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Chapter 13: F Distribution and One-Way ANOVA

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    For hypothesis tests comparing averages between more than two groups, statisticians have developed a method called "Analysis of Variance" (abbreviated ANOVA). In this chapter, you will study the simplest form of ANOVA called single factor or one-way ANOVA. You will also study the \(F\) distribution, used for one-way ANOVA, and the test of two variances. This is just a very brief overview of one-way ANOVA. You will study this topic in much greater detail in future statistics courses. One-Way ANOVA, as it is presented here, relies heavily on a calculator or computer

    • 13.1: F Distribution
      Here are some facts and applications of the F distribution.
    • 13.2: Multiple Comparisons
      When you perform a large number of statistical tests, some will have P values less than 0.05 purely by chance, even if all your null hypotheses are really true. The Bonferroni correction is one simple way to take this into account; adjusting the false discovery rate using the Benjamini-Hochberg procedure is a more powerful method.
    • 13.3: One-Factor ANOVA
      This section shows how ANOVA can be used to analyze a one-factor between-subjects design.

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