Factorial Anova

A very useful Analysis of VAriance (ANOVA) design that researchers use to control extraneous influences is analysis of covariance (ANCOVA). ANCOVA procedures are useful in quasi-experimental designs, and post facto designs. The factorial ANOVA performs the single ANOVA procedure twice within the same analysis. The factorial ANOVA also performs an additional analysis of the interaction effects. The key feature of an interaction effect is that both independent variables have effects on each other as well as the dependent variable; different levels of one independent variable affect the levels of the other independent variable. The factorial ANOVA has several comparisons that recognize the complexity of the data. There are three primary comparisons: row effects, column effects, and interaction effects. Calculating factorial ANOVA begins by calculating the total, between, and within sums of squares as you did with the one-way ANOVA. These are the “building blocks” of the two-way ANOVA (2XANOVA) calculations.