MBA SEMESTER IIIMB0050 –Research Methodology- 4 Credits

(Book ID:B1206)Assignment Set- 1 )60 Marks(

Q.1 a. Differentiate between nominal, ordinal, interval and ratio scales, with an example of each.

b. What are the purposes of measurement in social science research?

Answer )a(:

Measurement may be classified into four different levels in social research, based on the characteristics of order, distance and origin, each one adding more to the next. Thus ordinal data is also nominal and so on.

1. Nominal measurement:

The name 'Nominal' comes from the Latin nomen, meaning 'name' and nominal data are

items which are differentiated by a simple naming system.

This level of measurement consists in assigning numerals or symbols to different

categories of a variable. The only thing a nominal scale does is to say that items being

measured have something in common, although this may not be described.

For example; a survey is conducted to study the applicants for Driving License and one

of the objective of the study is to fine out the sex-wise break-up of applicants. In this

case, we may assign the number “0” to male applicant and number “1” to female

applicants. Thus number may be used to label individuals, events or things.

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 characteristics such as order, distance or

arithmetic origin.

A categorical variable, also called a nominal variable, is for mutual exclusive, but not ordered, categories. For example, a study might compare five different genotypes. We can code the five genotypes with numbers if we want, but the order is arbitrary and any calculations (for example, computing an average) would be meaningless.

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 paired comparisons.

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.

It is one where the order matters but not the difference between values.

For example, you might ask patients to express the amount of pain they are feeling on a

scale of 1 to 10. A score of 7 means more pain that a score of 5, and that is more than a

score of 3. But the difference between the 7 and the 5 may not be the same as that

between 5 and 3. The values simply express an order. Another example would be movie

ratings, from --- to ----.

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.

A interval variable is a measurement where the difference between two values is

meaningful. The difference between a temperature of 100 degrees and 90 degrees is the

same difference as between 90 degrees and 80 degrees.

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 of significance.

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 –

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

A ratio variable, has all the properties of an interval variable, and also has a clear

definition of 0.0. When the variable equals 0.0, there is none of that variable. Variables

like height, weight, enzyme activity are ratio variables.

Another counter example is pH. It is not a ratio variable, as pH=0 just means 1 molar of

H+. and the definition of molar is fairly arbitrary. A pH of 0.0 does not mean 'no acidity'

(quite the opposite!). When working with ratio variables, but not interval variables, you

can look at the ratio of two measurements. A weight of 4 grams is twice a weight of 2

grams, because weight is a ratio variable. A temperature of 100 degrees C is not twice as

hot as 50 degrees C, because temperature C is not a ratio variable. A pH of 3 is not twice

as acidic as a pH of 6, because pH is not a ratio variable.

Different definitions of measurement have been offered by different authors–

1. According to Stevens, measurement is “the assignment of numerals to objects or

events according to rules.”

A simple example of assignment of numerals according to a rule is described below:

Suppose a survey is conducted to study the applicants of an MBA program and one of the

objectives of the study is to find out the sex-wise break-up of applicants. In this case, we

may assign the number “0” to male applicants and the number “1” to female applicants.

Thus numbers may be used to label individuals, events or things.

2. Campbell defines measurement as “the assignment of numbers to represent

properties.”

3. In the words of Torgerson, measurement is “the assignment of numbers to objects to

represent amounts or degrees of a property possessed by all of the objects.

In research, it is necessary to distinguish between “objects” and “properties’ or

characteristics of these objects. For example, a person is an object and his/her physical

characteristics include height, weight, color, etc. while his or her psychological

characteristics include intelligence and attitudes. The important point to remember is that

the researcher is concerned with measuring properties and not the objects themselves.

While physical properties may be directly observed, psychological properties such as

intelligence are inferred. For example, a child’s score in an IQ test indicates his or her

level of intelligence.

b. Purposes of measurement in social science research:

Measurement also has several purposes :

One of the primary purposes of classifying variables according to their level or scale of

measurement is to facilitate the choice of a statistical test used to analyze the data. There

are certain statistical analyses which are only meaningful for data which are measured at

certain measurement scales. For example, it is generally inappropriate to compute the

mean for Nominal variables. Suppose you had 20 subjects, 12 of which were male, and 8

of which were female. If you assigned males a value of '1' and females a value of '2',

could you compute the mean sex of subjects in your sample? It is possible to compute a

mean value, but how meaningful would that be? How would you interpret a mean sex of

1.4? When you are examining a Nominal variable such as sex, it is more appropriate to

compute a statistic such as a percentage (60% of the sample was male).

When a research wishes to examine the relationship or association between two variables,

there are also guidelines concerning which statistical tests are appropriate.

For example, let's say a University administrator was interested in the relationship

between student gender (a Nominal variable) and major field of study (another Nominal

variable). In this case, the most appropriate measure of association between gender and

major would be a Chi-Square test. Let's say our University administrator was interested

in the relationship between undergraduate major and starting salary of students' first job

after graduation. In this case, salary is not a Nominal variable; it is a ratio level variable.

The appropriate test of association between undergraduate major and salary would be a

one-way Analysis of Variance (ANOVA), to see if the mean starting salary is related to

undergraduate major.

Finally, suppose we were interested in the relationship between undergraduate grade

point average and starting salary. In this case, both grade point average and starting salary

are ratio level variables. Now, neither Chi-square nor ANOVA would be appropriate;

instead, we would look at the relationship between these two variables using the Pearson

correlation coefficient

Further;

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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Q.2. a. What are the sources from which one may be able to identify research problems?

b. Why literature survey is important in research?

Answer )a(:

R. L. Ackoffs analysis affords considerable guidance in identifying problem for research.

He visualizes five components of a problem.

1) Research-consumer: There must be an individual or a group which experiences some

difficulty.

2) Research-consumer’s Objectives: The research-consumer must have available,

alternative means for achieving the objectives he desires.

3) Alternative Means to Meet the Objectives: The research-consumer must have

available, alternative means for achieving the objectives he desires.

4) Doubt in Regard to Selection of Alternatives: The existence of alternative courses of

action in not enough; in order to experience a problem, the research consumer must have

some doubt as to which alternative to select.

5) There must be One or More Environments to which the Difficulty or Problem Pertains:

A change in environment may produce or remove a problem. A research-consumer may

have doubts as to which will be the most efficient means in one environment but would

have no such doubt in another.

Identifying research Problem :

This involves the identification of a general topic and formulating it into a specific

research problem. It requires thorough understanding of the problem and rephrasing it in

meaningful terms from an analytical point of view.

The sources from which one may be able to identify research problems or develop problems awareness are:

• Review of literature

• Academic experience

• Daily experience

• Exposure to field situations

• Consultations

• Brain storming

• Research

• Intuition

Review of Literature:

Review of literature is a systematic process that requires careful and perceptive reading and attention to detail. In the review of the literature, the researcher attempts to determine what others have learned about similar research problems. It is important in the following ways:

specifically limiting and identifying the research problem and possible hypothesis or research questions i.e. sharpening the focus of the research.

informing the researcher of what has already been done in the area. This helps to avoid exact duplication.

“If one had the literature and exercised enough patience and industry in reviewing

available literature, it may well be that his problem has already been solved by someone

somewhere some time ago and he will save himself the trouble.” Nwana (1982).

Providing insights into possible research designs and methods of conducting the research and interpreting the results.

Providing suggestions for possible modifications in the research to avoid unanticipated difficulties.

The library can be an ideal physical location for the research literature. The availability

and access to books, periodicals, technical reports and academic theses facilitate the

researcher. Other sources are the Education Index and the Educational Resources

information centre (ERIC). Computer-assisted searchers of literature have become very

common today with advantage of comprehensiveness and speed. They are cost-effective

in terms of time and effort and sometimes access to some of the databases requires

payment. Irrespective of the sources of the literature, ethics of research require that the

source is acknowledged through a clear system of referencing.

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

explicit hypothesis have not yet been formulated. The researcher’s task is to review the

available material checking the possibilities of developing hypothesis from it. In some

areas of the subject matter, hypothesis may have already been stated by previous research

workers. In such cases, 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.

Further, there are four main possible sources of research opportunities: private

laboratories, universities, hospitals, and government research agencies.

When looking for research opportunities, look at the

international research community. The best way to get involved is to participate

in research reviews. Many journals and publications actively solicit submission

reviewers. As part of this role, you can gain a unique perspective on the research being

completed and the key team members.

Some more ways to find research opportunities are:

to become a graduate student. Every doctoral student is required to publish a

thesis. This is a unique research project. In order to prepare for this task, master's

and doctoral students are required to complete a series of research projects.

To identify opportunities is to subscribe to the journals in your area of expertise.

Read on the different research projects underway and make contact with the lead

researcher to identify research opportunities.

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 :

Internal Criteria consists of:

1( Researcher’s interest: The problem should be of researcher’s interest and be a

challenge to him. And curiosity may develop sustained perseverance and small

difficulties may not become an excuse for discontinuing the study. Interest in a problem

depends upon the researcher’s educational background, experience, outlook and

sensitivity.

2( Researcher’s competence: The researcher must be competent, must have ability and

possess adequate knowledge of subject-matter to deal with the problem and should be

aware of relevant methodology and statistical procedures.

3( Researcher’s own resource: To carry out research and complete on his own, a

researcher should consider his financial resources and limits. If it is beyond his means, he

needs some external financial support. Time is equally or more important than finance

and should be properly planned and 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.

For this, a question must be one for which observation or other data collection in the real

world can provide the answer.

2( Importance and urgency: Selection of the Problem for research should be on priority

basis of importance and urgency as Problems requiring investigation are unlimited, but

available research efforts are very much limited.

3( Novelty of the problem: The problem must have novelty. Necessity for selection of

problem already studied must be considered carefully checking its utility.

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 a prospective 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.

b. Why literature survey is important in research? [ 5 marks]

The review of concerning literature is the most simple and fruitful method of formulating

the research problem or developing hypothesis. Hypothesis mentioned by earlier workers

may be reviewed and its usefulness is evaluated as a basis for further research or it may

suggest new hypothesis. In this way the researcher review and build upon the work

already done by others. And if it is new, his task is to review the valuable material for

deriving the relevant hypothesis from it. Besides, he make the bibliographical review of

studies, already made in one’s area of interest. He should also attempt to apply concepts

and theories developed in different research contents to the area in which he is himself

working.

Sometimes the works of creative writers also provide good opportunities for hypothesis formulation.

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.

Literature Survey is a study involving a collection of literatures in the selected area of research in which the researcher has limited experience, and critical examination and comparison of them to have better understanding. It also helps the researchers to update with the past data, data sources and results, which will be useful for related researches in future.

Some examples of such researches are review of wholesale price index, demographic analysis, periodic stock exchange index reports, cross comparison of census details of different countries, etc.

Some key questions to ask are:

- whether researcher surveyed and described relevant studies related to the problem?

- Whether Researcher surveyed existing experts opinion of the problem?

- Has the Researcher summarized the existing state of opinion and research on the problem?

- Until literature is reviewed, there is no way of knowing whether the research question has already been adequately answered, of identifying the conceptual and practical obstacles that others have already encountered in the line of research, of learning how those obstacles have been overcome, and of deciding what lines of research can best build on the work that has already been done in a particular problem area.

- It is a prime source of selecting a research question to begin with.

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

b. What are the components of a research design?

Ans a:

The preparation of a research design is an important step in the research design. A research design is a written plan for a study.

According to W. Boyd and Westfall, Research design is a specified pattern of frame work for controlling the collection of data accurately and economically.”

Thomas Kinner defines research design as “ the basic plan which guides the data collection and analyses the phases of the project. It is the frame work which specifies the type of information to be collected, the sources of data and the data collection procedure.”

Thus, Research design is a logical and systematic plan prepared for conducting a research study. It is comparable to blue print which the architect prepare before construction of the building commences.

“A research design is the arrangement of conditions for collection and analysis of data in a manner that aims to combine relevance to the research purpose with economy in procedure” Is the conceptual structure within which research is conducted; it constitutes the blueprint for the collection, measurement and analysis of data more explicitly:

i.What is the study about?

ii.Why is the study being conducted?

iii.Where will the study be carried out?

iv.What type of data is required?

v.Where can the required data be found?

Characteristics of a Good Research Design are as follows:-

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

Components of Research Design are :

It is important to be familiar with the important concepts relating to research design.

They are:

1 . 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 points are 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;

whereas 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.

2. Extraneous variable:

The independent variables which are not directly related to the purpose of the study but

affect the dependent variable are known as extraneous variables. For instance, assume

that a researcher wants to test the hypothesis that there is relationship between children’s

school performance and their self-concepts, in which case the latter is an independent

variable and the former, the dependent variable. In this context, intelligence may also

influence the school performance. However, since it is not directly related to the purpose

of the study undertaken by the researcher, it would be known as an extraneous variable.

The influence caused by the extraneous variable on the dependent variable is technically

called as an ‘experimental error’. Therefore, a research study should always be framed in

such a manner that the dependent variable completely influences the change in the

independent variable and any other extraneous variable or variables.

3. Control:

One of the most important features of a good research design is to minimize the effect of

extraneous variable. Technically, the term control is used when a researcher designs the

study in such a manner that it minimizes the effects of extraneous independent variables.

The term control is used in experimental research to reflect the restrain in experimental

conditions.

4. Confounded relationship:

The relationship between dependent and independent 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 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.

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Q4. a. Distinguish between Doubles sampling and multiphase sampling.b. What is replicated or interpenetrating sampling?

Answer: Double Sampling and Multiphase Sampling :

Double sampling is resorted to when further information is needed from a subset of the

group from which some information has already been collected for the same study. A

sampling design where initially a sample is used in a study to collected some preliminary

information of interest, and later a subsample of this primary sample is used to examine

the matter in more detail, is called double sampling.

For example, a structured interview might indicate that a subgroup of the respondents

has more insight into the problems of the organization. These respondents might be called

again and asked additional questions. This research adopts a double sampling method.

A double sampling approach or a sample within a sample approach can be used to get the

population of well informed people, whose opinions are of greater importance to the

researcher than the opinions of comparatively less well informed.

In other words, Double sampling or two-phase 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 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.

In multi-phase sampling the purpose change at each phase. For example, at phase one the

selection of sample might be based on the criterion of geography (region), phase two

might be based on an economic criterion (standard of living), phase three might be based

on a political criterion ( influence of a political system of party) and so on.

b. 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 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 be employed.

Interpenetrating replicate subsamples, are useful in measuring the degree of agreement of

the results of successive samples. They are also useful in obtaining crash estimates. One

subsample can be used for this purpose prior to calculation of a final estimate from the

entire sample. A further use is to check one enumerator against another by giving each a

separate subsample to work on. For example, there are 1,000 one-kilogram bags of an

item numbered 1 to 1,000 consecutively. We might select 10 different samples of 10

bags each at random and select 10 items from each bag at random. If we put the 100

items from the first subsample of 10 bags into the 1st of 10 baskets, put the 100 items

from the second subsample of 10 bags into the 2nd of 10 baskets, etc., the 10 baskets of

100 items each would represent 10 interpenetrating replicate sub-samples.

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

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

Answer )a(: Usefulness of secondary data to researcher:

Secondary data are data which have been collected and analyzed by some other agency

for some other purpose. The sources containing data consists readily compendia and

already compiled statistical statements and reports whose data may be used by the

researchers for their studies e.g., census reports, annual reports, financial reports, reports

of Government departments, publication of international organizations such as UNO,

IMF, ILO, WHO, world bank, other statistical statements and so on. Secondary sources

are divers and consists both published and non-published records.

Secondary sources can also be interpretations of primary data. Examples of secondary

data are encyclopedias, textbooks, handbooks, magazine articles, newspaper articles etc. 

Secondary data is useful to researcher in the sense that the data is readymade and quickly

available, time saving, cost-effective, tabulated, compiled, covers even a larger area and

fields and consists of all sorts of material.

Mainly the secondary data may be used in three ways by the researcher:

1. Some specific information from secondary sources may be filtered and used for

reference.

For example, the general statistical information in the number of co-operative credit

societies in the country, their coverage of villages, their capital structure, 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.

2. Secondary data may be used as bench marks. The findings of research may be

compared and tested against the pre-set benchmark.

For Example, 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.

3. Secondary data may be used as the sole source of information for a research project.

Such studies as securities Market Behaviour, Financial Analysis and performance of

companies, Trade in credit allocation in commercial banks, sociological studies on

crimes, historical studies and so on, 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.

Some more uses/advantages of the secondary data are as follows:

4. Secondary data saves time as it can be secured quickly.

5. It covers wider geographical area and longer reference period in a cost-effective

manner. Thus, extends the researcher’s space and time.

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

can be made.

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

can be made.

8. 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.

B. Evaluation of Secondary Data is as follows:-

When a researcher wants to use secondary data for his research, the secondary data are to

be scrutinized before they are compiled from the source and before deciding to use them.

The scrutiny should be made to assess the data pertinence, quality (accuracy, reliability)

and completeness of the data.

1. Data Pertinence : The first consideration in evaluation of secondary data is to

examine the pertinence and suitability of the available secondary data to the research

problem under study. In particular, the conformity of the definitions, units of

measurement and time frame should be checked. For example, one US gallon is different

from one British gallon or one US dollar has a different value than Canadian dollar value.

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 : 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, mode of

collection, time period of collection and the purpose for which they were collected.

For example, secondary data collected by a voluntary agency with unskilled investigators

are unlikely to be reliable.

So there is a need to check 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 qualified investigators? 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 and

other comments that were made in the original source.

3. Data Completeness and adequacy: 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 organization’s 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 researcher’s study.

The source of the data may be suitable and reliable but the data may not be adequate for

the proposed enquiry. The original data may cover a bigger or narrow geographical

region or the data may not cover suitable periods. For example, per capita income of a

country or a state which divided after the data collection date (like Pakistan prior to 1971

and recently Sudan and division of some north eastern states of India, Up, Bihar etc in

recent past) is inadequate for reference during the subsequent periods as they separated

into divisions with considerable variation of revenues and expenditure thus affecting

standard of living.

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Q.6 What are the differences between observation and interviewing as methods of

data collection? Give two specific examples of situations where either observation or

interviewing would be more appropriate.

Answer: Observation means viewing or seeing. Observation may be defined as a

systematic viewing of a specific phenomenon in its proper setting for the specific purpose

of gathering data for a particular study. Observation is classical method of scientific

study.

I. Observation as a method of data collection has certain characteristics.

1. It is both a physical and a mental activity:

The observing eye catches many things that are present. But attention is focused

on data that are pertinent to the given study.

2. Observation is selective:

A researcher does not observe anything and everything, but selects the range of

things to be observed on the basis of the nature, scope and objectives of his study.

For example, suppose a researcher desires to study the causes of city road

accidents and also formulated a tentative hypothesis that accidents are caused by

violation of traffic rules and over speeding. When he observed the movements of

vehicles on the road, many things are before his eyes; the type, make, size and

colour of the vehicles, the persons sitting in them, their hair style, etc. All such

things which are not relevant to his study are ignored and only over speeding and

traffic violations are keenly observed by him.

3. Observation is purposive and not casual: It is made for the specific purpose

of noting things relevant to the study. It captures the natural social context in

which persons behavior occur. It grasps the significant events and occurrences

that affect social relations of the participants.

4. Observation should be exact and be based on standardized tools of research

and such as observation schedule, social metric scale etc., and precision

instruments, if any.

II. Interviewing is one of the prominent methods of data collection. It may be defined as

a two way systematic conversation between an investigator and an informant, initiated for

obtaining information relevant to a specific study. It involves not only conversation, but

also learning from the respondent’s gesture, facial expressions and pauses, and his

environment. Interviewing requires face to face contact or contact over telephone and

calls for interviewing skills. It is done by using a structured schedule or an unstructured

guide.

Interviewing may be used either as a main method or as a supplementary one in studies of

persons. Interviewing is the only suitable method for gathering information from illiterate

or less educated respondents. It is useful for collecting a wide range of data from factual

demographic data to highly personal and intimate information relating to a person’s

opinions, attitudes, values, beliefs past experience and future intentions. When qualitative

information is required or probing is necessary to draw out fully, and then interviewing is

required. Where the area covered for the survey is a compact, or when a sufficient

number of qualified interviewers are available, personal interview is feasible.

Interview is often superior to other data-gathering methods. People are usually more

willing to talk than to write. Once report is established, even confidential information

may be obtained. It permits probing into the context and reasons for answers to questions.

Interview can add flesh to statistical information. It enables the investigator to grasp the

behavioral context of the data furnished by the respondents.

There are several advantages to personal interviewing.

First the greatest value of this method is the depth and detail of information that can be

secured. When used with well conceived schedules, an interview can obtain a great deal

of information. It far exceeds mail survey in amount and quality of data that can be

secured.

Second, the interviewer can do more to improve the percentage of responses and the

quality of information received than other method. He can note the conditions of the

interview situation, and adopt appropriate approaches to overcome such problems as the

respondent’s unwillingness, incorrect understanding of questions, suspicion, etc.

Third, the interviewer can gather other supplemental information like economic level,

living conditions etc. through observation of the respondent’s environment.

Fourth, the interviewer can use special scoring devices, visual materials and the like in

order to improve the quality of interviewing.

Fifth, the accuracy and dependability of the answers given by the respondent can be

checked by observation and probing.

Last, interview is flexible and adaptable to individual situations. Even more, control can

be exercised over the interview situation.

Situation where observation is appropriate:

Observations make it possible to capture the whole event as it occurs. For example only

observation can provide an insight into all the aspects of the process of negotiation

between union and management representatives.

To study the Reading habits of newspaper/magazines readers etc.

Observation is suitable for a variety of research purposes. It may be used for studying

(a) The behavior of human beings in purchasing goods and services.: life style, customs,

and manner, interpersonal relations, group dynamics, crowd behavior, leadership styles,

managerial style, other behaviors and actions;

(b) The behavior of other living creatures like birds, animals etc.

(c) Physical characteristics of inanimate things like stores, factories, residences etc.

(d) Flow of traffic and parking problems

(e) movement of materials and products through a plant.

Situation where interview method is appropriate:

The interview method is more appropriate when a direct conversation with the

respondents is preferred. When interviewer wishes to have a direct rapport with the

interviewee and collect first hand information from the original source without using any

mediatory.

For example, in case of a job interview, the HR manager (selector) wishes to interview

the candidate directly to assess the candidate keenly and personally. The aim is to get

answers to the interview questions directly and instantly from the job seeker. In this

method, the interviewer can assess the capabilities of the candidate in terms of subject

knowledge, intelligence, area of expertise or experience, communication skills, level of

understanding etc.

Another example, when a new product/service or a brand is introduced in the market,

the company which introduced the product adopt various methods like survey method,

questionnaire etc. But the direct interview with the distributors, more importantly, with

the customers is much preferred and considered as reliable source of information. The

sales personnel or the surveyors directly get into touch with the customers in shopping

malls and market place to check their comments and opinions about the newly introduced

products. The consumers’ views and comments from the basis of information

highlighting the pros and cons of the product or service.

During the trade shows of products, say car exhibition, the media people or the company

representatives approach the visitors directly to know their interest and opinion about the

products.

We also watch on TV quite often, when the media people interviewing the celebraties

from different field to have first hand information directly from the concerned person.

So in situations where the interviewer wishes to have direct and unbiased information,

comments and views from the interviewer, the interview method is preferred.

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