ABSTRACT
The factorial analysis of variance (ANOVA) requires a single dependent variable, measured at the interval or ratio level, just like the one-way ANOVA and the independent samples t-test. However, the factorial ANOVA also requires two independent variables, with two or more groups each. Often, researchers describe the factorial ANOVA based on how many groups there are on each variable. The factorial ANOVA has all of the same assumptions as the one-way ANOVA, but some apply a bit differently in this design. The factorial ANOVA also assumes a normally distributed dependent variable. This assumption also does not differ from either the one-way ANOVA or the independent samples t-test. As with those designs, we will evaluate the normality of the dependent variable using skewness and kurtosis statistics. As with the one-way ANOVA or independent samples t-test, the factorial ANOVA requires that the observations be independent.
