mb0034 research me the do logy final

8/14/2019 MB0034 Research Me the Do Logy Final

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ASSIGNMENTS

MB 0034

RESEARCH METHODOLOGY

(3 credits)

Set I

Q.1. Explain the different types of research.

Ans. Although any typology of research is inevitability arbitrary. Research

may be classified crudely according to its major intent or the methods.

According to the intent, research may be classified as:

Pure Research :- It is undertaken for the sake of knowledge without anyintention to apply it in practice. It is also known as basic or fundamental

research. It is undertaken out of intellectual curiously or inquisitiveness. It is

not necessarily problem-oriented.

Applied Research :- It is carried on to find solution to a real life problem

requiring an action or policy decision. It is thus problem and action-directed.

It seeds an immediate and practical result. E.g. marketing research carried on

for developing a news market or for studying the post-purchase experience

of customers. Though the immediate purpose of an applied research is to

find solution to a practical problem. it may incidentally contribute to the

development of theoretical knowledge by leading to the discovery of new

facts or testing of theory or a conceptual clarity.

Exploratory Research :- It is also known as formulative research. It is

preliminary study of an unfamiliar problem about which the researcher has

or no knowledge. It is ill-structured and much less focused on pre-

determined objectives. It usually takes the form of a pilot study. The purpose

of this research may be to generate new ideas, or to increase the researchers

familiarity with the problem or to make a precise formulation of the problem


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or to gather information for clarifying concepts or to determine whether it is

feasible to attempt the study.

Descriptive study :- It is a fact-finding investigation with adequate

interpretation. It is simplest type of research. It is more specific than an

exploratory research. It aims at identifying the various characteristics of a

community or institution or problem under study and also aims at a

classification of the range of elements comprising the subject matter of

study.

Diagnostic Study :- It is similar to descriptive study but with a different

focus. It is directed towards discovering what is happening. Why it is

happening and what can be done about. It aims at identifying the causes of aproblem and the possible solutions for it. It may also be concerned with

discovering and testing whether certain variables are associated. This type of

research requires prior knowledge of the problems.

Evaluation study :- Its a type of applied research. It is made for assessing

the effectiveness of social or economic program implementated or for

assessing the impact of development project on the development of the

project area, it is thus directed to assess or appraises the quality or the

quantity of an activity an its performance, and to specify its attribute and

condition required for its success. It is concerned with casual relationship

and is more activity guided by hypotheses it is concern also with change

over time.

Action Research :- It is a type of evaluation study. It is a concurrent

evaluation study of an action programmed launched for solving a problem

for improving an existing situation. It includes six major steps : diagnosis,

sharing of diagnostic information, planning, developing change

programmed, initiation of organization change, implementation of

participation and communication process, and post experimental evaluation.


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Q.2.Discuss the criteria of good research problem.

Ans. A good research problem must support multiple perspectives.

The problem most be phrased in a way that avoids dichotomies and instead

supports the generation and exploration of multiple perspectives. A general

rule of thumb is that a good problem is one that would generate a variety of

viewpoints from a composite audience made up of reasonable people.

A good research problem must be researchable. It seems a bit obvious,

but more than one instructor has found her or himself in the midst of a

complex collaborative research project and realized that students don't havemuch to draw on for research, nor opportunities to conduct sufficient

primary research. Choose research problems that can be supported by the

resources available to your students.

Umbrella topics must be sufficiently complex. If you are using an

umbrella topic for a large class of students who will be working on related,

more manageable problems in their learning teams, make sure that there is

sufficient complexity in the research problems that the umbrella topic

includes. These research topics must relate strongly to one another in such a

way that there will be a strong sense of coherence in the overall class effort.


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Q.3. Describe the procedure used to test the hypothesis

Ans. Hypothesis Testing :-

The basic logic of hypothesis testing is to prove or disprovethe research question. By only allowing an error of 5% or 1% and makingcorrect decisions based on statistical principles, the researcher can conclude

that the result must be real if chance alone could produce the same result only5% of the time or less. These five steps consist of all the decisions aresearcher needs to make in order to answer any research question using aninferential statistical test.


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1. STATING THE RESEARCH QUESTION.

The first step is to state the research problem in terms of a question thatidentifies the population(s) of interest to the researcher, the parameter(s) ofthe variable under investigation, and the hypothesized value of the

parameter(s). This step makes the researcher not only define what is to be

tested but what variable will be used in sample data collection. The type ofvariable (or combination of variables as in relationship type researchquestions) whether categorical, discrete or continuous further defines thestatistical test which can be performed on the collected data set.

For example:Is the mean first salary of a newly graduated student equal to $30,000?

The population of interest is all students who have just graduated. Theparameter of interest is the mean and the variable salary is continuous. The

hypothesized value of the parameter, the mean, is $30,000. Since theparameter is a population mean of a continuous variable variable, thissuggests a one sample test of a mean.


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2. SPECIFY THE NULL AND ALTERNATIVE HYPOTHESES.

The second step is to state the research question in terms of a null hypothesis(H0) and an alternative hypothesis (HA). The null hypothesis is the

population parameter, = $30,000 (H0: = $30,000). The alternativehypothesis is the population parameter does not equal $30,000 ( HA: NE

$30,000). This HA suggests a two-tailed test as NE $30,000 can be less than$30,000 or more than $30,000. Sometimes the alternative hypothesis isstated in terms of a direction such as less than or greater than a value such at$30,000. A directional HA calls for a one-tailed test, in the direction stated inthe HA.

The next part of step 2 is to select a significance level typically alpha is usedat the .05 or the .01 level. A good researcher will also not neglect Type IIerror. In this step we are not only setting up our research question in terms ofstatistical hypotheses, but we must evaluate whether all the assumptionsappropriate for the statistical test have been met.

Example:H0: = $30,000HA: NE $30,000 alpha=.05

Test assumptions are 1) the population is normally distributed or sample sizeis approximately >=30 and 2) the sample we have used to collect the datawas drawn randomly from the population. If these test assumptions have not

been meeting, then data collection should be reevaluated or continued undercaution.


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3. CALCULATE TEST STATISTIC.

The third step is to calculate a statistic analogous to the parameter specifiedby the null hypothesis. If the null hypothesis is defined by the parameter ,then the statistics computed on our data set would be the mean (xbar) and thestandard deviation (s). A histogram of our sample data set gives us our best

approximation of what we expect our population distribution to look like.

Since the best estimate of is xbar, our sample mean, the test statistic isbased on a distribution of sample means, the sampling distribution of themean, xbar, with n, sample size, equal to the number of data values used tocompute xbar. We have hypothesized from the research question the mean ofthis distribution and want to see if our sample mean is close to this value. Todetermine where our sample mean fits on this sampling distribution, weconvert our sample mean, xbar, to a z-score. Thus the test statistic would be :

z = xbar- (hypothesized)standard error of xbar

The standard error of xbar (point estimate) is s, the sample standarddeviation, divided by square root of n, the sample size since the populationstandard deviation is unknown.

Example:Suppose we randomly sampled 100 high school seniors and determined their

salary of their first job. The sample mean salary, xbar, was $29,000 with astandard deviation of $6,000. Since sample size is >30, we don't have toworry about whether the population is normally distributed (Central LimitTheorem). The test statistic would be:

z = $29,000 - $30,000 = -$1,000 = -1.667$6,000/sqrt(100) $600


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4. COMPUTE PROBABILITY OF TEST STATISTIC OR

REJECTION REGION.

The fourth step is to calculate the probability value (often called thep-value)which is the probability of the test statistic for both tails since this this two-tailed test. The probability value computed in this step is compared with the

significance level selected in step 2. If the probability is less than or equal tothe significance level, then the null hypothesis is rejected. If the probabilityis greater than the significance level then the null hypothesis is not rejected.When the null hypothesis is rejected, the outcome is said to be "statisticallysignificant"; when the null hypothesis is not rejected then the outcome is said

be "not statistically significant." If the outcome is statistically significant,then the null hypothesis is rejected in favor of the alternative hypothesis.

Example:

P(z> 1.667) =.048 + P(z< -1.667)=.048, the p-value is .048+.048=.096

Since this value is greater than alpha=.05 selected when we set up outhypotheses, we accept the null hypothesis, H0: = $30,000.

If we wish to use a rejection region of alpha=.05 (.025 in each tail) todetermine if we accept or reject the null hypothesis, the cut-off z-score would

be -1.96 and 1.96. If our test statistic is >=1.96 or


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5. STATE CONCLUSIONS.

The fifth and final step is to describe the results and state correct statisticalconclusions in an understandable way. The conclusions consist of twostatments-one describing the results of the null hypothesis and the otherdescribing the results of the alternative hypothesis. The first statement should

state as to whether we accepted or rejected the null hypothesis and for whatvalue of alpha or p-value for our test statistic. The second statement shouldanswer the research question proposed in step 1 stating the sample statisticcollected which estimated the parameter we hypothesized.

Example:

Accept the null hypothesis at alpha=.05 or p-value of .096. Based on asample mean of $25,000, the mean salary of a newly graduated student doesnot equal $30,000.

Q.4.Write a note on experimental design

Ans. Design of experiments, orexperimental design, (DoE) is the design

of all information-gathering exercises where variation is present, whether

under the full control of the experimenter or not. (The latter situation is

usually called an observational study.) Often the experimenter is interested

in the effect of some process or intervention (the "treatment") on someobjects (the "experimental units"), which may be people, parts of people,

groups of people, plants, animals, etc. Design of experiments is thus a

discipline that has very broad application across all the natural and social

sciences.

Principles of experimental design, following Ronald A. Fisher

A methodology for designing experiments was proposed by Ronald A.Fisher, in his innovative bookThe Design of Experiments (1935). As anexample, he described how to test the hypothesis that a certain lady coulddistinguish by flavor alone whether the milk or the tea was first placed in thecup. While this sounds like a frivolous application, it allowed him toillustrate the most important ideas of experimental design:
http://en.wikipedia.org/wiki/Observational_studyhttp://en.wikipedia.org/wiki/Ronald_Fisherhttp://en.wikipedia.org/wiki/Ronald_Fisherhttp://en.wikipedia.org/wiki/The_Design_of_Experimentshttp://en.wikipedia.org/wiki/Hypothesishttp://en.wikipedia.org/wiki/Observational_studyhttp://en.wikipedia.org/wiki/Ronald_Fisherhttp://en.wikipedia.org/wiki/Ronald_Fisherhttp://en.wikipedia.org/wiki/The_Design_of_Experimentshttp://en.wikipedia.org/wiki/Hypothesis


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Comparison

In many fields of study it is hard to reproduce measured resultsexactly. Comparisons between treatments are much more reproducibleand are usually preferable. Often one compares against a standard ortraditional treatment that acts as baseline.

Randomization

There is an extensive body of mathematical theory that explores theconsequences of making the allocation of units to treatments by meansof some random mechanism such as tables of random numbers, or theuse of randomization devices such as playing cards or dice. Providedthe sample size is adequate, the risks associated with randomallocation (such as failing to obtain a representative sample in asurvey, or having a serious imbalance in a key characteristic betweena treatment group and a control group) are calculable and hence can

be managed down to an acceptable level. Random does notmean

haphazard, and great care must be taken that appropriate randommethods are used.Replication

Measurements are usually subject to variation, both between repeatedmeasurements and between replicated items or processes. Multiplemeasurements of replicated items are necessary so the variation can beestimated.

Blocking

Blocking is the arrangement of experimental units into groups(blocks) that are similar to one another. Blocking reduces known but

irrelevant sources of variation between units and thus allows greaterprecision in the estimation of the source of variation under study.

Orthogonality

Orthogonality concerns the forms of comparison (contrasts) that canbe legitimately and efficiently carried out. Contrasts can berepresented by vectors and sets of orthogonal contrasts areuncorrelated and independently distributed if the data are normal.Because of this independence, each orthogonal treatment providesdifferent information to the others. If there are Ttreatments and T 1

orthogonal contrast, all the information that can be captured from theexperiment is obtainable from the set of contrasts.Factorial experiments

Use of factorial experiments instead of the one-factor-at-a-timemethod. These are efficient at evaluating the effects and possibleinteractions of several factors (independent variables).
http://en.wikipedia.org/wiki/Randomizationhttp://en.wikipedia.org/wiki/Replication_(statistics)http://en.wikipedia.org/wiki/Blocking_(statistics)http://en.wikipedia.org/wiki/Orthogonalityhttp://en.wikipedia.org/wiki/Factorial_experimenthttp://en.wikipedia.org/wiki/Randomizationhttp://en.wikipedia.org/wiki/Replication_(statistics)http://en.wikipedia.org/wiki/Blocking_(statistics)http://en.wikipedia.org/wiki/Orthogonalityhttp://en.wikipedia.org/wiki/Factorial_experiment


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Analysis of the design ofexperiments was built on the foundation of theanalysis of variance, a collection of models in which the observed varianceis partitioned into components due to different factors which are estimatedand/or tested.

Q.5.Elaborate the ways of making a case study effective.

Ans. John Dollard has proposed seven criteria for evaluating such adequacy as follows:

i) The subject must be viewed as a specimen in a cultural series. That is, the case drawn out from itstotal context for the purposes of study must be considered a member of the particular cultural group orcommunity. The scrutiny of the life histories of persons must be done with a view to identify thecommunity values, standards and their shared way of life.

ii) The organic motto of action must be socially relevant. That is, the action of the individual casesmust be viewed as a series of reactions to social stimuli or situation. In other words, the socialmeaning of behavior must be taken into consideration.

iii) The strategic role of the family group in transmitting the culture must be recognized. That is, incase of an individual being the member of a family, the role of family in shaping his behavior mustnever be overlooked.

iv) The specific method of elaboration of organic material onto social behavior must be clearly shown.That is case histories that portray in detail how basically a biological organism, the man, gradually

blossoms forth into a social person, are especially fruitful.

v) The continuous related character of experience for childhood through adulthood must be stressed.In other words, the life history must be a configuration depicting the inter-relationships between the

person's various experiences.

vi) Social situation must be carefully and continuously specified as a factor. One of the importantcriteria for the life history is that a person's

life must be shown as unfolding itself in the context of and partly owing to specific socialsituations. vii) The 'life history material itself must be organized according to some conceptualframework, this in turn would facilitate generalizations at a higher level.

Q.6.What is non probability sampling? Explain its types with examples.

This article needs additional citations for verification.

Please help improve this article by adding reliable references. Unisourcematerial may be challenged and removed. (October 2009)

Sampling is the use of a subset of thepopulation to represent the wholepopulation. Probability sampling, orrandom sampling, is a samplingtechnique in which theprobability of getting any particular sample may becalculated. Nonprobability sampling does not meet this criterion and
http://en.wikipedia.org/wiki/Experimenthttp://en.wikipedia.org/wiki/Analysis_of_variancehttp://en.wikipedia.org/wiki/Wikipedia:Citing_sources#Inline_citationshttp://en.wikipedia.org/wiki/Wikipedia:Verifiabilityhttp://en.wikipedia.org/w/index.php?title=Nonprobability_sampling&action=edithttp://en.wikipedia.org/wiki/Wikipedia:Reliable_sourceshttp://en.wikipedia.org/wiki/Template:Facthttp://en.wikipedia.org/wiki/Wikipedia:Verifiability#Burden_of_evidencehttp://en.wikipedia.org/wiki/Sampling_(statistics)http://en.wikipedia.org/wiki/Population_(statistics)http://en.wikipedia.org/wiki/Random_samplinghttp://en.wikipedia.org/wiki/Probabilityhttp://en.wikipedia.org/wiki/Experimenthttp://en.wikipedia.org/wiki/Analysis_of_variancehttp://en.wikipedia.org/wiki/Wikipedia:Citing_sources#Inline_citationshttp://en.wikipedia.org/wiki/Wikipedia:Verifiabilityhttp://en.wikipedia.org/w/index.php?title=Nonprobability_sampling&action=edithttp://en.wikipedia.org/wiki/Wikipedia:Reliable_sourceshttp://en.wikipedia.org/wiki/Template:Facthttp://en.wikipedia.org/wiki/Wikipedia:Verifiability#Burden_of_evidencehttp://en.wikipedia.org/wiki/Sampling_(statistics)http://en.wikipedia.org/wiki/Population_(statistics)http://en.wikipedia.org/wiki/Random_samplinghttp://en.wikipedia.org/wiki/Probability


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should be used with caution. Nonprobability sampling techniques cannotbeused to infer from the sample to the general population. Any generalizationsobtained from a nonprobability sample must be filtered through one'sknowledge of the topic being studied. Performing nonprobability sampling isconsiderably less expensive than doing probability sampling, but the resultsare of limited value.

Examples of nonprobability sampling include:

Convenience, Haphazard or Accidental sampling - members of thepopulation are chosen based on their relative ease of access. To samplefriends, co-workers, or shoppers at a single mall, are all examples ofconvenience sampling. Convenience sampling generally assumes ahomogeneous population, and that one person is pretty much like another.Whilst people are known to be different, the difference is assumed to be

probabilistic - thus if 80% of a sample prefer coffee to tea, you mightconclude that 80% of the population at large would choose coffee. In

practice, your sample may be mostly middle class Parisians and the sametest in London may well give a different result.

Many famous psychological experiments were done with available people.Most typically, experiments done in universities use students, simply

because they are cheap, willing and available. This has caused significantdebate about the validity of results.

Convenience sampling is also known as Opportunity Sampling,AccidentalSamplingorHaphazard Sampling.

Snowball sampling - The first respondent refers a friend. The friend alsorefers a friend, etc. he 'snowball' effect occurs as referrals multiply at eachstep. For example if you got two referrals from each person, then startingfrom two people get four more, then eight, sixteen and so on.

Snowball sampling uses a method beloved by sales people, where customerreferrals to new prospects have particular value as the relationship of trust

and obligation between the identified person and the referrer makes it morelikely that the new person will make a purchase.

The way that the sample is chosen by target people makes it liable to variousforms of bias. People tend to associate not only with people with the samestudy selection characteristic but also with other characteristics. This
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increases the chance of correlations being found in the study that do notapply to the generalized wider population.

The need to get the person to give you a referral also means that theresearcher has to form a relationship with the person and be nice to them.This can change the study results as affective biases in both the researcher

and the target person change how they think and behave.

With care in selection (you do not have to use every referral) and avoidingpersonal bias, snowball sampling can still be a useful method, particularly ifyou have no other way of reaching the target population.

Snowball sampling is also known as chain sampling, chain-referralsamplingorreferral sampling.

Judgmental sampling orPurposive sampling - The researcher chooses the

sample based on who they think would be appropriate for the study. This isused primarily when there is a limited number of people that have expertisein the area being researched. Purposive sampling starts with a purpose inmind and the sample is thus selected to include people of interest andexclude those who do not suit the purpose.

This method is popular with newspapers and magazines which want to makea particular point. This is also true for marketing researchers who areseeking support for their product. They typically start with people in thestreet, first approaching only 'likely suspects' and then starting withquestions that reject people who do not suit.

Deviant Case-Get cases that substantially differ from the dominantpattern(a special type of purposive sample)

ad hoc quotas - A quota is established (say 65% women) andresearchers are free to choose any respondent they wish as long as thequota is met.

If care is not taken then significant bias can be introduced by quota

sampling. In the example above, the people accessed may change withthe time of day, the day of the week, whether they have an interest incheese and so on.

Even studies intended to be probability studies sometimes end up being non-probability studies due to unintentional or unavoidable characteristics of thesampling method. In public opinion polling by private companies (or other


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organizations unable to require response), the sample can be self-selectedrather than random. This often introduces an important type of error: self-selection error. This error sometimes makes it unlikely that the sample willaccurately represent the broader population. Volunteering for the samplemay be determined by characteristics such as submissiveness or availability.The samples in such surveys should be treated as non-probability samples of

the population, and the validity of the estimates of parameters based on themunknown.
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ASSIGNMENTS

MB 0034

RESEARCH METHODOLOGY

(3 credits)

Set II

Q.1. What are the advantages and disadvantages of secondary data?

Ans. Advantages of secondary data :-

Secondary data is provides a multipurpose bases to researchers.

Secondary data can be used for creating or generating new ideas byproviding a base for some core issues.

Secondary data can be very effectively used for the comparison of twostatistics and then drawing inferences based on these comparisons.

Secondary data is the best method of getting information regarding aparticular area where the direct collection of data is impossible.

Secondary data is the most easily accessible data and saves the researcherthe trouble of going through the tiresome process of collecting data

personally.

Secondary data is readily available at cheap rates and is usually quiteinexpensive.

Collecting secondary data and analyzing it saves time and effort.

Secondary data is unobtrusive. It is easily available and the researcher canget it without much struggle.

Secondary data avoids data collection problems and it provides a basis forcomparison.

Secondary data can be easily located by using printed indices.

It can be less expensive than gathering the data all over again.


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This data type may allow the researcher to cover a wider geographic ortemporal range.

Secondary data can allow for larger scale studies on a small budget.

It does not exhaust people's good will by re-collecting readily available

data.

Secondary data provides an opportunity for longitudinal analysis based onthe previous waves of survey.

Secondary data is a good indicator for analyzing the social changeovertime.

This type of data also provides an opportunity for cross-cultural analysiswith fewer limits of time, cost and language.

Collecting secondary data leaves more time for making in depth dataanalysis.

Re-analysis of the same secondary data may offer different insightsregarding the analysis by focusing on one variable or subgroup.

With secondary data the researchers might be able to test hypotheses theyhad not thought of, or examine the strengths of their arguments.

Secondary data may be available which is entirely appropriate and whollyadequate to draw conclusions and answer the question or solve the problem.Sometimes primary data collection simply is not necessary.

It is far cheaper to collect secondary data than to obtain primary data. Forthe same level of research budget a thorough examination of secondarysources can yield a great deal more information than can be had through a

primary data collection exercise.

When the researcher has collected the secondary data, there is no need to

repeat the field work necessary for the collection of data.

The time involved in searching secondary sources is much less than thatneeded to complete primary data collection.

Secondary sources of information can yield more accurate data than thatobtained through primary research. This is not always true but where a


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government or international agency has undertaken a large scale survey, oreven a census, this is likely to yield far more accurate results than customdesigned and executed surveys when these are based on relatively smallsample sizes.

It should not be forgotten that secondary data can play a substantial role in

the exploratory phase of the research when the task at hand is to define theresearch problem and to generate hypotheses. The assembly and analysis ofsecondary data almost invariably improves the researcher's understanding ofthe marketing problem, the various lines of inquiry that could or should befollowed and the alternative courses of action which might be pursued.

Often the secondary data provides valuable background for the research -for example, it enables users to judge whether a small sample they havegathered is typical of the national population.

Government survey organizations have considerable expertise andrelatively massive resources, including the power to compel participation(e.g. in census-taking), so samples are more likely to be of large size andtruly representative of the population.

Secondary sources help define the population. Secondary data can beextremely useful both in defining the population and in structuring thesample to be taken. For instance, government statistics on a country'sagriculture will help decide how to stratify a sample and, once sample

estimates have been calculated, these can be used to project those estimatesto the population.

Disadvantages of secondary Data :-

a. Difficult or costly access

b. Unsuitable aggregations and definitions

c. Does not meet the purpose of study

d. No real control over data quality

Quality of Researcher As we will discuss, research conducted usingprimary methods are largely controlled by the marketer. However, thisis not the case when it comes to data collected by others.Consequently, the quality of secondary research should be scrutinized


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closely since the origins of the information may be questionable.Organizations relying on secondary data as an important componentin their decision-making (e.g., market research studies) must takeextra steps to evaluate the validity and reliability of the information bycritically evaluating how the information was gathered, analyzed and

presented. Not Specific to Researchers Needs Secondary data is often not

presented in a form that exactly meets the marketers needs. Forexample, a marketer obtains an expensive research report that looks athow different age groups feel about certain products within themarketers industry. Unfortunately, the marketer may be disappointedto discover that the way the research divides age groups (e.g., under13, 14-18, 19-25, etc.) does not match how the marketers companydesignates its age groups (e.g., under 16, 17-21, 22-30, etc). Becauseof this difference the results may not be useful.

Inefficient Spending for Information Since the research receivedmay not be specific to the marketers needs, an argument can be madethat research spending is inefficient. That is, the marketer may notreceive a satisfactory amount of information for what is spent.

Incomplete Information Many times a researcher finds that researchthat appears promising is in fact a teaser released by the researchsupplier. This often occurs when a small portion of a study isdisclosed, often for free, but the full report, which is often expensive,is needed to gain the full value of the study.

Not Timely Caution must be exercised in relying on secondary data

that may have been collected well in the past. Out-of-date informationmay offer little value especially for companies competing in fastchanging markets.

Not Proprietary Information In most cases secondary research is notundertaken specifically for one company. Instead it is made availableto many either for free or for a fee. Consequently, there is rarely aninformation advantage gained by those who obtain the research.


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Q.2. Explain the prerequisites and advantages of observation.

Ans. Prerequisites of effective Observation :-

The prerequisites of effective observation consist of :

Observations must be done under conditions which will permit

accurate results. The observer must be in vantage point to see clearly

the objects to be observed. The distance and the light must be

satisfactory. The mechanical devices wised must be in good working

conditions and operated by skilled persons.

Observation must cover a sufficient number of representative samples

of the cases.

Recording should be accurate and complete.

Advantages of observation

Observation has certain advantages :

1. The main virtue of observation is its directness; its makes it possible

to study behavior as it occurs. The researcher need not ask people

about their behavior and interactions: he can simply watch they do

and say

2. Data collected by observations may describe the observed phenomena

as they occur in their natural settings. Other methods introduce

elements or artificially into the researched situation for instance in

interview ; the respondent may not behave in a natural way.

3. Observations is more suitable for studying subjects who are unable to

articulate meaningfully, e.g. studies of children, tribal, animals, birds

etc.

4. Observations improve the opportunities for analyzing the validated

and compared with behavior through observation

5. Observation make it possible to capture the whole event as it occurs.

For examples only observation can provide an insight into all the


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aspects of the process of negotiation between union and management

representatives.

6. It is easier to conduct disguised observation studies and has less

biasing effect on their conduct than questioning.

7. Mechanical devices may be used for recording data in order to secure

more accurate data and also of making continuous observation over

longer periods.

Q.3. Discuss the stages involved in data collection.

Ans.

Q.4. Briefly explain the types of interviews.Ans. The interview can be classified into

a. Structured or directive interview

b. Unstructured or non directive interview

c. Focused interview

d. Clinical interview

e. Depth interview

A. Structured Directive interview :-

This is an interview made with a detailed standardized schedule. The

same questions are put to all the respondent and in the same order.

Each question is asked in the same way in each interview promoting

measurement reliability. This type of interview is used for large scale

formularized surveys.

B. Unstructured or non Directive interview :-

This is the least structured one. The interviewer encourages the

respondent to talk freely about a give topic with a minimum of

prompting or guidance. In this type of interview, a detailed pre-

planned schedule is not used. Only a broad interview guide is used.


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The interviewer avoids channeling the interviewer directions. Instead

he develops a very permissive atmosphere.

This interviewing is more useful in case studies rather than in surveys.

It is particularly useful in exploratory research where the lines of

investigations are not clearly defined. It is also useful for gathering

information on sensitive topics such as divorce, social discrimination,

class conflict, generation gap, drug addiction etc.

C. Focused Interview :-

This is semi-structured interview where the investigator attempt to

focus the discussion on the actual effects of a given experience to

which the respondents have been exposed. It takes place with placewith the respondents known to have involved in a particular

experience. The situation is analyzed prior to the interview. An

interview guide specifying topics relating to the subjective experience

of the respondent.

D. Clinical Interview :-

This is similar to the focused interview but with a subtle difference.

While the focused interview is concerned with the effect of specific

experiment, clinical interview is concerned with broad underlying

feeling or motivations or with the course of the individuals life

experiences.

E. Depth Interview :- This is an intensive and searching interview

aiming are studying the respondents emotions or convictions on the

basis of an interview guide. This requires much more training on

inter-personal skill than structured interview. This deliberately aims to

elicit unconscious as well as extremely personal felling and emotions.

This is generally a lengthy procedure designed to encourage free

expression of affectively charged information. It requires probing. The


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interviewer should totally avoid advising or showing disagreement. Of

course, he should use encouraging like I see to motivate the

respondent to continue narration.

Q.5.Describe the principles involved in the table construction.

Ans. There are certain accepted principles of rules relating to

construction of tables.

1. Every table should not have a title . the title should represent a

succinct description of the content of the table. It should be clear and

concise

2. A number facilitating easy reference should indentify every table. The

number can be centered above the title. The table numbers should runin consecutive serial order, alternatively tables in chapter 1 be

numbered as 1.1 1.2 in chapter 2 as 2.1,2.2 and so on

3. The caption should be clear and brief.

4. the units of measurement under each heading must always be

indicated

5. If the data in series of tables have been obtained from different

sources, it is ordinarily advisable to indicate the specific sources in a

place just below the table.

6. Usually lines separate columns from one another. Lines are always

drawn at the top and bottom of the table and below the captions.

7. The columns may be numbered to facilitate reference.

8. All column figures should be properly aligned. Decimal points and

plus or minus sign should be in perfect alignment.

9. Totals of rows should be placed at the extreme right column and totals

of columns at the bottom

10. In order to emphasize the relative significance of certain categories

different kinds of type, spacing and identification can be used.


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11.The arrangement of the categorized in a table may be chronological,

geographical, alphabetical or according to magnitude.

12. Usually the larger number of items is listed vertically. This means that

a table length is more than its width.

13.Abbreviations should not be avoided whenever possible and ditto

marks should not be used in a table.


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Q.6.. Write a note on contents of research report.

Ans. CONTENTS OF A RESEARCH REPORT

The information in the first part of this section, Journal Articles, Books,Chapters in Books, Peer Reviewed Published Conference Proceedings, Non-

peer Reviewed Published Conference Proceedings is filtered and extracted toformulate the Preliminary Publication Count for the Department ofEducation. This is a crucial step in the subsidy calculation process and it isof the utmost importance that this information must be as comprehensiveaccurate as possible. All research publications, which appeared in 2004,must be included, even if they are "in press". There will be an opportunityearly in February to submit volume and page numbers of papers, which haveappeared in the interim. Publications should be listed using the Harvardreferencing system, without using italics or bold. Journal names must appearin full. Abbreviations will be returned to departments for expansion. (Theses

passed for higher degrees are subsidy earning but this information is notincluded in the Preliminary Publication Count.)

The second part of this section, Published Conference Abstracts, Patents, Theses &

Dissertations passed for Higher Degrees, University Publications & Publications of a

Popular Nature - Unreformed Journal Articles, Newspaper Articles, CD's, Online

Works, Extension and Development Work, Creative Work, Consultancy and Other

Activities based on Expertise Developed in Research (gives departments the

opportunity to demonstrate the extent and nature of their extension anddevelopment work), Motivation for the addition of a South AfricanJournal to the list of South African approved journals. The workincluded here is not subsidy earning but nevertheless is an important aspectof scholarly activity at UCT.

The outline of a research report is given below :-

1. Prefatory items

Title page Declaration

Certificates

Preface/acknowledgement

Table of content


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List of tables

List of graphs

Abstract of synopsis

2. Body of the report

Introduction

Theoretical background of the topic

Statement of the problem

Review of literature

The scope of the study

The objective of the study

Hypothesis to be tested

Definition of the concept

Models If any

Design of the study

Methodology

Method of data collection

Sources of data

Sampling plan

Data collection instrument

Field work

Data processing and analysis plan

Overview of the report Limitation of the study

Results : finding and discussion

Summary, conclusion and recommendation


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3. Reference material

Bibliography

Appendix

Copies of data collection instrument

Technical details on sampling plan

Complex tables glossary of new terms used

mb0034 research me the do logy final

Documents