ABSTRACT
This chapter deals with the one-factor analysis of variance (ANOVA) model and various multiple comparison procedures for that model. The first characteristic of the two-factor ANOVA model should be obvious by now; this model considers the effect of two factors or independent variables on one dependent variable. For the two-factor ANOVA model, there are three sets of hypotheses, one for each of the main effects, and one for the interaction effect. For a two-factor ANOVA, the dataset must consist of three variables or columns, one for the level of factor A, one for the level of factor B, and the third for the dependent variable. Remember that the residual was added to the dataset by saving it when we generated the factorial ANOVA model. To find the factorial ANOVA, we select “Tests” in the top pulldown menu, then “Means,” and then “Many groups: ANOVA: Main effects and interactions.
