The document defines key concepts in experimental design including independent and dependent variables, experimental and control groups, threats to internal and external validity, and guidelines for conducting experimental research. It discusses how experimental design involves manipulating independent variables, measuring effects on dependent variables, using random assignment and control groups, and controlling for confounding factors. The goal is to establish causal relationships while ruling out alternative explanations for observed effects.

1. 1
ExperimentationExperimentation

2. 2
Causal Relationship
A precondition influencing a variable of
interest, or, more strictly, a change in
one variable that produces a change in
another variable

3. 3
Independent Variable
The variable that can be manipulated,
changed or altered by the experimenter,
independently of any variable. The
independent variable is hypothesized to
be the causal influence.

4. 4
Dependent Variable
The variable whose value is dependent on
the experimenter’s manipulations. It is the
criterion or the standard by which the results
or the experiment are judged. Changes is the
dependent variable are presumed to be the
effect of changes in the independent variable.

5. 5
Manipulation
Creating different levels of the independent
variable is known as manipulation the
variable. In the experiment, the independent
variable is manipulated, and the effect on
each level of manipulation on the dependent
variable is observed

6. 6
Experimental Treatments
Experimental treatments are the alternative
manipulation of the independent variable
being investigated.
For example, low exposure level, medium
exposure level, and high exposure level might
be experimental treatments in an advertising
experiment.

7. 7
Experimental Group
The group of subjects exposed to the
experiment treatment is termed the
experimental group

8. 8
Control Group
The group of subjects not exposed to
the experimental treatments are termed
the experimental group

9. 9
Extraneous Variable
Variables other than the manipulated variable
that affect the response of the test units and
hence the results of the experimental
research. These variables interfere with the
change in the dependent variable and thus
confound the results of the experiment.
Hence they are also known as confounding
variables.

10. 10
Selection Bias
If an experimental group is systematically
different in some relevant way from the
population being studied, it invalidates the
results of the experiment. This is known as
selection bias. Also, if the subjects assigned
to the experimental group differ
systematically from the subjects assigned to
the control group, then the result of the
experiment could be attributed to the
differences between the groups than to the
experimental manipulations.

11. 11
Randomization
A procedure in which the assignment of
subjects and treatment to groups is based on
chance. Randomization ensures control over
extraneous variables and increases the
experiment’s reliability

12. 12
Blocking
Even after adopting random assignments of
subjects and treatments to groups, it is
possible at times for the experimental groups
to differ in systematic manner on some
relevant variable.
Blocking is a procedure by which a
nonmanipulated variable is introduced into
the experiment to ensure that the groups are
equalized on that variable

13. 13
Matching
A procedure for the assignment of subjects to
groups that ensures each of group of
respondents is matched on the basis of
pertinent characteristics. Matching helps
reduce the experimental error that arises out
of selection bias.

14. 14
Treatment Effect
Conducting the experiment by itself can
alter the effects of the manipulations
and thus affect the results of the
experiment

15. 15
Hawthorne Effect
A form of treatment effect where in the
results of the experimental research are
altered unintentionally by the subjects
being aware that they are participating
in an experiment.

16. 16
A Classification of Experimental DesignsA Classification of Experimental Designs
Preexperimental Designs
-One-group, After-Only design
-One-group, Befor-After Design
-Nonmatched Control Group Design
True Experimental Designs
-Two-group, After-only Design
-Solomon Four Group Design
Quasi experimental Designs
-Time series Design
-Continuous Panel Design
Completely Randomized Design
Randomized-Block Design
Latin Square Design
Factorial Design
Statistical
Design
Classical
Design
Experimental
Design

17. 17
Preexperimental Designs
Are somewhat exploratory types of
studies that have almost no control over
the influence of extraneous factors on the
results of the experiment.

18. 18
Preexperimental Designs
One Group, After-only Design
EG X O
One Group, Before-after Design
EG O1 X O2

19. 19
Preexperimental Designs
Nonmatched Control Group Design
EG X O1
CG O2
Matched Control Group Design
EG M X O1
CG M O2

20. 20
True Experimental Designs
Experimental designs that adopt that
random assignment procedure.
The designs are generally far superior
to preexperimetal designs in making
causal inferences with confidence.

21. 21
True Experimental Design
Two-group, After Only Design
EG R X O1
CG R O2
Two-group, Before - After Design
EG R O1 X O2
CG R O3 O4

22. 22
True Experimental Design
Solomon Group Design
EG R O1 X O2
CG R O3 O4
EG R X O5
CG R O6

23. 23
Quasi-Experimental Designs
An experimental design with some
degree of control (more than
preexperimental designs), but there is
random assignment of subjects as there
is for true experimental designs.

24. 24
Quasi-Experimental Design
Time-Series Designs: similar to the one group, before
after design except that a series of measurements is
employed during which an experimental treatment
occurs.
EG O1 O2 O3 O4 O5 O6 O7 O8
Continuous Panel Design: an experimental design
which is collect a series of a measurements on the
same sample of test units, over an extended period
of time.

25. 25
Completely Randomized Design
Is the simplest type of statistical design.
The experimental treatments are assigned to
test units on a random basis.
The notation is :
EG1 R X1 O1
EG2 R X2 O2
EG2 R X3 O3

26. 26
Randomized Block Design
A randomized control group design employs the
randomization process for all variables, since there
should be no tendency for an experimental groups to
differ systematically from the others on any
dimension.
The notation is:
EG1 R X O1
CG1 R O2
EG2 R X O3
CG2 R O3

27. 27
Factorial Design
An experimental design which is two or more
experimental variables are considered simultaneously.
The notation is :
EG1 R X1(Hi Adv, Hi Price) O1 n=6
EG2 R X2(Hi Adv, Low Price) O2 n=6
EG3 R X3(Low Adv, Hi Price) O3 n=6
EG4 R X4(Low Adv, Low Price) O4 n=6
EG5 R X5(No Adv, Hi Price) O5 n=6
EG6 R X6(No Adv, Low Price) O6 n=6

28. 28
Latin Square Design
Is a method to reduce the number of
groups involved when interactions
between the treatment levels and the
control variables can be considered
unimportant

29. 29
Latin Square DesignLatin Square Design
1 2 3 4
Private Brand A
21 Cents
III IV I II
Private Brand B
22 Cents
II III IV I
Private Brand A
25 Cents
I II III IV
Private Brand B
26 Cents
IV I II III
Stores

30. 30
Laboratory And Field Experiments
Field experiment is the experimental
treatment or intervention introduced in a
completely natural setting.
Laboratory experiment is an experiment
in which the experimental treatment is
introduced in an artificial or laboratory
setting.

31. 31
Threats to Experimental Validity
Threats to Internal Validity
Threats to External Validity

32. 32
Threats to Internal Validity
1. History
2. Maturation
3. Testing
4. Instrumentation
5. Statistical regression
6. Selection bias
7. Mortality
8. Selection-maturation interaction

33. 33
Threats to Internal Validity
1. History: events external to the experiment
that affect the responses of the people
involved in the experiment.
2. Maturation : Changes in the respondents
that are a consequence of time, such as
aging, getting hungry, or getting tired.
3. Testing: The effects of taking a test on the
results of a subsequent test

34. 34
Threats to Internal Validity
4. Instrumentation: The measuring instrument
may change, as when different interviews
are used
5. Statistical regression: Operates where
groups have been selected on the basis of
their extreme scores
6. Selection bias: An experimental group is
systematically different in some relevant
way from the population being studied

35. 35
Threats to Internal Validity
7. Mortality: Respondents dropping out
of the experiment while the
experimental research is in progress
8. Selection-maturation interaction: In
certain experimental designs, the
selection-maturation interaction effect
might be mistaken for the effect of the
experimental variable.

36. 36
Threats to External Validity
1. The reactive or interaction effect of
testing
2. The interaction effect of selection
biases and the experimental variable
3. Reactive effects of experimental
arrangements
4. Multiple treatment interference

37. 37
Guidelines For Conducting Experimental
Research
1. Recognition of and statement of the
problem.
2. Choice of factors and levels.
3. Selection of the response variable.
4. Choice of experimental design.
5. Performing the experiment.
6. Data analysis.
7. Conclusion and recommendation.

38. 38
Limitations of Experiment
1. Cost
2. Security
3. Implementation problem
4. Uncertain persistency of Results

39. 39
Experimental DesignExperimental Design
A set of procedures that guide an experimental study
by specifying
 what independent variables are to be
manipulated,
 what dependent variables are to be measured,
 what levels of the experimental treatment are to
be used,
 how to select test units and assign them to
different group,
 how to control for selection bias, and
 how to minimize the influence of extraneous
variables on the results of the experiment