RISEARCH ALL NOTES IS HERE

Skip to main content
web
texts
movies
audio
software
image
logo
Toggle navigation
search
Search the Archive

upload
person
Full text of "Research Methodology"
See other formats
UNIT - 1
INTRODUCTION
Learning Objectives

After reading this lesson, you should be able to understand:



•



Meaning, objectives and types of research



• Qualities of researcher

• Significance of research

• Research process



Research problem

Features, importance, characteristics, concepts and

types of Research design

Case study research

Hypothesis and its testing

Sample survey and sampling methods



1.1 Meaning of Research

Research in simple terms, refers to a search for knowledge. It is also known as a
scientific and systematic search for information on particular topic or issue. It is
also known as the art of scientific investigation. Several social scientists have
defined research in different ways

In the Encyclopedia of Social Sciences, D. Slesinger and M. Stephension
(1930) defined research as "the manipulation of things, concept or symbols for
the purpose of generalizing to extend, correct or verify knowledge, whether that
knowledge aids in construction of theory or in practice of an art".

According to Redman and Mory (1923), defined research is a
"systematized effort to gain new knowledge". It is an academic activity and
therefore the term should be used in a technical sense. According to Clifford
Woody (Kothari 1988) research comprises "defining and redefining problems,
formulating hypothesis or suggested solutions; collecting, organizing and



290



evaluating data; making deductions and reaching conclusions; and finally,
carefully testing the conclusions to determine whether they fit the formulating
hypothesis".

Thus, research is an original addition to the available knowledge, which
contributes to its further advancement. It is an attempt to pursue truth through
the methods of study, observation, comparison and experiment. In sum,
research is the search for knowledge, using objective and systematic methods to
find solution to a problem.

1.1.1 Objectives of research

The objective of research is to discover answers to questions by applying
scientific procedures. In the other words, the main aim of research is to find out
truth which is hidden and has not yet been discovered. Although every research
study has its own specific objectives, research objectives may be broadly
grouped as follows:-

1. to gain familiarity with or new insights into a phenomenon (i.e.,
formulative research studies);

2. to accurately portray the characteristics of a particular individual, group,
or a situation (i.e., descriptive research studies);

3. to analyse the frequency with which something occurs (i.e., diagnostic

research studies); and
4. to examine a hypothesis of a causal relationship between two variables

(i.e., hypothesis-testing research studies).

1.1.2 Research methods versus methodology

Research methods include all those techniques/methods that are adopted for
conducting research. Thus, research techniques or methods are the methods the
researchers adopt for conducting the research operations.

On the other hand, research methodology is the way of systematically
solving the research problem. It is a science of studying how research is
conducted scientifically. Under it, the researcher acquaints himself/herself with



291



the various steps generally adopted to study a research problem, along with the
underlying logic behind them. Hence, it is not only important for the researcher
to know the research techniques/methods, but also the scientific approach called
methodology.

1.1.3 Research approaches

There are two main approaches to research, namely quantitative approach and
qualitative approach. The quantitative approach involves the collection of
quantitative data, which are put to rigorous quantitative analysis in a formal and
rigid manner. This approach further includes experimental, inferential, and
simulation approaches to research. Meanwhile, the qualitative approach uses the
method of subjective assessment of opinions, behaviour and attitudes. Research
in such a situation is a function of the researcher's impressions and insights.
The results generated by this type of research is either in non-quantitative form
or in the form which can not be put to rigorous quantitative analysis. Usually,
this approach uses techniques like depth interviews, focus group interviews, and
projective techniques.

1.1.4 Types of research

There are different types of research. The basic ones are as follows:
1) Descriptive vs. Analytical:

Descriptive research comprises surveys and fact-finding enquiries of different
types. The main objective of descriptive research is describing the state of
affairs as it prevails at the time of study. The term ex post facto research is quite
often used for descriptive research studies in social sciences and business
research. The most distinguishing feature of this method is that the researcher
has no control over the variables here. He/she has to only report what is
happening or what has happened. Majority of the ex post facto research projects
are used for descriptive studies in which the researcher attempts to examine



292



phenomena, such as the consumers' preferences, frequency of purchases,
shopping, etc. Despite the inability of the researchers to control the variables, ex
post facto studies may also comprise attempts by them to discover the causes of
the selected problem. The methods of research adopted in conducting
descriptive research are survey methods of all kinds, including correlational and
comparative methods.

Meanwhile in the analytical research, the researcher has to use the
already available facts or information, and analyse them to make a critical
evaluation of the subject.

2) Applied vs. Fundamental

Research can also be applied or fundamental research. An attempt to find a
solution to an immediate problem encountered by a firm, an industry, a business
organisation, or the society is known as applied research. Researchers engaged
in such researches aim at drawing certain conclusions confronting a concrete
social or business problem. On the other hand, fundamental research mainly
concerns generalizations and formulation of a theory. In other words, "Gathering
knowledge for knowledge's sake is termed 'pure' or 'basic' research" (Young in
Kothari 1988). Researches relating to pure mathematics or concerning some
natural phenomenon are instances of fundamental research. Likewise, studies
focusing on human behaviour also fall under the category of fundamental
research. Thus, while the principal objective of applied research is to find a
solution to some pressing practical problem, the objective of basic research is to
find information with a broad base of application and add to the already existing
organized body of scientific knowledge.

3) Quantitative vs. Qualitative

Quantitative research relates to aspects that can be quantified or can be
expressed in terms of quantity. It involves the measurement of quantity or



293



amount. The various available statistical and econometric methods are adopted
for analysis in such research. They include correlation, regressions, time series
analysis, etc.

Whereas, qualitative research is concerned with qualitative phenomenon,
or more specifically, the aspects relating to or involving quality or kind. For
example, an important type of qualitative research is 'Motivation Research',
which investigates into the reasons for human behaviour. The main aim of this
type of research is discovering the underlying motives and desires of human
beings, using in-depth interviews. The other techniques employed in such
research are story completion tests, sentence completion tests, word association
tests, and other similar projective methods. Qualitative research is particularly
significant in the context of behavioural sciences, which aim at discovering the
underlying motives of human behaviour. Such research help to analyse the
various factors that motivate human beings to behave in a certain manner,
besides contributing to an understanding of what makes individuals like or
dislike a particular thing. However, it is worth noting that conducting
qualitative research in practice is considerably a difficult task. Hence, while
undertaking such research, seeking guidance from experienced expert
researchers is important.
4) Conceptual vs. Empirical

A research related to some abstract idea or theory is known as conceptual
research. Generally, philosophers and thinkers use it for developing new
concepts or for reinterpreting the existing ones. Empirical research, on the other
hand, exclusively relies on observation or experience with hardly any regard for
theory and system. Such research is data based. They often come up with
conclusions that can be verified through experiment or observation. They are
also known as experimental type of research. Under such research, it is



294



important to first collect facts, their source and actively do certain things to
stimulate the production of desired information. In such a research, the
researcher must first identify a working hypothesis or make a guess of the
probable results. Next, he/she gathers sufficient facts to prove or disprove the
stated hypothesis. Then he/she formulates experimental designs, which
according to him/her would manipulate the individuals or the materials
concerned, so as to obtain the desired information. This type of research is thus
characterized by the researcher's control over the variables used to study their
effects. Empirical research is most appropriate when an attempt is made to
prove that certain variables influence the other variables in some way.
Therefore, the results obtained using the experimental or empirical studies are
considered as one of the most powerful evidences for a given hypothesis.
5) Other types of research: The remaining types of research are variations
of one or more of the afore-mentioned methods. They vary in terms of the
purpose of research, or the time required to complete it, or based on some other
similar factor. On the basis of time, research may either be in the nature of one-
time or longitudinal research. While the research is restricted to a single time-
period in the former case, it is conducted over several time-periods in the latter
case. Depending upon the environment in which the research is to be
conducted, it may also be laboratory research or field-setting research, or
simulation research, besides being diagnostic or clinical in nature. Under such
research, in-depth approaches or case-study methods may be employed to
analyse the basic causal relations. These studies usually conduct a detailed in-
depth analysis of the causes of things or events of interest, and use very small
samples and a sharp data collecting method. The research may also be
explanatory in nature. Formalized research studies consist of substantial
structure and specific hypotheses to be verified. As regards historical research,



295



sources like historical documents, remains, etc., are utilized to study past events
or ideas. It also includes philosophy of persons and groups of the past or any
remote point of time. Research is also categorized as decision-oriented and
conclusion-oriented. In the case of decision-oriented research, it is always
carried out for the need of a decision maker and hence, the researcher has no
freedom to conduct the research as per his/her own desires. Whereas, under
conclusion-oriented research, the researcher is free to choose the problem,
redesign the enquiry as it progresses and even change conceptualization as
he/she wishes to. Further, operations research is a kind of decision- oriented
research, because it is a scientific method which provides the executive
departments a quantitative basis for decision-making with respect to the
activities under their purview.

1.1.5 Importance of knowing how to conduct research

The following are the importance of knowing how to conduct a research:

(i) the knowledge of research methodology provides training to new researchers

and enables them to do research properly. It helps them to develop

disciplined thinking or a 'bent of mind' to objectively observe the field,
(ii) the knowledge of doing research would inculcate the ability to evaluate and

utilise the research findings with confidence;
(hi) the knowledge of research methodology equips the researcher with tools

that help him/her to observe things objectively; and
(iv) the knowledge of methodology helps the research consumer to evaluate

research and make rational decisions.

1.1.6 Qualities of a researcher

It is important for a researcher to have certain qualities to conduct research.
Foremost, the researcher being a scientist should be firmly committed to the



296



'articles of faith' of the scientific methods of research. This implies that a
researcher should be a social science person in the truest sense.

Sir Michael Foster (Wilkinson and Bhandarkar 1979) identified a few
distinctive qualities of a scientist. According to him, a true research scientist
should possess the following main three qualities.

(1) First of all, the nature of a researcher must be of the temperament that
vibrates in unison with the theme which he is searching. Hence, the seeker of
knowledge must be truthful with truthfulness of nature, which is much more
important, much more exacting than what is sometimes known as truthfulness.
The truthfulness relates to the desire for accuracy of observation and precision
of statement. Ensuring facts is the principle rule of science, which is not an easy
matter. Such difficulty may arise due to untrained eye, which fails to see
anything beyond what it has the power of seeing and sometimes even less than
that. This may also be due to the lack of discipline in the method of science. An
unscientific individual often remains satisfied with expressions like
approximately, almost, nearly, etc., which is never what nature, is. It cannot see
two things which differ, however minutely, as the same.

(2) A researcher must possess an alert mind. The Nature is constantly
changing and revealing itself through various ways. A scientific researcher must
be keen and watchful to notice such changes, no matter how small or
insignificant they may appear. Such receptivity has to be cultivated slowly and
patiently over time by the researcher through practice. No individual who is not
alert and receptive, or is ignorant or has no keen eyes or mind to observe the
unusual behind the routine, can make a good researcher. Research demands a
systematic immersion into the subject matter for the researcher to be able to
grasp even the slightest hint that may culminate into significant research
problems. In this context, Cohen and Negal (Wilkinson and Bhandarkar 1979)



297



state that "The ability to perceive in some brute experience the occasion of a
problem is not a common talent among men. . . It is a mark of scientific genius to
be sensitive to difficulties where less gifted people pass by untroubled by doubt"
(Selltiz, et. al.,1965).

(3) Scientific enquiry is pre-eminently an intellectual effort. It requires
the moral quality of courage, which reflects the courage of a steadfast
endurance. The science of conducting research is not an easy task. There are
occasions when a research scientist might feel defeated or completely lost. This
is a stage when the researcher would need immense courage and a sense of
conviction. The researcher must learn the art of enduring intellectual hardships.
In the words of Darwin, "It's dogged that does it" (Wilkinson and Bhandarkar
1979).

In order to cultivate the afore-mentioned three qualities of a researcher, a
fourth one may be added. This is the quality of making statements cautiously.
According to Huxley, "The assertion that outstrips the evidence is not only a
blunder but a crime" (Thompson 1975). A researcher should cultivate the habit
of reserving judgment when the required data are insufficient.
1.1.7 Significance of research

According to a famous Hudson Maxim, "All progress is born of inquiry. Doubt
is often better than overconfidence, for it leads to inquiry, and inquiry leads to
invention" (Wilkinson and Bhandarkar 1979). It brings out the significance of
research, increased amounts of which makes progress possible. Research
encourages scientific and inductive thinking, besides promoting the
development of logical habits of thinking and organisation.

The role of research in applied economics in the context of an economy
or business is greatly increasing in modern times. The increasingly complex
nature of government and business has raised the use of research in solving



298



operational problems. Research assumes significant role in the formulation of
economic policy, for both the government and business. It provides the basis for
almost all government policies of an economic system. Government budget
formulation, for example, depends particularly on the analysis of needs and
desires of people, and the availability of revenues, which requires research.
Research helps to formulate alternative policies, in addition to examining the
consequences of these alternatives. Thus, research also facilitates the decision-
making of the policy- makers, although in itself it is not a part of research. In
the process, research also helps in the proper allocation of a country's scarce
resources. Research is also necessary for collecting information on the social
and economic structure of an economy to understand the process of change
occurring in the country. Collection of statistical information, though not a
routine task, involves various research problems. Therefore, large staff of
research technicians or experts is engaged by the government these days to
undertake this work. Thus, research as a tool of government economic policy
formulation involves three distinct stages of operation, viz., (i) investigation of
economic structure through continual compilation of facts; (ii) diagnosis of
events that are taking place and the analysis of the forces underlying them; and
(hi) the prognosis, i.e., the prediction of future developments (Wilkinson and
Bhandarkar 1979).

Research also assumes a significant role in solving various operational
and planning problems associated with business and industry. In several ways,
operations research, market research, and motivational research are vital and
their results assist in taking business decisions. Market research is refers to the
investigation of the structure and development of a market for the formulation of
efficient policies relating to purchases, production and sales. Operational
research relates to the application of logical, mathematical, and analytical



299



techniques to find solution to business problems such as cost minimization or
profit maximization, or the optimization problems. Motivational research helps
to determine why people behave in the manner they do with respect to market
characteristics. More specifically, it is concerned with the analyzing the
motivations underlying consumer behaviour. All these researches are very
useful for business and industry, who are responsible for business decision-
making.

Research is equally important to social scientists for analyzing social
relationships and seeking explanations to various social problems. It gives
intellectual satisfaction of knowing things for the sake of knowledge. It also
possess practical utility for the social scientist to gain knowledge so as to be able
to do something better or in a more efficient manner. This, research in social
sciences is concerned with both knowledge for its own sake, and knowledge for
what it can contribute to solve practical problems.
1.2 Research process

Research process comprises a series of steps or actions required for effectively
conducting research and for the sequencing of these steps. The following are the
various steps that provide useful procedural guideline regarding the conduct
research.

(1) formulating the research problem;

(2) extensive literature survey;

(3) developing hypothesis;

(4) preparing the research design;

(5) determining sample design;

(6) collecting data;

(7) execution of the project;

(8) analysis of data;

(9) hypothesis testing;

(10) generalization and interpretation, and



300



(11) preparation of the report or presentation of the results. In other
words, it involves the formal write-up of conclusions.

1.3 Research Problem

The first and foremost stage in the research process is to select and properly
define the research problem. A researcher should firstly identify a problem and
formulate it, so as to make it amenable or susceptible to research.

In general, a research problem refers to some kind of difficulty the
researcher might encounter or experience in the context of either a theoretical or
practical situation, which he/she would like to resolve and find a solution to. A
research problem is generally said to exist if the following conditions emerge
(Kothari 1988):

(i) there should be an individual or an organisation, say X, to whom the
problem can be attributed. The individual or the organization is situated
in an environment Y, which is governed by certain uncontrolled
variables Zj.

(ii) there should be atleast two courses of action to be pursued, say Ai and
A2. These courses of action are defined by one or more values of the
controlled variables. For example, the number of items purchased at a
specified time is said to be one course of action.

(iii) there should be atleast two alternative possible outcomes of the said
course of actions, say Bi and B2. Of them, one alternative should be
preferable to the other. That is, atleast one outcome should be what the
researcher wants, which becomes an objective.

(iv) the courses of possible action available must offer a chance to the
researcher to achieve the objective, but not the equal chance. Therefore,
if P(Bj / X, A, Y) represents the probability of the occurrence of an
outcome Bj when X selects A, in Y, then P(Bi / X, A h Y) ± P (Bi / X, A 2 ,
Y). Putting it in simple words, it means that the choices must not have
equal efficiencies for the desired outcome.



301



Above all these conditions, the individual or organisation may be said to
have arrived at the research problem only if X does not know what course of
action to be taken is the best. In other words, X should have a doubt about the
solution. Thus, an individual or a group of persons can be said to have a
problem if they have more than one desired outcome. They should have two or
more alternative courses of action, which have some but not equal efficiency for
probing the desired objectives, such that they have doubts about the best course
of action to be taken.

Thus, the various components of a research problem may be summarised as:

(i) there should be an individual or a group who have some difficulty or
problem.

(ii) there should be some objective(s) to be pursued. A person or an
organization who want nothing cannot have a problem.

(iii) there should be alternative ways of pursuing the objective the researcher
wants to pursue. This implies that there should be more than one
alternative means available to the researcher. This is because if the
researcher has no choice of alternative means, he/she would not have a
problem.

(iv) there should be some doubt in the mind of the researcher about the
choice of alternative means. This implies that research should answer
the question relating to the relative efficiency or suitability of the
possible alternatives.

(v) there should be a context to which the difficulty relates.

Thus, identification of a research problem is the pre-condition to
conducting research. A research problem is said to be the one which requires a
researcher to find the best available solution to the given problem. That is, the
researcher needs to find out the best course of action through which the research
objective may be achieved optimally in the context of a given situation. Several
factors may contribute to making the problem complicated. For example, the
environment may alter, thus affecting the efficiencies of the alternative course of
actions taken or the quality of the outcomes. Or, the number of alternative



302



course of actions may be very large and the individual not involved in making

the decision may be affected by the change in environment, and may react to it

favorably or unfavorably. Other similar factors are also likely to cause such

changes in the context of research, all of which may be considered from the

point of view of a research problem.

1.4 Research Design

The most important problem after defining the research problem is preparing

the design of the research project, which is popularly known as the 'research

design'. A research design helps to decide upon issues like what, when, where,

how much, by what means, etc., with regard to an enquiry or a research study.

"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. In fact, the research design is the conceptual structures

within which research is conducted; it constitutes the blueprint for the collection,

measurement and analysis of data" (Selltiz, et.al. 1962). Thus, research design

provides an outline of what the researcher is going to do in terms of framing the

hypothesis, its operational implications, and the final data analysis. Specifically,

the research design highlights decisions which include:

(i) the nature of the study

(ii) the purpose of the study

(iii) the location where the study would be conducted

(iv) the nature of data required

(v) from where the required data can be collected

(vi) what time period the study would cover

(vii) the type of sample design that would be used

(viii) the techniques of data collection that would be used

(ix) the methods of data analysis that would be adopted

(x) the manner in which the report would be prepared



303



In view of the stated research design decisions, the overall research
design may be divided into the following (Kothari 1988)

(a) the sampling design that deals with the method of selecting items to be
observed for the selected study;

(b) the observational design that relates to the conditions under which the
observations are to be made;

(c) the statistical design that concerns with the question of how many items
are to be observed, and how the information and data gathered are to be
analysed; and

(d) the operational design that deals with the techniques by which the
procedures specified in the sampling, statistical and observational
designs can be carried out.

1.4.1 Features of research design

The important features of research design may be outlined as follows:

(i) it constitutes a plan that identifies the types and sources of
information required for the research problem;

(ii) it constitutes a strategy that specifies the methods of data collection
and analysis which would be adopted; and

(iii) it also specifies the time period of research and monetary budget
involved in conducting the study, which comprise the two major
constraints of undertaking any research.



1.4.2 Concepts relating to research design

It is also important to be familiar with the important concepts relating to
research design. Some of them are discussed here.

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



304



sense or objectively. However, the qualitative phenomena may also be
quantified in terms of the presence or absence of the attribute(s) considered.
Phenomena that assumes 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 variables'. 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 own price, income and price of
substitutes.

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 a 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(s) on the
dependent variable is technically called as an 'experimental error'. Therefore, a



305



research study should always be framed in such a manner that the dependent
variable(s) that completely influence 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(s). 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 the dependent and
independent variables is said to be confounded by an extraneous variable(s),
when the dependent variable is not free from its effects.

5. 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 to 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 to be tested are predictive
statements that are not to be objectively verified are not classified as research
hypotheses.

6. Experimental and non-experimental hypothesis testing research: When
the objective of a research is to test a research hypothesis, it is known as a
hypothesis-testing research. Such research may be in the nature of experimental
design or non-experimental design. A research in which the independent
variable is manipulated is known as 'experimental hypothesis-testing research',
whereas a research in which the independent variable is not manipulated is
termed as 'non-experimental hypothesis-testing research'. For example, assume
that a researcher wants to examine whether family income influences the school



306



attendance of a group of students, by calculating the coefficient of correlation
between the two variables. Such an example is known as a non-experimental
hypothesis-testing research, because the independent variable family income is
not manipulated here. Again assume that the researcher randomly selects 150
students from a group of students who pay their school fees regularly and then
classifies them into two sub-groups by randomly including 75 in Group A,
whose parents have regular earning, and 75 in group B, whose parents do not
have regular earning. Assume that at the end of the study, the researcher
conducts a test on each group in order to examine the effects of regular earnings
of the parents on the school attendance of the student. Such a study is an
example of experimental hypothesis-testing research, because in this particular
study the independent variable regular earnings of the parents has been
manipulated.

7. 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 group. 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 both the
experimental and control groups together.

8. 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 the comparative impacts of three different types of fertilizers on the



307



yield of rice crop, then the three types of fertilizers would be treated as the three
treatments.

9. 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.

10. Experiment unit(s): Experimental units refer to the pre-determined 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.

1.4.3 Types of research design

There are different types of research designs. They may be broadly categorized

as:

(1) exploratory research design;

(2) descriptive and diagnostic research design; and

(3) hypothesis-testing research design.

1. Exploratory research design:

The exploratory research design is known as formulative research design. The
main objective of using such a research design is for formulating a research
problem for an in-depth or more precise investigation, or for developing a
working hypothesis from an operational aspect. The major purpose of such



308



studies is the discovery of ideas and insights. Therefore, such a research design
suitable for such a study should be flexible enough to provide opportunity for
considering different dimensions of the problem under study. The in-built
flexibility in research design is required as the initial research problem would be
transformed into a more precise one in the exploratory study, which in turn may
necessitate changes in the research procedure for collecting relevant data.
Usually, the following three methods are considered in the context of a research
design for such studies. They are (a) a survey of related literature; (b)
experience survey; and (c) analysis of 'insight-stimulating' instances.
2. Descriptive and diagnostic research design:

A descriptive research design is concerned with describing the characteristics of
a particular individual, or a group. Meanwhile, a diagnostic research design
determines the frequency with which a variable occurs or its relationship with
another variable. In other words, the study analyzing whether a certain variable
is associated with another comprises a diagnostic research study. On the other
hand, a study that is concerned with specific predictions or with the narration of
facts and characteristics relating to an individual, group or situation, are
instances of descriptive research studies. Generally, most of the social research
design falls under this category. As a research design, both the descriptive and
diagnostic studies share common requirements, and hence they may grouped
together. However, the procedure to be used must be planned carefully, and so
the research design should also be planned carefully. The research design must
also make appropriate provision for protection against bias and thus maximize
reliability, with due regard to the completion of the research study in as
economical manner as possible. The research design in such studies should be
rigid and not flexible. Besides, it must also focus attention on the following:
(a) formulation of the objectives of the study,



309



(b) proper designing of the methods of data collection ,

(c) sample selection,

(d) data collection,

(e) processing and analysis of the collected data, and

(f) Reporting the findings.

3. Hypothesis-testing research design:

Hypothesis-testing research designs are those in which the researcher tests the
hypothesis of causal relationship between two or more variables. These studies
require procedures that would not only decrease bias and enhance reliability, but
also facilitate deriving inferences about the causality. Generally, experiments
satisfy such requirements. Hence, when research design is discussed in such
studies, it often refers to the design of experiments.
1.4.4 Importance of research design

The need for a research design arises out of the fact that it facilitates the smooth
conduct of the various stages of research. It contributes to making research as
efficient as possible, thus yielding the maximum information with minimum
effort, time and expenditure. A research design helps to plan in advance of the
methods to be employed for collecting the relevant data and the techniques to be
adopted for their analysis, so as to pursue the objectives of the research in the
best possible manner, given the available staff, time and money. Hence, the
research design should be prepared with utmost care, so as to avoid any error
that may disturb the entire project. Thus, research design plays a crucial role in
attaining the reliability of the results obtained, which forms the strong
foundation of the entire process of the research work.

Despite its significance, the purpose of a well-planned design is not
realized at times. This is because it is not given the importance that this problem
deserves. As a consequence, many researchers are not able to achieve the
purpose for which the research designs are formulated, due to which they end up



310



arriving at misleading conclusions. Therefore, faulty designing of the research
project tends to render the research exercise meaningless. This makes it
imperative that an efficient and suitable research design must be planned before
commencing the process of research. The research design helps the researcher
to organize his/her ideas in a proper form, which would facilitate him/her to
identify the inadequacies and faults in them. The research design may also be
discussed with other experts for their comments and critical evaluation, without
which it would be difficult for any critic to provide a comprehensive review and
comment on the proposed study.
1.4.5 Characteristics of a good research design

A good research design often possesses the qualities such as being flexible,
suitable, efficient, economical, and so on. Generally, a research design which
minimizes bias and maximizes the reliability of the data collected and analysed
is considered a good design (Kothari 1988).

A research design which involves the smallest experimental error is said
to be the best design for investigation. Further, a research design that yields
maximum information and provides an opportunity of viewing the various
dimensions of a research problem is considered to be the most appropriate and
efficient design. Thus, the question of a good design relates to the purpose or
objective and nature of the research problem studied. While a research design
may be good, it may not be equally suitable to all studies. In other words, it may
be lacking in one aspect or the other in the case of some other research
problems. Therefore, no single research design can be applied to all types of
research problems.

A research design suitable for a specific research problem would usually
involve the following considerations:

(i) the methods of gathering the information;



311



(ii) the skills and availability of the researcher and his/her staff, if any;

(hi) the objectives of the research problem being studied;

(iv) the nature of the research problem being studied; and

(v) the available monetary funds and time duration for the research work.

1.5 Case Study Research

The method of exploring and analyzing the life or functioning of a social or

economic unit, such as a person, a family, a community, an institution, a firm or

an industry, is called a case study method. The objective of a case study method

is to examine the factors that cause the behavioural patterns of a given unit and

its relationship with the environment. The data for a study are always gathered

with the purpose of tracing the natural history of a social or economic unit, and

its relationship with the social or economic factors, besides the forces involved

in its environment. Thus, a researcher conducting a study using the case study

method attempts to understand the complexity of factors that are operative

within a social or economic unit as an integrated totality. Burgess (Kothari

1988) described the special significance of the case study in understanding the

complex behaviour and situations in specific detail. In the context of social

research, he called these data as a social microscope.

1.5.1 Criteria for evaluating adequacy of case study

John Dollard (Dollard 1935) specified seven criteria for evaluating the adequacy

of a case or life history in the context of social research. They are as follows: -

(i) The subject being studied must be viewed as a specimen in a cultural set
up. That is, the case selected from its total context for the purpose of study
should be considered a member of the particular cultural group or
community. The scrutiny of the life history of the individual must be
carried out with a view to identify the community values, standards and
shared ways of life.

(ii) The organic motors of action should be socially relevant. This is to say
that the action of the individual cases should be viewed as a series of



312



reactions to social stimuli or situations. Putting in simple words, the
social meaning of behaviour should be taken into consideration.

(iii) The crucial role of the family-group in transmitting the culture should be
recognized. This means that as the individual is a member of a family, the
role of the family in shaping his/her behaviour should never be ignored.

(iv) The specific method of conversion of organic material into social
behaviour should be clearly demonstrated. For instance, case-histories that
discuss in detail how basically a biological organism, that is man,
gradually transform into a social person are particularly important.

(v) The constant transformation of character of experience from childhood to
adulthood should be emphasised. That is, the life-history should portray
the inter-relationship between the individual's various experiences during
his/her life span. Such a study provides a comprehensive understanding of
an individual's life as a continuum.

(vi) The 'social situation' that contributed to the individual's gradual
transformation should carefully and continuously specified as a factor. One
of crucial the criteria for life-history is that an individual's life should be
depicted as evolving itself in the context of a specific social situations and
partially caused by it.

(vii) The life-history details themselves should be organized according to some
conceptual framework, which in turn would facilitate their generalizations
at higher levels.

These criteria discussed by Dollard emphasise the specific link of co-
ordinated, related, continuous and configured experience in a cultural pattern
that motivated the social and personal behaviour. Although, the criteria
indicated by Dollard are principally perfect, but some of them are difficult to put
to practice.

Dollard (1935) attempted to express the diverse events depicted in the
life-histories of persons during the course of repeated interviews by utilizing
psycho-analytical techniques in a given situational context. His criteria of life-



313



history originated directly from this experience. While the life-histories possess
independent significance as research documents, the interviews recorded by the
investigators can afford, as Dollard observed, "rich insights into the nature of the
social situations experienced by them".

It is a well-known fact that an individual's life is very complex. Till date
there is hardly any technique that can establish in some kind of uniformity, and
as a result ensure the cumulative of case-history materials by isolating the
complex totality of a human life. Nevertheless, although case history data are
difficult to put to rigorous analysis, a skilful handling and interpretation of such
data could help in developing insights into cultural conflicts and problems
arising out of cultural-change.

Gordon Allport (Kothari 1988) has recommended the following aspects

so as to broaden the perspective of case-study data as follows:

(i) if the life-history is written in first person, it should be as
comprehensive and coherent as possible.

(ii) Life-histories must be written for knowledgeable persons. That
is, if the enquiry of study is sociological in nature, the researcher
should write it on the assumption that it would be read largely by
sociologists only.

(iii) It would be advisable to supplement case study data by
observational, statistical and historical data, as they provide
standards for assessing the reliability and consistency of the case
study materials. Further, such data offer a basis for
generalizations.

(iv) Efforts must be made to verify the reliability of life-history data
by examining the internal consistency of the collected material,
and by repeating the interviews with the person, besides having
personal interviews with the persons of the subject's own group
who are well-acquainted with him/her.



314



(v) A judicious combination of different techniques for data-
collection is crucial for collecting data that are culturally
meaningful and scientifically significant.

(vi) Life-histories or case-histories may be considered as an adequate
basis for generalization to the extent that they are typical or
representative of a certain group.

(vii) The researcher engaged in the collection of case study data
should never ignore the unique or atypical cases. He/she should
include them as exceptional cases.

Case histories are filled with valuable information of a personal or
private nature. Such information not only help the researcher to portray the
personality of the individual, but also the social background that contributed to
it. Besides, it also helps in the formulation of relevant hypotheses. In general,
although Blummer (in Wilkinson and Bhandarkar 1979) was critical of
documentary materials, he gave due credit to case histories by acknowledging
the fact that the personal documents offer an opportunity to the researcher to
develop his/her spirit of enquiry. The analysis of a particular subject would be
more effective if the researcher acquires close acquaintance with it through
personal documents. However, Blummer also acknowledges the limitations of
the personal documents. According to him, independently such documents do
not entirely fulfill the criteria of adequacy, reliability, and representativeness.
Despite these shortcomings, avoiding their use in any scientific study of
personal life would be wrong, as these documents become necessary and
significant for both theory-building and practice.

In spite of these formidable limitations, case study data are used by
anthropologists, sociologists, economists and industrial psychiatrists. Gordon
Allport (Kothari 1988) strongly recommends the use of case study data for in-
depth analysis of a subject. For, it is one's acquaintance with an individual that



315



instills desire to know his/her nature and understand them. The first stage
involves understanding the individual and all the complexity of his/her nature.
Any haste in analyzing and classifying the individual would create the risk of
reducing his/her emotional world into artificial bits. As a consequence, the
important emotional organizations, anchorages, and natural identifications
characterizing the personal life of the individual might not yield adequate
representation. Hence, the researcher should understand the life of the subject.
Therefore, the totality of life-processes reflected in the well-ordered life-history
documents become invaluable source of stimulating insights. Such life-history
documents provide the basis for comparisons that contribute to statistical
generalizations and help to draw inferences regarding the uniformities in human
behaviour, which are of great value. Even if some personal documents do not
provide ordered data about personal lives of people, which is the basis of
psychological science, they should not be ignored. This is because the final aim
of science is to understand, control and make predictions about human life. Once
they are satisfied, the theoretical and practical importance of personal
documents must be recognized as significant. Thus, a case study may be
considered as the beginning and the final destination of abstract knowledge.
1.6 Hypothesis

"Hypothesis may be defined as a proposition or a set of propositions set forth as
an explanation for the occurrence of some specified group of phenomenon either
asserted merely as a provisional conjecture to guide some investigation or
accepted as highly probable in the light of established facts" (Kothari 1988). A
research hypothesis is quite often a predictive statement, which is capable of
being tested using scientific methods that involve an independent and some
dependent variables. For instance, the following statements may be considered:



316



i) "students who take tuitions perform better than the others who not receive

tuitions" or,

ii) "the female students perform as well as the male students".

These two statements are hypotheses that can be objectively verified and tested.

Thus, they indicate that a hypothesis states what one is looking for. Besides, it

is a proposition that can be put to test in order to examine its validity.



1.6.1 Characteristics of hypothesis:

A hypothesis should have the following characteristic features:-

(i) a hypothesis must be precise and clear . If it is not precise and clear,
then the inferences drawn on its basis would not be reliable.

(ii) a hypothesis must be capable of being put to test. Quite often, the
research programmes fail owing to its incapability of being subject to
testing for validity. Therefore, some prior study may be conducted
by the researcher in order to make a hypothesis testable. A
hypothesis "is tested if other deductions can be made from it, which
in turn can be confirmed or disproved by observation" (Kothari
1988).

(iii) a hypothesis must state relationship between two variable, in the case
of relational hypotheses.

(iv) a hypothesis must be specific and limited in scope. This is because a
simpler hypothesis generally would be easier to test for the research.
And therefore, he/she must formulate such hypotheses.

(v) as far as possible, a hypothesis must be stated in the most simple
language, so as to make it understood by all concerned. However, it
should be noted that simplicity of a hypothesis is not related to its
significance.

(vi) a hypothesis must be consistent and derived from the most known
facts. In other words, it should be consistent with a substantial body
of established facts. That is, it must be in the form of a statement
which judges accept as being the most likely to occur.



317



(vii) a hypothesis must be amenable to testing within a stipulated or
reasonable period of time. No matter how excellent a hypothesis, a
researcher should not use if it cannot be tested within a given period
of time, as none can afford to spend a life-time on collecting data to
test it.

(viii) a hypothesis should state the facts that gave rise to the necessity of
looking for an explanation. This is to say that by using the
hypothesis, and other known and accepted generalizations, a
researcher must be able to derive the original problem condition.
Therefore, a hypothesis should explain what it actually wants to
explain, and for this it should also have an empirical reference.

1.6.2 Concepts relating to testing of hypotheses

Testing of hypotheses requires a researcher to be familiar with various concepts
concerned with it. They are discussed here.



1) Null hypothesis and alternative hypothesis:

In the context of statistical analysis, hypothesis is of two types, viz., null
hypothesis and alternative hypothesis. When two methods A and B are
compared on their relative superiority, and it is assumed that both the methods
are equally good, then such a statement is called as the null hypothesis. On the
other hand, if method A is considered relatively superior to method B, or vice-
versa, then such a statement is known as an alternative hypothesis. The null
hypothesis is expressed as Ho, while the alternative hypothesis is expressed as
H a . For example, if a researcher wants to test the hypothesis that the population
mean (u) is equal to the hypothesized mean (H ) = 100, then the null hypothesis
should be stated as the population mean is equal to the hypothesized mean 100.
Symbolically it may be written as:-



318



H : = \i =|xH = 100
If sample results do not support this null hypothesis, then it should be
concluded that something else is true. The conclusion of rejecting the null
hypothesis is called as alternative hypothesis. To put it in simple words, the set
of alternatives to the null hypothesis is termed as the alternative hypothesis. If
Ho is accepted, then it implies that H a is being rejected. On the other hand, if Ho
is rejected, it means that H a is being accepted. For H : n = n H =100, the
following three possible alternative hypotheses may be considered (Kothari
1988).



Alternative hypothesis


to be read as follows


H a : |i ^ [i Ho


the alternative hypothesis is that the
population mean is not equal to 100,
i.e., it could greater than or less than
100


H a : |i > |i Ho


the alternative hypothesis is that the
population mean is greater than 100


H a : |i < |i Ho


the alternative hypothesis is that the
population mean is less than 100



Before the sample is drawn, the researcher has to state the null
hypothesis and the alternative hypothesis. While formulating the null
hypothesis, the following aspects need to be considered:

(a) alternative hypothesis is usually the one which a researcher wishes to prove,
whereas the null hypothesis is the one which he/she wishes to disprove.
Thus, a null hypothesis is usually the one which a researcher tries to reject,
while an alternative hypothesis is the one that represents all other
possibilities.

(b) the rejection of a hypothesis when it is actually true involves great risk, as it
indicates that it is a null hypothesis because then the probability of rejecting
it when it is true is a (i.e., the level of significance) which is chosen very
small.



319



(c) Null hypothesis should always be specific hypothesis i.e., it should not state
about or approximately a certain value.

(2) The level of significance:

In the context of hypothesis testing, the level of significance is a very important
concept. It is a certain percentage that should be chosen with great care, reason
and thought. If for instance, the significance level is taken at 5 per cent, then it
means that Ho would be rejected when the sampling result has a less than 0.05
probability of occurrence when Ho is true. In other words, the five per cent level
of significance implies that the researcher is willing to take a risk of five per
cent of rejecting the null hypothesis, when (H ) is actually true. In sum, the
significance level reflects the maximum value of the probability of rejecting Ho
when it is actually true, and which is usually determined prior to testing the
hypothesis.

(3) Test of hypothesis or decision rule

Suppose that the given hypothesis is Ho and the alternative hypothesis Ha, then
the researcher has to make a rule known as the decision rule. According to the
decision rule, the researcher accepts or rejects Ho. For example, if the Ho is that
certain students are good against the H a that all the students are good, then the
researcher should decide the number of items to be tested and the criteria on the
basis of which to accept or reject the hypothesis.

(4) Type I and Type II errors

As regards the testing of hypotheses, a research can make basically two types of
errors. He/she may reject Ho when it is true, or accept Ho when it is not true.
The former is called as Type I error and the latter is known as Type II error. In
other words, Type I error implies the rejection of a hypothesis when it must have
been accepted, while Type II error implies the acceptance of a hypothesis which



320



must have been rejected. Type I error is denoted by a (alpha) and is known as a
error, while Type II error is usually denoted by P (beta) and is known as [3 error.
(5) One-tailed and two-tailed tests

These two types of tests are very important in the context of hypothesis testing.
A two-tailed test rejects the null hypothesis, when the sample mean is
significantly greater or lower than the hypothesized value of the mean of the
population. Such a test is suitable when the null hypothesis is some specified
value, the alternative hypothesis is a value that is not equal to the specified value
of the null hypothesis.
1.6.3 Procedure of hypothesis testing

Testing a hypothesis refers to verifying whether the hypothesis is valid or not.
Hypothesis testing attempts to check whether to accept or not to accept the null
hypothesis. The procedure of hypothesis testing includes all the steps that a
researcher undertakes for making a choice between the two alternative actions of
rejecting or accepting a null hypothesis. The various steps involved in
hypothesis testing are as follows:-

(i) Making a formal statement: This step involves making a formal
statement of the null hypothesis (Ho) and the alternative hypothesis (H a ). This
implies that the hypotheses should be clearly stated within the purview of the
research problem. For example, suppose that a school teacher wants to test the
understanding capacity of the students which must be rated more than 90 per
cent in terms of marks. In this case, the hypotheses may be stated as follows:-
Null Hypothesis H : =100
Alternative Hypothesis H a : > 100

(ii) Selecting a significance level: The hypotheses should be tested on a
pre-determined level of significance, which should be specified. Usually, either



321



5% level or 1% level is considered for the purpose. The factors that determine
the levels of significance are: (a) the magnitude of difference between the
sample means; (b) the sample size: (c) the variability of measurements within
samples; and (d) whether the hypothesis is directional or non-directional
(Kothari 1988). In sum, the level of significance should be sufficient in the
context of the nature and purpose of enquiry.

(iii) Deciding the distribution to use: After making decision on the level of
significance for hypothesis testing, the research has to next determine the
appropriate sampling distribution. The choice to be made generally relates to
normal distribution and the t-distribution. The rules governing the selection of
the correct distribution are similar to the ones already discussed with respect to
estimation.

(iv) Selection of a random sample and computing an appropriate value:
Another step involved in hypothesis testing is the selection of a random sample
and then computing a suitable value from the sample data relating to test statistic
by using the appropriate distribution. In other words, it involves drawing a
sample for furnishing empirical data.

(v) Calculation of the probability: The next step for the researcher is to
calculate the probability that the sample result would diverge as far as it can
from expectations, under the situation when the null hypothesis is actually true.
(vi) Comparing the probability: Another step involved consists of making a
comparison of the probability calculated with the specified value for a, the
significance level. If the calculated probability works out to be equal to or
smaller than the a value in case of one-tailed test, then the null hypothesis is to
be rejected. On the other hand, if the calculated probability is greater, then the
null hypothesis is to be accepted. In case the null hypothesis H is rejected, the
researcher runs the risk of committing the Type I error. But, if the null



322



hypothesis Ho is accepted, then it involves some risk (which cannot be specified
in size as long as Ho is vague and not specific) of committing the Type II error.
1.7 Sample Survey

A sample design is a definite plan for obtaining a sample from a given
population (Kothari 1988). Sample constitutes a certain portion of the
population or universe. Sampling design refers to the technique or the
procedure the researcher adopts for selecting items for the sample from the
population or universe. A sample design helps to decide the number of items to
be included in the sample, i.e., the size of the sample. The sample design should
be determined prior to data collection. There are different kinds of sample
designs which a researcher can choose. Some of them are relatively more
precise and easier to adopt than the others. A researcher should prepare or select
a sample design, which must be reliable and suitable for the research study
proposed to be undertaken.



1.8.1 Steps in sampling design

A researcher should take into consideration the following aspects while
developing a sample design:

(i) Type of universe: The first step involved in developing sample design is to
clearly define the number of cases, technically known as the Universe, to be
studied. A universe may be finite or infinite. In a finite universe the number of
items is certain, whereas in the case of an infinite universe the number of items
is infinite (i.e., there is no idea about the total number of items). For example,
while the population of a city or the number of workers in a factory comprise
finite universes, the number of stars in the sky, or throwing of a dice represent
infinite universe.



323



(ii) Sampling unit: Prior to selecting a sample, decision has to be made about
the sampling unit. A sampling unit may be a geographical area like a state,
district, village, etc., or a social unit like a family, religious community, school,
etc., or it may also be an individual. At times, the researcher would have to
choose one or more of such units for his/her study.

(iii) Source list: Source list is also known as the 'sampling frame', from which
the sample is to be selected. The source list consists of names of all the items of
a universe. The researcher has to prepare a source list when it is not available.
The source list must be reliable, comprehensive, correct, and appropriate. It is
important that the source list should be as representative of the population as
possible.

(iv) Size of sample: Size of the sample refers to the number of items to be
chosen from the universe to form a sample. For a researcher, this constitutes a
major problem. The size of sample must be optimum. An optimum sample may
be defined as the one that satisfies the requirements of representativeness,
flexibility, efficiency, and reliability. While deciding the size of sample, a
researcher should determine the desired precision and the acceptable confidence
level for the estimate. The size of the population variance should be considered,
because in the case of a larger variance generally a larger sample is larger
required. The size of the population should considered, as it also limits the
sample size. The parameters of interest in a research study should also be
considered, while deciding the sample size. Besides, costs or budgetary
constraint also plays a crucial role in deciding the sample size.
(a) Parameters of interest: The specific population parameters of interest
should also be considered while determining the sample design. For example,
the researcher may want to be estimating the proportion of persons with certain
characteristic in the population, or may be interested in knowing some average



324



regarding the population. The population may also consist of important sub-
groups about whom the researcher would like to make estimates. All such
factors have strong impact on the sample design the researcher selects.

(b) Budgetary constraint: From the practical point of view, cost
considerations exercise a major influence on the decisions relating to not only
the sample size, but also on the type of sample selected. Thus, budgetary
constraint could also lead to the adoption of a non-probability sample design.

(c) Sampling procedure: Finally, the researcher should decide the type of
sample or the technique to be adopted for selecting the items for a sample. This
technique or procedure itself may represent the sample design. There are
different sample designs from which a researcher should select one for his/her
study. It is clear that the researcher should select that design which, for a given
sample size and budget constraint, involves a smaller error.

1.7.2 Criteria for selecting a sampling procedure

Basically, two costs are involved in a sampling analysis, which govern the

selection of a sampling procedure. They are:-

(i) the cost of data collection, and

(ii) the cost of drawing incorrect inference from the selected data.

There are two causes of incorrect inferences, namely systematic bias and

sampling error. Systematic bias arise out of errors in the sampling procedures.

They cannot be reduced or eliminated by increasing the sample size. Utmost,

the causes of these errors can be identified and corrected. Generally a

systematic bias arises out of one or more of the following factors:

a. inappropriate sampling frame,

b. defective measuring device,

c. non-respondents,

d. indeterminacy principle, and

e. natural bias in the reporting of data.



325



Sampling errors refers to the random variations in the sample estimates around
the true population parameters. Because they occur randomly and likely to be
equally in either direction, they are of compensatory type, the expected value of
which errors tend to be equal to zero. Sampling error tends to decrease with the
increase in the size of the sample. It also becomes smaller in magnitude when
the population is homogenous.

Sampling error can be computed for a given sample size and design. The
measurement of sampling error is known as 'precision of the sampling plan'.
When the sample size is increased, the precision can be improved. However,
increasing the sample size has its own limitations. The large sized sample not
only increases the cost of data collection, but also increases the systematic bias.
Thus, an effective way of increasing the precision is generally to choose a better
sampling design, which has smaller sampling error for a given sample size at a
specified cost. In practice, however, researchers generally prefer a less precise
design owing to the ease in adopting the same, in addition to the fact that
systematic bias can be controlled better way in such designs.

In sum, while selecting the sample a researcher should ensure that the
procedure adopted involves a relatively smaller sampling error and helps to
control systematic bias.

1.7.3 Characteristics of a good sample design
The following are the characteristic features of a good sample design:

(a) the sample design should yield a truly representative sample;

(b) the sample design should be such that it results in small sampling error;

(c) the sample design should be viable in the context of budgetary
constraints of the research study;

(d) the sample design should be such that the systematic bias can be
controlled; and

(e) the sample must be such that the results of the sample study would be
applicable, in general, to the universe at a reasonable level of confidence.



326



1.7.4 Different types of sample designs

Sample designs may be classified into different categories based on two factors,
namely, the representation basis and the element selection technique. Under the
representation basis, the sample may be classified as:-

I. non-probability sampling

II. probability sampling

While probability sampling is based on random selection, the non-
probability sampling is based on 'non-random' sampling.
I. Non-probability sampling:

Non-probability sampling is the sampling procedure that does not afford any
basis for estimating the probability that each item in the population would have
an equal chance of being included in the sample. Non-probability sampling is
also known as deliberate sampling, judgment sampling and purposive sampling.
Under this type of sampling, the items for the sample are deliberately chosen by
the researcher; and his/her choice concerning the choice of items remains
supreme. In other words, under non-probability sampling the researchers select
a particular unit of the universe for forming a sample on the basis that the small
number that is thus selected out of a huge one would be typical or representative
of the whole population. For example, to study the economic conditions of
people living in a state, a few towns or village may be purposively selected for
an intensive study based on the principle that they are representative of the
entire state. In such a case, the judgment of the researcher of the study assumes
prime importance in this sampling design.

Quota sampling: Quota sampling is also an example of non-probability
sampling. Under this sampling, the researchers simply assume quotas to be



327



filled from different strata, with certain restrictions imposed on how they should
be selected. This type of sampling is very convenient and is relatively less
expensive. However, the samples selected using this method certainly do not
satisfy the characteristics of random samples. They are essentially judgements
samples and inferences drawn based on the would not be amenable to statistical
treatment in a formal way.
II. Probability Sampling:

Probability sampling is also known as 'choice sampling' or 'random sampling'.
Under this sampling design, every item of the universe has an equal chance of
being included in the sample. In a way, it is a lottery method under which
individual units are selected from the whole group, not deliberately, but by using
some mechanical process. Therefore, only chance determines whether an item
or the other would be included in the sample or not. The results obtained from
probability or random sampling would be assured in terms of probability. That
is, the researcher can measure the errors of estimation or the significance of
results obtained from the random sample. This is the superiority of random
sampling design over the deliberate sampling design. Random sampling
satisfies the law of Statistical Regularity, according to which if on an average
the sample chosen is random, then it would have the same composition and
characteristics of the universe. This is the reason why the random sampling
method is considered the best technique of choosing a representative sample.
The following are the implications of the random sampling:

(i) it provides each element in the population an equal probability chance of
being chosen in the sample, with all choices being independent of one
another; and

(ii) it offers each possible sample combination an equal probability
opportunity of being selected.

1.7.5 Method of selecting a random sample

328



The process of selecting a random sample involves writing the name of each
element of a finite population on a slip of paper and putting them into a box or a
bag. Then they have to be thoroughly mixed and then the required number of
slips for the sample should be picked one after the other without replacement.
While doing this, it has to be ensured that in successive drawings each of the
remaining elements of the population has an equal chance of being chosen. This
method would result in the same probability for each possible sample.
1.7.6 Complex random sampling designs

Under restricted sampling technique, the probability sampling may result in
complex random sampling designs. Such designs are known as mixed sampling
designs. Many of such designs may represent a combination of non-probability
and probability sampling procedures in choosing a sample. Few of the
prominent complex random sampling designs are as follows:
(i) Systematic sampling: In some cases, the best way of sampling is to select
every ith item on a list. Sampling of this kind is called as systematic sampling.
An element of randomness is introduced in this type of sampling by using
random numbers to select the unit with which to start. For example, if a 10 per
cent sample is required, the first item would be selected randomly from the first
and thereafter every 10 l item. In this kind of sampling, only the first unit is
selected randomly, while rests of the units of the sample are chosen at fixed
intervals.

(ii) Stratified sampling: When a population from which a sample is to be
selected does not comprise a homogeneous group, stratified sampling technique
is generally employed for obtaining a representative sample. Under stratified
sampling, the population is divided into many sub-populations in such a manner
that they are individually more homogeneous than rest of the total population.



329



Then, items are selected from each stratum to form a sample. As each stratum is
more homogeneous than the remaining total population, the researcher would be
able to obtain a more precise estimate for each stratum and by estimating more
accurately each of the component parts, he/she is able to obtain a better estimate
of the whole. In some stratified sampling method yields a more reliable and
detailed information.

(iii) Cluster sampling: When the total area of research interest is large, a
convenient way in which a sample may be selected is to divide the area into a
number of smaller non-overlapping areas and then randomly selecting a number
of such smaller areas. In the process, the ultimate sample would consist of all
the units in these small areas or clusters. Thus in cluster sampling, the total
population is sub-divided into numerous relatively smaller subdivisions, which
in themselves constitute clusters of still smaller units. And then, some of such
clusters would be randomly chosen for inclusion in the overall sample.
(iv) Area sampling: When clusters are in the form of some geographic
subdivisions, then cluster sampling is termed as area sampling. That is, when
the primary sampling unit represents a cluster of units based on geographic area,
the cluster designs are distinguished as area sampling. The merits and demerits
of cluster sampling is equally applicable to area sampling.

(iv) Multi-stage sampling: A further development of the principle of cluster
sampling is multi-stage sampling. When the researcher desires to investigate the
working efficiency of nationalized banks in India and a sample of few banks is
required for this purpose, the first stage would be to select large primary
sampling unit like the states in the country. Next, certain districts may be
selected and all banks interviewed in the chosen districts. This represents a two-
stage sampling design, with the ultimate sampling units being clusters of
districts.



330



On the other hand, if instead of taking census of all banks within the
selected districts, the researcher chooses certain towns and interviews all banks
in it, this would represent three-stage sampling design. Again, if instead of
taking a census of all banks within the selected towns, the researcher randomly
selects sample banks from each selected town, then it represents a case of using
a four-stage sampling plan. Thus, if the researcher selects randomly at all
stages, then it is called as multi-stage random sampling design.
(vi) Sampling with probability proportional to size: When the case of cluster
sampling units does not have exactly or approximately the same number of
elements, it is better for the researcher to adopt a random selection process,
where the probability of inclusion of each cluster in the sample tends to be
proportional to the size of the cluster. For this, the number of elements in each
cluster has to be listed, irrespective of the method used for ordering it. Then the
researcher should systematically pick the required number of elements from the
cumulative totals. The actual numbers thus chosen would not however reflect
the individual elements, but would indicate as to which cluster and how many
from them are to be chosen by using simple random sampling or systematic
sampling. The outcome of such sampling is equivalent to that of simple random
sample. The method is also less cumbersome and is also relatively less
expensive.

Thus, a researcher has to pass through various stages of conducting
research once the problem of interest has been selected. Research methodology
familiarizes a researcher with the complex scientific methods of conducting
research, which yields reliable results that are useful to policy-makers,
government, industries, etc., in decision-making.

References:

331



Claire Sellitiz and others, Research Methods in Social Sciences, 1962, p. 50

DollardJ., Criteria for the life-history, Yale University Press, New York,1935,

pp.8-31.

C.R. Kothari, Research Methodology, Methods and Techniques, Wiley

Eastern Limited, New Delhi, 1988.

Marie Jahoda, Morton Deutsch and Staurt W. Cook, Research Methods in

Social Relations, p. 4.

Pauline V. Young, Scientific Social Surveys and Research, p. 30

L.V. Redman and A.V.H. Mory, The Romance of Research, 1923.

The Encylopaedia of Social Sciences, Vol. IX, MacMillan, 1930.

T.S. Wilkinson and P.L. Bhandarkar, Methodology and Techniques of Social

Research, Himalaya Publishing House, Bombay, 1979.

Questions:

1 . Define research.

2. What are the objectives of research?

3. State the significance of research.

4. What is the importance of knowing how to do research?

5. Briefly outline research process

6. Highlight the different research approaches.

7. Discuss the qualities of a researcher.

8. Explain the different types of research.

9. What is a research problem?

10. Outline the features of research design.

11. Discuss the features of a good research design.

12. Describe the different types of research design.

13. Explain the significance of research design.

14. What is a case study?

15. Discuss the criteria for evaluating case study.

16. Define hypothesis.

17. What are the characteristic features of a hypothesis?

18. Distinguish between null and alternative hypothesis.

19. Differentiate Type I error and Type II error.

20. How is a hypothesis tested?

21. Define the concept of sampling design.

22. Describe the steps involved in sampling design.

23. Discuss the criteria for selecting a sampling procedure.

24. Distinguish between probability and non-probability sampling.

25. How is a random sample selected?

26. Explain complex random sampling designs.



332



'k-k'k



333



UNIT— II



DATA COLLECTION



Z

o

x/i

w



1



SOURCES OF DATA



LESSON OUTLINE

Primary data-
Methods of collecting primary data-
Direct personal investigation
Indirect oral interviews
Information received through local
agencies

Mailed questionnaire method
Schedules sent through enumerators



334



Learning Objectives

After reading this lesson you
should be able to

• Understand the meaning of
primary data

• Preliminaries of data
collection

• Method of data collection

• Methods of collecting
primary data

• Usefulness of primary data

• Merits and demerits of
different methods of
primary data collection

• Pre cautions while collecting
primary data.



Introduction

It is important for a researcher to know the sources of data which he requires for
his different purposes. Data are nothing but the information. There are two
sources of information or to say data- Primary data and Secondary data. Primary
data mean the data collected for the first time, whereas secondary data mean the
data that have already been collected and used earlier by somebody or some
agency. For example, the statistics collected by the Government of India relating
to the population, are primary data for the Government of India since it has been
collected for the first time. Later when the same data are used by a researcher for
his study of a particular problem, then the same data become the secondary data
for the researcher.

Both the sources of information have their merits and demerits. The
selection of a particular source depends upon-(a) Purpose and scope of enquiry ;
(b) availability of time ;(c) availability of finance and;(d) accuracy required, (e)
Statistical units to be used (f) Sources of information (data) and (g) Method of
data collection. Let us discuss the above points in short.

(a) Purpose and scope of enquiry:-The purpose and scope of data
collection or survey should be clearly set out at the very beginning. It requires
the clear statement of the problem indicating the type of information which is
needed and the use to which it is needed .If for example, the researcher is
interested in knowing the nature of price change over a period of time, it would
be necessary to collect data of commodity prices and it must be decided whether
it would be helpful to study wholesale or retail prices and the possible uses to
which such information could be put. The objective of an enquiry may be either
to collect specific information relating to a problem or adequate data to test a



335



hypothesis. Failure to set out clearly the purpose of enquiry is bound to lead to
confusion and waste of resources.

After the purpose of enquiry has been clearly defined, the next step is to
decide about the scope of the enquiry. Scope of the enquiry means the coverage
with regard to the type of information, the subject-matter and geographical area.
For instance, an enquiry may relate to India as a whole or a state or an industrial
town where in a particular problem related to a particular industry can be
studied.

(b)Availability of time:- The investigation should be carried out within a
reasonable period of time; otherwise the information collected may become
outdated, and have no meaning at all. For instance, if a producer wants to know
the expected demand of a product newly launched by him and the result of the
enquiry that the demand would be meager, takes two years to reach to him then
the whole purpose of enquiry would become useless because by that time he
would have already received a huge loss. Thus in this respect the information is
quickly required and hence the researcher has to choose the type of enquiry
accordingly.

I Availability of resources:- The investigation will greatly depend on the
resources available like number of skilled personnel, the amount etc. If the
number of skilled personnel who will carry out the enquiry is quite sufficient
and the amount is not a problem then the enquiry can be conducted over a big
area covering a good number of samples otherwise a small sample size will do.
(d)The degree of accuracy desired:- Deciding the degree required is must for
the investigator, because absolute accuracy in statistical work is seldom
achieved. This is so because (a) statistics are based on estimates, (b) tools of
measurement are not always perfect and (c) there may be unintentional bias on
the part of the investigator,, enumerator or informant. Therefore, a desire of



336



100% accuracy is bond to remain unfulfilled. Degree of accuracy desired
primarily depends upon the object of enquiry. For example when we buy gold
even a difference of 1/1 l gram in its weight is significant whereas the same
will not be the case when we buy rice or wheat. However, the researcher must
aim at attaining a higher degree of accuracy otherwise the whole purpose of
research would become meaningless.

(e) Statistical Units to be used: A well defined and identifiable object or a
group of objects with which the measurements or counts in any statistical
investigation are associated is called a statistical unit. For example, in socio-
economic survey the unit may be an individual person, a family, a household or
a block of locality. A very important step before the collection of data begins is
to define clearly the statistical units on which the data are to be collected. In
number of situations the units are conventionally fixed like the physical units of
measurement such as metres, kilometers, quintals, hours, days, week etc., which
are well defined and do not need any elaboration or explanation. However in
many statistical investigations, particularly relating to socio-economic studies,
arbitrary units are used which must be clearly defined. This is must because in
the absence of a clear cut and precise definition of the statistical units, serious
errors in the data collection may be committed in the sense that we may collect
irrelevant data on the items, which should have, in fact, been excluded and omit
data on certain items which should have been included. This will ultimately lead
to fallacious conclusions.

(f) Sources of information (data):- After decided about the unit, a researcher
has to decide about the source from which the information can be obtained or
collected. For any statistical inquiry, the investigator may collect the data first
hand or he may use the data from other published sources such as the



337



publications of the government/semi-government organizations or journals and
magazines etc.

(g) Method of data collection:- There is no problem if secondary data are used
for the research . However, if primary data are to be collected a decision has to
be taken whether (i) census method or (ii) sample technique, is to be used for
data collection .In census method we go for total enumeration i.e. all the units of
a universe have to be investigated. But in sample technique, we inspect or study
only a selected representative and adequate fraction of the population and after
analyzing the results of the sample data we draw conclusions about the
characteristics of the population. Selection of a particular technique becomes
difficult because where population or census method is more scientific and
100% accuracy can be attained through this method, choosing this becomes
difficult because it is time taking, it requires more labor and after all it is very
expensive. Therefore, for a single researcher or for a small institution it proves
to be unsuitable. On the other hand, sample method is less time taking, less
laborious and less expensive but a 100% accuracy cannot be attained through
this method because of sampling and non sampling errors attached to this
method. Hence, a researcher has to be very cautious and careful while choosing
a particular method.
Methods of collecting Primary data
Primary data may be obtained by applying any of the following methods-

1 . Direct Personal Interviews

2. Indirect oral interviews.

3. Information from correspondents.

4. Mailed questionnaire methods.

5. Scheduled sent through enumerators.



338



1. Direct personal interviews:- A face to face contact is made with the
informants(persons from whom the information is to be obtained) under this
method of collecting data. The interviewer asks them questions pertaining to the
survey and collects the desired information. Thus, if a person wants to collect
data about the working conditions of the workers of the Tata Iron and Steel
Company, Jamshedpur, he would go to the factory, contact the workers and
obtain the desired information. The information collected in this manner is first
hand and also original in character.

There are many merits and demerits of this method which is discussed below:-
Merits

1. Most often respondents are happy to pass on the information required
from them when contacted personally and thus response is encouraging.

2. The information collected through this method is normally more accurate
because the interviewer can clear up doubts of the informants about
certain questions and thus obtain correct information. In case the
interviewer apprehends that the informant is not giving accurate
information, he may cross-examine him and thereby try to obtain the
information.

3. This method also provides the scope for getting the supplementary
information from the informant because while interviewing it is possible
to ask some supplementary questions which may be of great use latter.

4. It is experienced that there are some difficult questions which normally
becomes difficult to ask directly but a trained and experienced researcher
can sandwiched the difficult questions between other questions and get
the desired information. He can twist the questions keeping in mind the
informant's reaction. Precisely, a delicate situation can usually he



339



handled more effectively by a personal interview than by other survey

techniques.
5. The interviewer can adjust the language according to the status and

educational level of the person interviewed, and thereby can avoid

inconvenience and misinterpretation on the part of the informant.
Demerits: There are some demerits or limitations of this method which are
explained below:

1. This method can prove to be expensive if the number of informants is
large and the area is wide spread

2. There is a greater chance of personal bias and prejudice under this
method as compared to other method.

3. The interviewers have to be thoroughly trained and experienced
otherwise they may not be able to obtain the desired information.
Untrained or poorly trained interviewers may spoil the entire work.

4. This method is more time taking as compared to others. This is because
interviews can be held only at the convenience of the informants. Thus,
if information is required to be obtained from the working members of
households, interviews will have to be held in the evening or on week
end. Even during evening only an hour or two can be used for interviews
and hence, the work may have to be continued for a long time, or a large
staff may have to be employed which may involve huge expense.

Conclusion:-Though there are some demerits in this method of data collection
still we cannot say that it is not useful. The matter of fact is that this method is
suitable for intensive rather than extensive field surveys. Hence, it should be
used only in those cases where intensive study of a limited field is desired.



340



In the present time of extreme advancement in the communication system,
the investigator instead of going personally and conducting a face to face
interview may also obtain information on telephone. A good number of surveys
are being conducted every day by newspapers and television channels by
sending the reply either by e-mail or SMS. This method has become very
popular nowadays as it is less expensive and the response is extremely quick.
But this method suffers from some serious defects as - (a) very few people own
a phone or a television and hence a limited type of people can be approached by
this method,(b) only few questions can be asked over phone or through
television,(c) the respondents may give a vague and reckless answers because
answers on phone or through SMS would have to be very short.
2.1ndirect Oral Interviews:- Under this method of data collection, the
investigator contacts third parties generally called 'witnesses' who are capable
of supplying necessary information. This method is generally adopted when the
information to be obtained is of a complex nature and informants are not
inclined to respond if approached directly. For example, when the researcher is
trying to obtain data on drug addiction or the habit of taking liquor, there is high
probability that the addicted person will not supply the desired data and hence
disturb the whole research process. In this situation taking the help of such
persons or agency or the neighbour who know them well becomes necessary.
Since these people know the person well and hence, they can supply the desired
data. Enquiry Committees and Commissions appointed by the Government
generally adopt this method to get people's views and all possible details of
facts relating to the enquiry.

Though this method is very popular, its correctness depends upon a number of
factors which is discussed below: -



341



1. The person or persons or agency whose help is solicited must be of proven
integrity otherwise any bias or prejudiced on the part of them will not bring
the correct information and the whole process of research will become
useless.

2. The ability of the interviewers to draw out the information from witnesses
by means of appropriate questions and cross-examination.

3. It might happen that because of bribery, nepotism or certain other reasons
those who are collecting the information give it such a twist that correct
conclusions are nor arrived at.

Therefore, for the success of this method it is necessary that the evidence of
one person alone is not relied upon. Views from other persons and related
agencies should also be ascertained to find the real position .Utmost care must
be exercised in the selection of these persons because it is on their views that the
final conclusions are reached.

3. Information from Correspondents:- The investigator appoints local agents
or correspondents in different places to collect information under this method.
These correspondents collect and transmit the information to the central office
where data are processed. This method is generally adopted by news paper
agencies. Correspondents who are posted at different places supply information
relating to such events as accidents, riots, strikes, etc., to the head office. The
correspondents are generally paid staff or sometimes they may be honorary
correspondents also. This method is also adopted generally by the government
departments in such cases where regular information is to be collected from a
wide area. For example, in the construction of a wholesale price index numbers
regular information is obtained from correspondents appointed in different areas.
The biggest advantage of this method is that it is cheap and appropriate for
extensive investigation. But a word of caution is that it may not always ensure



342



accurate results because of the personal prejudice and bias of the
correspondents.

As already stated earlier, this method is suitable and adopted in those cases
where the information is to be obtained at regular intervals from a wide area.
1. Mailed Questionnaire Method:- Under this method, a list of questions
pertaining to the survey which is known as 'Questionnaire' is prepared
and sent to the various informants by post. Sometimes the researcher
himself too contacts the respondents and gets the responses relating to
the various questions in the questionnaire. The questionnaire contains
questions and provides space for answers. A request is made to the
informants through a covering letter to fill up the questionnaire and
send it back within a specified time.

The questionnaire studies can be classified on the basis of:
i. The degree to which the questionnaire is formalized or structured,

ii. The disguise or lack of disguise of the questionnaire , and

iii. The communication method used.

When no formal questionnaire is used, interviewers adapt their questioning
to each interview as it progresses or perhaps elicit responses by indirect methods
such as showing pictures on which the respondent comments. When a researcher
follows a prescribed sequence of questions, it is referred to as structured study.
On the other hand, when no prescribed sequence of questions exists, the study is
non-structured.

When questionnaires are constructed so that the objective is clear to the
respondents then these questionnaires are known as non- disguised; on the other
hand, when the objective is not clear the questionnaire is a disguised one. On the
basis of these two classifications, four types of studies can he distinguished:
i. Non-disguised structured,



343



ii. Non-disguised non-structured,

iii. Disguised structured, and

iv. Disguised non-structured.

There are certain merits and demerits or limitations of this method of data
collection which are discussed below:
Merits:

2. Questionnaire method of data collection can be easily adopted where
the field of investigation is very vast and the informants are spread over
a wide geographical area.

3. This method is relatively cheap and expeditious provided the
informants respond in time.

4. This method is pr…