The two-way ANOVA involves partitioning the total variability in the data into components associated with the two factors and their interaction. Here are the key components:
Main Effects: The individual impact of each independent variable on the dependent variable. Interaction Effect: The combined effect of the two independent variables on the dependent variable, which cannot be explained by their individual effects alone. Error Term: The variability in the data that cannot be explained by the two factors or their interaction.
