Page 169 - Statistics II for Dummies

Chapter 9

Testing Lots of Means?

Come On Over to ANOVA!

In This Chapter
▶ Extending the t-test for comparing two means by using ANOVA
▶ Utilizing the ANOVA process
▶ Carrying out an F-test
▶ Navigating the ANOVA table

ne of the most commonly used statistical techniques at the Stats II
Olevel is analysis of variance (affectionately known as ANOVA). Because
the name has the word variance in it, you may think that this technique has
something to do with variance — and you would be right. Analysis of vari-
ance is all about examining the amount of variability in a y (response) vari-
able and trying to understand where that variability is coming from.

One way you can use ANOVA is to compare several populations regarding
some quantitative variable, y. The populations you want to compare consti-
tute different groups (denoted by an x variable), such as political affiliations,
age groups, or different brands of a product. ANOVA is also particularly suit-
able for situations involving an experiment in which you apply certain treat-
ments (x) to subjects and measure a response (y).
In this chapter, you start with the t-test for two population means, the pre-
cursor to ANOVA. Then you move on to the basic concepts of ANOVA to
compare more than two means: sums of squares, the F-test, and the ANOVA
table. You apply these basics to the one-factor or one-way ANOVA, where you
compare the responses based only on one treatment variable. (In Chapter
11, you can see the basics applied to a two-way ANOVA, which has two treat-
ment variables.)

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