good notes

1. RESEARCH METHODOLOGY
INTRODUCTION
Introduction to research; Definitions and characteristics of research; Types of research –
Descriptive vs. Analytical, Applied vs. Fundamental, Quantitative vs. Qualitative, Conceptual
vs. Empirical, Main components of any research work.
Introduction to Research:
It is define as a scientific and systematic search for pertinent information on a specific
topic. In fact, research is an art of scientific investigation. Meaning of research as “a careful
investigation or inquiry specially through search for new facts in any branch of
knowledge.”The main aim of research is to find out the truth which is hidden and which has
not been discovered as yet.
1) To gain familiarity with a phenomenon or to achieve new insights into it
2) To portray accurately the characteristics of a particular individual, situation
3) To test a hypothesis of a causal relationship between variables
The possible motives for doing research may be either one or more of the following:
1. Desire to get a research degree along with its consequential benefits;
2. Desire to face the challenge in solving the unsolved problems
3. Desire to get intellectual joy of doing some creative work;
4. Desire to be of service to society;
5. Desire to get respectability.
Characteristics of research
1. The research should focus on priority problems
2. The research should be systematic. It emphasizes that a researcher should employ a
structured procedure.
3. The research should be logical. Without manipulating ideas logically, the scientific
researcher cannot make much progress in any investigation.
4. The research must be relatively simple, timely, and time-bound, employing a
comparatively simple design.
5. The research must be as much cost-effective as possible.
6. The research must be relatively simple, timely, and time-bound, employing a
comparatively simple design.
Types of Research
Basic Research:
 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.

2.  This type of research is often purely theoretical, with the intent of increasing our
understanding of certain phenomena or behavior but without seeking to solve or treat
these problems
 Most scientists believe that a basic, fundamental understanding of all branches of
science is needed in order for progress to take place. In other words, basic research
lays down the foundation for the applied science that follows. If basic work is done
first, then applied spin-offs often eventually result from this research.
Example
The author investigated the smoothness of the solution of the degenerate Hamilton-
Bellman (HJB) equation associated with a linear- quadratic regulator control.The author
established the existence of a classical solution of degenerate HJB equation associated with
this problem by the technique of viscosity solutions and hence derived an optimal control
from the optimality conditions in the HJB equation.
Applied Research
 Applied research aims at finding a solution for an immediate problem facing a society
or an industrial/business organization.
 Applied research refers to scientific study and research that seeks to solve practical
problems. This type of research plays an important role in solving everyday problems
that often have an impact on life, work, health, and overall well-being
 Scientists feel that the time has come for a shift in emphasis away from purely basic
research and toward applied science. This trend, they feel, is necessitated by the
problems resulting from global overpopulation, pollution, and the overuse of the
earth's natural resources.
Example
It has been observed that in Bangladesh, the proportion of women who are delivered
through Caesarean section is very high.It is suspected that a small height is one of the risk
factors for difficult deliveries. A study may, therefore, be conducted to verify if this
proposition is true.
Descriptive Research
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. In social science and business research we quite often use the term Ex post facto
research or after-the-fact research for descriptive research studies.
Analytical Research
Analytical research Carrying out analysis on a phenomenon and understanding the
phenomena discovering and measuring causal relations among them and focuses on
understanding the cause-effect relationships between two or more variables. In analytical

3. research, on the other hand, the researcher has to use facts or information already available,
and analyze these to make a critical evaluation of the material.
Descriptive Research Analytical Research
Fact-finding enquires and survey methods Collected data is analyzed and explained
Ascertains and describes the characteristics
of the issue
Beyond merely describing the characteristics
Describes of the state of affairs as it exists at
present
Explains existing state of affairs from
available data
No control over the variables Works within the constraints variables
Mostly pointed towards a particular problem
and ability to identify it
Sometimes indirect or makes the inferences
about the problem(s)
Failures caused by the Fatigue? How the fatigue of workers/operators can be
overcome? - Higher level Management.
Any way to solve instantaneously? Solving the problem by establishing various
components.
Quantitative Research
Quantitative research is based on the measurement of quantity or amount. It is
applicable to the phenomena that can be expressed in terms of quantity. So we can define that
quantitative research is the systematic scientific investigation of quantitative properties and
phenomena with their relationships. The process of measurement is central to quantitative
research because it provides the fundamental connection between empirical observation and
mathematical expression of quantitative relationship.
For example, the examination, analysis and interpretation of observations for the
purpose of discovering delaying meaning and patterns of relationships, including
classification of types of phenomena and ratites, in a manner that does not involve the
quantitative method.
Qualitative Research
Qualitative research is concerned with the qualitative phenomenon, i.e. phenomena
relating to or involving quality or kind. Qualitative researchers aim to gather an in-depth
understanding of human behaviour and the reason that govern such behaviour. While
discussing on the investigation of human behaviour we can use the times “motivation
research”, which is an important type of qualitative research. This type of research aims at
discovering the under lying motives and desires, using in depth indicators for the purpose.
Quantitative Research Qualitative Research
It is numerical, non-descriptive, applies
statistics or mathematics and uses numbers.
It is non-numerical, descriptive, applies
reasoning and uses words.
It is an iterative process whereby
Evidence is evaluated.
Its aim is to get the meaning, feeling and
describe the situation.
The results are often presented in tables and Qualitative data cannot be graphed.

4. graphs.
It is conclusive It is Exploratory
It investigates the what, where and when of
decision making.
It investigates the why and how of decision
making
All aspects of the study are carefully
designed before data is collected
The design emerges as the study unfolds
Researchers uses tools to collect data Researcher is the data gathering instrument
Data is in the form of numbers and statistics Data is in the form of words, Pictures and
objects
Quantitative Data is more efficient Qualitative Data is more rich
Conceptual Research
Conceptual research is a type of research that is generally related to abstract ideas or
concepts. It doesn‟t particularly involve any practical experimentation. However, this type of
research typically involves observing and analyzing information already present on a given
topic. Philosophical research is a generally good example for conceptual research.
For example, Copernicus used conceptual research to come up with the concepts
about stellar constellations based on his observations of the universe. Down the line, Galileo
simplified Copernicus‟s research by making his own conceptual observations which gave rise
to more experimental research and confirmed the predictions made at that time.
Empirical Research
Empirical research is basically a research that uses empirical evidence. Empirical
evidence refers to evidence verifiable by observation or experience rather than theory or pure
logic. Thus, empirical research is research studies with conclusions based on empirical
evidence. Moreover, empirical research studies are observable and measurable.
Empirical evidence can be gathered through qualitative research studies
or quantitative research studies. Qualitative research methods gather non-numerical or non-
statistical data. Thus, this type of studies helps to understand the underlying reasons,
opinions, and motivations behind something as well as to uncover trends in thought and
opinions. Quantitative research studies, on the other hand, gather statistical data.
Empirical research is appropriate when proof is sought that certain variables affect
other variables in some way. Evidence gathered through experiments or empirical studies is
today considered to be the most powerful support possible for a given hypothesis.
Main Components of Research Work
1. The Abstract
2. Introduction
3. Methodology
4. Results
5. Discussion

5. 6. References
Defining the problem, Literature survey to gaps, Objectives to fulfill, Methodology to
follow, Experimentation/Theoretical work procedure, Data Manipulation, Result Analysis,
Future Scope of Work, Conclusion, References
Research Process
Research process consists of series of actions or steps necessary to effectively carry
out research and the desired sequencing of these steps.
1. Formulating the research problem:
There are two types of research problems, viz., thosewhich 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.
2. Extensive literature survey:
Once the problem is formulated, a brief summary of it should be written down. It is
compulsory for a research worker writing a thesis for a Ph.D. degree to write a synopsis of
the topic and submit it to the necessary Committee or the Research Board for approval. At
this juncture the researcher should undertake extensive literature survey connected with the
problem.
3. Development of working hypotheses:
After extensive literature survey, researcher should state in clear terms the working
hypothesis or hypotheses. Working hypothesis is tentative assumption made in order to draw

6. out and test its logical or empirical consequences. As such the manner in which research
hypotheses are developed is particularly important since they provide the focal point for
research.
4. Preparing the research design:
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.
5. Determining sample design:
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. It can be presumed that in such an inquiry when all the items are covered no
element of chance is left and highest accuracy is obtained.
6. Collecting the data:
In dealing with any real life problem it is often found that data at hand are inadequate,
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.
8. Analysis of data:
After the data have been collected, the researcher turns to the task of analyzing them.
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.
Criteria of Good Research
Whatever may be the types of research works and studies, one thing that is important
is that they all meet on the common ground of scientific method employed by them. One
expects scientific research to satisfy the following criteria:
1. The purpose of the research should be clearly defined and common concepts be used.
2. The research procedure used should be described in sufficient detail to permit
anotherresearcher to repeat the research for further advancement, keeping the
continuity of what has already been attained.
3. The procedural design of the research should be carefully planned to yield results that
are as objective as possible.
4. The researcher should report with complete frankness, flaws in procedural design and
estimate their effects upon the findings.

7. 5. The analysis of data should be sufficiently adequate to reveal its significance and the
methods of analysis used should be appropriate. The validity and reliability of the data
should be checked carefully.
6. Conclusions should be confined to those justified by the data of the research and
limited to those for which the data provide an adequate basis.
7. Greater confidence in research is warranted if the researcher is experienced, has a
good reputation in research and is a person of integrity.
Problems Encountered by Researchers in India
1. Researchers in India, particularly those engaged in empirical research, are facing
several problems. Some of the important problems are as follows:
2. The lack of a scientific training in the methodology of research is a great
impedimentfor researchers in our country. There is paucity of competent researchers.
3. There is insufficient interaction between the university research departments on one
sideand business establishments, government departments and research institutions on
the otherside.
4. Most of the business units in our country do not have the confidence that the
materialsupplied by them to researchers will not be misused and as such they are often
reluctant insupplying the needed information to researchers.
5. Research studies overlapping one another are undertaken quite often for want
ofadequate information. This results in duplication and fritters away resources. This
problemcan be solved by proper compilation and revision, at regular intervals, of a list
of subjects onwhich and the places where the research is going on.
6. There does not exist a code of conduct for researchers and inter-university and inter-
departmental rivalries are also quite common.Many researchers in our country also
face the difficulty of adequate and timely secretarialassistance, including computerial
assistance.
7. Library management and functioning is not satisfactory at many places and much
ofthe time and energy of researchers are spent in tracing out the books, journals,
reports, etc.,rather than in tracing out relevant material from them.
8. There is also the problem that many of our libraries are not able to get copies of
oldand new Acts/Rules, reports and other government publications in time.
9. There may, at times, take place the problem of conceptualization and also
problemsrelating to the process of data collection and related things.
Research Methods VS Research Methodology

8. Scientific Method
The scientific method is, thus, based on certain basic postulates which can be stated as under:
1. It relies on empirical evidence
2. It utilizes relevant concepts
3. It is committed to only objective considerations
4. It presupposes ethical neutrality, i.e., it aims at nothing but making only adequate
and correctstatements about population objects
5. It results into probabilistic predictions
6. Its methodology is made known to all concerned for critical scrutiny is for use in
testingthe conclusions through replication
7. It aims at formulating most general axioms or what can be termed as scientific
theories
Importance of Knowing How Research is done
The study of research methodology gives the student the necessary training in gathering
material and arranging or card-indexing them, participation in the field work when required,
and also training in techniques for the collection of data appropriate to particular problems, in
the use of statistics, questionnaires and controlled experimentation and in recording evidence,
sorting it out and interpreting it. In fact, importance of knowing the methodology of research
or how research is done stems from the following considerations:
1. For one who is preparing himself for a career of carrying out research, the importance
of knowing research methodology and research techniques is obvious since the same
constitute the tools of his trade.
2. Knowledge of how to do research will inculcate the ability to evaluate and use
research results with reasonable confidence.

9. 3. When one knows how research is done, then one may have the satisfaction of
acquiring a new intellectual tool which can become a way of looking at the world and
of judging every day experience.
4. In this scientific age, all of us are in many ways consumers of research results and we
can use them intelligently provided we are able to judge the adequacy of the methods
by which they have been obtained.

10. RESEARCH FORMULATION
Defining and formulating the research problem: Selecting the problem - Necessity of
defining the problem, Literature review: Importance of literature review in defining a
problem, Primary and secondary sources –reviews, treatise, monographs-patents – web as a
source – searching in the web - Critical literature review – Identifying gap areas from
literature review.
In research process, the first and foremost step happens to be that of selecting and
properly defininga 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 (presented to him or observed by him) concerning a problem before he can
diagnose correctly. To define a problem correctly, a researcher must know: what a problem
is?
Selecting the 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. Nevertheless, every researcher must find out his own salvation for research
problems cannot be borrowed. A problem must spring from the researcher‟s mind like a plant
springing from its own seed. If our eyes need glasses, it is not the optician alone who decides
about the number of require.
(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.
(iii) Too narrow or too vague problems should be avoided.
(iv) The subject selected for research should be familiar and feasible so that the related
researchmaterial or sources of research are within one‟s reach. Even then it is quite
difficult to supply definitive ideas concerning how a researcher should obtain ideas
for his research.
(v) The importance of the subject, the qualifications and the training of a researcher, the
costs involved, the time factor are few other criteria that must also be considered in
selecting a problem.
Necessity of defining the problem
Quite often we all hear that a problem clearly stated is a problem half solved. This
statement signifies the need for defining a research problem. The problem to be investigated
must be defined unambiguously for that will help to discriminate relevant data from the
irrelevant ones. A proper definition of research problem will enable the researcher to be on
the track whereas an ill-defined problem may create hurdles.
Thus, defining a research problem properly is a prerequisite for any study and is a step
of the highest importance. In fact, formulation of a problem is often more essential than its

11. solution. It is only on careful detailing the research problem that we can work out the
research design and can smoothly carry on all the consequential steps involved while doing
research.
Technique involved in defining a problem
Defining a research problem properly and clearly is a crucial part of a research study
and must in no case be accomplished hurriedly. However, in practice this frequently
overlooked which causesa lot of problems later on.
The technique for the purpose involves the undertaking of the following steps generally
one after the other: (i) statement of the problem in a general way; (ii) understanding the
nature of the problem; (iii) surveying the available literature (iv) developing the ideas through
discussions; and (v) rephrasing the research problem into a working proposition.
1. First of all the problem should be stated in a broad general way, keeping in view
either some practical concern or some scientific or intellectual interest. For this
purpose, the researcher must immerse himself thoroughly in the subject matter
concerning which he wishes to pose a problem.
2. The next step in defining the problem is to understand its origin and nature
clearly. The best way of understanding the problem is to discuss it with those who
first raised it in order to find out how the problem originally came about and with
what objectives in view.
3. All available literature concerning the problem at hand must necessarily be
surveyed and examined before a definition of the research problem is given. This
means that the researcher must be well-conversant with relevant theories in the
field, reports and records as also all other relevant literature.
4. Discussion concerning a problem often produces useful information. Various new
ideas can be developed through such an exercise. Hence, a researcher must discuss
his problem with his colleagues and others who have enough experience in the
same area or in working on similar problems.
5. Finally, the researcher must sit to rephrase the research problem into a working
proposition
Example of difining problem
The technique of defining a problem outlined above can be illustrated for better
understanding bytaking an example as under:
Let us suppose that a research problem in a broad general way is as follows: “Why is
productivity in Japan so much higher than in India”? In this form the question has a number
of ambiguities such as: What sort of productivityis being referred to? With what industries
the same is related? With what period of timethe productivity is being talked about? In view
of all such ambiguities the given statementor the question is much too general to be amenable
to analysis. Rethinking and discussionsabout the problem may result in narrowing down the
question to:

12. “What factors were responsible for the higher labour productivity of Japan‟s
manufacturing industries during the decade 1971 to 1980 relative to India‟s manufacturing
industries? This latter version of the problem is definitely an improvement over its earlier
version for the various ambiguities have been removed to the extent possible. Further
rethinking and rephrasing might place the problem on a still better operational basis as shown
below:
“To what extent did labour productivity in 1971 to 1980 in Japan exceed that of India
in respect of 15 selected manufacturing industries? What factors were responsible for the
productivity differentials between the two countries by industries?”
With this sort of formulation, the various terms involved such as „labour
productivity‟, „productivity differentials‟, etc. must be explained clearly. The researcher must
also see that the necessary data are available.
Literature Review
A literature review or narrative review is a type of review article. A literature review
is a scholarly paper that presents the current knowledge including substantive findings as well
as theoretical and methodological contributions to a particular topic.
A literature review shows your readers that you have an in-depth grasp of your
subject; and that you understand where your own research fits into and adds to an existing
body of agreed knowledge.
Argumentative Review:
This form examines literature selectively in order to support or refute an argument,
deeply imbedded assumption, or philosophical problem already established in the literature.
The purpose is to develop a body of literature that establishes a contrarian viewpoint. Given
the value-laden nature of some social science research [e.g., educational reform; immigration
control], argumentative approaches to analysing the literature can be a legitimate and
important form of discourse.
Integrative Review:
Considered a form of research that reviews, critiques, and synthesizes representative
literature on a topic in an integrated way such that new frameworks and perspectives on the
topic are generated. The body of literature includes all studies that address related or identical
hypotheses.
Historical Review:
Few things rest in isolation from historical precedent. Historical reviews are focused
on examining research throughout a period of time; often starting with the first time an issue,
concept, theory, phenomena emerged in the literature, then tracing its evolution within the
scholarship of a discipline.

13. Systematic Review:
This form consists of an overview of existing evidence pertinent to a clearly
formulated research question, which uses pre-specified and standardized methods to identify
and critically appraise relevant research, and to collect, report, and analyse data from the
studies that are included in the review.
Theoretical Review:
The purpose of this form is to concretely examine the corpus of theory that has
accumulated in regard to an issue, concept, theory, phenomena. The theoretical literature
review help establish what theories already exist, the relationships between them, to what
degree the existing theories have been investigated, and to develop new hypotheses to be
tested.
Importance of Literature Review in Defining a Problem
The literature review is important because:
 It describes how the proposed research is related to prior research in statistics.
 It shows the originality and relevance of your research problem. Specifically, your
research is different from other statisticians.
 It justifies your proposed methodology.
What is a literature review and why is it necessary?
 Your dissertation is a substantial and lengthy piece of professional work that must
satisfy a number of academic requirements. The literature review is one of these
important academic requirements.
 The literature review is a critical discussion and summary of statistical literature that
is of „general‟ and „specialized‟ relevance to the particular area and topic of the
research problem in statistics.
 You should spend a lot of time on your literature review because if you do it well,
you can use most of it in your dissertation.
 In a weak literature review, the Ph.D. student did a poor job of reviewing the
relevant literature. It can be poor because there are too few references or the student
does not adequately summarize the important results in the cited references. Keeping
organized notes will help prevent a weak literature review.
Primary and Secondary Sources
A primary source is anything that gives you direct evidence about the people, events,
or phenomena that you are researching. Primary sources will usually be the main objects of
your analysis.

14. If you are researching something current, your primary sources can either be qualitative or
quantitative data that you collect yourself or sources produced by people directly involved in
the topic.
A secondary source is anything that describes, interprets, evaluates, or analyzes
information from primary sources. Common examples include:
 Books, articles and documentaries that synthesize information on a topic
 Synopses and descriptions of artistic works
 Encyclopaedias and textbooks that summarize information and ideas
 Reviews and essays that evaluate or interpret something

15. Treatise
A treatise is a compilation or summary of information on a subject. A treatise on a
subject provides enough information to a person to acquire basic knowledge, so essential for
carrying out advanced research. It also provides facts, along with discussion.
Monograph
A monograph is a special type of book written on a single specialized topic, devoted
mainly for research works; could pose some unsolved problems and may provide detained
explanation of some research papers. Unlike review papers, a research paper is a document
containing original results or findings.
Patents
A patent is protection granted by a national government for an invention. This
protection excludes others from making, using or selling an invention for a period of up to 20
years. Many drug companies and university researchers seek patent protection to recover
research and development costs for patents related to specific genes and proteins, laboratory

16. techniques and drugs. In order for patents to be issued by a granting agency such as a Patent
Office they need to be new, useful and not obvious to others working in the same field.
Types of Patents
1. Utlity patents - issued for any process, machine, article of manufacture, or
compositions of matters, or any new useful improvement. In general, this type of
patent protects the way an item is used or works. For example,Golf Club Head.
2. Design patents - issued for a new, original, and ornamental design for an article of
manufacture. In general, this type of patent protects the appearance of an item. For
example, Eyeglasses.
3. Plant patents - issued for asexually reproduced, distinct, and new variety of plants. For
example, Lavender plant named „Belpur‟.
Requirements for Patentability
1. Usefulness/Utility - The claimed invention must be useful/functional. A machine must
work according to its intended purpose and a chemical must exhibit an activity or
have some use.
2. Novelty -The invention must be different than anything known before; it must not
have been described in a prior publication and it must not have been publicly used or
sold.
3. Non-obviousness/Ingenuity -The invention must be a development or an improvement
that would not have been obvious beforehand to workers of average skill in the
technology involved.
Web as a Source
The web has been conceived of and created as an interconnected network of resources
and that is why we get the protocol „URL‟ as Uniform Resource Locator. So theoretically we
can make use of any resource available on the web for our research having an „identity‟.

17. Though web resources are found in unorganized forms, for our convenience we can divide
them into certain types:
Digital libraries: Digital libraries are being created as a full-fledged alternative to the
traditional physical library system for accessing a variety of materials (original texts, creative
works, movies, paintings, music albums etc) in various formats.
Online Archives: Just like digital libraries, archives are also being created online as an
alternative to traditional archives. However, an online archive may function just like a digital
library and the difference may be just in name.
Full text databases: A full-text database is a compilation of documents or other information
in the form of a database in which the complete text of each referenced document is available
for online viewing, printing, or downloading.
Independent scholarly sites: The publishing technology of the web has facilitated the rise of
many e-zines and e-journals.
Social networking sites: In the early days of social networking certain sites like Myspace,
Orkut, Facebook were avoided by scholars because of unscholarly nature of the contents
generated there.
Personal sites: Many authors and critics now maintain personal sites or blogs for
communication with readers or for advertising. A researcher can make use of those resources.
General websites: Depending upon the kind of research information available on general
websites can be used for the purpose of research.
Critical Literature Review
A literature review is a type of critical review in which you analyze and evaluate
many sources on a specific topic. The purpose is to provide your reader with an overview of
the research that has been done on your topic, and to evaluate the sources you are reviewing.
The main ideas or arguments in the book or article. Don‟t feel you have to mention
everything: part of being an effective evaluator is being able to extract the most important
ideas from a source.
1. Critically read each source, look for the arguments presented rather than for facts.
2. Take notes as you read and start to organiseyour review around themes and ideas.
3. Consider using a table, matrix or concept map to identifyhow the different sources
relate to each other.
4. In Journal article it evaluates the strengths andweaknesses of an article's ideas and
content.
5. Provides description, analysis and interpretation thatallow readers to assess the
article's value
Identifying gap areas from literature review

18. What is Gap in Literature?
A literature gap, or research gap, is an unexplored topic revealed during a literature
search that has scope for research or further exploration. To identify literature gaps, you need
to do a thorough review of existing literature in both the broad and specific areas of your
topic.
How do you identify gap
Conducting an exhaustive literature review is your first step. As you search for journal
articles, you will need to read critically across the breadth of the literature to identify these
gaps. You goal should be to find a „space‟ or opening for contributing new research. The first
step is gathering a broad range of research articles on your topic. You may want to look for
research that approaches the topic from a variety of methods – qualitative, quantitative, or
mixed methods.
Where you locate the gap
As you begin to gather the literature, you will want to critically read for what has, and
has not, been learned from the research. Use the Discussion and Future Research sections of
the articles to understand what the researchers have found and where they point out future or
additional research areas.
Why is it important to identify a unique research gap?
Assume that you have completed your research work and published the findings only
to find out that another researcher has already published something similar. How devastating
would that be! Therefore, it is necessary to find out those problems in your research field
which have not been addressed before. Not only would you be investing your funds and
resources in the right project but also increasing the chances of your research findings getting
published.
Challenges identifying research gaps
1. Effort of dealing with an enormous amount of information
There could be a lot of unanswered questions in an area of your interest. So you might
get overwhelmed with the number of research gaps you stumble upon and feel
confused about which one you should focus on.
2. Difficulty of searching in an organized manner
Some researchers may find it difficult to organize the information they have gathered.
One can easily lose ideas if they are not noted properly.
3. Hesitation in questioning established norms
Some researchers are not confident enough to challenge the existing knowledge in
their field and may hesitate to question what others have claimed in their work.

19. RESEARCH DESIGN
Essentials of Research Design, Need for Research Design, Classifications of Research
Design: causations and Experimental Design, Errors in Research Design, Types of
Research Errors.
The formidable problem that follows the task of defining the research problem is the
preparation ofthe design of the research project, popularly known as the “research design”.
Decisions regarding what, where, when, how much, by what means concerning an inquiry or
a research study constitute a 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.”
Need for research design
Research design is needed because it facilitates the smooth sailing of the various
research operations, thereby making research as efficient as possible yielding maximal
information with minimal expenditure of effort, time and money. Just as for better,
economical and attractive construction of a house, we need a blueprint (or what is commonly
called the map of the house) well thought out and prepared by an expert architect, similarly
we need a research design or a plan in advance of data collection and analysis for our
research project.
Even then the need for a well thought out research design is at times not realised by many.
The importance which this problem deserves is not given to it. As a result many researches
do not serve the purpose for which they are undertaken. In fact, they may even give
misleading conclusions. Thoughtlessness in designing the research project may result in
rendering the research exercise futile. It is, therefore, imperative that an efficient and
appropriate design must be prepared before starting research operations.
Features of a good design
A good design is often characterised by adjectives like flexible, appropriate, efficient,
and economical and so on. Generally, the design which minimises bias and maximises the
reliability of the datacollected and analysed is considered a good design. The design which
gives the smallest experimental error is supposed to be the best design in many
investigations. A design may be quite suitable in one case, but may be found wanting in one
respect or the other in the context of some other research problem. One single design cannot
serve the purpose of all types of research problems.
A research design appropriate for a particular research problem, usually involves the
considerationof the following factors:
o the means of obtaining information
o the availability and skills of the researcher and his staff, if any
o the objective of the problem to be studied
o the nature of the problem to be studied

20. o the availability of time and money for the research work
Concepts relating to Research Design
1. Dependent and independent variables:
A concept which can take on different quantitativevalues is called a variable. As such
the concepts like weight, height, income are all examples ofvariables. Qualitative phenomena
(or the attributes) are also quantified on the basis of the presence or absence of the concerning
attribute(s). Phenomena which can take on quantitatively differentvalues even in decimal
points are called „continuous variables‟. But all variables are not continuous.
If they can only be expressed in integer values, they are non-continuous variables or
in statistical language „discrete variables‟. Age is an example of continuous variable, but the
number of childrenis an example of non-continuous variable.
2. Extraneous variable:
Independent variables that are not related to the purpose of the study, but may affect
the dependent variable are termed as extraneous variables. Suppose the researcherwants to
test the hypothesis that there is a relationship between children‟s gains in social
studiesachievement and their self-concepts.
3. Control:
One important characteristic of a good research design is to minimise the influence or
effect of extraneous variable(s). The technical term „control‟ is used when we design the
study minimising the effects of extraneous independent variables. In experimental researches,
the term „control‟ is used to refer to restrain experimental conditions.
4. Confounded relationship:
When the dependent variable is not free from the influence of extraneous variable(s),
the relationship between the dependent and independent variables is said to be confounded by
an extraneous variable(s).
5. Research hypothesis:
When a prediction or a hypothesised relationship is to be tested by scientific methods,
it is termed as research hypothesis. The research hypothesis is a predictive statement that
relates an independent variable to a dependent variable. Usually a research hypothesis must
contain, at least, one independent and one dependent variable.
6. Experimental and non-experimental hypothesis-testing research:
When the purpose of research is to test a research hypothesis, it is termed as
hypothesis-testing research. It can be of the experimental design or of the non-experimental
design.

21. Research Design
Research design is the framework of research methods and techniques chosen by a
researcher. The design allows researchers to hone in on research methods that are suitable for
the subject matter and set up their studies up for success.
i) Research design in case of exploratory research studies
ii) Research design in case of descriptive and diagnostic research studies
iii) Research design in case of hypothesis-testing research studies.
Research design in case of exploratory research studies
Exploratory research is defined as the research used to investigate a problem that is
not clearly defined. It is being conducted in order to have a better understanding of the
existing problem, but it will not produce any conclusive results. For such research, a
researcher begins with a general idea and uses this research as a medium to identify issues
that may be the focus of future research. An important aspect here is that the researcher
should be willing to change his/her direction subject to the disclosure of new data or insight.
Such research is usually done when the problem is at a preliminary stage. It is often referred
to as grounded theoretical approach or interpretive research as it has been used to answer
questions such as what, why and how.
Examples
 A study into the role of social networking sites as an effective marketing
communication channel
 An investigation into the ways of improvement of quality of customer services
within hospitality sector in London
 An assessment of the role of corporate social responsibility on consumer
behaviour in pharmaceutical industry in the USA
Research design in case of descriptive research studies
Descriptive research definition: Descriptive research is defined as a research method
that describes the characteristics of the population or phenomenon studied. This methodology
focuses more on the “what” of the research subject than the “why” of the research subject.
The descriptive research method primarily focuses on describing the nature of a
demographic segment, without focusing on “why” a particular phenomenon occurs. In other
words, it “describes” the subject of the research, without covering “why” it happens.
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 exeunt. Because for the apparel brand

22. trying to break into this market, understanding the nature of their market is the study‟s
objective.
Research design in case of hypothesis-(Experimental) research studies:
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.
Basic Principals of Experimental Designs
Experimental design refers to the framework or structure of an experiment and as
such there areseveral experimental designs. We can classify experimental designs into two
broad categories, viz., informal experimental designs and formal experimental designs.
(a) Informal experimental designs:
(i) Before-and-after without control design.
(ii) After-only with control design.
(iii) Before-and-after with control design.
(b) Formal experimental designs:
(i) Completely randomized design (C.R. Design).
(ii) Randomized block design (R.B. Design).
(iii) Latin square design (L.S. Design).
(iv) Factorial designs.
1. Before-and-after without control design: In such a design a single test group or area
isselected and the dependent variable is measured before the introduction of the treatment.
The treatmentis then introduced and the dependent variable is measured again after the
treatment has beenintroduced
2.After-only with control design: In this design two groups or areas (test area and control
area)are selected and the treatment is introduced into the test area only. The dependent
variable is then measured in both the areas at the same time.

23. 3. Before-and-after with control design: In this design two areas are selected and the
dependent variable is measured in both the areas for an identical time-period before the
treatment. The treatment is then introduced into the test area only, and the dependent variable
is measured in both for an identical time-period after the introduction of the treatment.
4. Completely randomized design (C.R. design): Involves only two principles viz., the
principle of replication and the principle of randomization of experimental designs. It is the
simplest possible design and its procedure of analysis is also easier.
(i) Two-group simple randomized design: In a two-group simple randomized design, first
of all the population is defined and then from the population a sample is selected randomly.
Further, requirement of this design is that items, after being selected randomly from the
population, be randomly assigned to the experimental and control groups (Such random
assignment of items to two groups is technically described as principle of randomization).
(ii) Random replications design: The limitation of the two-group randomized design is
usually eliminated within the random replications design. In the illustration just cited above,
the teacher differences on the dependent variable were ignored, i.e., the extraneous variable
was not controlled. But in a random replications design, the effect of such differences are
minimised (or reduced) by providing a number of repetitions for each treatment.
5. Randomized block design (R.B. design) is an improvement over the C.R. design. In the
R.B. design the principle of local control can be applied along with the other two principles
of experimental designs. In the R.B. design, subjects are first divided into groups, known as
blocks, such that within each group the subjects are relatively homogeneous in respect to
some selected variable.
6. Latin square design (L.S. design) is an experimental design very frequently used in
agricultural research. The conditions under which agricultural investigations are carried out
are different from those in other studies for nature plays an important role in agriculture.
7. Factorial designs: Factorial designs are used in experiments where the effects of varying
more than one factor are to be determined. They are specially important in several economic
and social phenomena where usually a large number of factors affect a particular problem.

24. Factorial designs can be of two types: (i) simple factorial designs and (ii) complex factorial
designs. We take them separately
Errors in Research Design and Types of Errors in Research Design
At all stages, from problem formulation to report presentation– errors can arise. It is
rare that a research project will be error free. Errors in research design can be cause of
Research errors.Consequently the research designer must adopt a strategy for managing and
maintaining the error
Provide information that is to be accurate and error free as possible.
Total error has two distinct components:
Total Error = Sampling Error + Non Sampling Error
Total error is usually measured as total error variance also known as the mean squared
error:
(Total Error) = (Sampling Error ) + (Non Sampling Error )
Population Specification Error: It is defined as the “non correspondence of the required
population to the population selected by the investigator” It occurs when a researcher
selects an inappropriate population from which to obtain data. For example many times
package goods manufacturers conduct surveys amongst housewive- because they are easy
to contact and because it is assumed that as they are the end users they make the purchase
decisions.
Sampling Error: It is defined as the “non correspondence of sample selected by
when a probability sampling method is used to select a sample and this sample is not
people composed only of people between 35-50 years of age may not be representative of
adult population.
Selection Error: It is defined as the “Non correspondence of sample selected by non
natural tendency for the investigator to select those respondents who are most accessible
and agreeable. Such samples are often comprised of friends and associates who more or
less represent the desired population.
Frame Error: It is defined as the non-correspondence of the sought sample with the
required sample. I t is usually a listing of all the elements that identify a population. For
example a sampling frame that specifies the population as all adults using oral care
products – may well leave out people who prefer using neem and babool sticks,
homemade toothpaste and powders – leading to a frame error in defining the population.
Non Response Error: A nonresponse error occurs, when the obtained sample differs
-contact
errors : Arise due to the inability to reach the respondent.

25. Surrogate Information Error: This is defined as the non-correspondence of the
information being sought by the researcher and that is required to solve the problem.
Measurement Error: This may be defined as the non correspondence of information
obtained by measurement proces
errors can potentially arise at any stage of the measurement process – from the
development of the instrument till the analysis of findings.
Experimental Error: It can be defined as the non correspondence of the “ t rue impact
of” and the “impact attributed to” the independent variable. When an experiment is
conducted, the researcher attempts to measure the impact of one or more manipulated
independent variable on some dependent variable while controlling the impact of
exogenous variable.

26. DATA COLLECTION
Observation and Collection of data, Methods of data collection, Different types of variables,
Sampling Methods- Data Processing and Analysis strategies - Data Analysis with Statistical
Packages, Hypothesis-testing, Generalization and Interpretation
Implications of a sample design
A sample design is a definite plan for obtaining a sample from a given population. It
refers to the technique or the procedure the researcher would adopt in selecting items for the
sample. Sample design may as well lay down the number of items to be included in the
sample i.e., the size of the sample. Sample design is determined before data are collected.
There are many sample designs from which a researcher can choose.
Steps in sample design
While developing a sampling design, the researcher must pay attention to the
following points:
(i) Type of universe:
The first step in developing any sample design is to clearly define theset of objects,
technically called the Universe, to be studied. The universe can be finite orinfinite. In finite
universe the number of items is certain, but in case of an infinite universethe number of items
is infinite, i.e., we cannot have any idea about the total number ofitems.
(ii) Sampling unit:
A decision has to be taken concerning a sampling unit before selecting sample.
Sampling unit may be a geographical one such as state, district, village, etc., or a construction
unit such as house, flat, etc., or it may be a social unit such as family, club, school, etc.,
(iii) Source list:
It is also known as „sampling frame‟ from which sample is to be drawn. It contains
the names of all items of a universe (in case of finite universe only). If source list is not
available, researcher has to prepare it.
(iv) Size of sample:
This refers to the number of items to be selected from the universe to constitute a
sample. This a major problem before a researcher. The size of sample should neither be
excessively large, nor too small. It should be optimum. An optimum sample is one which
fulfills the requirements of efficiency, representativeness, reliability and flexibility
(v) Parameters of interest:

27. In determining the sample design, one must consider the question of the specific
population parameters which are of interest. For instance, we may be interested in estimating
the proportion of persons with some characteristic in the population.
Criteria of selecting a sampling procedure
In this context one must remember that two costs are involved in a sampling analysis
viz., the cost of collecting the data and the cost of an incorrect inference resulting from the
data. Researcher must keep in view the two causes of incorrect inferences viz., systematic
bias and sampling error.
1.Inappropriate sampling frame:
If the sampling frame is inappropriate i.e., a biased representation of the universe, it
will result in a systematic bias.
2.Defective measuring device:
If the measuring device is constantly in error, it will result in systematic bias. In
survey work, systematic bias can result if the questionnaire or the interviewer is biased.
Similarly, if the physical measuring device is defective there will be systematic bias in the
data collected through such a measuring device.
3.Non-respondents:
If we are unable to sample all the individuals initially included in the sample, there
may arise a systematic bias. The reason is that in such a situation the likelihood of
establishing contact or receiving a response from an individual is often correlated with the
measure of what is to be estimated.
4.Indeterminancy principle:
Sometimes we find that individuals act differently when kept under observation than
what they do when kept in non-observed situations. For instance, if workers are aware that
somebody is observing them in course of a work study on the basis of which the average
length of time to complete a task will be determined and accordingly the quota will be set for
piece work, they generally tend to work slowly in comparison to the speed with which they
work if kept unobserved. Thus, the indeterminancy principle may also be a cause of a
systematic bias.
5.Natural bias in the reporting of data:
Natural bias of respondents in the reporting of data is often the cause of a systematic
bias in many inquiries. There is usually a downward bias in the income data collected by
government taxation department, whereas we find an upward bias in the income data
collected by some social organisation.
Characteristics of a good sample design

28. From what has been stated above, we can list down the characteristics of a good
sample design as under:
(a) Sample design must result in a truly representative sample.
(b) Sample design must be such which results in a small sampling error.
(c) Sample design must be viable in the context of funds available for the research
study.
(d) Sample design must be such so that systematic bias can be controlled in a better
way.
(e) Sample should be such that the results of the sample study can be applied, in
general, for
the universe with a reasonable level of confidence.
Different types of sample methods
There are different types of sample designs based on two factors, the representation
basis and the element selection technique. On the representation basis, the sample may be
probability sampling or it may be non-probability sampling. Probability sampling is based on
the concept of random selection, whereas non-probability sampling is „non-random‟
sampling.
Non-probability sampling:
Non-probability sampling is that sampling procedure which does not afford any basis
for estimating the probability that each item in the population has of being included in the
sample. Non-probability sampling is also known by different names such as deliberate
sampling, purposive sampling and judgement sampling. In this type of sampling, items for
the sample are selected deliberately by the researcher; his choice concerning the items
remains supreme.
In other words, under non-probability sampling the organisers of the inquiry
purposively choose the particular units of the universe for constituting a sample on the basis
that the small mass that they so select out of a huge one will be typical or representative of
the whole.
For instance, if economic conditions of people living in a state are to be studied, a few
towns and villages may be purposively selected for intensive study on the principle that they
can be representative of the entire state. Thus, the judgement of the organisers of the study
plays an important part in this sampling design.
Probability sampling:
Probability sampling is also known as „random sampling‟ or „chance sampling‟.
Under this sampling design, every item of the universe has an equal chance of inclusion in
the sample. It is, so to say, a lottery method in which individual units are picked up from the
whole group not deliberately but by some mechanical process. Here it is blind chance alone
that determines whether one item or the other is selected.

29. The results obtained from probability or random sampling can be assured in terms of
probability i.e., we can measure the errors of estimation or the significance of results obtained
from a random sample, and this fact brings out the superiority of random sampling design
over the deliberate sampling design. Random sampling ensures the law of Statistical
Regularity which states that if on an average the sample chosen is a random one, the sample
will have the same composition and characteristics as the universe. This is the reason why
random sampling is considered as the best technique of selecting a representative sample.
How to select a random sample
With regard to the question of how to take a random sample in actual practice, we
could, in simple cases like the one above, write each of the possible samples on a slip of
paper, mix these slips thoroughly in a container and then draw as a lottery either blindfolded
or by rotating a drum or by any other similar device. Such a procedure is obviously
impractical, if not altogether impossible in complex problems of sampling. In fact, the
practical utility of such a method is very much limited.
Random sample from an infinite universe
So far we have talked about random sampling, keeping in view only the finite
populations. But what about random sampling in context of infinite populations? It is
relatively difficult to explain the concept of random sample from an infinite population.
However, a few examples will show the basic characteristic of such a sample. Suppose we
consider the 20 throws of a fair dice as a sample from the hypothetically infinite population
which consists of the results of all possible throws of the dice.
Complex random sampling designs
Probability sampling under restricted sampling techniques, as stated above, may result
in complex random sampling designs.
(i) Systematic sampling:
In some instances, the most practical way of sampling is to select every ith item on a
list. Sampling of this type is known as systematic sampling. An element of randomness is
introduced into this kind of sampling by using random numbers to pick up the unit with
which to start.
(ii)Stratified sampling:
If a population from which a sample is to be drawn does not constitute a
homogeneous group, stratified sampling technique is generally applied in order to obtain a
representative sample.
(iii)Cluster sampling:
If the total area of interest happens to be a big one, a convenient way in which a
sample can be taken is to divide the area into a number of smaller non-overlapping areas and

30. then to randomly select a number of these smaller areas (usually called clusters), with the
ultimate sample consisting of all (or samples of) units in these small areas or clusters.
(iv)Area sampling:
If clusters happen to be some geographic subdivisions, in that case cluster sampling is
better known as area sampling. In other words, cluster designs, where the primary sampling
unit represents a cluster of units based on geographic area, are distinguished as area sampling.
The plus and minus points of cluster sampling are also applicable to area sampling.
(v)Multi-stage sampling:
Multi-stage sampling is a further development of the principle of cluster sampling.
Suppose we want to investigate the working efficiency of nationalised banks in India and we
want to take a sample of few banks for this purpose.
(vi)Sampling with probability proportional to size:
In case the cluster sampling units do not have the same number or approximately the
same number of elements, it is considered appropriate to use a random selection process
where the probability of each cluster being included in the sample is proportional to the size
of the cluster.
(vii)Sequential sampling:
This sampling design is some what complex sample design. The ultimate size of the
sample under this technique is not fixed in advance, but is determined according to
mathematical decision rules on the basis of information yielded as survey progresses.
Methods of Data Collections
Primary Data Collecting Method
We collect primary data during the course of doing experiments in an experimental
research but in case we do research of the descriptive type and perform surveys, whether
sample surveys or census surveys, then we can obtain primary data either through observation
or through direct communication with respondents in one form or another or through personal
interviews.

31. There are several methods of collecting primary data, particularly in surveys and
descriptive researches. Important ones are: (i) observation method, (ii) interview method, (iii)
through questionnaires, (iv) through schedules, and (v) other methods which include (a)
warranty cards; (b) distributor audits; (c) pantry audits; (d) consumer panels; (e) using
mechanical devices; (f) through projective techniques; (g) depth interviews, and (h) content
analysis. We briefly take up each method separately.
Observation Method
The observation method is the most commonly used method specially in studies
relating to behavioural sciences. In a way we all observe things around us, but this sort of
observation is not scientific observation. Observation becomes a scientific tool and the
method of data collection for the researcher when it serves a formulated research purpose, is
systematically planned and recorded and is subjected to checks and controls on validity and
reliability. Under the observation method, the information is sought by way of investigator‟s
own direct observation without asking from the respondent.
Interview Method-Personal and Phone Interview
The interview method of collecting data involves presentation of oral-verbal stimuli and reply
in terms of oral-verbal responses. This method can be used through personal interviews and,
if possible, through telephone interviews.
Collection of data through questionnaires
This method of data collection is quite popular, particularly in case of big enquiries. It is
being adopted by private individuals, research workers, private and public organisations and
even by governments. In this method a questionnaire is sent (usually by post) to the persons
concerned with a request to answer the questions and return the questionnaire. A
questionnaire consists of a number of questions printed or typed in a definite order on a form
or set of forms.
Collection of data through schedules
This method of data collection is very much like the collection of data through questionnaire,
with little difference which lies in the fact that schedules (proforma containing a set of
questions) are being filled in by the enumerators who are specially appointed for the purpose.

32. These enumerators along with schedules, go to respondents, put to them the questions from
the proforma in the order the questions are listed and record the replies in the space meant for
the same in the proforma.
Some other methods of data collection
Let us consider some other methods of data collection, particularly used by big business
houses in modern times.
1.Warranty cards:
Warranty cards are usually postal sized cards which are used by dealers of consumer
durables to collect information regarding their products. The information sought is printed in
the form of questions on the „warranty cards‟ which is placed inside the package along with
the product with a request to the consumer to fill in the card and post it back to the dealer.
2.Distributor or store audits:
Distributor or store audits are performed by distributors as well as manufactures
through their salesmen at regular intervals. Distributors get the retail stores audited through
salesmen and use such information to estimate market size, market share, seasonal purchasing
pattern and so on.
4.Consumer panels:
An extension of the pantry audit approach on a regular basis is known as „consumer
panel‟, where a set of consumers are arranged to come to an understanding to maintain
detailed daily records of their consumption and the same is made available to investigator on
demands.
5.Use of mechanical devices:
The use of mechanical devices has been widely made to collect information by way of
indirect means.
7.Depth interviews:
Depth interviews are those interviews that are designed to discover underlying
motives and desires and are often used in motivational research. Such interviews are held to
explore needs, desires and feelings of respondents.
8. Content-analysis:
Content-analysis consists of analysing the contents of documentary materials such as
books, magazines, newspapers and the contents of all other verbal materials which can be
either spoken or printed.
Collection of secondary data
Secondary data means data that are already available i.e., they refer to the data which
have already been collected and analysed by someone else. When the researcher utilises
secondary data, then he has to look into various sources from where he can obtain them. In

33. this case he is certainly not confronted with the problems that are usually associated with the
collection of original data. Secondary data may either be published data or unpublished data.
Usually published data are available in:
(a) various publications of the central, state are local governments;
(b) various publications of foreign governments or of international bodies and their
subsidiary organisations;
(c) technical and trade journals;
(d) books, magazines and newspapers;
(e) reports and publications of various associationsconnected with business and
industry, banks, stock exchanges, etc.;
(f) reports prepared by research scholars, universities, economists, etc. in different
fields; and
(g) public records and statistics, historicaldocuments, and other sources of published
information.
Selection of appropriate method for data collection
Thus, there are various methods of data collection. As such the researcher must
judiciously select the method/methods for his own study, keeping in view the following
factors:
1. Nature, scope and object of enquiry:
This constitutes the most important factor affecting the choice of a particular method.
The method selected should be such that it suits the type of enquiry that is to be conducted by
the researcher. This factor is also important in deciding whether the data already available
(secondary data) are to be used or the data not yet available (primary data) are to be collected.
2. Availability of funds:
Availability of funds for the research project determines to a large extent the method
to be used for the collection of data. When funds at the disposal of the researcher are very
limited, he will have to select a comparatively cheaper method which may not be as efficient
and effective as some other costly method. Finance, in fact, is a big constraint in practice and
the researcher has to act within this limitation.
3. Time factor:
Availability of time has also to be taken into account in deciding a particular method
of data collection. Some methods take relatively more time, whereas with others the data can
be collected in a comparatively shorter duration. The time at the disposal of the researcher,
thus, affects the selection of the method by which the data are to be collected.
4. Precision required:

34. Precision required is yet another important factor to be considered at the time of
selecting the method of collection of data.
Different Types of Variables
A variable is a characteristic or feature that varies, or changes within a study. The
opposite of variable is constant: something that doesn't change. In math, the symbols "x" , "y"
or "b" represent variables in an equation, while "pi" is a constant. In an experimental
example, if a study is investigating the differences between males and females, gender would
be a variable (some subjects in the study would be men, and others would be women). If a
study has only female subjects, gender would not be a variable, since there would be only
women. If a study includes both males and females as subjects, but is not interested in
differences between men and women - and does not compare them, gender would not be a
variable in that study.
Example
If a study compares three different diets, but keeps all 3 diets the same in the amount
of sodium, then sodium isn't a variable in that study - it's a constant. Other features of the
diets would be variables of interest - maybe the calories or carbohydrates or fat content.
Dependent variables
The outcome variable measured in each subject, which may be influenced by
manipulation of the independent variable is termed the dependent variable. In experimental
studies, where the independent variables are imposed and manipulated, the dependent
variable is the variable thought to be changed or influenced by the independent variable.
Example: study title: Effects of a new tooth paste (YummyTooth) on incidence of
caries in 1st grade children. The intervention group was given YummyTooth toothpaste,
while the control group was given an identical toothpaste that did not contain the secret
ingredient in YummyTooth. Subjects were observed brushing their teeth 3x per day with the
assigned toothpaste (by teacher or parent). 6 months later, dental appointments were
scheduled, and the number of dental caries present in each child was reported.
Independent variables
In experimental research, an investigator manipulates one variable and measures the
effect of that manipulation on another variable. The variable that the researcher manipulates
is called the independent, or grouping variable. The independent variable is the variable that
is different between the groups compared: all the members of one group will have the
same level of the independent variable, a second group will have a different level of that
same variable, and the same for a 3rd or 4th group, if present.
For example, let's take a study in which the investigators want to determine how often
an exercise must be done to increase strength. Stop for a minute and think about how they

35. might organize a study so they could figure this out. There are usually several possible
studies that could be done to address a question.
These investigators decided to compare 3 groups, one group participate in a set of specific
exercises 4 times per week; a second group would do the same exercises, but only twice per
week, and a control group would participate in stretching exercises that would have no
impact on strength. The variable that differs between these 3 groups that are compared is
an Independent Variable. This particular independent variable has 3 levels of the single
independent variable - in this example: type of exercise.
Intervening variables
Refer to abstract processes that are not directly observable but that link the
independent and dependent variables. In language learning and teaching, they are usually
inside the subjects' heads, including various language learning processes which the
researcher cannot observe. For example, if the use of a particular teaching technique is the
independent variable and mastery of the objectives is the dependent variable, then the
language learning processes used by the subjects are the intervening variables.
Moderator variables
Affect the relationship between the independent and dependent variables by modifying
the effect of the intervening variable(s). Unlike extraneous variables, moderator variables
are measured and taken into consideration. Typical moderator variables in TESL and
language acquisition research (when they are not the major focus of the study) include the
sex, age, culture, or language proficiency of the subjects.
Control variables
Language learning and teaching are very complex processes. It is not possible to
consider every variable in a single study. Therefore, the variables that are not measured in a
particular study must be held constant, neutralized/balanced, or eliminated, so they will not
have a biasing effect on the other variables. Variables that have been controlled in this way
are called control variables.
Extraneous variables
In the best circumstances, the only consistent feature that differs between the
intervention and control groups is the intervention level itself. The groups that are compared
should be similar in every other way, and only differ in the independent variable level. In the
YummyTooth toothpaste example above, this would mean that the groups receiving the two
types of toothpaste should be similar. If children with a history of many more caries were
systematically put into the control group, this would introduce bias. When the two groups
start out the same (have the same incidence of prior caries), then introduce a single
intervention difference, any difference in later number of caries reflects only the influence of
the intervention. If there are other differences between the two groups of children, such as a

36. bias that put children with more caries in the control group, then we can no longer have that
confidence. In this situation, even if the YummyTooth group of children have significantly
fewer caries, we won't be able to tell whether it was the toothpaste, or the history of caries, or
some combination, that caused the different number of caries between the groups. These
biasing variables are called confounding or extraneous variables.
The confounding variables are differences between groups other than the independent
variables. That means that most members of a group are alike on a variable, but different
from the other group, e.g., if the control group was mostly smokers and the experimental
group mostly non-smokers. These variables interfere with assessment of the effects of the
independent variable because they, in addition to the independent variable, potentially affect
the dependent variable. Since they cannot be separated from the independent variable, they
are said to be confounding variables.
Data Analysis with Statistical Package
As stated earlier, by analysis we mean the computation of certain indices or measures
along with searching for patterns of relationship that exist among the data groups. Analysis,
particularly in case of survey or experimental data, involves estimating the values of
unknown parameters of the population and testing of hypotheses for drawing inferences.
We may as well talk of correlation analysis and causal analysis. Correlation analysis
studies
the joint variation of two or more variables for determining the amount of correlation
between two ormore variables.
In modern times, with the availability of computer facilities, there has been a rapid
development of multivariate analysis which may be defined as “all statistical methods which
simultaneously analyse more than two variables on a sample of observations”. Usually the
following analyses are involved when we make a reference of multivariate analysis:
(a) Multiple regression analysis:
This analysis is adopted when the researcher has one dependent variable which is
presumed to be a function of two or more independent variables. The objective of this
analysis is to make a prediction about the dependent variable based on its covariance with all
the concerned independent variables.
(b) Multiple discriminant analysis:
This analysis is appropriate when the researcher has a single dependent variable that
cannot be measured, but can be classified into two or more groups on the basis of some
attribute. The object of this analysis happens to be to predict an entity‟s possibility of
belonging to a particular group based on several predictor variables.
(c) Multivariate analysis of variance (or multi-ANOVA):

37. This analysis is an extension of twoway ANOVA, wherein the ratio of among group
variance to within group variance is worked out on a set of variables.
(d) Canonical analysis:
This analysis can be used in case of both measurable and non-measurable variables
for the purpose of simultaneously predicting a set of dependent variables from their joint
covariance with a set of independent variables
Statistical Analysis
The role of statistics in research is to function as a tool in designing research,
analysing its data and drawing conclusions therefrom. Most research studies result in a large
volume of raw data which must be suitably reduced so that the same can be read easily and
can be used for further analysis. Clearly the science of statistics cannot be ignored by any
research worker, even though he may not have occasion to use statistical methods in all their
details and ramifications.
The important statistical measures that are used to summarise the survey/research data
are:(1) Measures of central tendency or statistical averages; (2) measures of dispersion; (3)
measuresof asymmetry (skewness); (4) measures of relationship; and (5) other measures.
Hypothesis Testing
hypothesis may be defined as a proposition or a set of proposition 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 or accepted as highly probable in the
light of established facts.
Characteristics of hypothesis:
(i) Hypothesis should be clear and precise. If the hypothesis is not clear and precise,
theinferences drawn on its basis cannot be taken as reliable.
(ii) Hypothesis should be capable of being tested. In a swamp of untestable
hypotheses, manya time the research programmes have bogged down. Some prior
study may be done byresearcher in order to make hypothesis a testable one. A
hypothesis “is testable if otherdeductions can be made from it which, in turn, can be
confirmed or disproved by observation.”
(iii) Hypothesis should state relationship between variables, if it happens to be a
relational hypothesis.
(iv) Hypothesis should be limited in scope and must be specific. A researcher must
remember that narrower hypotheses are generally more testable and he should
develop such hypotheses.

38. (v) Hypothesis should be stated as far as possible in most simple terms so that the
same is easily understandable by all concerned. But one must remember that
simplicity of hypothesishas nothing to do with its significance.
Basic concepts concerning testing of hypotheses
(a) Null hypothesis and alternative hypothesis: In the context of statistical analysis,
we often talk about null hypothesis and alternative hypothesis. If we are to compare
method A with method B about its superiority and if we proceed on the assumption
that both methods are equally good, then this assumption is termed as the null
hypothesis. The null hypothesis is generally symbolized as H0 and the alternative
hypothesis as Ha
(b) The level of significance: This is a very important concept in the context of
hypothesis testing.
It is always some percentage (usually 5%) which should be chosen which great care, thought
and reason.
Hypothesis Testing Procedure
i) Making a formal statement: The step consists in making a formal statement of the null
hypothesis (H0) and also of the alternative hypothesis (Ha). This means that hypotheses
should be clearly stated, considering the nature of the research problem.

39. (ii) Selecting a significance level: The hypotheses are tested on a pre-determined level of
significance and as such the same should be specified. Generally, in practice, either 5% level
or 1% level is adopted for the purpose.
(iii) Deciding the distribution to use: After deciding the level of significance, the next step
in hypothesis testing is to determine the appropriate sampling distribution. The choice
generally remains between normal distribution and the t-distribution.
(iv) Selecting a random sample and computing an appropriate value: Another step is to
select a random sample(s) and compute an appropriate value from the sample data concerning
the test statistic utilizing the relevant distribution.
v) Calculation of the probability: One has then to calculate the probability that the sample
result would diverge as widely as it has from expectations, if the null hypothesis were in fact
true.
(vi) Comparing the probability:
Generalization and Interpretation
Interpretation refers to the task of drawing inferences from the collected facts after an
analytical and/or experimental study. In fact, it is a search for broader meaning of research
findings. The task of interpretation has two major aspects viz., (i) the effort to establish
continuity in research through linking the results of a given study with those of another, and
(ii) the establishment of some explanatory concepts.

40. Why interpretation?
Interpretation is essential for the simple reason that the usefulness and utility of research
findings lie in proper interpretation. It is being considered a basic component of research
process because of the following reasons:
(i) It is through interpretation that the researcher can well understand the abstract
principle that works beneath his findings.
(ii) Interpretation leads to the establishment of explanatory concepts that can serve as
a guide for future research studies; it opens new avenues of intellectual adventure and
stimulates the quest for more knowledge.
(iii) Researcher can better appreciate only through interpretation why his findings are
what they are and can make others to understand the real significance of his research
findings.
Technique of interpretation
The task of interpretation is not an easy job, rather it requires a great skill and dexterity on the
part of researcher. Interpretation is an art that one learns through practice and experience.
(i) Researcher must give reasonable explanations of the relations which he has found
and he must interpret the lines of relationship in terms of the underlying processes and must
try to find out the thread of uniformity that lies under the surface layer of his diversified
research findings.
(ii) Extraneous information, if collected during the study, must be considered while
interpreting the final results of research study, for it may prove to be a key factor in
understanding the problem under consideration.
(iii) It is advisable, before embarking upon final interpretation, to consult someone
having insight into the study and who is frank and honest and will not hesitate to point out
omissions and errors in logical argumentation.
(iv) Researcher must accomplish the task of interpretation only after considering all
relevant factors affecting the problem to avoid false generalization.
Quantitative Methods ( Remain Topics in PPT)
Probability Distributions, Fundamentals of Statistical Analysis and Inference,
Multivariate methods, Concepts of Correlation and Regression, Fundamentals of Time Series
Analysis and Spectral Analysis
Multivariate methods
Multivariate analysis in a broad sense is the set of statistical methods aimed
simultaneously analyze datasets. That is, for each individual or object being studied, analyzed
several variables. The essence of multivariate thinking is to expose the inherent structure and

41. meaning revealed within these sets if variables through application and interpretation of
various statistical methods.
There are two determining factors that have to take into account when doing a
multivariate approach (1): (I) the multidimensional nature of the data matrix and (II) the
purpose of trying it, preserving its complex structure.
I-According to the methods of dependency:
Analyzed variables are divided into two groups: dependent and independent variables.
The aim is to determine whether the set of independent variables affects all dependent
variables and how. They develop a hypothesis that attempts to validate empirically are
explanatory or predictive techniques.
II-According to the methods of interdependence:
It is based in to do a reality approach without specific hypotheses and try to describe
reality by synthesizing the relevant information; they are descriptive or reductive techniques.
They can be classified into two groups based on whether the data analyzed are metric or non-
metric.

42. OPTIMIZATION
Introduction to evolutionary algorithms - Fundamentals of Genetic algorithms, Particle
Swarm Optimization, Simulated Annealing, Introduction to Neural Networks, Neural
Network based optimization, Introduction to Fuzzy sets and Fuzzy Logic, Optimization of
fuzzy logic
Simulated Annealing
Simulated annealing (SA) is a probabilistic technique for approximating the global optimum
of a given function. Specifically, it is a metaheuristic to approximate global optimization in a
large search space for an optimization problem.

43. Ethics
Ethical issues - Copy right - Intellectual property rights and patent law - Reproduction
of published material - Plagiarism - Citation and acknowledgement - Reproducibility
and accountability
Ethical issues
When most people think of research ethics, they think about issues that arise when
research involves human or animal subjects.
Honesty and Integrity
This means that you need to report your research honestly, and that this applies to
your methods (what you did), your data, your results, and whether you have previously
published any of it.
Objectivity
You should aim to avoid bias in any aspect of your research, including design, data
analysis, interpretation, and peer review. For example, you should never recommend as a
peer reviewer someone you know, or who you have worked with, and you should try to
ensure that no groups are inadvertently excluded from your research. This also means that
you need to disclose any personal or financial interests that may affect your research.
Carefulness

44. Take care in carrying out your research to avoid careless mistakes. You should also
review your work carefully and critically to ensure that your results are credible. It is also
important to keep full records of your research. If you are asked to act as a peer reviewer, you
should take the time to do the job effectively and fully.
Openness
You should always be prepared to share your data and results, along with any new
tools that you have developed, when you publish your findings, as this helps to further
knowledge and advance science. You should also be open to criticism and new ideas.
Respect for Intellectual Property
You should never plagiarise, or copy, other people‟s work and try to pass it off as
your own. You should always ask for permission before using other people‟s tools or
methods, unpublished data or results. Not doing so is plagiarism. Obviously, you need to
respect copyrights and patents, together with other forms of intellectual property, and always
acknowledge contributions to your research. If in doubt, acknowledge, to avoid any risk of
plagiarism.
Confidentiality
You should respect anything that has been provided in confidence. You should also
follow guidelines on protection of sensitive information such as patient records.
Responsible Publication
You should publish to advance to state of research and knowledge, and not just to
advance your career. This means, in essence, that you should not publish anything that is not
new, or that duplicates someone else‟s work.
Legality
You should always be aware of laws and regulations that govern your work, and be
sure that you conform to them.
Copy Right
Copyright is a branch of Intellectual Property Rights and an exclusive legal right
given by the judiciary to the creator on his creation. ... On the other hand law permits libraries
to use copyrighted material for research and academic purpose without any permission from
the copyright holder.

45. Copyright is an exclusive legal right given to the creator or a group of individuals to
protect their work or creativity from reproduction, adaption, translation, distribution and
public performance by others without prior permission from the creator/person responsible
for the existence of the work.
Term of Copyright protection: Normally current copyright doesn‟t require any kind of
registration for its protection. Once the work created in tangible form, an author
automatically gets the copyright on his creation. The term of the copyright protection on
different works has described in section 22-29 of chapter V of Indian copyright act.
Infringement of Copyright: Violation of a copyright law by any person without a
license or permission by the owner of the creation is called as infringement of copyright.
Copyright law provides exclusive legal rights to an author to get all kind of benefits on his
creation.

46. patent law
Patent law is the branch of intellectual property law that deals with new inventions.
Traditional patents protect tangible scientific inventions, such as circuit boards, car engines,
heating coils, or zippers.

47. Reproduction of published material
When your thesis is deposited in Spiral and made available to the public, legally it
will be viewed as published and you must get permission to reproduce any extracts, images,
figures, etc. for which you do not own the copyright (you can use works which are out of
copyright without permission).
Permissionsforreproducingpublishedmaterialinyourarticle

48. If your article makes use of any previously published material (including
figures/diagrams, or short extracts, or content taken from websites) then you must first obtain
the written permission of the copyright owner. The copyright owner is usually the publisher
(for material taken from journal or proceedings articles), website owner/company (for
material taken from websites) or the author or their employer (if the work is unpublished).
Some publishers will also require that you seek the permission of the original author (you
will need to check the terms of the publisher‟s permission).
Pilgrims:
Citation and acknowledgement
A citation is both a signpost and an acknowledgement. As an acknowledgement, it
reveals that you are indebted to that source. A citation can appear in different formats: within
the text (in-text citation) at the bottom of the page (footnotes), or at the end of the paper
(endnotes).
A citation is both a signpost and an acknowledgement. As a signpost, it signals the
location of your source. As an acknowledgement, it reveals that you are indebted to that source.
A citation can appear in different formats: within the text (in-text citation) at the bottom
of the page (footnotes ), or at the end of the paper (endnotes). Different disciplines use different
formats. The mechanics of citing are complicated, and vary in each format. To answer specific
questions on the mechanics of citation, please consult sources describing each type.
You may find it most useful to think about how citations function as a way for you as a
writer to communicate with your reader. By using citations, you keep the reader always
apprised of whose idea or words you are using at any given time in each sentence and in each
paragraph.
Citation is important because it is the basis of academics, that is, the pursuit of
knowledge. In the academic endeavor, individuals look at evidence and reason about that
evidence in their own individual ways. That is, taking what is already known, established, or
thought, they use their reasoning power to create new knowledge.
Reproducibility and accountability

50. Types of Intellectual property rights
When a business or an individual has an idea that they want to protect from being used by
others without their permission, it is best to seek legal protection of that intellectual property.
There are four types of intellectual property rights and protections (although multiple types of
intellectual property itself). Securing the correct protection for your property is important,
which is why consulting with a lawyer is a must. The four categories of intellectual property
protections include:
Trade Secrets
Trade secrets refer to specific, private information that is important to a business because it
gives the business a competitive advantage in its marketplace. If a trade secret is acquired by
another company, it could harm the original holder.
Patents
As defined by the U.S. Patent and Trademark Office (USPTO), a patent is a type of limited-
duration protection that can be used to protect inventions (or discoveries) that are new, non-
obvious, and useful, such a new process, machine, article of manufacture, or composition of
matter.
Copyrights
Copyrights and patents are not the same things, although they are often confused. A copyright
is a type of intellectual property protection that protects original works of authorship, which
might include literary works, music, art, and more. Today, copyrights also protect computer
software and architecture.
Trademarks
Finally, the fourth type of intellectual property protection is a trademark protection.
Remember, patents are used to protect inventions and discoveries and copyrights are used to
protect expressions of ideas and creations, like art and writing.

51. RESEARCH REPORT WRITING & LATEX
Structure and Components of Research Report, Types of Report, Layout of Research Report,
Mechanism of writing a research report, Latex Commands, Latex Styles Files, Presentations
in Latex, Report writing on Latex
Significance of report writing
Research report is considered a major component of the research study for the
research task remains incomplete till the report has been presented and/or written. As a matter
of fact even the most brilliant hypothesis, highly well designed and conducted research study,
and the most striking generalizations and findings are of little value unless they are
effectively communicated to others.
Writing of report is the last step in a research study and requires a set of skills
somewhat different from those called for in respect of the earlier stages of research.
This task should be accomplished by the researcher with utmost care; he may seek the
assistance and guidance of experts for the purpose
Different steps in writing report
Research reports are the product of slow, painstaking, accurate inductive work. The
usual steps involved in writing report are: (a) logical analysis of the subject-matter; (b)
preparation of the final outline; (c) preparation of the rough draft; (d) rewriting and polishing;
(c) preparation of the final bibliography; and (f) writing the final draft. Though all these steps
are self-explanatory, yet a brief mention of each one of these will be appropriate for better
understanding.
Logical analysis of the subject matter:
It is the first step which is primarily concerned with the development of a subject.
There are two ways in which to develop a subject (a) logically and (b) chronologically.
Preparation of the final outline:
It is the next step in writing the research report “Outlines are the framework upon
which long written works are constructed. They are an aid to the logical organisation of the
material and a reminder of the points to be stressed in the report.”
Preparation of the rough draft:
This follows the logical analysis of the subject and the preparation of the final outline.
Rewriting and polishing of the rough draft:
This step happens to be most difficult part of all formal writing. Usually this step
requires more time than the writing of the rough draft. The careful revision makes the

52. difference between a mediocre and a good piece of writing. While rewriting and polishing,
one should check the report for weaknesses in logical development or presentation.
Preparation of the final bibliography:
Next in order comes the task of the preparation of the final bibliography. The
bibliography, which is generally appended to the research report, is a list of books in some
way pertinent to the research which has been done.
Layout of the research report
Anybody, who is reading the research report, must necessarily be conveyed enough
about the study so that he can place it in its general scientific context, judge the adequacy of
its methods and thus form an opinion of how seriously the findings are to be taken. For this
purpose there is the need of proper layout of the report. The layout of the report means as to
what the research report should contain. A comprehensive layout of the research report
should comprise (A) preliminary pages; (B) the main text; and (C) the end matter. Let us deal
with them separately.
(A) Preliminary Pages
In its preliminary pages the report should carry a title and date, followed by
acknowledgements in the form of „Preface‟ or „Foreword‟. Then there should be a table of
contents followed by list of tables and illustrations so that the decision-maker or anybody
interested in reading the report can easily locate the required information in the report.
(B) Main Text
The main text provides the complete outline of the research report along with all details. Title
of the research study is repeated at the top of the first page of the main text and then follows
the other details on pages numbered consecutively, beginning with the second page. Each
main section of the report should begin on a new page. The main text of the report should
have the following sections:
(i) Introduction; (ii) Statement of findings and recommendations; (iii) The results; (iv) The
implications drawn from the results; and (v) The summary.
(C) End Matter
At the end of the report, appendices should be enlisted in respect of all technical data such as
questionnaires, sample information, mathematical derivations and the like ones. Bibliography
of sources consulted should also be given.
Types of reports
Research reports vary greatly in length and type. In each individual case, both the length and
the form are largely dictated by the problems at hand. For instance, business firms prefer
reports in the letter form, just one or two pages in length.