ABSTRACT
This chapter addresses the statistical analysis of experimental designs incorporating more than one independent variable. Another name for variable is factor, hence the term factorial Analysis of variance (ANOVA). The simplest possible factorial ANOVA is a two-way ANOVA where each factor has only two levels. In the two-way ANOVA, authors formulate several null hypotheses and test them with several separate F-ratios. The decision whether to reject or accept the null hypothesis for interaction will help us decide about the generalizability of the main effects. For fixed factors, the researcher selects the particular levels of the independent variables for which he or she desires information. The important points to note are the significance values for all three of the main effects and the interactions—three two-way interactions and one three-way interaction. None of the interactions is statistically significant, and only one of the main effects is significant.
