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1. a. Differentiate between nominal, ordinal, interval and ratio

scales, with an example of each.

Measurement may be classified into four different levels, based on the

characteristics of order, distance and origin.

1. Nominal measurement

This level of measurement consists in assigning numerals or symbols to

different categories of a variable. The example of male and female applicants

to an MBA program mentioned earlier is an example of nominal measurement.

The numerals or symbols are just labels and have no quantitative value. The

numbers of cases under each category are counted. Nominal measurement is

therefore the simplest level of measurement. It does not have characteristicssuch as order, distance or arithmetic origin.

2. Ordinal measurement

In this level of measurement, persons or objects are assigned numerals which

indicate ranks with respect to one or more properties, either in ascending or

descending order.

Example

Individuals may be ranked according to their socio-economic class, which is

measured by a combination of income, education, occupation and wealth. The

individual with the highest score might be assigned rank 1, the next highest

rank 2, and so on, or vice versa.

The numbers in this level of measurement indicate only rank order and not

equal distance or absolute quantities. This means that the distance between

ranks 1 and 2 is not necessarily equal to the distance between ranks 2 and 3.

Ordinal scales may be constructed using rank order, rating and pairedcomparisons. Variables that lend themselves to ordinal measurement include

preferences, ratings of organizations and economic status. Statistical

techniques that are commonly used to analyze ordinal scale data are the

median and rank order correlation coefficients.

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3. Interval measurement

This level of measurement is more powerful than the nominal and ordinal levels

of measurement, since it has one additional characteristic equality of

distance. However, it does not have an origin or a true zero. This implies that it

is not possible to multiply or divide the numbers on an interval scale.

Example

The Centigrade or Fahrenheit temperature gauge is an example of the interval

level of measurement. A temperature of 50 degrees is exactly 10 degrees

hotter than 40 degrees and 10 degrees cooler than 60 degrees.

Since interval scales are more powerful than nominal or ordinal scales, they

also lend themselves to more powerful statistical techniques, such as standard

deviation, product moment correlation and t tests and F tests ofsignificance.

4. Ratio measurement

This is the highest level of measurement and is appropriate when measuring

characteristics which have an absolute zero point. This level of measurement

has all the three characteristics order, distance and origin.

Examples

Height, weight, distance and area.

Since there is a natural zero, it is possible to multiply and divide the numbers

on a ratio scale. Apart from being able to use all the statistical techniques that

are used with the nominal, ordinal and interval scales, techniques like the

geometric mean and coefficient of variation may also be used.

The main limitation of ratio measurement is that it cannot be used for

characteristics such as leadership quality, happiness, satisfaction and other

properties which do not have natural zero points.

The different levels of measurement and their characteristics may be summed

up.

In the table below

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Levels of measurement Characteristics

Nominal No order, distance or origin

Ordinal Order, but no distance or origin

Interval Both order and distance, but no origin

Ratio Order, distance and origin

1. b. What are the purposes of measurement in social science

research?

Measurement has several purposes

The researcher constructs theories to explain social and psychological

phenomena (e.g. labor unrest, employee satisfaction), which in turn are used to

derive hypotheses or assumptions. These hypotheses can be verified

statistically only by measuring the variables in the hypotheses.

Measurement makes the empirical description of social and psychological

phenomena easier.

Example When conducting a study of a tribal community, measuring devices

help the researcher in classifying cultural patterns and behaviors.

Measurement also makes it possible to quantify variables and use statistical

techniques to analyze the data gathered.

Measurement enables the researcher to classify individuals or objects and to

compare them in terms of specific properties or characteristics by measuring

the concerned variables.

Examples

Comparison of male and female students performance in college exams or of

length of stay on the job of older and younger employees.

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2. a. What are the sources from which one may be able to

identify research problems?

The selection of one appropriate researchable problem out of the identified

problems requires evaluation of those alternatives against certain criteria,

which may be grouped into:

A. Internal Source

1) Researchers interest: The problem should interest the researcher and be

a challenge to him. Without interest and curiosity, he may not develop

sustained perseverance. Even a small difficulty may become an excuse fordiscontinuing the study. Interest in a problem depends upon the

researchers educational background, experience, outlook and sensitivity.

2) Researchers competence: A mere interest in a problem will not do. The

researcher must be competent to plan and carry out a study of the problem.

He must have the ability to grasp and deal with int. he must possess

adequate knowledge of the subject-matter, relevant methodology and

statistical procedures.

3) Researchers own resource: In the case of a research to be done by a

researcher on his won, consideration of his own financial resource is pertinent.

If it is beyond his means, he will not be able to complete the work, unless he

gets some external financial support. Time resource is more important than

finance. Research is a time-consuming process; hence it should be properly

utilized.

B. External Source

1) Research-ability of the problem: The problem should be researchable,

i.e., amendable for finding answers to the questions involved in it through

scientific method. To be researchable a question must be one for which

observation or other data collection in the real world can provide the

answer.

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2) Importance and urgency: Problems requiring investigation are unlimited,

but available research efforts are very much limited. Therefore, in selecting

problems for research, their relative importance and significance should be

considered. An important and urgent problem should be given priority over

an unimportant one.

3) Novelty of the problem: The problem must have novelty. There is no use

of wasting ones time and energy on a problem already studied thoroughly

by others. This does not mean that replication is always needless. In social

sciences in some cases, it is appropriate to replicate (repeat) a study in

order to verify the validity of its findings to a different situation.

4) Feasibility: A problem may be a new one and also important, but if

research on it is not feasible, it cannot be selected. Hence feasibility is a

very important consideration.

5) Facilities: Research requires certain facilities such as well-equipped library

facility, suitable and competent guidance, data analysis facility, etc. Hence the

availability of the facilities relevant to the problem must be considered.

6) Usefulness and social relevance: Above all, the study of the problem

should make significant contribution to the concerned body of knowledge or to

the solution of some significant practical problem. It should be socially relevant.

This consideration is particularly important in the case of higher level academic

research and sponsored research.

7) Research personnel: Research undertaken by professors and by research

organizations require the services of investigators and research officers. But in

India and other developing countries, research has not yet become aprospective profession. Hence talent persons are not attracted to research

projects.

Each identified problem must be evaluated in terms of the above internal and

external criteria and the most appropriate one may be selected by a research

scholar.

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2. b. Why literature survey is important in research?

Frequently, an exploratory study is concerned with an area of subject matter in

which explicit hypothesis have not yet been formulated. The researchers taskthen is to review the available material with an eye on the possibilities of

developing hypothesis from it. In some areas of the subject matter, hypothesis

may have been stated by previous research workers. The researcher has to

take stock of these various hypotheses with a view to evaluating their

usefulness for further research and to consider whether they suggest any new

hypothesis. Sociological journals, economic reviews, the bulletin of abstracts of

current social sciences research, directory of doctoral dissertation accepted by

universities etc afford a rich store of valuable clues. In addition to these

general sources, some governmental agencies and voluntary organizations

publish listings of summaries of research in their special fields of service.

Professional organizations, research groups and voluntary organizations are a

constant source of information about unpublished works in their special fields.

3. a. What are the characteristics of a good research design?

Characteristics of a Good Research Design

1. It is a series of guide posts to keep one going in the right direction.

2. It reduces wastage of time and cost.

3. It encourages co-ordination and effective organization.

4. It is a tentative plan which undergoes modifications, as circumstances

demand, when the study progresses, new aspects, new conditions and new

relationships come to light and insight into the study deepens.

5. It has to be geared to the availability of data and the cooperation of the

informants.

6. It has also to be kept within the manageable limits

3. b. What are the components of a research design?

Components of Research Design

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Dependent and Independent variables: A magnitude that varies is known

as a variable. The concept may assume different quantitative values, like

height, weight, income, etc. Qualitative variables are not quantifiable in the

strictest sense of objectivity. However, the qualitative phenomena may also be

quantified in terms of the presence or absence of the attribute considered.

Phenomena that assume different values quantitatively even in decimal pointsare known as continuous variables. But, all variables need not be continuous.

Values that can be expressed only in integer values are called non-continuous

variables. In statistical term, they are also known as discrete variable. For

example, age is a continuous variable; where as the number of children is a

non-continuous variable. When changes in one variable depends upon the

changes in one or more other variables, it is known as a dependent or

endogenous variable, and the variables that cause the changes in the

dependent variable are known as the independent or explanatory or exogenous

variables. For example, if demand depends upon price, then demand is a

dependent variable, while price is the independent variable.

And if, more variables determine demand, like income and prices of substitute

commodity, then demand also depends upon them in addition to the own price.

Then, demand is a dependent variable which is determined by the independent

variables like own price, income and price of substitute.

1. Extraneous variable: The independent variables which are not directlyrelated to the purpose of the study but affect the dependent variable are

known as extraneous variables. For instance, assume that a researcher wantsto test the hypothesis that there is relationship between childrens schoolperformance and their self-concepts, in which case the latter is an independentvariable and the former, the dependent variable. In this context, intelligencemay also influence the school performance. However, since it is not directlyrelated to the purpose of the study undertaken by the researcher, it would beknown as an extraneous variable. The influence caused by the extraneousvariable on the dependent variable is technically called as an experimentalerror . Therefore, a research study should always be framed in such a manner that the dependent variable completely influences the change in theindependent variable and any other extraneous variable or variables.

2. Control: One of the most important features of a good research design is tominimize the effect of extraneous variable. Technically, the term control isused when a researcher designs the study in such a manner that it minimizesthe effects of extraneous independent variables. The term control is used inexperimental research to reflect the restrain in experimental conditions.

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3. Confounded relationship: The relationship between dependent andindependent variables is said to be confounded by an extraneous variable,when the dependent variable is not free from its effects.

Research hypothesis: When a prediction or a hypothesized relationship

is tested by adopting scientific methods, it is known as research hypothesis.

The research hypothesis is a predictive statement which relates a

dependent variable and an independent variable. Generally, a research

hypothesis must consist of at least one dependent variable and one

independent variable. Whereas, the relationships that are assumed but not

be tested are predictive statements that are not to be objectively verified

are not classified as research hypothesis.

Experimental and control groups: When a group is exposed to usual

conditions in an experimental hypothesis-testing research, it is known as

control group . On the other hand, when the group is exposed to certain

new or special condition, it is known as an experimental group . In the

afore-mentioned example, the Group A can be called a control group and

the Group B an experimental one. If both the groups A and B are exposed to

some special feature, then both the groups may be called as experimental

groups . A research design may include only the experimental group or the

both experimental and control groups together.

Treatments: Treatments are referred to the different conditions to which

the experimental and control groups are subject to. In the example

considered, the two treatments are the parents with regular earnings and

those with no regular earnings. Likewise, if a research study attempts to

examine through an experiment regarding the comparative impacts of

three different types of fertilizers on the yield of rice crop, then the three

types of fertilizers would be treated as the three treatments.

Experiment: An experiment refers to the process of verifying the truth of a

statistical hypothesis relating to a given research problem. For instance,

experiment may be conducted to examine the yield of a certain new variety

of rice crop developed. Further, Experiments may be categorized into two

types namely, absolute experiment and comparative experiment. If a

researcher wishes to determine the impact of a chemical fertilizer on the

yield of a particular variety of rice crop, then it is known as absolute

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experiment. Meanwhile, if the researcher wishes to determine the impact of

chemical fertilizer as compared to the impact of bio-fertilizer, then the

experiment is known as a comparative experiment.

Experiment unit: Experimental units refer to the predetermined plots,

characteristics or the blocks, to which the different treatments are applied.

It is worth mentioning here that such experimental units must be selected

with great caution.

4. a. Distinguish between Doubles sampling and multiphase

sampling.

Double Sampling and Multiphase Sampling

Double sampling refers to the subsection of the final sample form a pre-selected larger sample that provided information for improving the final

selection. When the procedure is extended to more than two phases of

selection, it is then, called multi-phase sampling. This is also known as

sequential sampling, as sub-sampling is done from a main sample in phases.

Double sampling or multiphase sampling is a compromise solution for a

dilemma posed by undesirable extremes. The statistics based on the sample

of n can be improved by using ancillary information from a wide base: but this

is too costly to obtain from the entire population of N elements. Instead,

information is obtained from a larger preliminary sample nL which includes the

final sample n. extraneous Double sampling refers to the subsection of the finalsample form a pre-selected larger sample that provided information for

improving the final selection. When the procedure is extended to more than

two phases of selection, it is then, called multi-phase sampling. This is also

known as sequential sampling, as sub-sampling is done from a main sample in

phases. Double sampling or multiphase sampling is a compromise solution for a

dilemma posed by undesirable extremes. The statistics based on the sample

of n can be improved by using ancillary information from a wide base: but this

is too costly to obtain from the entire population of N elements. Instead,

information is obtained from a larger preliminary sample nL which includes the

final sample n.

4. b. What is replicated or interpenetrating sampling?

Replicated or Interpenetrating Sampling

It involves selection of a certain number of sub-samples rather than one full

sample from a population. All the sub-samples should be drawn using the same

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sampling technique and each is a self-contained and adequate sample of the

population. Replicated sampling can be used with any basic sampling

technique: simple or stratified, single or multi-stage or single or multiphase

sampling. It provides a simple means of calculating the sampling error. It is

practical. The replicated samples can throw light on variable non-sampling

errors. But disadvantage is that it limits the amount of stratification that can beemployed.

5. a. How is secondary data useful to researcher?

Use of Secondary Data

The second data may be used in three ways by a researcher. First, some

specific information from secondary sources may be used for reference

purpose. For example, the general statistical information in the number of co-

operative credit societies in the country, their coverage of villages, their capitalstructure, volume of business etc., may be taken from published reports and

quoted as background information in a study on the evaluation of performance

of cooperative credit societies in a selected district/state.

Second, secondary data may be used as bench marks against which the

findings of research may be tested, e.g., the findings of a local or regional

survey may be compared with the national averages; the performance

indicators of a particular bank may be tested against the corresponding

indicators of the banking industry as a whole; and so on.

Finally, secondary data may be used as the sole source of information for a

research project. Such studies as securities Market Behaviour, Financial

Analysis of companies, Trade in credit allocation in commercial banks,

sociological studies on crimes, historical studies, and the like, depend primarily

on secondary data. Year books, statistical reports of government departments,

report of public organizations of Bureau of Public Enterprises, Censes Reports

etc, serve as major data sources for such research studies.

Advantages of Secondary Data

Secondary sources have some advantages:

1. Secondary data, if available can be secured quickly and cheaply. Once their

source of documents and reports are located, collection of data is just matter of

desk work. Even the tediousness of copying the data from the source can now

be avoided, thanks to Xeroxing facilities.

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2. Wider geographical area and longer reference period may be covered

without much cost. Thus, the use of secondary data extends the researchers

space and time reach.

3. The use of secondary data broadens the data base from which scientific

generalizations can be made.

4. Environmental and cultural settings are required for the study.

5. The use of secondary data enables a researcher to verify the findings bases

on primary data. It readily meets the need for additional empirical support. The

researcher need not wait the time when additional primary data can be

collected.

Disadvantages of Secondary Data

The use of a secondary data has its own limitations.

1. The most important limitation is the available data may not meet our specific

needs. The definitions adopted by those who collected those data may be

different; units of measure may not match; and time periods may also be

different.

2. The available data may not be as accurate as desired. To assess their

accuracy we need to know how the data were collected.

3. The secondary data are not up-to-date and become obsolete when they

appear in print, because of time lag in producing them. For example,

population census data are published tow or three years later after compilation,

and no new figures will be available for another ten years.

4. Finally, information about the whereabouts of sources may not be available

to all social scientists. Even if the location of the source is known, the

accessibility depends primarily on proximity. For example, most of the

unpublished official records and compilations are located in the capital city,

and they are not within the easy reach of researchers based in far off places.

5. b. What are the criteria used for evaluation of secondary data?

Evaluation of Secondary Data

When a researcher wants to use secondary data for his research, he should

evaluate them before deciding to use them.

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1. Data Pertinence

The first consideration in evaluation is to examine the pertinence of the

available secondary data to the research problem under study. The following

questions should be considered.

What are the definitions and classifications employed? Are they

consistent ?

What are the measurements of variables used? What is the degree to which

they conform to the requirements of our research?

What is the coverage of the secondary data in terms of topic and time?

Does this coverage fit the needs of our research?

On the basis of above consideration, the pertinence of the secondary data to

the research on hand should be determined, as a researcher who is imaginative

and flexible may be able to redefine his research problem so as to make use of

otherwise unusable available data.

2. Data Quality

If the researcher is convinced about the available secondary data for his needs,

the next step is to examine the quality of the data. The quality of data refers to

their accuracy, reliability and completeness. The assurance and reliability of

the available secondary data depends on the organization which collected

them and the purpose for which they were collected. What is the authority and

prestige of the organization? Is it well recognized? Is it noted for reliability? It is

capable of collecting reliable data? Does it use trained and well qualifiedinvestigators? The answers to these questions determine the degree of

confidence we can have in the data and their accuracy. It is important to go to

the original source of the secondary data rather than to use an immediate

source which has quoted from the original. Then only, the researcher can

review the cautionary ands other comments that were made in the original

source.

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3. Data Completeness

The completeness refers to the actual coverage of the published data. This

depends on the methodology and sampling design adopted by the original

organization. Is the methodology sound? Is the sample size small or large? Is

the sampling method appropriate? Answers to these questions may indicate

the appropriateness and adequacy of the data for the problem under study.

The question of possible bias should also be examined. Whether the purpose

for which the original organization collected the data had a particular

orientation? Has the study been made to promote the organizations own

interest? How the study was conducted? These are important clues. The

researcher must be on guard when the source does not report the methodology

and sampling design. Then it is not possible to determine the adequacy of the

secondary data for the researchers study.

6. What are the differences between observation andinterviewing as methods of data collection? Give two specificexamples of situations where either observation or interviewingwould be more appropriate.

Observation vs. interviewing as Methods of Data Collection

Collection of data is the most crucial part of any research project as the

success or failure of the project is dependent upon the accuracy of the data.

Use of wrong methods of data collection or any inaccuracy in collecting data

can have significant impact on the results of a study and may lead to results

that are not valid. There are many techniques of data collection along a

continuum and observation and interviewing are two of the popular methods

on this continuum that has quantitative methods at one end while qualitative

methods at the other end. Though there are many similarities in these two

methods and they serve the same basic purpose, there are differences that will

be highlighted in this article.

Observation

Observation, as the name implies refers to situations where participants are

observed from a safe distance and their activities are recorded minutely. It is a

time consuming method of data collection as you may not get the desired

conditions that are required for your research and you may have to wait till

participants are in the situation you want them to be in. Classic examples of

observation are wild life researchers who wait for the animals ofbirds to be in a

natural habitat and behave in situations that they want to focus upon. As a

method of data collection, observation has limitations but produces accurate

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results as participants are unaware of being closely inspected and behave

naturally.

Interviewing

Interviewing is another great technique of data collection and it involves asking

questions to get direct answers. These interviews could be either one to one, in

the form of questionnaires, or the more recent form of asking opinions through

internet. However, there are limitations of interviewing as participants may not

come up with true or honest answers depending upon privacy level of the

questions. Though they try to be honest, there is an element of lie in answers

that can distort results of the project.

Though both observation and interviewing are great techniques of datacollection, they have their own strengths and weaknesses. It is important to

keep in mind which one of the two will produce desired results before finalizing.

Interview format:

Interviews take many different forms. It is a good idea to ask the organisation

in advance what format the interview will take.

Competency/criteria based interviews:

These are structured to reflect the competencies or qualities that an employer

is seeking for a particular job, which will usually have been detailed in the job

specification or advert. The interviewer is looking for evidence of your skills and

may ask such things as: Give an example of a time you worked as part of a

team to achieve a common goal.

Technical interviews:

If you have applied for a job or course that requires technical knowledge, it is

likely that you will be asked technical questions or has a separate technical

interview. Questions may focus on your final year project or on real

or hypothetical technical problems. You should be prepared to prove yourself,

but also to admit to what you do not know and stress that you are keen to

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learn. Do not worry if you do not know the exact answer - interviewers are

interested in your thought process and logic.

The Screening Interview:

Companies use screening tools to ensure that candidates meet minimum

qualification requirements. Computer programs are among the tools used to

weed out unqualified candidates. (This is why you need a digital resume that is

screening-friendly. See our resume centre for help.) Sometimes human

professionals are the gatekeepers. Screening interviewers often have honed

skills to determine whether there is anything that might disqualify you for the

position. Remember they do not need to know whether you are the best fit for

the position, only whether you are not a match. For this reason, screeners tend

to dig for dirt. Screeners will hone in on gaps in your employment history orpieces of information that look inconsistent. They also will want to know from

the outset whether you will be too expensive for the company.

The Informational Interview:

On the opposite end of the stress spectrum from screening interviews is the

informational interview. A meeting that you initiate, the informational interview

is underutilized by job-seekers who might otherwise consider themselves savvy

to the merits of networking. Jobseekers ostensibly secure informationalmeetings in order to seek the advice of someone in their current or desired

field as well as to gain further references to people who can lend insight.

Employers that like to stay apprised of available talent even when they do not

have current job openings, are often open to informational interviews,

especially if they like to share their knowledge, feel flattered by your interest,

or esteem the mutual friend that connected you to them. During an

informational interview, the jobseeker and employer exchange information and

get to know one another better without reference to specific job opening.

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