ABSTRACT
In this chapter, the authors present several examples of published research that used the one-way analysis of variance (ANOVA). The t-test is a special case of the ANOVA, and so has simpler calculations and interpretations, but accomplishes that simplification by limiting the number of groups we can compare to two. The ANOVA can handle multiple groups, while the t-test can only handle two groups at a time. In other words, one ANOVA can do the work of multiple t-tests. The ANOVA offers us some more interpretive options versus the t-test, which is another reason the authors prefer it when there are more than two groups to compare. Because the ANOVA and the t-test are both part of the general linear model, they share similar sets of assumptions. In fact, in the case of the one-way ANOVA, the assumptions are nearly identical.
