PROBLEMS IN RESEARCH
1
• Not similar to science
• Uncontrollable variables
• Human tendencies
• Time and money
• Lack of computerization

RESEARCH APPROACHES
There are two basic approaches to
research
• Quantitative approach
• Qualitative approach
Research
Approaches
Quantitative
Approach
Inferential
approach
Experimental
approach
Simulation
approach
Qualitative
Approach
2

1.10 RESEARCH PROCESS
3
• Research process consists of series of actions
or steps necessary to effectively carry out
research and the desired sequencing of these
steps.
• The chart shown in Figure well illustrates a
research process.
• The chart indicates that the research process
consists of a number of closely related
activities, as shown through I to VII.
• However, the following order concerning
various steps provides a useful procedural

4

) Establishment of research objectives
• Research Objectives are the specific components
of the research problem, which you’ll be working to
answer or complete, in order to answer the overall
research problem. - Churchill,
2001
• The objectives refer to the questions to be
answered through the study. They indicate what
we are trying to get from the study or the
expected results / outcome of the study.

• Research Objectives should be clear and
achievable, as they directly assist in answering the
research problem.
• The objectives may be specified in the form of
either statements or questions.
• Generally, they are written as statements, using
the word “to”. (For example, ‘to discover …’, ‘to
determine …’, ‘to establish …’, etc. )

LITERATURE REVIEW
7
• Literature Review is the documentation of a
comprehensive review of the published and unpublished
work from secondary sources of data in the areas of
specific interest to the researcher.
• The main aim is to find out problems that are already
investigated and those that need further investigation.
• It is an extensive survey of all available past studies
relevant to the field of
investigation.
• It gives us knowledge about what others have found
out in the related field of study and how they have
done so.

a) Purpose of review
• To gain a background knowledge of the research
topic.
• To identify the concepts relating to it, potential
relationships between them and to formulate
researchable hypothesis.
• To identify appropriate methodology, research
design, methods of measuring concepts and
techniques of analysis.
• To identify data sources used by other researchers.
• To learn how others structured their reports.

b) How to conduct the
literature survey?
• Identify the relevant sources.
• Extract and Record relevant
information.
• Write-up the Literature Review.
9

c) Sources of literature
• Books and Journals
• Electronic Databases
oBibliographic Databases
oAbstract Databases
oFull-Text Databases
• Govt. and Industry Reports
• Internet
• Research Dissertations / Thesis

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:
(i) 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. The knowledge of methodology
provides good training specially to the
new research worker and enables him to do better
research. It helps him to develop disciplined
thinking or a ‘bent of mind’ to observe the field objectively.
Hence, those aspiring for careerism in research must
develop the skill of using research techniques and must
thoroughly

understand the logic behind them.
(ii) Knowledge of how to do research will inculcate the
ability to evaluate and use research
results with reasonable confidence. In other words, we
can state that the knowledge of
research methodology is helpful in various fields such as
government or business

administration, community development and social work
where persons are increasingly
called upon to evaluate and use research results for action.
(iii) 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. Accordingly, it enables use to make
intelligent decisions concerning problems

facing us in practical life at different points of time. Thus, the knowledge of research
methodology provides tools to took at things in life objectively.
(iv) 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. The knowledge of methodology helps the consumer of research
results to evaluate them and enables him to take rational decisions.

Research
Process
Before embarking on the details of research methodology and techniques, it seems appropriate to
present a brief overview of the research process. Research process consists of series of actions or
steps necessary to effectively carry out research and the desired sequencing of these steps. The
chart shown in Figure 1.1 well illustrates a research process

1. Formulating
the research
problem:
The best way of understanding the problem is to discuss it with one’s own colleagues or with
those having some expertise in the matter. In an academic institution the researcher can seek the
help from a guide

2. Extensive
literature survey:
At this juncture the researcher should undertake extensive literature survey connected with the
problem. For this purpose, the abstracting and indexing journals and published or unpublished
bibliographies are the first place to go to. Academic journals, conference proceedings, government
reports, books etc., must be tapped depending on the nature of the problem

3. Development
of working
hypotheses:
(a) Discussions with colleagues and experts about the problem, its origin and the objectives in
seeking a solution;
(b) Examinationof data and records, if available, concerning the problem for possible trends,
peculiarities and other clues;
(c) Review of similar studies in the area or of the studies on similar problems; and

(d) Exploratory personal investigation which involves original field interviews on a limited scale
with interested parties and individuals with a view to secure greater insight into the practical
aspects of the problem.
Working hypotheses are more useful when stated in precise and clearly defined terms

4. Preparing the
research design:
(i) the means of obtaining the information;
(ii) the availability and skills of the researcher and his staff (if
any);
(iii) explanation of the way in which selected means of
obtaining information will be organised
and the reasoning leading to the selection;
(iv) the time available for research; and
(v) the cost factor relating to research, i.e., the finance
available for the purpose

5. Determining
sample design:

6.
Collectin
g the
data:
Primary data can be collected either through experiment or
through survey. If the researcher
conducts an experiment, he observes some quantitative
measurements, or the data, with the help of
which he examines the truth contained in his hypothesis. But
in the case of a survey, data can be
collected by any one or more of the following ways:

(i) By observation:
(ii) Through personal interview:
(iii) Through telephone interviews:
(iv) By mailing of questionnaires:
(v) Through schedules:

7. Execution of
the project:

8. Analysis of
data:
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. The unwieldy data should necessarily be condensed into a few manageable
groups and tables for further analysis.

INTRODUCTION TO
RESEARCH METHODOLOGY
MAM SONIA GHAFOOR
Faculty – Department of Optics
and Vision Science
Sonia.ghafoor@d
ovs.uol.edu.pk

TABLE OF CONTENT
1. MEANING OF RESEARCH
2. OBJECTIVES OF RESEARCH
3. CHARACTERISTICS OF RESEARCH
4. CRITERIA OF AGOOD RESEARCH
5. QUALITIES OF GOOD RESEARCH
6. RESEARCH MOTIVATIONS
7. TYPES OF RESEARCH
30

1. PROBLEMS IN RESEARCH
2. RESEARCH APPROACHES
3. RESEARCH PROCESS
4. LITERATURE REVIEW
5. HYPOTHESIS
6. CRITERIA OF GOOD RESEARCH
7. PROBLEMS ENCOUNTERED BY
RESEARCHERS

INTRODUCTION TO RESEARCH METHODS
32

1.1 MEANING OF RESEARCH
33
• Research in general refers to….
o A search for knowledge.
o A scientific and systematic search for relevant information
on a specific topic.
o Research is an art of scientific investigation.
o Research is a careful investigation or inquiry especially
through search for new facts in any branch of knowledge.
o “Redman and Mory” define research as a “systematized
effort to gain new knowledge.”
o Research is a movement, a movement from the known to
the unknown.

o A voyage of discovery.
o “Clifford Woody” defines research as “a
comprises defining and redefining problems,
formulating hypothesis or suggested solutions;
collecting, organizing and evaluating data;
making deductions and reaching conclusions;
and at last carefully testing the conclusions to
determine whether they fit the formulating
hypothesis”.

o D. Slesinger and M. Stephenson, defines research is “the
manipulation of things, concepts or symbols for the
purpose of generalizing to extend, correct or verify
knowledge, whether that knowledge aids in construction
of theory or in the practice of an art.”
o Research is the systematic process of collecting
and analyzing information (data) in order to
increase our understanding of the phenomenon
about which we are concerned or interested.

1.2 OBJECTIVES OF RESEARCH
36
• The purpose of research is to discover
answers through the application of scientific
procedures.
• The main aim of research is to find out the truth
which is hidden and which has not been
discovered as yet.
• Research objectives falling into a number of
following broad groupings:

o Exploratory or Formulative Research studies:
To gain familiarity with a phenomenon or to
achieve new insights into it.
o Descriptive Research studies : To depict
accurately the characteristics of a particular
individual, situation or a group
o Diagnostic Research studies: To determine the
frequency with which something
occurs or with which it is associated with something else.
o Hypothesis-Testing Research studies: To test a
hypothesis of a causal relationship between variables.

1.3 CHARACTERISTICS OF RESEARCH
38
• Research is directed towards the solution of a
problem.
• Research is based upon observable experience
or empirical evidence.
• Research demands accurate observation and
description.
• Research involves gathering new data from
primary sources or using existing data for a new
purpose.

• Research activities are characterized by carefully designed procedures.
• Research requires expertise i.e., skill necessary to carryout investigation,
search the related literature and to understand and analyze the data
gathered.
• Research is objective and logical – applying every possible test to
validate the data collected and conclusions reached.
• Research involves the quest for answers to unsolved problems.
• Research requires courage.
• Research is characterized by patient and unhurried activity.
• Research is carefully recorded and reported.

1.4 CRITERIA OF A GOOD RESEARCH
• Purpose clearly defined.
• Research process detailed.
• Research design thoroughly planned.
• High ethical standards applied.
• Limitations frankly revealed.
• Adequate analysis for decision maker’s needs.
• Findings presented unambiguously.
• Conclusions justified.
• Researcher’s experience reflected.
40

1.5 QUALITIES OF GOOD RESEARCH
• Systematic
• Logical
• Empirical
• Replicable
• Creative
• Use of multiple
methods
Rajasekar Ramalingam - Research Methodology 41

1.6 RESEARCH MOTIVATIONS
42
• The possible motives for doing research
are:
• Desire to get a research degree along with
its consequential benefits
• Desire to face the challenge in solving the
unsolved problems.

• Desire to get intellectual joy of doing some creative
work
• Desire to be of service to society
• Desire to get respectability.
• Other motivating factors are: directives of
government, employment conditions, curiosity
about new things, desire to understand causal
relationships, social thinking and awakening.

Types of
Research
Descriptive Vs
Analytical
Research
Applied Vs.
Fundamental
Research
Quantitative
Vs. Qualitative
Research
Conceptual Vs.
Empirical
Research
Other Types of
Research
One time
Research
Longitudinal
Research
Historical
Research
Diagnostic
Research
Experimental
Research
Exploratory
Research
1.7 TYPES OF RESEARCH
44

1. Descriptive Vs Analytical research.
45
Descriptive research:
• Includes surveys and fact-finding enquiries of different
kinds.
• The major purpose of descriptive research is description of
the state of affairs as it exists
at present.

• The main characteristic of this method is that the
researcher has no control over the variables; he can only
report what has happened or what is happening.
• Researchers discover causes even when they cannot
control the variables.
• The methods of research utilized in descriptive research are
survey methods of all kinds,
including comparative and correlational methods.
Analytical research:
• The researcher has to use facts or information already
available, and analyze these to make a critical evaluation
of the material.

2. Applied vs. Fundamental.
47
Applied research:
• Aims at finding a solution for an immediate problem
facing a society or an industrial/business
organization.
• The central aim of applied research is to discover a
solution for some pressing practical problem.
• Example for Applied research.
• Research aimed at certain conclusions (say, a solution)
facing a concrete social or business problem.
• Research to identify social, economic or political trends
that may affect a particular institution or the copy
research or the marketing research or evaluation
research.

Fundamental research:
• is mainly concerned with generalizations and with
the formulation of a theory.
• Fundamental research is directed towards finding
information that has a broad base of applications
• Examples of fundamental research:
• Research concerning some natural phenomenon or
relating to pure mathematics.
• Research carried on with a view to make
generalizations about human behavior.

3. Quantitative vs. Qualitative:
49
Quantitative research:
• is based on the measurement of quantity or amount.
• It is applicable to phenomena that can be expressed in terms of
quantity.
• Quantitative Research is used to quantify the problem by way of
generating numerical data or data that can be transformed into
usable statistics.
• It is used to quantify attitudes, opinions, behaviors, and other defined
variables – and generalize results from a larger
sample population.
• Quantitative Research uses measurable data to formulate facts and
uncover patterns in research.
• Quantitative data collection methods are much more structured than
Qualitative data collection methods.
• Quantitative data collection methods include various forms of surveys –
online surveys, paper surveys, mobile surveys and kiosk surveys,
face-to-face interviews, telephone interviews, longitudinal studies,
website interceptors, online polls, and systematic observations.

Qualitative research:
• is concerned with qualitative phenomenon.
• Phenomena relating to or involving quality or kind.
• Qualitative Research is primarily exploratory research.
• It is used to gain an understanding of underlying reasons, opinions, and
motivations.
• It provides insights into the problem or helps to develop ideas or
hypotheses for potential quantitative research.
• Qualitative Research is also used to uncover trends in thought and
opinions, and dive deeper into the problem.
• Qualitative data collection methods vary using unstructured or semi-
structured techniques.
• Some common methods include focus groups (group discussions),
individual interviews, and participation/observations.
• The sample size is typically small, and respondents are selected to fulfill
a given quota.

4. Conceptual vs. Empirical:
51
Conceptual research:
• is that related to some abstract idea(s) or theory.
• It is generally used by philosophers and thinkers to develop
new concepts or to reinterpret existing ones.
Empirical research:
• relies on experience or observation alone, often without due
regard for system and theory.
• It is data-based research, coming up with conclusions
which are capable of being verified by observation or
experiment.
• We can also call it as experimental type of research.

• In such a research it is necessary to get at facts firsthand,
at their source, and actively to go about doing certain
things to stimulate the production of desired information.
• In such a research, the researcher must first provide himself
with a working hypothesis or guess as to the probable
results.
• He then works to get enough facts (data) to prove or
disprove his hypothesis.
• He then sets up experimental designs which he thinks will
manipulate the persons or the materials concerned so as
to bring forth the desired information.
• Evidence gathered through experiments or empirical studies
is today considered to be the most powerful support
possible for a given hypothesis.

5. Some other types of research
53
• One-time Research: Research confined to a
single time period.
• Longitudinal Research: Research carried on
over several time periods.
• Diagnostic Research: It is also called clinical
research which aims at identifying the causes of
a problem, frequency with which it occur and the
possible solutions for it.

• Exploratory Research: It is the preliminary study of an
unfamiliar problem, about which the researcher has little or
no knowledge. It is aimed to gain familiarity with the
problem, to generate new ideas or to make a precise
formulation of the problem. Hence it is also known as
formulative research.
• Experimental Research: It is designed to assess the
effect of one particular variable on a phenomenon by
keeping the other variables constant or controlled.
• Historical Research: It is the study of past records and
other information sources, with a view to find the origin and
development of a phenomenon and to discover the trends
in the past, in order to understand the present and to
anticipate the future.

1.8 PROBLEMS IN RESEARCH
55
• Not similar to science
• Uncontrollable variables
• Human tendencies
• Time and money
• Lack of computerization

• Lack of scientific training in the methodology of research
• Insufficient interaction between university research
departments and business establishments
• Lack of confidence on the part of business units to give
information
• Lack of code of conduct
• Difficulty of adequate and timely secretarial assistance
• Poor library management and functioning
• Difficulty of timely availability of published data.
• Ignorance
• Research for the sake of research-limited practical utility
though they may use high sounding business jargon.

9. RESEARCH APPROACHES
There are two basic approaches to research
• Quantitative approach
• Qualitative approach
Research
Approaches
Quantitative
Approach
Inferential
approach
Experimental
approach
Simulation
approach
Qualitative
Approach
57

1. Quantitative approach
58
• Quantitative approach involves the generation of data in quantitative
form which can be subjected to rigorous quantitative analysis in a
formal and rigid fashion.
• This approach can be further sub-classified into
1) Inferential approach
2) Experimental approach
3) Simulation approach
• The purpose of inferential approach to research is to form a
data base from which to infer characteristics or relationships
of population.

2. Qualitative approach
59
• Qualitative approach to research is concerned
with subjective assessment of attitudes, opinions
and behavior.
• Research in such a situation is a function of
researcher’s insights and
impressions.
• Such an approach to research generates results
either in non-quantitative form or in the form
which are not subjected to rigorous quantitative
analysis.
• Generally, the techniques of focus group
interviews, projective techniques and depth
interviews are used.

• This usually means survey research where a sample of population is studied
(questioned or observed) to determine its characteristics, and it is then inferred
that the population has the samecharacteristics.
• Experimental approach is characterized by much greater control over the
research environment and in this case some variables are manipulated to
observe their effect on othervariables.
• Simulation approach involves the construction of an artificial environment
within which relevant information and data can be generated.
• This permits an observation of the dynamic behavior of a system (or its sub-
system) under controlled
conditions.
• Simulation approach useful in building models for understandingfuture
conditions.

1.10 RESEARCH PROCESS
61
• Research process consists of series of actions or steps
necessary to effectively carry out research and the
desired sequencing of these steps.
• The chart shown in Figure well illustrates a research
process.
• The chart indicates that the research process consists
of a number of closely related activities, as shown
through I to VII.
• However, the following order concerning various steps
provides a useful procedural guideline regarding the
research process:

62

(1) Formulating the research problem
(2) Extensive literature survey
(3) Developing the hypothesis
(4) Preparing the research design
(5) Determining sample design
(6) Collecting the data
(7) Execution of the project
(8) Analysis of data
(9) Hypothesis testing
(10) Generalizations and interpretation
(11) Preparation of the report or presentation of theresults
63

a) What is a Research problem?
• The term ‘problem’ means a question or issue to be examined.
• Research Problem refers to some difficulty/need which a researcher
experiences in the context of either theoretical or practical situation
and wants to obtain a solution for the same.
b) How do we know we have a research problem?
• Customer complaints
• Conversation with company employees
• Observation of inappropriate behavior or conditions in the firm
• Deviation from the business plan
• Success of the firm’s competitor’s
• Relevant reading of published material (trends, regulations)
• Company records and reports.
c) Definition of the problem involves two activities:
• Identification / Selection of the Problem
• Formulation of the Problem
64

d) Identification/selection of the research problem.
• This step involves identification of a few problems and selection of one out of them, after evaluating the
alternatives against certain selectioncriteria.
e) Sources of problems.
• Reading
• Academic Experience
• Daily Experience
• Exposure to Field Situations
• Consultations
• Brainstorming
• Research
• Intuition
f) Criteria of Selection
• The selection of one appropriate researchable problem out of the identified problems requires evaluation
of those alternatives against certain criteria. Theyare:
• Internal / Personal criteria – Researcher’s Interest, Researcher’s Competence, Researcher’s own
Resource: finance and time.
• External Criteria or Factors – Research-ability of the problem, Importance and Urgency, Novelty of the
Problem, Feasibility, Facilities, Usefulness and Social Relevance, ResearchPersonnel.
65

g) Definition/formulation of the research problem.
• Formulation is the process of refining the research ideas into research questions and objectives.
• Formulation means translating and transforming the selected research problem/topic/idea into a
scientifically researchable question. It is concerned with specifying exactly what the research problem
is.
• Problem definition or Problem statement is a clear, precise and succinct statement of the question or
issue that is to be investigated with the goal of finding an answer orsolution.
• There are two ways of stating a problem:
• Posting question / questions
• Making declarative statement / statements
h) Process involved in defining the problem
• Statement of the problem in a generalway.
• Understanding the nature of problem.
• Surveying the available literature.
• Developing ideas through discussions.
• Rephrasing the research problem.
i) Criteria of a good research problem
• Clear and Unambiguous
• Empirical
• Verifiable
• Interesting
• Novel and Original
• Availability of Guidance
66

j) Defining problem, results in clear cut researchobjectives.
k) Establishment of research objectives
• Research Objectives are the specific components of the research problem, which you’ll be working to
answer or complete, in order to answer the overall research problem. - Churchill, 2001
• The objectives refer to the questions to be answered through the study. They indicate what weare
trying to get from the study or the expected results / outcome of the study.
• Research Objectives should be clear and achievable, as they directly assist in answering theresearch
problem.
• The objectives may be specified in the form of either statements orquestions.
• Generally, they are written as statements, using the word “to”. (For example, ‘to discover …’, ‘to
determine …’, ‘to establish …’, etc. )
67

1.11 LITERATURE REVIEW
68
• Literature Review is the documentation of a comprehensive review of the published
and unpublished work from secondary sources of data in the areas of specific interest
to the researcher.
• The main aim is to find out problems that are already investigated and those that need
further investigation.
• It is an extensive survey of all available past studies relevant to the field of
investigation.
• It gives us knowledge about what others have found out in the related field of study
and how they have done so.
a) Purpose of review
• To gain a background knowledge of the researchtopic.
• To identify the concepts relating to it, potential relationships between them and to
formulate researchable hypothesis.
• To identify appropriate methodology, research design, methods of measuring concepts
and techniques of analysis.
• To identify data sources used by otherresearchers.
• To learn how others structured theirreports.

b) How to conduct the literature survey?
• Identify the relevant sources.
• Extract and Record relevant information.
• Write-up the Literature Review.
c) Sources of literature
• Books and Journals
• Electronic Databases
o Bibliographic Databases
o Abstract Databases
o Full-Text Databases
• Govt. and Industry Reports
• Internet
• Research Dissertations / Thesis
d) Recording the literature
• The most suitable method of recording notes is the card system.
• The recording system involves use of two sets of cards:
1) Source cards (3”x 5”) – used for noting bibliographic information.
2) Note cards (5”x 8”) – used for actual note taking.
69

1. Source cards
70
• Source Cards serve two purposes:
• Provide documentary information for footnotes.
• It is used for compiling bibliography to be given at the end of thereport.
• Source Cards can be coded by a simple system in order to relate them to the corresponding note cards.
• Marking a combination of letters and a number on the right hand top corner that begins with ‘C’. For
example; C1, C2 etc.
OR
• Marking the letter ‘B’ or ‘J’ or ‘R’ (B=Books, J=Journal, R=Report) on the left hand top corner.
• The recording of bibliographic information should be made in proper bibliographicformat.
• The format for citing a book is: Author’s name, (year), Title of the book, Place of publication,
Publisher’s name.
• For Example; Koontz Harold (1980), Management, New Delhi, McGraw-Hill International.
•
• The format for citing a journal article is: Author’s name, (year), Title of the article, Journalname,
Volume (number), pages.
• For Example; Sheth J.N (1973),A Model of Industrial Buying Behavior, Journal of Marketing, 37(4), 50-
56.

2. Note cards
71
• Detailed Information extracted from a printed source is recorded on the note cards.
• It is desirable to note a single fact or idea on each card, on one side only.
• How to write the review?
• There are several ways of presenting the ideas of others within the body of the paper.
• For Example; If you are referring the major influencing factors in the Sheth’s model of
Industrial Buying Behavior, it can be written as, Sheth (1973, p-50) has suggested that,
there are a number of influencing factors ……..
• According to Sheth (1973) model of industrial buying behavior, there are a number of
influencing factors……..
• In some models of industrial buying behavior, there are a number of influencing factors
(Sheth, 1973).
• In some models of industrial buying behavior, there are a number of influencing factors1.
• Sheth J.N (1973), A Model of Industrial Buying Behavior, Journal of Marketing, 37(4), 50-
56.

e) How to write the review?
• There are several ways of presenting the ideas of others within the body of the paper.
• For Example; If you are referring the major influencing factors in the Sheth’s model of
Industrial Buying Behavior, it can be written as,
• Sheth (1973, p-50) has suggested that, there are a number of influencing factors ……..
• According to Sheth (1973) model of industrial buying behavior, there are a number of
influencing factors……..
• In some models of industrial buying behavior, there are a number of influencing factors
(Sheth, 1973).
• In some models of industrial buying behavior, there are a number of influencing factors1.
• Sheth J.N (1973), A Model of Industrial Buying Behavior, Journal of Marketing, 37(4), 50-
56.
f) Points to be kept in mind while reviewing literature.
• Read relevant literature.
• Refer original works.
• Read with comprehension.
• Read in time.
• Index the literature.
72

1.12 HYPOTHESIS
73
a. Hypothesis
• A hypothesis is an assumption about relations between variables.
• Hypothesis can be defined as a logically conjectured relationship between two or more
variables expressed in the form of a testable statement.
• Relationships are conjectured on the basis of the network of associations established in
the theoretical framework formulated for the research study.
b. Variables
• Anything that can vary can be considered as a variable.
• A variable is anything that can take on differing or varying values.
o For example; Age, Production units, Absenteeism, Sex, Motivation, Income, Height,
Weight etc.
• Note: The values can differ at various times for the same object or person (or) at the
same time for different objects or persons.
• A variable is a characteristic that takes on two or more values whereas; an attribute is a
specific value on a variable (qualitative).
o For example;
o The variable SEX/GENDER has 2 attributes - Male and Female.
o The variable AGREEMENT has 5 attributes – Strongly Agree, Agree, Neutral,
Disagree, and Strongly Disagree.

c. Types of variables
• Explanatory Vs Extraneous Variable
• The variables selected for analysis are called explanatory variables and all other variables
that are not related to the purpose of the study but may affect the dependent variable are
extraneous.
• Dependant Vs Independent Variable
• The variable that changes in relationship to changes in another variable(s) is called
dependant variable.
• The variable whose change results in the change in another variable is called an
independent variable.
• OR
• An independent variable is the one that influences the dependant variable in either a
positive or negative way.
74

d. Hypothesis
• Research Hypothesis is a predictive statement that relates an independent
variable to a dependant variable.
o Hypothesis must contain atleast one independent variable and one
dependant variable.
• Hypotheses are tentative, intelligent guesses as to the solution of the problem.
• Hypothesis is a specific statement of prediction. It describes in concrete terms
what you expect to happen in the study.
• Hypothesis is an assumption about the population of the study.
• It delimits the area of research and keeps the researcher on the right track.
e. Problem (vs) Hypothesis
• Hypothesis is an assumption, which can be tested and can be proved to be right
or wrong.
• A problem is a broad question which cannot be directly tested. A problem can be
scientifically investigated after converting it into a form of hypothesis.
75

f. Characteristics of Hypothesis
• Conceptual Clarity - It should be clear and precise.
• Specificity - It should be specific and limited in scope.
• Consistency - It should be consistent with the objectives of research.
• Testability - It should be capable of being tested.
• Expectancy - It should state the expected relationships between variables.
• Simplicity - It should be stated as far as possible in simple terms.
• Objectivity - It should not include value judgments, relative terms or any moral
preaching.
• Theoretical Relevance - It should be consistent with a substantial body of established
or known facts or existing theory.
• Availability of Techniques – Statistical methods should be available for testing the
proposed hypothesis.
76

g. Sources of Hypothesis
• Discussions with colleagues and experts about the problem, its origin
and objectives in seeking a solution.
• Examination of data and records for possible trends, peculiarities.
• Review of similar studies.
• Exploratory personal investigation / Observation.
• Logical deduction from the existing theory.
• Continuity of research.
• Intuition and personal experience.
77

h. Types of Hypothesis
Descriptive Hypothesis
• These are assumptions that describe the characteristics (such as size, form
or distribution) of a variable. The variable may be an object, person,
organization, situation or event.
• Examples: “Public enterprises are more amenable for centralized
planning”.
Relational Hypothesis [Explanatory Hypothesis]
• These are assumptions that describe the relationship between two
variables. The relationship suggested may be positive, negative or causal
relationship.
• Examples: “Families with higher incomes spend more for recreation”.
Casual Hypothesis
• Causal Hypothesis state that the existence of or change in one variable
causes or leads to an effect on another variable. The first variable is called
the independent variable and the latter is the dependant variable.
78

Null Hypothesis
• When a hypothesis is stated negatively, it is called null hypothesis. It is a
‘no difference’, ‘no relationship’ hypothesis. ie., It states that, no difference
exists between the parameter and statistic being compared to or no
relationship exists between the variables being compared. It is usually
represented as HO or H0.
• Example: H0: There is no relationship between a family’s income and
expenditure on recreation.
Alternate Hypothesis
• It is the hypothesis that describes the researcher’s prediction that, there
exist a relationship between two variables or it is the opposite of null
hypothesis. It is represented as HA or H1.
• Example: HA: There is a definite relationship between family’s income
and expenditure on recreation.
79

i. Functions or role of hypothesis
• It gives a definite point to the investigation and provides direction to the
study.
• It determines the data needs.
• It specifies the sources of data.
• It suggests which type of research is likely to be more appropriate.
• It determines the most appropriate technique of analysis.
• It contributes to the development of theory.
80

1.13 CRITERIA OF GOOD RESEARCH
81
• The scientific research must satisfy the following criteria:
• The purpose of the research should be clearly defined and common concepts be used.
• The research procedure used should be described in sufficient detail to permit another
researcher to repeat the research for further advancement, keeping the continuity of what
has already been attained.
• The procedural design of the research should be carefully planned to yield results that are
as objective as possible.
• The researcher should report with complete frankness, flaws in procedural design and
estimate their effects upon the findings.
• 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.
• 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.
• Greater confidence in research is warranted if the researcher is experienced, has a good
reputation in research and is a person of integrity.

1.14 PROBLEMS ENCOUNTERED BY RESEARCHERS
82
• The lack of a scientific training in the methodology of research.
• Insufficient interaction between the university research departments on one side and
business establishments, government departments and research institutions on the other
side.
• The need for generating the confidence that the information/data obtained from a
business unit will not be misused.
• Research studies overlapping one another are undertaken quite often for want of
adequate information.
• There does not exist a code of conduct for researchers and inter-university and
interdepartmental rivalries are also quite common.
• Researchers in our country also face the difficulty of adequate and timely secretarial
assistance, including computerial assistance.
• Library management and functioning is not satisfactory at many places and much of the
time and energy of researchers are spent in tracing out the books, journals, reports, etc.,
rather than in tracing out relevant material from them.
• There is also the problem that many of our libraries are not able to get copies of old and
new Acts/Rules, reports and other government publications in time.
• There is also the difficulty of timely availability of published data from various government
and other agencies doing this job in our country.
• The problem of conceptualization and also problems relating to the process of data
collection and related things.

Coding operation is usually done at this stage through which the
categories of data are transformed into symbols that may be tabulated and counted
Editingis the procedure that improves the quality of the data for coding. With coding the stage is ready for
tabulation.
Tabulation is a part of the technical procedure wherein the classified data are put in the form of
tables

DATA ENTRY IN SPSS

• “Statistical package for the social
sciences”
• It is a software used for data analysis in
business research. Can be used for :
• Processing questionnaires.
• Reporting in tables and graphs.
• Analyzing;means,chi-square,
regression.
What is SPSS?

History
Introduced in 1968.
It was originally developed to facilitate
statistical analysis in the social sciences.
Early versions designed to run on
mainframe computers.
Purchased by IBM in 2009 for more than 1
billion dollars.

Important factors to consider
before data entry into SPSS
Question response formats.
Scale characteristics.
Levels of measurement.
Converting all these formats into numeric
or string (alphabet) data for entering into
SPSS.

Question-response formats can be
of following types
Closed-Ended
Open-Ended with numerical response
Open-Ended with text response
Multiple response questions

1. Clos
ed-
End
ed:
A closed-ended question can be answered
in a short or single-word answer. They are
used to obtain facts and specific pieces of
information.

Examples:
Closed-Ended
How is your satisfaction with the customer
service?
Excellent
Good
Bad
Very bad

Coding
the
answers:
1 = Excellent
2 = Good
3 = Bad
4 = Very bad

Closed-
Ended
Please indicate your gender.
Female
Male
Codes:
1 = Female
2 = Male

2.
Open-
Ended
with
numeric
response
:-
An open-ended question is designed to
encourage a full, meaningful answer using
the subject's own knowledge and/or
feelings. It is the opposite of a closed-
ended question, which encourages a short
or single-word answer.

3. Open-
Ended
with text
response
:-
An Open-Ended Response is a meaningful
answer to a question, task, or problem
presented to students that has more than
one possible answer.

4.
Multiple
response
question
s:
A Multiple Response question is similar to
a Multiple Choice question, except that
instead of being required to make one (and
only one) choice, the user is allowed to
make none, one, or more than one choice.

Scale characteristics:
Scale characteristics are of three types in
SPSS:
Nominal
Ordinal
Scale (also called as interval or ratio)

Levels of measurement:

Used in;
• Telecommunication.
• Banking.
• Finance.
• Insurance.
• Health care.
• Manufacturing.
USES

• Retail.
• Consumer package goods.
• High education.
• Government and market research.

• It can be expanded.
• It can easily and quickly displays data
tables.
• Many complex statistical tests are
available in it.
• It has a ability of data management.
• It has a ability to manage a complex data
set.
ADVANTAGES

• User friendly interface with dialogue
boxes.
• Probably the most accessible software.
• Limited background in statistics.
• Good range of methodology.

• It is easy to learn and use.
• It includes a full range of data, management
system and editing tools.
• It provides statistical capabilities.
• It offers complete plotting, reporting and
presentation features.
FEATURES OF SPSS

LIMITATIONS OF SPSS
Here are some limitations of SPSS:
Default graphics are far from publication quality:
In general, it’s better to use other programs for graphics. For some important
questions (such as interaction or moderation in regression), SPSS does not
provide any graphic capabilities.
Information about effect size and confidence intervals is missing for many
techniques:
There is no reason why SPSS could not provide effect size information. The
frequent omission of effect size and confidence interval limits is particularly
troubling now that many fields, such as psychology, call for reporting effect
size and CIs.

It is expensive:
It is expensive compared to many competitive alternatives.
Documentation about algorithms is sometimes difficult or
impossible to find:
SPSS sometimes uses names for statistics that are not consistent
with most common uses in books. This sometimes leaves
important questions unanswered.
Many useful procedures (such as Missing Values) are not
included in the base package and are available only as
expensive add ones.
Support for individual users is not easily accessible.

DISADVANTAGES OF SPSS
Requires annual license.
Limited statistical procedures.
Some procedures require purchase of add-on modules.
No reduction in the number of test cases.
Requires some training.
Need to be able to read and appropriately interpret data.
Limited data visualization capabilities.
Potential problem; too easy to run analysis without understanding
them.
A lot of options; need to know how to select appropriate options for
analysis.

There are often compatibility issues.
It makes doing an inappropriate analysis very easy.
If you delete any of your variable you can not restore it.

Transformation and computation of variables in SPSS

SPSS
SPSS is short form of Statistical Package for the Social Sciences, and
it's used by various kinds of researchers for complex statistical data
analysis. The SPSS software package was created for the management
and statistical analysis of social science data.

transformation
SPSS transformation commands (or simply “transformations”) can be
loosely defined as commands that are not immediately carried out when
you run them. Instead, they are kept in mind by SPSS and executed only
when necessary.

Recoding (Transforming) Variables
Sometimes you will want to transform a variable by grouping its
categories or values together. For example, you may want to change a
continuous variable into a categorical variable, or you may want to merge
the categories of a nominal variable. In SPSS, this type of transform is
called recoding.

In SPSS, there are three basic options for recoding variables:
Recode into Different Variables
Recode into Same Variables
DO IF syntax

What is syntax?
SPSS syntax is a programming language that is unique to SPSS. It
allows you to write commands that run SPSS procedures, rather than
using the graphical user interface.

Basic syntax rules

 FORMATTING
•Statements in SPSS end with a period.
•SPSS syntax is not case-sensitive. You can use all lower case, all upper
case, or a mixture of both when writing syntax.

 COMMENTS
•A comment is a line of text in a program that is not read by the computer
as a command. Comments do not affect how the program functions; they
exist purely for the humans reading and writing the program. Comments
help the reader understand what the program is doing. In general, it is
good practice to use brief but descriptive comments in your code. Your
comments should be clear enough that a reader completely unfamiliar
with your work can understand what your program is doing.
•In SPSS syntax, placing an asterisk (*) or a forward-slash followed by an
asterisk (/*) at the start of a line will turn all text on that line into a
comment. Hitting the Enter key will create a new, un-commented line.
Typically, comments in SPSS syntax are color-coded with the color gray.

 COLOR-CODING
SPSS Syntax Color Coding
Dark blue/purple Procedure names; execution
statements
Green Statements associated with the given
procedure
Dark red/orange Option keywords
Gray Comments
Black Variable names; other text
By default, SPSS uses color and bolding to indicate the roles of the words in the syntax.

 Using Syntax
OPENING THE SYNTAX EDITOR:
To open a new Syntax Editor window, click File > New > Syntax.

•After you've opened a Syntax Editor window, you can start writing your
syntax directly in this window. Alternatively, you can generate syntax while
using the graphical user interface: almost all SPSS procedures accessed
through the dropdown menus can generate syntax by clicking
the Paste button instead of clicking OK/Run. After clicking the Paste
button, the new syntax will automatically be added to your open Syntax
Editor window.

EXECUTING SYNTAX COMMANDS:
•To execute (or run) the commands, highlight the lines you want to run,
then click Run > Selection, or press Ctrl + R on your keyboard.

SAVING SYNTAX FILES:
•You can save your SPSS syntax as an *.sps file so that you can re-use it
later. To save your syntax file, make sure that you have the Syntax Editor
window open and active, then click File > Save or File > Save As to save
the syntax file.

OPENING SYNTAX FILES:
•To open a syntax file on your computer, click File > Open > Syntax. You
can do this from any open window (including the Data View or Output
View).

Recode into Different Variables
•Recoding into a different variable transforms an original variable into a
new variable. That is, the changes do not overwrite the original variable;
they are instead applied to a copy of the original variable under a new
name.
•To recode into different variables, click Transform > Recode into Different
Variables.

The Recode into Different Variables window will appear.

•The left column lists all of the variables in your dataset. Select the
variable you wish to recode by clicking it. Click the arrow in the center to
move the selected variable to the center text box, (B)

A.Input Variable -> Output Variable:
The center text box lists the variable(s) you have selected to recode, as
well as the name your new variable(s) will have after the recode. You
will define the new name in (C).
B.Output Variable:
Define the name and label for your recoded variable(s) by typing them
in the text fields. Once you are finished, click Change. Now the center
text box, (B), will display both the name of the original variable as well
as the name for the new variable (e.g., “Height --> Height_categ”).

C. Old and New Variables:
•Click the Old and New Values to specify how you wish to recode the
values for the selected variable.
D. IF:
•The If option allows you to specify the conditions under which your
recode will be applied. (We discuss the If option in more detail later in this
tutorial.)

Old and New Values:
Once you click Old and New Values, a new window where you will specify how to transform the values
appear.

1.Old Value:
Specify the type of value you wish to recode (e.g., a specific value, missing
data, or a range of values) and the specific value to be recoded (e.g., a value
of “1” or a range of “1-5”).
Value: Enter a specific numeric code representing an existing category.
System-missing: Applies to any system-missing values (.)
System- or user-missing: Applies to any system-missing values (.) or special
missing value codes defined by the user in the Variable View window
Range: For use with ordered categories or continuous measurements. Enter
the lower and upper boundaries that should be coded. The recoded category
will include both endpoints, so data values that are exactly equal to the
boundaries will be included in that category.
Range, lowest through value: For use with ordered categories or continuous
measurements. Recode all values less than or equal to some number.
Range, value through highest: For use with ordered categories or continuous
measurements. Recode all values greater than or equal to some number.
All other values: Applies to any value not explicitly accounted for by the
previous recoding rules. If using this setting, it should be applied last.

2. New Value:
Specify the new value for your variable (i.e., a specific numeric code such
as “2,” system-missing, or copy old values).
3.Old -> New:
Once you have selected the old and new values for your selected
variable in (1) and (2), click Add in area (3), Old-->New. The recode that
you have specified now appears in the text field. If you need to change
one of the recodes that you have added to the Old-->New area section,
simply click on the one you wish to change and make changes in (1) and
(2) as necessary.
You will need to repeat these steps for each value that you wish to
recode. Once you have specified all the transformations that you wish to
make for the selected variable, click the “Continue” button.

4.Output variables are strings and Convert numeric strings to numbers:
These options change the variable type of the new variable
•Output variables are strings:
The new variable will be a string variable.
•Convert numeric strings to numbers:
This option can only be used when your input variable is a string, and will be grayed out otherwise. If the input variable is a string, but the data values themselves are valid numbers, selecting this option will convert the number strings into actual numbers. (If any other character symbols appear in the data values, the conversion will fail, even if the numbers are otherwise valid. This includes
dollar signs and percent symbols.)

The “If” option:
Sometimes you may wish to recode values for a specific variable only
when other conditions in your data are satisfied. This means that cases
meeting the conditions will be recoded, and cases not meeting the
conditions will be assigned a missing value. To specify such conditions,
click If to bring up the Recode into Different Variables: If Cases window.

1.1 The left column displays all of the variables in your dataset. You will use one or more variables to define the conditions under which your recode should be applied to the data.
2.2 The default specification for a recode is to Include all cases. To specify the conditions under which the recode should be applied, however, you will need to click Include if case satisfies condition. This will allow you to specify the conditions under which the recode will be applied to your data.
3.3 The center of the window includes a collection of arithmetic operators, Boolean operators, and numeric characters, which you can use to specify the conditions under which your recode will be applied to the data. There are many kinds of conditions you can specify by selecting a variable (or multiple variables) from the left column, moving them to the center text field, and using the blue buttons to specify values (e.g., “1”) and operations (e.g., +, *, /). You can also use the options in the Function
group list.

4. The Function Group box contains common functions that may be used for calculating values for new variables (e.g., mean, logarithm, sine). After selecting a category, you will see function names appear in the Functions and Special Variables box. Double-clicking on a function name will add it to the "Include if case satisfies condition" box.
When you are finished defining the conditions under which your recode will be applied to the data, click Continue.
When you are ready to run the procedure, click OK. Now your new variable will be recoded according to the criteria you specified. You can find your new variable in the last column in Data View or in the last row of Variable View.

Recode into Same Variables
•Recoding into the same variable (Transform > Recode into Same
Variables) works the same way as described above, except for that any
changes made will permanently alter the original variable. That is, the
original values will be replaced by the recoded values.
•In general, it is good practice not to recode into the same variable
because it overwrites the original variable. If you ever needed to use the
variable in its original form (or wanted to double-check your steps), that
information would be lost.

DO IF - ELSE IF Syntax
DO IF-ELSE IF syntax performs similarly to the Recode procedures, but
allows for more control over specifying numeric ranges. If you want to
discretize a numeric variable into more than three categories, or if you
want to perform a recoding based on more than one variable, you'll need
to use DO IF-ELSE IF syntax. (You could use DO IF-ELSE IF for recoding
a categorical variable, but there's no real reason to use it over Recode;
the Recode syntax is shorter and more efficient for that situation.)

The DO IF-ELSE IF syntax is:
DO IF (conditional statement).
COMPUTE (variable assignment statement).
ELSE IF (conditional statement)
COMPUTE (variable assignment statement).
…
ELSE.
COMPUTE (variable assignment statement).
END IF.
EXECUTE.

A list of operators that SPSS recognizes in conditional (or logical)
statements is given in the following table. Note that you can use the letter
combinations or the mathematical symbols in your statements. You can
also use parentheses to group or distribute the effects of an operator.

Operators for logical statements.
Operator Symbol Definition
EQ = Equal to
NE ~= Not equal to
LT < Less than
LE <= Less than or equal to
GT > Greater than
GE >= Greater than or equal to
AND & Both statements must be
true
OR | One or both statements
must be true
NOT ~ Negation (must not be true)

The ELSE line tells SPSS to perform its nested computation on all other
values not accounted for by the previous conditional statements. ELSE is
optional -- you don't necessarily have to use it, but it is often more
convenient to use than addressing every possible outcome using ELSE
IF. If you do use ELSE, it must be at the very end of the loop (right before
the END DO statement).

computation
SPSS COMPUTE command sets the data values for (possibly
new) numeric variables and string variables. These values are usually
a function (such as MEAN, SUM or something more advanced) of other
variables.

•Sometimes you may need to compute a new variable based on existing
information (from other variables) in your data. For example, you may
want to:
•Convert the units of a variable from feet to meters
•Use a subject's height and weight to compute their BMI
•Compute a subscale score from items on a survey
•Apply a computation conditionally, so that a new variable is only
computed for cases where certain conditions are met

To compute a new variable, click Transform > Compute Variable.

The Compute Variable window will open where you will specify how to
calculate your new variable.

A. Target Variable:
The name of the new variable that will be created during the
computation. Simply type a name for the new variable in the text field.
Once a variable is entered here, you can click on “Type & Label” to
assign a variable type and give it a label. The default type for new
variables is numeric.
B. The left column lists all of the variables in your dataset. You can use
this menu to add variables into a computation: either double-click on a
variable to add it to the Numeric Expression field, or select the variable(s)
that will be used in your computation and click the arrow to move them to
the Numeric Expression text field (C).

C. Numeric Expression:
Specify how to compute the new variable by writing a numeric expression. This expression must includ
more variables from your dataset, and can use arithmetic or functions.
•When writing an expression in the Compute Variables dialog window:
•SPSS is not case-sensitive with respect to variable names.
•When specifying the formula for a new variable, you have to option to include or not include spaces a
commas that go between arguments in a function.
•Do not put a period at the end of the expression you enter into the Numeric Expression box.

D. The center of the window includes a collection of arithmetic operators,
Boolean operators, and numeric characters, which you can use to specify
how your new variable will be calculated. There are many kinds of
calculations you can specify by selecting a variable (or multiple variables)
from the left column, moving them to the center text field, and using the
blue buttons to specify values (e.g., “1”) and operations (e.g., +, *, /).
E. If: The If option allows you to specify the conditions under which your
computation will be applied.

F. Function group: You can also use the built-in functions in the Function
group list on the right-hand side of the window. The function group
contains many useful, common functions that may be used for calculating
values for new variables (e.g., mean, logarithm). To find a specific
function, simply click one of the function groups in the Function
Group list. You will now see a list of functions that belong to that function
group in the Functions and Special Variables area. If you click on a
specific function, a description of that function will appear in the text field
to the left.

Click If (indicated by letter E in the image) to open the Compute Variable: If
Cases window.

1.The left column displays all of the variables in your dataset. You will use
one or more variables to define the conditions under which your
computation should be applied to the data.
2.The default specification is to Include all cases. To specify the
conditions under which your computation should be applied, however, you
will need to click Include if case satisfies condition. This will allow you to
specify the conditions under which the computation will be applied to your
data.
3.The center of the dialog box includes a collection of arithmetic
operators, Boolean operators, and numeric characters, which you can use
to specify the conditions under which your recode will be applied to the
data. There are many kinds of conditions you can specify by selecting a
variable (or multiple variables) from the left column, moving them to the
center text field, and using the blue buttons to specify values (e.g., “1”)
and operations (e.g., +, *, /). You can also use the built-in functions in
the Function Group list under the right column

After you are finished defining the conditions under which your
computation will be applied to the data, click Continue. Note that when
you specify a condition in the Compute Variable: If Cases window, the
computation will only be performed on the cases meeting the specified
condition. If a case does not meet that condition, it will be assigned a
missing value for the new variable.

Computing Variables using Syntax:
You do not necessarily need to use the Compute Variables dialog window
in order to compute variables or generate syntax. You can write your own
syntax expressions to compute variables (and it is often faster and more
convenient to do so!) Syntax expressions can be executed by opening a
new Syntax file (File > New > Syntax), entering the commands in the
Syntax window, and then pressing the Run button.
The general form of the syntax for computing a new (numeric) variable is:
COMPUTE NewVariableName = formula.
EXECUTE

• The first line gives the COMPUTE command, which specifies the name
of the new variable on the left side of the equals sign, and its formula
on the right side of the equals sign. The formula on the right side of the
equals sign corresponds to what you would enter in the Numeric
Expression field in the Compute Variables dialog window.
• The EXECUTE command on the second line is what actually carries
out the computation and adds the variable to the active dataset. (If you
have tried to run COMPUTE syntax but do not see variables added to
your dataset and do not also see error or warning messages in the
Output Viewer, you may have forgotten to run
the EXECUTE statement.)

In general, when writing an expression or formula using COMPUTE
syntax:
a)SPSS is not case-sensitive with respect to variable names.
b)When specifying the formula for a new variable, you have to option to
include or not include spaces around the equals sign and/or after the
commas between arguments in a function.
c)A period goes at the end of the COMPUTE statement, after the end of
the formula.

Research Design

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.” In fact, the research design is the conceptual
structure within which research is conducted; it constitutes
the blueprint for the collection, measurement and analysis
of data.

Reason of
Research Design
(i) What is the study about?
(ii) Why is the study being made?
(iii) Where will the study be carried out?
(iv) What type of data is required?
(v) Where can the required data be found?
(vi) What periods of time will the study include?

(vii) What will be the sample design?
(viii) What techniques of data collection will be used?
(ix) How will the data be analysed?
(x) In what style will the report be prepared?

Parts of Research
Design
(a) the sampling design which deals with the method of selecting items to be observed for the
given study;
(b) the observational design which relates to the conditions under which the observations
are to be made;

(c) the statistical design which concerns with the question of how many items are to be
observed and how the informationand data gathered are to be analysed; and
(d) the operational design which deals with the techniques by which the procedures specified
in the sampling, statistical and observationaldesigns can be carried out.

Important
Features
(i) It is a plan that specifies the sources and types of information relevant to the research
problem.
(ii) It is a strategy specifying which approach will be used for gathering and analysing the data.
(iii)It also includes the time and cost budgets since most studies are done under these two
constraints.

Research Design
must contain
(a) a clear statement of the research problem;
(b) procedures and techniques to be used for gathering information; (c) the population to be studied;
and (d) methods to be used in processing and analysing data.

NEED FOR
RESEARCH
DESIGN
Smooth sailing of the various research operations
Making research as efficient as possible

FEATURES OF A
GOOD DESIGN
flexible, appropriate, efficient, economical
The design which gives the smallest experimental
error is supposed to be the best design in many investigations.
good design is related to the purpose or objective of the research problem and also with
the nature of the problem to be studied.

. 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

Factors Involved
(i) the means of obtaining information;
(ii) the availability and skills of the researcher and his staff, if any;
(iii) the objective of the problem to be studied;
(iv) the nature of the problem to be studied; and
(v) the availability of time and money for the research work.

IMPORTANT
CONCEPTS
RELATING TO
RESEARCH
DESIGN
1. Dependent and independent variables:
2. Extraneous variable:
3. Control:
4. Confounded relationship:
5. Research hypothesis:
6. Experimental and non-experimental hypothesis-testing research:

7. Experimental and control groups:
8. Treatments:
9. Experiment:
10. Experimental unit(s):

1. Dependent and
independent
variables:
A concept which can take on different quantitative
values is called a variable. As such the concepts like weight, height, income are all examples of
variables. Qualitative phenomena (or the attributes) are also quantified on the basis of the presence or absence of the
concerning attribute(s).

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.