Research Methodology by Dr. Jatinder Kumar.pdf

Dr. Jatinder Kumar
Associate Professor,
Lovely Professional University,
Phagwara, Punjab.

2
What is research?
• Research.
• 1. A systematic investigation into and study
of materials, sources, etc, in order to
establish facts and reach new conclusions.
• 2. An endeavour to discover new or collate
old facts etc by the scientific study of a
subject or by a course of critical
investigation. [Oxford Concise Dictionary]

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.
• Common quantitative methods include experiments,
observations recorded as numbers, and surveys with closed-
ended questions.

Qualitative research
• 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..
• Common qualitative methods include interviews with open-
ended questions, observations described in words, and
literature reviews that explore concepts and theories.

Scientific research
• Research is "creative and systematic work undertaken to increase
the stock of knowledge". It involves the collection, organization,
and analysis of information to increase understanding of a topic or
issue. A research project may be an expansion on past work in the
field.
• Scientific research is a systematic way of gathering data and
harnessing curiosity. This research provides scientific information
and theories for the explanation of the nature and the properties of
the world. It makes practical applications possible. Scientific
research is funded by public authorities, by charitable organizations
and by private groups, including many companies. Scientific
research can be subdivided into different classifications according
to their academic and application disciplines. Scientific research is a
widely used criterion for judging the standing of an academic
institution, but some argue that such is an inaccurate assessment of
the institution, because the quality of research does not tell about
the quality of teaching

Historical research
• Historical method is the collection of techniques and guidelines
that historians use to research and write histories of the past. Secondary
sources, primary sources and material evidence such as that derived
from archaeology may all be drawn on, and the historian's skill lies in
identifying these sources, evaluating their relative authority, and
combining their testimony appropriately in order to construct an accurate
and reliable picture of past events and environments.
• In the philosophy of history, the question of the nature, and the possibility,
of a sound historical method is raised within the sub-field of epistemology.
The study of historical method and of different ways of writing history is
known as historiography.
• Source criticism (or information evaluation) is the process of evaluating
the qualities of an information source, such as its validity, reliability, and
relevance to the subject under investigation.
• Gilbert J. Garraghan and Jean Delanglez divide source criticism into six
inquiries:[1]
– When was the source, written or unwritten, produced (date)?
– Where was it produced (localization)?
– By whom was it produced (authorship)?
– From what pre-existing material was it produced (analysis)?
– In what original form was it produced (integrity)?
– What is the evidential value of its contents (credibility)?

Descriptive research
• Descriptive research is used to describe characteristics of a population or
phenomenon being studied. It does not answer questions about how/when/why
the characteristics occurred. Rather it addresses the "what" question (what are the
characteristics of the population or situation being studied?).[1] The characteristics
used to describe the situation or population are usually some kind of categorical
scheme also known as descriptive categories. For example, the periodic
table categorizes the elements. Scientists use knowledge about the nature of
electrons, protons and neutrons to devise this categorical scheme. We now take for
granted the periodic table, yet it took descriptive research to devise it. Descriptive
research generally precedes explanatory research. For example, over time the
periodic table's description of the elements allowed scientists to explain chemical
reaction and make sound prediction when elements were combined.
• Hence, descriptive research cannot describe what caused a situation. Thus,
descriptive research cannot be used as the basis of a causal relationship, where
one variable affects another. In other words, descriptive research can be said to
have a low requirement for internal validity.
• The description is used for frequencies, averages and other statistical calculations.
Often the best approach, prior to writing descriptive research, is to conduct a
survey investigation. Qualitative research often has the aim of description and
researchers may follow-up with examinations of why the observations exist and
what the implications of the findings are.

Survey research
• In research of human subjects, a survey is a list of questions aimed at extracting
specific data from a particular group of people. Surveys may be conducted by
phone, mail, via the internet, and sometimes face-to-face on busy street corners or
in malls. Surveys are used to increase knowledge in fields such as social
research and demography.
• Survey research is often used to assess thoughts, opinions, and feelings.[1] Surveys
can be specific and limited, or they can have more global, widespread
goals. Psychologists and sociologists often use surveys to analyze behavior, while it
is also used to meet the more pragmatic needs of the media, such as, in evaluating
political candidates, public health officials, professional organizations,
and advertising and marketing directors. Survey research has also been employed
in various medical and surgical fields to gather information about healthcare
personnel’s practice patterns and professional attitudes toward various clinical
problems and diseases. Healthcare professionals that may be enrolled in survey
studies in include physicians,[2][3] nurses,[4] and physical therapists[5] among others.
A survey consists of a predetermined set of questions that is given to a
sample.[1] With a representative sample, that is, one that is representative of the
larger population of interest, one can describe the attitudes of the population from
which the sample was drawn. Further, one can compare the attitudes of different
populations as well as look for changes in attitudes over time. A good sample
selection is key as it allows one to generalize the findings from the sample to the
population, which is the whole purpose of survey research.

Case study research
• In the social and life sciences, a case study is a research method involving an up-
close, in-depth, and detailed examination of a particular case. For example, a case
study in medicine may examine a specific patient a doctor treated, and a case
study in business might study a particular firm's strategy. Generally, a case can be
nearly any unit of analysis, including individuals, organizations, events, or actions.
• Case studies can be produced by following a formal research method. These case
studies are likely to appear in formal research venues, as journals and professional
conferences, rather than in popular works. Case study research can mean single
and multiple case studies, can include quantitative evidence, relies on multiple
sources of evidence, and benefits from the prior development of theoretical
propositions. Case studies may involve both qualitative and quantitative
research methods.[1] Single-subject research provides the statistical framework for
making inferences from quantitative case-study data.[2][3] Another suggestion is
that case study should be defined as a "research strategy", an empirical inquiry
that investigates a phenomenon within its real-life context. A case study does not
necessarily have to be N=1, as there may be many observations within a case
(many individuals and entities across many time periods).[4][5]
• The resulting body of case study research has long had a prominent place in many
disciplines and professions, ranging from psychology, anthropology, sociology, and
political science to education, clinical science, social work, and administrative
science.[6][2]:5–6[7] Case study research have also played a prominent place in
business and management research.[

Experimental Research
• An experiment is a procedure carried out to support, refute, or validate
a hypothesis. Experiments provide insight into cause-and-effect by demonstrating
what outcome occurs when a particular factor is manipulated. Experiments vary
greatly in goal and scale, but always rely on repeatable procedure and logical
analysis of the results. There also exists natural experimental studies.
• A child may carry out basic experiments to understand gravity, while teams of
scientists may take years of systematic investigation to advance their
understanding of a phenomenon. Experiments and other types of hands-on
activities are very important to student learning in the science classroom.
Experiments can raise test scores and help a student become more engaged and
interested in the material they are learning, especially when used over
time.[1] Experiments can vary from personal and informal natural comparisons (e.g.
tasting a range of chocolates to find a favorite), to highly controlled (e.g. tests
requiring complex apparatus overseen by many scientists that hope to discover
information about subatomic particles). Uses of experiments vary considerably
between the natural and human sciences.
• Experiments typically include controls, which are designed to minimize the effects
of variables other than the single independent variable. This increases the
reliability of the results, often through a comparison between
control measurements and the other measurements. Scientific controls are a part
of the scientific method. Ideally, all variables in an experiment are controlled
(accounted for by the control measurements) and none are uncontrolled. In such
an experiment, if all controls work as expected, it is possible to conclude that the
experiment works as intended, and that results are due to the effect of the tested
variables.

Structure of experiments
• An experiment examines the effect of an independent variable on a dependent
variable. Typically, a stimulus is either absent or present. In this way, a hypothesis
on the causal influence between two variables can be tested. Both variables are, of
course, operationalized.
• An experiment involves pretesting and posttesting, i.e., the attributes of a
dependent variable are measured, first before manipulation of the independent
variable, and second after the anipulation. Of course, applied to one group, this
may affect the validity of the results, since the group is aware of what is being
measured (research affects what is being researched).
• Therefore, it is better to work with experimental groups and control groups. We
select two groups for study, then apply the pretesting-posttesting, and thus
conclude that any effect of the tests themselves must occur in both groups. There
can indeed be a Hawthorne effect, i.e., the attention given to the group by the
researchers affects the group’s behavior. Note that there can also be an
experimenter bias, which calls for accurate observation techniques of the expected
change in the dependent variable.
• Selecting Subjects—there can always be some bias because often students are
selected (problem of generalizability). Also, note that samples of 100 or not very
representative, and that experiments often have fewer than 100 subjects.

Survey research
• The main advantage of survey research is of
course the generalization of its findings
because of the representativeness of the
sample. Note that a pre-test of the
questionnaire is always necessary (as a matter
of validity).

Research Problem
• In research process, the first and foremost step
happens to be that of selecting and properly defining a
research problem. A researcher must find the problem
and formulate it so that it becomes susceptible to
research. Like a medical doctor, a researcher must
examine all the symptoms concerning a problem
before he can diagnose correctly. To define a problem
correctly, a researcher must know: what a problem is?
• A research problem, in general, refers to some
difficulty which a researcher experiences in the context
of either a theoretical or practical situation and wants
to obtain a solution for the same.

Components of Research problem
• (i) There must be an individual or a group which has
some difficulty or the problem.
• (ii) There must be some objective(s) to be attained at.
If one wants nothing, one cannot have a problem.
• (iii) There must be alternative means for obtaining the
objective(s) .
• (iv) There must remain some doubt in the mind of a
researcher to answer the question concerning the
research problem.
• (v) A research problem is one which requires a
researcher to find out the best solution for the

Selecting a Research problem
• The research problem undertaken for study must be carefully selected.
• The task is a difficult one, although it may not appear to be so.
• Help may be taken from a research guide in this connection.
• A research guide can be the most important help to a researcher to choose a
subject.
• However, the following points may be observed by a researcher in selecting a
research problem or a subject for research:
– (i) Subject which is overdone should not be normally chosen, for it will be a difficult task to
throw any new light in such a case.
– (ii) Controversial subject should not become the choice of an average researcher.
– Too narrow or too vague problems should be avoided.
– Before the final selection of a problem is done, a researcher must ask himself the following
questions:
• (a) Whether he is well equipped in terms of his background to carry out the research?
• (b) Whether the study falls within the budget he can afford?
• (c) Whether the necessary cooperation can be obtained from those who must participate in research
as subjects?

Research Process
• The research process involves identifying,
locating, assessing, and analyzing the
information you need to support your
research question, and then developing and
expressing your ideas. These are the same
skills you need any time you write a
report, proposal, or put together a
presentation.

1.Research Problem
• The first and foremost task in the entire process of scientific
research is to identify a research problem.
• A well-identified problem will lead the researcher to
accomplish all-important phases of the research process,
starting from setting objectives to the selection of the
research methodology.
• But the core question is: whether all problems require
research.
• We have countless problems around us, but all that we
encounter do not qualify as research problems, and thus,
these do not need to be researched.
• Keeping this point in view, we must draw a line between a
research problem and a non-research problem.

Statement of Problem
• A clear and well-defined statement of the problem is
considered as the foundation for the development of
the research proposal.
• It enables the researcher to systematically point out
why the proposed research on the problem should be
undertaken and what he hopes to achieve with the
findings of the study.
• A well-defined statement of the problem will lead the
researcher to formulate the research objectives, to
understand the background of the study, and to choose
a proper research methodology.

Justifying the problem
• Once the problem situation has been identified and
clearly stated, it is important to justify the importance
of the problem.
• In justifying the problems, we ask such questions as to
why the problem of the study is important, how large
and widespread is the problem, can others be
convinced about the importance of the problem and
the like.
• Answers to the above questions should be reviewed
and presented in one or two paragraphs that justify the
importance of the problem.

Analyzing the problem
• As a first step of analyzing the problem, critical
attention should be given to accommodate
the viewpoints of the managers, users, and
the researchers to the problem through
threadbare discussions.
• The next step is to identify the factors that
may have contributed to the perceived
problems.

2.Reviewing literature
• A review of relevant literature is an integral part of the
research process. It enables the researcher to
formulate his problem in terms of the specific aspects
of the general area of his interest that has not been so
far researched.
• Such a review, not only provides him exposure to a
larger body of knowledge but also equips him with
enhanced knowledge to efficiently follow the research
process.
• Through a proper review of the literature, the
researcher may develop the coherence between the
results of his study and those of the others.

In sum, we enumerate the following arguments in favor of reviewing
the literature:
• It avoids duplication of the work that has been done in the recent
past.
• It helps the researcher to find out what others have learned and
reported on the problem.
• It helps the researcher to become familiar with the types of
methodology followed by others.
• It helps the researcher to understand what concepts and theories
are relevant to his area of investigation.
• It helps the researcher to understand if there are any significant
controversies, contradictions, and inconsistencies in findings.
• It allows the researcher to understand if there are any unanswered
research questions.
• It might help the researcher to develop an analytical framework.
• It will help the researcher to consider the inclusion of variables in
his research that he might not otherwise have thought about.

3. Setting research objectives, and
hypotheses
• After discovering and defining the research
problem, researchers should make a formal
statement of the problem leading to research
objectives.
• An objective will precisely say what should be
researched, to delineate the type of information
that should be collected, and provide a
framework for the scope of the study. The best
expression of a research objective is a well-
formulated, testable research hypothesis.
• A hypothesis is an unproven statement or
proposition that can be refuted or supported by
empirical data. Hypothetical statements assert a
possible answer to a research question.

4. Research design
The research design is the blueprint or framework for fulfilling objectives and
answering research questions. It is a master plan specifying the methods and
procedures for collecting, processing, and analyzing the collected data. There are
four basic research designs that a researcher can use to conduct his or her study;
• survey,
• experiment,
• secondary data study, and
• observational study.
The type of research design to be chosen from among the above four designs depends
primarily on four factors:
• The type of problem
• The objectives of the study,
• The existing state of knowledge about the problem that is being studied, and
• The resources are available for the study.

5. Deciding on the sample design
• Sampling is an important and separate step in the research process. The
basic idea of sampling is that it involves any procedure that uses a
relatively small number of items or portions (called a sample) of a
universe (called population) to conclude the whole population.
• It contrasts with the process of complete enumeration, in which every
member of the population is included.
• Such a complete enumeration is referred to as census.
• A population is the total collection of elements about which we wish to
make some inference or generalization.
• A sample is a part of the population, carefully selected to represent that
population. If certain statistical procedures are followed in selecting the
sample, it should have the same characteristics as the population as a
whole. These procedures are embedded in the sample design.
• Sample design refers to the methods to be followed in selecting a sample
from the population and the estimating technique, vis-a-vis formula for
computing the sample statistics.

• The basic question is, then, how to select a sample?
• To answer this question, we must have acquaintance with the sampling
methods.
• These methods are basically of two types: probability sampling and non-
probability sampling. Probability sampling ensures every unit a known
nonzero probability of selection within the target population.
• If there is no feasible alternative, a non-probability sampling method may
be employed.
• The basis of such selection is entirely dependent on the researcher’s
discretion. This approach is variously called judgment sampling,
convenience sampling, accidental sampling, and purposive sampling.
• The most widely used probability sampling methods are simple random
sampling, stratified random sampling, cluster sampling, and systematic
sampling. They have been classified by their representation basis and unit
selection techniques.
• Two other variations of the sampling methods that are in great use
are multistage sampling and probability proportional to size (PPS)
sampling.
• Multistage sampling is most commonly used in drawing samples from very
large and diverse populations.
• The PPS sampling is a variation on multistage sampling in which the
probability of selecting a cluster is proportional to its size, and an equal
number of elements are sampled within each cluster.

6. Data collection
• The gathering of data may range from simple observation to a large-
scale survey in any defined population. There are many ways to
collect data.
• The approach selected depends on the objectives of the study, the
research design, and the availability of time, money, and personnel.
• With the variation in the type of data (qualitative or quantitative) to
be collected, the method of data collection also varies.
• The most common means for collecting quantitative data is
the structured interview.
• Studies that obtain data by interviewing respondents are called
surveys. Data can also be collected by using self-administered
questionnaires. Telephone interviewing is another way in which
data may be collected.
• Other means of data collection include the use of secondary
sources, such as the census, vital registration records, official
documents, previous surveys, etc.
• Qualitative data are collected mainly through in-depth interviews,
focus group discussions, and observational studies.

7. Data Processing and analyzing
• Data processing generally begins with the editing and coding of data. Data are
edited to ensure consistency across respondents and to locate omissions, if
any.
• In survey data, editing reduces errors in the recording, improves legibility, and
clarifies unclear and inappropriate responses. In addition to editing, the data
also need coding.
• Because it is impractical to place raw data into a report, alphanumeric codes
are used to reduce the responses to a more manageable form for storage and
future processing.
• This coding process facilitates processing the data. The personal computer
offers an excellent opportunity in data editing and coding processes.
• Data analysis usually involves reducing accumulated data to a manageable
size, developing summaries, searching for patterns, and applying statistical
techniques for understanding and interpreting the findings in the light of the
research questions.
• Further, the researcher, based on his analysis, determines if his findings are
consistent with the formulated hypotheses and theories.
• The techniques to be used in analyzing data may range from simple graphical
technique to very complex multivariate analysis depending on the objectives
of the study, research design employed, and the nature of data collected.
• As in the case of methods of data collection, an analytical technique
appropriate in one situation may not be appropriate for another.

8. Writing the Report
To this end, it is necessary to prepare a report and transmit the findings and recommendations to
administrators, policymakers, and program managers for the intended purpose of making a decision.
There are various forms of research reports: term papers, dissertations, journal articles, papers for
presentation at professional conferences and seminars, books, and so on. The results of a research
investigationprepared in any form are of little utility if they are not communicated to others.
The primary purpose of a dissemination strategy is to identify the most effective media channels to reach
different audience groups with study findings most relevant to their needs.
The dissemination may be made through a conference, a seminar, a report, or an oral or poster
presentation.
The style and organizationof the report will differ according to the target audience, the occasion, and the
purpose of the research. Reports should be developed from the client’s perspectives.
A report is an excellent means that helps to establish the researcher’s credibility. At a bare minimum, a
research report should contain sections on:
• An executive summary;
• Background of the problem;
• Literaturereview;
• Methodology;
• Findings;
• Discussion;
• Conclusions and
• Recommendations.
The results of the study can also be disseminated through peer-reviewedjournals published by academic
institutions and reputed publishers both at home and abroad.
These journals have their format and editorial policies. The contributorscan submit their manuscripts
adhering to the policies and format for possible publications of their papers.

What is a Research Design
• Research is an important activity affecting the society as a whole
therefore, it involves a lot of decision making.
• Research design also involves a lot of decision - making. It provides
a structure and shape to your research project.
• After finalising your topic, you decide about how you are going to
conduct your study.
• It involves formulation of strategy for all the stages starting from
formulation of hypotheses to the analysis of data
• a blueprint or detailed plan for a research
• study - starting from operationalising variables so that they can be
measured, to selecting
• It is a sample of interest to study, collecting data to be used as a
basis for testing hypotheses,
• and finally analysing the results

Need and Purpose of Research Design
The purpose of a research design is to provide
information regarding:
• What is the study about?
• Why is the study being carried out?
• Where will the study be carried out?
• How will the study be carried out?
• What will be the processes and tasks involved?
• What will be the data?
• How will the data be collected?
• What methods of sampling will be used? and
• How will the analysis be done?

Types of Research design
• There are different types of research design. Which one is the best for your study,
depends on the purpose and scope of your study. While taking decisions on the
research design, a number of factors have to be taken into consideration. These
include: Nature of investigation, Data collection methods, Number of contacts
made with the subjects, and the Period of reference of your study.
• Nature of Investigation:
– Exploratory;
– Descriptive;
– Experimental;
– Semi or Quasi- experimental;
– Non- experimental; and
– Field research.
• Data Collection Methods:
– Survey;
– Case studies;
– Content analysis;
• Reference Period
– Retrospective;
– Prospective; and
– Retrospective - Prospective.

Exploratory Research Design
• Exploratory research is the process of investigating a problem that
has not been studied or thoroughly investigated in the past .
Exploratory type of research is usually conducted to have a better
understanding of the existing problem, but usually doesn't lead to a
conclusive result.
• Researchers use exploratory research when trying to gain familiarity
with an existing phenomenon and acquire new insight into it to
form a more precise problem. It begins based on a general idea and
the outcomes of the research are used to find out related issues
with the topic of the research.
• In exploratory research, the process of the research varies
according to the finding of new data or insight. Also referred to as
interpretative research or grounded theory approach, the outcomes
of this research provide answers to questions like what, how and
why.

Characteristics of Exploratory research Design
• Exploratory research is inexpensive, highly interactive and open-ended in
nature.
• There is usually no prior relevant information available from past
researchers.
• It has no predefined structure.
• It answers questions like how and why aiding the researcher to acquire
more information about the research.
• The absence of relevant information from past research means the
researcher will spend a lot of time studying materials in detail. Therefore,
spending so much time conducting exploratory research.
• Since there is no standard for carrying out exploratory research, it is
usually flexible and scattered.
• There must a few theories which can verify your outcome.
• Researchers cannot form a conclusion based on exploratory research.
• The research problem must be important and valuable
• Exploratory research mostly deals with qualitative data.

Descriptive research Design
• Descriptive research is a type of research that describes a
population, situation, or phenomenon that is being studied.
It focuses on answering the how, what, when, and
where questions If a research problem, rather than the why.
• This is mainly because it is important to have a proper
understanding of what a research problem is about before
investigating why it exists in the first place.
• For example, an apparel brand that wants to understand the
fashion purchasing trends among New York buyers will
conduct a demographic survey of this region, gather
population data and then conduct descriptive research on
this demographic segment. The study will then uncover
details on “what is the purchasing pattern of New York
buyers,” but not cover any investigative information about
“why” the patterns exits. Because for the apparel brand
trying to break into this market, understanding the nature
of their market is the study’s objective.

Characteristics of Descriptive research Design
• Quantitative research: Descriptive research is a quantitative
research method that attempts to collect quantifiable information
for statistical analysis of the population sample. It is a popular
market research tool that allows us to collect and describe the
demographic segment’s nature.
• Uncontrolled variables: In descriptive research, none of the
variables are influenced in any way. This uses observational methods
to conduct the research. Hence, the nature of the variables or their
behavior is not in the hands of the researcher.
• Cross-sectional studies: Descriptive research is generally a cross-
sectional study where different sections belonging to the same
group are studied.
• The basis for further research: Researchers further research the
data collected and analyzed from descriptive research using
different research techniques. The data can also help point towards
the types of research methods used for the subsequent research.

Experimental Research Design
• Experimental research is a scientific approach to research, where
one or more independent variables are manipulated and applied to
one or more dependent variables to measure their effect on the
latter. The effect of the independent variables on the dependent
variables is usually observed and recorded over some time, to aid
researchers in drawing a reasonable conclusion regarding the
relationship between these 2 variable types.
• The experimental research method is widely used in physical and
social sciences, psychology, and education. It is based on the
comparison between two or more groups with a straightforward
logic, which may, however, be difficult to execute.
• Mostly related to a laboratory test procedure, experimental
research designs involve collecting quantitative data and
performing statistical analysis on them during research. Therefore,
making it an example of quantitative research method.

• Pre-experimental Research Design
• In pre-experimental research design, either a group or
various dependent groups are observed for the effect of
the application of an independent variable which is
presumed to cause change. It is the simplest form of
experimental research design and is treated with no control
group.
• Quasi-experimental Research Design
• The word "quasi" means partial, half, or pseudo. Therefore,
the quasi-experimental research bearing a resemblance to
the true experimental research, but not the same. In quasi-
experiments, the participants are not randomly assigned,
and as such, they are used in settings where randomization
is difficult or impossible.
• This is very common in educational research, where
administrators are unwilling to allow the random selection
of students for experimental samples.

Characteristics of Experimental research Design
• Variables
• Experimental research contains dependent, independent and extraneous
variables. The dependent variables are the variables being treated or manipulated
and are sometimes called the subject of the research.
• The independent variables are the experimental treatment being exerted on the
dependent variables. Extraneous variables, on the other hand, are other factors
affecting the experiment that may also contribute to the change.
• Setting
• The setting is where the experiment is carried out. Many experiments are carried
out in the laboratory, where control can be exerted on the extraneous variables,
thereby eliminating them.
• Other experiments are carried out in a less controllable setting. The choice of
setting used in research depends on the nature of the experiment being carried
out.
• Multivariable
• Experimental research may include multiple independent variables, e.g. time,
skills, test scores, etc.

Non-experimental research Design
• Non-experimental research is the type of research that does not
involve the manipulation of control or independent variable. In non-
experimental research, researchers measure variables as they
naturally occur without any further manipulation.
• This type of research is used when the researcher has no specific
research question about a causal relationship between 2 different
variables, and manipulation of the independent variable is
impossible. They are also used when:
– subjects cannot be randomly assigned to conditions.
– the research subject is about a causal relationship but the
independent variable cannot be manipulated.
– the research is broad and exploratory
– the research pertains to a non-causal relationship between variables.
– limited information can be accessed about the research subject.

Field research Design
• Field research is defined as a qualitative method of data
collection that aims to observe, interact and understand
people while they are in a natural environment. For
example, nature conservationists observe behavior of
animals in their natural surroundings and the way they
react to certain scenarios. In the same way, social scientists
conducting field research may conduct interviews or
observe people from a distance to understand how they
behave in a social environment and how they react to
situations around them.
• Field research encompasses a diverse range of social
research methods including direct observation, limited
participation, analysis of documents and other information,
informal interviews, surveys etc. Although field research is
generally characterized as qualitative research, it often
involves multiple aspects of quantitative research in it.

Methods of Field Research Design
• Direct Observation: In this method, the data is collected via an observational method or subjects in a
natural environment. In this method, the behavior or outcome of situation is not interfered in any way
by the researcher. The advantage of direct observation is that it offers contextual data on people,
situations, interactions and the surroundings. This method of field research is widely used in a public
setting or environment but not in a private environment as it raises an ethical dilemma.
• Participant Observation: In this method of field research, the researcher is deeply involved in the
research process, not just purely as an observer, but also as a participant. This method too is conducted
in a natural environment but the only difference is the researcher gets involved in the discussions and
can mould the direction of the discussions. In this method, researchers live in a comfortable
environment with the participants of the research, to make them comfortable and open up to in-depth
discussions.
• Ethnography: Ethnography is an expanded observation of social research and social perspective and the
cultural values of an entire social setting. In ethnography, entire communities are observed objectively.
For example, if a researcher would like to understand how an Amazon tribe lives their life and operates,
he/she may chose to observe them or live amongst them and silently observe their day-to-day behavior.
• Qualitative Interviews: Qualitative interviews are close-ended questions that are asked directly to the
research subjects. The qualitative interviews could be either informal and conversational, semi-
structured, standardized and open-ended or a mix of all the above three. This provides a wealth of data
to the researcher that they can sort through. This also helps collect relational data. This method of field
research can use a mix of one-on-one interviews, focus groups and text analysis.
• Case Study: A case study research is an in-depth analysis of a person, situation or event. This method
may look difficult to operate, however, it is one of the simplest ways of conducting research as it involves
a deep dive and thorough understanding the data collection methods and inferring the data.

SAMPLING PROCEDURES
• Sampling helps a lot in research. It is one of the most important factors
which determines the accuracy of your research/survey result. If anything
goes wrong with your sample then it will be directly reflected in the final
result. There are lot of techniques which help us to gather sample
depending upon the need and situation. This blog post tries to explain
some of those techniques.
• To start with, let’s have a look on some basic terminology
– Population
– Sample
– Sampling
• Population is the collection of the elements which has some or the other
characteristic in common. Number of elements in the population is the
size of the population.
• Sample is the subset of the population. The process of selecting a sample
is known as sampling. Number of elements in the sample is the sample
size.

Types of sampling
• There are lot of sampling techniques which
are grouped into two categories as
– Probability Sampling
– Non- Probability Sampling
• The difference lies between the above two is
whether the sample selection is based on
randomization or not. With randomization,
every element gets equal chance to be picked
up and to be part of sample for study.

Probability sampling
• This Sampling technique uses randomization to
make sure that every element of the population
gets an equal chance to be part of the selected
sample. It’s alternatively known as random
sampling.
• Types of Probability sampling
– Simple Random Sampling
– Stratified sampling
– Systematic sampling
– Cluster Sampling
– Multi stage Sampling

Simple Random Sampling
• Simple Random Sampling: Every element has
an equal chance of getting selected to be the
part sample. It is used when we don’t have
any kind of prior information about the target
population.
• For example: Random selection of 20 students
from class of 50 student. Each student has
equal chance of getting selected. Here
probability of selection is 1/50

Stratified sampling
• This technique divides the elements of the population
into small subgroups (strata) based on the similarity in
such a way that the elements within the group are
homogeneous and heterogeneous among the other
subgroups formed. And then the elements are
randomly selected from each of these strata. We need
to have prior information about the population to
create subgroups.

Cluster Sampling
• Our entire population is divided into clusters
or sections and then the clusters are randomly
selected. All the elements of the cluster are
used for sampling. Clusters are identified using
details such as age, sex, location etc.

• Cluster sampling can be done in following
ways:
Single Stage Cluster Sampling
– Entire cluster is selected randomly for sampling.

• · Two Stage Cluster Sampling
– Here first we randomly select clusters and then
from those selected clusters we randomly select
elements for sampling

Systematic clustering
• Here the selection of elements is systematic and not random except the
first element. Elements of a sample are chosen at regular intervals of
population. All the elements are put together in a sequence first where
each element has the equal chance of being selected.
• For a sample of size n, we divide our population of size N into subgroups of
k elements.
• We select our first element randomly from the first subgroup of k
elements.
• To select other elements of sample, perform following:
• We know number of elements in each group is k i.e N/n
• So if our first element is n1 then
• Second element is n1+k i.e n2
• Third element n2+k i.e n3 and so on..
• Taking an example of N=20, n=5
• No of elements in each of the subgroups is N/n i.e 20/5 =4= k
• Now, randomly select first element from the first subgroup.
• If we select n1= 3
• n2 = n1+k = 3+4 = 7
• n3 = n2+k = 7+4 = 11

Multi-stage sampling
• It is the combination of one or more methods
described above.
• Population is divided into multiple clusters and then
these clusters are further divided and grouped into
various sub groups (strata) based on similarity. One or
more clusters can be randomly selected from each
stratum. This process continues until the cluster can’t
be divided anymore. For example country can be
divided into states, cities, urban and rural and all the
areas with similar characteristics can be merged
together to form a strata.

Non-probability sampling
• It does not rely on randomization. This technique
is more reliant on the researcher’s ability to
select elements for a sample. Outcome of
sampling might be biased and makes difficult for
all the elements of population to be part of the
sample equally. This type of sampling is also
known as non-random sampling.
– Convenience Sampling
– Purposive Sampling
– Quota Sampling
– Referral /Snowball Sampling

Convenience sampling
• Here the samples are selected based on the
availability. This method is used when the
availability of sample is rare and also costly. So
based on the convenience samples are
selected.
• For example: Researchers prefer this during
the initial stages of survey research, as it’s
quick and easy to deliver results.

Purposive sampling
• This is based on the intention or the purpose of
study. Only those elements will be selected from
the population which suits the best for the
purpose of our study.
• For Example: If we want to understand the
thought process of the people who are interested
in pursuing master’s degree then the selection
criteria would be “Are you interested for Masters
in..?”
• All the people who respond with a “No” will be
excluded from our sample.

Quota sampling
• Quota Sampling
• This type of sampling depends of some pre-set
standard. It selects the representative sample
from the population. Proportion of
characteristics/ trait in sample should be same as
population. Elements are selected until exact
proportions of certain types of data is obtained or
sufficient data in different categories is collected.
• For example: If our population has 45% females
and 55% males then our sample should reflect
the same percentage of males and females.

Referral/Snowball sampling
• This technique is used in the situations where the
population is completely unknown and rare.
• Therefore we will take the help from the first element
which we select for the population and ask him to
recommend other elements who will fit the description of
the sample needed.
• So this referral technique goes on, increasing the size of
population like a snowball.
• For example: It’s used in situations of highly sensitive topics
like HIV Aids where people will not openly discuss and
participate in surveys to share information about HIV Aids.

Questionnaire
• Survey research typically involves administering a
questionnaire to a sample of respondents to
draw conclusions on the population from which
the sample is drawn. The questionnaire is
standardized to ensure that the same observation
method is used on all respondents. This involves
considerations of questionnaire construction,
question wording, and the way in which the
questionnaire is administered to the
respondents.

Questionnaire construction
• In the construction of the questionnaire, attention is devoted to
increase the respondents’ cooperation and avoid misunderstanding
of the questions.
• First, the questionnaire format should be presentable, not too
densely packed, and clear. This involves using intelligible
contingency (“if no/yes /go to...”) questions, or matrix questions
that contain al the items or response options to a question.
• Second, the effects of question order have to be considered, and
this can be pre-tested with different questionnaires, and by being
sensitive to the research problem.
• Third, clear instructions on how to answer the questions should be
given, and it is best to divide the questionnaire into different
sections that are each preceded with instructions

Question wording
• The question wording should equally enhance the unambiguous
nature of the questionnaire. Several options are available
depending on the research perspective: attitudes, for instance, can
be measured with Likert scale questions (variation from strongly
disagree to strongly agree). Questions can also be open-ended (and
coded by the researcher for analysis) or closed-ended (an
exhaustive list of mutually exclusive alternatives). Note that open-
ended questions may pose problems for analysis (too many
responses), while closed-ended questions may impose too rigid a
framework on the respondents.
• Also, each statement should not be too long, not negatively
phrased, and posed in neutral, unambiguous terms to avoid social
desirability effects and bias in any one (pro/con) direction. Also
avoid double-barreled questions, and make sure to ask
comprehensible and relevant questions.

Administration of questionnaire
• Questionnaires can be administered in a variety of ways.
• (a) Self-Administered Questionnaire: In this type of survey, respondents fill out a
questionnaire delivered to them by mail, taking precautions to ensure a
sufficiently high response rate, or they can be delivered “on the spot”, e.g., in a
factory or school. The basic problem is the monitoring of returns, which have to be
identified, i.e., you have to make up a return graph to indicate the response rate
(over 50%), and you have to send follow-up mailings to non-respondents.
• (b) Interview Survey: In a (more time-consuming and expensive) interview survey,
sensitive and complicated issues can be explored face-to-face. This method also
ensures a higher response rate, and a reduction of “don’t know” answers. The
interviewer has more control over the data collection process (note that
observations can be made during the interview) and can clarify, in a standardized
way, unclear questions. Since the questionnaire is the main measurement
instrument, the interviewer must make sure that the questions have identical
meaning to all respondents: interviewers should (and are trained to) be familiar
with the questionnaire, dress like the respondents, behave in a neutral way during
the interview, follow the given question wording and order, record the answers
exactly, and probe for answers. Interview surveys typically have a higher response
rate.
• (c) Telephone Survey: A questionnaire conducted by telephone is a cheaper and
less time-consuming method, one moreover in which the researcher can keep an
eye on the interviewers, but one on which the respondents can also hang up.

Observation method
• The observation method is the most commonly used method specially in studies
relating to behavioural sciences.
• Under the observation method, the information is sought by way of investigator’s
own direct observation without asking from the respondent.
• For instance, in a study relating to consumer behaviour, the investigator instead of
asking the brand of wrist watch used by the respondent, may himself look at the
watch.
• The main advantage of this method is that subjective bias is eliminated, if
observation is done accurately. Secondly, the information obtained under this
method relates to what is currently happening; it is not complicated by either the
past behaviour or future intentions or attitudes. Thirdly, this method is
independent of respondents’ willingness to respond and as such is relatively less
demanding of active cooperation on the part of respondents as happens to be the
case in the interview or the questionnaire method.
• This method is particularly suitable in studies which deal with subjects (i.e.,
respondents) who are not capable of giving verbal reports of their feelings for one
reason or the other.

• However, observation method has various limitations. Firstly, it is an
expensive method. Secondly, the information provided by this
method is very limited. Thirdly, sometimes unforeseen factors may
interfere with the observational task. At times, the fact that some
people are rarely accessible to direct observation creates obstacle
for this method to collect data effectively.
• While using this method, the researcher should keep in mind things
like: What should be observed? How the observations should be
recorded? Or how the accuracy of observation can be ensured?
• In case the observation is characterised by a careful definition of
the units to be observed, the style of recording the observed
information, standardised conditions of observation and the
selection of pertinent data of observation, then the observation is
called as structured observation.
• But when observation is to take place without these characteristics
to be thought of in advance, the same is termed as unstructured
observation. Structured observation is considered appropriate in
descriptive studies, whereas in an exploratory study the
observational procedure is most likely to be relatively unstructured.

Merits of Observation method
• (i) The researcher is enabled to record the
natural behaviour of the group.
• (ii) The researcher can even gather
information which could not easily be
obtained if he observes in a disinterested
fashion.
• (iii) The researcher can even verify the truth of
statements made by informants in the context
of a questionnaire or a schedule.

Rating Scales and Checklist
• Checklists and rating scales are tools that state specific criteria and allow teachers
and students to gather information and to make judgements about what students
know and can do in relation to the outcomes. They offer systematic ways of
collecting data about specific behaviours, knowledge and skills.
• The quality of information acquired through the use of checklists and rating scales
is highly dependent on the quality of the descriptors chosen for assessment.
• Checklists is a one-page, non-technical checklist for the key points of good
practice in research. Use of the Checklist can assist researchers and organisations
in fulfilling the requirements of regulatory, funding and other bodies and ensure
that important issues have not been overlooked
• Rating Scales allow teachers to indicate the degree or frequency of the
behaviours, skills and strategies displayed by the learner. To continue the light
switch analogy, a rating scale is like a dimmer switch that provides for a range of
performance levels. Rating scales state the criteria and provide three or four
response selections to describe the quality or frequency of student work.

Purpose of Checklists and rating scales
• The purpose of checklists and rating scales is to:
– provide tools for systematic recording of observations
– provide tools for self-assessment
– provide samples of criteria for students prior to
collecting and evaluating data on their work
record the development of specific skills, strategies,
attitudes and behaviours necessary for demonstrating
learning
– clarify students' instructional needs by presenting a
record of current accomplishments.

Types of Scales
• Nominal scale
– A nominal scale is where:
• the data can be classified into a non-numerical or named categories, and
• the order in which these categories can be written or asked is arbitrary.
• Ordinal scale
– An ordinal scale is where:
• the data can be classified into non-numerical or named categories
• an inherent order exists among the response categories.
• Ordinal scales are seen in questions that call for ratings of quality (for example, very
good, good, fair, poor, very poor) and agreement (for example, strongly agree, agree,
disagree, strongly disagree).
• Numerical scale
– A numerical scale is:
• where numbers represent the possible response categories
• there is a natural ranking of the categories
• zero on the scale has meaning
• there is a quantifiable difference within categories and between consecutive categories.

Likert Scale
• Likert Scale is a psychometric scale where questions based on this scale
are normally used in a survey. It is one of the most widely used question
types in a survey. In a Likert Scale Survey respondents simply don't
choose between "yes/no", there are specific choices based on "agreeing"
or "disagreeing" on a certain question in the survey.
• Likert scale survey questions are essential in measuring a respondent's
opinion or attitude towards a given subject. Likert Scale is typically a five,
seven, or nine point agreement scale used to measure respondents'
agreement with a variety of statements. Organizational psychologist
Rensis Likert developed the Likert Scale in order to assess the level of
agreement or disagreement of a symmetric agree-disagree scale

Advantages of Likert scale
• Likert Scale survey is a universal method of collecting
data or information, which means its is easy to
understand and respond.
• When the survey creator tends to work around
quantitative data, it is easier to report results from the
respondents.
• Since likert scale survey involves using a scale,
respondents are not forced to choose response options
in extremes, allowing them to be neutral if they choose
so.
• Last but not the least it's very easy to run this kind of
survey as they are not time consuming.

Library records and reports
• Catalog
– University Library Catalog.
• Course Reserves
– Find library materialsplaced on course reserves.
• Databases
– Use databases to find articles and other research materials.
• Newspapers
– A research portal highlightingmajor newspaper collections at University in electronic format
• Research Guides
– Listing of recommended research resources by subject .
• Digital Maps and Geographic Data Portal
– Search for digitized maps and geographicdata available.
• E-journals
– Search tool to identify and access electronic journals.
• Archives/Rare documents
– Catalog of descriptive inventories for archival records and manuscript collections held within
the University Library.
• University Digital Library
– Collection of theses/dissertation, audio-visual material, special reports, high-resolution digital
images of selected materials from University Library
• Specialized Catalogs & Collection of Databases
• Supplementary library catalogs and other research databases, including catalogs of
the Departmental libraries.

Research Process Checklist
• This Reseach Process Checklist is desgined to
provide general guidelines for conducting
educational research. It can be used as a
planning guide before a research study begins,
as a review procedure for a research study in
progress. The major issues that must be
addressed in each step of the research process
are enumerated in the checklist.

Depending on the nature of a particular study, a checklist might include;
I. Defining the reseach question and the nature of the research
1. Specify the research problem in clear and explicit terms.
2. Review the literature related to the research problem.
A.Review substantive/conceptual issues.
B.Review technical/methodological issues.
C.Enumerate recommendations for improving research offered by those
who have conducted previous research.
3. Determine whether the research questions deals with:
A. Description
B. Relationships or correlation
C. Differences
4. Specify each research hypothesis to be explored in the study.
5. Classify the research approach as:
A. Descriptive
B. Correlational
C. Quasi-experimental
D. Experimental
6. Specify delimitations of the study.

Role of statistical methods in research
• statistics is a range of procedures for gathering, organising, analysing and presenting quantitative
data. ‘Data’ is the term for facts that have been obtained and subsequently recorded, and, for
statisticians, ‘data’ usually refers to quantitative data that are numbers. Essentially therefore,
statistics is a scientific approach to analysing numerical data in order to enable us to maximise our
interpretation, understanding and use. This means that statistics helps us turn data into
information; that is, data that have been interpreted, understood and are useful to the recipient.
Some other reasons to use statistical methods in research are;
• measure things;
• examine relationships;
• make predictions;
• test hypotheses;
• construct concepts and develop theories;
• explore issues;
• explain activities or attitudes;
• describe what is happening;
• present information;
• make comparisons to find similarities and differences;
• draw conclusions about populations based only on sample results
The important statisticalmeasures that are used to summarise the survey/research data are:
– (1) measures of central tendency or statistical averages;
– (2) measures of dispersion;
– (3) measures of asymmetry ;
– (4) measures of relationship; and
– (5) other measures.
Amongst the measures of central tendency, the three most important ones are the arithmeticaverage
or mean, median and mode.

Central Tendency
• In statistics, a central tendency is a central or typical value for a probability
distribution. It may also be called a center or location of the distribution.
Colloquially, measures of central tendency are often called averages. The
most common measures of central tendency are the arithmetic mean,
the median and the mode.
• The following may be applied to one-dimensional data. Depending on the
circumstances, it may be appropriate to transform the data before
calculating a central tendency.
– Mean (Average): Represents the sum of all values in a dataset divided
by the total number of the values.
– Median: The middle value in a dataset that is arranged in ascending
order (from the smallest value to the largest value). If a dataset
contains an even number of values, the median of the dataset is the
mean of the two middle values.
– Mode: Defines the most frequently occurring value in a dataset. In
some cases, a dataset may contain multiple modes while some
datasets may not have any mode at all.

Mean
• In mathematics and statistics, the arithmetic mean or simply
the mean or average is the sum of a collection of numbers divided by the
count of numbers in the collection. The arithmetic mean is the most
commonly used and readily understood measure of central tendency in
a data set. In statistics, the term average refers to any of the measures of
central tendency.

Median
• The median is the value separating the higher half from the
lower half of a data sample (a population or a probability
distribution). For a data set, it may be thought of as the
"middle" value. For example, in the data set {1, 3, 3, 6, 7, 8,
9}, the median is 6, the fourth largest, and also the fourth
smallest, number in the sample.

Mode
• Mode is the most commonly or frequently occurring value
in a series. The mode in a distribution is that item around
which there is maximum concentration. In general, mode is
the size of the item which has the maximum frequency, but
at items such an item may not be mode on account of the
effect of the frequencies of the neighbouring items.
The number which appears most often in a set of numbers.
Example: in {6, 3, 9, 6, 6, 5, 9, 3} the Mode is 6 (it occurs
most often).

Research Methodology by Dr. Jatinder Kumar.pdf

Research Methodology by Dr. Jatinder Kumar.pdf

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