1. MODULE 1-
RESEARCH DESIGN
SUBMITTED BY:
SHIVANGI SOBTI
NITYA MEHTA
PADMINI BASU
KRISH SAPRA
PREKSHA JOSHI
HARLEEN CHAWLA

2. WHAT IS A RESEARCH DESIGN?
 Task of defining the research problem is the preparation of the 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 can be defined as a framework of methods and
techniques chosen by researcher to combine various components in a
logical manner so that research problem can be handled well.
 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.

3. WHAT IS A GOOD RESEARCH
DESIGN ?
Generally, the design which minimizes bias and maximizes the reliability
of the data collected and analyzed is considered a good design. The
design which gives the smallest experimental error is supposed to
be the best design in many investigations. Similarly, a design which
yields maximal information and provides an opportunity for
considering many different aspects of a problem is considered most
appropriate and efficient design in respect of many research
problems. Thus, the question of 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.

4. FEATURES OF A GOOD RESEARCH
DESIGN
A research design appropriate for a particular
research problem, usually involves the
consideration of the following factors:
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.

5. PRINCIPLES OF RESEARCH
DESIGN
1. Formulating the Problem.
2. Review of Literature.
3. Formulating Hypotheses and Making Assumptions Explicit.
4. Specification of Needed Data.
5. Selection of Methods and Techniques to Yield Needed Data.
6. Planning the Analysis.
7. Pretesting Study Design.
8. Collection of Data.
9. Analysis of Data.
10. Interpretation and Reporting

6. PRINCIPLES OF RESEARCH DESIGN
 Principles of Research Design are as follows :-
 Formulating the research problem: There are 2 types of research problems, first which
relate to states of nature and second which relate to the relationships between variables.
The researcher must first decide the general area of interest that he’d like to inquire into.
The research topic of problem should be practical, relatively important, feasible, ethically
and politically acceptable. The research problem should be on a topic of which literature is
available so that researcher can easily examine it to get himself acquainted with the
research problem. The research problem should be clearly defined to help discriminating
relevant data with the irrelevant ones which also depends upon the objective of the
statement.
 Literature Review/ Review of Literature - After the selection of the research problem, the
second step is review of literature. There is a conceptual literature which consists theories
and concepts and an empirical one consisting of studies.
 Making Hypothesis – It is a predictive and a tentative statement which shows the
relationship between Dependent and Independent Variables and which can be tested.
Hypothesis narrows down the area of a research and keeps the researcher on the right
path. It should be specific and limited as it has to be tested.
 Preparing the Research Design – It may draw the conceptual structure of the problem. It
makes the research efficient yielding maximum information.

7.  Data collection – The method of collecting data should be selected considering
nature of investigation, objective and scope of the inquiry, financial resources,
available time and degree of accuracy. Its 2 types are : -
Primary data collection – collecting data through experiments, or in case of
survey through questionnaires, observation and interviews.
Secondary data collection – Review of literature
 Data Analysis – After the collection of the data, it is analyzed. Then Data
Processing is done which includes editing, coding, classification, tabulation,
presentation and measurement of data. Coding is the transformation of
categories of data into symbols.
 Verification and Hypothesis testing – Research data is then forwarded to the test
of hypothesis. Is the hypothesis related to the facts? For finding this hypothesis is
tested which may result in accepting and rejecting of the hypothesis. Various
tests like Chi square test, T test, F test etc. have been developed for this purpose.
 Generalization and Interpretation- Researcher then arrives at generalization i.e.
a theory
 Preparation of the report – A research should be prepared by the researcher for
which he has done his work.

8. Experimental research design
• Experimental design refers to how participants are allocated to
the different conditions (or IV levels) in an experiment.
• Probably the commonest way to design an experiment in
psychology is to divide the participants into two groups, the
experimental group, and the control group, and then introduce
a change to the experimental group and not the control group.
• The researcher must decide how he/she will allocate their
sample to these IV level. For example, if there are 10
participants, will all 10 participants take part in both conditions
(e.g., repeated measures) or will the participants be split in half
and take part in only one condition each

9.  Experimental research design is centrally concerned
with constructing research that is high in causal
(internal) validity.
 The design of research is fraught with decisions.
 Researchers must decide which research questions to
address, which theoretical perspective will guide the
research, how to measure key constructs reliably and
accurately, who or what to sample and observe, how
many people/places/things need to be sampled in
order to achieve adequate statistical power, and which
data analytic techniques will be applied

10. Uses
 There is time priority in a causal relationship (cause
precedes effect)
 There is consistency in a causal relationship (a cause
will always lead to the same effect)
 The magnitude of the correlation is great

11. Types
 Pre-Experimental Designs:
Pre-experiments are the simplest form of research design. In a pre-experiment
either a single group or multiple groups are observed subsequent to some
agent or treatment presumed to cause change.
 True Experimental Design:
True experimental design is regarded as the most accurate form of
experimental research, in that it tries to prove or disprove a hypothesis
mathematically, with statistical analysis.

12. Quasi- Experimental Research
Design
 The prefix quasi means “resembling.” Thus quasi-experimental research is
research that resembles experimental research but is not true experimental
research.
 Although the independent variable is manipulated, participants are not randomly
assigned to conditions or orders of conditions.
 The independent variable is manipulated before the dependent variable is
measured, quasi-experimental research eliminates the directionality problem.
 But because participants are not randomly assigned—making it likely that there
are other differences between conditions—quasi-experimental research does not
eliminate the problem of extraneous variables.
 Quasi-experiments are most likely to be conducted in field settings in which
random assignment is difficult or impossible. They are often conducted to
evaluate the effectiveness of a treatment—perhaps a type of psychotherapy or
an educational intervention.
 It has several types, the most common ones being:

13. Non- Equivalent Group Design
 It is a “between- subject” design in which participants have not been
randomly assigned to conditions. When participants are not randomly
assigned to conditions, the resulting groups are likely to be dissimilar in
some ways. For this reason, researchers consider them to be nonequivalent.
 The groups may be different prior to the study which poses a threat to the
internal validity of the study. Any prior differences between the groups may
also affect the outcome of the study.
 In order to prevent this the researcher tries to use pre-existing (intact)
groups, which are as similar to each other as possible, as control group and
experimental group.

14. Pre-Test Post-Test Design
 In a Pre-Test Post-Test research design, the dependent variable is
measured once before the treatment is implemented and once after it is
implemented, thus explaining the name.
 The pretest-posttest design is much like a within-subjects experiment in
which each participant is tested first under the control condition and then
under the treatment condition.
 It is unlike a within-subjects experiment, however, in that the order of
conditions is not counterbalanced because it typically is not possible for a
participant to be tested in the treatment condition first and then in an
“untreated” control condition.
 If the average posttest score is better than the average pretest score, then
it makes sense to conclude that the treatment might be responsible for the
improvement. Unfortunately, one often cannot conclude this with a high
degree of certainty because there may be other explanations for why the
posttest scores are better.

15. Interrupted Time Series Design
 A time series is a set of measurements taken at certain intervals over a
period of time.
 It is similar to pretest-posttest design in the sense that it includes
measurements of the dependent variable both before and after the
treatment. It is unlike the pretest-posttest design, however, because it
includes multiple pretest and posttest measurements.
 For Eg: A manufacturing company might measure its workers’
productivity each week for a year. In an interrupted time series-design,
a time series like this one is “interrupted” by a treatment. The treatment
was the reduction of the work shifts in a factory from 10 hours to 8
hours (Cook & Campbell, 1979). Because productivity increased rather
quickly after the shortening of the work shifts, and because it remained
elevated for many months afterward, the researcher concluded that the
shortening of the shifts caused the increase in productivity.

16. Ex-Post Facto
Research Design
In simple words ex post facto means ‘ with retrospective action or force .
Its also called after the cause research .
Ex Post facto research is a kind of research in which the researcher predicts
the possible causes behind an effect that has already occurred.For
example , if a child is delinquent then in order to find out
The various events that have occurred and the many possibilities that
could have contributed to the concerned delinquent behaviour . The
expected reasons may be lack of discipline at school, family history, peer
effect , neighbourhood or socialisation .

17. Researcher predicts a cause on the basis of a controlled effect ( since no
variation can be done on the effect that has already taken place in the basis
of the independent variable or the cause ).
Thus, ex post facto research is to be defined as an emprically based
investigation which does not involve the researches direct control over the
independent variables because they have already to effects Which can no
more be manipulated.
The conclusions regarding the relationships between the variables are
inferred without intervening or varying the independent or dependent
variable .
In ex post facto research according To Landman the researcher instead of
finding the treatment he or she examines the effect of the naturally
occurring treatment after its being occurred .

18. However , it should be pointed out that most serious issue of ex post facto is
the conclusion that because two factors go together , one is the cause and the
other is the effect .
CHARACTERISTICS OF EX POST FACTO RESEARCH
The research has a comparison group : Research is it on the basis of the study of
the Cause which has Which has led to the effects, its becomes very necessary for
the researcher to keep a comparison group , so there can be a comparison
between the actual experiment group , in order to analyse the cause of an
already occurred event .
The behavior , action ,event or the treatment or the independent variable cannot
be manipulated: As the ex post facto is the kind of study which tries to predict
the causes on the basis of action that have already occurred ,the researcher
cannot manipulate the action or behavior that has already occurred .

19. The research focuses on the effect : Since the researcher tries to predict and
analyze the reasons behind the occurrence of an event ,there first effect is
to focus on the event that has already occurred . Only after having the
detailed study of the phenomena, the researcher tries to determine cause
behind such event .
The research tries to analyze the What and How factor: Researcher tries to
understand the causal effects behind a phenomena, the research basically
focuses on how and what reasons have led to the phenomena to occur
Research explores effects and causes :With the help of this research, the
researcher tries to analyze the cause and effect phenomena of an event or
action .

20. ADVANTAGES AND DISADVANTAGES OF
THIS RESEARCH
ADVANTAGES:
- It’s considered a relevant method in those behavioral researches where the
variables cannot be manipulated or are ethically wrong to altered .
- Its less time consuming and economical.
- It is more useful than an experimental research as it can be used in
analyzing a cause on the basis of the effect , which is impossible in an
experimental research.
DISADVANTAGES:
- The researcher cannot manipulate independent variables.
- The researcher cannot randomly assign the subjects to different groups .
- The researcher cannot provide a reasonable explanation for the relationship
between the variables .

21. Correlational Research Design.
 In their simplest form, correlational studies investigate the possibility of
relationships between only two variables, although investigations of more
than two variables are common.
 Correlational research is also sometimes referred to as a form of descriptive
research because it describes an existing relationship between variables.
 It involves data of a specific population.
 There is neither random assignment nor manipulation of experimental
variables.
 This method understands the relationship between IV and DV.
 It measures a relationship between two or more variables without the
researcher controlling them.
 It is of two types: Explanatory and Prediction

22. Types of Correlational Research
Design
 POSITIVE CORRELATION
In this type both the variables increase or decrease at the same time.
It is denoted by +1.
+1 means that there is a strong correlation.
E.g. the more one exercises the more fit he/ she gets.
 NEGATIVE CORRELATION
In this type one of the variables increase and the other decreases.
It is denoted by -1.
-1 means a strong negative correlation.
E.g. the more a person smokes the less healthy his/ her lungs become.
 NO- CORRELATION
In this type there is no correlation between two variables , hence there is no relationship.
A correlation efficient of 0 shows no relationship between two variables.
E.g. the more you water a plant, your marks improve.

23. Advantages and Disadvantages
 ADVANTAGES:
Researches can study the variables which would be unethical to
be manipulated.
Researches can study variable as they exist naturally.
 DISADVANTAGES:
Correlations will not be able to show the cause and effect.
They provide little control over extraneous variables.

24. Explanatory Type
 It Co-relates two variables
 It Collects data at one point of time.
 It Analyses all participants as a single group.
 The researcher obtains 2 scores from each individual from
each group.

25. Prediction Type
 It anticipates outcomes by using certain variables as
predictors.
 A variable that is used to make a forecast about an
outcome in the correlational study measured at one point
of time.
 E.g. if rain(predictors) increase then it is predicted that the
growth of the crops will also increase.