Module I

Fundamentals of Social Research

Research simply means a search for facts – answers to questions and solutions to
problems. It is a purposive investigation. It is an organized inquiry. It seeks to find
explanations to unexplained phenomenon, to clarify the doubtful propositions and to
correct the misconceived facts.

Social Sciences

Sciences are broadly divided into natural (or physical) science and social sciences.
Social sciences include various disciplines dealing with human life, human behaviour,
social groups and social institutions. They consist of anthropology, behaviour science,
commerce, demography, economics, education, geography, history, law, linguistics,
management, political science, psychology, public administration, sociology and social
work. .
Social sciences are not exact science like physical sciences, they deal with human
beings. Human nature and man’s environment are so complex that it is more difficult
comprehend and predict human behaviour than the physical phenomena.

Social science research

Social science research is a systematic method of exploring, analyzing and

conceptualizing human life in order to extend, correct or verify knowledge of human
behaviour and social life. In other words, social science research ‘seek to find explanations
to unexplained social phenomena, to clarify the doubtful, and correct the misconceived
facts of social life.’

According to P.V. Young, we may define social research as “the systematic method of
discovering new facts and verifying old facts. Their sequences inter relationship, causal

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explanations and the natural laws govern them”. From the above definition we can identify
the following,

Characteristics of Social Research

• Social research deals with social phenomena. It studies human behavior and their
feelings.
• Social research is carried on both for discovering new facts and verification of the
old ones.
• Social research tries to establish casual connection between various human
activities.

Objectives of Social Research

The major objectives of social research are listed as follows:-

a) The aim of social research is to discover new facts and verifying or testing old facts.
b) It tries to understand the human behavior and its interaction with the environment.
c) It tries to find out the casual connection between human activities and natural laws
governing them.

Functions of Social Science Research

The important functions of social science research are discussed below;

a) Discovery of facts and their interpretation.

Social research provides answer to questions of what, when, how and why of man, social
life and institutions. Discover of facts and their inter relationship help us to discard
distortions and contribute to our understanding of social reality.

b) Diagnosis of problems and their analysis.

Our society has innumerable problems such as poverty, unemployment, economic
inequality, social tension etc,. The nature and dimensions of such problems have to be

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diagnosed and analyzed. An analysis of problems leads to an identification of appropriate
remedial actions.
c) Systematization of knowledge.
The facts discovered through research are systematized and the body of knowledge is
developed. It contributes to the growth of theory building.

d) Control over social phenomena.

Research in social science provides first hand information about the nature of social
institutions. This knowledge helps us to control over the social phenomena.

e) Prediction.
Social research aims at finding an order among social fact and their casual relations. This
affords a sound basis for prediction in several cases.

f) Development planning.
Systematic research can give us the required data base for planning and designing
developmental schemes and programmes.

g) Social welfare.
Social research can identify the causes of social evils and problems. It can thus help in
taking appropriate remedial actions. It also provides guideline for social welfare.

Scope of Social Science Research

The fields of social science research unlimited and the materials of research are endless.
Every group of social phenomena, every phase of human life and every stages of past and
present development are materials for the social scientist. The area of research in various
social sciences provides vast scope for research in social sciences.

The main scope of social research are :

• Social research provides new insight in to the organized society and its social
structure.

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 • Social research also provide new horizon in scientific explanation; advanced and
tested principles of procedure and suggested new concepts.
• Another scope of social research is that exemplified by studies and attempt to test
or challenge existing theories and revise them the light of new evidence.
• Social research helpful to establish new theory and established techniques of
exploration.
• Social research also provides contributions to existing stone of fruitful ideas,
methodology and basis understanding of social life and control of its problems.

Types of Research

Pure Research
Pure research is undertaken for the sake of knowledge without any intention to
apply it in practice, e.g., Einstein’s theory of relativity, Newton’s contributions, Galileo’s
contribution etc.

Pure research is also known as basic or fundamental research. It is undertaken out

of intellectual curiosity or inquisitiveness. It is not necessarily problem oriented. It aims
at extension of knowledge. It may be lead to either discovery of a new theory or refinement
of an existing theory. The development of various sciences owes much to pure research.
The findings of pure research enrich the storehouse of knowledge that can be drawn upon
in the future to formulate significant practical researches. Pure research lays the foundation
for applied research. The findings of pure research formed the basis for innumerable
scientific and technological inventions like steam engine, machines, automobiles,
electronic gadgets, electronic data processing etc., which have revolutionized and enriched
our human life.

Contribution of pure research

• By developing principle, pure research offers solutions to many practical problems

• Pure research helps to find the critical factors in a practical problem

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 • Pure research develops many alternative solutions and thus enables us to choose
the best solution

Applied Research

Applied research is carried on to find solution to a real – life problem requiring an

action or poly decision. It is thus problem oriented and action directed. It seeks an
immediate and practical result, e.g., marketing research carried on for developing a new
market or for studying the post purchase experience of customers.
There is vast scope for applied research in the fields of technology, management,
commerce, economics and other social sciences. Innumerable problems are faced in these
areas. They need empirical study fro finding solutions.
Though the immediate purpose of an applied research is to find solutions to a
practical problem, it may incidentally contribute to the development of theoretical
knowledge by leading to the discovery of new facts or testing of a theory or to conceptual
clarity.

Contribution of Applied Research

• Applied research can contribute new facts.
• Applied research can put theory to the test.
• Applied research may aid in conceptual clarification
• Applied research may integrate previously existing theories

The interplay between pure and applied research

The distinction between pure and applied research is not absolute, but at best only
relative, for pure research may have significant potential for its application to the solution
of a practical problem now or later; and applied research may end up making a scientific
contribution to the development of theoretical knowledge.

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Action Research

Action research is a type of evaluation study. It is a concurrent evaluation study of

an action programme launched for solving a problem / for improving an existing situation.
In the quest for development, advancement, excellence and promotion of welfare
of people, government, institutions and voluntary agencies undertake action programmes
for achieving specific goals or objectives. Land reform programmes, agricultural extension
programmes, social welfare programmes, programmes for improving the quality of life in
factories and offices, etc., are some examples of action programmes.

The phases in the action research

The different phases in the action research are:
• a baseline survey of the pre-action situation
• a feasibility study of the proposed action programme
• planning and launching the programme
• concurrent evaluation of the programme
• making modifications and changes in the programme and its method of
implementation in the light of the research findings; and
• final evaluation, if the programme is time-bound

The success of the action research depends on the cooperation of action implementing
people and the beneficiaries of the action programme.

Research Methods vs Research Methodology

• Research methods are the methods used for data collection in research.
• On the other hand research methodology explains the overarching theoretical and
philosophical frameworks which guide the research.

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 • This highlights that there is a clear difference between the two, Research
methodologies are the overarching frameworks that we use for research. Research
methods are the techniques that we use. Different methodologies employ different
methods. Through this article let us clarify the difference.
What are Research Methods?
• Research methods are the methods used for data collection in research. Research
methods involve surveys, interviews, case studies, observation, experiments, etc.
• In the social sciences the research methods mostly provide the researcher with
quantitative data. However, this does not mean that in social sciences qualitative
data is ignored. On the contrary, a combination of data can be used for social
research.
What is a Research Methodology?
• Research methodology explains the overarching theoretical and philosophical
frameworks which guide the research. Research methodology works as a
framework within which the researcher works.
• It is even accurate to consider it as the inception of the research. For various
researches, the researcher can employ different methodologies. This will allow him
to look at the research problem from different angles and use different methods,
techniques and even perspectives.
Difference Between Research Methods and Research Methodology

Content:
Research Methods: Research methods involve surveys, interviews, case studies,
observation, experiments, etc.
Research Methodology: Research methodology involves the theoretical frameworks and
learning of the various techniques that can be used in the conduct of research and the
conduct of tests, experiments, surveys and critical studies.
Aim:
Research Methods: Research methods aim at finding solutions to research problems.
Research Methodology: Research methodology aims at the employment of the correct
procedures to find out solutions.

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Relationship:
Research Methods: Research methods are the end of any research.
Research Methodology: Research methodology is the beginning.

Scientific Method

• All scientists use common methods for their enquiry.

• All sciences whether natural or social agree up on methods of studying phenomena.
But their materials differ.
• All follows similar scientific methods of inquiry. But their subjects of study are
different.
• Therefore, they use different techniques of investigation for their study. As their
materials are different, their purposes also differ.
• All of them will observe the phenomenon and analyze them to find out their
sequences this is called scientific method.
• Thus scientific method is a systematic step-by-step procedure (three steps-
observation, hypothesis and verification) following logical process of reasoning.
• According to prof. Morgan “scientific method being highly elastic, can be
applicable to all domain of human activity where the discovery of truth is the
objective”.
• Two elements of scientific method are, a) Procedural components and b) Personal
Components.
a) Procedural Components.
Observation, hypothesis and verification are the three procedural components. Observation
helps to collect data and help to build hypothesis. The second step is formation of one or
more hypotheses. A hypothesis is tentative conclusion. It guides collection of data. The
third stage is verification of hypothesis. It is done by analytical tools.
b) Personal Components.
The researcher needs imagination, analytical ability resourcefulness, skill, capacity to find
out the hearts of the problem. Researcher’s ability and attitude are more important than the
method of approach. Ambitions interest and perseverance are very much required to go on

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successfully with research. Researcher should have an objective scientific and professional
qualification and personal quality and interest.

Meaning and essentials of scientific method

Scientific method is a way in which one can test opinion, impressions or guess by
examining available evidences fore and against them. So it is controlling lot of things and
establishing stable belief.
Essentials of scientific method are,
Scientific method aims at discovering facts.
It is itself corrective in nature.
It is itself based on systematic doubts.
Scientific theories are abstract in nature.

Basis of scientific method

Following are the major basis of scientific method,
(a) Reliance on empirical evidence:-
Scientific method involves a systematic process. The answer to a question is not decided
by intuition or imagination. Relevant data are collected through observation and
experimentation. The validity and the reliability of data are checked carefully and the data
are analyzed thoroughly using appropriate methods of analyses.
(b) Use of concepts:-
We use concepts to deal with real facts. Concepts are logical constructs or abstractions
created from sense impressions. They are the symbols representing the meaning that we
hold.
(c) Commitment to objectivity:-
Objectivity is the hallmark of the scientific method. It means forming a judgment upon
facts unbiased by personal impressions. The conclusion should not vary from person to
person. It should be same for all persons.
(d) Ethical neutrality.
Science does not pass normative judgment on facts. It does not say they are good or bad.
Science aims nothing but making true and adequate statements about its object.

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(e) Generalization.
Scientist tries to find out the commonality of a series of event. They aim at discovering the
uniformity. Assumed a discovered uniformity a logical class and it’s observed pattern, a
descriptive generalization is formulated.
(f) Verifiability.
The findings of a research should be verifiable. Scientist must make know to others, how
he arrived at his conclusion. He should thus expose his own methods and conclusions to
critical scrutiny. When others test his conclusion under the same conditions, then it is
accepted as correct.
(g) Logical reasoning process.
The scientist method involves the logical process of reasoning. This reasoning process is
used for drawing inference from the finding of a study or for arriving at conclusion. This
logical reasoning process consists of induction and deduction.

Induction: One of the methods of logical reasoning process. The inductive method consists
of studying several individual cases drawing a generalization. It involves two processes-
observation and generalization. Conclusion from induction method is subjected to further
conformation based on more evidence
Deduction: deduction is reasoning from the general to the particular. This reasoning
establishes a logical relationship between a major premise. A minor premise and a
conclusion. A major premise is a previously established generalization or assumption. A
minor premise is a particular case related to the major premise. The logical relationship of
these premise lead to conclusion.
E.g. major premise: - All men are mortal
Minor premise: - A is a man
Conclusion: - A is mortal.
The logical process of both induction and deduction are useful in research studies. Both
are inseparable parts of a system of reasoning. Both processes are often used
simultaneously.

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Difficulties in the use of scientific methods in social science research
Some theorists argue that scientific method is more applicable to physical or natural
sciences: and it can not applicable to social sciences. The following are the major
difficulties.
a) Human behavior is different. It s very difficult to categories.
b) When human behavior is studied and analyses by another human, there may be personal
problems.
c) Psychological nature of human behavior can not be measurable.
d) Human behavior is not uniformed and predictable. Uncertainty is existing.
e) Difference in choice and decision.

OBJECTIVITY
Objectivity in social research.
• The question of objectivity has been central to the methodological debates of the
social sciences from the beginning. It means the willingness and ability to examine
evidence dispassionately.
• It is the first condition of research.
• Objectivity means basing conclusion on facts without any bias and value
judgement. The conclusion should be independent of one’s personal beliefs, likes
dislikes and hopes.
• Both the data and the inference drawn from their analysis must be free from bias
and prejudices.
• But modern feminist researchers and critical social researchers argued research is a
moral-political activity that requires the researcher to commit to a value position.
Value freedom is a myth.

Factors Affecting Objectivity

It is very difficult to achieve objectivity in social science research. This difficulty arises
out of the adverse influences of (a) personal prejudices and bias, (b) value judgement, (c)
ethical dilemma and (d) complexity of social phenomena.

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Personal prejudices and biases
Prejudices and biases are like fantasies to believe what is comforting to believe. It makes
to believe something without considering evidence.
Value related problem arises
Value related problem arises from the social context with in which research occurs. A
researcher’s attitudes towards socio-economic issues are influenced by his values.
Personal preconceptions
Personal preconceptions of research create not only a distorting effect on the data but are
also highly insidious. Research failed to examination objectivity.
Ethical dilemmas
Research relation with other aspect of research creates ethical problems. E.g. Relation with
sponsors, relation with source data, relation with research subject etc,.

Limits of objectivity in social sciences

Objectivity in social science research has certain limitations, they are:

a) Social scientist is part of human society and their judgements are subjective and coloured
by researchers own experience.
b) The subject matter of social science research is too complex. All propositions are limited
particular social groups and contexts. Thus objectivity in a major issue in social science
research.
c) All members of the society have different values, social researcher will unconsciously
influenced by their values.
d) Social scientist fails to achieve objectivity because the respondents are human beings
have certain human problems. e.g. refusal of respondent, improper understanding,
reluctance etc,. All these problems cause biases and invalidate the research findings and
conclusions.

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Ethical Issues in Social Sciences
• An ethic is more than presence of a basic value or values. It is base of action in any
science.
• Issues of ethics arise primarily out of researcher’s relation with different sections
of society. E.g. research respondents, sponsors’ of research, sources of data etc,.
• When we talk about ‘ethics’ in social research, we are addressing those issues that
concern the behavior of social researcher and the consequences that their research
bring to the people they study.

Some of the ethical issues can arise during the course of the research process:-
• The research problem itself: - determinants of alcoholism or child sexual abuse.
• The research setting:- hospitals, prisons or schools
• The procedure of research: - an experiment method has a negative effect on research
participants.
• The kinds of people serving as research participants:- homeless people, patients,
children and relatively powerless to resist being studied.
• The type of data collected:- sensitive, personal or financial information.
• The pressure put upon research participants by external agencies such as
government, employers etc,.
• The communication of results:- the sponsors withhold certain results that do not
accord with their objectives.
Ethical issues relating to the respondents and subject:-
• Of all ethical issues, the issues concerned with the respondents are far more
important. The respondents constitute the research subjects, Some respondents are
made to participate in a research project without their consent or knowledge; e.g.
socio-anthropological studies of rural or tribal community. The purpose of research
is not fully revealed to the respondents.
• Another non ethical practice is to expose participants to physical or mental stress.
In depth interviews or disguised projective test and participant observation are may
be an attack on privacy.

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• Other ethical issues related to maintaining anonymity of the respondent.
Anonymity might be violated through report and publications.
• Another ethical issue in social science research is related to agency or sponsors of
research. The granting agencies impose several restrictions up on the researcher.
• To overcome above ethical dilemma in social science research, the research must
keep a balance between the moral cost of unethical practices and the potential
benefits of research.

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 MODULE II
Methods and Techniques in Quantitative and Qualitative Research

Qualitative Research- Ethnography and Participant Observation, Structured and Unstructured

interviews, Focus Group Discussions, Case Studies and Oral Narratives
Quantitative research –Social Survey

QUALITATIVE RESEARCH

• Qualitative research is concerned with qualitative phenomenon, i.e., phenomena

relating to or involving quality or kind.
• Qualitative research is specially important in the behvaioural sciences where the aim is
to discover the underlying motives of human behaviour.
• Qualitative research is concerned with subjective assessment of attitudes, opinions and
behaviour.
• Research in such a situation is a function of researcher’s insights and impressions.
• Such an approach to research generates results either in non-quantitative form or in the
form which are not subjected to rigorous quantitative analysis. Generally, the
techniques of focus group interviews, case study, content analysis and narratives are
used.

ETHNOGRAPHY

• The ethnographic approach to qualitative research comes largely from the field of
anthropology.
• The emphasis in ethnography is on studying an entire culture.
• Originally, the idea of a culture was tied to the notion of ethnicity and geographic
location (e.g., the culture of the Trobriand Islands), but it has been broadened to include
virtually any group or organization.
• That is, we can study the "culture" of a business or defined group (e.g., a Rotary club).
• Ethnography is an extremely broad area with a great variety of practitioners and
methods.

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• However, the most common ethnographic approach is participant observation as a part
of field research.
• The ethnographer becomes immersed in the culture as an active participant and records
extensive field notes.
• Thus, ethnography may be defined as both a qualitative research process or method
(one conducts an ethnography) and product (the outcome of this process is an
ethnography) whose aim is cultural interpretation.
• Ethnographers generate understandings of culture through representation of what we
call an emic perspective, or what might be described as the "'insider's point of view."
• An ethnographic understanding is developed through close exploration of several
sources of data. Using these data sources as a foundation, the ethnographer relies on a
cultural frame of analysis.
• Most anthropologists today point to Bronislaw Malinowski, author of such landmark
ethnographies as Argonauts of the Western Pacific (first published in 1922), as a kind
of founding father to ethnographic fieldwork, the practice of “participant-observation.”
• Malinowski’s early twentieth century ethnographies were written in a voice removed
and utterly unrevealing about the nature of the ethnographer and his relationship to
people studied.
• Malinowski’s diaries were published after his death in a revealing autobiographical
account of his inner life while in the field (A Diary in the Strict Sense of the Term, first
published in 1967).
• Of many important lessons for anthropologists, Malinowski’s diaries hold two
especially relevant ones here. First of these is that, at its heart, ethnographic writing is
a means of expressing a shared interest among cultural anthropologists for telling
stories – stories about what it means to be human. T
• he other is that the explicit professional project of observing, imagining and describing
other people need not be incompatible with the implicit personal project of learning
about the self.
• It is the honest truth of fieldwork that these two projects are always implicated in each
other.
• Good ethnography recognizes the transformative nature of fieldwork where as we
search for answers to questions about people we may find ourselves in the stories of
others.

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 • Ethnography should be acknowledged as a mutual product born of the intertwining of
the lives of the ethnographer and his or her subjects (for more on these points, please
see Hoey 2008).

The ethnographic method is different from other ways of conducting social science approach
due to the following reasons:

• It is field-based. It is conducted in the settings in which real people actually live, rather
than in laboratories where the researcher controls the elements of the behaviours to be
observed or measured.
• It is personalized. It is conducted by researchers who are in day-to day, face-to-face contact
with the people they are studying and who are thus both participants in and observers of
the lives under study.
• It is multifactorial. It is conducted through the use of two or more data collection techniques
- which may be qualitative or quantitative in nature - in order to get a conclusion.
• It requires a long term commitment i.e. it is conducted by researcher who intends to interact
with people they are studying for an extended period of time. The exact time frame can
vary from several weeks to a year or more.
• It is inductive. It is conducted in such a way to use an accumulation of descriptive detail to
build toward general patterns or explanatory theories rather than structured to test
hypotheses derived from existing theories or models.
• It is dialogic. It is conducted by a researcher whose interpretations and findings may be
expounded on by the study’s participants while conclusions are still in the process of
formulation.
• It is holistic. It is conducted so as to yield the fullest possible portrait of the group under
study.

PARTICIPANT OBSERVATION

• Participant observation is a qualitative method with roots in traditional ethnographic research

• Participant observation always takes place in community settings, in locations believed to have
some relevance to the research questions.
• The method is distinctive because the researcher approaches participants in their own
environment rather than having the participants come to the researcher.

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 • Generally speaking, the researcher engaged in participant observation tries to learn what life is
like for an “insider” while remaining, inevitably, an “outsider.”
• While in these community settings, researchers make careful, objective notes about what they
see, recording all accounts and observations as field notes in a field notebook.
• Informal conversation and interaction with members of the study population are also important
components of the method and should be recorded in the field notes, in as much detail as
possible.
• Information and messages communicated through mass media such as radio or television may
also be pertinent and thus desirable to document.
• Data obtained through participant observation serve as a check against participants’ subjective
reporting of what they believe and do.
• Participant observation is also useful for gaining an understanding of the physical, social,
cultural, and economic contexts in which study participants live; the relationships among and
between people, contexts, ideas, norms, and events; and people’s behaviors and activities –
what they do, how frequently, and with whom.
• In addition, the method enables researchers to develop a familiarity with the cultural milieu that
will prove invaluable throughout the project.
• It gives them a nuanced understanding of context that can come only from personal experience.
• Observing and participating are integral to understanding the breadth and complexities of the
human experience – an overarching research endeavor for any public health or development
project.
• Through participant observation, researchers can also uncover factors important for a thorough
understanding of the research problem but that were unknown when the study was designed.
• This is the great advantage of the method because, although we may get truthful answers to the
research questions we ask, we may not always ask the right questions.
• Thus, what we learn from participant observation can help us not only to understand data
collected through other methods (such as interviews, focus groups, and quantitative research
methods), but also to design questions for those methods that will give us the best understanding
of the phenomenon being studied.

Strengths and weaknesses of participant observation

Strengths

Allows for insight into contexts, relationships, behavior Can provide information previously unknown
to researchers that is crucial for project design, data collection, and interpretation of other data

Weaknesses

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Time-consuming

Documentation relies on memory, personal discipline, and diligence of researcher Requires conscious
effort at objectivity because method is inherently subjective

STRUCTURED AND UNSTRUCTURED INTERVIEWS

UNSTRUCTURED INTERVIEWS

• Unstructured interviews are very informal and produce qualitative data (descriptive
data).
• Although the researcher has an aim for the research there are no set questions as such.
• The researcher can ask the participant questions based on their previous answers, giving
the participant opportunity to raise related topics and take the interview in their chosen
direction.
• Using this technique can bring in new ideas for the researcher, the participant may
discuss something which the researcher had not previously considered related to their
research.
• As the interview is informal, more like a chat than an interview, participants may feel
a lot more at ease in the situation.
• This may help them to build up a relationship of trust with the researcher which may
encourage complete honesty in their answers which will give the researcher a more
accurate view on his research.
• But, as there are no question set previously the researcher may ask leading questions or
be bias in the way they choose the questions.
• Also if there is more than one researcher, there may be individual differences in the
way they conduct the interview which could again lead to biases within the findings of
the research.
• An interview schedule might not be used, and even if one is used, they will
contain open-ended questions that can be asked in any order. Some questions might be
added / missed as the Interview progresses.

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Merits

1. Unstructured interviews are more flexible as questions can be adapted and changed
depending on the respondents’ answers. The interview can deviate from the interview
schedule.

2. Unstructured interviews generate qualitative data through the use of open questions. This
allows the respondent to talk in some depth, choosing their own words. This helps the
researcher develop a real sense of a person’s understanding of a situation.

3. They also have increased validity because it gives the interviewer the opportunity to
probe for a deeper understanding, ask for clarification & allow the interviewee to steer the
direction of the interview etc.
Limitations

1. It can be time consuming to conduct an unstructured interview and analyze the qualitative
data (using methods such as thematic analysis).

2. Employing and training interviewers is expensive, and not as cheap as collecting data via
questionnaires. For example, certain skills may be needed by the interviewer. These include
the ability to establish rapport & knowing when to probe.

STRUCTURED INTERVIEWS

• Structured interviews are very formal.

• The participants will be asked set questions which have previously been carefully
thought out in order to get the best findings for the research.
• As these questions have already been set the participants will all receive the same
questions in the same order which makes the research fair and able to collect
quantitative data.
• It would be very unlikely for there to be any misleading or bias questions within the
interview as the question would have been checked beforehand, and as the researcher
will be reading questions in a formal manor they will therefore be unable to impose any
of their personal beliefs into the conversation.
• The researcher will act as a professional, this may make some participants feel
uncomfortable which may cause them to be less honest especially if the questions are

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 personal, they may not feel comfortable revealing certain information in this way to a
professional’s face.

Strengths

1. Structured interviews are easy to replicate as a fixed set of closed questions are used,
which are easy to quantify – this means it is easy to test for reliability.
2. Structured interviews are fairly quick to conduct which means that many interviews can
take place within a short amount of time. This means a large sample can be obtained
resulting in the findings being representative and having the ability to be generalized to a
large population.

Limitations

1. Structure interviews are not flexible. This means new questions cannot be asked
impromptu (i.e. during the interview) as an interview schedule must be followed.

2. The answers from structured interviews lack detail as only closed questions are asked
which generates quantitative data. This means a research will won't know why a person
behaves in a certain way.

FOCUSED GROUP INTERVIEW

• A focus group is a form of qualitative research in which a group of people are asked
about their perceptions, opinions, beliefs, and attitudes towards a product, service,
concept, advertisement, idea, or packaging.
• Questions are asked in an interactive group setting where participants are free to talk
with other group members.
• The first focus groups were created at the Bureau of Applied Social Research in the
USA, by associate director, sociologist Robert K. Merton.
• The term itself was coined by psychologist and marketing expert Ernest Dichter. Powell
et al define a focus group as “A group of individuals selected and assembled by
researchers to discuss and comment on, from personal experience, the topic that is the
subject of the research. (1996: 499)”

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 • Focus groups are discussions that last one to two hours, usually done with 6-12 people.
The discussion is led by a moderator asking open-ended questions.
• Focus groups can be used to discover people's general reactions to an interface or
services. A wide range of information can be gathered in a relatively short time span.
• In the social sciences and urban planning, focus groups allow interviewers to study
people in a more natural setting than a one-to-one interview.
• In combination with participant observation, they can be used for gaining access to
various cultural and social groups, selecting sites to study, sampling of such sites, and
raising unexpected issues for exploration. Focus groups have a high apparent validity -
since the idea is easy to understand, the results are believable.
• Also, they are low in cost, one can get results relatively quickly, and they can increase
the sample size of a report by talking with several people at once.
• Focus groups are particularly helpful when used in conjunction with surveys. Your
library can follow up a survey with focus groups to clarify the issues revealed, and
perhaps hear surprising new ideas or concerns.
• Unlike doing polls or asking a listserv, the strength of this technique is the interaction
between participants. With a skilled moderator, the conversation can go beyond "like
it, don't like it" and allow new views to surface. Since there is no pressure to reach a
consensus, all views can be encouraged and aired.
• The first step is to understand what you want to learn. Focus groups are not polls or
surveys; they are in-depth, qualitative interviews with a small number of carefully
selected people, to help you develop an idea or specific service.
• To prepare, you may want to first consider your budget. This is a labor intensive project;
time may be the most expensive item.
• It takes considerable time to plan the sessions, recruit volunteers, and develop your
questions. If you hire a professional moderator, that could be a considerable expense,
other optional things can add to the cost, including honorariums, refreshments and
video taping

Features/advantages of focus group interview

• Focus group research involves organised discussion with a selected group of

individuals to gain information about their views and experiences of a topic.

8
 • Focus group interviewing is particularly suited for obtaining several perspectives about
the same topic.
• The benefits of focus group research include gaining insights into people’s shared
understandings of everyday life and the ways in which individuals are influenced by
others in a group situation.
• Problems arise when attempting to identify the individual view from the group view,
as well as in the practical arrangements for conducting focus groups.
• The role of the moderator is very significant. Good levels of group leadership and
interpersonal skill are required to moderate a group successfully.
• You can get feedback about what people do over a long period of time.
• Focus groups used early in a project can produce insights and questions from the
interaction among different users or stakeholders.
• Focus groups are relatively inexpensive (assuming that participants are from the same
geographical area) and can be arranged quickly.

CASE STUDY

• A case study is an in-depth comprehensive study of a person, a social group, an

episode, and process, a situation, a programme, a community, an institution or
any other social unit.
• It is one of the most popular types of research methods. Its purpose may be to
understand the life cycle of the unit under study or the interaction between
factors that explain the present status or the development over a period of time.
Some examples of a case study are: a social – anthropological study of a rural
or tribal community; a causative study of a successful cooperative society; a
study of a financial health of a business undertaking; a study of a juvenile
delinquency; a study of life style of working women etc.

Definition

Different scholars from different disciplines have defined the term ‘case study’
differently.

9
 Pauline V Young has defined it as “ a comprehensive study of a social unit, be that unit
a person, a group, a social institution, a district or community.”

Queen has stated that , case study is “the examination of a single situation, persons,
groups, or institution as complex wholes inn order to identify types and process.”

Burgess has defined it in his book entitled : ‘Research methods in sociology’. He used
the words ‘the social microscope’ for the case study method.

Characteristics of the case study method

In modern social research, case study method is extensively used to meet different
problems in different disciplines. It is a ‘qualitative’ technique which was once thought to be
exclusive characteristic of the case study approach.

1. Single unit analysis: The case study method is generally known as ‘single analysis
method’. Under this method, one single social unit or more of such units can be
studied for the study purpose. One single unit means single person, family,
institution or community may be studied under this head.
2. Intensive study : The method is generally applied to study a particular unit
intensively. Generally, this study covers a long period of time to know the history
of the unit concerned.
3. Integrated study: In this method, one has to make a complete study of the social
unit covering all facts. A social unit always has complex phenomena. Different
forces are working which affects the social unit. Hence, an integrated study is
needed to understand the social unit under consideration.
4. Qualitative analysis: This method is known as qualitative analysis. It does not just
merely collect the information concerning all aspects of life but also depend on
perception and gives us a clear insight into life. For example, in this method, we
not only study how many crimes a man has committed but also investigate the
factors which compelled him to commit a crime when we study a man as a criminal.

10
 5. Interrelationship can be studied: Different factors can act and react upon each other.
So does the casual factors, also one has to take into consideration these mutual
interrelationship of casual factors.
6. Behaviour pattern can be studied: The case study being a qualitative tool of
analysis, it studies not only the cause and effect relationship of the factors but also
the reasons for change in the behaviour of the unit concerned. For instance, what
are the reasons which causes increase in crimes in a particular social unit.
7. It Helps to Generalize Social Science: The case study method is helpful in testing
the hypothesis and thereby building the generalized social science to get the
knowledge richer and richer.
8. Flexible Method: The case study method is flexible in nature. The researcher has
complete freedom to change or omit or distort variable under study.
9. Mutual interrelationship can be studied: In case study method an effort is made to
know the mutual interrelationship of casual factors.
10. Complementary study: The case study method stresses the need of complementary
study for getting proper solution to the problems

Types of Case Studies

Burns (2000) has stated six types of case studies:

1. Historical case studies : these studies trace the development of an organization /

system over time. The study of an adult criminal right from his childhood through
adolescence and youth is and example of this type of case study. This type depends
more on interviews, recording and documents.
2. Observational case studies: These focus on observing a drunkard, a teacher, a
student, a union leader, some activity, event or a specific group of people.
3. Oral history case studies: These are usually first person narratives that the
researcher collects using extensive interviewing of a single individual. For
example, the case of a drug addict or an alcoholic, or a prostitute or a retired person
who fails to adjust himself in son’s family.
4. Situational case studies: This form studies particular events. The views of all
participants in event are sought. For example, a communal riot : how it started with

11
 conflict between two persons of two different religious groups, how each person
sought support of persons of his own relgion present at the spot, how police was
informed, how did pubic and the media react and so on. Pulling all these views
together, a depth is provided that contributes significantly to the understanding of
the event.
5. Clinical case studies: This approach aims at understanding in depth a particular
individual such as a patient in the hospital, a prisoner in the jail, a problem child in
a school etc. These studies involve detailed interviews, observation, going through
records and reports, and so on.
6. Multi – case studies: it is a collection of case studies or a form of replication, i.e.,

Sources of case study method

1. Personal documents: From personal diaries, letters or from autobiographies, the

necessary information is collected. The hidden secrets of an individual, his way of
life, the objects and the mode of life are written in one’s personal diary. So personal
documents can be a source of a great deal of information necessary for the study of
the problem.
2. Life History: In the case study method, the life history of a person may be very
essential. This can be obtained through interviews with the respondent. In this
study, the entire life of the respondent is taken into account. The material for the
case study can also be gathered from writing materials about the respondent and
through interviews. Briefly, the entire life cycle of an individual is studied, tested
and enquired in this type of case study.
Merits

The merits of a case study method are as follows

1. Case studies are flexible with respect to data collection methods. All methods of
data collection are useful to case studies
2. A case study can extend virtually to any dimension of the topic studied. All aspects
may be studied or specific aspects may be emphasized
3. Case studies may be conducted in practically any kind of social setting

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 4. Case studies offer specific instances of tests of theories
5. Case study is a highly fruitful approach for the purpose of group or process analysis
as against the analysis of individual traits alone.
6. Case studies give to the researcher a wider range of insights into human life, which
cannot be gained through a general survey
Demerits

The major disadvantages or limitation of case study are:

• The most prominent disadvantage of case studies is their limited generalizability.

As case studies of stray cases, they are not sufficient for making meaningful
generalization to larger social aggregates.
• Case studies are generally more time – consuming than surveys
• Case study method is inadequate for an analysis of macro-problems
• The danger of investigator’s over confidence is more in a case study. This leads to
various biases such as errors of perception, judgement and over emphasis of unusual
events, unwarranted extrapolation, and theorizing and sweeping generalizations.

NARRATIVE METHOD
• A narrative is a constructive format (as a work of speech, writing, song, film,
television,video games, photography or theatre) that describes a sequence of non-
fictional or fictional events.
• The word derives from the Latin verb “narrare" to recount", and is related to the
adjective “gnarus”,"knowing" or "skilled".
• Narrative is often used in case study research in the social sciences.
• Here it has been found that the dense, contextual, and interpenetrating nature of
social forces uncovered by detailed narratives is often more interesting and useful
for both social theory and social policy than other forms of social inquiry.
• Prominent social scientists have pointed out that a social science expressed in terms
of narrative case studies would provide better access for policy intervention than
the present social science of variables.
• Narrative Inquiry emerged as a discipline within the broader field of qualitative
research.

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 • It is an approach to understanding/researching the way people make meaning of
their lives as narratives, linked fields are narrative analysis, narratology and life
writing.
• Narrative Inquiry should be distinguished from storytelling in that the word
narrative implies an audience and a narrator. Of interest to narrative inquirers is not
what happened so much as what meaning did people make of what happened.
• Narrative Inquiry is a fairly recent movement in social science qualitative research.
It has been employed as a tool for analysis in the fields of cognitive science,
organizational studies, knowledge theory, sociology and education studies, among
others.
• The starting point of the Narrative Method is the story. Story telling is a deeply
rooted human phenomenon. It is a natural way of sharing our knowledge, insights
and feelings with others.
• Stories or personal experiences are especially appropriate for making complicated
subjects comprehensible to others. Compared to answers to specific questions,
stories (and the context in which they are told) frequently lead to a much richer
output and to richer and more profound insights.

QUANTITATIVE RESEARCH

Quantitative research is based on the measurement of quantity or amount. It is

applicable to phenomena that can be expressed in terms of quantity. This research employs
quantitative measurement and the use of statistical analysis. For example, what percentage of
medical engineering, law, arts, science and commerce students take drugs or alcohol, like that.
Social survey is an example of quantitative research method.

SOCIAL SURVEY

Survey is a ‘fact finding’ study. It is a method of research involving collection of data

directly from a population or a sample thereof at particular time. It must not be confused with
the mere clerical routine of gathering and tabulating figures. It requires expert and imaginative
planning, careful analysis and rational interpretation of the findings.

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 Data may be collected by observation, or interviewing or mailing questionnaires.

The analysis of data may be made by using simple or complex statistical techniques
depending upon the objectives of the study.

The subject – matter of surveys

All aspects of human behaviour, social institutions, economic system, and business
undertaking lend themselves to surveys. The subject matter of surveys may be brodly
categorized into:

a) Social surveys
1. Demographic characteristics of a group of people
2. Social environment of people
3. People’s opinions and attitudes
4. People’s behaviour and activities
b) Economic Surveys
1. Economic conditions of people
2. Working of economic units
3. Operations of an economic system

Demographic characteristics include family composition, marital status, fertility , age

and so on. Population census is primarily on the demographic aspects of people. All social
surveys include some demographic aspects.

Social environment covers all social factors, housing and social amenities and social
institutions.

Surveys of opinions and attitudes deal with various issues (e.g., direct vs indirect
election of the head of government), systems (e.g. democracy )and schemes and programme
(e.g., family planning).

People’s activities refer to ‘what people do’, e.g., use of leisure time, newspaper
reading, and recreation etc. people’s behaviour is concerned with their consumption pattern,
life style, organizational behaviour, group dynamics etc.

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The characteristics of survey method

The survey method has certain characteristics:

1. It is always conducted in a natural setting: it is a field study

2. It seeks responses directly from the respondents
3. It can cover a very large population
4. A survey may involve an extensive study or an intensive study. An extensive study
covers a wider sample. An intensive one covers a few samples and tends to ‘dig
deeper’. These two approaches serve different ends; where generalization or
estimation is necessary, the extensive approach is useful, but where one wants to
make an indepth study of some aspects of a subject – matter, the intensive approach
is preferable.
5. A survey covers a definite geographical area: a city, or a district, or a state
The quality of a survey depends upon the thoroughness of the planning, the soundness of
sampling , the adequacy and reliability of data, the quality of analysis and the interpretation
of the findings.

The Purposes of Surveys

Survey serves several purposes:

1. The purpose of many surveys such as population census, socio – economic surveys,
expenditure surveys, marketing surveys etc., is simple to provide information to
government or planners or business enterprises. These surveys have a descriptive
purpose. In short, all fact finding surveys have this purpose
2. Many enquiries aim to explain certain phenomena. Their function is to test hypotheses,
to explain the causal relationship between variables and to assess the influences or
various factors on a given phenomenon like job satisfaction, labour productivity and
consumer behaviour. Surveys aiming at explanation involve indepth analysis and
complex interpretations.
3. Surveys may be designed to make comparisons of demographic groups (e.g.,
comparison of low income groups with high income groups) or real groups, e.g., work
groups in factories or offices. Comparison of behavioural or attitudinal groups can also
be made. For example, in a factory, the attitudes of high production workers toward
the company may be compared with the attitudes of low production workers.

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 4. Surveys concerned with cause and effect relationships can be useful for making
predictions. For example, if relationships between income increases and purchase of
durable goods are established in a consumer behaviour survey, a prediction about future
demand for durable goods with reference to anticipated income increases can be made.
A survey of people’s future plans and intentions is another approach to make
predictions. This is one of the methods adopted for demand forecasts.
Merits of survey research

The major advantages of a survey method are:

1. The versatility of the survey method is its greatest strength. It is the only practical
way to collect many types of information from individuals, such as personal
characteristics, scoio economic data, attitudes, opinions, experiences and
expectations
2. The survey method facilitates drawing generalizations about large populations on
the basis of studies of representative sample
3. The survey method is flexible to permit the use of various methods of collection of
data observation interviewing and mailing
4. Surveys sensitize the researcher to unanticipated or unknown problems. The
collection of data from respondents through interviewing or mailing often uncovers
facts previously unknown to the researcher
5. surveys are useful instruments for verifying theories

Limitations

1. Survey method is primarily meant for collection of data from primary sources:
individuals, households and institutions; thence its feasibility depends upon the
willingness and cooperation of the respondents.
2. A sample survey is subject to sampling error.
3. The survey method depends primarily on verbal behaviour. The respondent can
give untrue or misleading answers. Hence, a survey is subject to response errors
4. A survey is also subject to the errors of measurement implicit in quantifying
attitudes, abilities, behaviour and other personal traits.

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5. There is a limit of the number of items of information that can be collected in a
single survey. There is an optimal length of time for an interview. Beyond that
point, interview weariness sets in. Hence the extent of data requirement should be
delimited to the tolerance level of respondents
6. A sample survey designed to represent a population over a wider geographical area
may not give adequate representation to any population characteristic, which is
highly localized. This means that the influences of specific local social groups
cannot be assessed through a national survey
7. The survey method alone is inadequate to analyse adequately the complex fabric of
social organization. It also not well suited to studies of historical development
8. Survey is very expensive in terms of time and cost. Hence, an individual cannot
afford to carry out an extensive survey out of his resources.

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 MODULE III
Steps in Social Research

Formulation of research problem-steps, Literature Review , Objectives, Concepts, variables,

Formulation of Hypothesis, Research Design-types, Data Collection- Types of Data -
Primary and Secondary. Tools of Primary data collection –Questionnaire, Interview
Schedule Methods-Sampling and Census, Data Analysis, Report Writing.

SELECTION OF A PROBLEM FOR RESEARCH

The selection of a problem is the first step in research. The term ‘problem’ means a
question or issue to be examined. The selection of a problem for research is not an easy task;
itself is a problem. It is least amenable to formal methodological treatment. Vision, an
imaginative insight, plays an important role in this process.

Sources of problems

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

Reading, academic experience, daily experience, exposure to field situations, consultations,

brain storming, research and intuition.

Formulation of the selected problem

Formulation means translating transforming the selected research problem / topic into
a scientifically researchable question. It is concerned with specifying exactly what the
research problem is and why is it studied. The formulation should include both the what and
the why aspects.

LITERATURE SURVEY

Once a topic has been decided upon, it is essential to review all relevant material
which has a bearing on the topic. In fact, review of literature begins with a search for a
suitable topic and continues throughout the duration of the research project work. It is
necessary to show how the problem under investigation relates to previous research studies.
In some subject areas it is important to locate the problem within a theoretical framework and
in such cases the underlying theory needs to be reviewed as well.

The purpose of review

The reasons of review of related literature are;

• To gain a background knowledge of the research topic,

• To identify the concepts relating to it, potential relationships between
them an dto formulate researchable hypotheses
• To identify appropriate methodology, research design, methods, of
measuring concepts and techniques of analysis
• To identify data sources used by other researchers, and
• To learn how others structured their reports
Source of literature

The sources of documentary information, which can aid the process of locating
literatures relating to selected research topics are:

• Subject catalogues of libraries

• Documentation services
• Bibliographies
• List of books and publishers’ bulletins
• Journals
• Government reports
• Research abstracts
• Information on research done

OBJECTIVES

Objectives of a study refers to aim of the study. They are the questions to be
answered through the study. They indicate what we are trying to get from the study.
Objectives are made either in the forms of questions or in the form of statement.
CONCEPTS

A concept is an abstract symbol representing an object, a property of an object or a

certain phenomenon, e.g., book, person, intelligence and meeting. A concept like
‘aggression’ or ‘frustration’ or ‘political participation’, represents a number of events under
one general name or label. Therefore, ‘a concept is in reality a definition in short hand of a
class or group of facts’.

Characteristics of concepts

1. Concepts are symbols which we attach to the bundle of meanings that we hold
2. concepts represent only one pat of reality
3. thus different people hold different concepts of the same thing
4. concepts represent various degrees of abstraction
Types of concepts

Concrete concepts : - symbolize material objects, which can be seen, touched and
felt, e.g., book, table, building

Abstract concepts – refers to properties or characteristics of objects, e.g., weight,

height, attitude, intelligence, leadership. They are constructs, i.e., they represent inferences
deduced from observable events.

VARIABLES

A variable is a characteristic that takes on two or more values. It is something that

varies. It is a characteristic that is common to a number of individuals, groups, events
objects, etc. The individual cases differ in the extent to which they posses the characteristics.
Thus, age (young, middle aged, old), income class (lower, middle, upper), caste (low,
intermediate, high), education (illiterate, less educated, highly educated) are all variables.

.
HYPOTHESES

Hypothesis is a tentative proposition formulated for empirical testing. It is declarative

statement combining concepts. It is tentative answer to a research question. Lundberg
defines hypothesis as ‘a tentative generalization, the validity of which remain to be tested.’

TYPES OF HYPOTHESIS
• Descriptive hypothesis: It describes the characteristics of a variable.
• Relational hypothesis: It describes the relationship between the variables.
• Casual hypothesis: It describes the causal relationship between the variables.
• Working hypothesis: Hypotheses which are subject to modification as the
investigation
• Null hypothesis: They state that no difference exists between the parameter and
statistic
• Statistical hypothesis: These are statements about a statistical population. These are
• Analytical hypothesis: these are concerned with the relationship of analytic
variables. These hypotheses occur at the highest level of abstraction. It also
specifies the relationship
.

Sources of hypotheses

Hypotheses can be derived from various sources such as theory, observation,

intuition and personal experience, findings of studies, state of knowledge, culture etc.

Functions or the role of hypotheses

1. Hypothesis gives a definite point to the investigation, and it guides the direction
on the study.
2. It determines the data needs.
3. A hypothesis suggests which type of research is likely to be most appropriate
4. A hypothesis contributes to the development of theory
RESEARCH DESIGN

The term ‘design’ means ‘drawing an outline’ or planning or arranging details. It is a

processes of making decisions before the situation arises in which the decision has to be
carried out. ‘Research design’ is planning a strategy of conducting research. Martin Bulmer
has said that ‘research design is the specification of the problem, conceptual definitions,
derivation of hypotheses to test, and defining of population to be studied.

The following are the important research designs

Descriptive research design

Descriptive study is a fact – finding investigation with adequate interpretation. It is

the simplest type of research. It is more specific. It has focus on particular aspects or
dimensions of the problem studied. It designed to gather descriptive information and
provides information for formulating more sophisticated studies.

All problems do not lend themselves to descriptive study. This method is applicable
to problems, which satisfy certain criteria. First, the problem must be describable and not
arguable. For instance, philosophical and controversial issues are not suitable for descriptive
study. Second, the data should be amenable to an accurate, objective, and if possible,
quantitative assemblage for reliability and significance. Third, it should be possible to
develop valid standards of comparison. Last, it should lend itself to verifiable procedure of
collection and analysis of data

A descriptive study aims at identifying the various characteristics of a community or

institution or problem under study, but it does not deal with the testing of proposition or
hypothesis.

Advantages

The descriptive studies are useful in their own way

 1. They have much to contribute to the development of a young science, as
descriptive information can focus directly on a theoretical point. It may be useful
in verifying focal concepts through empirical observation.
2. Descriptive information obtained in a research may be useful for prediction about
areas of social life outside the boundaries of the research.
3. Descriptive studies are valuable in providing facts needed for planning social
action programmes
Limitation

The descriptive method of study has certain limitations:

1. It is not applicable to problems, which cannot satisfy the required criteria

mentioned earlier.
2. The researcher may make description an end in itself. Research must lead to
discovery of facts
3. Although social science problems are continuous and have a past and a future, the
researcher may lose himself in current conditions only
4. The researcher may tend to over use statistics. In making statistical analysis, its
limitations should be recognized.

Exploratory Research Design

Exploratory research is preliminary study of an unfamiliar problem about which the

researcher has little or no knowledge. It is similar to a doctor’s initial investigation of a
patient suffering from an unfamiliar malady for getting some clues for identifying it. “It is
ill-structured and much less focused on pre-determined objectives”. It usually takes the form
of a pilot study.

Purposes

The purpose of an exploratory study may be:

• To generate new ideas or

• To increase the researcher’s familiarity with the problem or
• To make a precise formulation of the problem or
• To gather information for clarifying concepts or
 • To determine whether it is feasible to attempt the study
An exploratory study does not aim at testing hypothesis. According to Daniel Katz, it just
attempts “to see what there rather than to predict the relationships that will be founded. But it
should be so designed as to provide as definite information as possible for a set of research
objectives.

Experimental study or hypothesis-testing research studies

• Experimental studies are mainly designed to find out the cause and effect
relationships of the phenomenon under study, or the researcher tests the hypothesis of
causal relationships between the variables.
• The experimental designs are used in researches relating to the phenomena of several
disciplines.
• The experimental designs originated in the context of agricultural operations. The
beginning of such designs was made by Professor R.A. Fisher when he was working
at Centre of Agricultural Research in England. The principle of replications, the
principle of randomizations and the principle of local control are the three main
principles of experimental designs given by Prof. Fisher.

Diagnostic research design

This is similar to descriptive study but with a different focus. It is directed towards
discovering what is happening, why is it happening and what can be done about. It aims
at identifying the causes of a problem and the possible solutions for it.

A diagnostic study may also be concerned with discovering and testing whether
certain variables are associated, e.g., are persons hailing from rural areas more suitable
for manning the rural branches of banks? Do more villagers than city voters vote for a
particular party?

Both descriptive and diagnostic studies share common requirements, viz., prior
knowledge of the problem, its thorough formulation, clear –cut definition of the given
 population, adequate methods for collecting accurate information, precise measurement
of variables, statistical analysis and test of significance. As the aim is to obtain complete
and accurate information about a given situation/ phenomenon, the research design must
make much more provision for protection against bias than is required in an exploratory
study. Moreover, the amount of work involved is considerable and so concern with
economy of research effort is extremely important.

A diagnostic study is more directly concerned with causal relationships and with
implications for action. It is directed towards discovering not only what is occurring but
why it is occurring and what can be done about it. It is more actively guided by
hypothesis.

Types of Data

The sources of data may be classified into (a) primary sources and (b) secondary
sources

Primary Sources

Primary sources are original sources from which the researcher directly collects data
that have not been previously collected. Primary data are first – hand information collected
through various methods such as observation, interviewing, mailing etc.

Secondary Sources

These are sources containing data which have been collected and compiled for
another purpose. The secondary sources consists of readily available and already compiled
statistical statements and reports whose data may be used by researches for their studies, e.g.,
census reports, annual reports, statistical statements, reports of the National Sample Survey
Organisation, Trade and financial journals, newspapers, etc.
 Secondary sources consists of not only published records and reports, but also
unpublished records. The latter category includes various records and registers maintained
by firms and organizations.

Method of Collecting primary data

a. Observation method
b. Interview method
c. Local correspondences
d. Questionnaire and schedule method

Questionnaire

This method of data collection is quite popular, particularly in case of big enquiries.
It is being adopted by private individuals, research workers, private and public organizations
and even by governments. In this method a questionnaire is sent to the persons concerned
with a request to answer the questions and return the questionnaire. A questionnaire consists
of a number of questions printed or typed in a definite order on a form or set of forms. The
questionnaire is mailed to respondents who are expecte to read and understand the questions
and wirte down the reply in the space meant for the purpose in the questionnaire itself. The
respondents have to answer the questions on their own.

The method of collecting data by mailing the questionnaires to respondents is most

extensively employed in various economic and business surveys.

The merits of this method as follows

1) There is low cost even when the universe is large and is widely spread
geographically
2) It is free from the bias of the interviewer; answers are in respondents’s own words
3) Respondents have adequate time to give well thought out answers.
4) Respondents, who are not easily approachable, can also be reached conveniently.
5) Large samples can be made use of and thus the results can be made more
dependable and reliable
The main demerits of this system can also be listed here:
 1) Low rate of return of the duly filled in questionnaires; bias due to no response is
often indeterminate
2) It can be used only when respondents are educated and cooperating
3) The control over questionnaire may be lost once it is sent
4) There is inbuilt inflexibility because of the difficulty of amending the approach
once questionnaires have been dispatched.
5) There is also possibility of ambiguous replies or omission of replies altogether to
certain questions; interpretation of omission is difficult
6) It is difficult to know whether willing respondents are truly representative
7) This method is likely to be slowest of all
Schedules

This method of data collection is very much like the collection of data through
questionnaire, with little difference which lies in the fact that schedules are being filled in by
the enumerators who are specially appointed for the purpose. These enumerators along with
schedules, go to respondents, put to them the questions from the proforma in the order the
questions are listed and record the replies in the space meant for the same in the proforma. In
certain situations, schedules may be handed over to respondents and enumerators may help
them in recording their answers to various questions in the said schedules. Enumerators
explain the aims and objects of the investigation and also remove the difficulties which any
respondent may feel in understanding the implications of a particular question or the
definition or concept of difficult terms.

This method requires the selection of enumerators for filling up schedules or assisting
respondents to fill up schedules and as such enumerators should be very carefully selected.
The enumerators should be trained to perform their job well and the nature and scope of the
investigation should be explained to them thoroughly so that they may well understand the
implications of different questions put in the schedule. Enumerator should be intelligent and
must possess the capacity of cross-examination in order to find out the truth. Above all, they
should be honest, sincere, hardworking and should have patience and perseverance.

This method of data collection is very useful in extensive enquiries and can lead to
fairly reliable results. It is, however, very expensive and is usually adopted in investigations
conducted by governmental agencies or by some big organizations. Population census all
over the world is conducted through this method.
SAMPLING

• Empirical filed studies require collection of first hand information or data

pertaining to the units of study from the field.
• The units of study may include geographical areas like districts, talukas, cities
or villages which are covered by the study ,or institutions or households about
which information is required, or persons from whom information is required,
or persons from information is available. T
• he aggregate of all the units pertaining to a study is called the population or
the universe. Population is the target group to be studied.
• A member of the population is an element. It is the subject on which
measurement is taken. It is the unit of study.
• A part of the population is known as a sample.
• The process of drawing a sample from a larger population is called sampling.
• The list of sampling units from which a sample is taken is called the sampling
frame, e.g. a map, a telephone directory, a list of industrial undertakings, a list
of car licensees etc.
• The chief aim of sampling is to make an inference about an unknown
parameter from a measurable sample statistics
• A second aim of sampling is to test a statistical hypothesis relating to
population.
• A sample is drawn and the data collected from the sample informants are
analysed and on the basis of the result hypothesis may be accepted or rejected.

Characteristics of good sample

1. Representativeness: A sample must be representative of the population. Probability

sampling technique yield representative sample. In measurement terms, the sample
must be valid. The validity of a sample depends upon its accuracy and precision.
2. Accuracy : Accuracy is defined as the degree to which bias is absent from the
sample. An accurate (unbiased) sample is one which exactly represents the
population. It is free from any influence that causes any difference between sample
value and population value.
 3. Precision: The sample must yield precise estimate. Precision is measured by the
standard error or standard deviation of the sample estimate. The smaller the standard
error or estimate, the higher is the precision of the sample.
4. Size: a god sample must be adequate in size in order to be reliable. The sample
should be of such size that the inference drawn from the sample are accurate to the
given level of confidence.

Types of Sampling

Probability sampling

• Probability sampling is based on the theory of probability

• Probability sampling should be used when generalization is the objective of
study and a greater degree of accuracy of estimation of population parameters
is required.
• The type of probability sampling are simple random sampling, systematic
sampling, stratified sampling and cluster sampling.

Simple Random Sampling

• This sampling technique gives each element an equal and independent chance
of being selected.

Procedure

The procedure of drawing a simple random sample consist of

1. Enumeration of all elements in the population

2. Preparation of a list of all elements, giving them numbers in a serial order 1,2,3,...
so on,
3. Drawing sample numbers by using a) Lottery method, b) a table of random
numbers or c) a computer

Stratified Random Sampling

• This is an improved type of random or probability sampling.

 • In this method, the population is sub divided into homogeneous groups or
strata, and from each stratum, random sample is drawn.
• For example, university students may be divided on the basis of discipline, and
each discipline group may again be divided into juniors and seniors.
• The stratified random sampling is appropriate for a large heterogeneous
population.

Systematic sampling

• This method of sampling is an alternative to random sampling.

• It consist of taking every Kth item in the population after a random start with
an item from 1 to k.
• For example, suppose it is desired to select a sample of 20 students, from a
list of 300 students, divide the population total of 300 by 20, the quotient is
15.
• Select a number at random between 1 and 15, using lottery method or table of
random numbers. Suppose the selected number is 9. Then the students
numbered 9, 24 (9 + 15), 39 (24 +15), 54, 69, ... are selected as the sample.
• As the interval between sample units is fixed, this method is also known as
fixed interval method. This is also called real systematic sampling or pseudo –
random sampling.

Cluster sampling

• Cluster sampling means random selection of sampling units consisting of

population elements.
• Each such sampling unit is a cluster of population elements. Then from each
selected sampling unit, a sample of population elements is drawn by either
simple random selection or stratified random selection.

Non probability sampling

Non probability sampling does not adopt the theory of probability and it does not give
a representative sample of population. The primary methods of non – probability sampling
are:
 1. Convenience sampling
2. Purposive or judgement sampling
3. Quota sampling
4. Accidental sampling
5. Snow ball sampling

Convenience or accidental sampling

• This is non probability sampling.

• It means selecting sample units in a just ‘hit and miss’ fashion, e.g.,
interviewing people whom we happen to meet.
• This sampling also mean selecting whatever sampling units are conveniently
available, e.g., a teacher may select students in his class.
• This method is also known as accidental sampling because the respondents
whom the researcher meets accidently are included in sample.

Purposive or Judgement Sampling

• This method means deliberate selection of sample units that conform to some
pre-determined criteria.
• This is also known as judgement sampling.
• This involves selection of cases which we judge as the most appropriate ones
for the given study. It is based on the judgement of the researcher or some
expert.

Quota Sampling

• This is a form of convenient sampling involving selection of quota group of

accessible sampling units by traits such as sex, age, social class etc.
• When the population is known to consist of various categories by sex, age ,
religion, social class etc., in specific proportions, each investigator may be
given an assignment of quota groups specified by the pre-determined traits in
specific proportions.
 • Quota sampling is therefore a method of stratified sampling in which selection
within strata is non-random. It is this non-random element that constitutes its
greatest weakness.

Snowball sampling

• This is the colourful name for a technique of building up a list or sample of a

special population by using an initial set of its members as informants.
• This sampling technique may also be used in socio metric studies.
• For example, the members of social group may be asked to name the persons
with whom they have social contacts, each one of the persons so named may
also be asked to do so, and so on.

Census

Census refers to a periodic collection of information from the entire population. It is a time-
consuming affair as it involves counting all heads and generating information about them. For
better governance, every government requires specific data and information about the
populace to make programs and policies that match the needs and requirements of the
population. A census allows the government to gain such information.

Format of a Research Report

Generally a report contains the following items.

1. Pre-factory items
a) Title
The tile page is the first page of a research report. It carries 1) the title of the
study, 2) the name of the degree for which it is submitted, 3) the name of the
author, 4) name of the institution on which the report is submitted and date of
presentation
b) Researcher’s declaration
In the case of a research undertaken by a student in fulfilment of the
requirements of a Degree, he may be required to make a declaration.
c) Certificate of the supervisor
 In the case of a student’s research work, his research supervisor has to certify
that it was a record of independent research work done by the student.
d) Acknowledgement
In this section, the researcher acknowledges the assistance and support
received from individuals and organisations in conducting the research. It is
thus intended to show his gratitude.
e) Contents

A table of contents gives an outline of the contents of the report. It contains a

list of the chapters and their sub titles with page numbers. It facilitates ready
location of topics in the report.

f) List of tables
This come after the table of contents.
g) List of graphs and charts
If there are many graphs and charts or other exhibits they should also be listed
after the list of tables.

2. Body of the Report

i. Introduction

This is the first chapter in the body of research report. It may consist of the
following sections.

a) Background of the topic

The first task is to introduce the background and the nature of the
problem so as to place it into a larger context to enable the reader to know its
significance in a proper perspective. This section summarises the theory or
conceptual framework .

b) Statement of the problem

In this section, why and how the problem was selected are stated, the
problem is clearly defined and its facets and significance are pointed out.

c) Review of the literature

 It is devoted for making a brief review of previous studies on the
problem and significant writings on the topic under study. This review
provides a summary of the current state of knowledge in the area of
investigation.
d) Scope of the present study
The dimensions of the study in terms of the geographical area covered,
the designation of population being studied and level of generality of
the study are specified.
ii. Design of the study
a) Methodology

In this section, the overall typology of research used, and the data
collection methods employed are described

b) Objectives of the study

The objective of the study and the investigative questions relating to
each of the objectives are presented
c) Hypothesis to be tested
The specific hypotheses to be tested are stated. The source of their
formulation may be indicated.
d) Definition of concepts
Here the operational definitions of the key concepts and variable’s of
the study are presented, giving justifications for the definitions
adopted.
e) Sources of the data
The sources from which the secondary and or primary data were
gathered are stated.
f) Sampling plan
The size of the universe from which the sample was drawn, the
sampling methods adopted and the sample size and processes of
sampling are described in this section.
g) Tools of data collection
The type of instruments used for data collection and their contents,
scales and other devices used for measuring variables and the
 procedure of establishing their validity and reliability are described in
this section

h) Field work
When and how the field work was conducted, and what problems and
difficulties were faced during the field work are described under this
sub heading.
i) Data processing and analysis
The method – manual or mechanical – adopted for data processing, and
an account of methods used for data analysis and testing hypotheses
must be outlined and justified.
j) Limitations of the study
No research is free from limitation and weakness. These arise from
methodological weakness, sampling, imperfections, non – responses,
measurement deficiencies and the like.

iii. Results, Findings and Discussions

This is the major part of the report. It may be divided into several
chapters depending upon the number of objectives of the study, each
being devoted for presenting the results pertaining to art objective.
Each chapter should be given an appropriate heading.
iv. Summary, conclusions and recommendations
The presentation of analysis and results is followed by a separate final
chapter. This chapter should be a self – contained summary of the
whole report, containing a summary of essential background
information, findings and inclusions and recommendations.

3. Terminal Item

a) Bibliography
This is the first of the terminal items presented at the end of the
research report. The bibliography lists in alphabetical order all
published and unpublished references used by the writer in preparing
the report. The bibliography may be classified into three or four
 sections: a) Books, b) Articles c) Reports and d) Other documents, and
in each section relevant references may be arranged in alphabetical
order.
Basic format of bibliography:- Author’s name, title of the work, place
of publication: Publisher’s name, Year , Page no.(s)
Eg:- Peter F Drucker, The Practice of Management, London : Pan
Books Limited, 1955, p. 150
b) Appendix
The following documents are included in appendix : a) copies of data
collection instruments like interview schedules or questionnaires used
for the study, b) technical details on sampling plan, c) complex and
long primary tables, d) statistical computations, e) supporting
documents and any other evidence that may be important backup
details for the report.
 MODULE IV
Role of Statistics in Social Research
Definition, Nature, and Scope of Statistics, Use of Statistical methods in Social Research,
Limitations of Statistics, Classification and Tabulation of data, Diagrammatic and Graphical
Representations, Context of using Measures of Central Tendencies and Measures of
Dispersion.

DEFINITION AND MEANING

Different writer has defined the statistics differently.

Harlow defines the statistics as the science and art of handling aggregates of facts – observing,
enumerating, recording, classifying and otherwise systematically treating them.

Croxton and Cowelen defined the statistics as the science of collection, presentation, analysis
and interpretation of numerical data.

Bowley defined the statistics as numerical statements of facts in any department of enquiry
placed in relation to each other.

Thus it can be further defined as the science of collection, presentation, analysis

and interpretation of data which means statistics is concerned with scientific methods of
collecting, organizing, summarizing, presenting and analyzing data and what is even more
important is drawing valid conclusions and making reasonable interpretation based on such
analysis.

SCOPE OF STATISTICS:

In the early period of development of Statistics, it had only limited scope. But in modern times,
the scope of statistics has become as wide as to include in its fold all quantitative studies and
analysis relating to any department of enquiry. It is used in all spheres of life such as social,
economic and political fields.

In the field of economics it is almost impossible to find a problem which does not require an
extensive use of statistical data. Modern age is an age of planning. Plans of economic
development are constricted on the basis of statistical data. Bankers, brokers and Insurance
companies make use of statistical data for the study of business cycles, future trends, mortality
rate ctc..

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Statistics comes to the field of Business management also. Statistics are very helpful to state
asthey help it in administration. Modern statistical data are being found increasingly useful in
research in different fields.

1. Importance of statistics in the field of commerce and business.

Statistics is an aid to business and commerce. It said that a business runs on estimates and
probabilities. Statistics help business to forecast its expectations come to true. Modern
statistical devices help business forecasting more precise and accurate. Business men need
statistics right from his business. He should have relevant facts and figures to prepare the
financial plan of the proposed business.

2. Uses of Statistics in Business Management

One of the important functions of business management is to coordinate the activities of the
various departments so as to secure maximum efficiency with minimum effort. To discharge
this function efficiently, management should have adequate statistical data. Another function
of management is marking wise decisions in the face of uncertainty. Modern Statistics has
developed certain general principles and devices to deal with uncertainty wisely. Modern
statistical tools of collection, classification, tabulation, analysis and interpretation of data, have
been found to be an important aid in making wise decisions at various levels of managerial
function. The success of production programming both in the short as well as long period
depends to a great extent on the quality of sales forecasts. Statistical methods can be applied to
have better sales forecasts. Effective control on sales can also be exercised through regional
allocations. Market research consumer preference studies etc. are some other methods of sales
control, which make an extensive use of statistical tools.

3. Importance of Statistics in Economics

The Science of Economics is becoming statistical in its method. Statistical data are extensively
used in all economic problems. As economic theory advances, uses of statistical methods also
increase. The laws of Economics like Law of demand, Law of supply etc. can be considered
true and established with the help of statistical methods. Statistics of consumption tell us about
the relative strength of the desire of a section of people. Statistics of production describe the
wealth of a nation. Distribution Statistics disclose the economic conditions of the various
classes of people. Therefore statistical methods are necessary for proving economic laws.

2
Index number like Cost of living index number, Whole sale price index number etc. and
analysis of time series are important statistical concepts in economic theory. The planning is
based on the correct analysis of statistical data. Our five year plan is statistical methods. They
are extensively used in Economics. Thus one can say that without Statistics many theories of
Economics would have remained closed to mankind.

4. Uses of Statistics in other fields

To the State (or Government): Statistics are the eyes of government administration.
Government has since long collected and interpreted data concerning the state. In fact, the word
Statistics if originally derived from state. Conceptions of welfare state and increase in the duties
and functions of state are reasons for the increase in the importance of Statistics in Government
administration. For efficient administration, statistics are essential tools. The government have
to collect statistical data whenever they adopt measures to achieve the objectives like reducing
inequalities in the distribution of wealth, income etc. The Government administration n is run
through budgets which are formulated on the basis of statistics. The commissions and
committees appointed by the Governments base their reports on statistics. A state, besides
being an administrative body is a big commercial concern also. So it needs statistics to carry
on these business works. Thus it can be said that statistics is the point around which government
activities cluster.

To Research: Modern statistical methods and statistical data are being found increasingly
useful in research in different fields. In the field of science, in the literary field, in the field of
business activities, in the field of economic activities, research works are being undertaken
with the help of statistical methods.

In Planning: Modern age is an age of planning. For the planning to be successful, statistical
data are necessary. So planning cannot be managed without statistics. National sample survey
scheme was primarily started to collect statistical data.

For Bankers, brokers and Insurance Companies: Statistical methods help various economic
entities. A banker has to make statistical study of business cycles. The stock exchange brokers
speculators and investors etc. have to rely on statistical data for precise forecasting. The
Success of insurance company depends on the accurate basic data that it uses for the calculation
of premium rates etc.

3
USE OF STATISTICAL METHODS IN SOCIAL RESEARCH

Statistics has patently two broad functions. The first of these functions is description and the
summarizing of information in a manner so as to make it more usable.

The second function of statistics is induction, which involves either making generalizations
about some ‘population’ on the basis of a sample drawn from this population or formulating
general laws on the basis of repeated observations. The two functions of statistical methods
can be easily understood by the following example. Suppose it is desired to study the problem
of labour unrest in a particular area. The first thing to be done here will be to analyse the various
causes of labour unrest and to stdy the impact of each one of these on the various categories of
labour, viz., male workers and female workers or skilled labour and unskilled labour. This kind
of analysis will give us an insight into the problem and we may be able to know from such an
analysis many important things, e.g., that the involvement of male workers in strikes is much
higher than that of the female workers or that the labour unrest in big industries is much higher
than in small industries. Such an analysis may lead us to the conclusion regarding the incidence
of labour unrest in the country and factors responsible for it. the former example illustrates the
process of descriptive statistics whereas the latter, that of inductive statistics.

There are essentially two reasons why the expertise in statistics and the need to study statistics
have grown enormously in the field of social sciences. One reason is that the huge amount of
data collected by researchers needs simplification so as to render them capable of being
commonly understood without much difficulty. The second and even more important reason is
the increasing quantitative approach being currently employed in social science research.

Seemingly statistical considerations enter only at the analysis stage of the research process after
the data have been collected, and near to the point in time when the initial plans for analysis
are formulated and a sample is to be drawn. But this does not imply that a social researcher can
plan and carry out his entire research without any knowledge of statistics and then hand over
the data to the statistician for analysis. If a researcher lacked conversance in statistics the results
of a costly research project would probably be disappointing if not unless.

Indeed, the problems that will be encountered in analysis and interpretation have to be
anticipated at every stage in the research process and in this sense, statistical methods are
involved throughout. This implies that statistics is a very useful tool for the social scientist. It
is a much more useful tool for exploratory analyses than might possibly be imagined.

4
 • Statistics is helpful in data collection
• Statistics is helpful in investigation
• Statistics provide the tools of comparison and further evaluation
• Statistics is useful in planning controlling and decision making
• Statistics facilitate the idea of character, size and summary of data
• Statistics helps in estimation and prediction and interpretation
• Statistics fetch the reliable results
• Statistics can condense the data without affecting the objectivity
• Statistics can very well measure the interrelation between two or more variable
• Statistics can reduce the time and cost and can increase the scope and accuracy in
research and its findings

THE FOLLOWING ARE SOME IMPORTANT LIMITATIONS OF STATISTICS:

1. Statistics does not study individuals. It deals with an aggregate of facts and ones not give
any specific recognition to the individual items of a series. Individual items, taken separately,
do not constitute statistical data and are meaningless for any statistical inquiry. W.I. King
observes: “Statistics from their very nature of subject cannot and will never be able to take into
account individual cases. When these are never be able to take into account individual cases.
When these are important, other means must be used for their study.” Hence, statistical analysis
is only for those problems where group characteristics are to be studied.

2. Statistics does not study qualitative phenomena. Being a science dealing with a set of
numerical data, it is applicable only to the quantitative aspect of a problem. As such, qualitative
phenomena like honesty, poverty, wisdom, etc., which cannot be expressed numerically, are
not capable of direct statistical analysis. However, statistical techniques may be applied
indirectly by first reducing the qualitative expressions into some quantitative terms. For
example, the intelligence of a group of candidates can be studied on the basis of the scores
assigned for various qualitative characteristics.

3. Statistical results are true only on an average. W.I. King writes, “Statistics largely deals with
averages and these averages may be made up of individual items radically different from each
other.” We known that statistical results reveal the average behaviour, the normal or the general

5
trend; they are, therefore, useful for a general appraisal of a phenomenon and not for
substitutions for any specific unit or event. Sometimes the average or trend indicated by
statistics is applied to individual cases which are not proper. This may lead to what is called
the error of false deduction. For example, the per capita income figure of Indians cannot be
used for forming an idea about the income of an individual or a group without knowing the
dispersion of income which would show the degree of variability in incomes of the units
comprising the group.

4. Statistical laws are not exact. Unlike the laws of physical and natural sciences, statistical
laws are only approximations and not exact. On the basis of statistical analysis of the problem,
we can talk only in terms of probability and not certainty.

5. Statistics does not reveal the entire story. It only simplifies and helps the analysis of certain
qualitative facts. But the real background of the data may not be reflected through these facts.

6. Statistics is liable to be misused. Perhaps the most important limitation of statistics is that it
must be used by experts. As the saying goes “statistics one of the dangerous tool in the hands
of the in experts”. Thus the use of statistics by the inexperienced and untrained person might
lead to very fallacious conclusions.

CLASSIFICATION AND TABULATION

After the data are collected with the help of questionnaire, interview schedule, observation etc,
they need to be properly tabulated and presented. This process helps the researcher to eliminate
the unnecessary details and keeps only the relevant part of the whole collected. The procedure
adopted for this purpose is known as the method of classification and tabulation.
L.R.Connor has defined classification in the following words: “Classification is the
process of arranging things – either actually or notionally – in groups or classes according to
their resemblances and affinities.”

Objectives of classification

The objectives of the classification are given below:

a) Through classification, the complex, scattered and haphazard data is organized into
concise, logical and intelligible form

6
 b) Through classification, it is possible to make the characteristics of similarities and
dissimilarities clear.
c) Through classification, comparative study is possible
d) Through classification, understanding of significance is made easier and thereby
good deal of human energy is saved.
e) Underlying unity amongst different items is made clear and expressed.
f) Data is so arranged that analysis and generalization become possible.

Types of classification

Classification is of two types, viz. quantitative classification, which is on the basis of

variables or quantity and qualitative classification (classification according to attributes). The
former is the way of grouping the variables, say, quantifying the variables in cohesive groups,
while the latter groups the data on the basis of attributes or qualities. Various enquires deal
with qualitative phenomena which cannot be reduced to numerical characteristics. These are
to be classified according to attributes and is technically known as ‘classification according to
attributes’. Suppose, in a particular enquiry, we have to deal with blindness, baldness,
deafness, etc. These are ‘qualities’ or attributes which cannot be directly ‘measured’. In this
type of enquiry and their classification may be based on the ‘units’ having these attributes or
not-possessing these attributes.

Simple classification or classification by Dichotomy

Simple classification or classification by dichotomy is another method of classification.

If the ‘object’ of classification is a simple one and can easily be put under two columns, its is
known as simple classification. Under this type, we normally deal with simple attributes and
their classification. Suppose, the male population of a particular area is to be classified into
educated and non-educated only, then the type of classification adopted would be known as
simple classification.

Classification on Periodical Basis

In this type of classification the data belonging to a particular time or period is put under
one class. This type of classification is based on period.

7
Classification on Geographical Basis

In this type of classification, the data has been collected from different places and
placed in different classes. For example, the income for different states may be classed under
different head on the basis of the geographical arrangements or pattern.

TABULATION

“Tabulation is a process of orderly arrangement of data into series of rows and columns
where they can be read in two dimensions.” Tabulation is essential to represent a particular
result of enquiry or investigation. Analysis of data is made through tables. Therefore,
preparing tables is a very important step. Tabulation may be by hand, mechanical or electronic.
The choice is made largely on the basis of the size and type of study, alternative costs, time
pressures, and the availability of computers and computer programmes.

Tables can be divided into :

1) Frequency tables
2) Response tables
3) Contingency tables
4) Univariate tables
5) Bivariate tables
6) Statistical tables
7) Time series tables

As a general rule the following steps are necessary in the preparation of table

i) Title of Table: The table should be first given a brief, simple and clear title which
may express the basis of classification
ii) Columns and Rows: Each table should be prepared in just adequate number of
columns and rows
iii) Captions and Stubs: The columns and rows should be given simple and clear
captions and stubs
iv) Ruling: Columns and rows should be divided by means of thin or thick rulings
v) Arrangement of items: Comparable figures should be arranged side by side

8
 vi) Derivations: These should be arranged in the column near the original data so that
their presence may easily be noted.
vii) Size of columns: This should be according to requirement
viii) Arrangement of items: This should be according to the problem
ix) Special Emphasis: This can be done by writing important data in bold or special
letters
x) Unit of measurement: The unit should be noted below the line
xi) Approximation: This should also be noted below the title.
xii) Foot notes: These may be given below the table
xiii) Total : Totals of each column and grand total should be in one line.
Types of Tabulations

On the basis of construction, tables have been classified as follows:

Simple table: This is made on the basis of just one quality or character. Hence, it is called one
– way table. Examples of such tabulation are the classification of states on the basis of
population, distribution of students on the basis of subjects of their study, etc.

Complex table: This is formed on the basis of more than one quality or characteristic, e.g.,
distribution of students on the basis of sex and marks obtained, etc. If complex table is based
on two qualities it is called a two-way table and if it is based on three qualities, it is named
three-way table. If there are more than three qualities, it is called manifold – table.

Methods of Tabulation

Hand Tabulation

When the survey is a small sample survey and a few questionnaires are filled
in, it is simple to sort them out manually. Generally, cards are used in collecting information.
A card is a thick paper in which collected information is recorded as it is or in a coded manner.
The questionnaires or cards are put in different lots, for example, we can sort them out i) male
workers and ii) female workers. We can count them out and get the desired information.

Mechanical Tabulation

It is used when there are a large number of questionnaires involved in a survey.

Mechanical sorting and tabulation help us to organize the work speedily and accurately. But
the system is pretty costly and can be used only when the study is very expensive. The tabulator

9
is used for adding, subtracting and accumulating totals and for printing contents of punched
cards. It can also be used for complex tabulations and some of the statistical calculations.

Electronic Computers

The use of electronic computers have revolutionized data analysis. They can
perform all the specialized functions at a much higher speed. The use of computers has
facilitated large scale studies and above all the use of complex techniques of analysis such as
multi-variate analysis, factor analysis and the like.

The researcher who wishes to use computer for data processing has to locate an
appropriate program among the programs available with computer installations. In recent
times, some computer programs suitable for research analysis have been developed. One of
them is Statistical Package for the social sciences (SPSS). It is an integrated set of programs
suitable for analysis of social science data.

Frequency Table
A table that displays the number and or percentage of units (people) in different categories of
a variable. Frequency tables are the normal tabular method of presenting distributions of a
single variable. Tabulation is a process of summarizing raw data and displaying them on
compact statistical tables for further analysis. It involves counting the number of cases falling
into each of the categories identified by the researcher. Tabulation can be done manually or
through the computer. The choice depends upon the size and type of study, cost considerations,
time pressures and the availability of software packages. Manual tabulation is suitable for small
and simple studies.
Construction of Frequency Table

Frequency tables provide a ‘shorthand’ summary of data. The importance of presenting

statistical data in tabular form needs no emphasis. Tables facilitate comprehending masses of
data at a glance; they conserve space and reduce explanations and descriptions to a minimum.
They give a visual picture of relationships between variables and categories. They facilitate
summation of items and the detection of errors and omissions and they provide a basis for
computations.

10
 It is important to make a distinction between the general purpose tables and specific
tables. The general purpose tables are primary or reference tables designed to include large
amounts of source data in convenient and accessible form. The special purpose tables are
analytical or derivate ones that demonstrate significant relationships in the data or the results
of statistical analysis. Tables in reports of government on population, vital statistics,
agriculture, industries etc., are of general purpose type. They represent extensive repositories
of statistical information. Special purpose tables are found in monographs, research reports
and articles and are used as instruments of analysis. In research, we are primarily concerned
with special purpose tables.

DIAGRAMMATICAL AND GRAPHICAL REPRESENTATION OF DATA

In presenting the data of frequency distributions and statistical computations, it is often

desirable to use appropriate forms of graphic presentation. In addition to tabular forms, graphic
presentation involves use of graphics, charts and other pictorial devices such as diagrams.
These forms and devices reduce large masses of statistical data to a form that can be quickly
understood at a glance. The meaning of figures in tabular form may be difficult for the mind
to grasp or retain. “Properly constructed graphs and charts relieve the mind of burdensome
details by portraying facts concisely, logically and simply.”

The device of graphic presentation is particularly useful when the prospective readers
are non technical people or general public. It is useful to even technical people for dramatizing
certain points about data for important points can be more effectively captured in pictures than
in tables. However, graphic forms are not substitutes for tables, but are additional tools for the
researcher to emphasize the research findings. Graphic presentation must be planned with
utmost care and diligence. Graphic forms used should be simple, clear and accurate and also
be appropriate to the data.

Bar Diagram

These charts consist of either vertical or horizontal bars to represent variables. The
length of the bars varies corresponding to the values of the variable. Bar charts are the most
effective pictorial device for comparing data. The bars may be depicted in solid blocks or in
patterns of dots, dashes etc. They may be of different forms: (1) linear or one – dimensional
(2) a real or two dimensional, and (3) cubic or three dimensional. The actual numerical values
may be shown on the X- axis or Y – axis.

11
 Vertical bar charts consists of vertical bars or columns erected on the horizontal line
and the values of the bars are shown on the Y axis.

Horizontal Bar charts are commonly used for presenting qualitative and geographical
distributions. They are also used for discrete quantitative distributions.

Component bar chart : This is employed to show comparisons involving two or more
variables on a single chart. This may consist of either horizontal bars or vertical bars. This
type of chart shows not only variations in total values, but also components of the respective
totals.

Simple Bar (vertical) Diagram :

India's Total Population During 1951 and 2000 (in
crores)
120
100.1
Population (in crores)

100
84.6
80 68.3
54.8
60
43.9
36.1
40

20

0
1951 1961 1971 1981 1991 2001
Year

Simple Bar (Horizontal) Diagram :

India's Total Population During 1951 and 2000
(in crores)

2001 100.1

1991 84.6

1981 68.3
Year
1971 54.8

1961 43.9

1951 36.1

0 20 40 60 80 100 120
Population (in crores)

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 Component Bar chart: India's population (male & females) during
1951 and 2000 (in crores)

120
100
Population

80
Male
60
Female
40
20
0
1951 1961 1971 1981 1991 2001
Year

Pie Diagram

The circle or pie chart is a component parts bar chart. The component parts form the
segments of the circle. The circle chart is usually a percentage chart. The data are converted
to percentage of total; and the proportional segments, therefore, give a clear picture of the
relationship among the component charts. The name of each segment and its percentage are
placed inside its own area. When a segment is too small, an arrow is drawn to it and the legend
is placed outside, in a horizontal position. The pie chart is commonly used for presenting the
sectoral distribution of national income, the cost structure of a firm, or any other type of simple
percentage distribution.

Pie Digram of Percentage Distribution of Crimes

(IPC) in India in 1998
Violent
crimes, 14%

property
crimes, 23%

other crimes,
60%

economic
crimes, 3%

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Graphs

Graphs offer a visual presentation of the results. The horizontal line is the x-axis and
vertical line intersecting it, is y-axis or ordinate. The point of intersection is the origin. The
values of independent variable are scaled on the x-axis and of dependent variable on the y-axis.
Some times, the multiple line graph is also used for indicating comparisons between two or
more elements

Graph - Male and Female population of India (between 1941 and 2000)

60
Population in crores

50 52
43.9
40 40
35.3
30 32.1
28.4 26
20 22.6 22.1
18.5 18.2
10 12.5

0
1951 1961 1971 1981 1991 2001
Year
Male Female

Histograms

In histogram, the values of variables are presented in vertical bars drawn adjacent to
each other. The difference between graph and histogram is that while in graph, points are
plotted and then joined with each other, in the histogram only bars are drawn. A histogram can
be transformed into a line graph by joining the mid-points of the tops of blocks with straight
lines.

Histogram - Population of India (between 1941 and 2000)

60 52
Population in crores

50 43.9
40 35.3
28.4
30 22.6
18.5
20
10
0
1951 1961 1971 1981 1991 2001
Year

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Frequency Polygon

It is often more convenient to draw a frequency polygon instead of drawing a histogram

of a distribution. In laying out a frequency polygon, the frequency of each class is located at
the midpoint of the interval and straight lines then connect the plotted points. If two or more
series are shown on the same graph, the curves can be made with different kinds of ruling. If
the total number of cases in the two series is of different size, the frequencies are often reduced
to percentages. The frequency polygon is particularly appropriate for portraying continuous
series.

Frequency curve

Another method of representation is t draw the frequency curves. It is a process in

which basis is the histogram. It follows the making off of the midpoints on the upper surface
of the frequency rectangles. The essential difference between a frequency polygon and a
frequency curve is that while the former is obtained by joining the midpoints by straight lines,
in latter case, a freehand smooth curve is drawn. The greatest advantage of this method is the
simplicity of its drawing and a more natural appearance

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Cumulative Frequency Polygon:
Cumulative frequency polygon is similar to a frequency polygon. The difference is that in
creating a cumulative frequency polygon we consider cumulative frequencies instead of actual
frequencies. Cumulative frequency of less than type is obtained by adding the frequency of
each class interval to the sum of all frequencies in the lower intervals.

Cumulative Frequency Curve (ogives):

Ogive
The ogive is a line chart plotted on arithmetic graph paper from a cumulative frequency
distribution that maybe cumulated upward or downward. It is useful in representing population,
per capital income, per capital earnings etc. Converting the data of the distribution of the
percentage of the total then cumulating the percentages and plotting the ogives on the same
grid may give a useful comparison of two or more distributions. The differences in steepness
and share of the ogives facilitate comparative observations

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MEASURES OF CENTRAL TENDECY
Measures of central tendency encapsulate in one figure a value that is typical for a distribution
of values.It is also known as Statistical average.
MEAN
There are three types of mean
1. Arithmetic mean
2. Geometric mean
3. Harmonic mean
Simple arithmetic mean
The arithmetic mean is most commonly used statistical average in the disciplines such as
commerce, management, economics, etc. the arithmetic mean of series of data in the sum of all
the values divided by this total numbers. If x1,x2 …. ,xn are the ‘n’ values of the variant x. the
arithmetic mean of these values which is denoted by x is defined by
x--= (X1+X2+…+X2) n =Σx/n
Where Σ stands for the sum of all observations.
Advantages
1. The arithmetic mean is the most familiar and widely used measure of central tendency. It
is simple to understand and easy to calculate.
2. It is rigidly defined.
3. It acts as a single representative value of the whole data.
4. Its calculation depends upon all the values in the series.
5. It is suitable for algebraic treatment.
6. It is least affected by sampling fluctuations.
7. It is useful in further statistical analysis, i.e. useful in the computation of standard
deviation, correlation, coefficient of skewness, etc.

Disadvantages
1. It is very much affected by the presence of a few extremely large or small values of the
variable.
2. Mean cannot be calculated, if a single item is missing.
3. Arithmetic mean form a grouped frequency distribution cannot be calculated unless some
assumptions are made regarding the sizes of the classes.
4. Arithmetic mean has no significance of its own.
5. For non-homogeous data, the average may give misleading conclusions.

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Median
Median is another measure of central tendency. This is the mid-point in a distribution of values.
Unlike arithmetic mean, median is based on the position of a given observation in a series
arranged in ascending order. Therefore, it is called positional average. It is unaffected by the
presence of an extremely large or small value. Median of a given series is the value of the
variable that divides the series into two equal parts. It can be calculated from a grouped
frequency distributions with the open-end classes.
Calculation of Median
Ungrouped Data: The given values are arranged in order of magnitudes. Median is calculated
by formula((n+1)/2)th item, N being the numbers of items.
When N id odd: When the number of observations is an odd number, the median will be
calculated by the formula N-((N+1)/2) the item, where ‘N” is the numbers of items.
Advantages
1. It is simple to understand and easy to calculate.
2. For an open-end distribution median gives a more representative value.
3. For a qualitative phenomena, median is the most suitable average.
4. It is not affected by the extreme values
5. It is rigidly defined.
Disadvantages
1. It is not based on all the values.
2. It is much affected by sampling fluctuations in comparison to mean
3. It is not suitable for algebraic treatment.
4. Its calculation depends on the arrangement of the data inorder of magnitude.
5. The formula for median depends on the assumption that the items in the median class are
uniformly distributed, which is not very true.

Mode
Mode is another measure of central tendency. It is also a positional average like the median.
The mode is defined as the most frequently occurring value. In other words mode is that value
of frequency distribution whose frequency is maximum. But for some frequency distributions
mode may not be most frequent value. It is that value of the variate around which other items
tend to concentrate most heavily. For some distributions the mode may not exist and even if it
exists it may not be unique as there may be more than one mode. A distribution having only

18
one mode is called unimodal,the distribution having two modes is called bimodal and the
distribution having more than two modes is called multimodal. Mode is often used in business.
In many situations mode is more suitable than mean or median. For example, when we speak
of “most common wage”. We mean model wage is the usage that the largest number of workers
receive. In the case of a shopkeeper who sells shoes, he is interested in knowing the size of
shoes which are commonly demanded.In such a situation, the mean would indicate a size that
may not fit any person. Mode will give most common size of shoe which is most usually
purchased by the customers.
Advantages
1. Mode is easily understood.
2. It is used widely for market research.
3. In certain situations mode is the only suitable average, e.g., modal size of shoes, model wages
etc.
4. For the preference of consumers’ product, the modal preference is considered.
5. Mode can be calculated for open end classes also provided the closed classes are of equal
widths.
6. It is not affected by extreme values.
Disadvantages
1. It is not always possible to find the well defined mode.
2. It is not suitable for further algebraic treatment.
3. It is not based on all the items of the data.
4. The value of the mode is affected significantly by the size of the class interval.

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