Experimental design is a way to carefully plan experiments in advance so that results are both objective and valid. Ideally, an experimental design should: • Describe how participants are allocated to experimental groups. A common method is completely randomized design, where participants are assigned to groups at random. A second method is randomized block design, where participants are divided into homogeneous blocks (for example, age groups) before being randomly assigned to groups. • Minimize or eliminate confounding variables, which can offer alternative explanations for the experimental results. • Allows making inferences about the relationship between independent variables and dependent variables. • Reduce variability, to make it easier to find differences in treatment outcomes. Types of Experimental Design 1. Between Subjects Design. 2. Completely Randomized Design. 3. Factorial Design. 4. Matched-Pairs Design. 5. Observational Study • Longitudinal Research • Cross Sectional Research 6. Pretest-Posttest Design. 7. Quasi-Experimental Design. 8. Randomized Block Design. 9. Randomized Controlled Trial 10. Within subjects Design.

1. Factorial designs
Sana Afreen
Msc I Food and Nutrition
Subject: Statistics

2. Experimental Design
Experimental design is a way to carefully plan experiments in advance so that results
are both objective and valid. Ideally, an experimental design should:
 Describe how participants are allocated to experimental group. A common method
is completely randomized design, where participants are assigned to groups at
random. A second method is randomized block design, where participants are
divided into homogeneous blocks (for example, age groups) before being
randomly assigned to groups.
 Minimize or eliminate confounding variables, which can offer alternative
explanations for the experimental results.
 Allows making inferences about the relationship between independent
variables and dependent variables.
 Reduce variability, to make it easier to find differences in treatment outcomes.

3. Types of Experimental Design
1. Completely Randomized Design
2. Factorial Design
3. Matched-Pairs Design
4. Observational Study
i. Longitudinal Research
ii. Cross Sectional Research
5. Pretest-Posttest Design
6. Quasi-Experimental Design
7. Randomized Block Design
8. Randomized Controlled Trial

4. Terms
 Factor- a type of treatment
 Level- a particular treatment
 Experimental treatment- a combination of one level for
each factor in the experiment.
 Complete factorial experiment- an experiment
containing all possible experimental treatments , possibly
replicated a number of times.
 Symmetrical factorial- if all factors have the same levels
, the experiment is called symmetrical factorial , otherwise
is called Mixed factorial.

5. Factorial designs
 Allow experiments to have more than one independent
variable.
 An experiment whose design consists of two or more
factors, each with discrete possible values or "levels", and
whose experimental units take on all possible
combinations of these levels across all such factors.
 The factorial experiment is a powerful weapon for
investigating responses affected by many stimuli.

6. An example

7.  We could think about having four separate groups to
do this, but when we are varying the amount of time
in instruction, what setting would we use: in-class or
pull-out? And, when we were studying setting, what
amount of instruction time would we use: 1 hour, 4
hours, or something else?
 With factorial designs, we don't have to compromise
when answering these questions. We can have it
both ways if we cross each of our two time in
instruction conditions with each of our two settings

8. Null Outcome
 A null outcome is when the experiment’s outcome is the
same regardless of how the levels and factors were
combined.

10. Main Effect
 The main effect is the effect of an independent
variable on the dependent variable .

14. Interaction effect
 An interaction effect occurs between factors.
 A comparison among the simple effects of the
component experiments (i.e., differences in the
simple effects) is called the analysis of interaction.
 It's important to recognize that an interaction is
between factors, not levels.

15. How do you know if there is an
interaction in a factorial design?
 When you run the statistical analysis, the statistical
table will report on all main effects and interactions.
 When you can't talk about effect on one factor
without mentioning the other factor.
 It is impossible to describe your results accurately
without mentioning both factors.
 Whenever there are lines that are not parallel there
is an interaction present. If you check out the main
effect graphs above, you will notice that all of the
lines within a graph are parallel. In contrast, for all of
the interaction graphs, you will see that the lines are
not parallel.

18. Advantages
 Its easier to study the combined effect of two or more
factors simultaneously and analyze their
interrelationships.
 It has a wide range of factor combination are used.
 It saves time.
 It permits the evaluation of interaction effects.

19. Disadvantages
 Its complex when several factors are involved
simultaneously.
 Wastage of time and experimental material.
 Increase in factor size leads to increase in block size
which increases the chances of error.

20. Thank you