ABSTRACT
In the previous chapter, we examined one-way ANOVA. In this chapter and the one that follows it, we explore the wonders of two more advanced methods of analyzing variance: factorial ANOVA and repeated-measures ANOVA. These techniques are based on the same general principles as one-way ANOVA. Namely, they all involve the partitioning of the variance of a dependent variable into its component parts (e.g., the part attributable to between-group differences, the part attributable to within-group variance, or error). In addition, these techniques allow us to examine more complex, and often more interesting, questions than allowed by simple one-way ANOVA. As mentioned at the end of the last chapter, these more advanced statistical techniques involve much more complex formulas than those we have seen previously. Therefore, in this chapter and those that follow, only a basic introduction to the techniques is offered. You should keep in mind that there is much more to these statistics than described in these pages, and you should consider reading more about them in the suggested readings at the end of the book.
