The very cool thing about analysis of variance when more than one factor or independent variable is tested is that the researcher can look not only at the individual effects of each factor but also at the simultaneous effects of both, through what is called an interaction. An interaction means that the strength of the effect of one independent variable on the dependent variable differs depending on how people score on the other independent variable.
