ABSTRACT
The œrst six chapters are concerned with different analysis of variance (ANOVA) models. In this chapter, we consider the most basic ANOVA model, known as the onefactor ANOVA model. Recall the independent t test from Chapter 7 of An Introduction to Statistical Concepts, Third Edition where the means from two independent samples were compared. What if you wish to compare more than two means? The answer is to use the analysis of variance. At this point, you may be wondering why the procedure is called the analysis of variance rather than the analysis of means, because the intent is to study possible mean differences. One way of comparing a set of means is to think in terms of the variability among those means. If the sample means are all the same, then the variability of those means would be 0. If the sample means are not all the same, then the variability of those means would be somewhat greater than 0. In general, the greater the mean differences are, the greater is the variability of the means. Thus, mean differences are studied by looking at the variability of the means; hence, the term analysis of variance is appropriate rather than analysis of means (further discussed in this chapter).
