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Chapter 16: One-Way Analysis of Variance
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CHAPTER 16
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One-Way Analysis of Variance
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You should study the topics in this chapter if you need to review
or want to learn about
Comparing Population Means Graphically
Some Terminology Associated with Analysis of Variance
(ANOVA)
The F-Distribution
One-way or Single Factor ANOVA F Tests
Technology integration for one-way ANOVA
16-1 Introduction
In the real world, there are many situations where we may want to compare
more than two population means at the same time. For example, a
researcher may want to compare the average time to failure for four different
but similar brands of smart phones. Another researcher may want to
compare the average time it takes a certain level of pain to subside to a
specified level for at least two different dosages of the same medication or
for the same dosage for different medications. A farmer may want to
compare the average yield of his soy-bean crops when using the same
amounts per acre of different fertilizers.
These are just a few examples where we may need to compare several means
at the same time. These comparisons can be achieved simultaneously by
using procedures which are generally called ANalysis Of VAriance
(ANOVA). Note, for instance if we have five different population means to
compare, one may be tempted to do pairwise
t
-tests. However, with this
approach one will have to do ten different pairwise tests. This is not an
efficient way to approach the problem. In addition, there are other
complicated issues which are associated with the pairwise approach. For