Ph.D. -Research methodology tools techniques, research publication and ethics (for ph.d scholars based 2020 syllabus)

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DR.TR. KALAI LAKSHMI/ SIST/ SREX5002 -RESEARCH METHODOLOGY TOOLS TECHNIQUES, RESEARCH PUBLICATION AND ETHICS
(FOR PH.D SCHOLARS BASED 2020 SYLLABUS)
SREX5002 -RESEARCH METHODOLOGY TOOLS TECHNIQUES, RESEARCH
PUBLICATION AND ETHICS (FOR PH.D SCHOLARS BASED 2020 SYLLABUS)
UNIT1 -INTRODUCTION TO RESEARCH METHODOLOGY
Research Methodology- Definition and significance- Types of research - Exploratory research,
Conclusive research, Modeling research, Algorithmic research, Casual research, Theoretical and
Empirical research, Cross-Sectional research and Time Series research, Research process-, Research
problem- Objectives, Characteristics, Hypothesis and research in evolutionary perspective. Research
Design- Definition, Types- Descriptive research design and Experimental research design-
Questionnaire preparation- prerequisites of a good questionnaire, Data Collection methods in research
-Primary data and Secondary data.
DEFINITION OF RESEARCH:
• ―Research as a ―systematized effort to gain new knowledge.‖ Redman and Mory
• Research comprises defining and redefining problems, formulating hypothesis or suggested
solutions, collecting, organizing and evaluating data; making deductions and reaching
conclusions; and at last carefully testing the conclusions to determine whether they fit the
formulating hypothesis. -CliffordWoody
Features of research
• Research is a systematic process of collecting and analyzing information in order to
increase our understanding of the topic.
• Research is the search of knowledge. Research is an investigation.

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• Research methodology is a way to systematically solve the research problem.
• It is a science of studying how research is donescientifically.
• Research can be defined as the search for knowledge through objective and systematic
method of finding solution to a problem. The systematic approach concerning
generalization and the formulation of a theory is also research.
Significance of Research
1. The role of research in several fields of applied economics, whether related to business
or to the economyas a whole, has greatly increased in modern times.
2. Researchprovides thebasis for nearlyall government policies in our economicsystem.
3. Research has its special significance in solving various operational and planning
problems of business and industry
4. Research is equally important for social scientists in studying social relationships and in
seeking answers to various social problems.
5. Research is equally important for social scientists in studying social relationships and in
seeking answers to various social problems.
OBJECTIVES OF RESEARCH
• The purpose of research is to discover answers to questions through the application of scientific
procedures.
• The main aim of research is to find out the truth which is hidden and which has not been
discovered as yet.
• To gain familiarity with a phenomenon or to achieve new insights into it (studies with this object
in view are termed as exploratory or formulative research studies);
• To portray accurately the characteristics of a particular individual, situation or a group (studies with
this object in view are known as descriptive research studies);
• To determine the frequency with which something occurs or with which it is associated with
something else (studies with this object in view are known as diagnostic researchstudies)
• To test a hypothesis of a causal relationship between variables (such studies are known as
hypothesis-testing research studies).
• To find solutions to the given problems

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CHARACTERISTICS OF RESEARCH
The main characteristics for good quality research are listed below:
• It is based on the work of others.
• It can be replicated and doable.
• It is generalizable to other settings.
• It is based on some logical rationale and tied to theory. In a way that it has the potential to
suggest directions for future research.
• It generates new questions or is cyclical in nature.
• It is incremental.
• It addresses directly or indirectly some real problem in the world.
• It clearly states the variables or constructs to be examined.
• Valid and verifiable such that whatever you conclude on the basis of your findings is correct and
can be verified by you and others.
• The researcher is sincerely interested and/or invested in this research.
TYPES OF RESEARCH
The basic types of research are as follows:
i) Descriptive Analytical:
Descriptive research includes surveys and fact-finding enquiries of different kinds. The major
purpose of descriptive research is description of the state of affairs as it exists at present. The main
characteristics if this method us that the researcher has no control over the variables, the
researcher can report only report what has happened or what is happening.
E.g. Fluctuation of Indian share market for a period,2. Blood pressure of a patient for a period post
operation
Analytical research: The researcher has to use the facts and informational already available and
analyze these to make a critical evaluation on the information acquired. Analytical research
attempts to explain why and how. It usually concerns itself with cause-effect relationship among
variables.
Egg: Why Indian share market fluctuated? Why patients BP was not stable post operation / Why
market of gold went high during recession.

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ii) Applied vs. Fundamental:
Applied research aims at finding a solution for an immediate problem facing a society or an
industrial business organization Research aimed at certain conclusions (say, a solution) facing
concrete social or business problem is applied research. It aims to find solution to a given problem
e.g. Market research, heath pollution safety etc.
,Fundamental research is mainly concerned with generalizations and with the formulation of a
theory. ―Gathering knowledge for knowledge‘s sake is termed ‗pure‘ or ‗basic‘ research.‖ E.g.
Research concerning some natural phenomenon or relating to pure mathematics are examples of
fundamental research. Research studies, concerning human behaviour carried on with a view to
makee generalizations about human behavior.

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Qualitative Research
Quantitative research is ―explaining phenomena by collecting numerical data that are analyzed using
mathematically based methods Qualitative Research is primarily exploratory research. It is used to
gain an understanding of underlying reasons, opinions, and motivations. It provides insights into
the problem or helps to develop ideas or hypotheses for potential quantitative research.
Qualitative Research is also used to uncover trends in thought and opinions, and dive deeper into
the problem. Qualitative data collection methods vary using unstructured or semi-structured
techniques. Some common methods include focus groups (group discussions), individual
interviews, and participation/observations. The sample size is typically small, and respondents are
selected to fulfil a given quota.
Quantitative Research
Quantitative Research is used to quantify the problem by way of generating numerical data or data
that can be transformed into usable statistics. It is used to quantify attitudes, opinions, behaviors,
and other defined variables – and generalize results from a larger sample population. Quantitative
Research uses measurable data to formulate facts and uncover patterns in research. Quantitative
data collection methods are much more structured than Qualitative data collection methods.
Quantitative data collection methods include various forms of surveys – online surveys, paper
surveys, mobile surveys and kiosk surveys, face-to- face interviews, telephone interviews,
longitudinal studies, website interceptors, online polls, and systematic observations.

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(iii) Conceptual vs. Empirical:
(iv) Conceptual research is that related to some abstract idea(s) or theory. It is generally used by
philosophers and thinkers to develop new concepts or to reinterpret existing ones. The
Researcher breaks down a theorem or concept into its constituents‘ parts to gain better and deeper
understanding of the issue concerning the theorem. E.g. philosophers and scientist use this
method to explore the existing knowledge
(v) Empirical research relies on experience or observation alone, often without due regard for
system and theory. It is data-based research, coming up with conclusions which are capable of
being verified by observation or experiment The researcher provide himself with a working
hypothesis to the probable results Facts are found to prove or disprove the hypothesis after which
experimental designs are made to bring forth the desired information.
E.g. for setting hypothesis for a social research
A simple hypothesis is a hypothesis that reflects a relationship between two variables –
independent and dependent variable. Examples: Higher the unemployment, higher would be the
rate of crime in society. Lower the use of fertilizers, lower would be agricultural productivity.
RESEARCH APPROACHES
There are two basic approaches to research,

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1. Quantitative Approach
2. Qualitative Approach
Quantitative Approach:
It involves the generation of data in quantitative form which can be subjected to rigorous quantitative analysis in
a formal and rigid fashion.
It can be further sub-classified
a. Inferential approach
b. Experimental approach
c. Simulation approach.
Inferential approach
The purpose of inferential approach to research is to form a data base from which to infer characteristics
or relationships of population. This usually means survey research where a sample of population is
studied (questioned or observed) to determine its characteristics, and it is then inferred that the population
has the same characteristics.
Experimental approach
Experimental approach is characterized by much greater control over the research environment and in this
case some variables are manipulated to observe their effect on other variables.
Simulation approach
Simulation approach involves the construction of an artificial environment within which relevant
information and data can be generated. This permits an observation of the dynamic behaviour of a system
(or its sub-system) under controlled conditions. E.g. Simulation approach can also be useful in building
models for understanding future conditions.
Qualitative Approach:
Qualitative approach to research is concerned with subjective assessment of attitudes, opinions and
behaviour. Research in such a situation is a function of researcher‘s insights and impressions. Such
an approach to research generates results either in non-quantitative form or in the form which are not
subjected to rigorous quantitative analysis. Generally, the techniques of focus group interviews,
projective techniques and depth interviews areused.
TYPES OF RESEARCH

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On the basis of application
1. Pure research (also called as fundamental or basis research) Pure research mainly concerned with
generalizations and with the formulation of a theory. Gathering knowledge for knowledge‘s sake is
termed as ‗pure‘ or ‗basic‘ research. Research concerning some natural phenomenon or relating to
pure mathematics are examples of pure research. The pure research is directed towards finding
information that has a broad base of applications and thus, adds to the already existing organized
body of scientific knowledge.
2. Applied Research :Applied research aims at finding a solution for an immediate problem facing a
society or an industrial / business organisation. The research that aimed at certain conclusions (ex.
solution) facing a concrete social or business problem is an example of applied research. The
research to identify social, economic or political trends that may affect a particular institution or
the copy research (research to find out whether certain communications will be read and
understood) or the marketing research or evaluation research are examplesof applied research.
Thus, the central aim of applied research is to discover a solution for some pressing practical
problem.
I. On the basis of Objectives
• Exploratory research
It is a type of research conducted for a problem that has not been clearly defined. The
exploratory research helps determine the best research design, data collection method and
selection of subjects. The results of exploratory research are not usually useful for decision-
making by themselves, but they can provide significant insight into a given situation. The
exploratory research is not typically generalizable to the population at large. The exploratory
research can be quite informal, relying on secondary research such as reviewing available
literature and/or data like informal discussions with consumers, employees, management, case
studies or pilot studiesetc.
• Conclusive research
Conclusive research is meant to provide information that is useful in reaching conclusions or
decision- making. It tends to be quantitative in nature, that is to say in the form of numbers
that can be quantified and summarized. It relies on both secondary data, particularly existing
databases that are reanalyzed to shed light on a different problem and primarydata.
• Descriptive research
Descriptive research includes surveys and fact-finding enquiries of different kinds. The major

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purpose of descriptive research is description of the state of affairs as it exists at present. In
social science and business research, it is quite often, the term Ex post facto research is used
for descriptive research studies. The main characteristic of this method is that the researcher
has no control over the variables; she/he can only report what has happened or what is
happening. The methods of research utilized in descriptive research and survey methods of all
kinds, including comparative and correlation methods.
• Causal / Experimental research
Experimental research is an objective, systematic, controlled investigation for the purpose of
predicting and controlling phenomena and examining probability and causality among
selected variables. Experimental research helps in best establishing the cause-and-effect
relationships the simplest experimental design includes two variables (Dependent and
Independent variable) and two groups of participants (Control and Experimental group). The
independent variable is the predictor variable whereas the dependent variable is the outcome
variable. Researchers manipulate and control the independent variable to study its effect on
the dependent variable. Before the beginning of experiment, the researcher (randomly) assigns
her/his sample to two different groups; the control group and the experimental (treatment
group or clinical group). The control group receives no manipulation of the independent
variable (no treatment), whereas the experimental group receives the manipulation of the
independent variable.
II. On the basis of extent of theory
1.Theoretical research
Theoretical research generally uses the findings from existing works to develop new ideas
through analyzing existing theory and explanations. These new ideas are not tested through
collecting evidence in the form of primary data.
2.Empirical research
Empirical research relies on experience and observation alone, often without due regard for
system and theory. It is a data-based research, coming up with conclusions which are capable
of being verified by observation or experiment. In empirical research, the researcher must first
provide himself with a working hypothesis or guess as to the probable results. He then works to
get enough facts (data) to prove or disprove his hypothesis.
III. On the basis of time dimension

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1. Cross sectionalresearch
Cross-sectional research is used to examine one variable in different groups that are similar
in all other characteristics. It means, the Cross-sectional research involves using different
groups of people who differ in the variable of interest but share other characteristics, such as
socioeconomic status, educational background, and ethnicity.
Cross-sectional research studies are based on observations that take place in different groups
at one time. This means there is no experimental procedure, so no variables are manipulated
by the researcher. Instead of performing an experiment, the researcher would simply record
the information that she/he observe in the groups they are examining. The following are the
characteristics of cross-sectional research
• Takes place at a single point intime
• Variables are not manipulated by theresearcher
• Provide information only; do not answerwhy
2. Longitudinal research
Longitudinal research is used to study individuals at different stages in their lives. A
longitudinal study is correlational research which follows one group of individuals over a
long period of time, perhaps decades. Frequently, researchers meet with the subjects many
times on a regular basis. The length of time is dependent on the topic of the research, the
length of the study, and the age of the subjects
a) Time series:
An ordered sequence of values of a variable at equally spaced time intervals. The usage
of time series models is twofold: Obtain an understanding of the underlying forces and
structure that produced the observed data. Fit a model and proceed to forecasting,
monitoring or even feedback and feedforward control. Time Series Analysis is used for
many applications such as:
• Economic Forecasting
• Sales Forecasting
• Budgetary Analysis
• Stock Market Analysis

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• Yield Projections
• Process and QualityControl
• Inventory Studies
• Workload Projections
• Utility Studies
• Census Analysis
b) Panel study
A panel usually involves a somewhat random sample of subjects. Panel studies are a
particular design of longitudinal study in which the unit of analysis is followed at specified
intervals over a long period, often many years. The key feature of panel studies is that they
collect repeated measures from the same sample at different points in time. Most panel
studies are designed for quantitative analysis and use structured survey data. Panel data
analysis is a statistical method, widely used in social science, epidemiology, and
econometrics, which deals with two and "n"-dimensional (in and by the - cross
sectional/times series time) panel data. The data are usually collected over time and over the
same individuals and then a regression is run over these two dimensions.
c) Cohort study
Cohort study observes subjects in a similar group based on region, age, or common
experiences. A cohort is a group of people who share a common characteristic or experience
within a defined period. Prospective cohort studies re-investigate groups of people who share
some social characteristic. Cohort study takes its name from two intellectual traditions.
Cohort studies are observational in design and are generally concerned with information
regarding the prevalence distribution and inter- relationship of variables in a population. They
are also used to identify risk factors and to collect information to describe the natural history
or progression of disease. Cohort studies provide a wealth of valuable information about
population health- which informs the planning and implementation of health policy. Cohort
designs are thus ideal for many of the health-related areas that interest nursing and
midwifery researcher. An algorithm is a well-defined sequence of steps to solve a problem of
interest in industry, business and government.
d) Algorithmic Research Report:

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This type of research provides well defined sequence of steps to solve organizational
problems; it may be government business or any industry. These problems can be
polynomial or combinatorial. Combinatorial problems are those problems which take the
exponential form of volume and time complexity. In polynomial category researchers
develop the proper algorithm for optimal solution. Otherwise the researchers shoulddevelop
efficient heuristic for the problem. There are problems, viz., production scheduling. JIT,
supply chain management, line balancing, layout design, portfolio management, etc., exist in
reality. The solution for each of the above problems can be obtained through algorithms. So,
the researchers some out with newer algorithms or improved algorithms for such problems.
e) Modelling Research
Models are developed and used to help scientists, engineers, decision makers to understand
and communicate about a system of interest with the ultimate aim of bringing a positive
change to how a system is built and/or managed. Models are simplified representation of the
modelled system. To be useful, models need to provide a cognitively-mediated environment
to explain the systemic behaviour.
TYPES OF MODELS:
a) Symbolic model
Symbolic model is representation of the performance measure of the system of interest in
terms of its variables. This means that the attributes of a system are related by an equation.
Regression equation is an example of a symbolic model
b) Mathematical model
Mathematical model are mainly operations research models which are aimed to solve
complex real-life problems arising in the direction and management of large systems of men,
machines, materials and money in the industry, business and government. Some examples of
mathematical models are linear programming models, transportation models, assignment
models, inventory models, replacement models, goal programming models, parametric
programming models, quadratic programming models, change constrained programming
models, separable programming modelsetc.
c) Simulation model:
Simulation models is an experiment conducted over a real-life stochastic system in a scaled
time frame to extract as many average operational statistics as possible to formicate

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1
• FORMULATING THE RESEARCH
PROBLEM
2
• EXTENSIVE LITERATURE SURVEY
3
• FRAMING HYPOTHESIS
4
• DATA COLLECTION
5
• HYPOTHESIS-TESTING
6
• GENERALIZATIONS AND
INTERPRETATION:
7
• PREPARATION OF THE REPORT OR
THESIS
respective decision guidelines at all the levels of management, industry, business or
government. the simulation model can be either continuous or discrete.
STEPS IN RESEARCH PROCESS

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FORMULATING THE 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 said to be the one which requires a
researcher to find the best available solution to the given problem. That is, the researcher needs to
find out the best course of action through which the research objective may be achieved optimally in
the context of a given situation There are two types of research problems, viz., those which relate to
states of nature and those which relate to relationships between variables. At the very outset the
researcher must single out the problem he wants to study, i.e., he must decide the general area of
interest or aspect of a subject-matter that he would like to inquire into. Initially the problem may be
stated in a broad general way and then the ambiguities, if any, relating to the problem be resolved.
Then, the feasibility of a particular solution has to be considered before a working formulation of the
problem can be set up.
The formulation of a general topic into a specific research problem, thus, constitutes the first step
in a scientific enquiry. Essentially two steps are involved in formulating the research problem
Understanding the problem thoroughly,
Rephrasing the same into meaningful terms from an analytical point of view.
Understanding the problem
The best way of understanding the problem is to discuss it with one‘s own colleagues or with
those having some expertise in thematter.
o In an academic institution the researcher can seek the help from a guide who is usually an
experienced man and has several research problems in mind. Often, the guide puts forth the
problem in general terms and it is up to the researcher to narrow down and phrase the problem
in operational terms.
o In private business units or in governmental organizations, the problem is usually earmarked
by the administrative agencies with whom the researcher can discuss as to how the problem
originally came about and what considerations are involved in its possible

solutions.
o The researcher must at the same time examine all available literature to get himself acquainted
with the selected problem. The basic outcome of reviewing literature will be to enhance
knowledge as to what data and other materials are available for operational purposes which
will enable the researcher to specify his own research problem in a meaningful context
EXTENSIVE LITERATURE SURVEY
Once the problem is formulated, a brief summary of it should be written down. At this juncture the
researcher should undertake extensive literature survey connected with the problem. For this
purpose, the abstracting and indexing journals and published or unpublished bibliographies are the
first place to go to. Academic journals, conference proceedings, government reports, books etc., must
be tapped depending on the nature of the problem. In this process, it should be remembered that one
source will lead to another. The earlier studies, if any, which are similar to the study in hand should
be carefully studied. A good library will be a great help to the researcher at this stage.
Review of literature are of two different types
• Conceptual literature concerning the concepts andtheories,
• Empirical literature consisting of studies made earlier which are similar to theone
proposed.
• Rephrasing the problem
FRAMING HYPOTHESIS
―Hypothesis may be defined as a proposition or a set of propositions set forth as an explanation
for the occurrence of some specified group of phenomena either asserted merely as a provisional
conjecture to guide some investigation in the light of established facts‖ (Kothari, 1988).
A research hypothesis is quite often a predictive statement, which is capable of being tested using
scientific methods that involve an independent and some dependent variables.
For instance, the following statements may be considered:
―Students who take tuitions perform better than the others who do not receive tuitions‖
―The female students perform as well as the male students‖.
These two statements are hypotheses that can be objectively verified and tested. Thus, they

indicate that a hypothesis states what one is looking for. Besides, it is a proposition that can be
put to test in order to examine its validity.
HYPOTHESIS IS NOT A QUESTION, BUT RATHER IT IS A STATEMENT ABOUT THE
RELATIONSHIPBETWEEN TWO OR MORE VARIABLES.
In research, a hypothesis is characterized by three essential elements: variables, population and the correlation
between the variables.
• Tobe complete a hypothesis must include three components:
• The variables : A sample is representative of that population
• The population: A population is what we call the entire group of individuals or elements who meet the
sampling criteria
• The relationship between the variables
Example: If we were interested in looking at the number of childhood cancers in 2006 in the United Kingdom (i.e.
population), we obviously could not survey the entire population of children with cancer in that year who live in the
United Kingdom, and so consequently we would look at a smaller sample taken from all the children with cancer in
2006 who live in the United Kingdom.
• Theindividual units of a populationarewhat wecall the elements.
• Now an element can be anything that we are studying, for example it could be a person, an event, their
behaviour, or indeed anyother singleunit of a study.
• However, when elements are actually human beings, then rather than calling them elements, we call
themsubjects.
Characteristics of Hypothesis:
1. A hypothesis must be precise and clear. If it is not precise and clear, then the inferences
drawn on its basis would not bereliable.
2. A hypothesis must be capable of being put to test. Quite often, the research programmes fail
owing to its incapability of being subject to testing for validity. Therefore, some prior study
may be conducted by the researcher in order to make a hypothesis testable. A hypothesis ―is
tested if other deductions can be made from it, which in turn can be confirmed or disproved by
observation‖ (Kothari, 1988).
3. A hypothesis must state relationship between two variables, in the case of relational
hypotheses.
4. A hypothesis must be specific and limited in scope. This is because a simpler hypothesis

generally would be easier to test for the researcher. And therefore, he/she must formulate
such hypotheses.
5. As far as possible, a hypothesis must be stated in the simplest language, so as to make it
understood by all concerned. However, it should be noted that simplicity of a hypothesis
is not related to its significance.
6. A hypothesis must be consistent and derived from the most known facts. In other words, it
should be consistent with a substantial body of established facts. That is, it must be in the
form of a statement which is most likely tooccur.
7. A hypothesis must be amenable to testing within a stipulated or reasonable period of time.
No matter how excellent a hypothesis, a researcher should not use it if it cannot be tested
within a given period of time, as no one can afford to spend a life-time on collecting data
to test it.
Testing of hypothesis:
1. As a part of investigation, samples are drawn from the population and results are derived
to help in taking the decisions. But such decisions involve an element of uncertainty
causing wrong decisions.
2. Hypothesis is an assumption which may or may not be true about a population parameter.
For example, if we toss a coin 200 times, we may get 110 heads and 90 tails.
3. At this instance, we are interested in testing whether the coin is unbiased or not
.Therefore, we may conduct a test to judge the significance of the difference of sampling
or otherwise. To carry out a test of significance, the following procedure has to be
followed:
Framing the Hypothesis:
To verify the assumption, which is based on sample study, we collect data and find out the
difference between the sample value and the population value. If there is no difference found or
the difference is very small then the hypothetical value is correct. Generally two hypotheses
complementaryto each offer are constructed, and if one is found correct, the other is rejected.
• Null Hypothesis: The random selection of the samples from the given population makes the
tests of significance valid for us. For applying any test of significance we first set up a
hypothesis- a definite statement about the population parameter/s. Such a statistical hypothesis,
which is under test, is usually a hypothesis of no difference and hence is called null hypothesis.

It is usually denoted by Ho. In the words of Prof. R.A.Fisher ―Null Hypothesis is the hypothesis
which is tested for possible rejection under the assumption that it is true.‖
• Alternative Hypothesis: Any hypothesis which is complementary to the null hypothesis is called
an alternative hypothesis. It is usually denoted by H1. It is very important to explicitly state the
alternative hypothesis in respect of any null hypothesis H0 because the acceptance or rejection of
Ho is meaningful only if it is being tested against an opposite hypothesis.
.Working hypothesis
Working hypothesis is tentative assumption made in order to draw out and test its logical or empirical
consequences A working hypotheses arise as a result of a-priori thinking about the subject, examination
of the available data and material including related studies and the counsel of experts and interested
parties. As such the manner in which research hypotheses are developed is particularly important since
they provide the focal point for research. They also affect the manner in which tests must be conducted in
the analysis of data and indirectly the quality of data which is required for the analysis. In most types of
research, the development of working hypothesis plays an important role. The role of the hypothesis is to
guide the researcher by delimiting the area of research and to keep him on the right track. It sharpens the
researchers thinking and focuses attention on the more important facets of the problem. It also indicates
the type of data required and the type of methods of data analysis to be used. Hypothesis should be very
specific and limited to the piece of research in hand because it has to betested.
Developing working hypotheses
• Discussions with colleagues and experts about the problem, its origin and the
objectives in seeking a solution;
• Examination of data and records, if available, concerning the problem for
possible trends, peculiarities and other clues;
• Review of similar studies in the area or of the studies on similar problems; and
• Exploratory personal investigation which involves original field interviews on a
limited scale with interested parties and individuals with a view to secure greater
insight into the practical aspects of the problem.
Types of errors in testing of hypothesis:
The inductive inference consists in arriving at a decision to accept or reject a null hypothesis (Ho)
after inspecting only a sample from it. As such an element of risk – the risk of taking wrong decision

is involved. In any test procedure, the four possible mutually disjoint and exhaustive decisions are:
• Reject Ho when actually it is not true i.e., when Ho isfalse.
• Accept Ho when it is true.
• Reject Ho when it is true.
• Accept Ho when it is false.
The decisions in (i) and (ii) are correct decisions while the decisions in (iii) and (iv) are wrong decisions.
These decisions may be expressed in the following dichotomous table:
Thus, in testing of hypothesis we are likely to commit two types of errors.
The error of rejecting Ho when Ho is true is known as Type I Error and the error of accepting Ho
when Ho is false is known as Type II Error.
For example, in the Industrial Quality Control, while inspecting the quality of a manufactured lot, the
Inspector commits Type I Error when he rejects a good lot and he commits Type II Error when he
accepts a bad lot
TYPES OF HYPOTHESIS
1. Simple Hypothesis
It shows a relationship between one dependent variable and a single independent variable. For
example – If you eat more vegetables, you will lose weight faster. Here, eating more
vegetables is an independent variable, while losing weight is the dependent variable.
2. Complex Hypothesis
It shows the relationship between two or more dependent variables and two or more

independent variables. Eating more vegetables and fruits leads to weight loss, glowing skin,
reduces the risk of many diseases such as heart disease, high blood pressure, and some
cancers.
3. Directional Hypothesis
It shows how a researcher is intellectual and committed to a particular outcome. The
relationship between the variables can also predict its nature. For example- children aged four
years eating proper food over a five year period are having higher IQ level than children not
having a proper meal. This shows the effect and the direction of effect.
4. Non-directional Hypothesis
It is used when there is no theory involved. It is a statement that a relationship exists between
two variables, without predicting the exact nature (direction) of the relationship.
5. Null Hypothesis It provides the statement which is contrary to hypothesis. It‘s a negative
statement, and there is no relationship between independent and dependent variable. The
symbol is denoted by ―HO‖.
6. Associative and Causal Hypothesis
Associative hypothesis occurs, When there is a change in one variable resulting a change in
the other variable. Whereas, Causal hypothesis propose a cause and effect interaction
between two or more variables.
Examples of Hypothesis
Following are the examples of hypothesis based on their types:
• Consumption of sugary drinks everyday leads to obesity is an example of simple
hypothesis.
• All lilies have same number of petals is an example of null hypothesis.
• If a person gets 7 hours of sleep, then he will feel less fatigue than if he sleeps less.
Functions of Hypothesis
Following are the functions performed by the hypothesis:
• Hypothesis helps in making an observation and experiments possible.
• It becomes the start point for the investigation.
• Hypothesis helps in verifying the observations.
• It helps in directing the inquiries in the right directions.

PREPARING THE RESEARCH DESIGN
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. Infact, research
design is the conceptual structure within which research is conducted; it constitutes the blueprint for
the
collection, measurement and analysis of data (Selltiz et al, 1962). Thus, research design provides an
outline of what the researcher is going to do in terms of framing the hypothesis, its operational
implications and the final data analysis. Specifically, the research design highlights decisions which
include: The research problem having been formulated in clear cut terms, the researcher will be
required to prepare a research design, i.e., he will have to state the conceptual structure within which
research would be conducted. The preparation of such a design facilitates research to be as efficient as
possible yielding maximal information. In other words, the function of research design is to provide
for the collection of relevant evidence with minimal expenditure of effort, time and money. But how
all these can be achieved depends mainly on the research purpose.
A research design suitable for a specific research problem would usually involve the
following considerations:
The methods of gathering the information;
The skills and availability of the researcher and his/her staff, if
any; The objectives of the research problem being studied
The nature of the research problem being studied; and
The available monetary support and duration of time for the research work.
DATA COLLECTION
The researcher should select one of these methods of collecting the data taking into consideration the
nature of investigation, objective and scope of the inquiry, financial resources, available time and the
desired degree of accuracy. Though he should pay attention to all these factors but much depends upon the
ability and experience of the researcher.
There are two methods of data collection Primary data and secondary data collection methods.
Primary data is data that is collected by a researcher from first-hand sources, using methods like surveys,
interviews, or experiments. It is collected with the research project in mind, directly from primary sources.
Secondary data is data gathered from studies, surveys, or experiments that have been run by other people
or for another research.In dealing with any problem it is often found that data at hand are in adequate, and

hence, it becomes necessary to collect data that are appropriate. There are several ways of collecting the
appropriate data which differ considerably in context of money costs, time and other resources at the
disposal of the researcher.
Methods of Primary data collection
Primary data can be collected either through experiment or through survey. If the researcher which he
examines the truth contained in his hypothesis. But in the case of a survey, data can be collected by any
one or more of the following ways:
1. By observation: This method implies the collection of information by way of
investigator‘s own observation, without interviewing the respondents. The information
obtained relates to what is currently happening and is not complicated by either the past
behaviour or future intentions or attitudes of respondents. This method is no doubt an
expensive method and the information provided by this method is also very limited. As
such this method is no suitable in inquiries where large samples are concerned.
2. Through personal interview: The investigator follows a rigid procedure and seeks
answers to a set of pre-conceived questions through personal interviews. This method of
collecting data is usually carried out in a structured way where output depends upon the
ability of the interviewer to a large extent.
3. Through telephone interviews: This method of collecting information involves contacting
the respondents on telephone itself. This is not a very widely used method but it plays an
important role in industrial surveys in developed regions, particularly, when the survey has to
be accomplished in a very limited time.
4. By mailing of questionnaires: The researcher and the respondents do come in contact with
each other if this method of survey is adopted. Questionnaires are mailed to the
respondents with a request to return after completing the same. It is the most extensively used
method in various economic and business surveys. Before applying this method, usually a
Pilot Study for testing the questionnaire is conduced which reveals the weaknesses, if any,
of the questionnaire. Questionnaire to be used must be prepared very carefully so that it
mayprove to be effective in collecting the relevant information.
5. Through schedules: Under this method the enumerators are appointed and given
training. They are provided with schedules containing relevant questions. These
enumerators go to respondents with these schedules. Data are collected by filling up the
schedules by enumerators on the basis of replies given by respondents. Much depends upon

the capability of enumerators so far as this method is concerned. Some occasional field
checks on the work of the enumerators may ensure sincere work.
Secondary Data
A researcher may have collected the data for a particular project, then made it available to be
used by another researcher. The data may also have been collected for general use with no
specific research purpose like in the case of the national census.
A data classified as secondary for a particular research may be said to be primary for another
research. This is the case when a data is being reused, making it a primary data for the first
research and secondary data for the second research it is being used for.
Sources of Secondary Data
Sources of secondary data includes books, personal sources, journal, newspaper, website, government
record etc. Secondary data are known to be readily available compared to that of primary data. It requires
very little research and need for manpower to use these sources. With the advent of electronic media and
the internet, secondary data sources have become more easily accessible. Some of these sources are
highlighted below.
1. Books: Books are one of the most traditional ways of collecting data. Today, there are
books available for all topics you can think of. When carrying out research, all you have
to do is look for a book on the topic being researched on, then select from the available
repository of books in that area. Books, when carefully chosen are an authentic source
of authentic data and can be useful in preparing a literaturereview.
2. Published Sources: There are a variety of published sources available for different
research topics. The authenticity of the data generated from these sources depends
majorly on the writer and publishing company. Published sources may be printed or
electronic as the case may be. They may be paid or free depending on the writer and
publishing company's decision.
3. Unpublished Personal Sources: This may not be readily available and easily
accessible compared to the published sources. They only become accessible if the
researcher shares with another researcher who is not allowed to share it with a third
party.
4. For example, the product management team of an organization may need data on
customer feedback to assess what customers think about their product and improvement
suggestions. They will need to collect the data from the customer service department,

which primarily collected the data to improve customer service.
5. Journal: Journals are gradually becoming more important than books these days when
data collection is concerned. This is because journals are updated regularly with new
publications on a periodic basis, therefore giving to date information.
6. Also, journals are usually more specific when it comes to research. For example, we can
have a journal on, "Secondary data collection for quantitative data" while a book will
simply be titled, "Secondary data collection".
7. Newspapers: In most cases, the information passed through a newspaper is usually very
reliable. Hence, making it one of the most authentic sources of collecting secondary
data.
The kind of data commonly shared in newspapers is usually more political, economic, and
educational than scientific. Therefore, newspapers may not be the best source for scientific data
collection.
1. Websites: Theinformation shared on websites are mostly not regulated and as such may
not be trusted compared to other sources. However, there are some regulated websites
that only share authentic data and can be trusted by researchers.
2. Most of these websites are usually government websites or private organizations that are
paid, data collectors.
3. Blogs: Blogs are one of the most common online sources for data and may even be less
authentic than websites. These days, practically everyone owns a blog and a lot of
people use these blogs to drive traffic to their website or make money through paid ads.
Therefore, they cannot always be trusted. For example, a blogger may write good things
about a product because he or she was paid to do so by the manufacturer even though
these things are not true.
4. Diaries: They are personal records and as such rarely used for data collection by
researchers. Also, diaries are usually personal, except for these days when people now
share public diaries containing specific events in their life. A common example of this is
Anne Frank's diary which contained an accurate record of the Nazi wars.
5. Government Records: Government records are a very important and authentic source
of secondary data. They contain information useful in marketing, management,
humanities, and social science research.
6. Some of these records include; census data, health records, education institute records,

etc. They are usually collected to aid proper planning, allocation of funds, and
prioritizing of projects.
7. Podcasts: Podcasts are gradually becoming very common these days, and a lot of
people listen to them as an alternative to radio. They are more or less like online radio
stations and are generating increasing popularity. Information is usually shared during
podcasts, and listeners can use it as a source of data collection.
8. Library: This is a traditional secondary data collection tool for researchers. The library
contains relevant materials for virtually all the research areas you can think of, and it is
accessible to everyone. A researcher might decide to sit in the library for some time to
collect secondary data or borrow the materials for some time and return when done
collecting the required data.
9. Radio: Radio stations are one of the secondary sources of data collection, and one
needs a radio to access it. The advent of technology has even made it possible to listen
to radio on mobile phones, deeming it unnecessary to get a radio
10. Some other sources of data collection include:
• Letters
• Radio stations
• Public sector records.
Modern tools for secondary data collection
Popular tools used to collect secondary data include; bots, devices, libraries. In order to
ease the data collection process from the sources of secondary data highlighted above,
researchers use these important tools which are explained below.
1. Bots: There are lots of data online and it may be difficult for researchers to browse through
all these data and find what they are actually looking for. In order to ease this process of
data collection, programmers have created bots to do an automatic web scraping for
relevant data. These bots are "software robots" programmed to perform some task for the
researcher. It is common for businesses to use bots to pull data from forums and social
media for sentiment and competitive analysis.
1. Internet-Enabled Devices: This could be a mobile phone, PC, or tablet that has access
to an internet connection. They are used to access journals, books, blogs, etc. to collect

secondary data.
Execution of the project:
Execution of the project is a very important step in the research process. If the execution of the
project proceeds on correct lines, the data to be collected would be adequate and dependable.
The researcher should see that the project is executed in a systematic manner and in time. If the
survey is to be conducted by means of structured questionnaires, data can be readily machine-
processed. In such a situation, questions as well as the possible answers may be coded. If the data
are to be collected through interviewers, arrangements should be made for proper selection and
training of the interviewers. The training may be given with the help of instruction manuals
which explain clearly the job of the interviewers at each step.
Occasional field checks should be made to ensure that the interviewers are doing their assigned
job sincerely and efficiently. A careful watch should be kept for unanticipated factors in order to
keep the survey as much realistic as possible. This, in other words, means that steps should be
taken to ensure that the survey is under statistical control so that the collected information is in
accordance with the pre-defined standard of accuracy. If some of the respondents do not
cooperate, some suitable methods should be designed to tackle this problem. One method of
dealing with the non-response problem is to make a list of the non- respondents and take a small
sub-sample of them, and then with the help of expert‘s vigorous efforts can be made for securing
response.
DATA ANALYSIS
After the project execution the researcher acquired the data. The next step is the researcher turns
to the task of analyzing the data collected. The analysis of data requires a number of closely
related operations such as establishment of categories, the application of these categories to raw
data through coding, tabulation and then drawing statistical inferences.
• Coding operation is usually done at this stage through which the categories of data are
transformed into symbols that may be tabulated and counted. Editing is the procedure
that improves the quality of the data forcoding.
• Tabulation is a part of the technical procedure wherein the classified data are put in the
form of tables
• The mechanical devices can be made use of at this juncture. A great deal of data,
especially in large inquiries, is tabulated by computers. Computers not only save time but

also make it possible to study large number of variables affecting a problem
simultaneously.
• Analysis work after tabulation is generally based on the computation of various
percentages, coefficients, etc., by applying various well-defined statistical formulae. In
the process of analysis, relationships or differences supporting or conflicting with
original or new hypotheses should be subjected to tests of significance to determine
with what validity data can be said to indicate anyconclusion(s).
HYPOTHESIS-TESTING:
After analyzing the data as stated above, the researcher is in a position to test the hypotheses, if
any, he had formulated earlier. Do the facts support the hypotheses or they happen to be
contrary? This is the usual question which should be answered while testing hypotheses.
Various tests, such as Chi square test, t-test, F-test, have been developed by statisticians for the
purpose. The hypotheses may be tested through the use of one or more of such tests, depending
upon the nature and object of research inquiry.
Hypothesis-testing will result in either accepting the hypothesis or in rejecting it. If the
researcher had no hypotheses to start with, generalizations established on the basis of data may
be stated as hypotheses to be tested by subsequent researches in times to come.
GENERALIZATIONS AND INTERPRETATION:
`If a hypothesis is tested and upheld several times, it may be possible for the researcher to arrive
at generalization, i.e., to build a theory. As a matter of fact, the real value of research lies in its
ability to arrive at certain generalizations. If the researcher had no hypothesis to start with, he
might seek to explain his findings on the basis of some theory. It is known as interpretation. The
process of interpretation may quite often trigger off new questions which in turn may lead to
further researches.
PREPARATION OF THE REPORT OR THE THESIS
Finally, the researcher has to prepare the report of what has been done by him. Writing of report
must be done with great care keeping in view the following:
The layout of the report should be as follows:
• the preliminary pages;

• he main text,
• the end matters
In its preliminary pages the report should carry title and date followed by acknowledgements and
foreword. Then there should be a table of contents followed by a list of tables and list of graphs
and charts, if any, given in the report.
The main text of the report should have the following parts:
• Introduction: It should contain a clear statement of the objective of the research and an
explanation of the methodology adopted in accomplishing the research. The scope of the
study along with various limitations should as well be stated in this part.
• Summary of findings: After introduction there would appear a statement of findings and
recommendations in non-technical language. If the findings are extensive, they should be
summarized.
• Main report: The main body of the report should be presented in logical sequence and
broken-down into readily identifiablesections.
• Conclusion: Towards the end of the main text, researcher should again put down the
results of his research clearly and precisely. In fact, it is the final summing up. At the end
of the report, appendices should be enlisted in respect of all technical data. Bibliography,
i.e., list of books, journals, reports, etc., consulted, should also be given in the end.
Index should also be given specially in a published research report.
SAMPLING
A sample design is a definite plan determined before any data are actually collected for obtaining a sample
from a given population in practice, several of the methods of sampling described above may well be used
in the same study in which case it can be called mixed sampling. It may be pointed out here that normally
one should resort to random sampling so that bias can be eliminated and sampling error can be estimated.
But purposive sampling is considered desirable when the universe happens to be small and a known
characteristic of it is to be studied intensively. Also, there are conditions under which sample designs other
than random sampling may be considered better for reasons like convenience and low costs. The sample
design to be used must be decided by the researcher taking into consideration the nature of the inquiry and
other relatedfactors

Probability samples: With probability samples each element has a known probability of being included
in the sample. Probability samples are those based on simple random sampling, systematic sampling,
stratified sampling, cluster/area samples.
Non-probability samples: Non-probability samples do not allow the researcher to determine this
probability. Non-probability samples are those based on convenience sampling, judgement sampling and
quota sampling techniques.
A brief mention of the important sample designs is as follows:
Deliberate sampling: Deliberate sampling is also known as purposive or non-probability sampling.
This sampling method involves purposive or deliberate selection of particular units of the universe
for constituting a sample which represents the universe. When population elements are selected for
inclusion in the sample based on the ease of access, it can be also called convenience sampling.
Judgment sampling: Judgment sampling is used quite frequently in qualitative research where them
desire happens to be to develop hypotheses rather than to generalize to larger populations. The
researcher‘s judgment is used for selecting items which he considers as representative of the
population. For example, a judgment sample of college students might be taken to secure reactions
to a new method of teaching.
Simple random sampling: This type of sampling is also known as chance sampling or p
robability sampling where each and every item in the population has an equal chance of inclusion
in the sample and each one of the possible samples, in case of finite universe, has the same
probability of being selected. For example, if we have to select a sample of 300 items from a
universe of 15,000 items, then we can put the names or numbers of all the 15,000 items on slips of
paper and conduct a lottery. Using the random number tables is another method of random
sampling. To select the sample, each item is assigned a number from 1 to 15,000. Then, 300 five-
digit random numbers are selected from the table. To do this we select some random starting point
and then a systematic pattern is used in proceeding through the table. We might start in the 4th
row, second column and proceed down the column to the bottom of the table and then move to
the top of the next column to the right. When a number exceeds the limit of the numbers in the
frame, in our case over 15,000, it is simply passed over and the next number selected that does fall
within the relevant range. Since the numbers were placed in the table in a completely random
fashion, the resulting sample is random. This procedure gives each item an equal probability of
being selected. In case of infinite population, the selection of each item in a random sample is
controlled by the same probability and that successive selections are independent of oneanother.

Systematic sampling: In some instances, the most practical way of sampling is to select every
15th name on a list, every 10th house on one side of a street and so on. Sampling of this type is
known as systematic sampling. An element of randomness is usually introduced into this kind of
sampling by using random numbers to pick up the unit with which to start. This procedure is
useful when sampling frame is available in the form of a list. In such a design the selection
process starts by picking some random point in the list and then every nth element is selected
until the desired number is secured.
Stratified sampling: If the population from which a sample is to be drawn does not constitute a
homogeneous group, then stratified sampling technique is applied so as to obtain a representative
sample. In this technique, the population is stratified into a number of no overlapping
subpopulations or strata and sample items are selected from each stratum. If the items selected
from each stratum is based on simple random sampling the entire procedure, first stratification
and then simple random sampling, is known as stratified randomsampling.
Quota sampling: In stratified sampling the cost of taking random samples from individual strata is
often so expensive that interviewers are simply given quota to be filled from different strata, the actual
selection of items for sample being left to the interviewer‘s judgement. This is called quota sampling.
The size of the quota for each stratum is generally proportionate to the size of that stratum in the
population. Quota sampling is thus an important form of non-probability sampling. Quota samples
generally happen to be judgement samples rather than random samples.
Cluster sampling and area sampling: Cluster sampling involves grouping the population and
then selecting the groups or the clusters rather than individual elements for inclusion in the
sample. Suppose some departmental store wishes to sample its credit card holders. It has issued its
cards to 15,000 customers. The sample size is to be kept say 450. For cluster sampling this list of
15,000 card holders could be formed into 100 clusters of 150 card holders each. Three clusters
might then be selected for the sample randomly. The sample size must often be larger than the
simple random sample to ensure the same level of accuracy because is cluster sampling procedural
potential for order bias and other sources of error is usually accentuated. The clustering approach
can, however, make the sampling procedure relatively easier and increase the efficiency of field
work, especially in the case of personal interviews. Area sampling is quite close to cluster
sampling and is often talked about when the total geographical area of interest happens to be big
one. Under area sampling we first divide the total area into a number of smaller non-
overlapping areas, generally called geographical
clusters, then a number of these smaller areas are randomly selected, and all units in these small

areas are included in the sample. Area sampling is especially helpful where we do not have the
list of the population concerned. It also makes the field interviewing more efficient since
interviewer can do many interviews at each location.
Multi-stage sampling: This is a further development of the idea of cluster sampling. This
technique is meant for big inquiries extending to a considerably large geographical area like an
entire country. Under multi-stage sampling the first stage may be to select large primary
sampling units such as states, then districts, then towns and finally certain families within towns.
If the technique of random-sampling is applied at all stages, the sampling procedure is described
as multi-stage random sampling.
Sequential sampling: This is somewhat a complex sample design where the ultimate size of the
sample is not fixed in advance but is determined according to mathematical decisions on the basis
of information yielded as survey progresses. This design is usually adopted under acceptance
sampling plan in the context of statistical qualitycontrol
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. Infect, research design is the conceptual structure
within which research is conducted; it constitutes the blueprint for the collection, measurement
and analysis of data (Selltiz et al, 1962). Thus, research design provides an outline of what the
researcher is going to do in terms of framing the hypothesis, its operational implications and the
final data analysis. In view of the stated research design decisions, the overall research design
may be divided into the following (Kothari1988):
• The sampling design that deals with the method of selecting items to be observed for the
selected study;
• The observational design that relates to the conditions under which the observations are to be
made;
• The statistical design that concerns with the question of how many items are to be
observed, and how the information and data gathered are to be analyzed; and The
operational design that deals with the techniques by which the procedures specified in the
sampling, statistical and observational designs can be carried out.
Research design highlights decisions which includes:

• The nature of thestudy
• The purpose of thestudy
• The location where the study would be conducted
• The nature of datarequired
• From wherethe required data can be collected
• What time period the studywould cover
• The type of sample design that would be used
• The techniques of data collection that would be used
• The methods of data analysis that would be adopted and
• The manner in which the report would be prepared
The preparation of the research design, appropriate for a particular research problem, involves
usually the consideration of the following:
• The means of obtaining theinformation;
• The availabilityand skills of the researcher and his staff (if any);
• Explanation of the wayin which selected means of obtaining information will
be organized and the reasoning leading to theselection;
• The time available for research; and
• The cost factor relatingto research
• the finance available for the purpose
Characteristics of A Good Research Design:
A good research design often possesses the qualities of being flexible, suitable, efficient,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.
Importance of Research Design:
• 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 moneyare given.
• A 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
• Research purposes may be grouped into four categories,viz.,
Types of Research Design
1. Exploratory research design
2. Description and Diagnostic research design
3. Experimental research design
Exploratory ResearchDesign:
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, such a research
design suitable for such a study should be flexible enough to provide opportunity for
considering different dimensions of the problem under study. The in-built flexibility in research
design is required as the initial research problem would be transformed into a more precise one in
the exploratory study, which in turn may necessitate changes in the research procedure for
collecting relevant data. Usually, the following three methods are considered in the context of a

research design for such studies. They are (a) a survey of related literature; (b) experience
survey; and (c) analysis of ‗insight-stimulating‘instances.
Descriptive and Diagnostic ResearchDesign:
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.
Specifically, the research design highlights decisions which include:
1. The nature of thestudy
2. The purpose of thestudy
3. The location where the study would beconducted
4. The nature of data required
5. From where the required data can becollected
6. What time period the study wouldcover
7. The type of sample design that would beused
8. The techniques of data collection that would beused
9. The methods of data analysis that would be adoptedand
10. The manner in which the report would beprepared
The preparation of the research design, appropriate for a particular research problem, involves
usually the consideration of the following:
1. The means of obtaining theinformation;
2. The availabilityand skills of the researcher and his staff (if any);
3. Explanation of the way in which selected means of obtaining information will be organized and

the reasoning leading to theselection;
4. The time available for research;and
5. The cost factor relating to research, i.e., the finance available for the purpose.
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 thestudy,
b) Proper designing of the methods of datacollection,
c) Sample selection,
d) Data collection,
e) Processing and analysis of the collected data,and
f) Reporting the findings.
3. Experimental or Hypothesis-Testing Research Design:
A blueprint of the procedure that enables the researcher to test his hypothesis by reaching valid
conclusions about relationships between independent and dependent variables. It refers to the
conceptual framework within which the experiment is conducted. 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.
Determining sample design:
A sample design is a definite plan determined before any data are actually collected for
obtaining a sample from a given population All the items under consideration in any field of
inquiry constitute a ‗universe‘ or ‗population‘. A complete enumeration of all the items in the
‗population‘ is known as a census inquiry. Census inquiry is not possible in practice under
many circumstances. For instance, blood testing is done only on sample basis. Hence only a few
items from the universe for our study purposes. The items so selected constitute what is
technically called a sample. The researcher must decide the way of selecting a sample or what is
popularly known as the sample design. Thus, the plan to select 12 of a city‘s 200 drugstores in a

certain way constitutes a sample design.
Experimental or Hypothesis-Testing Research Design:
A blueprint of the procedure that enables the researcher to test his hypothesis by reaching valid
conclusions about relationships between independent and dependent variables. It refers to the
conceptual framework within which the experiment is conducted. 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 ofexperiments.
PREPARATION OF A QUESTIONNAIRE
Questionnaire is widely used for data collection in social research. It is a reasonably fair tool for
gathering data from large, diverse, varied and scattered social groups. The questionnaire is the media
of communication between the investigator and the respondents. According to Bogardus, a
questionnaire is a list of questions sent to a number of persons for their answers and which obtains
standardized results that can be tabulated and treated statistically. The Dictionary of Statistical Terms
defines it as a ―group of or sequence of questions designed to elicit information upon a subject or
sequence of subjects from information.‖ A questionnaire should be designed or drafted with utmost
care and caution so that all the relevant and essential information for the enquiry may be collected
without any difficulty, ambiguity and vagueness. Drafting of a good questionnaire is a highly
specialized job and requires great care skill, wisdom, efficiency and experience. No hard and fast rule
can be laid down for designingor framing a questionnaire.
Prerequisites/ Characteristics of a good questionnaire:
1. Size of The QuestionnaireShould Be Small:
A researcher should try his best to keep the number of questions as small as possible, keeping in
view the nature, objectives and scope of the enquiry. Respondent‘s time should not be wasted by
asking irrelevant and unimportant questions. A large number of questions would involve more work
for the investigator and thus result in delay on his part in collecting and submitting the information.

A large number of unnecessary questions may annoy the respondent and he may refuse to
cooperate. A reasonable questionnaire should contain from 15 to 25 questions at larger If a still
larger number of questions are a must in any enquiry, then the questionnaire should be divided into
various sections or parts.
2. Questions Should BeClear:
The questions should be easy, brief, unambiguous, non-offending, courteous in tone, corroborative in
nature and to the point, so that much scope of guessing is left on the part of the respondents.
3. Questions should be arranged in a logical sequence:
Logical arrangement of questions reduces lot of unnecessary work on the part of the researcher
because it not only facilitates the tabulation work but also does not leave any chance for omissions or
commissions. For example, to find if a person owns a television, the logical order of questions would
be: Do you own a television? When did you buy it? What is it make? How much did it cost you? Is
its performance satisfactory? Have you ever got it serviced? 63
4. Questions should be simple tounderstand:
The vague words like good, bad, efficient, sufficient, prosperity, rarely, frequently, reasonable, poor,
rich etc., should not be used since these may be interpreted differently by different persons and as
such might give unreliable and misleading information. Similarly, the use of words having double
meaning like price, assets, capital income etc., should also be avoided.
5. Questions should be comprehensive& easily answerable:
Questions should be designed in such a way that they are readily comprehensible and easy to answer
for the respondents. They should not be tedious nor should they tax the respondents‘ memory. At the
same time questions involving mathematical calculations like percentages, ratios etc., should not be
asked.
6. Questions of personal & sensitive nature should not be asked:
There are some questions which disturb the respondents and he/she may be shy or irritated by hearing
such questions. Therefore, every effort should be made to avoid such questions. For example, ‗do you
cook yourself or your wife cooks?‘ ‗Or do you drink?‘ Such questions will certainly irk the respondents
and thus be avoided at any cost. If unavoidable then highest amount of politeness should be used.
Types of Questions:

Under this head, the questions in the questionnaire may be classified as follows:
Shut Questions: Shut questions are those where possible answers are suggested by the framers of the
questionnaire and the respondent is required to tick one of them. Shut questions can further be
subdividedinto the following forms:
• Simple Alternate Questions: In this type of questions the respondent has to choose from the
two clear cut alternatives like ‗Yes‘ or ‗No‘, ‗Right or Wrong‘ etc. Such questions are also
called as dichotomous questions. This technique can be applied with elegance to situations
where two clear cut alternatives exist:
• Multiple Choice Questions: Many at times it becomes difficult to define a clear-cut
alternative and accordingly in such a situation additional answers between Yes and No, like
Do not know, no opinion, Occasionally, Casually, seldom etc., are added. For example, in order
to find if a person smokes or drinks, the following multiple-choice answers may be used:
Do you smoke?
(a) Yes regularly [] (b) No never []
(c) Occasionally [] (d) Seldom []
Multiple choice questions are very easy and convenient for the respondents to answer. Such
questions save time and also facilitate tabulation. This method should be used if only a selected
few alternative answer exists to a particular question.
Leading Questions Should Be Avoided:
Questions like ‗why do you use a particular type of car, say Maruti car‘ should preferably be framed
into two questions-
(i) which car do you use?
(ii) why do you prefer it?
1. It gives smooth ride []
2. It gives more mileage []
3. It is cheaper []
4.. It is maintenance free []
Cross Checks:

The questionnaire should be so designed as to provide internal checks on the accuracy of the
information supplied by the respondents by including some connected questions at least with
respect to matters which are fundamental to the enquirer Testing theQuestionnaire:
It would be practical in every sense to try out the questionnaire on a small scale before using it for
the given enquiry on a large scale. This has been found extremely useful in practice. The given
questionnaire can be improved or modified in the light of the drawbacks, shortcomings and
problems faced by the investigator in the pretest.
Covering Letter:
A covering letter from the organizers of the enquiry should be enclosed along with the
questionnaire for the purposes regarding definitions, units, concepts used in the questionnaire,
for taking the respondent‘s confidence, self-addressed envelope in case of mailed questionnaire,
mention about award or incentives for the quick response, a promise to send a copy of the survey
report etc.
A good questionnaire should not be too lengthy. Simple English should be used and the question
shouldn‘t be difficult to answer. A good questionnaire requires sensible language, editing,
assessment, and redrafting.
QUESTIONNAIRE DESIGN PROCESS
1. State the information required- This will depend upon the nature of the problem, the purpose
of the studyand hypothesis framed. The target audience must be concentrated on.
2. State the kind of interviewing technique- interviewing method can be telephone, mails,
personal interview or electronic interview. Telephonic interview can be computer assisted.
Personal interview can be conducted at respondent‘s place or at mall or shopping place. Mail
interview can take the form of mail panel. Electronic interview takes place either through
electronic mails or through theinternet.
3. Decide the matter/content of individual questions-There are two deciding factors for this-
a. Is the question significant? - Observe contribution of each question.
b. Does the question contribute for the objective of the study?
c. Is there a need for several questions or a single
question? Several questions are asked in the following
cases:
• When there is a need forcross-checking
• When the answers areambiguous

4. When people are hesitant to give correct information. Overcome the respondents’ inability
and unwillingness to answer- Therespondents may be unableto answer the questions because
of followingreasons-
• The respondent may not be fullyinformed
• The respondent maynot remember
• He may be unable to express or articulate
• There may be sensitive information which may cause embarrassment or harm the
respondent‘s image.
• The respondent may not be familiar with the genuine purpose
• The question may appear to be irrelevant to the respondent
• The respondent will not be willing to reveal traits like aggressiveness (For instance - if he is
asked ―Do you hit your wife, sister‖, etc.)
• To overcome the respondent‘s unwillingness to answer:
5. Place the sensitive topics at the end of the questionnaire
• Preface the question with a statement
• Use the third person technique (For example - Mark needed a job badly and he used wrong
means to get it - Is it right?? Different people will have different opinions dependingupon the
situation)
• Categorize the responses rather than asking a specific response figure (For example- Group for
income levels 0-25000, 25000-50000, 50000 and above)
Decide on the structure of the question- Questions can be of two types:
1. Structured questions- These specify the set of response alternatives and the response
format.
2. These can be classified into multiple choice questions (having various response categories),
3. dichotomous questions (having only 2 response categories such as ―Yes‖ or ―No‖) and
scales
4. Unstructured questions- These are also known as open-ended question. No alternatives are
suggested and the respondents are free to answer these questions in any way theylike.
5. Determine the question language/phrasing- If the questions are poorly worded, then either
the respondents will refuse to answer the question or they may give incorrect answers. Thus,
the words of the question should be carefully chosen. Ordinary and unambiguous words

should be used. Avoid implicit assumptions, generalizations and implicit alternatives. Avoid
biased questions. Define the issue in terms of who the questionnaire is being addressed to,
what information is required, when is the information required, why the question is being
asked, etc.
6. Properly arrange the questions- To determine the order of the question, take decisions on
aspects like opening questions (simple, interesting questions should be used as opening
questions to gain co-operation and confidence of respondents), type of information (Basic
information relates to the research issue, classification information relates to social and
demographic characteristics, and identification information relates to personal information
such as name, address, contact number of respondents), difficult questions (complex,
embarrassing, dull and sensitive questions could be difficult), effect on subsequent
questions, logical sequence, etc.
7. Recognize the form and layout of the questionnaire- This is very essential for self-
administered questionnaire. The questions should be numbered and pre-coded. The layout
should be such that it appears to be neat and orderly, and not clattered.Reproduce the
questionnaire- Paper quality should be good. Questionnaire should appear to be
professional. The required space for the answers to the question should be sufficient. The
font type and size should be appropriate. Vertical response questions should be used, for
example: Do you use brand X of shampoo? 1. Yes ,2. No
8. Pre-test the questionnaire- The questionnaire should be pre-tested on a small number of
respondents to identify the likely problems and to eliminate them. Each and every dimension
of the questionnaire should be pre-tested. The sample respondents should be similar to the
target respondents of thesurvey.
9. Finalize the questionnaire- Check the final draft questionnaire. Ask yourself how much
will the information obtained from each question contribute to the study. Make sure that
irrelevant questions are not asked. Obtain feedback of the respondents on the questionnaire.
DATA COLLECTION
There are two types of data, primary and secondary
Data which are collected first hand are called Primary data

Sources of Primary data: Direct Personal Interviews, Indirect Oral Interviews, Information from
Correspondents, mailed questionnaire method, Schedules sent through enumerators and so on.
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 fromCorrespondents.
4. Mailed Questionnaire Methods.
5. Schedule Sent ThroughEnumerators.
Data which have already been collected and used by somebody are called Secondary data.
• Published sources: Published sources are like publications of different government and semi-
government departments, research institutions and agencies etc.
• Unpublished sources. Whereas unpublished sources are like records maintained by different
government departments and unpublished theses of different universities etc.
There are two approaches of collecting primary data:
• Survey method or total enumeration method: When a researcher goes for investigating all the
units of the subject, it is called as survey method.
• Sample method: If a researcher resorts to investigating only a few units of the
subject and gives the result on the basis of that, it is known as sample survey method.
Direct Personal Interviews:
A face to face contact is made with the informants (persons from whom the information is to be obtained)
under this method of collecting data. The interviewer asks them questions pertaining to the survey and
collects the desired information. Thus, if a person wants to collect data about the working conditions of
the workers of the Tata Iron and Steel Company, Jamshedpur, he would go to the factory, contact the
workers and obtain the desired information. The information collected in this manner is first hand and also
original in character. There are many merits and demerits of this method, which are discussed as under:
Merits:

• Most often respondents are happy to pass on the information required from them when contacted
personally and thus response isencouraging.
• 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-
examinehimand therebytry 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 uselater.
• 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 can 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
mayinvolve huge expenses.

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 neighbours
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
• 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 becomeuseless.
• The ability of the interviewers to draw information from witnesses by means of appropriate
questions and cross-examination.
• 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.
Information fromCorrespondents:
The investigator appoints local agents or correspondents in different places to collect information under
this method. These correspondents collect and transmit the information to the central office where data are
processed. This method is generally adopted by 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
Mailed QuestionnaireMethod
: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. He 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: The degree to which the questionnaire is formalized or
structured.
The disguise or lack of disguise of the questionnaireand
The communication methodused.
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
studyis 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 structuredand
4. Disguised non-structured.

Ph.D. -Research methodology tools techniques, research publication and ethics (for ph.d scholars based 2020 syllabus)

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