The document discusses various research designs, emphasizing their importance as a blueprint for conducting investigations and analyzing data. It outlines types such as exploratory, descriptive, hypothesis-testing, and experimental designs, detailing their objectives, methodologies, and key principles like replication and randomization. Additionally, it covers quasi-experimental and ex-post-facto designs, highlighting their applications and characteristics in research.

1. RESEARCH DESIGNS
Sanchita Garai, Mathangi Sumana Sri and Sanjit Maiti

2. RESEARCH DESIGN
Concept
• Research design is the detailed plan of an
investigation
• It is the blue print of the detailed procedure of
testing the hypotheses and analysis of the obtained
data
Importance of Research Design
• How to collect data for testing the hypotheses
• Arrive at a valid, objective, accurate & economic
solution of the given problem
• Control variables which may influence the research
outcome
• Which variables should be treated as control
variables, what methods of manipulation will be
relevant in a particular situation
• What types of statistical analyses should be
performed

3. TYPES OF RESEARCH DESIGNS
Exploratory or formulative research design
The main purpose of this design is to formulate a problem for more
precise investigation or to develop working hypothesis. Pilot study is
conducted prior to the main investigation.
Techniques used in conducting Exploratory Research Study
• Secondary data analysis
• Experience survey or Pilot survey
• Focus group interview

4. TYPES OF RESEARCH DESIGNS
Descriptive and Diagnostic research design
A descriptive research design is used for fact
finding with adequate interpretation. Diagnostic
research design is concerned with the testing of
hypothesis and interpreting relationship between
the variables.
This design serves a variety of research
objectives:
• Description of phenomena or characteristics
associated with the population
• Discovery of associations among different
variables and in case of causal relationship studies
• Discovery and measurement of cause-and-effect
relationships among variables

5. Steps to be followed in Descriptive and Diagnostic
Research Design
1. Selection of the problem
2. Formulation of the objectives of the study
3. Formulation of hypothesis
4. Selection and development of tools for data collection
5. Defining the population and selection of sample
6. Preparation of structured interview schedule/ questionnaire
7. Pretesting the interview schedule/ questionnaire
8. Determination of the reliability and validity of the instruments developed
9. Collection of data
10. Processing and analysis of data
11. Findings and discussions
12. Preparation of report

6. TYPES OF RESEARCH DESIGNS
Hypothesis-testing or Experimental research design
It is the blue print of procedures that enables the researcher to test
hypothesis by reaching valid conclusions about relationships between
independent and dependent variables. In descriptive research study, no
control as well as manipulation of variables are required but in
experimental study some degree of control over variables and
manipulation of independent variables, to study their effect on
dependent variables are desirable.
Principles of experimental research design (Prof R.A. Fisher)
• Principle of Replication
• Principle of Randomization
• Principle of Local control

7. Principles of Experimental Research Design
• Principle of Replication: Deliberate repetition of an experiment, using
nearly identical procedure, which may sometimes be with a different set
of subjects in a different setting and at different time periods.
• Principle of Randomization: Technique in which each member of the
population or universe has an equal and independent chance of being
selected.
• Principle of Local control: Refers to the amount of balancing, blocking
and grouping of subjects or the experimental units employed in the
research design.
Grouping- assignment of homogenous subjects or experimental units into
a group
Blocking- assignment of experimental units to different blocks in such a
way that the assigned experimental units within a block may be
homogenous
Balancing- grouping, blocking and assignment of experimental units to the
different treatments in such a way that the resulting design appears to be a
balanced one

8. Types of Experimental Research Designs
True experimental designs:
1. Posttest only, Equivalent-group design
2. Pretest-Posttest control group design
Quasi-experimental designs:
3. Time-series design
4. Equivalent time samples design
5. Non-equivalent control group design
Ex-post facto designs:
6. Ex-post-facto cause to effect design
7. Ex-post-facto effect to cause design

9. TRUE EXPERIMENTAL RESEARCH DESIGNS
• Researchers have complete control over extraneous variables
• Can predict confidently that the observed effect on the dependent
variable is only due to the manipulation of the independent variable
Essential characteristics of true experimental research:
1. Manipulation
2. Control
3. Randomization

10. • Two equivalent groups of the same size are randomly selected from a
population
• One group, randomly given the treatment, is experimental group and the
other group for which no treatment is given, is called the control group
• After the treatment, posttests are administered to both the groups and the
difference is measured
• Also known as After only design
Posttest only, Equivalent Group Design
Example: Impact of the farm advisories during COVID-19 pandemic on
the mental health of the farming community in the Haryana state of India

11. Posttest only, Equivalent Group Design

12. • This design is similar to the posttest only equivalent group design,
except for the fact that it also makes a provision for pretest of both
experimental and control groups before the treatment is administered
• Also known as Before-after design
• This design provides for following measurements and comparisons:
1. Change in score of experimental group due to treatment
2. Change in score of control group due to natural causes
3. Effect of treatment, by taking into consideration (controlling) both the
initial condition (pretest score) and the impact due to natural causes
Pretest-posttest Control Group Design
Example: Effectiveness of a mobile app on the adoption of the eco-
friendly dairy farming by the farmers in Haryana state of India

13. Pretest-posttest Control Group Design

14. QUASI-EXPERIMENTAL RESEARCH DESIGNS
• Quasi-experimental research design involves the
manipulation of independent variable to observe the
effect on dependent variable, but it lacks at least one of
the two characteristics of the true experimental design,
randomization or a control group
• In other words, quasi-experimental designs have an
element of manipulation but lack at least one of the other
two properties that characterize true experiments,
randomization or control group
• These designs are generally used to establish the
causality (effect of independent variable on dependent
variables) in situations where researchers are not able to
randomly assign the subjects to groups or for various
reasons no control group is available for an experimental
study

15. • A series of pretests are given or pre treatment measurements are made of
the selected group or equivalent groups
• Then the treatment is administered and a series of posttests are given or
post treatment measurements are made of the selected group or
equivalent groups
• A control group or comparison group is not included in this design
• This design is more applicable where testing is a regular feature of the
setting, such as educational institutions, or where data are regularly
collected, such as records of production, cost of living indices, etc
Time-series Design
Example: Comparison of performance of students in the final examination
for a number of years before and after the introduction of a new method of
teaching or evaluation

16. SELECTION OF A GROUP
SERIES OF PRETESTS OR PRETREATMENT MEASUREMENTS
OF THE SAME GROUP OR EQUIVALENT GROUPS AT
REGULAR INTERVALS
TREATEMENT
SERIES OF POSTTESTS OR POSTTREATMENT
MEASUREMENTS OF THE SAME GROUP OR EQUIVALENT
GROUPS AT REGULAR INTERVALS
Time-series Design

17. • This design is an improvement over and extension of time-series
design, because of repeated introduction of treatments, followed by
posttests every time in a systematic way
• A single group is used and there is no control group
• Overall change and change separately with different treatments can
be measured
• As there is carry over experience from one treatment to the other, it
cannot be specifically stated which treatment produced what effect
Equivalent Time-samples Design
Example: Effect of NICRA Project on the attitude change of farmers
towards climate resilient practices in Haryana state of India

18. SELECTION OF A GROUP
TREATMENT-A, POSTTEST-A
TREATMENT-B, POSTTEST-B
TREATMENT-C, POSTTEST-C
TREATMENT-D, POSTTEST-D
Equivalent Time-samples Design

19. • The design is similar to pretest posttest control group design, except that
the method of randomization cannot be applied in the assignment of
subjects to experimental and control groups
• To find out treatment effect, the difference between the posttest and
pretest scores of the experimental and control groups may be computed
Non-Equivalent Control Group Design
Example: Impact of climate resilient agricultural practices in
improving livelihood of the farmers of Coastal Andhra Pradesh

20. Non-Equivalent Control Group Design

21. EX-POST-FACTO RESEARCH DESIGNS
• Researches in which the events have taken place prior to undertaking
the investigation fall under this category of research design
• Investigator has no scope to manipulate the independent variables as
they have already occurred
• Inferences on the relationships between independent and dependent
variables are drawn on the basis of effects already manifest
• In this design, the treatment is determined not by manipulation but by
selection

22. • In this design, a worthwhile cause is first identified and then its effects
are traced out
• The presumed cause is regarded as the independent variable
(treatment) and the presumed effect as the dependent variable
• Matching of groups is an important aspect of this design
• Unless the experimental and control groups are properly matched on
important variables, the investigator may come out with erroneous
conclusions
• The random selection of respondents makes the design valid
Ex-post-facto Cause to Effect Design
Example: Impact of TV viewing on the change in Knowledge and
Adoption of farmers in the Haryana state of India

23. Ex-post-facto Cause to Effect Design

24. • This is a reverse process of cause to effect design, in which the
presumed cause is traced from the presumed effects
• As in the earlier design, matching of groups is important
• Random selection of respondents makes the design valid
Ex-post-facto Effect to Cause Design
Example: Extent to which levels of knowledge, motivation and
adoption of farmers could be attributed to TV viewing

25. Ex-post-facto Effect to Cause Design