ABSTRACT
The univariate analysis of variance (ANOVA) is one of the most frequently used procedures for comparing estimates of differences between groups on a single variable. When more than two groups are observed on several variables, a multivariate analysis of variance (MANOVA) is used. The analysis of variance applied to factorial designs with two factors is also called a two-way analysis of variance. The logic of a two-way analysis of variance is a direct extension of the rationale underlying one-way ANOVA. The purpose of the two-way analysis of variance is to compare the mean scores from several groups in a factorial design in order to decide whether the differences between the means are due to chance or to the effect of the first factor, the second factor or a combination of certain levels of the first factor with levels of the second factor. The presence of a significant interaction can certainly complicate the interpretation of a factorial analysis.
