UNIT – I

INTRODUCTION
Meaning of research:
Research in simple terms refers to search for knowledge. It is a scientific and systematic search for
information on a particular topic or issue. It is also known as the art of scientific investigation.
Several social scientists have defined research in different ways.
Objectives of research:
The objective of research is to find answers to the questions by applying scientific procedures. In
other words, the main aim of research is to find out the truth which is hidden and has not yet been
discovered. Although every research study has its own specific objectives, theresearch objectives
may be broadly grouped as follows:
1. To gain familiarity with new insights into a phenomenon (i.e., formulative research studies);
2. To accurately portray the characteristics of a particular individual, group, or a situation (i.e.,
descriptive research studies);
3. To analyze the frequency with which something occurs (i.e., diagnostic research studies)
4. To examine the hypothesis of a causal relationship between two variables (i.e., hypothesis-
testing research studies).
Research Methods versus methodology:
Research methods include all those techniques/methods that are adopted for conducting research.
Thus, research techniques or methods are the methods that the researchers adopt for conducting
the research studies. On the other hand, research methodology is the way in which research
problems are solved systematically. It is a science of studying how research is conducted
scientifically. Under it, the researcher acquaints himself/herself with the various steps generally
adopted to study a research problem, along with the underlying logic behind them. Hence, it not only
important for the researcher to know the research techniques/ methods, but also the scientific
approach called methodology.
Research approaches:
Research approach is a plan and procedure that consists of the steps of broad assumptions to
detailed method of data collection, analysis and interpretation. It is therefore, based on the nature of
the research problem being addressed.
There are two main approaches to research, namely quantitative approach and qualitative
approach. The quantitative approach involves the collection of quantitative data, which are put to
rigorous quantitative analysis in a formal and rigid manner. This approach further includes
experimental, inferential, and simulation approaches to research. Meanwhile, the qualitative
approach uses the method of subjective assessment of opinions, behavior and attitudes. Research
in such a situation is a function of the researcher‘s impressions and insights. The results generated
by this type of research are either in non-quantitative form or in the form which cannot be put to
rigorous quantitative analysis. Usually, this approach uses techniques like in depth interviews, focus
group interviews, and projective techniques.
Types of research:
There are different types of research. The basic ones are as follows.
1. Descriptive versus analytical:
Descriptive research consists of surveys and fact-finding enquiries of different types. The main
objective of descriptive research is describing the state of affairs as it prevails at the time of study.
The term ‗ex post facto research‘ is quite often used for descriptive research studies in social
sciences and business research. The most distinguishing feature of this method is that the
researcher has no control over the variables here. He/she has to only report what is happening or
what has happened.Majority of the ex post facto research projects are used for descriptive studies in
which the researcher attempts to examine phenomena, such as the consumers‘ preferences,
frequency of purchases, shopping, etc. Despite the inability ofthe researchers to control the
variables, ex post facto studies may also comprise attempts by themto discover the causes of the
selected problem. The methods of research adopted in conducting descriptive research are survey
methods of all kinds, including correlational and comparative methods. Meanwhile in the Analytical
research, the researcher has to use the already available facts or information, and analyze them to
make a critical evaluation of the subject.
2. Applied versus fundamental:
Research can also be applied or fundamental in nature. An attempt to find a solution to an
immediate problem encountered by a firm, an industry, a business organization, or the society is
known as applied research. Researchers engaged in such researches aim at drawing certain
conclusions confronting a concrete social or business problem.
On the other hand, fundamental research mainly concerns generalizations and formulation of a
theory. In other words, ―Gathering knowledge for knowledge‘s sake is termed
‗pure‘ or ‗basic‘ research‖ (Young in Kothari, 1988). Researches relating to pure mathematics or
concerning some natural phenomenon are instances of Fundamental Research. Likewise, studies
focusing on human behavior also fall under the category of fundamental research.
Thus, while the principal objective of applied research is to find a solution to some pressing practical
problem, the objective of basic research is to find information with a broad base of application and
add to the already existing organized body of scientific knowledge.
3. Quantitative versus qualitative:
Quantitative research relates to aspects that can be quantified or can be expressed in terms of
quantity. It involves the measurement of quantity or amount. Various available statistical and
econometric methods are adopted for analysis in such research. Which includes correlation,
regressions and time series analysis etc,.
On the other hand, Qualitative research is concerned with qualitative phenomena, or more
specifically, the aspects related to or involving quality or kind. For example, an important type of
qualitative research is ‗Motivation Research‘, which investigates into the reasons for certain human
behavior. The main aim of this type of research is discovering the underlying motives and desires of
in-depth interviews. The other techniques employed in such research are story completion tests,
sentence completion tests, word association tests, and other similar projective methods. Qualitative
research is particularly significant in the context of behavioral sciences, which aim at discovering the
underlying motives of human behaviour. Such research helps to analyze the various factors that
motivate human beings to behave in a certain manner, besides contributing to an understanding of
what makes individuals like or dislike a particular thing. However, it is worth noting that conducting
qualitative research in practice is considerably a difficult task. Hence, while undertaking such
research, seeking guidance from experienced expert researchers is important.
4. Conceptual versus empirical:
The research related to some abstract idea or theory is known as Conceptual Research. Generally,
philosophers and thinkers use it for developing new concepts or for reinterpreting the existing ones.
Empirical Research, on the other hand, exclusively relies on the observation or experience with
hardly any regard for theory and system. Such research is data based, which often comes up with
conclusions that can be verified through experiments or observation. Empirical research is also
known as experimental type of research, in which it is important to first collect the facts and their
sources, and actively take steps to stimulate the production of desired information. In this type of
research, the researcher first formulates a working hypothesis, and then gathers sufficient facts to
prove or disprove the stated hypothesis. He/she formulates the experimental design, which
according to him/her would manipulate the variables ,so as to obtain the desired information. This
type of research is thus characterized by the researcher‘s control over the variables under study. In
simple term, empirical research is most appropriate when an attempt is made to prove that certain
variables influence the other variables in some way. Therefore, the results obtained by using the
experimental or empirical studies are considered to be the most powerful evidences for a given
hypothesis.
5. Other types of research:
The remaining types of research are variations of one or more of the afore-mentioned type of
research. They vary in terms of the purpose of research, or the time required to complete it, or may
be based on some other similar factor. On the basis of time, research may either be in the nature of
one-time or longitudinal time series research. While the research is restricted to a single time-period
in the former case, it is conducted over several time-periods in the latter case. Depending upon the
environment in which the research is to be conducted, it can also be laboratory research or field-
setting research, or simulation research, besides being diagnostic or clinical in nature. Under such
research, in-depth approaches or case study method may be employed to analyse the basic causal
relations. These studies usually undertake a detailed in-depth analysis of the causes of certain
events of interest, and use very small samples and sharp data collection methods. The research
may also be explanatory in nature. Formalized research studies consist of substantial structure and
specific hypotheses to be verified. As regards to historical research, sources like historical
documents, remains, etc. Are utilized to study past events or ideas. It also includes philosophy of
persons and groups of the past or any remote point of time.
Research has also been classified into decision-oriented and conclusion-oriented categories. The
decision-oriented research is always carried out as per the need of a decision maker and hence,
there searcher has no freedom to conduct the research according to his/her own desires. On the
other hand, in the case of Conclusion-oriented research, the researcher is free to choose the
problem, redesign the enquiry as it progresses and even change conceptualization as he/she
wishes. An operation research is a kind of decision- oriented research, where in scientific method is
used in providing the departments, a quantitative basis for decision-making with respect to the
activities under their preview.
Importance of knowing how to conduct research:
The importance of knowing how to conduct research are listed below:
i. The knowledge of research methodology provides training to new researchers and enables them
to do research properly. It helps them to develop disciplined thinking or a ‗bent of mind‘ to
objectively observe the field.

ii. The knowledge of doing research inculcates the ability to evaluate and utilize the research
findings with confidence.

iii. The knowledge of research methodology equips the researcher with the tools that help him/her to
make the observations objectively; and

iv. The knowledge of methodology helps the research consumers to evaluate research and make
rational decisions.

Qualities of are searcher:

It is important for a researcher to possess certain qualities to conduct research. First and foremost,
he being a scientist should be firmly committed to the ‗articles of faith‘ of the scientific methods of
research. This implies that a researcher should be a social science person in the truest sense. Sir
Michael Foster cited by (Wilkinson and Bhandarkar, 1979) identified a few distinct qualities of a
scientist. According to him, a true research scientist should possess the following qualities:
(1) First of all, the nature of are searcher must be of the temperament that vibrates in unison with
the theme which he is searching. Hence, the seeker of knowledge must be truthful with
truthfulness of nature, which is much more important, much more exacting than what is
sometimes known as truthfulness. The truthfulness relates to the desire for accuracy of
observation and precision of statement. Ensuring facts is the principle rule of science, which
is not an easy matter. The difficulty may arise due to untrained eye, which fails to see
anything beyond what it has the power of seeing and sometimes even less than that. This
may also be due to the lack of discipline in the method of science. An unscientific individual
often remains satisfied with the expressions like approximately, almost, or nearly, which is
never what nature is. A real research cannot see two things which differ, however minutely,
as the same.
(2) A researcher must possess an alert mind. Nature is constantly changing and revealing itself
through various ways. A scientific researcher must be keen and watchful to notice such
changes, no matter how small or insignificant they may appear. Such receptivity has to be
cultivated slowly and patiently over time by the researcher through practice. An individual who
is ignorant or not alert and receptive during his research will not makea good researcher. He
will fail as a good researcher if he has no keen eyes or mind to observe the unusual changes
behind the routine. Research demands a systematic immersion into the subject matter by the
researcher grasp even the slightest hint that may culminate into significant research
problems. In this context, Cohen and Negal cited by (Selltiz et al, 1965; Wilkinson and
Bhandarkar, 1979) state that ―the ability to perceive in some brute experience the occasion
of a problem is not a common talent among men… it is a mark of scientific genius to be
sensitive to difficulties where less gifted people pass by untroubled by doubt‖.
(3) Scientific enquiry is pre-eminently an intellectual effort. It requires the moral quality of
courage, which reflects the courage of a steadfast endurance. The process of conducting
research is not an easy task. There are occasions when a research scientist might feel
defeated or completely lost. This is the stage when a researcher would need immense
courage and the sense of conviction. The researcher must learn the art of enduring
intellectual hardships. In the words of Darwin, ―It‘s dogged that does it‖.
In order to cultivate the afore-mentioned three qualities of a researcher, a fourth one may be added.
This is the quality of making statements cautiously. According to Huxley, the assertion that outstrips
the evidence is not only a blunder but a crime (Thompson, 1975). A researcher should cultivate the
habit of reserving judgment when the required data are insufficient.
Significance of research:
According to a famous Hudson Maxim, ―All progress is born of inquiry. Doubt is often better than
overconfidence, for it leads to inquiry, and inquiry leads to invention‖. It brings out the significance of
research, increased amount of which makes the progress possible. Research encourages scientific
and inductive thinking, besides promoting the development of logical habits of thinking and
organisation. The role of research in applied economics in the context of an economy or business is
greatly increasing in modern times. The increasingly complex nature of government and business
has raised the use of research in solving operational problems. Research assumes significant role in
the formulation of economic policy for both, the government and business. It provides the basis for
almost all government policies of an economic system. Government budget formulation, for
example, depends particularly on the Analysis of needs and desires of people, and the availability of
revenues, which requires research. Research helps to formulate alternative policies, in addition to
examining the consequences of these alternatives. Thus, research also facilitates the decision-
making of policy-makers, although in itself is not a part of research. In the process, research also
helps in the proper allocation of a country‘s scarce resources.
 Research is also necessary for collecting information on the social and economic
structure of an economy to understand the process of change occurring in the country. Collection of
statistical information, though not a routine task, involves various research problems. Therefore,
large staff of research technicians or experts is engaged by the government these days to undertake
this work. Thus, research as a tool of government economic policy formulation involves three distinct
stages of operation:

(i) investigation of economic structure through continual compilation of facts; (ii) diagnosis of events
that are taking place and analysis of the forces underlying them; and (iii) the prognosis i.e., the
prediction of future developments (Wilkinson and Bhandarkar,1979).

Research also assumes significance in solving various operational and planning problems
associated with business and industry. In several ways, operations research, market research and
motivational research are vital and their results assist in taking business decisions. Market research
refers to the investigation of the structure and development of a market for the formulation of
efficient policies relating to purchases, production and sales. Operational research relates to the
application of logical, mathematical, and analytical techniques to find solution to business problems,
such as cost minimization or profit maximization, or the optimization problems. Motivational research
helps to determine why people behave in the manner they do with respect to market characteristics.
More specifically, it is concerned with the analysis of the motivations underlying consumer behavior.
All these researches are very useful for business and industry, and are responsible for business
decision-making.
Research is equally important to social scientists for analyzing the social relationships and seeking
explanations to various social problems. It gives intellectual satisfaction of knowing things for the
sake of knowledge. It also possesses the practical utility for the social scientist to gain knowledge so
as to be able to do something better or in a more efficient manner. The research in social sciences is
concerned with both knowledge for its own sake, and knowledge for what it can contribute to solve
practical problems.
Research process:
Research process consists of a series of steps or actions required for effectively conducting
research. The following are the steps that provide useful procedural guidelines regarding the
conduct of research:
(1) Formulating the research problem;
(2) Extensive literature survey;
(3) Developing hypothesis;
(4) Preparing the research design;
(5) Determining sample design;
(6) Collecting data;
(7) Execution of the project;
(8) Analysis of data;
(9) Hypothesis testing;
(10) Generalization and interpretation and
(11) Preparation of the reporter presentation of the results.
 In other words, it involves the formal write-up of conclusions.

Research problem:
The first and foremost stage in the research process is to select and properly define the research
problem. A researcher should first identify a problem and formulate it, so as to make it amenable or
susceptible to research. In general, a research problem refers to an unanswered question that a
researcher might encounter in the context of either a theoretical or practical situation, which he/she
would like to answer or find a solution to. A research problem is generally said to exist if the
following conditions emerge (Kothari, 1988):
i. There should be an individual or an organization, say X, to whom the Problem can be
attributed. The individual or the organization is situated in an environment Y, which is
governed by certain uncontrolled variables Z;
ii. ii. There should be at least two courses of action to be pursued, say A1 and A2. These
courses of action are defined by one or more values of the controlled variables. For
example, the number of items purchased at a specified time is said to be one course of
action.
iii. iii. There should be atleast two alternative possible outcomes of the said courses of
action, say B1 and B2. Of them, one alternative should be preferable to the other. That is,
atleast one outcome should be what the researcher wants, which becomes an objective.
iv. iv. The courses of possible action available must offer a chance to the researcher to
achieve the objective, but not the equal chance. Therefore, if P(Bj / X, A, Y) represents the
probability of the occurrence of an outcome Bj when X selects Aj in Y, then P(B1 / X,
A1,Y) ≠ P (B1 / X, A2, Y). Putting it in simple words, it means that the choices must not
have equal efficiencies for the desired outcome.
Above all these conditions, the individual or organization may be said to have arrived at the
research problem only if X does not know what course of action to be taken is the best. In other
words, X should have a doubt about the solution. Thus, an individual or a group ofpersonscan be
said to have a problem if they have more than one desired outcome. They should have two or
more alternative courses of action, which have some but not equal efficiency. This is required for
probing the desired objectives, such that they have doubts about the best course of action to be
taken. Thus, the components of a research problem may be summarized as:
a) There should be an individual or a group who have some difficulty or problem.

b) There should be some objective(s) to be pursued. A person or an organization who wants nothing
cannot have a problem.

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

d) There should be some doubt in the mind of the researcher about the choice of alternative means.
This implies that research should answer the question relating to the relative efficiency or suitability
of the possible alternatives.
Elements of a research problem:
A research problem refers to some difficulty either of a theoretical or practical character
which an individual or organization is experiencing and wants to obtain a solution for the same.
There are a number of elements (components) which a problem must have before it becomes a
research problem ready for study.
1. Objective or aim of the problem which is to be investigated. This answers the question
―Why?‖ Why is there a need for investigation, inquiry or study?
 2. The topic or theme which needs to be investigated. This answers the question
―What?‖ What is to be researched or studied?‖ For example: What would a rival company do if we
decrease our prices by 25%? What would sales be if prices were Rs. 89?Rs. 99? How would a rival
firms action influence our sales and profits? The right question needs to be addressed if research is
to help decision makers. The decision maker can‘t acquire all the information, but it is often feasible
to identify the factors that are critical to the existing problem. These factors are then included in the
problem definition.

3. The time dimension of a decision problem is always the future. The period or time of the
study when the data are to be gathered. This answers the question ―When?‖ When is the research
to be performed?‖ Managers frequently run the risk of making the correct decision at incorrect time.
It is essential that the decision maker as well as the researcher determine the right time reference
for-the decision.
4. The area or location in which the study is to be conducted. This answers the question
―Where?‖ Where we need to conduct the study? The space coordinates give you the geographic
boundaries within which the action is to be taken. In the problem definition, these lines are hardly
ever neat political divisions or subdivisions. The universe of interest should be defined either
conceptually or by enumeration.
5. Population or universe from whom the data needs to be gathered. This answers the question
―Who?‖ or ―from whom?‖ Who are the respondents? From who are the data to be collected?‖
They may include persons, groups of persons, business establishments. Criteria/ characteristics
of a good research problem:
Criteria for selection of research problem depend on the following characteristics.
• Personal Inclination.
• Resources Availability.
• Relative Importance. .
• Researcher Knowledge.
• Practicality: Practicality is also responsible for the selection. ...
• Time-lines of the Problem. ...
• Urgency.

Personal Inclination: The chief motivation in the way of selecting research problem is the personal
inclination of the researcher. If a researcher has personal interest in the topic, he would select that
problem for his research work
Resources Availability: During the selection, a researcher will see to the resources available. If
these resources like money, time, accommodation and transport are available to the selection place,
then the selection of the problem is easy.
Data Availability: If the desired data is available to the researcher, then the problem would be
selected.
Urgency: Urgency is a pinpoint in the way of the selection of research problem. Urgent problem
must be given priority because the immediate solution can benefit the people.
Feasibility: Feasibility is also an important factor for the selection of the research problem. The
researcher qualification, training and experience should match the problem.
Area Culture: The culture of the area for which a researcher conducts his research is also
responsible for the selection of research problem.
Characteristic of Research Problem
Any research is a difficult task to achieve and research needs to do a great effort. Selection of
research topic is the first step to success.
1. Research topic must be very clear and easy to understand. It should not distract people.
2. If a topic is well defined is the only way to successful research. The topic should not create doubt
and double impression.
3. Easy language is a key to success. Use technical words if necessary otherwise focus of
simplicity.
4. Research title should be according to the rules of titling. There are different rules of titling, a
researcher must aware before writing a research title.
5. While selecting a research topic current importance of a researcher should also be considered.
Topic should not be obsolete and it should have great importance in the current day.
Criteria of Good Research
Whatever may be the types of research works and studies, one thing that is important is that they all
meet on the common ground of scientific method employed by them. One expects scientific
research to satisfy the following criteria.
1. The purpose of the research should be clearly defined and common concepts be used.
2. The research procedure used should be described in sufficient detail to permit another researcher
to repeat the research for further advancement, keeping the continuity of what has already been
attained.
3. The procedural design of the research should be carefully planned to yield results that areas
objective as possible.
4. The researcher should report with complete frankness, flaws in procedural design and estimate
their effects upon the findings.
5. The analysis of data should be sufficiently adequate to reveal its significance and the methods of
analysis used should be appropriate. The validity and reliability of the data should be checked
carefully.

6. Conclusions should be confined to those justified by the data of the research and limited to those
for which the data provide an adequate basis.
7. Greater confidence in research is warranted if the researcher is experienced, has a good
reputation in research and is a person of integrity.
In other words, we can state the qualities of a good research12 as under:
1. Good research is systematic: It means that research is structured with specified steps to be taken
in a specified sequence in accordance with the well-defined set of rules. Systematic characteristic of
the research does not rule out creative thinking but it certainly does reject the use of guessing and
intuition in arriving at conclusions.

2. Good research is logical: This implies that research is guided by the rules of logical reasoning and
the logical process of induction and deduction are of great value in carrying out research. Induction
is the process of reasoning from a part to the whole where as deduction is the process of reasoning
from some premise to a conclusion which follows from that very premise. In fact, logical reasoning
makes research more meaningful in the context of decision making.
3. Good research is empirical: It implies that research is related basically to one or more aspects of
a real situation and deals with concrete data that provides a basis for external validity to research
results.
4. Good research is replicable: This characteristic allows research results to be verified by
replicating the study and thereby building a sound basis for decisions
Problems Encountered by Researchers in India
Researchers in India, particularly those engaged in empirical research, are facing several problems.
Some of the important problems are as follows:
1. The lack of a scientific training in the methodology of research is a great impediment for
researchers in our country. There is paucity of competent researchers. Many researchers take a
leap in the dark without knowing research methods. Most of the work, which goes in the name of
research is not methodologically sound. Research to many researchers and even to their guides, is
mostly a scissor and paste job without any insight shed on the collated materials. The consequence
is obvious, viz., the research results, quite often, do not reflect the reality or realities. Thus, a
systematic study of research methodology is an urgent necessity. Before undertaking research
projects, researchers should be well equipped with all the methodological aspects. As such, efforts
should be made to provide short duration intensive courses for meeting this requirement.
2. There is insufficient interaction between the university research departments on one side and
business establishments, government departments and research institutions on the other side. A
great deal of primary data of non-confidential nature remains untouched/untreated by the
researchers for want of proper contacts. Efforts should be made to develop satisfactory liaison
among all concerned for better and realistic researches. There is need for developing some
mechanisms of a university—industry interaction programme so that academics can get ideas from
practitioners on what needs to be researched and practitioners can apply the research done by the
academics.
3. Most of the business units in our country do not have the confidence that the material supplied by
them to researchers will not be misused and as such they are often reluctant in supplying the
needed information to researchers. The concept of secrecy seems to besacrosanct to business
organisations in the country so much so that it proves an impermeable barrier to researchers. Thus,
there is the need for generating the confidence that the information/data obtained from a business
unit will not be misused.
4. Research studies overlapping one another are undertaken quite often for want of adequate
information. This results in duplication and fritters away resources. This problem can be solved by
proper compilation and revision, at regular intervals, of a list of subjects on which and the places
where the research is going on. Due attention should be given toward identification of research
problems in various disciplines of applied science which are of immediate concern to the industries.
5. There does not exist a code of conduct for researchers and inter-university and inter departmental
rivalries are also quite common. Hence, there is need for developing a code of conduct for
researchers which, if adhered sincerely, can win over this problem.

6. Many researchers in our country also face the difficulty of adequate and timely secretarial
assistance, including computerial assistance. This causes unnecessary delays in the completion of
research studies. All possible efforts be made in this direction so that efficient secretarial assistance
is made available to researchers and that too well in time. University Grants Commission must play
a dynamic role in solving this difficulty.
7. Library management and functioning is not satisfactory at many places and much of the time and
energy of researchers are spent in tracing out the books, journals, reports, etc., rather than in tracing
out relevant material from them.
8. There is also the problem that many of our libraries are not able to get copies of old and new
Acts/Rules, reports and other government publications in time. This problem is felt more in libraries
which are away in places from Delhi and/or the state capitals. Thus, efforts should be made for the
regular and speedy supply of all governmental publications to reach our libraries.
9. There is also the difficulty of timely availability of published data from various government and
other agencies doing this job in our country. Researcher also faces the problem on account of the
fact that the published data vary quite significantly because of differences in coverage by the
concerning agencies.
10. There may, at times, take place the problem of conceptualization and also problems relating to
the process of data collection and related things.
Errors in selecting a research problem:
Researcher in selecting a research problem should be aware of
1. Subject which is overdone should not be normally chosen, for I will be a difficult task tothrow any
new light in such a case.
2. Controversial subject should not become the choice of an average researcher.
3. Naming a broad field/area of the study instead of a specific problem.
4. Starting it in such a way that investigation is impossible.
5. Narrowing/localizing a topic
6. Including in it terms of an unscientific, emotional or biased nature.
7. Lack of precision in the instruments.
8. Quantitative errors such as
- Population specification error
- Sampling error.
- Selection error
- Non response error
- Surrogate information error.
- Measurement error
- Experiment error.
Scope and objectives of research problem:
The scope of the study basically means all those things that will be covered in the research
project. objective of an activity, project or procedure represents the output or what you want to
accomplish by doing it.
Scope: Scope of an activity, project or procedure represents their limitations or defines the
boundaries of its application.
Research design:
The most important step after defining the research problem is preparing the design of the research
project, which is popularly known as the ‗research design. A research design helps to decide upon
issues like what, when, where, how much, by what means etc. With regard to an enquiry or a
research study. A research design is the arrangement of conditions for collection and analysis of
data in a manner that aims to combine relevance to the research purpose with economy in
procedure. In fact, research design is the conceptual structure within which research is conducted; it
constitutes the blueprint for the collection, measurement and analysis of data (Selltizetal, 1962).
Thus, research design provides an outline of what the researcher is going to do in terms of framing
the hypothesis, its operational implications and the final data analysis. Specifically, the research
design highlights decisions which include:
1. The nature of the study
2. The purpose of the study
3. The location where the study would be conducted
4. The nature of data required
5. From where the required data can be collected
6. What time period the study would cover
7. The type of sample design that would be used
8. The techniques of data collection that would be used
9. The methods of data analysis that would be adopted and
10. The manner in which the report would be prepared
In view of the stated research design decisions, the overall research design may be divided into the
following (Kothari 1988):

a) The sampling design that deals with the method of selecting items to be observed for the
selected study;
b) The observational design that relates to the conditions under which the observations are to be
made;
c) The statistical design had concerns with the question of how many items are to be observed, and
how the information and data gathered are to be analyzed; and
d) The operational design that deals with the techniques by which the procedures specified in the
sampling, statistical and observational designs can be carried out.
Features of research design:
The important features of Research Design may be outlined as follows:
i. It constitutes a plan that identifies the types and sources of information required for the Research
problem;
ii. It constitutes a strategy that specifies the methods of data collection and analysis which would be
adopted; and
iii. It also specifies the time period of research and monetary budget involved in conducting the
study, which comprise the two major constraints of undertaking any research
CONCEPTS RELATING TO RESEARCHDESIGN:
Some of the important concepts relating to Research Design are discussed below:
1. Dependent and independent variables:
A magnitude that varies is known as a variable. The concept may assume different quantitative
values like height, weight, income etc. Qualitative variables are not quantifiable in the strictest sense
of the term. However, the qualitative phenomena may also be quantified in terms of the presence or
absence of the attribute(s) considered. The phenomena that assume different values quantitatively
even in decimal points are known as ‗continuous variables. But all variables need not be
continuous. Values that can be expressed only in integer values are called ‗non-continuous
variables. In statistical terms, they are also known as ‗discrete variables. For example, age is a
continuous variable, whereas the number of children is a non-continuous variable. When changes in
one variable depend upon the changes in other variable or variables, it is known as a dependent or
endogenous variable, and the variables that cause the changes in the dependent variable are
known as the independent or explanatory or exogenous variables. For example, if demand depends
upon price, then demand is a dependent variable, while price is the independent variable. And, if
more variables determine demand, like income and price of the substitute commodity, then demand
also depends upon them in addition to the price of original commodity. In other words, demand is a
dependent variable which is determined by the independent variables like price of the original
commodity, income and price of substitutes.
2. Extraneous variables:
The independent variables which are not directly related to the purpose of the study but affect the
dependent variables, are known as extraneous variables. For instance, assume that are searcher
wants to test the hypothesis that there is a relationship between children‘s school performance and
their self-confidence, in which case the latter is an independent variable and the former, a
dependent variable. In this context, intelligence may also influence the school performance.
However, since it is not directly related to the purpose of the study undertaken by the researcher, it
would be known as an extraneous variable. The influence caused by the extraneous variable(s) on
the dependent variable is technically called the ‗experimental error‘. Therefore, a research study
should always be framed in such a manner that the influence of extraneous variables on the
dependent variable/s is completely controlled, and the influence of independent variable/s is clearly
evident. Control, One of the most important features of a good research design is to minimize the
effect of extraneous variable(s). Technically, the term ‗control‘ is used when a researcher designs
the study in such a manner that it minimizes the effects of extraneous variables. The term ‗control‘
is used in experimental research to reflect the restrain in experimental conditions.
3. Confounded relationship:
The relationship between the dependent and independent variables is said to be confounded by an
extraneous variable, when the dependent variable is not free from its effects.
4. Research hypothesis:
When a prediction or a hypothesized relationship is tested by adopting scientific methods, it is
known as research hypothesis. The research hypothesis is a predictive statement which relates to a
dependent variable and an independent variable. Generally, a research hypothesis must consist of
at least one dependent variable and one independent variable. Whereas, the relationships that are
assumed but not to be tested are predictive statements that are not to be objectively verified, thus
are not classified as research hypotheses.
5. Experimental and non-experimental hypothesis testing research:
When the objective of a research is to test a research hypothesis, it is known as hypothesis- testing
research. Such research may be in the nature of experimental design or non- experimental design.
The research in which the independent variable is manipulated is known as ‗experimental
hypothesis-testing research‘, whereas the research in which the independent
Variable is not manipulated is termed as ‗non-experimental hypothesis- testing research‘. For
example, assume that a researcher wants to examine whether family income influences the school
attendance of a group of students, by calculating the coefficient of correlation between the two
variables. Such an example is known as a non-experimental hypothesis- testing research, because
the independent variable - family income is not manipulated here. Again assume that the researcher
randomly selects150 students from a group of students who pay their school fees regularly and then
classifies them into two sub-groups by randomly including 75 in Group A, whose parents have
regular earning, and 75 in Group B, whose parents do not have regular earning. Assume that at the
end of the study, the researcher conducts a test on each group in order to examine the effects of
regular earnings of the parents on the school attendance of the student. Such a study is an example
of experimental hypothesis-testing research, because in this particular study the independent
variable regular earnings of the parents have been manipulated.
6. Experimental and control groups:
When a group is exposed to usual conditions in an experimental hypothesis-testing research, it is
known as ‗control group‘. On the other hand, when the group is exposed to certain new or special
condition, it is known as an ‗experimental group‘. In the afore-mentioned example, Group A can be
called as control group and Group B as experimental group. If both the groups, A and B are exposed
to some special feature, then both the groups may be called as
‗experimental groups‘. A research design may include only the experimental group or both the
experimental and control groups together.
7. Treatments:
Treatments refer to the different conditions to which the experimental and control groups are subject
to. In the example considered, the two treatments are the parents with regular earnings and those
with no regular earnings. Likewise, if a research study attempts to examine through an experiment
the comparative effect of three different types of fertilizers on the yield of rice crop, then the three
types of fertilizers would be treated as the three treatments.
8. Experiment:
Experiment refers to the process of verifying the truth of a statistical hypothesis relating to a given
research problem. For instance, an experiment may be conducted to examine the yield of a certain
new variety of rice crop developed. Further, Experiments may be categorized
intotwotypes,namely,‗absoluteexperiment‘and‗comparativeexperiment‘. If a researcher wishes to
determine the impact of a chemical fertilizer on the yield of a particular variety of rice crop, then it is
known as absolute experiment. Meanwhile, if the researcher wishes to determine the impact of
chemical fertilizer as compared to the impact of bio-fertilizer, then the experiment is known as a
comparative experiment.
9. Experimental unit(s):
Experimental units refer to the pre-determined plots, characteristics or the blocks, to which different
treatments are applied. It is worth mentioning here that such experimental units must be selected
with great caution.
Types of research design:
There are different types of research designs. They may be broadly categorized as:
(1) Exploratory research design;
(2) Descriptive and diagnostic research design; and
(3) Hypothesis-testing research design.

1. Exploratory research design:

The Exploratory Research Design is known as formulative research design. The main objective of
using such a research design is to formulate a research problem for an in-depth or more precise
investigation, or for developing a working hypothesis from an operational aspect. The major purpose
of such studies is the discovery of ideas and insights. Therefore,
sucharesearchdesignsuitableforsuchastudyshouldbeflexibleenoughto provide opportunity for
considering different dimensions of the problem understudy. The in- built flexibility in research
design is required as the initial research problem would be transformed Into a more precise one in
the exploratory study, which in turn may necessitate changes in the research procedure for
collecting relevant data. Usually, the following three methods are considered in the context of a
research design for such studies. They are (a) a survey of related literature; (b) experience survey;
and (c) analysis of ‗insight-stimulating instances.
2. Descriptive and diagnostic research design:
A Descriptive Research Design is concerned with describing the characteristics of a particular
individual or a group. Meanwhile, a diagnostic research design determines the frequency with which
a variable occurs or its relationship with another variable. In other words, the study analyzing
whether a certain variable is associated with another comprises a diagnostic research study. On the
other hand, a study that is concerned with specific predictions or with the narration of facts and
characteristics related to an individual, group or situation, are instances of descriptive research
studies. Generally, most of the social research design falls under this category. As a research
design, both the descriptive and diagnostic studies share common requirements, hence they are
grouped together. However, the procedure to be used and the research design need to plan
carefully. The research design must also make appropriate provision for protection against bias and
thus maximize reliability, with due regard to the completion of the research study in an economical
manner. The research design in such studies should be rigid and not flexible. Besides, it must also
focus attention on the following:
a) Formulation of the objectives of the study,
b) Proper designing of the methods of data collection,
c) Sample selection,
d) Data collection,
e) Processing and analysis of the collected data, and
f) Reporting the findings.
3. Hypothesis-Testing research design:
Hypothesis-Testing Research Designs are those in which the researcher tests the hypothesis of
causal relationship between two or more variables. These studies require procedures that would not
only decrease bias and enhance reliability, but also facilitate deriving inferences about the causality.
Generally, experiments satisfy such requirements. Hence, when research design is discussed in
such studies, it often refers to the design of experiments.
Importance of Research design:
The need for a research design arises out of the fact that it facilitates the smooth conduct of the
various stages of research. It contributes to making research as efficient as possible, thus yielding
the maximum information with minimum effort, time and expenditure. A research design helps to
plan in advance, the methods to be employed for collecting the relevant data and the techniques to
be adopted for their analysis. This would help in pursuing the objectives of the research in the best
possible manner, provided the available staff, time and money are given. Hence, the research
design should be prepared with utmost care, so as to avoid any error that may disturb the entire
project. Thus, research design plays a crucial role in attaining the reliability of the results obtained,
which forms the strong foundation of the entire process of the research work.
Despite its significance, the purpose of a well-planned design is not realized at times. This is
because it is not given the importance that it deserves. As a consequence, many researchers are
not able to achieve the purpose for which the research designs are formulated, due to which they
end up arriving at misleading conclusions. Therefore, faulty designing of the research project tends
to render the research exercise meaningless. This makes it imperative that an efficient and suitable
research design must be planned before commencing the process of research. The research design
helps the researcher to organize his/her ideas in a proper form, which in turn facilitates him/her to
identify the inadequacies and faults in them. The research design is also discussed with other
experts for their comments and critical evaluation, without which it would be difficult for any critic to
provide a comprehensive review and comments on the proposed study.
Characteristics of a good research design:
A good research design often possesses the qualities of being flexible, suitable, efficient, and
economical and so on. Generally, a research design which minimizes bias and maximizes the
reliability of the data collected and analyzed is considered a good design (Kothari 1988). A research
design which does not allow even the smallest experimental error is said to be the best design for
investigation. Further, a research design that yields maximum information and provides an
opportunity of viewing the various dimensions of a research problem is considered to be the most
appropriate and efficient design. Thus, the question of a good design relates to the purpose or
objective and nature of the research problem studied. While a research design may be good, it may
not be equally suitable to all studies. In other words, it may be lacking in one aspect or the other in
the case of some other research problems. Therefore, no single research design can be applied to
all types of research problems.
A research design suitable for a specific research problem would usually involve the following
considerations:

i. The methods of gathering the information; ii. The skills and availability of the researcher and
his/her staff, if any;
iii. The objectives of the research problem being studied;
iv. The nature of the research problem being studied; and
v. The available monetary support and duration of time for the research work.
Case study research:
The method of exploring and analyzing the life or functioning of a social or economic unit,
such as a person, a family, a community, an institution, a firm or an industry is called case study
method. The objective of case study method is to examine the factors that cause the behavioral
patterns of a given unit and its relationship with the environment. The data for a study are always
gathered with the purpose of tracing the natural history of a social or economic unit, and its
relationship with the social or economic factors, besides the forces involved in its environment.
Thus, a researcher conducting a study using the case study method attempts to understand the
complexity of factors that are operative within a social or economic unit as an integrated totality.
Burgess (Kothari, 1988) described the special significance of the case study in understanding the
complex behavior and situations in specific detail. In the context of social research, he called such
data as social microscope.
Characteristics of a good sample design:
The following are the characteristic features of a good sample design

a. The sample design should yield a truly representative sample;

b. The sample design should be such that it results in small sampling error;
c. The sample design should be viable in the context of budgetary constraints of the research study;
d. The sample design should be such that the systematic bias can be controlled; and
e. The sample must be such that the results of the sample study would be applicable, in general, to
the universe at a reasonable level of confidence.
Data Collection & Sources of Data
1) Primary data, secondary data
2) Investigation
3) Indirect oral methods of collecting primary data
4) Direct personal Interviews
5) Information received through local agencies
6) Mailed Questionnaire method
7) Schedules Sent through enumerators
Introduction:
It is important for a researcher to know the sources of data which he requires for different purposes.
Data are nothing but the information. There are two sources of information or data they are - Primary
and Secondary data. The data are name after the source. Primary data refers to the data collected
for the first time, whereas secondary data refers to the data that have already been collected and
used earlier by somebody or some agency. For example, the statistics collected by the Government
of India relating to the population is primary data for the Government of India since it has been
collected for the first time. Later when the same 26

data are used by a researcher for his study of a particular problem, then the same data become the
secondary data for the researcher. Both the sources of information have their merits and demerits.
The selection of a particular source depends upon the
a) Purpose and scope of enquiry,
b) Availability of time,
c) Availability of finance,
d) Accuracy required, e)Statistical tools to be used,
f) Sources of information (data)
g) Method of data collection.
(a) Purpose and Scope of enquiry:
The purpose and scope of data collection or survey should be clearly set out at the very beginning. It
requires the clear statement of the problem indicating the type of information which is needed and
the use for which it is needed. If for example, the researcher is interested in knowing the nature of
price change over a period of time, it would be necessary to collect data of commodity prices. It
must be decided whether it would be helpful to study wholesale or retail prices and the possible
uses to which such information could be put. The objective of an enquiry may be either to collect
specific information relating to a problem or adequate data to test a hypothesis. Failure to set out
clearly the purpose of enquiry is bound to lead to confusion and waste of resources.
After the purpose of enquiry has been clearly defined, the next step is to decide about the scope of
the enquiry. Scope of the enquiry means the coverage with regard to the type of information, the
subject-matter and geographical area. For instance, an enquiry may relate to India as a whole or a
state or an industrial town wherein a particular problem related to a particular industry can be
studied.
b) Availability of time:
The investigation should be carried out within a reasonable period of time, failing which the
information collected may become outdated, and would have no meaning at all. For instance, if a
producer wants to know the expected demand for a product newly launched by him and the result of
the enquiry that the demand would be meager takes two ear to reach him, and then the whole
purpose of enquiry would become useless because by that time he would have already incurred a
huge loss. Thus, in this respect the information is quickly required and hence the researcher has to
choose the type of enquiry accordingly.
c) Availability of resources:
The investigation will greatly depend on the resources available like number of skilled personnel, the
financial position etc. If the number of skilled personnel who will carry out the enquiry is quite
sufficient and the availability of funds is not a problem, then enquiry can be conducted over a big
area covering a good number of samples, otherwise a small sample size will do.
d) The Degree of accuracy desired:
Deciding the degree of accuracy required is a must for the investigator, because absolute accuracy
in statistical work is seldom achieved. This is so because (i) statistics are based on estimates, (ii)
tools of measurement are not always perfect and (iii) there may be unintentional bias on the part of
the investigator, enumerator or informant. Therefore, a desire of 100% accuracy is bound to remain
unfulfilled. Degree of accuracy desired primarily depends upon the object of enquiry. For example,
when we buy gold, even a difference of 1/10 gram in its weight is significant, whereas the same will
not be the case when we buy rice or wheat. However, the researcher must aim at attaining a higher
degree of accuracy; otherwise the whole purpose of research would become meaningless.
e) Statistical tools to be used:
A well-defined and identifiable object or a group of objects with which the measurements or counts
in any statistical investigation are associated is called a statistical unit. For example, in socio-
economic survey the unit may be an individual, a family, a household or a block of locality. A very
important step before the collection of data begins is to define clearly the statistical units on which
the data are to be collected. In number of situations the units are conventionally fixed like the
physical units of measurement,suchasmeters,kilometers,quintals,hours,days,weeksetc., which are
well defined and do not need any elaboration or explanation. However, in many statistical
investigations, particularly relating to socio-economic studies, arbitrary units are used which must be
clearly defined. This is a must because in the absence of a clear cut and precise definition of the
statistical units, serious errors in the data collection may be committed in the sense that we may
collect irrelevant data on the items, which should have, in fact, been excluded and omit data on
certain items which should have been included. This will ultimately lead to fallacious conclusions.
f) Sources of information (Data):
After deciding about the unit, a researcher has to decide about the source from which the
information can be obtained or collected. For any statistical inquiry, the investigator may collect the
data first hand or he may use the data from other published sources, such as publications of the
government/semi-government organizations or journals and magazines etc.
g) Method of data collection:
There is no problem if secondary data are used for research. However, if primary data are to be
collected, a decision has to be taken whether (i) census method or (ii) sampling technique is to be
used for data collection. In census method, we go for total enumeration i.e., all the units of a
universe have to be investigated. But in sampling technique, we inspect or study only a selected
representative and adequate fraction of the population and after analyzing the results of the sample
data we draw conclusions about the characteristics of the population. Selection of a particular
technique becomes difficult because where population or census method is more scientific and
100% accuracy can be attained through this method, choosing this becomes difficult because it is
time taking, it requires more labor and it is very expensive. Therefore, for a single researcher or for a
small institution it proves to be unsuitable. On the other hand, sample method is less time taking,
less laborious and less expensive but 100% accuracy cannot be attained through this method
because of sampling and non-sampling errors attached to this method. Hence, a researcher has to
be very cautious and careful while choosing a particular method.
Methods of Collecting Primary Data:
Primary data may be obtained by applying any of the following methods:

1. Direct Personal Interviews.

2. Indirect Oral Interviews.
3. Information from correspondents.
4. Mailed questionnaire methods.
5. Schedule Sent through enumerators.

1. Direct personal interviews:

A face to face contact is made with the informants (persons from whom the information is to be
obtained) under this method of collecting data. The interviewer asks them questions pertaining to
the survey and collects the desired information. Thus, if a person wants to collect data about the
working conditions of the workers of the Tata Iron and Steel Company, Jamshedpur, he would go to
the factory, contact the were a obtain the desired information. The information collected in this
manner is first hand and also original in character. There are many merits and demerits of this
method, which are discussed asunder:
Merits:
• Most often respondents are happy to pass on the information required from them when contacted
personally and thus response is encouraging.
The information collected through this method is normally more accurate because interviewer can
clear doubts of the informants about certain questions and thus obtain correct information. In case
the interviewer apprehends that the informant is not giving accurate information, he may cross-
examine him and thereby try to obtain the information.
• This method also provides the scope for getting supplementary information from the informant,
because while interviewing it is possible to ask some supplementary questions which may be of
greater use later.
• There might be some questions which the interviewer would find difficult to ask directly but with
some tactfulness, he can mingle such questions with others and get the desired information. He
cannot twist the questions keeping in mind the informant‘s reaction. Precisely, a delicate situation
can usually he handled more effectively by a personal interview than by other survey techniques.
• The interviewer can adjust the language according to the status and educational level of the
person interviewed, and thereby can avoid inconvenience and misinterpretation on the part of the
informant.
Demerits:
• This method can prove to be expensive if the number of informants is large and the area is widely
spread.
• There is a greater chance of personal bias and prejudice under this method as compared to other
methods.
• The interviewers have to be thoroughly trained and experienced; otherwise they may not be able to
obtain the desired information. Untrained or poorly trained interviewers may spoil the entire work.
• This method is more time taking as compared to others. This is because interviews can be held
only at the convenience of the informants. Thus, if information is to be obtained from the working
members of households, interviews will have to be held in the evening or on week end. Even during
evening only an hour or two can be used for interviews and hence, the work may have to be
continued for a long time, or a large number of people may have to be employed which may involve
huge expenses.
2. Indirect Oral Interviews:
Under this method of data collection, the investigator contacts third parties generally called‗
witnesses‘ who are capable of supplying necessary information. This method is generally adopted
when the information to be obtained is of a complex nature and informants are not inclined to
respond if approached directly. For example, when the researcher is trying to obtain data on drug
addiction or the habit of taking liquor, there is high probability that the addicted person will not
provide the desired data and hence will disturb the whole research process. In this situation taking
the help of such persons or agencies or the neighbor‘s who know them well becomes necessary.
Since these people know the person well, they can provide the desired data. Enquiry Committees
and Commissions appointed by the Government generally adopt this method to get people‘s views
and all possible details of the facts related to the enquiry.
Though this method is very popular, its correctness depends upon a number of factors such as

i. The person or persons or agency whose help is solicited must be of proven integrity; otherwise
any bias or prejudice on their part will not bring out the correct information and the whole process of
research will become useless.
ii. The ability of the interviewers to draw information from witnesses by means of appropriate
questions and cross-examination.
iii. It might happen that because of bribery, nepotism or certain other reasons those who are
collecting the information give it such a twist that correct conclusions are not arrived at.
Therefore, for the success of this method it is necessary that the evidence of one person alone is
not relied upon. Views from other persons and related agencies should also be ascertained to find
the real position. Utmost care must be exercised in the selection of these persons because it is on
their views that the final conclusions are reached.
3. Information from correspondents:
The investigator appoints local agents or correspondents indifferent places to collect information
under this method. These correspondents collect and transmit the information to the central office
where data are processed. This method is generally adopted by newspaper agencies.
Correspondents who are posted at different places supply information relating to such events as
accidents, riots, strikes, etc., to the head office. The correspondents are generally paid staff or
sometimes they may be honorary correspondents also. This method is also adopted generally by
the government departments in such cases where regular information is to be collected from a wide
area. For example, in the construction of a wholesale price index numbers regular information is
obtained from correspondents appointed in different areas. The biggest advantage of this method is
that, it is cheap and appropriate for extensive investigation. But a word of caution is that it may not
always ensure accurate results because of the personal prejudice and bias of the correspondents.
As stated earlier, this method is suitable and adopted in those cases where the information is to be
obtained at regular intervals from a wide area.
4. Mailed questionnaire Method:
Under this method, a list of questions pertaining to the survey which is known as
‗Questionnaire‘ is prepared and sent to the various informants by post. Sometimes the researcher
himself too contacts the respondents and gets the responses related to various questions in the
questionnaire. The questionnaire contains questions and provides space for answers. A request is
made to the informants through a covering letter to fill up the questionnaire and send it back within a
specified time. The questionnaire studies can be classified on the basis of:

i. The degree to which the questionnaire is formalized or structured.

ii. The disguise or lack of disguise of the questionnaire and
iii. The communication method used.

When no formal questionnaire is used, interviewers adapt their questioning to each interview
as it progresses. They might even try to elicit responses by indirect methods, such as showing
pictures on which the respondent comments. When a researcher follows a prescribed sequence of
questions, it is referred to as structured study. On the other hand, when no prescribed sequence of
questions exists, the study is non-structured.
When questionnaires are constructed in such a way that the objective is clear to the
respondents then these questionnaires are known as non- disguised; on the other hand, when the
objective is not clear, the questionnaire is a disguised one. On the basis of these two classifications,
four types of studies can be distinguished:
1. Non-disguised structured,
2. Non-disguised non-structured,
3. Disguised structured and
4. Disguised non-structured.
There are certain merits and demerits of this method of data collection which are discussed below:
Merits:
• Questionnaire method of data collection can be easily adopted where the field of investigation
is very vast and the informants are spread over a wide geographical area.
• This method is relatively cheap and expeditious provided the informants respond in time.
• This method has proved to be superior when compared to other methods like personal
interviews or telephone method. This is because when questions pertaining to personal nature or
the ones requiring reaction by the family are put forth to the informants, there is a chance for them to
be embarrassed in answering them.
Demerits:
• This method can be adopted only where the informants are literates so that they can understand
written questions and lend the answers in writing.

• It involves some uncertainty about the response. Co-operation on the part of informants may be
difficult to resume.

• The information provided by the informants may not be correct and it may be difficult to verify the
accuracy.
However, by following the guidelines given below, this method can be made more effective: The
questionnaires should be made in such a manner that they do not become an undue burden on the
respondents; otherwise the respondents may not return them back.

i. Prepaid postage stamp should be affixed

ii. The sample should be large
iii. It should be adopted in such enquiries where it is expected that the respondents would return the
questionnaire because of their own interest in the enquiry.
iv. It should be preferred in such enquiries where there could be a legal compulsion to provide the
information.

5. Schedules sent through enumerators:

Another method of data collection is sending schedules through the enumerators or interviewers.
The enumerators contact the informants, get replies to the questions contained in a schedule and fill
them in their own handwriting in the questionnaire form. There is difference between questionnaire
and schedule. Questionnaire refers to a device for securing answers to questions by using a form
which the respondent fills in himself, whereas schedule is the name usually applied to a set of
questions which are asked in a face-to face situation with another person. This method is free from
most of the limitations of the mailed questionnaire method.
Merits:

The main merits or advantages of this method are listed below:

• It can be adopted in those cases where informants are illiterate.

• There is very little scope of non-response as the enumerators go personally
to obtain the information.
• The information received is more reliable as the accuracy of statements
can be checked by supplementary questions where ever necessary.
This method too like others is not free from defects or limitations. The main limitations are listed
below:

Demerits:

• In comparison to other methods of collecting primary data, this method is quite

costly as enumerators are generally paid persons.
• The success of the method depends largely upon the training imparted to the
enumerators.
• Interviewing is a very skilled work and it requires experience and training. Many
statisticians have the tendency to neglect this extremely important part of the data
collecting process and this result in bad interviews. Without good interviewing
most of the information collected may be of doubtful value.
• Interviewing is not only a skilled work but it also requires a great degree of
politeness and thus the way the enumerators conduct the interview would affect
the data collected. When questions are asked by a number of different
interviewers, it is possible that variations in the personalities of the interviewers
will cause variation in the answers obtained. This variation will not be obvious.
Hence, every effort must be made to remove as much of variation as possible
due to different interviewers.

Secondary Data:

As stated earlier, secondary data are those data which have already been
collected and analyzed by some earlier agency for its own use, and later the same
data are used by a different agency. According to W.A. Neiswanger, ―A primary
source is a publication in which the data are published by the same authority which
gathered and analyzed them. A secondary source is a publication, reporting the data
which was gathered by other authorities and for which others are responsible.‖
Sources of secondary data:

The various sources of secondary data can be divided into two broad categories:
1. Published sources, and
2. Unpublished sources.

1. Published sources:

The governmental, international and local agencies publish statistical data, and chief
among them are explained below:
(a) International publications:

There are some international institutions and bodies like I.M.F, I.B.R.D, I.C.A.F.E
 And U.N.O who publish regular and occasional reports on economic and statistical
matters.

(b) Official Publications of Central and State Governments:

Several departments of the Central and State Governments regularly publish

reports on a number of subjects. They gather additional information. Some of the
important publications are: The Reserve Bank of India Bulletin, Census of India,
Statistical Abstracts of States, Agricultural Statistics of India, Indian Trade Journal,
etc.

(c) Semi-official publications:

Semi-Government institutions like Municipal Corporations, District Boards

Panchayats, etc. Publish reports relating to different matters of public concern.

(d) Publications of research institutions:

Indian Statistical Institute (I.S.I), Indian Council of Agricultural Research (I.C.A.R),
Indian Agricultural Statistics Research Institute (I.A.S.R.I) etc. Publish the findings
of their research programs.

(e) Publications of various commercial and financial Institutions

(f) Reports of various Committees and Commissions appointed by the Government as

the Raj Committee‘s report on Agricultural Taxation, Wanchoo Committee‘s Report
on Taxation and Black Money, etc. Are also important source of secondary data.

(g) Journals and News Papers:

Journals and News Papers are very important and powerful source of secondary data.
Current and important materials on statistics and socio- economic problems can be
obtained from journals and newspapers like Economic Times, Commerce, Capital,
Indian Finance, Monthly Statistics of trade etc.

2. Unpublished sources:

Unpublished data can be obtained from many unpublished sources like records
maintained by various government and private offices, the theses of the numerous
research scholars in the universities or institutions etc.

Precautions in the use of secondary data:

Since secondary data have already been obtained, it is highly desirable that a proper scrutiny of
such data is made before they areused by the investigator. In fact, the user has to be extra-
cautious while using secondary data. In this context Prof. Bowel rightly points out
that―Secondary data should not be accepted at their face value.‖ The reason being that data
may be erroneous in many respect due to bias , inadequate size of the sample, substitution, errors
of definition, arithmetical errors etc. Even if there is no error such data may not be suitable and
adequate for the purpose of the enquiry. Prof. Simon Kuznet‘s view in this regard is also of
great importance. According to him, ―the degree of reliability of secondary source is to be
assessed from the source, the compiler and his capacity to produce correct statistics and the
users also, for the most part, tend to accept a series particularly one issued by a government
agency at its face value without enquiring its reliability‖.

Therefore, before using the secondary data the investigators should consider the following
factors:
4.The Suitability of data:

The investigator must satisfy himself that the data available are suitable for the purpose of
enquiry. It can be judged by the nature and scope of the present enquiry with the original enquiry.
For example, if the object of the present enquiry is to study the trend in retail prices, and if the
data provide only wholesale prices, such data are unsuitable.

a) Adequacy of data:

If the data are suitable for the purpose of investigation then we must consider whether the data
are useful or adequate for the present analysis. It can be studied by the geographical area
covered by the original enquiry. The time for which data are available is very important element.
In the above example, if our object is to study the retail price trend of India, and if the available
data cover only the retail price trend in the state of Bihar, then it would not serve the purpose.
b) Reliability of data:

The reliability of data is must. Without which there is no meaning in research. The reliability of
data can be tested by finding out the agency that collected such data. If the agency has used
proper methods in collection of data, statistics may be relied upon.

It is not enough to have baskets of data in hand. In fact, data in a raw form are nothing but a
handful of raw material waiting for proper processing so that they can become useful. Once
data have been obtained from primary or secondary source, the next step in a statistical
investigation is to edit the data i.e. to scrutinize the same. The chief objective of editing is to
detect possible errors and irregularities. The task of editing is a highly specialized one and
requires great care and attention. Negligence in this respect may render useless the findings of
an otherwise valuable study. Editing data collected from internal records and published sources is
relatively simple but the data collected from a survey need excessive editing.
While editing primary data, the following considerations should be borne in mind:
1. The data should be complete in every respect
2. The data should be accurate
3. The data should be consistent, and
4. The data should be homogeneous.

Data to possess the above mentioned characteristics have to undergo the same type
of editing which is discussed below:

5.Editing for completeness:

While editing, the editor should see that each schedule and
questionnaireiscompleteinallrespects.Heshouldseetoitthattheanswers to each and
every question have been furnished. If some questions are not answered and if
they are of vital importance, the informants should be contacted again either
personally or through correspondence. Even after all the efforts it may happen
that a few questions remain unanswered. In such questions, the editor should
mark ‗No answer‘ in the space provided for answers and if the questions are of
vital importance then the schedule or questionnaire should be dropped.

(a) Editing for consistency:

At the time of editing the data for consistency, the editor should see
that the answers to questions are not contradictory in nature. If they
are mutually contradictory answers, he should try to obtain the correct
answers either by referring back the questionnaire or by contacting,
wherever possible, the informant in person. For example, if amongst
others, two questions in questionnaire are (a) Are you a
student?
(b) Which class do you study and the reply to the first question is‗
no and to the latter ‗ tenth then there is contradiction and it should
be clarified.

(b) Editing for accuracy:

The reliability of conclusions depends basically on the correctness of

information. If the information supplied is wrong, conclusions can
never be valid. It is, therefore, necessary for the editor to see that the
information is accurate in all respects. If the inaccuracy is due to
arithmetical errors, it can be easily detected and corrected. But if the
cause of inaccuracy is faulty information supplied, it may be difficult to
 verify it and an example of this kind is information relating to income,
age etc.
(c) Editing for homogeneity:

Homogeneity means the condition in which all the questions have been
understood in the same sense. The edit or must check all the questions for
uniform interpretation. For example, as to the question of income, if
some informants have given monthly income, others annual income and
still others weekly income or even daily income, no comparison can
be made. Therefore, it becomes an essential duty of the editor to
check up that the information supplied by the various people is
homogeneous and uniform.

Choice between Primary and Secondary Data:

As we have already seen, there are a lot of differences in the methods

of collecting Primary and Secondary data. Primary data which is to be
collected originally involves an entire scheme of plan starting with the
definitions of various terms used, units to be employed, type of
enquiry to be conducted, extent of accuracy aimed at etc. For the
collection of secondary data, recompilation of the existing data would be
sufficient. A proper choice between the type of data needed for any
particular statistical investigation is to be made after taking into
consideration the nature, objective and scope of the enquiry; the time
and the finances at the disposal of the agency; the degree of precision
aimed at and the status of the agency (whether government- state or
central-or private institution of an individual).

In using the secondary data, it is best to obtain the data from the
primary source as far as possible. By doing so, we would at least save
ourselves from the errors of transcription which might have
inadvertently crept in the secondary source. Moreover, the primary
source will also provide us with detailed discussion about the
terminology used, statistical units employed, size of the sample and the
technique of sampling (if sampling method was used), methods of data
collection and analysis of results and we can ascertain ourselves if
these would suit our purpose. Now-a-days in a large number of
statistical enquiries, secondary data are generally used because fairly
reliable published data on a large number of diverse fields are now
available in the publications of governments, private organizations and
research institutions, agencies, periodicals and magazines etc. In fact,
primary data are collected only if there do not existany secondary data
 suited to the investigation under study. In some of the investigations
both primary as well as secondary data may be used.

Summary:

There are two types of data, primary and secondary. Data which are
collected first hand are called Primary data and data which
have already been collected and used by somebody are called
Secondary data. There are two methods of collecting data: (a) Survey
method or total enumeration method and (b) Sample method. When a
researcher goes for investigating all the units of the subject, it is called
sources of collecting Primary and Secondary data. Some of the
important sources of Primary data are—Direct Personal Interviews,
Indirect Oral Interviews, Information from Correspondents, mailed
questionnaire method, Schedules sent through enumerators and so
on. Though all these sources or methods of Primary data have their
relative merits and demerits, a researcher should use a particular
method with lot of care. There are basically two sources of collecting
secondary data- (a) Published sources and (b) Unpublished sources.
Published sources are like publications of different government and
semi-government departments, research institutions and agencies etc.
Where as unpublished sources are like records maintained by different
government departments and unpublished theses of different
universities etc. Editing of secondary data is necessary for different
purposes as editing for completeness, editing for consistency, editing
for accuracy and editing for homogeneity.

It is always a tough task for the researcher to choose between primary

and secondary data. Though primary data are more authentic and
accurate, time, money and labor involved in obtaining these more often
prompt the researcher to go for the secondary data. There are certain
amount of doubt about its authenticity and suitability, but after the arrival
of many government and semi government agencies and some private
institutions in the field of data collection, most of the apprehensions in
the mind of the researcher have been removed.

What is a Research Question?

A research question is a question that a study or research project, through its thesis
statement, aims to answer. This question often addresses an issue or a problem,
which, through analysis and interpretation of data, is answered in the study's
conclusion. In most studies, the research question is written so that it outlines
various aspects of the study, including the population and variables to be studied
and the problem the study addresses.

As their name implies, a research question is often grounded on research. As a

result, these questions are dynamic; this means researchers can change or refine
the research question as they review related literature and develop a framework for
the study. While many research projects will focus on a single research question,
larger studies often use more than one research question.

Importance of the research question

The primary importance of developing a research question is that it narrows down a

broad topic of interest into a specific area of study (Creswell, 2014). Research
questions, along with hypotheses, also serve as a guiding framework for research.
These questions also specifically reveal the boundaries of the study, setting its limits,
and ensuring cohesion.

Moreover, the research question has a domino effect on the rest of the study. These
questions influence factors, such as the research methodology, sample size, data
collection, and data analysis (Lipowski, 2008).

Types of Research Questions

Research questions can be classified into different categories, depending on the

type of research to be done. Knowing what type of research one wants to do—
quantitative, qualitative, or mixed-methods studies—can help in writing effective
research questions.

Doody and Bailey (2016) suggest a number of common types of research questions,
as outlined below.

Quantitative research questions

Quantitative research questions are precise. These questions typically include the
population to be studied, dependent and independent variables, and the research
design to be used. They are usually framed and finalized at the start of the study
(Berger, 2015).

Quantitative research questions also establish a link between the research question
and the research design. Moreover, these questions are not answerable with "yes"
or "no" responses. As a result, quantitative research questions don't use words such
as "is," "are," "do," or "does."

Quantitative research questions usually seek to understand particular social, familial,

or educational experiences or processes that occur in a particular context and/or
location (Marshall & Rossman, 2011). They can be further categorized into three
types: descriptive, comparative, and relationship.

• Descriptive research questions aim to measure the responses of a study's

population to one or more variables or describe variables that the research
will measure. These questions typically begin with "what". Students aim for a
what is research question to uncover particular processes.
• Comparative research questions aim to discover the differences between two
or more groups for an outcome variable. These questions can be causal, as
well. For instance, the researcher may compare a group where a certain
variable is involved and another group where that variable is not present.
• Relationship research questions seek to explore and define trends and
interactions between two or more variables. This research question design
often includes both dependent and independent variables and use words such
as "association" or "trends."

Qualitative research questions

Qualitative research questions may concern broad areas of research or more

specific areas of study. Similar to quantitative research questions, qualitative
research questions are linked to research design. Unlike their quantitative
counterparts, though, qualitative research questions are usually adaptable, non-
directional, and more flexible (Creswell, 2013). As a result, studies using these
questions generally aim to "discover," "explain," or "explore."

Ritchie et al. (2014) and Marshall and Rossman (2011) have also further categorized
qualitative research questions into a number of types, as listed below:

• Contextual research questions seek to describe the nature of what already

exists.
• Descriptive research questions attempt to describe a phenomenon.
• Emancipatory research questions aim to produce knowledge that allows for
engagement in social action, especially for the benefit of disadvantaged
people.
• Evaluative research questions assess the effectiveness of existing methods or
paradigms.
• Explanatory research questions seek to expound on a phenomenon or
examine reasons for and associations between what exists.
 • Exploratory research questions investigate little-known areas of a particular
topic.
• Generative research questions aim to provide new ideas for the development
of theories and actions.
• Ideological research questions are used in research that aims to advance
specific ideologies of a position.

The following table illustrates the differences between quantitative and qualitative
research questions.

Example: Factors that increase the likelihood of childhood anxiety include

peer pressure, genetics, and higher intelligence levels.

Topic childhood anxiety

Key aspects of the topic to be peer pressure, parental education, and higher
discussed intelligence levels

Mixed-methods studies

Mixed-methods studies typically require a set of both quantitative and qualitative

research questions. Separate questions are appropriate when the mixed-methods
study focuses on the significance and differences in quantitative and qualitative
methods and not on the study's integrative component (Tashakkori & Teddlie, 2010).

Researchers also have the option to develop a single mixed-methods research

question. According to Tashakkori and Teddlie (2010), this suggests an integrative
process or component between the study's quantitative and qualitative research
methods.

Steps to Developing a Good Research Question

Before learning how to write a research paper, you must first learn how to create a
research question. Based on the research question definition provided, formulate
your query. If you are looking for criteria for a good research question, Stone (2002)
says that a good research question should be relevant, decided, and meaningful.
Creating a research question can be a tricky process, but there is a specific method
you can follow to ease the process.

The following steps will guide you on how to formulate a research question:

1. Start with a broad topic.

A broad topic provides writers with plenty of avenues to explore in their search for a
viable research question. Techniques to help you develop a topic into subtopics and
potential research questions include brainstorming and concept mapping. For
example, you can raise thought-provoking questions with your friends and flesh out
ideas from your discussions. These techniques can organize your thoughts so you
can identify connections and relevant themes within a broad topic.

When searching for a topic, it's wise to choose an area of study that you are
genuinely interested in, since your interest in a topic will affect your motivation levels
throughout your research. It's also wise to consider the interests being addressed
recently by the research community, as this may affect your paper’s chances of
getting published.

2. Do preliminary research to learn about topical issues.

Once you have picked a topic, you can start doing preliminary research. This initial
stage of research accomplishes two goals. First, a preliminary review of related
literature allows you to discover issues that are currently being discussed by
scholars and fellow researchers. This way, you get up-to-date, relevant knowledge
on your topic.

Second, a preliminary review of related literature allows you to spot existing gaps or
limitations in existing knowledge of your topic. With a certain amount of fine-tuning,
you can later use these gaps as the focus of your research question.

Moreover, according to Farrugia et al. (2010), certain institutions that provide grants
encourage applicants to conduct a systematic review of available studies and
evidence to see if a similar, recent study doesn't already exist, before applying for a
grant.

3. Narrow down your topic and determine potential research questions.

Once you have gathered enough knowledge on the topic you want to pursue, you
can start focusing on a more specific area of study and narrowing down a research
question. One option is to focus on gaps in existing knowledge or recent literature.
Referred to by Sandberg and Alvesson (2011) as "gap-spotting," this method
involves constructing research questions out of identified limitations in literature and
overlooked areas of study. Similarly, researchers can choose research questions
that extend or complement the findings of existing literature.

Another way of identifying and constructing research questions: problematization

(Sandberg & Alvesson, 2011). As a research question methodology,
problematization aims to challenge and scrutinize assumptions that support others'
and the researcher's theoretical position. This means constructing research
questions that challenge your views or knowledge of the area of study.

Lipowski (2008), on the other hand, emphasizes the importance of taking into
consideration the researcher's personal experiences in the process of developing a
research question. Researchers who are also practitioners, for instance, can reflect
on problematic areas of their practice. Patterns and trends in practice may also
provide new insights and potential research question examples.

4. Evaluate the soundness of your research question.

Your initial research and review of related literature will have produced some
interesting questions that seem like they're worth pursuing. However, not all
interesting questions make for sound research questions. Keep in mind the research
question meaning -- that a research question draws its answer or conclusion through
an analysis of evidence. Here we present a set of criteria that can guide you on how
to formulate research questions.

Hulley et al. (2007) suggest using a set of criteria- known as the "FINER" criteria-to
find out if you have a good research question. The FINER criteria are outlined below:

F-Feasible
A good research question is feasible, which means that the question is well within
the researcher's ability to investigate. Researchers should be realistic about the
scale of their research as well as their ability to collect data and complete the
research with their skills and the resources available to them. It's also wise to have a
contingency plan in place in case problems arise.

I-Interesting
The ideal research question is interesting not only to the researcher but also to their
peers and community. This interest boosts the researcher's motivation to see the
question answered. For instance, you can do research on student housing trends if it
is right up your alley, as they do change often.

N-Novel
Your research question should be developed to bring new insights to the field of
study you are investigating. The question may confirm or extend previous findings on
the topic you are researching, for instance.

E-Ethical
This is one of the more important considerations of making a research question.
Your research question and your subsequent study must be something that review
boards and the appropriate authorities will approve.

R-Relevant
Aside from being interesting and novel, the research question should be relevant to
the scientific community and people involved in your area of study. If possible, your
research question should also be relevant to the public's interest.

5. Construct your research question properly.

Considering research question importance, research questions should be structured

properly to ensure clarity. Look for good research questions examples. There are a
number of frameworks that you can use for properly constructing a research
question. The two most commonly used frameworks are explained below.

PICOT framework

The PICOT research question framework was first introduced in 1995 by Richardson
et al. Using the PICOT framework, research questions can be constructed to
address important elements of the study, including the population to be studied, the
expected outcomes, and the time it takes to achieve the outcome. With these
elements, the framework is more commonly used in clinical research and evidence-
based studies.

• P - population, patients, or problem

• I - intervention or indicator being studied
• C - comparison group
• O - outcome of interest
• T - timeframe of the study

The sample research question below illustrates how to write research questions
based on the PICOT framework and its elements:

Between the ages of five and 18, are children of parents with diagnosed
mental health issues at increased risk of depression or anxiety compared with
children of parents with no diagnosed mental health issues?

P (population being studied) Children

I (indicator or intervention) parents with diagnosed mental health issues

children of parents with no diagnosed mental

C (comparison group)
health issues

O (outcome of interest) increased risk of depression or anxiety

T (timeframe of interest) between the ages of five and 18

PEO framework

Like the PICOT framework, the PEO framework is commonly used in clinical studies
as well. However, this framework is more useful for qualitative research questions.
This framework includes these elements:

• P - population being studied

• E - exposure to preexisting conditions
• O - outcome of interest

Below is an example of research question in the PEO framework:

Journal Article Reporting Standards (JARS)

Information recommended for inclusion in manuscripts that report new data

collections regardless of research design
Paper section
Description
and topic
Paper section
Description
and topic

Identify variables and theoretical issues under investigation

1. Title and title
and the relationship between them; Author note contains
page
acknowledgment of special circumstances.

Problem under investigation; Participants or subjects;

specifying pertinent characteristics; in animal research, include
2. Abstract genus and species Study method; Findings, including effect
sizes and confidence intervals and/or statistical significance
levels; Conclusions and the implications or applications

The importance of the problem; Review of relevant

3. Introduction scholarship; Specific hypotheses and objectives; How
hypotheses and research design relate to one another

4. Method

Eligibility and exclusion criteria; Major demographic

Participant
characteristics as well as important topic-specific
characteristics
characteristics.

Procedures for selecting participants; Settings and locations

Sampling where data were collected; Agreements and payments made to
procedures participants; Institutional review board agreements, ethical
standards met, safety monitoring

Sample size,
Intended sample size; Actual sample size; How sample size
power, and
was determined
precision

Definitions of all primary and secondary measures and

Measures and covariates; Methods used to collect data; Methods used to
covariates enhance the quality of measurements; Information on validated
or ad hoc instruments created for individual studies

Whether conditions were manipulated or naturally

Research design
observed; Type of research design.

5. Results

Total number of participants; Flow of participants through each

Participant flow
stage of the study

Dates defining the periods of recruitment and repeated

Recruitment
measurements or follow-up
Paper section
Description
and topic

Information concerning problems with statistical assumptions

and/or data distributions that could affect the validity of
Statistics and
findings; Missing data, etc. Statistical software program, if
data analysis
specialized procedures were used Report any other analyses
performed,

Ancillary Discussion of implications of ancillary analyses for statistical

analyses error rates.

Statement of support or nonsupport for all original

hypotheses; Similarities and differences between the results
6. Discussion and work of others Interpretation of the results; Generalizability
(external validity) of the findings; Discussion of implications for
future research, program, or policy.
What Is Qualitative Research? | Methods & Examples
Qualitative research involves collecting and analyzing non-numerical data (e.g., text,
video, or audio) to understand concepts, opinions, or experiences. It can be used to
gather in-depth insights into a problem or generate new ideas for research.

Qualitative research is the opposite of quantitative research, which involves

collecting and analyzing numerical data for statistical analysis.

Qualitative research is commonly used in the humanities and social sciences, in

subjects such as anthropology, sociology, education, health sciences, history, etc.

Qualitative research question examples

• How does social media shape body image in teenagers?

• How do children and adults interpret healthy eating in the UK?
• What factors influence employee retention in a large organization?
• How is anxiety experienced around the world?
• How can teachers integrate social issues into science curriculums?

Approaches to qualitative research

Qualitative research is used to understand how people experience the world. While
there are many approaches to qualitative research, they tend to be flexible and focus
on retaining rich meaning when interpreting data.

Common approaches include grounded theory, ethnography, action research,

phenomenological research, and narrative research. They share some similarities,
but emphasize different aims and perspectives.

Qualitative research approaches

Approach What does it involve?

Grounded theory Researchers collect rich data on a topic of interest and

develop theories inductively.

Ethnography Researchers immerse themselves in groups or

organizations to understand their cultures.

Action research Researchers and participants collaboratively link theory to

practice to drive social change.

Phenomenological Researchers investigate a phenomenon or event by

research describing and interpreting participants’ lived
experiences.

Narrative research Researchers examine how stories are told to understand

how participants perceive and make sense of their
experiences.

Note that qualitative research is at risk for certain research biases including the
Hawthorne effect, observer bias, recall bias, and social desirability bias. While not
always totally avoidable, awareness of potential biases as you collect and analyze
your data can prevent them from impacting your work too much.

Qualitative research methods

Each of the research approaches involve using one or more data collection methods.
These are some of the most common qualitative methods:

• Observations: recording what you have seen, heard, or encountered in

detailed field notes.
• Interviews: personally asking people questions in one-on-one conversations.
• Focus groups: asking questions and generating discussion among a group
of people.
• Surveys: distributing questionnaires with open-ended questions.
• Secondary research: collecting existing data in the form of texts, images,
audio or video recordings, etc.

Research exampleTo research the culture of a large tech company, you decide to
take an ethnographic approach. You work at the company for several months and
use various methods to gather data:

• You take field notes with observations and reflect on your own experiences of
the company culture.
• You distribute open-ended surveys to employees across all the company’s
offices by email to find out if the culture varies across locations.
• You conduct in-depth interviews with employees in your office to learn about
their experiences and perspectives in greater detail.
Qualitative researchers often consider themselves “instruments” in research because
all observations, interpretations and analyses are filtered through their own personal
lens.

For this reason, when writing up your methodology for qualitative research, it’s
important to reflect on your approach and to thoroughly explain the choices you
made in collecting and analyzing the data.

Qualitative data analysis

Qualitative data can take the form of texts, photos, videos and audio. For example,
you might be working with interview transcripts, survey responses, fieldnotes, or
recordings from natural settings.

Most types of qualitative data analysis share the same five steps:

1. Prepare and organize your data. This may mean transcribing interviews or
typing up fieldnotes.
2. Review and explore your data. Examine the data for patterns or repeated
ideas that emerge.
3. Develop a data coding system. Based on your initial ideas, establish a set
of codes that you can apply to categorize your data.
4. Assign codes to the data. For example, in qualitative survey analysis, this
may mean going through each participant’s responses and tagging them with
codes in a spreadsheet. As you go through your data, you can create new
codes to add to your system if necessary.
5. Identify recurring themes. Link codes together into cohesive, overarching
themes.

There are several specific approaches to analyzing qualitative data. Although these
methods share similar processes, they emphasize different concepts.

Qualitative data analysis

Approach When to use Example

Content To describe and categorize A market researcher could perform

analysis common words, phrases, and content analysis to find out what kind
ideas in qualitative data. of language is used in descriptions of
therapeutic apps.

Thematic To identify and interpret A psychologist could apply thematic

analysis patterns and themes in analysis to travel blogs to explore
qualitative data. how tourism shapes self-identity.

Textual To examine the content, A media researcher could use textual

analysis structure, and design of texts. analysis to understand how news
coverage of celebrities has changed
Qualitative data analysis

Approach When to use Example

in the past decade.

Discourse To study communication and A political scientist could use

analysis how language is used to discourse analysis to study how
achieve effects in specific politicians generate trust in election
contexts. campaigns.

Advantages of qualitative research

Qualitative research often tries to preserve the voice and perspective of participants
and can be adjusted as new research questions arise. Qualitative research is good
for:

• Flexibility

The data collection and analysis process can be adapted as new ideas or patterns
emerge. They are not rigidly decided beforehand.

• Natural settings

Data collection occurs in real-world contexts or in naturalistic ways.

• Meaningful insights

Detailed descriptions of people’s experiences, feelings and perceptions can be used

in designing, testing or improving systems or products.

• Generation of new ideas

Open-ended responses mean that researchers can uncover novel problems or

opportunities that they wouldn’t have thought of otherwise.

Disadvantages of qualitative research

Researchers must consider practical and theoretical limitations in analyzing and
interpreting their data. Qualitative research suffers from:

• Unreliability

The real-world setting often makes qualitative research unreliable because of

uncontrolled factors that affect the data.

• Subjectivity
Due to the researcher’s primary role in analyzing and interpreting data, qualitative
research cannot be replicated. The researcher decides what is important and what is
irrelevant in data analysis, so interpretations of the same data can vary greatly.

• Limited generalizability

Small samples are often used to gather detailed data about specific contexts.
Despite rigorous analysis procedures, it is difficult to draw generalizable conclusions
because the data may be biased and unrepresentative of the wider population.

• Labor-intensive

Although software can be used to manage and record large amounts of text, data
analysis often has to be checked or performed manually.
What Is an Observational Study?
An observational study is used to answer a research question based purely on
what the researcher observes. There is no interference or manipulation of the
research subjects, and no control and treatment groups.

These studies are often qualitative in nature and can be used for
both exploratory and explanatory research purposes.
While quantitative observational studies exist, they are less common.

Observational studies are generally used in hard science, medical, and social
science fields. This is often due to ethical or practical concerns that prevent the
researcher from conducting a traditional experiment. However, the lack of control
and treatment groups means that forming inferences is difficult, and there is a risk of
confounding variables and observer bias impacting your analysis.

Types of observation
There are many types of observation, and it can be challenging to tell the difference
between them. Here are some of the most common types to help you choose the
best one for your observational study.

Type Definition Example

Naturalistic The researcher observes how the Observing monkeys in a

observation participants respond to their environment zoo enclosure
in “real-life” settings but does not
influence their behavior in any way

Participant Also occurs in “real-life” settings, but Spending a few months in

observation here, the researcher immerses a hospital with patients
themselves in the participant group over suffering from a particular
a period of time illness

Systematic Utilizing coding and a strict observational Counting the number of

observation schedule, researchers observe times children laugh in a
participants in order to count how often a classroom
particular phenomenon occurs

Covert Hinges on the fact that the participants Observing interactions in

observation do not know they are being observed public spaces, like bus
rides or parks

Quantitative Involves counting or numerical data Observations related to

observation age, weight, or height

Qualitative Involves “five senses”: sight, sound, Observations related to

observation smell, taste, or hearing colors, sounds, or music

Case study Investigates a person or group of people Observing a child or group

over time, with the idea that close of children over the course
investigation can later be generalized to of their time in elementary
other people or groups school

Archival Utilizes primary sources from libraries, Analyzing US Census data

research archives, or other repositories to or telephone records
investigate a research question

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Types of observational studies

There are three main types of observational studies: cohort studies, case–control
studies, and cross-sectional studies.

Cohort studies
Cohort studies are more longitudinal in nature, as they follow a group of
participants over a period of time. Members of the cohort are selected because of a
shared characteristic, such as smoking, and they are often observed over a period of
years.

Case–control studies
Case–control studies bring together two groups, a case study group and a control
group. The case study group has a particular attribute while the control group does
not. The two groups are then compared, to see if the case group exhibits a particular
characteristic more than the control group.
For example, if you compared smokers (the case study group) with non-smokers
(the control group), you could observe whether the smokers had more instances of
lung disease than the non-smokers.

Note: In case–control studies, the case study group is chosen because they already
possess the attribute of interest—in this case, smoking.

Cross-sectional studies
Cross-sectional studies analyze a population of study at a specific point in time.

This often involves narrowing previously collected data to one point in time to test the
prevalence of a theory—for example, analyzing how many people were diagnosed
with lung disease in March of a given year. It can also be a one-time observation,
such as spending one day in the lung disease wing of a hospital.

Observational study example

Observational studies are usually quite straightforward to design and conduct.
Sometimes all you need is a notebook and pen! As you design your study, you can
follow these steps.

Step 1: Identify your research topic and objectives

The first step is to determine what you’re interested in observing and why.
Observational studies are a great fit if you are unable to do an experiment
for practical or ethical reasons, or if your research topic hinges on natural behaviors.

Example: Observational study topicYou’re interested in the interactions of toddlers at

day care, specifically how they deal with big emotions like excitement, fear, anger, or
sadness. Running an experiment could be challenging for ethical reasons: toddlers
are a vulnerable population and cannot consent to participate.

Step 2: Choose your observation type and technique

In terms of technique, there are a few things to consider:

• Are you determining what you want to observe beforehand, or going in open-
minded?
• Is there another research method that would make sense in tandem with an
observational study?
• Does it make a difference to your analysis if your participants know you are
there?
o If yes, make sure you conduct a covert observation.
o If not, think about whether observing from afar or actively participating
in your observation is a better fit.
• How can you preempt confounding variables that could impact your analysis?

Example: Observational study approachesThere are a few ways that you could
proceed with your research, depending on your research topic:
 • You could observe the children playing at the playground in a naturalistic
observation.
• You could spend a month at a day care in your town conducting participant
observation, immersing yourself in the day-to-day life of the children.
• You could conduct covert observation behind a wall or glass, where the
children can’t see you.

Overall, it is crucial to stay organized. Devise a shorthand for your notes, or perhaps
design templates that you can fill in. Since these observations occur in real time, you
won’t get a second chance with the same data.

Step 3: Set up your observational study

Before conducting your observations, there are a few things to attend to:

• Plan ahead: If you’re interested in day cares, you’ll need to call a few in your
area to plan a visit. They may not all allow observation, or consent from
parents may be needed, so give yourself enough time to set everything up.

• Determine your note-taking method: Observational studies often rely on

note-taking because other methods, like video or audio recording, run the risk
of changing participant behavior.

• Get informed consent from your participants (or their parents) if you
want to record: Ultimately, even though it may make your analysis easier,
the challenges posed by recording participants often make pen-and-paper a
better choice.

Step 4: Conduct your observation

After you’ve chosen a type of observation, decided on your technique, and chosen a
time and place, it’s time to conduct your observation.

Example: Observational studyYou’ve decided that there is a particular characteristic

about the toddlers that you are interested in. Let’s say you hypothesize that only
children are more likely to be upset when they are dropped off at day care than
children with siblings.
Here, you can split them into case and control groups. The children with siblings
have a characteristic you are interested in (siblings), while the children in the control
group do not.

You can then attend the morning drop-off at the carpool lane, observing whether the
children with siblings are, indeed, less upset when their caregivers drop them off.
When conducting observational studies, be very careful of confounding or “lurking”
variables. In the example above, you observed children as they were dropped off,
gauging whether or not they were upset. However, there are a variety of other
factors that could be at play here (e.g., illness).

Step 5: Analyze your data

After you finish your observation, immediately record your initial thoughts and
impressions, as well as follow-up questions or any issues you perceived during the
observation. If you audio- or video-recorded your observations, you
can transcribe them.

Your analysis can take an inductive or deductive approach:

• If you conducted your observations in a more open-ended way, an inductive

approach allows your data to determine your themes.
• If you had specific hypotheses prior to conducting your observations,
a deductive approach analyzes whether your data confirm those themes or
ideas you had previously.

Next, you can conduct your thematic or content analysis. Due to the open-ended
nature of observational studies, the best fit is likely thematic analysis.

Step 6: Discuss avenues for future research

Observational studies are generally exploratory in nature, and they often aren’t
strong enough to yield standalone conclusions due to their very high susceptibility
to observer bias and confounding variables. For this reason, observational studies
can only show association, not causation.

If you are excited about the preliminary conclusions you’ve drawn and wish to
proceed with your topic, you may need to change to a different research method,
such as an experiment.

Advantages and disadvantages of observational studies

Advantages

• Observational studies can provide information about difficult-to-analyze topics

in a low-cost, efficient manner.
• They allow you to study subjects that cannot be randomized safely, efficiently,
or ethically.
• They are often quite straightforward to conduct, since you just observe
participant behavior as it happens or utilize preexisting data.
• They’re often invaluable in informing later, larger-scale clinical trials or
experimental designs.

Disadvantages

• Observational studies struggle to stand on their own as a reliable research

method. There is a high risk of observer bias and undetected confounding
variables or omitted variables.
• They lack conclusive results, typically are not externally valid or generalizable,
and can usually only form a basis for further research.
• They cannot make statements about the safety or efficacy of the intervention
or treatment they study, only observe reactions to it. Therefore, they offer less
satisfying results than other methods.

Experiment and survey

 • Surveys and experiments are two commonly used methods in research and
data collection. While both approaches aim to gather information and insights,
they differ in their purpose, methodology, and the type of data they generate.
In this article, we will explore the differences between surveys and
experiments, their respective uses, advantages, limitations, and provide a
comprehensive comparison.

Point Survey Experiment

1 Involves collecting data by Involves manipulating variables
asking questions or gathering and measuring the effects of the
information from a sample or manipulation on outcomes
population
2 Focuses on gathering Focuses on testing causal
information about opinions, relationships between variables
attitudes, behaviors, or and determining cause-and-effect
characteristics of individuals relationships
or groups
3 Uses questionnaires, Involves manipulating independent
interviews, or online forms to variables and measuring
collect data from participants dependent variables to observe the
effects
4 Provides descriptive data, Provides causal data, allowing
allowing researchers to researchers to make conclusions
examine patterns, trends, or about the cause-and-effect
relationships among variables relationships between variables
5 Does not involve Involves manipulating variables,
manipulation of variables or often with the use of control
control groups groups, to establish cause-and-
effect relationships
6 Participants respond to Participants are exposed to
predefined questions or specific conditions or treatments,
prompts, providing subjective allowing for controlled comparisons
information
7 Provides a snapshot of a Allows for the examination of
specific population or sample changes or differences between
at a particular point in time groups under different
experimental conditions
8 Can be conducted using Requires careful design, random
various methods such as assignment, and control over
online surveys, phone extraneous variables to ensure
interviews, or in-person internal validity
questionnaires
9 Enables researchers to Enables researchers to establish
collect data on a wide range cause-and-effect relationships and
of topics from a large number test hypotheses through rigorous
of participants experimental design
10 Allows for the exploration of Allows for the identification of
relationships, correlations, or causal relationships between
 associations between variables by manipulating
variables independent variables
11 Data analysis involves Data analysis involves statistical
summarizing responses, tests, comparing experimental
calculating descriptive groups, and analyzing the effects
statistics, and identifying of the manipulated variables
patterns or trends
12 Provides insights into Provides insights into the causal
opinions, preferences, mechanisms and effects of
behaviors, or characteristics independent variables on
of a specific population or dependent variables
sample
13 Findings are based on self- Findings are based on controlled
reported information, which manipulation of variables, allowing
may be subject to bias or for greater control and precision in
inaccuracies data collection
14 Can be conducted in various Commonly used in scientific
settings, including academic research, medical studies, or
research, market research, or psychology experiments to
social science studies establish cause-and-effect
relationships
15 Surveys are more cost- Experiments are more resource-
effective, require less time, intensive, require careful planning,
and can gather data from a and may involve smaller sample
large number of participants sizes
16 Can be used for exploratory Can be used to test specific
research, hypothesis research hypotheses, theories, or
generation, or understanding predictions
population characteristics
17 Provides a broader Provides a narrower focus by
perspective by gathering data isolating specific variables and
from a large number of their effects through controlled
participants or a conditions
representative sample
18 Does not establish causality, Allows for the establishment of
but rather examines causal relationships between
associations or correlations variables through manipulation and
between variables control of independent variables
19 Can provide valuable insights Allows researchers to draw
into public opinion, customer conclusions about the causal
satisfaction, or market trends relationships between variables
and inform decision-making
20 Requires careful survey Requires rigorous experimental
design, sampling techniques, design, random assignment, and
and consideration of potential control over confounding variables
biases or limitations to ensure internal validity
21 Offers flexibility in data Requires adherence to ethical
collection methods, allowing considerations, such as obtaining
 for online surveys, phone informed consent and ensuring
interviews, or in-person participant safety
administration
22 Does not require Requires careful consideration of
manipulation of variables or ethical implications, including
ethical concerns related to potential risks and benefits for
exposing participants to participants
specific conditions
23 Can be conducted quickly, Requires careful planning,
providing rapid data collection implementation, and data
and immediate results for collection to ensure valid and
analysis reliable results
24 Can provide valuable insights Allows for controlled
into population experimentation, hypothesis
characteristics, preferences, testing, and the establishment of
or opinions for various causal relationships in scientific
applications research
25 Can be used to inform Allows researchers to draw strong
decision-making, evaluate conclusions about the cause-and-
programs, or gain a better effect relationships between
understanding of a target variables and contribute to
audience scientific knowledge

• Definition of Survey
• A survey is a research method used to collect data from a targeted group of
respondents using a set of predetermined questions. It aims to gather
information about opinions, attitudes, behaviors, preferences, or
characteristics of a specific population. Surveys can be conducted through
various means, including online questionnaires, telephone interviews, face-to-
face interviews, or paper-based surveys.
• Purpose and Methodology of Surveys
• The purpose of surveys is to obtain a snapshot of people's opinions, beliefs,
or experiences on a particular topic. Surveys often involve a large sample size
to ensure representation of the target population. Researchers design a
survey questionnaire with carefully crafted questions, which can be multiple-
choice, rating scales, open-ended, or a combination of different formats. The
data collected through surveys is primarily quantitative in nature, allowing for
statistical analysis and generalization.
• Advantages of Surveys
• Surveys offer several advantages. Firstly, they allow researchers to collect
data from a large number of respondents, providing a broader perspective on
a specific topic. Surveys are relatively cost-effective and can be administered
remotely, making them accessible to a wide range of participants. Moreover,
surveys provide standardized data, ensuring consistency and comparability
across different respondents. They also allow for the exploration of
correlations and relationships between variables through statistical analysis.
• Limitations of Surveys
• Despite their advantages, surveys have certain limitations. One limitation is
the potential for response bias, where respondents may provide socially
 desirable answers or be influenced by the way questions are phrased.
Surveys rely on self-reported data, which may not always accurately reflect
respondents' true behaviors or attitudes. Additionally, surveys are limited to
the information provided in the questionnaire and may not capture complex or
nuanced responses. Surveys also require careful sampling techniques to
ensure representative results.
• Definition of Experiment
• An experiment is a research method used to investigate cause-and-effect
relationships between variables through controlled manipulation and
observation. Experiments involve the deliberate introduction of specific
conditions or treatments to measure their impact on the dependent
variable(s). This method allows researchers to establish causal relationships
and understand the effects of certain variables on an outcome of interest.
• Purpose and Methodology of Experiments
• The purpose of experiments is to determine the cause-and-effect relationships
between variables by manipulating independent variables and measuring their
effects on dependent variables. Experiments typically involve two or more
groups: an experimental group exposed to the treatment or condition being
tested and a control group that remains unchanged. Researchers carefully
control the conditions of the experiment to isolate the effects of the
independent variable(s) and minimize other potential influences. Data
collected in experiments can be both quantitative and qualitative, depending
on the research design.
• Advantages of Experiments
• Experiments offer several advantages. Firstly, they provide a high level of
control over the variables being studied, allowing researchers to establish
causal relationships. Experiments also allow for the replication of results,
enhancing the reliability of findings. Moreover, experiments enable
researchers to study complex phenomena by manipulating variables and
studying their effects. They provide detailed insights into the underlying
mechanisms and processes involved in the research question.
• Limitations of Experiments
• While experiments have advantages, they also have limitations. One limitation
is that experiments may not always reflect real-world conditions or contexts,
limiting the generalizability of findings. Ethical considerations may restrict
certain types of experiments, particularly those involving human subjects.
Experiments can also be time-consuming and resource-intensive, requiring
careful planning and implementation. Additionally, some phenomena or
variables may be challenging to manipulate in an experimental setting,
making it difficult to study certain research questions using this method.
• Comparison between Surveys and Experiments
• In summary, surveys and experiments differ in their purpose and
methodology. Surveys are used to gather data on opinions, attitudes, and
behaviors through predetermined questions, primarily relying on self-reported
information. On the other hand, experiments focus on establishing cause-and-
effect relationships by manipulating variables and observing their effects.
Experiments provide a higher level of control but may be less applicable to
real-world scenarios. Surveys allow for larger sample sizes and provide
standardized data, but they are subject to response biases. Both methods
have their strengths and weaknesses, and the choice between them depends
 on the research objectives, available resources, and the nature of the
research question.
• Conclusion
• Surveys and experiments are valuable research methods that serve different
purposes in data collection and analysis. Surveys provide insights into
opinions and behaviors, while experiments establish causal relationships.
Understanding the differences between surveys and experiments helps
researchers choose the most appropriate method for their specific research
goals. By utilizing these methods effectively, researchers can generate
meaningful and reliable data to advance knowledge and make informed
decisions.