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Chapter 10
Experimental Design
Summary of Chapter
By James Valenza
GEOG 3000
Experimental Design
 The following slides will contain
theoretical material pertaining to the
Experimental Design Process as seen in
Chapter 10 of Larry Gonick’s ‘The
Cartoon Guide to Statistics’
Elements of a Design
 There are two basic elements of a
design.
1.
2.
Experimental Units
Treatments (assigned to the units)
Elements of a Design cont…
The objective of any Experimental Design
is to Compare the Treatments.
An example would be to testing new fertilizers for corn crops.
In this case, the Experimental Units would be the different
plots within the experimental area, while the Treatments
would be the different fertilizers used.
Why Use Experimental Design?
Because we are concerned with the
analysis of data generated from an
experiment.
Industries in which Experimental
Design Process is used.
To name a few……….
•Agriculture
•Medicine
•Social Sciences
•Industrial Processes
Principles of Experimental Design
3 Basic Principles…
1. Local Control
2. Randomization
3. Replication
Local Control
Local Control refers to any method that
accounts for and reduces natural
variability. One way is to group similar
experimental units into blocks. (Gonick,
pg.183)
Lack of controls can lead to experimental
bias, the favoring of certain outcomes
over others.
Randomization
Randomization is an extremely important step in
statistics.
Because it is generally extremely difficult for
experimenters to eliminate bias using only their
expert judgment, the use of randomization in
experiments is common practice. In a
randomized experimental design, objects or
individuals are randomly assigned (by chance)
to an experimental group. Using randomization
is the most reliable method of creating
homogeneous treatment groups, without
involving any potential biases or judgments.
(Yale, 1997)
Replication
To improve the significance of an experimental
result, replication, the repetition of an
experiment on a large group of subjects, is
required. If a treatment is truly effective, the
long-term averaging effect of replication will
reflect its experimental worth.
Replication reduces variability in experimental
results, increasing their significance and the
confidence level with which a researcher can
draw conclusions about an experimental factor.
Supplemental Material
 The following was not covered in this
chapter but I would briefly like to touch
upon ANOVA
 ANOVA- Analysis of Variance (is used as
a model to for analyzing complex
experimental designs)
ANOVA
There are two types of ANOVA tests:
1-way ANOVA- Divides the variance into 2 parts
Treatment
Error
2-way ANOVA- Divides the variance into 4 parts
Row Effect
Column Effect
Interaction Effect
Error
ANOVA cont…
Example of 1-way ANOVA Test
Resources
•Khan Academy http://www.Khanacademy.org/
•Yale Department of Statistics, 1997
http://www.stat.yale.edu/Courses/1997-98/101/expdes.htm
•Weiss, Neil. Introductory Statistics: 8th Edition, 2008. Pearson Education Inc.
•Wikipedia http://www.wikipedia.org