875byHelmert andwas againdiscoveredindependentlyin1900byKarlPearsonwhoapplieditasatestofgoodnessoffit.
Definition of χ2 (Or Chi-square)
Iffoandfedenotetheobservedandcorrespondingexpectedfrequenciesofaclassinterval(orcell),thenchi-squareisdefinedbytherelation:
χ2=Σf f
fo e
e
−RS|T|
UV|W|
b g2
wherethesummationextendstothewholesetofclass-intervals.Anotherformofχ2isobtainedasfollows:
χ2 = Σf f
fo e
e
−RS|T|
UV|W|
b g2 = Σf f f f
fo e o e
e
2 2 2+ −RS|T|
UV|W|
.
=Σ
ff
f fo
ee o
22+ −
RS|T|
UV|W|
=
22o
e oe
f f ff
Σ + Σ − Σ
=Σ
ff
N No
e
22
FHG
IKJ + −
(∴∑ fe = ∑ fo = N,thetotalfrequency)
χ2210= Σff
No
e
2FHG
IKJ −
Note: Itcanbeprovedthatifx1,x2,···,xn be in nindependentnormalvariateseachhavingzeromeanandunitvariance,thenthesumofthesquaresofthesenvariatesi.e., ( )2 2 2
1 2 ... nx x x+ + + isastatisticcalledχ2 with‘n’degreesoffreedomorastochastic
variatehavingχ2 distributionwith‘n’degreesoffreedom(Theno.ofindependentvariatesiscalledtheno.ofdegreesoffreedom).
Degrees of Freedom and Constraints
Lettheindividualsofasamplebegroupedinto‘n’classesorcellsbutinsteadof thesebeing independent, let thosebesubject to ‘v’ independent linearconstraints,thentheno.ofdegreesoffreedomnisdefinedbytherelationv=(n–c).
i.e.,degrees
of freedom =
no. of no. of l ineargroups const raints
−
NOTES
Self-InstructionalMaterial 211
Test of SignificanceNote:Eachindependentlinearconstraintreducestheno.ofdegreesoffreedombyone.
The Chi-square Distribution
For large sample size, the sampling (probability) distribution ofχ2 canbecloselyapproximatedbyacontinuouscurveknownas thechi-square distribution.
Theprobabilityfunctionofχ2distributionisgivenby
F(χ2) = c eχν χ2 1 2
22
e j( )−
⋅
where e= + + +1 11 ...1! 2!
ad inf
=2.71828 υ=no.ofdegreesoffreedom c=aconstantdependingonlyonυ.Thechi-squaredistributionhasonlyoneparameterυ,theno.ofdegrees
offreedom.Thisissimilartothecaseofthet-distribution. Hence f(χ2)isafamilyofdistributions,oneforeachvalueofυ.
Important Properties of the Distribution
df=1
df=5 df=10
2 4 6 8 10 12 14
F(χ2)
X2O
(i)χ2distributionisacontinuousprobabilitydistributionwhichhasthevalue zero at its lower limit and extends to infinity in the positivedirection.Negativevalueofχ2isnotpossible(sincethedifferencesbetweentheobservedandexpectedfrequenciesarealwayssquared).
(ii)Theexactshapeofdistributiondependsupontheno.ofdegreesoffreedomυ.Fordifferentvaluesofυ,weshallhavedifferentshapesofdistribution. Ingeneral,whenυ is small, theshapeof thecurveisskewedtotherightandasυgetslarger,thedistributionbecomesmoreandmoresymmetricalandcanbeapproximatedbythenormaldistribution.
(iii)Themeanoftheχ2distributionisgivenbythedegreesoffreedomi.e.,E(χ2)=υandvarianceistwicethedegreesoffreedom,i.e.,V(χ2)=2υ.
(iv)Asυgetslarger,χ2approachesthenormaldistributionwithmeanυ andstandarddeviation 2v .Inpractice,ithasbeendeterminedthatthequantity 22χ providesabetterapproximationtonormalitythan
Test of Significance
NOTES
Self-Instructional 212 Material
χ2itselfforvaluesof30ormore.Thedistributionof 22χ hasameanequalto (2 1)v − andastandarddeviationequalto1.
(v)Thesumof independentχ2variates isalsoaχ2variate.Therefore,if
21χ isaχ2variatewithυ1degreesoffreedomand
22χ isanotherχ2
variatewithυ2degreesoffreedom,thentheirsum( )2 2
1 2χ + χ isalsoaχ2variatewith(υ1+υ2)degreesoffreedom.Thispropertyisknownastheadditivepropertyofχ2.
Contingency Table
LetthegivendatabeclassifiedintopclassesA1,A2,···,ApaccordingtoattributexandintoqclassesB1,B2,··,Bqaccordingtoattributey.LetfijdevotetheobservedfrequencyofthecellbelongingtoboththeclassesAi(i=1,2,···,p) andBj (j=1,2,···,q).
LetthetotalofallthefrequenciesbelongingtotheclassAi be denoted by(Ai)andsimilarlylet(Bj)denotethetotalofallthefrequenciesbelongingtotheclassBj. Thenthe givendatacanbesetintoatableofrrowsands columnsinthefollowingmanner:
Classes B1 B2 ··· Bj ··· Bq –1 Bq Totals A1 f11 f12 ··· f1j ··· f1,q–1 f1q (A1) A2 f21 f22 ··· f2j ··· f2,q–1 f2q (A2) ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· Ai fi1 fi2 ··· fij ··· fi,q–1 fiq (Ai) ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· ··· Ap–1 fp–1,1 fp–1,2 ··· fp–1,j ··· fp–1,q–1 fP–1,q (AP–1) Ap fp1 fp2 ··· fpj ··· fp,q–1 fPq (AP)
Totals (B1) (B2) ··· (Bj) ··· (Bq–1) (Bq) N.
Calculation of υ for Contingency Table
Thetheoreticalfrequenciesinacontingencytablearecalculatedbyimposingthelimitationsthattherowtotals,columntotalsandthegrandtotalremainconstant(i.e.,unchanged).Therefore,iftherebeprowsandqcolumns,theneachofprowtotalsandqcolumn–totalsgivesrisetooneconstraintandsowehave(p + q)constraints.But,thesumoftheborderrowsandthesumofthebordercolumnsmusteachbeequaltothegrandtotalandsooneconstraintisdiminishedandsothereareonly(p + q – 1)constraints.
NOTES
Self-InstructionalMaterial 213
Test of SignificanceSo,theno.ofdegreesoffreedomisgivenasfollows: υ=(n – c) = [pq – (p + q –1)]=[pq – p – q +1] =[p (q – 1)–(q –1)]=(p – 1)(q –1)
Check Your Progress
3.Whatisaparametrictest? 4.Whatischi-squaredistribution?
12.6 ANSWERS TO CHECK YOUR PROGRESS QUESTIONS
1.Hypothesistestingcanbebroadlydividedintotwotypes,whichareasfollows:• Parametrictestsorstandardtestsofhypothesis• Non-parametrictestsordistribution-freetestsofhypothesis
2.Fisher–Irwintestisappliedwherethereisnodifferencebetweentwosetsofdata.
3.Aparametricstatisticaltestisonethatmakesassumptionsabouttheparameters(definingproperties)ofthepopulationdistribution(s)fromwhichone’sdataaredrawn.
4.Forlargesamplesize,thesampling(probability)distributionofχ2canbecloselyapproximatedbyacontinuouscurveknownasthechi-squaredistribution.
12.7 SUMMARY
•Thefirststepofthetestingprocedureis toestablishthehypothesistobetested.Asitisknown,thesestatisticalhypothesesaregenerallyassumptionsaboutthevalueofthepopulationparameter;thehypothesisspecifiesasinglevalueorarangeofvaluesfortwodifferenthypothesesratherthanconstructingasinglehypothesis.
•Thetwohypothesesaregenerallyreferredtoasthe(1)nullhypothesesdenoted by H0and(2)alternativehypothesisdenotedbyH1.
•Thehypothesismayberejectedoraccepteddependinguponwhetherthevalueoftheteststatisticfalls intherejectionortheacceptanceregion.
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•Hypothesistestingcanbebroadlydividedintotwotypes,whichareasfollows:o Parametrictestsorstandardtestsofhypothesiso Non-parametrictestsordistribution-freetestsofhypothesis
• Parametrictestsassumecertainpropertiesofthepopulationsamplesuch as observations froma normal population, large sample size,populationparameterslikemeanandvariance.
•McNamaratestisappliedwherethedataisnominalinnatureandisrelatedtotwointerrelatedsamples.
•Themethodforcomparingtworelatedsamplesinhypothesistestingisthepairedt-test.
•The statistical techniques of hypothesis testing involves proving astatementthatactsasanalternativeforthehypothesis.
• Fromtheobservation(ofdata),differentstatisticsareconstructedtoestimate thepopulationparameters.Ingeneral(butnotalways) thesamplingdistributionofthesestatisticsdependsontheparametersandformoftheparentpopulation.
•Thetheoreticalfrequenciesinacontingencytablearecalculatedbyimposingthelimitationsthattherowtotals,columntotalsandthegrandtotalremainconstant(i.e.,unchanged).
12.8 KEY WORDS
• T-Test:ItisanystatisticalhypothesistestinwhichtheteststatisticfollowsaStudent’st-distributionunderthenullhypothesis.
• Z-Test:Itisanystatisticaltestforwhichthedistributionoftheteststatisticunderthenullhypothesiscanbeapproximatedbyanormaldistribution
• Chi-Test: It is any statistical hypothesis testwhere the samplingdistributionoftheteststatisticisachi-squareddistributionwhenthenullhypothesisistrue.
12.9 SELF ASSESSMENT QUESTIONS AND EXERCISES
Short Answer Questions
1. Whatarenon-parametrictests? 2.Whatisthef-test?
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Test of Significance 3.Howischi-squaretestingclassified? 4.Listtheimportantpropertiesofchi-squaredistribution.
Long Answer Questions
1. Describethevariousstepsofthetestingprocedure. 2. Illustratehowtotestthedifferencebetweentwopopulationmeans. 3.Examinethehypothesistestforcomparingtworelatedterms. 4.Describethechi-squaretest.
12.10 FURTHER READINGS
Creswell,JohnW.2002.Research Design: Qualitative, Quantitative, and Mixed Methods Approaches.London:SagePublicationsInc.
Booth,Wayne,GregoryG.ColombandJosephM.Williams.1995.The Craft of Research.Chicago:UniversityofChicagoPress.
Bryman,AlanandEmmaBell.2015.Business Research Methods.4thEdition.UnitedKingdom:OxfordUniversityPress.
Gupta,S.L.andHiteshGupta. 2012. Business Research Methods. NewDelhi: TataMcGrawHillEducationPrivateLimited.
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UNIT 13 OVERVIEW OF NON-PARAMETRIC TESTS
Structure 13.0 Introduction 13.1 Objectives 13.2 Non-ParametricTest:ConceptandTypes
13.2.1 Mann-WhitneyTest 13.2.2 KruskalWallis 13.2.3 SignTest
13.3 MultivariateAnalysis 13.3.1 FactorAnalysis 13.3.2 Cluster 13.3.3 MultidimensionalScaling(MDS) 13.3.4 DiscriminantAnalysis
13.4 TheProcessofInterpretationofTestResults 13.4.1 GuidelinesforMakingValidInterpretation
13.5 AnswerstoCheckYourProgressQuestions 13.6 Summary 13.7 Key Words 13.8 SelfAssessmentQuestionsandExercises 13.9 FurtherReadings
13.0 INTRODUCTION
Inthepreviousunit,youprimarilylearntaboutthedifferentparametrictests.Inthisunit,wewilldiscussnon-parametrictests.Aswehavelearnt,non-parametric testsare sometimescalleddistribution-free testsbecause theyarebasedonfewerassumptions(e.g.,theydonotassumethattheoutcomeisapproximatelynormallydistributed).Thecostof fewerassumptions isthatnonparametrictestsaregenerallylesspowerful thantheirparametriccounterparts(i.e.,whenthealternativeistrue,theymaybelesslikelytorejectH0).Wewilldiscussthedifferenttypesofnon-parametrictestsinthisunit.
13.1 OBJECTIVES
Aftergoingthroughthisunit,youwillbeableto: •Discussthedifferenttypesofnon-parametrictests •Examinemultivariateanalysis •Describetheprocessofinterpretingtestsresults
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Overview of Non-Parametric Tests13.2 NON-PARAMETRIC TEST: CONCEPT AND
TYPES
Asyouhavelearnt,therearesituationswhereassumptionscannotbemade.Insuchsituations,differentstatisticalmethodsareused,whichareknownasnon-parametrictests.Thus,wecansaythatanon-parametrictestisatestthatdoesnotassumeanythingabouttheunderlyingdistribution.Itissometimescalledadistributionfreetest.Therearevarioustypesofnon-parametrictests.Theseinclude: •Signtest:Theyincludeone-samplesigntestandtwo-samplesigntest. •Fisher–Irwintest •McNamaratest •Wilcoxonmatched-pairstest
13.2.1 Mann-Whitney Test
ThistestwasdevelopedbyHBMannandRWhitneyinthe1940s.Thetestisusedtoexaminewhethertwosampleshavebeendrawnfrompopulationswithsamelocations(mean).Theapplicationofattestinvolvestheassumptionthat the samples aredrawn from thenormalpopulation. If thenormalityassumptionisviolated,thistestcanbeusedasanalternativetoattest.Thisisaverypowerfulnon-parametrictestasthiscanbeusedbothforqualitativeandquantitativedata.AtwotailedhypothesisforaMann-Whitneytestcouldbewrittenas:
H0: Twosamplescomefromidenticalpopulations or Twopopulationshaveidenticalprobabilitydistribution. H1: Twosamplescomefromdifferentpopulations orTwopopulationsdifferinlocations.TheprocedureinvolvedintheuseofMann-WhitneyUtest isvery
simpleandisdescribedinthefollowingsteps: (i)The twosamplesarecombined(pooled) intoone largesampleand
thenwedeterminetherankofeachobservationinthepooledsample.Iftwoormoresamplevaluesinthepooledsamplesareidentical,i.e.,ifthereareties,thesamplevaluesareeachassignedarankequaltothemeanoftheranksthatwouldotherwisebeassigned.
(ii)Wedetermine the sumof the ranksof each sample.LetR1 andR2 representthesumoftheranksofthefirstandthesecondsamplewhereasn1andn2aretherespectivesamplesizesofthefirstandthesecond
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sample.Forconvenience,choosen1asasmallsizeiftheyareunequalsothatn1 ≤ n2.AsignificantdifferencebetweenR1andR2impliesasignificantdifferencebetweenthesamples.
(iii)DefineU1=n1 n2+1 1n (n +1)
2–R1
and U2=n1 n2+2 2n (n +1)
2–R2
Pleasenotethatthefollowingexpressionwillholdtrue:U1=U2=n1n2
Mann-Whitney test for a large sample:Ifn1 or n2isgreaterthan10,alargesampleapproximationcanbeusedforthedistributionoftheMann-WhitneyUstatistic.Forthispurpose,eitherofU1 or U2couldbeusedfortestingaone-tailedoratwo-tailedtest.Inthistest,U2willbeusedforthepurpose.
Undertheassumptionthatthenullhypothesisistrue,theU2statisticfollowsanapproximatelynormaldistributionwithmean:
2
1 2n n2uµ =
( )2
1 2 1 2n n n +n 112u
+s =
Theteststatisticis:
2
2
2U –Z= u
u
µs
Assumingthelevelofsignificanceasequaltoa,iftheabsolutesamplevalueofZisgreaterthantheabsolutecriticalvalueofZ,i.e.,Za/2,thenullhypothesisisrejected.Asimilarprocedureisusedforaonetailedtest.ForaonesideduppertailtestifthesamplevalueofZisgreaterthanthecriticalZa,thenullhypothesisisrejected.Foraone-sidedlowertailtest,thenullhypothesisisrejectedifthesampleZislessthan–Za.
13.2.2 Kruskal Wallis
OneoftheassumptionsusedintheANOVAtechniqueisthatalltheinvolvedpopulationsfromwherethesamplesaretakenarenormallydistributed.Ifthisassumptiondoesnotholdtrue,theF-statisticusedinANOVAbecomesinvalid.Thenormalityassumptionsmaynotholdtruewhenwearedealingwithordinaldataorwhenthesizeofthesampleisverysmall.
TheKruskal-Wallistestcomestoourrescueduringsuchsituations.Thisis,infact,anon-parametriccounterparttotheone-wayANOVA.Thetest is an extension of theMann-WhitneyU test discussed earlier.Bothmethodsrequirethatthescaleofthemeasurementofasamplevalueshouldbeatleastordinal.
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Thehypothesistobetestedin-Kruskal-Wallistestis: H0: Thekpopulationshaveidenticalprobabilitydistribution. H1: Atleasttwoofthepopulationsdifferinlocations.
Theprocedureforthetestislistedbelow: (i)Obtainrandomsamplesofsizen1,...,nkfromeachofthekpopulations.
Therefore,thetotalsamplesizeisn=n1+n2+...+nk (ii)Poolallthesamplesandrankthem,withthelowestscorereceivinga
rankof1.Tiesaretobetreatedintheusualfashionbyassigninganaverageranktothetiedpositions.
(iii)Letri=thetotaloftheranksfromtheithsample.
TheKruskal-Wallistestusestheχ2totestthenullhypothesis.Theteststatisticisgivenby:
whichfollowsaχ2distributionwiththek–1degreesoffreedom.where, k=Numberofsamples n=Totalnumberofelementsinksamples. Thenullhypothesisisrejected,ifthecomputedχ2isgreaterthanthe
criticalvalueofχ2atthelevelofsignificancea.
13.2.3 Sign Test
TheMann-WhitneyUtestjustdiscussedassumesthatthetwosamplesareindependent.However,thereareinstanceswhenthenormalityassumptionisnotsatisfiedandonehastoresorttoanon-parametrictest.Onesuchtestearlierdiscussedwasthetwo-samplesigntest.Inthistest,onlythesignofthedifference(positiveornegative)wastakenintoaccountandnoweightagewasassignedtothemagnitudeofthedifference.TheWilcoxonmatched-pairsignedranktesttakescareofthislimitationandattachesagreaterweightagetothematchedpairwithalargerdifference.Thetest,therefore,incorporatesandmakesuseofmoreinformationthanthesigntest.Thisis,therefore,amorepowerfultestthanthesigntest.Thetestprocedureisoutlinedinthefollowingsteps: (i)Letdidenotethedifferenceinthescorefortheithmatchedpair.Retain
signs,butdiscardanypairforwhichd=0. (ii) Ignoringthesignsofdifference,rankallthedi’sfromthelowestto
highest.Incasethedifferenceshavethesamenumericalvalues,assigntothemthemeanoftheranksinvolvedinthetie.
(iii)Toeachrank,prefixthesignofthedifference.
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(iv)ComputethesumoftheabsolutevalueofthenegativeandthepositiverankstobedenotedasT–andT+respectively.
(v)LetTbethesmallerofthetwosumsfoundinstepiv.Whenthenumberofthepairsofobservation(n)forwhichthedifference
isnotzeroisgreaterthan15,theTstatisticfollowsanapproximatenormaldistributionunder thenullhypothesis, that thepopulationdifferencesarecentredat0.ThemeanµTandstandarddeviationsTofTaregivenby:
Theteststatisticisgivenby:
Foragivenlevelofsignificancea,theabsolutesampleZshouldbegreaterthantheabsoluteZa/2torejectthenullhypothesis.Foraone-sideduppertailtest,thenullhypothesisisrejectedifthesampleZisgreaterthanZaandforaone-sidedlowertailtest,thenullhypothesisisrejectedifsampleZislessthan–Za.
13.3 MULTIVARIATE ANALYSIS
Letusnowdiscussmultivariateanalysis.
13.3.1 Factor Analysis
Factoranalysis isamultivariatestatistical techniqueinwhichthereisnodistinctionbetweendependentandindependentvariables.Infactoranalysis,allvariablesunderinvestigationareanalysedtogethertoextracttheunderlinedfactors.Factoranalysisisadatareductionmethod.Itisaveryusefulmethodtoreducealargenumberofvariablesresultingindatacomplexitytoafewmanageablefactors.Thesefactorsexplainmostpartofthevariationsoftheoriginalsetofdata.Amarketresearchermighthavecollecteddataonsay,more than50attributes (or items)of aproductwhichmaybecomeverydifficulttoanalyse.Factoranalysiscouldhelptoreducethedataon50oddattributestoafewmanageablefactors.Ithelpsinidentifyingtheunderlyingstructureofthedata.
A factor isalinearcombinationofvariables.Itisaconstructthatisnotdirectlyobservablebutthatneedstobeinferredfromtheinputvariables.Thefactorsarestatisticallyindependent.Wewillshowyoutheirapplicationina
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regressionanalysisasthefactorscores,whenusedasindependentvariablesinregressionanalysis,helptosolvetheproblemofmulticollinearity.(Theproblemofmulticollinearityinaregressionmodelariseswhentheindependentvariablesaresohighlycorrelatedthatitbecomesdifficulttoseparateouttheinfluenceofeachoftheindependentvariablesonthedependentvariable.)Thefactorscorescouldalsobeusedinothermultivariatetechniques.
Uses of Factor Analysis
The technique of factor analysis hasmultiple uses as discussed in thefollowingsituations:Scale construction: Factoranalysiscouldbeusedtodevelopconcisemultipleitemscalesformeasuringvariousconstructs.WehavealreadydiscussedinthechapterAttitudeMeasurementandScaling theprocessofdevelopingamultiple item scale that typically starts generating a large set of items(statements)relatingtotheattitudebeingmeasured.Thisisdoneaspartofexploratoryresearch.Factoranalysiscanreducethesetofstatementstoaconciseinstrumentandatthesametime,ensurethattheretainedstatementsadequatelyrepresentthecriticalaspectsoftheconstructsbeingmeasured.Supposewewant toprepareamultiple itemscale formeasuring the jobsatisfactionofskilledworkersinanorganization.Asthefirststep,wewouldgeneratealargenumberofstatements,numberingsay100orsoaspartofexploratoryresearch.Thesestatementscouldbesubjectedtofactoranalysisand letusassumethatweget threefactorsoutof it.Now, ifwewant toconstructa15-itemscaletomeasurejobsatisfaction,whatcouldbedoneistoseparatefiveitemsineachofthefactorshavingthehighestfactorloading.Theconceptoffactorloadingwillbediscussedlaterinthebook.Thisway,a15-itemscaletomeasurejobsatisfactioncouldbedeveloped.Establish antecedents: Thismethodreducesmultipleinputvariablesintogroupedfactors.Thus,theindependentvariablescanbegroupedintobroadfactors.For example, all thevariables thatmeasure the safety clauses inamutualfundcouldbereducedtoafactorcalledsafetyclause.Thus,thecompanycouldknowaboutthebroadbenefitthataninvestorseeksinafund.Psychographic profiling: Differentindependentvariablesaregroupedtomeasureindependentfactors.Thesearethenusedforidentifyingpersonalitytypes.Oneofthemostwell-knowninventoriesbasedonthistechniqueiscalledthe16PFinventory.Segmentation analysis: Factoranalysiscouldalsobeusedforsegmentation.Forexample,therecouldbedifferentsetsoftwo-wheelers-customersowningtwowheelersbecauseofdifferentimportancetheygivetofactorslikeprestige,economyconsiderationandfunctionalfeatures.Marketing studies: Thetechniquehasextensiveuseinthefieldofmarketingand can be successfully used for new product development; product
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acceptanceresearch,developingofadvertisingcopy,pricingstudiesandforbrandingstudies.Forexamplewecanuseitto: • identifytheattributesofbrandsthatinfluenceconsumers’choice; • getaninsightintothemediahabitsofvariousconsumers; • identifythecharacteristicsofprice-sensitivecustomers.
Conditions for a Factor Analysis Exercise
Factoranalysisrequiressomespecificconditionsthatmustbeensuredbeforeexecutingthetechnique.Thesearementionedindetailinthissection. • Factor analysis exercise requiresmetric data.Thismeans the data
shouldbeeitherintervalorratioscaleinnature.Thevariablesforfactoranalysis are identified through exploratory researchwhichmaybeconductedbyreviewingtheliteratureonthesubject,researchescarriedout already in this area, by informal interviews of knowledgeablepersons,qualitativeanalysis likefocusgroupdiscussionsheldwithasmallsampleoftherespondentpopulation,analysisofcasestudiesandjudgementoftheresearcher.Generallyinasurveyresearch,afiveorseven-pointLikertscaleoranyotherintervalscalesmaybeused.
•Astheresponsestodifferentstatementsareobtainedthroughdifferentscales,alltheresponsesneedtobestandardized.Thestandardizationhelps in comparison of different responses from such scales.Thestandardizationiscarriedoutusingthefollowingformulae:
Standardizedscoreofithrespondentonastatement=
•Thesizeofthesamplerespondentsshouldbeatleastfourtofivetimesmorethanthenumberofvariables(numberofstatements).
•Thebasicprinciplebehindtheapplicationoffactoranalysisisthattheinitialsetofvariablesshouldbehighlycorrelated.Ifthecorrelationcoefficientsbetweenallthevariablesaresmall,factoranalysismaynotbeanappropriatetechnique.Acorrelationmatrixofthevariablescouldbecomputedandtestedforitsstatisticalsignificance.Thehypothesistobetestedmaybewrittenas: H0 : Correlationmatrix is insignificant, i.e., correlationmatrix is
an identitymatrixwhere diagonal elements are one andoffdiagonalelementsarezero.
H1 : Correlationmatrixissignificant. ThetestiscarriedoutbyusingaBartletttestofsphericity,whichtakes
thedeterminantofthecorrelationmatrixintoconsideration.Thetestconvertsitintoachi-squarestatisticswithdegreesoffreedomequal
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to [(k(k-1))/2],wherek is thenumberofvariablesonwhichfactoranalysisisapplied.Thesignificanceofthecorrelationmatrixensuresthatafactoranalysisexercisecouldbecarriedout.
•Anotherconditionwhichneedstobefulfilledbeforeafactoranalysiscould be carried out is the value ofKaiser-Meyer-Olkin (KMO)statisticswhichtakesavaluebetween0and1.Fortheapplicationoffactoranalysis,thevalueofKMOstatisticsshouldbegreaterthan0.5.TheKMOstatisticscomparesthemagnitudeofobservedcorrelationcoefficientswiththemagnitudesofpartialcorrelationcoefficients.AsmallvalueofKMOshowsthatcorrelationbetweenvariablescannotbeexplainedbyothervariables.
Steps in a Factor Analysis Exercise
Therearebasicallytwostepsthatarerequiredinafactoranalysisexercise. 1. Extraction of factors: Thefirstandtheforemoststepistodecideon
howmanyfactorsaretobeextractedfromthegivensetofdata.Thiscouldbeaccomplishedbyvariousmethodslikethecentroidmethod,theprincipalcomponentmethodandthemaximumlikelihoodmethod.Here,only theprincipal componentmethodwillbediscussedverybriefly.Asweknowthatfactorsarelinearcombinationsofthevariableswhicharesupposedtobehighlycorrelated,themathematicalformofthesamecouldbewrittenas:
Fi=Wi1X1*+Wi2X2*+Wi3X3*+...+WikXk*where, Xi*= i
thstandardizedvariable Fi = Estimateofithfactor Wi = Weightorfactorscorecoefficientforithstandardized
variable. k = Numberofvariables
Theprincipalcomponentmethodologyinvolvessearchingforthosevalues ofWi so that thefirst factor explains the largest portion oftotalvariance.Thisiscalledthefirstprincipalfactor.Thisexplainedvariance is then subtracted from the original inputmatrix so as toyieldaresidualmatrix.Asecondprincipalfactorisextractedfromtheresidualmatrixinawaysuchthatthesecondfactortakescareofmostoftheresidualvariance.Onepointthathastobekeptinmindisthatthesecondprincipalfactorhastobestatisticallyindependentofthefirstprincipalfactor.Thesameprincipleisthenrepeateduntilthereislittlevariancetobeexplained.Theorymaybeusedtospecifyhowmanyfactorsshouldbeextractedoritmaybebasedonthecriterion
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oftheKaiserGuttmanmethod.Thismethodstatesthatthenumberoffactorstobeextractedshouldbeequaltothenumberoffactorshavinganeigenvalueofatleast1.Sinceeachofthevariablesintheoriginaldatasethasavarianceof1(eigenvalueof1),therefore,ifthereare50variablesthenthetotalvariationinthedatasetwillbe50.
Weknowthatafactorisalinearcombinationofthevariousvariables.Noweigenvalue foreachof the factor iscomputedandonly thosefactorsthathaveaneigenvalueatleast1areacceptedasperKaiserGuttmanmethod.Allthosefactorshavingeigenvalueslessthan1arerejected.Thisisbecauseeachofthevariableshasavarianceof1and,therefore,alinearcombinationofthesevariablescalledfactorshouldnothaveaneigenvaluelessthan1.
Another output of the factor analysis exercise is a factor score,which is computed for each of the factors corresponding to eachrespondent.Mostsoftware,includingSPSS,providefactorscoreforeachrespondentandeachfactor.Asthefactorscoresarestatisticallyindependent,theycanbeusedinregressionanddiscriminantanalysisasindependentvariables.Thiswillbeexplainedbrieflyinthetextlateron.
Thecorrelationcoefficientoftheextractedfactorscorewithavariableiscalledthefactor loading.Inmostcomputerprintouts,amatrixoffactorloadingscalledfactormatrixorcomponentmatrixispresented.Factor loadings play a very important role in the computations ofeigenvaluesofeachfactorandalsoincomputingthecommunalitiesofeachvariable.Theseconceptswouldbediscussedindepthwiththehelpofanumericalexercise.
2. Rotation of factors: Thesecondstepinthefactoranalysisexerciseistherotationofinitialfactorsolutions.Thisisbecausetheinitialfactorsareverydifficulttointerpret.Therefore,theinitialsolutionisrotatedsoastoyieldasolutionthatcanbeinterpretedeasily.Mostofthecomputersoftwarewouldgiveoptionsfororthogonal rotation, varimax rotation and oblique rotation.Generally,thevarimaxrotationisusedasthisresultsinindependentfactors.Thevarimaxrotationmethodmaximizesthevarianceoftheloadingswithineachfactor.Thevarianceofthefactorislargestwhenitssmallestloadingtendstowardszeroanditslargestloadingtendstowardsunity.Thebasicideaofrotationistogetsomefactorsthathaveafewvariablesthatcorrelatehighwiththatfactorandsomethatcorrelatepoorlywiththatfactor.Similarly,thereareotherfactorsthatcorrelatehighwiththosevariableswithwhichtheother factorsdonothavesignificantcorrelation.Therefore, therotationiscarriedoutinsuchwaysothatthefactorloadingsasinthe
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firststepareclosetounityorzero.Thisprocedureavoidsproblemsofhavingfactorswithallvariableshavingmidrangecorrelations.Thisisdoneforabetterinterpretationoftheresultsandfortheeaseobtainedinnamingthefactors.Oncethisisdone,acut-offpointonthefactorloading is selected.There isnohardand fast rule todecideon thecut-offpoint.However,generallyitistakentobegreaterthan0.5.Allthosevariablesattachedtoafactor,oncethecut-offpointisdecided,areusedfornamingthefactors.Thisisaverysubjectiveprocedureanddifferentresearchersmaynamesamefactorsdifferently.Anotherpointtobenotedisthatavariablewhichappearsinonefactorshouldnotappearinanyotherfactor.Thismeansthatavariableshouldhaveahighloadingonlyononefactorandalowloadingonotherfactors.Ifthatisnotthecase,itimpliesthatthequestionhasnotbeenunderstoodproperlybytherespondentoritmaynothavebeenphrasedclearly.Anotherpossiblecausecouldbethattherespondentmayhavemorethanoneopinionaboutagivenitem(statement). Thetotalvarianceexplainedbyallthefactorstakentogetherremains
thesameafterrotation.However,theamountofvariationsforeachindividualfactormayundergoachange.Thecommunalitiesforeachvariableunderthetwoproceduresremainunchanged.
13.3.2 Cluster
Clusteranalysisisagroupingtechnique.Thebasicassumptionunderlyingthetechniqueisthefactthatsimilarityisbasedonmultiplevariables,andthe technique attempts tomeasure the proximity in terms of the studyvariables.Theemerginggroupsarehomogenousintheircompositionandheterogeneousascomparedtotheothergroups.Thegroupingcanbedoneforobjects, individuals, entities andproducts.The researcher identifiesasetofclusteringvariableswhichhavebeenassumedassignificantforthepurposeofclassifyingtheobjects intogroups.Thus, it isalsoreferredtoasaclassificationtechnique,numericaltaxonomyandQanalysis.Thisisbasicallybecausethetechniqueisusedinvariousbranchesofsocialscience,likepsychology,sociology,engineeringandmanagement.Ifoneweretoplotthegroupsgeometrically,arobustclusteranalysisisonewhereindividualobjects inoneclusterareconcentrated togetherandwhere the individualclustersarefarapartfromeachother.Figure13.1(a)showsasimpleclustersolutionofbreakfastfoodbasedonpeoplewhoseeknutritionandconvenience(easeofpreparation).
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Fig 13.1(a) Ideal Cluster Solution
Fig 13.1(b) Actual Cluster Solution
However,theactualsituationmightbedifferentasthepersonmightbeusingdifferentcriteriaforaweekdayandforaweekendbreakfast.Thus,asthecriteriafordecision-makingbecomemultiple,thegroupingdoesnothappenonasimpletwo-dimensionalspacebutbecomesmultidimensional[Figure13.1(b)].Thus,theresearcherisabletogrouppeopleonthesethreedimensions and the point regarding the interpretation of benefits soughtbecomesclearasoneunderstandsthemultidimensionalityofneeds.Thus,abakery/confectioneryshopsellingsandwiches,patties,breadrollsaswellasfreshlygroundidlibatter,usingthesolutionwouldknow:(1)thelucrativesegment,(2)thesegmentwhichmightbemotivatedtobuyifonetakescareoftheirweekday/weekendneeds,and(3)Asegmentwhichiscurrentlynotinterestedingettinga‘ready-to-eat’breakfastsolutionandmightnotlookatthebakeryasanoutlettovisitinthemorning.Oncethehomogenousclusters
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emerge, thenextstepis todeterminetheprofileof thegroupin termsofwhotheyare?Whatistheirgender,agegroup,familysize,etc.?Whatdealsmotivatethemtobuyfromaparticularstorewhentheyarebuyingeatablesingeneral?
Differentiating Cluster Analysis
In terms of the nature of the technique vis-á-vis the othermultivariatetechniques,clusteranalysisissimilarintermsof analysingthefunctionofmultiple independent variables.However, there are essential differencesbetweentheotherdatareductiontechniquesandclusteranalysis.
Infactoranalysis,theobjectivewastoreducetheoriginalcorrelatedvariablestoamoremanageablenumberoforthogonalorobliquefactors.However, the data reductionwas carriedout on the columnsof the datamatrix.Ontheotherhand,inclusteranalysisthefocusisontherows,ortheindividualsorentitiesandtheobjectiveistogrouptheindividualsonthevariables.
Theotherdataclassificationtechniqueisthetwogroupdiscriminantanalyses.Here also, onemightwish to group individuals or objects intogroups,buttheclassificationoridentificationofgroupsisa priori.Thus,inthetechniqueonehasanestablishedclassificationruleandtheobjectiveofthetechniqueistovalidatetheinformationtoattestwhetherthegroupsobtainedbytheidentifiedfunctionarecorrectlyclassifiedornot.Inclusteranalysis,thewholepopulation/sampleisundifferentiatedandtheattemptstoassesssimilarityinresponsetovariablesandthegroupinghappenspost theclustering.
Usage of Cluster Analysis
Clusteranalysishaswidespreadapplicabilityinallthebranchesofsocialsciences andmanagement. Inmanagement science, itsmost valuablecontribution is in the areaofmarketing, especiallymarket segmentation.Someapplicationsofthetechniqueareasfollows: • Market segmentation: Aswe know,Market segmentation is the
processof splittingcustomers/potential customers,withinamarketintodifferentgroups/segments,wherecustomershavethesame/similarrequirement satisfied by a distinctmarketingmix (McDonald and Dunbar,1998).Thisisoneareathathasseenmaximumtheorizationon the basis of the outputs of the technique. Some examples areACORN (Aclassificationofresidentialneighbourhoodbasedon40variables,e.g.,house/carownership,employment,religion,lifestyle,etc.), PRIZM (Potentialratingindexbyzipmarket.Thisisbasedon39 variables (for example, education, affluence, family life cycle,urbanization,raceandethnicity,mobility,etc.).Thesolutionprovides62lifestylecategories.Theadvantagewiththetechniqueisthatonecan
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lookatthecombinationofvariablestopredictconsumerorpotentialconsumergroups.Thebestexampleofclusteredsolutionsareintheareaofbenefit segmentation (Haley,1968).Here,the consumersaredividedintogroupsbasedonthebenefitstheyseekfromtheproductcategory.These,then,couldbeacrossagegroups,genderandothervariables.Thus,amarketercoulddesignhisproductonthebasisofthissegmentationapproach.Yankelovich(1964)segmentedconsumersintermsof‘whattheylookforinawatch’andclassifiedpeopleintothosewhoareprice driven, durabilityand quality driven,andthosedriven by occasion-bound symbolism. Sinha (2003) classified foodshoppersintofun and work shoppers basedonthebenefitstheyseekfromgrocery/foodpurchase.Sondhi andSinghvi (2005) classifiedgroceryshoppersinto transition shoppers, traditional shoppers, thrifty shoppers andindifferent shoppers.
• Segmenting industries/sectors: Theresearchercouldalsogoaboutgroupingproductsor sectors (e.g.,healthoreducation) intoblocksthat have some common trait(s).Thismakes it easier for both theorganizations and policy-makerswhile planning or evaluating theperformanceofthegroup.
• Segmenting markets: Citiesorregionswithsomecommontraitslikepopulationmix,infrastructuredevelopment,climaticorsocio-economicconditionscouldbeclusteredtogether.IfonecityinKeralaandanotherinAndhraPradeshareinonecluster,thentheorganizationisabletoplanandexecuteasimilarbusinessapproachinthetwoareas.
• Career planning and training analysis: Inthe areaofhumanresources(HR)thetechniquecanbeusedtogrouppeopleintoclustersonthebasisoftheireducationalqualification,experience,aptitudeandaspirations.ThisgroupingcanassisttheHRdivisiontoeffectivelymanagetrainingandmanpower development for themembers of different clusterseffectively.
• Segmenting financial sectors/instruments:Thisisanemergingareawheredifferent factors likerawmaterialcost,financialallocations,seasonalityandotherfactorsarebeingusedtogroupsectorstogethertounderstandthegrowthandperformanceofagroupofindustries.Thisalsoassiststhepolicy-makersandthefinancialanalystsinassessingthemonetaryimplications.Anumberofresearchersaremakinguseof clustering principles to group consumers and their investmentbehaviouronthebasisofthecombinationofdifferentvariablesandbenefitssought(behaviouralfinance).Thebasicpremiseoftheabovetechniqueis,aswesaidearlier,wherever
aresearcherwantstomanagethedata(especiallyindividualororganizational)
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andhe/sheperceivesthattherecouldbemultiplefactorsinvolved,clusteranalysisisthebestclassificationtechniqueathis/herdisposal.
Statistics Associated With Cluster Analysis
Beforewereviewthestatisticsinvolvedwiththetechnique,itisessentialonceagaintoexaminethesimplicityofthetechnique.Unliketheothermultivariatetechniquesthatwehavediscussedtillnow,clusteranalysisisthesimplestintermsofmathematicalderivations.Thesimplestwaytoexplainthetechniqueistounderstandthatitsimplymeasuresthedistancebetweenobjectsonthebasisofmultiplevariablesandlooksforsimilarityasafunctionofdistance,i.e.,theshorterthedistancebetweentwoobjects,themoresimilartheyare.Metric data analysis: Forobtaining a clustersolutiontodatathatiscollectedonanintervalorratioscalethestatisticalassessmentofthedistancebetweentwoobjects can be done by calculating theEuclidean distance betweenthem.Incasethestudyhastwovariables(asstatedintheearlierexampleofnutritionandeaseofpreparation)thenthedistancebetweenpersonAandBcanbecalculated:
whereXB1representsthecoordinateofpersonBonnutrition(intervalscaledata).A note of caution here:TheEuclideandistanceisnot‘scaleinvariant’.Itmayhappenthattherelativeorderingoftheobjectsintermsoftheirsimilaritycanbeaffectedbyasimplechangeinthescalebywhichoneormoreofthevariablesaremeasured.Thus, it isadvisable that thedata isstandardizedbeforebeingsubjectedtoanyanalysis.However,itmaysometimeshappenthatstandardizationcanreducethedifferencesbetweenthegroupsonthevariables thatmaywell be the best discriminators of group differences.Thus,careneedstobetakeninitiallyinquestionnairedesigningtokeepthevariablesmeasurementscalesasroughlyofmoreorlessthanthesamerangeandavoidstandardizingthem.Onlyifthevariablesaremeasuredonwidelydifferentunits,standardizationisneededtopreventthevariablesmeasuredinlargerunitsfromdominatingtheclustersolution.
Intheexample,thetwovariableswereplacedona10-pointscaleofimportance(with1=veryimportantand10=veryunimportant).ThevaluesselectedbypersonAandBwereasfollows: Person Nutrition Ease of preparation A 1 2 B 5 2
Thenthedistancebetweenthetwois,
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SupposetherewasathirdpersonCwhohadselected Person Nutrition Easeofpreparation C 6 2
ThenthedistancebetweenAandCwouldbe5.0andbetweenBandC would be 1.0.
Thus,BandCarethemostsimilarpairastheinter-persondistanceistheleastand,asstatedearlier,theshorterthedistance,thegreaterthesimilarity.
If,inadditiontohavingnutritionandeaseofpreparationforbreakfast,we also had a variable thatmeasured cost,wewould effectively have a3-dimensionalsolution.Thentheformulawouldhavebeen:
Andgenerally,foranytwoobjects,iandj:
where,
dij=Distancebetweenpersoniandj k=Variable(interval/ratio) i=Object/person j=Object/personAlso,thereareotherdistancemeasuresavailablelikethecity-blockor
Manhattan distancebetweentwoobjects,whichisthesumoftheabsolutedifferencesinthevaluesforeachvariable.AnotherdistancemeasureistheChebychev distancebetweentwoobjects,whichisthemaximumabsolutedifferenceinvaluesforanyvariable.However, themostcommonlyusedmeasure is the squaredEuclidean distance.A point to be noted here isthat clusteringwith squaredEuclideandistance is faster than the regularEuclideandistance.Thus, for the purpose of clustering,wemakeuse ofsquaredEuclideandistance.TheequationforthisisthesameastheEuclideandistance;onlythesquarerootisnotcalculated.
Then,basedonthedistancecalculated,adistancematrixiscreatedandclustersarecreatedbymovingfromthemosttotheleastsimilarpairbasedonaclusteringmethod.
13.3.3 Multidimensional Scaling (MDS)
TheunderlyingpresumptionsthatonemakeswhilecreatinganMDSare: •Theindividualtriestogroupobjectstogether. •Thegroupedobjectsareusuallyevaluatedandcomparedwitheach
othersothattheycancoexistonaspatialmap.
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•Thebasisofevaluationisnotunidimensionalandtheuserisatalltimes(consciouslyorunconsciously)usinganunderlyingmultidimensionalspacetoevaluatetheobjects.MDS essentially visually plots the perceptions and preferences of
individualssinglyandasagroup,regardingagroupofobjects,individualsorboth;evenwhentheinformationaboutthedimensionsorbasesofevaluationsisminimal.
Thus, the technique uses powerfulmathematical tools in order tocondensethedatabycreatingvisualrepresentationsbasedonthesimilaritiesordissimilaritiesofdataonaspatialmap(Schiffman,et al.1981).Themapdimensionsarehypothesizedtobetheattributesorfeaturesthatthepersonusestoformcertainimpressionsabouttheobject.OneofthemostwidelyusedmathematicalmethodstocreatethemapsisbasedonKruskal’s(1964)stresscalculations(tobediscussedfurtherinthechapter).
MDS usually involves a comparison of sorts to create a relativepositionoftheconsideredobjects.Thecomparisoncouldbemadeondefined dimensions,ortheapparentbasisofcomparison.However,moreoftenthannot, peoplemakeuseof their ownpeculiar and sometimes subjectiveorperceived dimensionstomakethecomparison.Forexample,itcouldbethetrustorfaithintheserviceproviderinhandlingtheinsuredperson’sproblemseffectively.Thus,twoobjectsorbrandswiththesamedefineddimensionsmightbeperceivedverydifferentlybythepersonbecause: •The evaluationsmight not be solely basedondefinedor observed
parameters. •The subjective and the objective dimensionsmight be absolutely
unrelated.Tosimplifytheprocessfurther,thetechniquepresentsthedependent
variable (whichmightbea similarityordissimilaritybetween theobjector preferences) and then tries to figure outwhatwere the underlyingindependentsorantecedents that led to theobtainedmap.Theadvantageofthismethodis that theresearcher’s influencewherehe/sheattemptstoprovidethedimensionsofcomparisongetsminimized.Thedisadvantage,however,wouldbetoclearlyfigureoutthedimensiontherespondentsmighthaveusedforthecomparison.
Thus,theresearcherneedstobefairlywellversedwiththeprobableparameters that a personmight use for comparison.These perceivedparametersmight emerge fromaqualitative analysis of the respondents’decisionprocessorthroughtheresearcher’sreviewofthesecondaryliteratureabouttheproduct.Theinputsobtainedwouldhavetobeobjectively—withoutanyelementofpersonalbias—assessedtocomprehendthedefinedorapparentandthehiddenorsubjectivedimensionsbeingused.
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A simple explanation of the concept:Tounderstandtheconceptofmappingtherespondent’schoices,letuslookataverysimpleexampleofaconsumerwhobuysbreadeverydayforhisfamilybreakfast.Now,weaskhimwhichbreadhebuys.Hetellsus,‘HarvestGold,BritanniaandPerfect.’Next,weaskhim the similaritybetween twobreadbrands, say,HarvestGoldandBritannia,ona7-pointscale,where1isverysimilarand7isverydissimilar.Hesays,thesimilarityis1.Whatthismeansisthat: • Ifweweretotakeamentalmodelofhisbrainwhenhesaidthis,the
twobrandswouldbeveryclosetoeachother. • Supposewesaythattheconsumerwasthinkingofpriceandavailability
whenhewastellingusthis.Thus,theunconsciousevaluationthathedidwasonthetwodimensionsof‘price’and‘brand’.So,thesetwobrandaretwopointsclosetoeachotherinthistwo-dimensionalmap.
•Thetwomanufacturershavetounderstandthatthereisnobrandloyaltyfromthecustomer,ashecouldveryeasilybuythecompetingbrandastheyarealmostidenticaltoeachotherinhis‘mind’.Now,suppose,weaskhimifhehasconsumedHarvestGoldmulti-
grainbread,andhesays,‘yes’.SowenowaskhimtotellusthesimilaritybetweenHarvestGoldregularandHarvestGoldmulti-grainbreadonthesame7-pointscale.Hisansweris6.Now,whatwillhappenifweusethesamedimensionsasintheabovecase?Thebrandisthesameforboth,thususingatwo-dimensionalmapwouldnotbewiseastheconsumermaybenowlookingatthehealthbenefitornutritionalcontentinthebreadsalsoasadimension.Thusthismeans: •The bread brands nowneed a three-dimensional representation to
representtheirrelativepositioningintheconsumersmind. •HarvestGoldmulti-grain need notworry about competitionwith
theothertwoastheconsumerwhobuysthemulti-grainwillnotbuythemasasubstituteastheyareverydifferentfromthebreadtheyeatregularly.MDSisonlyoneofthewidearrayofstatisticaltechniquesavailable
forobtainingtheobjectmap.Thewholerangeofthesemethodsgroupedtogetheristermedasperceptualmappingtechniques.
LetusnowbrieflyattempttounderstandtheunderlyingalgorithmsofMDS. •Theinputsobtainedbytherespondentscouldbeintermsofobjects,
individuals,brands,corporationsorcountries. •Thecomparisoncouldbeintermsofsimilarities/dissimilarities,e.g.
howsimilarisDelhitoMumbaiona7-pointscalerangingfromthemostdissimilartothemostsimilar;orpreferences,e.g.outofthefive
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listedbrands,indicatetheoneyoupreferthemosttotheonethatisleastpreferred.
•Asyoucanobserve,therespondentisNOTgivenanydimensiontomeasuresimilarityordissimilarity.
•Thepreferencescouldbebasedonrankeddata. •Therespondentmightbeaskedtoconductapairedcomparisonofthe
data.
13.3.4 Discriminant Analysis
Discriminantanalysisisusedtopredictgroupmembership.Thistechniqueisusedtoclassifyindividuals/objectsintooneofthealternativegroupsonthebasisofasetofpredictorvariables.Thedependentvariableindiscriminantanalysisiscategoricalandonanominalscale,whereastheindependentorpredictorvariablesareeitherintervalorratioscaleinnature.Whenthereare two groups (categories) of dependent variable,we have two-groupdiscriminantanalysisandwhentherearemorethantwogroups,itisacaseofmultiplediscriminantanalysis.Incaseoftwo-groupdiscriminantanalysis,thereisonediscriminantfunction,whereasincaseofmultiplediscriminantanalysis,thenumberoffunctionsisonelessthanthenumberofgroups.
Objectives and Uses of Discriminant Analysis
Theobjectivesofdiscriminantanalysisarethefollowing: •Tofindalinearcombinationofvariablesthatdiscriminatebetween
categoriesofdependentvariableinthebestpossiblemanner. •To find outwhich independent variables are relatively better in
discriminatingbetweengroups. •Todeterminethestatisticalsignificanceofthediscriminantfunction
andwhetheranystatisticaldifferenceexistsamonggroupsintermsofpredictorvariables.
•Todeveloptheprocedureforassigningnewobjects,firmsorindividualswhoseprofilebutnotthegroupidentityareknowntooneofthetwogroups.
•To evaluate the accuracy of classification, i.e., the percentage ofcustomersthatitisabletoclassifycorrectly.Discriminantanalysiscanbeaverypowerfultechniqueofanalysisin
multiplesituations.Someareasinwhichitisextensivelyusedareasfollows: • Scale construction: Discriminant analysis is used to identify the
variables/statements that are discriminating and onwhich peoplewith diverse viewswill respond differently. For example, in caseonewantstoassesspeoplewhobelievethatcorporategovernanceistheresponsibilityofpolicy-makersagainstthosewhothinkitneeds
Overview of Non-Parametric Tests
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tobeselfdrivenor individualcentric,onemaygenerateanumberof statements and then conduct a pilot study and select only thosestatementsonwhichthetwogroupsdiffersignificantly.
• Segment discrimination: Most businessmanagers recognize thatthepopulationunderconsiderationcanneverbetotallyhomogeneousincomposition.Therefore,tounderstandwhatthekeyvariablesareonwhichtwoormoregroupsdifferfromeachother,thistechniqueisextremelyuseful.Questionstowhichonemayseekanswersareasfollows:o Whatarethedemographicvariablesonwhichpotentiallysuccessful
salesmenandpotentiallyunsuccessfulsalesmendiffer?o Whatarethevariablesonwhichusers/non-usersofaproductcan
bedifferentiated?o Whataretheeconomicandpsychographicvariablesonwhichprice-
sensitiveandnon-pricesensitivecustomersbedifferentiated?o Whatarethevariablesonwhichthebuyersoflocal/nationalbrand
ofaproductbedifferentiated? • Perceptual mapping: Thetechniqueisalsousedextensivelytocreate
attribute-basedspatialmapsoftherespondent’smentalpositioningofbrands.Theadvantageofthetechniqueisthatitcanpresentbrandsorobjectsandtheattributesonthesamemap.Therefore,thebusinessmanagercandeterminewhatattributeistheuniquesellingproposition(USP)ofwhichbrandandwhicharetheattributesthatarevaluedbytherespondentbutthereisnobrandthatcurrentlysatisfiesthatneed.
Discriminant Analysis Model
Themathematicalformofthediscriminantanalysismodelis:Y=b0+b1 X1+b2 X2+b3 X3+...+bK XK
where, Y= Dependentvariable bs= Coefficientsofindependentvariables Xs= PredictororindependentvariablesItmaybe kept inmind that the dependent variableY should be a
categorized variable,whereas the independent variablesXs should becontinuous.Asthedependentvariableisacategorizedvariable,itshouldbecodedas0,1or1,2and3,similartothedummyvariablecoding.
Themethodofestimatingbsisbasedontheprinciplethattheratioofbetweengroupsumofsquarestowithingroupsumofsquaresbemaximized.Thiswillmakethegroupsdifferasmuchaspossibleonthevaluesofthediscriminantfunction.
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After having estimated themodel, the bs coefficients (also calleddiscriminantcoefficient)areusedtocalculateY,thediscriminantscorebysubstitutingthevaluesofXsintheestimateddiscriminantmodel.Foranynewdatapointthatwewanttoclassifyintooneofthegroups,adecisionruleisformulatedforthispurposetodeterminethecut-offscore,whichisusuallythemidpointofthemeandiscriminantscoresofthetwogroupsincaseoftwo-groupdiscriminantanalysis,providedthesizeofthesamplesinthetwogroupsaresame.Theaccuracyofclassificationisdeterminedbyusingaclassificationmatrix(alsocalledconfusionmatrix).
The relative importance of the independent variables could bedeterminedfromthestandardizeddiscriminantfunctioncoefficientandthestructurematrix.Thedifferencebetweenthestandardizedandunstandardizeddiscriminant function is that in theun-standardizeddiscriminant functionwehaveaconstantterm,whereasinthestandardizeddiscriminantfunction,thereisnoconstantterm.
13.4 THE PROCESS OF INTERPRETATION OF TEST RESULTS
Alotofstatisticalinformationisavailableintoday’sglobalandeconomicenvironment,whichcanbeusedsuccessfullyonlyifdecision-makersareabletonotonlyunderstandbutalsointerprettheinformation,anduseiteffectively.Thestepsinvolvedinstatisticaldataanalysisare:
Step 1— Defining the problem
Toobtaincorrectdataitisessentialtodefinetheproblemaccurately.
Step 2 — Collecting data
Thenextstepistodesignwaysfordatacollection.Youcouldcollectdatafromtheentirepopulation,thatisasetofallelementsofinterestinastudyoryoucouldcollectfromasampleofthepopulation,thatis,asubsetofthepopulation.Itcanbecollectedthroughobservationalorexperimentalstudiesor fromexistingsources.Thedatacouldeitherbecross-sectional, that iscollectedatthesameorapproximatelythesamepointintimeortimeseries,thatis,collectedoverseveraltimeperiods.Datacouldbequalitative,thatis,labelsornamesusedtoidentifyanattributeofeachelement.Quantitativedata,ontheotherhand,couldbenumericdataindicativeofnumbersorvolumes.
Step 3— Analysing the data
Thedatacollectedcanbeanalysedusingexploratorymethodsorconfirmatorymethods.Whileexploratorytechniquestrytofindoutwhatthedataistryingtosayusingsimplemathsorillustrations,confirmatorymethodsuseideas(fromprobabilitytheory)totryananswerspecificquestions.
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Step 4 — Reporting the results
Theresultsoftheanalysiscanbepresentedintheformofagraph,atable,apiechartorasetofpercentages,incasethesampleissmall.Incasetheanalysisinvolvesanentirepopulation,thereportwillalsohavetobedetailed.
13.4.1 Guidelines for Making Valid Interpretation
Validation is theprocessbywhichevidence isgathered tocomeupwithareliableandsoundscientificbasis tohelp interpret theresults/scoresasproposedbythetestdeveloperoruser.Validation,startswithaframeworkthatdefinesthescopeandaspects(inthecaseofmulti-dimensionalscales)oftheproposedinterpretation.Theframeworkalsoincludesarationaljustificationthatlinkstheinterpretationtothetest.
Thenextstepistolistaseriesofpropositionstobefulfilledfortheinterpretationtobevalid.Theotheroptionistocompilealistofissuesthatmayadverselyaffectthevalidityoftheinterpretations.Ineithercaseevidenceneedstobegatheredthroughoriginalorempiricalresearchorthroughmeta-analysisorreviewofexistingliterature,orlogicalanalysisoftheissues.Thissupportsorquestionstheinterpretation’spropositionsorthreatstoitsvalidity.Thefocusisonquality,ratherthanquantity,oftheevidence.
Asingleinterpretationofanytestmayrequiremanypropositionstobetrue.Evenastrongevidencesupportingasinglepropositionwillnotlessentheneedtosupporttheotherpropositions.
Evidencetosupport(orquestion)thevalidityofaninterpretationcanbeclassifiedintooneofthefollowingcategoriesbasedon: 1. Test content 2.Responseprocesses 3. Internalstructure 4.Relationstoothervariables 5.Consequencesoftesting
Methodstocollecteachtypeofevidenceshouldonlybeusedwhentheyresultininformationthatwouldeitherbackorchallengethepropositionsneededtointerpret.Eachevidenceisthenabsorbedintoavalidityargument,whichmayrequirethetesttoberevised,ortheadministrationprotocolofthetesttobemodifiedorthetheoriesorconceptsformingthebaseoftheinterpretationstoberevised.Ifanyofthisisdoneinanyway,anewvalidationprocesswillrequiretocollectevidence,whichwillsupporttherevisedornew version.
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Qualitative Research and Validity
Inquantitativeresearchvalidityreferstothefollowing: • Internalvalidity(dependentonthestrengthof therelationbetween
causeandeffect) •Externalvalidity(indicatingthepossibilitytogeneralizefindings).
Inqualitativeresearch,validityisarathercomplexissueanditisnotpossibletoapplytraditionalstandardseasily.Iftheknowledgeissubjectiveorifthereisasingleinaccessibletruth,thevaliditycriteriacanonlybeverygenericor/andsubjective.LincolnandGuba (1985) suggestedempiricistcriteriaforqualitativeresearch,asfollows: •Credibilityorinternalvalidity •Transferabilityorexternalvalidity •Dependability •Confirmability
Latertheconceptsofauthenticityandmoralitywerebroughtin(Angen2000).
Check Your Progress
1.ListoneassumptionintheANOVAtechnique. 2.Whatisfactoranalysis? 3.Whatisthefirststepoffactoranalysis? 4.Whatisvalidation?
13.5 ANSWERS TO CHECK YOUR PROGRESS QUESTIONS
1.OneoftheassumptionsusedintheANOVAtechniqueisthatalltheinvolvedpopulationsfromwherethesamplesaretakenarenormallydistributed.
2.Factoranalysisisamultivariatestatisticaltechniqueinwhichthereisnodistinctionbetweendependentandindependentvariables.
3.Thefirstandtheforemoststepinfactoranalysisistodecideonhowmanyfactorsaretobeextractedfromthegivensetofdata.
4.Validationistheprocessbywhichevidenceisgatheredtocomeupwithareliableandsoundscientificbasistohelpinterprettheresults/scoresasproposedbythetestdeveloperoruser.
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13.6 SUMMARY
•There are situationswhere assumptions cannot bemade. In suchsituations,differentstatisticalmethodsareused,whichareknownasnon-parametrictests.
•TheMann-Whitneytestisusedtoexaminewhethertwosampleshavebeendrawnfrompopulationswithsamelocations(mean).
•TheKruskal-Wallis test is an extension of theMann-WhitneyUtest discussed earlier.Bothmethods require that the scale of themeasurementofasamplevalueshouldbeatleastordinal.
•Factoranalysisisamultivariatestatisticaltechniqueinwhichthereisnodistinctionbetweendependentandindependentvariables.Infactoranalysis, all variables under investigation are analysed together toextracttheunderlinedfactors.
•Cluster analysis is a grouping technique.The basic assumptionunderlyingthetechniqueisthefactthatsimilarityisbasedonmultiplevariables,andthetechniqueattemptstomeasuretheproximityintermsofthestudyvariables.
•Discriminant analysis is used to predict groupmembership.Thistechnique is used to classify individuals/objects into one of thealternativegroupsonthebasisofasetofpredictorvariables.
•Thedependentvariableindiscriminantanalysisiscategoricalandonanominalscale,whereastheindependentorpredictorvariablesareeitherintervalorratioscaleinnature.
•Validation,startswithaframeworkthatdefinesthescopeandaspects(inthecaseofmulti-dimensionalscales)oftheproposedinterpretation.The framework also includes a rational justification that links theinterpretationtothetest.
13.7 KEY WORDS
•Factor Analysis:Itisaprocessinwhichthevaluesofobserveddataareexpressedasfunctionsofanumberofpossiblecausesinordertofindwhicharethemostimportant.
•Cluster Analysis:Itisthetaskofgroupingasetofobjectsinsuchawaythatobjectsinthesamegrouparemoresimilartoeachotherthantothoseinothergroups
•Perceptual Mapping:Itisadiagrammatictechniqueusedbyassetmarketersthatattemptstovisuallydisplaytheperceptionsofcustomersorpotentialcustomers.
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Overview of Non-Parametric Tests13.8 SELF ASSESSMENT QUESTIONS AND
EXERCISES
Short Answer Questions
1. DiscusstheMann-Whitneytest. 2.ListthetestingprocedureoftheWilcoxonmatched-pairsignedrank
test. 3.Writeashort-noteontheusesoffactoranalysis. 4.Listthestepsinstatisticaldataanalysis.
Long Answer Questions
1. IllustratetheKruskal-Wallistest. 2.Examinethefactoranalysisexerciseindetail. 3.Describetheuseofclusteranalysis. 4.Explainthediscriminantanalysismodelindetail.
13.9 FURTHER READINGS
Creswell,JohnW.2002.Research Design: Qualitative, Quantitative, and Mixed Methods Approaches.London:SagePublicationsInc.
Booth,Wayne,GregoryG.ColombandJosephM.Williams.1995.The Craft of Research.Chicago:UniversityofChicagoPress.
Bryman,AlanandEmmaBell.2015.Business Research Methods.4thEdition.UnitedKingdom:OxfordUniversityPress.
Gupta,S.L.andHiteshGupta. 2012. Business Research Methods. NewDelhi: TataMcGrawHillEducationPrivateLimited.
Report Writing
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UNIT 14 REPORT WRITINGStructure 14.0 Introduction 14.1 Objectives 14.2 RoleandTypesofResearchReports 14.3 StepsInvolvedinDraftingResearchReports 14.4 ContentsofResearchReport 14.5 ReportWriting:Principles,FeaturesandCriteria
14.5.1 PrinciplesofaGoodReportWriting 14.5.2 FeaturesofaGoodResearchReport 14.5.3 CriteriaforEvaluatingResearchReports/Findings
14.6 ResearchReport:LanguageFlowandGrammaticalQuality 14.6.1 ClarityandBrevityofExpressions 14.6.2 ReferencesandAnnotations
14.7 DataSupportandDiagrammaticElucidation 14.8 AnswerstoCheckYourProgressQuestions 14.9 Summary 14.10 Key Words 14.11 SelfAssessmentQuestionsandExercises 14.12 FurtherReadings
14.0 INTRODUCTION
In this unit, youwill learn about the various aspects of research reportwriting.Oncompletionoftheresearchstudyandafterobtainingtheresearchresults,therealskilloftheresearcherliesinanalysingandinterpretingthefindingsandlinkingthemwiththepropositionsformulatedintheformofresearchhypothesesatthebeginningofthestudy.Thestatisticalorqualitativesummaryofresultswouldbelittlemorethannumbersorconclusionsunlesstheresearcherisabletopresentthedocumentedversion(researchreport)oftheresearchendeavour.
Thus,onecannotoveremphasizethesignificanceofawell-documentedandstructuredresearchreport.Justlikealltheotherstepsintheresearchprocess,thisrequirescarefulandsequentialtreatment.Inthisunit,wewillbediscussingindetailthedocumentationoftheresearchstudy.Theformatandthestepsmightbemoderatelyadjustedandalteredbasedonthereader’srequirement.Thus,itmightbeforanacademicandtheoreticalpurposeormightneedtobeclearlyspeltandlinkedwiththebusinessmanager’sdecisiondilemma.
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Report Writing14.1 OBJECTIVES
Aftergoingthroughthisunit,youwillbeableto: •Discusstheroleandtypesofreports • Identifythestepsinvolvedindraftingreports •Describethevariouscontentsofaresearchreport •Explaintheprinciples,criteriaandfeaturesofagoodresearchreport •Discussthemethodstobefollowedindiagrammaticelucidationof
datainresearchreports • Statehowclarityandbrevityofexpressionsenhancesthequalityof
researchreports
14.2 ROLE AND TYPES OF RESEARCH REPORTS
Researchreportsaredesignedinordertoconveyandrecordtheinformationthatwillbeofpracticalusetothereader.Itisorganizedintodistinctunitsofspecificandhighlyvisibleinformation.Theroleofresearchreportsmaybesummarizedasfollows: •Theresearchreportfulfilsthehistoricaltaskofservingasaconcrete
proofof the study thatwasundertaken.This serves thepurposeofprovidingaframeworkforanyworkthatcanbeconductedinthesameorrelatedareas.
• Itisthecompletedetailedreportoftheresearchstudyundertakenbytheresearcher,thusitneedstobepresentedinacomprehensiveandobjectivemanner.Thisisaone-waycommunicationoftheresearcher’sstudyandanalysis to the reader/manager,and thusneeds tobeall-inclusiveandyetneutralinitsreporting.
• Foracademicpurpose,therecordeddocumentpresentsaknowledgebaseonthetopicunderstudyandforthebusinessmanagerseekinghelpintakingmoreinformeddecisions,thereportprovidesthenecessaryguidancefortakingappropriateaction.
•Asthereportdocumentsallthestepsfollowedandtheanalysiscarriedout,italsoservestoauthenticatethequalityoftheworkcarriedoutandestablishesthestrengthofthefindingsobtained.Thus, effective recording and communicatingof the results of the
studybecomesanextremelycriticalstepoftheresearchprocess.Basedonthenatureoftheresearchstudyandtheresearcher’sorientation,thereportcantakedifferentforms.
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Types of Research Reports
Researchreportscanbecategorizedonthefollowingbases: 1.Onthebasisofsize 2.Onthebasisofinformation 3.Onthebasisofrepresentation
1. Classification on the basis of size
Basedonthesizeofthereport,itispossibletodividethereportintobriefreportsanddetailedreports. • Brief reports: Thesekindsofreportsarenotformallystructuredand
are generally short, sometimes not runningmore than four tofivepages.Theinformationprovidedhaslimitedscopeandisapreludetotheformalstructuredreportthatwouldsubsequentlyfollow.Thesereportscouldbedesignedinseveralways.o Working papers or basic reportsarewrittenforthepurposeof
recordingtheprocesscarriedoutintermsofscopeandframeworkofthestudy,themethodologyfollowedandinstrumentdesigned.Theresultsandfindingswouldalsoberecordedhere.However,theinterpretationofthefindingsandstudybackgroundmightbemissing,asthefocusismoreonthepresentstudyratherthanpastliterature.
o Survey reports mightormightnothaveanacademicorientation.Thefocushereistopresentfindingsineasy-to-comprehendformatthatincludesfiguresandtables.Theadvantageofthesereportsisthattheyaresimpleandeasytounderstandandpresentthefindingsinaclearandusableformat.
• Detailed reports: These aremore formal and could be academic,technicalorbusinessreports.Sometimes,theresearchermaypreparebothkinds—foranindividual
aswellasforabusinesspurpose.
2. Classification on the basis of information
Thewaysthroughwhichtheresultsoftheresearchreportcanbepresentedonthebasisofinformationcontainedasfollows: • Technical report:Atechnicalreportisnotwrittenbytheresearcher
himselfbutiswrittenonbehalfofotherresearchers.Inwritingtechnicalreports,importanceismainlygiventothemethodsthathavebeenusedtocollect the informationand thedata, thepresumptions thatweremadeandfinally,thevariouspresentationtechniquesthatwereused
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Report Writingtopresentthefindingsandthedata.Followingarethemainfeaturesofatechnicalreport:o Summary:Itcoversabriefanalysisofthefindingsoftheresearch
inafewpages.o Nature:Itcontainsthereasonsforwhichtheresearchisundertaken,
theanalysisandthedatathatisrequiredinordertopreparethereport.o Methods employed:Itcontainsadescriptionofthemethodsthat
wereemployedinordertocollectdata.o Data:Itcoversabriefanalysisofthevarioussourcesfromwhich
thedatawascollectedwiththeirfeaturesanddrawbacks.o Analysis of data and presentation of the findings:Itcontainsthe
variousformsinwhichthedatathathasbeenanalysedandcanbepresented.
o Conclusions:Itcontainsabriefexplanationofthefindingsoftheresearch.
o Bibliography: It contains a detailed analysis of the variousbibliographiesthathavebeenusedinordertoconducttheresearch.
o Technical appendices:Itcontainstheappendicesforthetechnicalmattersandforquestionnairesandmathematicalderivations.
o Index:Theindexofthetechnicalreportmustbeprovidedattheendofthereport.
• Popular report:Apopularreportisformulatedwhenthereisaneedtodrawtheconclusionsofthefindingsoftheresearchreport.Oneofthemainconsiderationsthatshouldbekeptinmindwhileformulatingaresearchreportisthatitmustbesimpleandattractive.Itmustbewritteninaverysimplemannerthatcanbeisunderstoodall,andalsobemadeattractivebyusinglargeprints,varioussub-headingsandbygivingcartoonsoccasionally.Thefollowingarethemainpointsthatmustbekeptinmindwhilepreparingapopularreport:o Findings and their implications:While preparing a popular
report,importanceisgiventothefindingsoftheinformationandtheconclusionsthatcanbedrawnoutofthesefindings.
o Recommendations for action:Ifthereareanydeviationsinthereportthenrecommendationsaremadefortakingcorrectiveactioninordertorectifytheerrors.
o Objective of the study:Inapopularreport,thespecificobjectiveforwhichtheresearchhasbeenundertakenispresented.
o Methods employed:Thereportmustcontainthevariousmethodsthathavebeenemployedinordertoconductaresearch.
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o Results:Theresultsoftheresearchfindingsmustbepresentedinasuitableandappropriatemannerbytakingthehelpofchartsanddiagrams.
o Technical appendices: The reportmust contain an in-depthinformationusedtocollectthedataintheformofappendices.
• Technical reports: Thesearemajordocumentsandwould includeall elements of the basic report, aswell as the interpretations andconclusions, as related to the obtained results.Thiswould have acompleteproblembackgroundandanyadditionalpastdata/recordsthatareessentialforunderstandingandinterpretingthestudyresults.Allsourcesofdata,samplingplan,datacollectioninstrument(s),dataanalysisoutputswouldbeformallyandsequentiallydocumented.
• Business reports: Thesereportsincludeconclusionsasunderstoodbythebusinessmanager.Thetables,figuresandnumbersofthefirstreportwouldnowbepictoriallyshownasbarchartsandgraphsandthereportingtonewouldbemoreinbusinessterms.Tabulardatamightbeattachedintheappendix.
3. Classification on the basis of representation
Followingarethewaysthroughwhichtheresultsoftheresearchreportcanbeclassifiedonthebasisofrepresentation: • Written report: Awrittenreportplaysavitalroleineverybusiness
operation.Themannerinwhichanorganizationwritesbusinesslettersandbusinessreportscreatesanimpressionaboutitsstandard.Therefore,theorganizationshouldemphasizeontheimprovementofwritingskillsof theemployees inorder tomaintaineffective relationswith theircustomers.Makinganeffectivewrittenreportrequiresalotofhardwork.Therefore,beforeyoubeginwriting,itisimportanttoknowtheobjective,i.e.,thepurposeofwriting,collectionandorganizationofrequireddata.
• Oral report: Attimes,oralpresentationoftheresultsthataredrawnoutofresearchisconsideredeffective,particularlyincaseswherepolicyrecommendations are to bemade.This approachprovesbeneficialbecauseitprovidesamediumofinteractionbetweenthelistenersandthespeakers.Thisleadstoabetterunderstandingofthefindingsandtheirimplications.However,themaindrawbackoforalpresentationislackofanypermanentrecordsrelatedtotheresearch.Oralpresentationofareportismoreeffectivewhenit issupportedbyvariousvisualdevicessuchasslides,wallchartsandwhiteboardsthathelpinbetterunderstandingoftheresearchreports.
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Report Writing14.3 STEPS INVOLVED IN DRAFTING RESEARCH
REPORTS
Whateverthetypeofreport,thereportinganddisseminationofthestudyanditsfindingsrequireastructuredformatandbyandlarge,theprocessisstandardized.Asstatedabove, themajordifferenceamongst the typesofreportsisthatalltheelementsthatessentiallyconstitutearesearchreportwouldbepresent only in a detailed technical report. In themanagementreport, the information on the sampling techniques follows the researchintention, and thequestionnairedesigndetails neednot be reported.Thereviewofpast literaturewouldbeperfunctoryinthemanagementreport;however, theywouldbedetailedandaccompaniedwith thebibliographyinthetechnicalreport.Usageoftheoreticalandtechnicaljargonwouldbehigherinthetechnicalreportandvisualpresentationofdatawouldbehigherinthemanagementreport.
The process of report formulation and presentation is presentedinFigure14.1.As canbeobserved, thepreliminary section includes therudimentary parts, for example the title page, followed by the letter ofauthorization, acknowledgements, executive summary and the table ofcontents.Thencomethebackgroundsection,whichincludestheproblemstatement,introduction,studybackground,scopeandobjectivesofthestudyandthereviewofliterature(dependsonthepurpose).Thisisfollowedbythemethodologysection,which,asstatedearlier,isagainspecifictothetechnicalreport.Thisisfollowedbythefindingssectionandthencometheconclusions.Thetechnicalreportwouldhaveadetailedbibliographyattheend.
In themanagement report, the sequencing of the reportmight bereversedtosuittheneedsofthedecision-maker,asherethereaderneedstoreviewandabsorbthefindings.Thus,insteadofsimplysummarizingthestatisticalresults,thefindingsneedtobepresentedinsuchawaythattheycanbeuseddirectlyasinputsfordecision-making.Thus,thelastsectionwouldbepresentedimmediatelyafterthestudyobjectivesandashortreportingonmethodologycouldbepresentedintheappendix.
Thus,theentireresearchprojectneedstoberecordedeitherasasinglewrittenreportorintoseveralreports,dependingontheneedofthereaders.Theresearcherwouldneedtoassistthebusinessmanagerindecipheringthereport,executingthefindings,andincaseofneed,torevisethereporttosuitthespecificactionablerequirementsofthemanager.
Thus,researchreportsaretheproductofslow,painstaking,accurateinductivework.Theusualstepsinvolvedinwritingaresearchreportareasfollows:
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Step 1:Logicalanalysisofthesubject-matterStep 2:PreparationofthefinaloutlineStep 3:PreparationoftheroughdraftStep 4:RewritingandpolishingStep 5:PreparationofthefinalbibliographyStep 6:Writingthefinaldraft
14.4 CONTENTS OF RESEARCH REPORT
Aspresented inFigure14.1,most research reports include the followingsections:
Fig. 14.1 The Process of Report Formulation and Writing
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Report WritingPreliminary section
This sectionmainly consists of identification information for the studyconducted.Ithasthefollowingindividualelements:Title page: Thisincludesclassificationdataabout: •Thetargetaudience,ortheintendedreaderofthereport •Thereportauthor(s),includingtheirname,affiliationandaddress. •The titleof the studypresented inamanner toclearly indicate the
studyvariables;therelationshiporstatusofthevariablesstudiedandthepopulationtowhichtheresultsapply.Thetitleshouldbecrispandindicativeofthenatureoftheproject,asillustratedinthefollowingexamples.o Comparative analysis ofBPOworkers and schoolteacherswith
referencetotheirwork–lifebalanceo SegmentationanalysisofluxuryapartmentbuyersintheNational
CapitalRegion(NCR).o Anassessmentofbehaviouralfactorsimpactingconsumerfinancial
investment decisions. Letter of transmittal: Thisistheletterthatgoesalongsidetheformalizedcopyofthefinalreport.Itbroadlyreferstothepurposebehindthestudy.Thetoneinthisnotecanbeslightlyinformalandindicativeoftherapportbetween the client-reader and the researcher.The letter broadly refers tothreeissues.Itindicatesthetermofthestudyorobjectives;nextitgoesontobroadlygiveanindicationoftheprocesscarriedouttoconductthestudyandtheimplicationsofthefindings.Theconclusionsgenerallyareindicativeoftheresearcher’sinterest/learningfromthestudyandinsomecasesmaybelayingthefoundationforfutureresearchopportunities.Letter of authorization: Sometimes the letter of authorizationmay beredundantasindicationsoftheformalapprovalforconductingthestudymightbeincludedintheletteroftransmittal.Theauthorofthisletteristhebusinessmanagerorcorporaterepresentativewhoformallygivesthepermissionforexecutingtheproject.Thetoneofthisletter,unliketheabovedocument,isverypreciseandformal,leavingnoroomforspeculationorinterpretation.
Asexplained,thisletterisnotcriticaltosubmission,incasereferencetothesamehasbeenmadeinthetransmittalletter.However,incaseitistobeincludedinthereport,itisadvisabletoreproducetheexactprototypeoftheoriginalletter.Table of contents:Allreportsshouldhaveasectionthatclearlyindicatesthedivisionofthereportbasedontheformalareasofthestudyasindicatedintheresearchstructure.Themajordivisionsandsubdivisionsofthestudy,alongwiththeirstartingpagenumbers,shouldbepresented.Thesubheadings
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andthesmallersectionsofatopicneednotbeindicatedhereasthenthepresentationofthecontentseemscluttered.
Oncethemajorsectionsofthereportarelisted,thelistoftablescomenext,followedbythelistoffiguresandgraphs,exhibits(ifany)andfinallythelistofappendices.Executive summary: Thisisthelastandthemostcriticalelementofthepreliminary section.The summaryof the entire report, starting from thescope andobjectivesof the study to themethodology employed and theresultsobtained,havetobepresentedinabriefandconcisemanner.Incasetheresearchrequirementwastoproviderecommendedchangesbasedonthefindings,itisadvisabletoprovideshortpointershere.Interestingly,ithasbeenobservedthatinmostinstancesthebusinessmanagersreadonlytheexecutivesummaryinitscompletedetailandmostoftenjustglancethroughtherestofthereport.Thus,itbecomesextremelycriticaltopresentaGestaltanviewoftheentirereportinasuitablecondensedform.
Theexecutivesummaryessentiallycanbedividedintofourorfivesections. It beginswith the study background, scope and objectives ofthe study, followed by the execution, including the sample details andmethodologyofthestudy.Nextcomesthefindingsandresultsobtained.Thefourthsectioncoverstheconclusionswhicharemoreorlessbasedontheopinionoftheresearcher.Finally,asstatedearlier,incasethestudyobjectivesnecessitatesimplications,thelastsectionwouldincluderecommendationsandsuggestions.Acknowledgements:A small note acknowledging the contribution ofthe respondents, the corporates and the expertswhoprovided inputs foraccomplishingthestudyistobeincludedhere.
Thoughtheexecutivesummarycomesbeforethemainbodyofthereport,itisalwayspreparedaftertheentirereporthasbeenfinalizedandisreadyinitsfinalform.Thelengthofthissectionisoneortwopagesonlyandtheresearcherneedstoeffectivelypresentthemostsignificantpartsofthestudyinasuccinctform.Ithasbeenobservedthattheexecutivesummaryisastandalonedocumentthatisoftencirculatedindependentlytotheinterestedmanagerswhomightbedirectlyorindirectlyrelatedtothestudy.
Main report
Thisisthemostsignificantandacademicallyrobustpartofthereport.Thesectionsofthisdivisionfollowtheessentialpatternofatypicalresearchstudy.Problem definition:Thissectionbeginswiththeformaldefinitionoftheresearchproblem.Theproblemstatementistheresearchintentionandismoreorlesssimilartowhatwasstatedearlierasthetitleoftheresearchstudy.
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Report WritingStudy background:Studybackgroundpresentsdetailsofthepreliminaryconceptualizationofthemanagementdecisionproblemandallthegroundworkdoneintermsofsecondarydataanalysis,industryexperts’perspectivesandanyotherearlierreportingofsimilarapproachesundertaken.Thus,essentially,thesectionbeginsbypresentingthedecision-makers’problemandthenmovesontoadescriptionofthetheoreticalandcontemporarymarketdatathatlaidthefoundationthatguidedtheresearch.
Incasethestudyisanacademicresearch,thereisaseparatesectiondevotedtothereviewofrelatedliterature,whichpresentsadetailedreportingofworkdoneonthesameorrelatedtopicofinterest.Study scope and objectives:Thelogicalargumentsthenconcludeintheformofdefinitestatementsrelatedtothepurposeofthestudy.Acleardefinitionofthescopeandobjectiveofthestudyispresentedusuallyafterthestudybackground;incasethestudyiscausalinnature,theformulatedhypothesesarepresentedhereaswell.Methodology of research:Thissectionwouldnotbesequentiallyplacedhere, for short reports or for a business report. In such reports, a shortdescription of themethodology followedwould be documented in theappendix.However,foratechnicalandacademicreport,thisisasignificantandprimarycontributionoftheresearchstudy.Thesectionwouldessentiallyhavefive to six sections specifying the details of how the researchwasconducted.Thesewouldessentiallybe: • Research framework or design: The variables and concepts being
investigated are clearly defined, with a clear reference to therelationshipbeingstudied.Thejustificationforusingaparticulardesignhastobepresentedinasequentialandstep-wisemannerenlistingtheexperimentalandcontrolconditions, incaseofacausalstudy.Theresearchermusttakecaretokeepthetechnicaldetailsoftheexecutionintheappendixandpresenttheexecutiondetailsinsimplelanguage,inthemainbody.
• Sampling design: Theentiresamplingplanintermsofthepopulationbeingstudied,alongwiththereasonsforcollectingthestudy-relatedinformationfromthegivengroupisgivenhere. Theexecutiondetails,intermsofsamplesizecalculations,samplingframeconsideredandfieldworkdetailscanberecordedintheappendixratherthaninthemainbodyofthereport.However,thesampleprofileandidentificationdetailsareincludedinthemainsection.Asstatedearlier,thereportneedstobereader-friendly,andtoomuchtechnicalinformationmightnotberequiredbythedecision-maker.
• Data collection methods: Inthissection,theresearchershouldclearlylist the informationneeded for the study as drawn from the study
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objectivesstatedearlier. Thesecondarydatasources consideredandtheprimaryinstrumentdesignedforthespecificstudyarediscussedhere.However,thefinaldraftofthemeasuringinstrumentcanbeincludedintheappendix,whichincludestheexecutiondetailsintermsofhowtheinformationwascollected;howtheopenendedoropinion-basedquestionswere handled; and how irregularitieswere handled andaccounted for in the study.Theseandsimilar informationenableaclearinsightintothestandardizationofproceduresmaintained.
• Data analysis: Here,theresearcheragainneedstorevisittheresearchobjectivesandthestudydesigninordertojustifytheanalyticaltoolsand techniques used in the study.The assumptions and constraintsof the analysis need to be explainedhere in simple, non-technicalterms.Thereisnoneedtogiveadetaileddescriptionofthestatisticalcalculationshere.
• Study results and findings: Thisisthemostcriticalchapterofthereportandrequiresspecialcare;itisprobablyalsooneofthelongestchaptersinthedocument.Theresearchercould,thus,considereitherbreakingthisintosubchaptersoratleastclearsubheadings. Researchers commonlydivide the chapter on the basis of the data
collectionplan,i.e.,thereisasectiononinterviewanalysis,anotheroneonfocusgroupdiscussionandthethirdreferringtothequestionnaireanalysis.This,however,doesnotserveanypurposeas theresultswouldthenseemrepetitiveanddisjointed.Instead,theresultshouldbeorganizedaccordingtotheinformationareasonwhichthedatawascollectedoronthebasisoftheresearchobjectives.Therearealsotimeswhenthedatawouldbepresentedforthewholesampleandthenwillbesplitandpresentedforthesub-populationstudied.Forexample,inthestudyonwork-lifebalance,thefindingswerepresented for thewhole sampleand thenat themicro level for theBPOsectorandseparatelyfortheschoolteachersegment.Foreachgroup,firstthesampleprofileintermsofthedemographicdetailsofage,education,income(individualandfamily),yearsofexperience,maritalstatus,familysizeandotherdetailswaspresented.Next,thedescriptivedatawasmadeavailableonthesevensub-scalesstudied—andlastly—thepredictivedata–basedonamultipleregressionanalysiswithwork-lifebalanceasthedependentvariableandthesevenvariablesasindependent,waspresented.Therewasonlyoneopen-endedquestionrelatedtotheindividual’ssuggestionastowhatsupportwasrequiredfromone’splaceofworktoachievework-lifebalance.Thiswaspresentedlastintheformofabarchartshowingvariabilityintheresponsesgiven.Againasadvisedearlier,itisessentialtopresentthefindingsintheformofsimplifiedtables,graphsandfigures,withthesamebeingexplainedinsimpletextsubsequently.
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Report WritingInterpretations of results and suggested recommendations
Thesectionstudyresultsandfindings,i.e.,themainreport,presentsabird’seyeviewoftheinformationasitexistsinasummarizedandnumericalform.Thiskindofinformationmightbecomedifficulttounderstandandconvertintoactionablesteps,thustherealskilloftheresearcherliesinsimplifyingthedata in a reader-friendly language.Here, it is recommended that thissection should bemore analytical and opinion based.The results couldbesupportedbythedatathatwaspresentedearlier,forexample,industryforecastsortheexpertopinion.Incasethereporthadanearliersectiononliteraturereview,theresearchercoulddemonstratethesimilarityoffindingswithpaststudiesdoneonthetopic.Forexample,inastudyconductedonanalysingtheantecedentsof turnoverintention, theresultsobtainedwereexplainedasfollows:
The results of the logit regression indicate that organizational commitment, age and martial status are significant at 5 per cent and 10 per cent levels respectively. The results indicate that as organizational commitment increases, the log of odd ratios in the favour of high turnover intention reduces, which is very logical. This is in accordance with the results obtained by Mobley, et al. (1978), Cotton and Tuttle (1986), Igbaria and Greenhaus (1992), Ahuja, et al. (2007). Thus, when employees feel committed to an organization, they are more likely to stay with the organization.
Sometimes,theresearchresultsobtainedmaynotbeinthedirectionasfoundbyearlierresearchers.Here,theskilloftheresearcherinjustifyingtheobtaineddirectionisbasedonhis/herindividualopinionandexpertiseintheareaofstudy.Forexample,inthesamestudyonturnoverintentions,contraryfindingswereexplainedasfollows.
……..the results indicate that the log of odd ratios in favour of high turnover intention is more in the case of older respondents; this is contrary to the findings of Zeffane and Gul (1995) and Finegold, et al. (2002). However, this has to be understood in the light of the profession, as in India, most people take the BPO sector as a stop-gap career and use the time at the BPO employment as an opportunity to enhance their academic qualification and then move on, which is also one of the reasons why this sector is a young sector.
Subsequenttothesubsectionontheinterpretationofresults,sometimes,thestudyrequirementmightbetoformulateindicativerecommendationstothedecision-makersaswell.Thus,incasethereportincludesrecommendations,theyshouldberealistic,workableandtopicallyrelatedtotheindustrystudied.Forexample,tothebusinessmanageroforganicfoodproducts,thefollowingrecommendationwasmadetobuildawarenessamongstpotentialcustomersaboutthebenefitsoforganicproducts:
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Organic food study: An illustration: Thepower of the printmedia inpromoting a high-involvement product is unsurpassed.Thus, articles byleadingnutritionistsanddoctors(88percentofconsumersareinfluencedbyothersinconsuminghealthalternatives)onanyaspectoforganicfoodwouldworkwell.Theorganicplayersneedtotakecarethattheydonotadvertiseonlytheirproductofferingsandpricealonebuttheyalsoneedtoeducatetheconsumeronthehealthbenefitsoftheproductsintheiradvertisements.
Thearticle/advertisementcouldbeplacedintheSundaysupplementsofnewspaperssothatpeoplewouldreadthematleisure.Themajordecision-makersforgroceriesarewomenthusmagazineslikeFemina,HealthandSavvywould be likely choices (themagazines suggested are Englishfortnightliesandhaveareaderprofilesimilartooursampleprofile).Thisisalsobecausetheproductisapremiumandnicheproductandthusrequiresselectiveexposure.
Limitations of the study
Thelast in thissection isabriefdiscussionof theproblemsencounteredduringthestudyandtheconstraints in termsof time,financialorhumanresources.Therecouldalsohavebeenconstraintsinobtainingtherequiredinformation,eitherbecausethedataaboutthetopicofinteresthasnotbeencollectedorbecauseitisnotreadilyavailabletoall.Theseclearrevelationsaboutthedrawbacksarethuskeptinmindbythereaderwhenanalysingtheresultsandtheimplicationsofthestudy.
End notes
Thefinalsectionof the reportprovidesall thesupportivematerial in thestudy.Someofthecommondetailspresentedinthissectionareasfollows:Appendices:Theappendixsectionfollowsthemainbodyofthereportandessentiallyconsistsoftwokindsofinformation: 1.Secondaryinformationlikelongarticlesorincasethestudyuses/is
basedon/referstosometechnicalinformationthatneedstobeunderstoodbythereader.Orlongtablesorarticlesorlegalorpolicydocuments.
2.Primarydatathatcanbecompressedandpresentedinthemainbodyofthereport.Thisincludes:Originalquestionnaire,discussionguides,formulausedforthestudy,sampledetails,originaldata,longtablesandgraphswhichcanbedescribedinstatementforminthetext.
Bibliography: Thisisanimportantpartofthefinalsectionasitprovidesthecompletedetailsoftheinformationsourcesandpaperscitedinastandardizedformat. It is recommended to follow the publicationmanuals from theAmerican PsychologicalAssociation (APA) or theHarvardmethod ofcitationforpreparingthissection.Infact,withtheadvancementincomputertechnology theMicrosoftofficeWord2007canautomaticallygeneratea
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Report Writingbibliographybasedonanyoftheseformats,basedonthesourceinformationprovidedinthedocument.
Thereportingcontentofthebibliographycouldalsobeintermsof:• Selected bibliography:Selectivereferencesarecitedintermsof
relevanceandreaderrequirement.Thus,thebooksorjournalsthataretechnicalandnotreallyneededtounderstandthestudyoutcomesarenotreported.
• Complete bibliography:Alltheitemsthathavebeenreferredto,evenwhennotcitedinthetext,aregivenhere.
• Annotated bibliography:Alongwith thecompletedetailsof thecitedwork,somebriefinformationaboutthenatureofinformationsoughtfromthearticleisgiven.Thiscouldrunintothreeorfourlinesorabriefparagraph.
Atthisjuncturewewouldliketorefertoanothermethodofcitationthatanauthormightwishtouseduringreportwriting.Thiscouldbeintheformofafootnote.Toexplainthedifferencewewouldfirstliketoexplainwhatatypicalfootnoteis:Footnote: Atypicalfootnote,asthenameindicates,ispartofthemainreportandcomesatthebottomofapageorattheendofthemaintext.Thiscouldrefertoasourcethattheauthorhasreferredtooritmaybeanexplanationofaparticularconceptreferredtointhetext.
Thereferencingprotocolofafootnoteandbibliographyisdifferent.Inafootnote,onegivesthefirstnameofthepersonfirstandthesurnamenext.However,thisorderisreversedinthebibliography.Herewestartfirstwiththesurnameandthenthefirstname.Inabibliography,wegenerallymentionthepagenumbersofthearticleorthetotalpagesinthebook.However,inafootnote,thespecificpagefromwhichtheinformationiscitedismentioned.Abibliographyisgenerallyarrangedalphabeticallydependingontheauthor’sname,butinthefootnotethereportingisbasedonthesequenceinwhichtheyoccurinthetext.Glossary of terms: Incase thereare specific termsand technical jargonusedinthereport,theresearchershouldconsiderputtingaglossaryintheformofawordlistoftermsusedinthestudy.Thissectionisusuallythelastsectionofthereport.
Check Your Progress
1.Whatarethevariousbasesofcategorizingresearchreports? 2.Whenisapopularreportformulated? 3.Listtheusualstepsinvolvedinwritingaresearchreport. 4.Whatdoyouunderstandbytheletteroftransmittal?
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14.5 REPORT WRITING: PRINCIPLES, FEATURES AND CRITERIA
An important point to remember in reportwriting is that the documentcompiledismeantforspecificreaders.Thus,oneneedstodesignthesameaccordingtotheneedsofthereader.Listedbelowaresomefeaturesofagood researchstudy that shouldbekept inmindwhiledocumentingandpreparingthereport.Clear report mandate: Whilewritingtheresearchproblemstatementandstudybackground,thewriterneedstobefocused,preciseandveryexplicitin terms of the problemunder study, the background that provided theimpetustoconducttheresearchandthestudydomain.Thisispreparedontheassumptionthatthewriteratnopointintimeneedstobephysicallypresentinordertoclarifytheresearchmandate.Onecannotmakeanassumptionthatthereaderhasearlierinsightsintotheproblemsituation.Thewriterneedstobeabsolutelyclearontheneedforlucidityofthoughtanddisseminationofthisknowledgetothereader.Clearly designed methodology: Anyresearchstudyhasitsuniqueorientationandscopeandthushasaspecificandcustomizedresearchdesign,samplinganddatacollectionplan.Thewriter,thus,needstobeexplicitintermsofthelogicaljustificationforhavingusedthestudymethodsandtechniques.However,asstatedearlier,thelanguageshouldbenon-technicalandreaderfriendlyandanytechnicalexplanationsordetailsmustbeprovidedintheappendix.Inresearches, thatarenotcompletely transparentonthesetofprocedures,onecannotbeabsolutelyconfidentofthefindingsandresultingconclusions. Clear representation of findings: Thesamplesizeforeachanalysis,anyspecialconditionsordatatreatmentmustbeclearlymentionedeitherasafootnoteorasanendnote,sothatthereadertakesthisintoaccountwhileinterpretingandunderstandingthestudyresults.Thesamplebaseisveryimportantinjustifyingatrendortakingastrategicdecision;forexample,ifamongstasampleofbachelorswesaythat100percentyoungbachelorswanttobuygroceryonlineoronthetelephoneandtherecommendedstrategyistosuggestthisasthedeliverychannel,onemightbemakinganerrorifthesizeofthebachelorswasfouroutofatotalsampleof100grocerybuyersconsidered.Thus,completehonestyandtransparencyinstatingthetreatmentandeditingofmissingorcontrarydataisextremelycritical.Representativeness of study finding: Agoodresearchreportisalsoexplicitin termsof extent and scopeof the resultsobtained, and in termsof theapplicabilityoffindings.Thisisalsodependentonwhethertheassumptionsandpreconditionsmadeforformulatingtheconclusionsandrecommendationsofthestudyhavebeenexplicitlystated.
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Report WritingInordertoensurethatonehasbeenabletoachievetheabovestatedobjective,thereadermustensureastandardizationofproceduresinwritingthedocumentaswellasfollowstandardprotocolsforpreparinggraphsandtables.Inthefollowingsectionwewillbrieflydiscusssomesimplerulesthattheresearchercanuseasguidelinesforthis.
Guidelines for Effective Documentation
Theguidelinesforaneffectivedocumentationmaybediscussedunderthefollowingheads:Command over the medium:Eventhoughonemayhavedoneanextremelyrigorousandsignificantresearchstudy,thefundamentalteststillremainsastohowthelearninghasbeendisseminated.Regardlessofhoweffectivethegraphsandfiguresareinshowcasingthefindings,theverbaldescriptionandexplanation—intermsofwhyitwasdone,howitwasdone,andwhatwastheoutcome,stillremaintheacidtest.
Thus,acorrectandeffectivelanguageofcommunicationiscriticalinputtingideasandobjectivesinthevernacularofthereader/decision-maker.Thewritermay,thus,beadvisedtoreadprofessionallywrittenreportsand,ifnecessary,seekassistancefromthoseproficientinpreparingbusinessreports.Phrasing protocol: Thereisadebateaboutwhetherornotonemakesuseofpersonalpronounwhilereporting.Tounderstandthis,oneneedstorevisittheresponsibilityoftheresearcher,whichistopresentthefindingsofhis/her study,with complete objectivity and precision.The use of personalpronoun such as ‘I think…..’ or ‘inmyopinion…..’ lends a subjectivityandpersonalizationofjudgement.Thus,thetoneofthereportingshouldbeneutral.Forexample:
‘Given the nature of the forecastedgrowth and the opinionof therespondents,itislikelythatthe……’
Whenever thewriter is reproducing theverbatim information fromanother document or comment of an expert or published source, itmustbeininvertedcommasor italicsandtheauthororsourceshouldbedulyacknowledged.Forexample:
SarahChurchman,HeadofDiversity,PricewaterhouseCoopers,states ‘At PricewaterhouseCoopers we firmly believe that promoting work–life balance is a ‘business-critical’ issue and not simply the ‘right thing to do’. Profitable growth and sustainable business depends on attracting and retaining top talent and we know, from our own research and experience that work–life policies are an essential ingredient of successful recruitment and retention strategies.’
Thewritershouldavoidlongsentencesandbreakuptheinformationinclearchunks,sothatthereadercanprocessitwithease.Similaristhecaseinstructuringofthechaptersorsectionsofthereportthatcanbelogically
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brokendownintosmallersectionsthatarecomprehensiveandcompleteandyetmaintainastrongbutlogicallinkwiththeflowofreporting.
WiththeonsetoftheuseofabbreviatedcommunicationsinSMSandemails,mostpeopletendtouseshortenedformas‘cd.’forcouldand‘u’foryou,etc.Alsotheuseofcolloquiallanguageandslangsmustbeavoided,asthisisaformaldocumentandonemustmaintainthesanctityoftheformaldocumentationrequiredinaresearchreport.Simplicity of approach:Alongwithgrammaticallyandstructurallycorrectlanguage,caremustbetakentoavoidtechnicaljargonasfaraspossible.Thebusinessmanager,mighthavebeenabusinessstudentwhohadpreparedaresearchreportinhisacademicpursuitsbutnowunderstandssimplecommontermsanddoesnothavethetimeorinclinationtojugglethedictionaryandthereporttogether.Incaseitisimperativetousecertainterminology,then,asstatedearlier,thedefinitionofthesetermscanbeprovidedintheglossaryoftermsattheendofthereport.
Sometimesthewritermaypreparedifferentresearchreportsforthesamestudytosuittheneedofdiversereaders,forexample,thebusinessreportneedstobecrispandsimplewithdefinableandworkablerecommendations.Ontheotherhand,anacademicreportcoulddiscussextensivelytheliteraturereviewsection,aswellasthestatisticalanalysisandinterpretation.Report formatting and presentation:Intermsofpaperquality,pagemarginsandfontstyleandsize,aprofessionalstandardshouldbemaintained.Thefont stylemust be uniform throughout the report.The topics, subtopics,headingsandsubheadingsmustbeconstruedinthesamemannerthroughoutthe report. Sometimes certain academic reports have amandated formatforpresentationwhichthewritersneedtofollow,inwhichcasethereisnochoiceinpresentation.
However,whenthisisnotclear,itisadvisablethatthewritercreateshis/herownformattingrulesandsavesitonanotepadsothattheycanbeimplementedinastandardizedandprofessionalmanner.
The researcher canprovidedata relief andvariationby adequatelysupplementingthetextwithgraphsandfigures.Pictorialrepresentationsaresimpletocomprehendandalsobreakthemonotonyandfatigueofreading.Theyshouldbeusedeffectivelywheneverpossibleinthereport.
14.5.1 Principles of a Good Report Writing
Basedon the abovedescription, itmaybe concluded that reportwritingshouldbebasedonthefollowingprinciples: • Principle of purpose:A reportmust have a clear andmeaningful
purposethatcanbeconvertedintoaneffectivemanagement.Aclearstatementofpurposehelpsprepareawell-focussedreportonwhichthemanagementcanwork.Specificationofpurposeisimportantbecause:
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Report Writingo Reportsareanalysesoffactsandproposals.o Theyarerecordsofparticularbusinessactivities.
• Principles of organization:Awrittenreportshouldbewell-designedandwell-ordered.Themanagerialplanofareportmustincludethefollowing:o Purposeofthereporto Informationrequiredtobeincludedinthereporto Methodusedtocollectreportdatao Summaryofthereporto Problemsandsolutionsofthesubjectmentionedinthereporto Anappendixthatdescribesandconfirmsthecontentandconclusion
ofthereport • Principles of brevity:Reportsshouldbeconcise.Itisessentialbecause
longreports:o Are costly.o Aredifficulttoexamine.o Arepronetodisapproval,astheyseeminsufficient.o Focusonirrelevantminordetailsthatmayleadtotheignoranceof
majorpoints. • Principles of clarity:Reportsshouldbeclear.Claritycanbemaintained
byusingsimplelanguageforwritingthereport.Newterms,ifanyinthereport,shouldbeproperlyexplainedtoavoidconfusion.
• Principle of scheduling:Reportsshouldbepreparedatthattimewhenthereisnoundueburdenonthestafforwhenthestaffhassufficienttimetopreparereports.However,thetimeperiodbetweenthegatheringofdataandgeneratingfinishedreportsshouldnotbelong;otherwise,thereportmaybecomeoutdatedanduselessifitisnotcompletedintime.
• Principle of cost:Whilepreparingreports,itisnecessarythattheircost–benefitanalysisshouldbedone.Areportshouldbeminimumatcostsandmaximumatbenefits.Ifthecostofpreparationofthereportishighbutitsbenefitislow,thenitisnotadvisabletopreparethatreport.
14.5.2 Features of a Good Research Report
Research reportsmustbeabsolutelyefficientandwell formattedand thematter should be clear, analytical anddirective.The actual facts need tobeexplainedclearly.Dataandresultsshouldbefurnishedingraphicalortabularformatasitwouldcreateasubstantiallygoodimpressionandwouldbeunambiguoustounderstand.
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Thecharacteristicfeaturesofagoodresearchmaybelistedasfollows:• Informationcollectedinthereportshouldberelevantandfocused
to derive desired results. • Thereportshouldstrictlyadheretopredefinedgoalsandobjectives.• Thereportshouldprovidethedescriptionofthequestionnairesused
inanalysisandthemeansadoptedintheirpreparation.• Thereportshouldelaboratethemethodologyusedintheinterviews.• Theremustbeanexecutivesummaryoftheworkinthereport.• Thereportshouldnotonlypresenttheactualanalysisbutalsothe
reasonsofmakingthisreport.Itshouldalsohighlighttheadvantagesandprofititcanprovideaftersuccessfulimplementationofbusinessplansdescribedinsidethereport.
• Itshouldalsomentionthemethodologyoftheresearchpresentingtheoverallprocessadoptedtocreatethereport.
• Thereportneedstobeflexibleenoughsothatitmaybechangedaccordingtorequirements.
14.5.3 Criteria for Evaluating Research Reports/Findings
Researchreports/findingsareevaluatedonthebasisoffollowingcriteria: • Clarity: Thereportshouldbeclearintermsofrepresentationofdata.
Itshouldbeeasytounderstand. • Statement of objective: Theobjectiveofthereportshouldbestated
inthebeginningofareport.Whileevaluating,itisimportanttocheckwhethertheresearchachievedthestatedobjective.
• Relevance of data: Thedataofthereportshouldberelevanttotheresearchtopic.Inaddition,itisimportanttocheckwhethertherecentdatawasusedinreport.
• Analysis of data: Thedatashouldbeproperlyanalyzed.Thus, theevaluatorcheckswhetherallthefindingsaresupportedbyanalysis.
• Unbiased: The report should not be biased towards a particularinterpretationbecausebiasnessaffectsthecompleteprocessofresearch.
14.6 RESEARCH REPORT: LANGUAGE FLOW AND GRAMMATICAL QUALITY
Areportmusthaveaclearandlogicalstructurewithclearindicationofwheretheideasareleading.Itshouldbeabletomakeagoodfirstimpression.Thepresentationofthereportisveryimportant.Allreportsmustbewritteninagoodlanguage,usingshortsentencesandcorrectgrammarandspellings.Themainpointstobekeptinmindinthislightareasfollows:
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Report Writing •Contextandstyle:o Appropriate,informativetitleforthereporto Crisp,specific,unbiasedwritingwithminimaljargono Adequateanalysisofpriorrelevantresearch
•Questions/hypotheses:o Clearlystatedquestionsorhypotheseso Thoroughoperationaldefinitionsofkeyconceptsalongwiththe
exactwordingormeasurementofthekeyvariables •Researchprocedures:
o Fullandcleardescriptionoftheresearchdesigno Demographicprofileoftheparticipants/subjectso Specificdatagatheringprocedures
•Dataanalysis:o Appropriateinferentialstatisticsforsampleorexperimentaldata
andappropriateuseofdescriptivestatisticso Clear and reasonable interpretation of the statistical findings,
accompaniedbyeffectivetablesandfigures •Summary:
o Fairassessmentoftheimplicationsandlimitationsofthefindingso Effectivecommentaryontheoverallimplicationsofthefindings
fortheoryand/orpolicy
14.6.1 Clarity and Brevity of Expressions
Thereisafamoussayingthat‘wordsarelikemirrorthatreflectthepersonalityofthepersonfromwhosemouththeycomeout’.Thus,ifaresearchwantstoabsorbtheattentionofthereader,thenitmusthaveclarityinitsexpressionasthiswillalsotellalotabouttheclarityoftheresearcher’sthought.Expertsemphasizetheimportanceofusingasfewwordsaspossibletodeliveryourmessage.However,sometimesmessagesthatareverybriefsacrificeclarityandleaveoutvitalinformation.Thus,whilecraftinghisreport,theresearchershouldchooseclarityoverbrevity,andincludeallrelevantinformationandbesureitislogicallyorganized.
Three rules for bringing clarity in reports
Inbusinesswriting,yougetpointsforclarity,notstyle.Insteadoftryingtowaxpoeticaboutyourdivision’splansforthenext60days,justmakeyourpoint.Herearethreewaystodothat:
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(i) Limit one idea to one paragraph:Theresearchershouldlimithisthoughtstooneperparagraph.Whenhehasanothersuggestion,thoughtoridea,heshouldstartanewparagraph.
(ii) Make it scannable:Thereportshouldbesopreparedthataudienceisablequicklyscantheresearcher’smessageandunderstandhispoint.
(iii) Put your point in the first sentence.Theresearchershouldnotenticehisreaderswithbackgroundinformationandbuild-up.Heshouldmakehisprimarypointfirst.Thenheshouldgointosupportingdetail.
14.6.2 References and Annotations
Severalreporttypeslikescientific,engineering,technicalandcensusreportscontain eitheroriginalwritingor text adopted fromapreviouswork.Assuch,areportwritershouldbecarefulandshouldavoidanyviolationofcopyrightlawsandplagiarism.Thenecessaryruleofthumbinthisregardcanbestatedasfollows: • Citations and referencing:
o A citationistheacknowledgementinyourwritingoftheworkofotherauthorsandincludesparaphrasingandmakingdirectquotes.
o Unlesscitationisverynecessary,youshouldwritethematerialinyourownwords.Thisshowsthatyouunderstandwhatyouhavereadandknowhowtoapplyit,toyourowncontext.
o Directquotesshouldbeusedsparingly. • Direct quotes:
o Short direct quotes:Theseneedtobeplacedbetweenquotationmarks.Forexample,Rosenfielddefinesaclusterasa‘geographicallybounded concentration of similar, related or complementarybusinesses, with active channels for business transactions,communicationsanddialoguethatsharespecializedinfrastructure,commonopportunities and threats.’This shows clearly that thewordsbeingusedarenotyourownwords.
o Long direct quotes:Thereareoccasionswhenitisusefultoincludelongdirectquotes.Ifyouarequotingmorethanfortywords,youshould again use quotationmarks but also indent the text. Forexample:
Thesustainabilityofhighervalue-addedindustryisgroundedinthediminishing significanceof cost structures.At the level of theEuropeanUnion,aweakcapacitytoinnovatehasbeenidentifiedasaninnovation,inthesenseofproduct,processandorganizationalinnovation,accountsforaverylargeamount,perhaps80–90percentofthegrowthinproductivityinadvancedeconomies.
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Report Writing14.7 DATA SUPPORT AND DIAGRAMMATIC
ELUCIDATION
Thevisualrepresentationofthefindingsintheformoflinesorboxesandbarsrelativetoanumberlineiseasytocomprehendandinterpret.Therearesomestandardrulesandproceduresavailabletotheresearcherforthis;alsotherearecomputerprogramslikeMSExcelandSPSS,wherethenumbereddatacanbeconvertedwitheaseintographicalform.Line and curve graphs:Usually,whentheobjectiveistodemonstratetrendsandsomesortofpatterninthedata,alinechartisthebestoptionavailabletotheresearcherasthelineisabletoclearlyportrayanychangeinpatternduringaparticulartimeperiod.Onthesamechart,itisalsopossibletoshowpatternsofgrowthofdifferentsectorsorindustriesinthesametimeperiodortocomparethechangeinthestudiedvariableacrossdifferentorganizationsor brands in the same industry.Certain points to be kept inmindwhileformulatinglinechartsinclude: •Thetimeunitsorthecausalvariablebeingstudiedaretobeputonthe
X-axis,orthehorizontalaxis. • Iftheintentionistocomparedifferentseriesonthesamechart,the
linesshouldbeofdifferentcoloursorforms(Figure14.2). •Toomanylinesarenotadvisableonthesamechartasthenthedata
becomestoocluttered;anidealnumberwouldbefiveorlessthanfivelinesonthechart.
Fig. 14.2 Comparative Analysis of Vehicles (including Nano) on Features Desired by Consumers
Source: vytrak.com
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•Theresearcheralsomusttakecaretoformulatethezerobaselineinthechartasother-wise, thedatawouldseemtobemisleading.Forexample,inFigure14.3(a),incasethezerobaselineis(asshowninthechart)theexpectedchangeinthenumberofhearingaidsunitstobesoldoverthetimeperiod2002–03to2007–08,itcanbeaccuratelyperceived.However,inFigure14.3(b),wherethezeroisat1,50,000units,therateofgrowthcanbemisjudgedtobemoreswift.
Fig. 14.3(a) Expected Growth in the Number of Hearing Aids Units to be sold in North India (Three Perspectives)
Fig. 14.3(b) Expected Growth in the Number of Hearing Aids Units to be sold in North India (Three Perspectives)
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Report WritingArea or stratum charts:Areachartsarelikethelinecharts,usuallyusedtodemonstratechangesinapatternoveraperiodoftime.However,heretherearemultiplelinesthatareessentiallycomponentsoftheoriginalcompositedata.Whatisdoneisthatthechangeineachofthecomponentsisindividuallyshownonthesamechartandeachofthemisstackedoneontopoftheother.Theareasbetweenthevariouslinesindicatethescaleorvolumeoftherelevantfactors/categories(Figure14.4).
Fig. 14.4 Perception of Nano by Three Psychographic Segments of Two-wheeler Owners
Pie charts:Anotherwayofdemonstratingtheareaorstratumorsectionalrepresentationisthroughthepiecharts. Thecriticaldifferencebetweenalineandpiechartisthatthepiechartcannotshowchangesovertime.Itsimplyshowsthecross-sectionofasingletimeperiod. Thesectionsorslicesofthepieindicatetheratioofthatsectiontothetotalareaoftheparameterbeingdisplayed.Therearecertainrulesthattheresearchershouldkeepinmindwhilecreatingpiecharts. •Thecompletedatamustbeshownasa100percentareaofthesubject
beinggraphed. • It isagoodideatohavethepercentagesdisplayedwithinorabove
thepieratherthaninthelegendasthenitiseasiertounderstandthemagnitude of the section in comparison to the total. For example,Figure14.5showsthebrand-wisesalesinunitsfortheexistingbrandsofhearingaidsintheNorthIndianmarket.
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Fig. 14.5 Brandwise Sales (units) of Hearing aids in the North India Market (2002–03)
• Showingchangesovertimeisdifficultthroughapiechart,asstatedearlier.However,thechangeinthecomponentsatdifferenttimeperiodscouldbedemonstratedas inFigure14.6, showing shareof thecarmarketinIndiain2009andtheexpectedmarketcompositionof2015.
Fig. 14.6 Current Structure of the Indian car Market (2009) and the Forecasted Structure for 2015
Bar charts and histograms: Averyusefulrepresentationofquantumormagnitudeofdifferentobjectsonthesameparameterarebardiagrams.Thecomparativepositionofobjectsbecomesveryclear.Theusualpracticeistoformulateverticalbars;however,itispossibletousehorizontalbarsaswellifnoneofthevariableistimerelated[Figure14.7(a)].Horizontalbarsareespeciallyusefulwhenoneisshowingbothpositiveandnegativepatternsonthesamegraph[Figure14.7(b)].Thesearecalledbilateralbarchartsandareespeciallyusefultohighlighttheobjectsorsectorsshowingavariedpattern
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Report Writingonthestudiedparameter.Itispossibletogeneratebargraphswithrelativeeasewithcomputerprogramstodayandthedistancebetweenthebarscanbeextremelypreciseascomparedtothosecreatedbyhand.
Fig. 14.7(a) Bar Chart per Day, Unit Sales (Thousands) at Fast Food Outlets in Mumbai
Fig. 14.7(b) Bilateral Bar Chart—the Brand Recall and Brand Purchase Response for Pizza Joints in the NCR
Anothervariationofthebarchartisthehistogram(Figure14.8)herethebarsareverticalandtheheightofeachbarreflectstherelativeorcumulativefrequencyofthatparticularvariable.
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Fig. 14.8 Histogram (with Normal Curve) Displaying Marks in a Course on Research Methods for Management
Pictogram:Apictogramshowsgraphicalrepresentationofdata.Pictogramsaremostoftenusedinpopularandgeneralreadsuchasinmagazinesandnewspapers,astheyareeye-catchingandeasytocomprehendbyoneandall.Theyarenotaveryaccurateorscientificrepresentationoftheactualdataand,thus,shouldbeusedwithcautioninanacademicortechnicalreport.Geographic representation: Geographic or regionalmaps related tocountries,states,districts,territoriescanbeusedasabasetoshowoccurrenceofthestudiedvariableinvariousregionsortoshowcomparativeanalysisaboutmajorbrandsorindustriesorminerals.Incaseofcomparativedata,theresearchermustprovidethelegendinthedisplayedmap.
Check Your Progress
5.Whydoesareportneedaclearstatementofpurpose? 6.Whenshouldlinechartsbeused? 7.Whatisthedifferencebetweenalineandpiechart? 8.Whatisapictogram?
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Report Writing14.8 ANSWERS TO CHECK YOUR PROGRESS
QUESTIONS
1.Researchreportscanbecategorizedonthefollowingbases:• Onthebasisofsize• Onthebasisofinformation• Onthebasisofrepresentation
2.A popular report is formulatedwhen there is a need to draw theconclusionsof thefindingsof theresearchreport.Oneof themainconsiderationstobekeptinmindwhileformulatingaresearchreportisthatitmustbesimpleandattractive.
3.Theusualstepsinvolvedinwritingaresearchreportareasfollows:• Logicalanalysisofthesubject-matter• Preparationofthefinaloutline• Preparationoftheroughdraft• Rewritingandpolishing• Preparationofthefinalbibliography• Writingthefinaldraft
4.Theletteroftransmittalistheletterthatgoesalongsidetheformalizedcopyof thefinalreport. Itbroadlyrefers to thepurposebehindthestudy.Thetoneinthisnotecanbeslightlyinformalandindicativeoftherapportbetweentheclient-readerandtheresearcher.
5. Areportmusthaveaclearandmeaningfulpurposethatcanbeconvertedinto an effectivemanagement.A clear statement of purpose helpsprepareawell-focussedreportonwhichthemanagementcanwork.
6.Whentheobjectiveistodemonstratetrendsandsomesortofpatterninthedata,alinechartisthebestoptionavailabletotheresearcherasthelineisabletoclearlyportrayanychangeinpatternduringaparticulartime period.
7. Thecriticaldifferencebetweenalineandpiechartisthatthepiechartcannotshowchangesovertime.Itsimplyshowsthecross-sectionofasingletimeperiod.
8. Apictogramshowsgraphicalrepresentationofdata.Pictogramsaremostoftenusedinpopularandgeneralreadsuchasinmagazinesandnewspapers,astheyareeye-catchingandeasytocomprehendbyoneandall.
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14.9 SUMMARY
•Oncearesearchprojectreachesitsconclusion,themostimportanttaskaheadoftheresearcheristodocumenttheentireworkdoneintheformofawell-structuredresearchreport.
•Therearebriefreportswhich,asthenamesuggests,areofashorterlengthandcouldbe in the formofworkingpapersorshortsurveyreports.Thesemightbeexpandedwhilepreparingthedetailedreport.
•Thedetailed reportmayvary in scope and style dependingon therequirementofthereaderforwhomitistobecreated.Thesecouldbeintheformofhighlystructuredandcomprehensivetechnicalreportsorsimpleraction-orientedbusinessreports.
•Nomatterwhattheorientationis,reportsgenerallyfollowastandardizedstructure.Theentirereportcanbedividedintothreemainsections—thepreliminarysection,themainbodyandendnotes.
•Thepreliminarysectiontypicallyincludesthetitlepage,thetableofcontentsandtheletterofauthorizationandtheletteroftransmittal.Themostsignificantsectionofthispartisashortbutsuccinctexecutivesummary,whichsummarizesthemainreport.
•Themainreportincludesthebackgroundofthestudy,aswellasthescope,frameworkandthemethodologyofthestudy,includingthedatacollectionandsamplingplan.Thesectionculminates into themostimportantpartofthereport,thestudyfindingsandinterpretationoftheseresults.
•The last sectionof the report includes thebibliographyandall thesupportivedocumentslikemeasuringinstrument(questionnaire),thesampledetailsandanyrelevantdocumentthatneedstobereferredtocomprehendthereport.
•Anywelldocumentedreportmustbeclearandexplicitinitsreporting.Theremust be no ambiguity in either presenting the findings orrepresentativeness of the findings.The designed reportmust beformulated, keeping the reader and the researcher’s capabilities inmind.
•The authormust followawidelymandated and followedprotocolforreportingandreferencinginthereport.Thereportingneedstobeobjectiveandsimpleratherthancomplexandopinionated.
•Theresearcherattimesmightneedtoverballypresenttheresearchstudy.Thesepresentationsessionsneedtobebriefandcrisp,withthethrustbeingmoreonthemethodologyandfindings.
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Report Writing •Communicatingandpresentingtheresearchresultsisbothaskillandanartandtherichnessoftheresearchfindingsneedstobeappropriatelysharedwith the interested listeners inamannerbest suited to theirindividualneeds.
14.7 KEY WORDS
• Technical Reports:Thesearemajordocumentsandwouldincludeall elements of the basic report, aswell as the interpretations andconclusions,asrelatedtotheobtainedresults.
• Business Reports: Thesereportsincludeconclusionsasunderstoodbythebusinessmanager.
• Letter of Transmittal:This is the letter that goes alongside theformalizedcopyof thefinalreport.Itbroadlyrefers tothepurposebehindthestudy.
• Bibliography:Thisisanimportantpartofthefinalsectionasitprovidesthecompletedetailsoftheinformationsourcesandpaperscitedinastandardizedformat.
• Footnote:Atypicalfootnote,asthenameindicates,ispartofthemainreportandcomesatthebottomofapageorattheendofthemaintext.
• Citation:Itistheacknowledgementinyourwritingoftheworkofotherauthorsandincludesparaphrasingandmakingdirectquotes.
14.8 SELF ASSESSMENT QUESTIONS AND EXERCISES
Short Answer Questions
1.Whatarethedifferentbasesofclassifyingresearchreports? 2.Statethevariousprinciplesonwhichagoodresearchreportisbased. 3. Identifythevariouscriteriaofevaluatingresearchreports/findings. 4.What are the rules for presenting references and annotations in a
researchreport? 5.Whatisgeographicrepresentation?
Long Answer Questions
1.Discussindetailthestepsthataresearcherneedstofollowtoformulateagoodresearchreport.Dothecriteriabecomedifferentfordifferentkindsofreports?Explainwithexamples.
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2.Whatshouldbetheidealstructureofaresearchreport?Whataretheelementsofthestructuredefinedbyyou?
3.Whatare theguidelinesforeffectivereportwriting?Illustratewithsuitableexamples.
4. ‘Visualrepresentationsofresultsarebestunderstoodbyareader,thusspecialcaremustbetakenforthisformulation.’Examinethetruthofthisstatementbygivingsuitableexamples.
5.Whataretheguidelinesaresearchermustfollowforgraphicalandtabularrepresentationoftheresearchresults?Discuss.
14.9 FURTHER READINGS
Creswell,JohnW.2002.Research Design: Qualitative, Quantitative, and Mixed Methods Approaches.London:SagePublicationsInc.
Booth,Wayne,GregoryG.ColombandJosephM.Williams.1995.The Craft of Research.Chicago:UniversityofChicagoPress.
Bryman,AlanandEmmaBell.2015.Business Research Methods.4thEdition.UnitedKingdom:OxfordUniversityPress.
Gupta,S.L.andHiteshGupta. 2012. Business Research Methods. NewDelhi: TataMcGrawHillEducationPrivateLimited.
Master of Business Administration317 21
RESEARCH METHODSII - Semester
You are instructed to update the cover page as mentioned below:
1. Increase the font size of the Course Name.
2. use the following as a header in the Cover Page.
ALAGAPPA UNIVERSITY [Accredited with ’A+’ Grade by NAAC (CGPA:3.64) in the Third Cycle
and Graded as Category–I University by MHRD-UGC]
KARAIKUDI – 630 003 DIRECTORATE OF DISTANCE EDUCATION
You are instructed to update the cover page as mentioned below:
1. Increase the font size of the Course Name.
2. use the following as a header in the Cover Page.
ALAGAPPA UNIVERSITY [Accredited with ’A+’ Grade by NAAC (CGPA:3.64) in the Third Cycle
and Graded as Category–I University by MHRD-UGC]
KARAIKUDI – 630 003 DIRECTORATE OF DISTANCE EDUCATION
Master of Business Administration317 21
RESEARCH METHODSII - Semester
You are instructed to update the cover page as mentioned below:
1. Increase the font size of the Course Name.
2. use the following as a header in the Cover Page.
ALAGAPPA UNIVERSITY [Accredited with ’A+’ Grade by NAAC (CGPA:3.64) in the Third Cycle
and Graded as Category–I University by MHRD-UGC]
KARAIKUDI – 630 003 DIRECTORATE OF DISTANCE EDUCATION
You are instructed to update the cover page as mentioned below:
1. Increase the font size of the Course Name.
2. use the following as a header in the Cover Page.
ALAGAPPA UNIVERSITY [Accredited with ’A+’ Grade by NAAC (CGPA:3.64) in the Third Cycle
and Graded as Category–I University by MHRD-UGC]
KARAIKUDI – 630 003 DIRECTORATE OF DISTANCE EDUCATION
RESEA
RC
H M
ETHO
DS
Master of Business Adm
inistration