In a Two-Way ANOVA, the "main effect" refers to the impact that each independent variable has on the dependent variable on its own, without considering the influence of other variables. Essentially, it helps you understand how one factor affects the outcome by itself. For example, if you're studying how both diet and exercise influence weight loss, the main effect of diet would show how different diets affect weight loss, ignoring the exercise part. Similarly, the main effect of exercise would show how different levels of exercise impact weight loss, regardless of the diet.

to the effect of one independent variable on the dependent variable, ignoring the influence of the other independent variable.

refers to the impact of one independent variable on the dependent variable, averaging over the levels of the other independent variable.

It is the differences in means over levels of one factor collapsed over levels of the other factor. the difference between the grand mean and zero.

In a Two-Way ANOVA, the "main effect" refers to the individual impact of each independent variable on the dependent variable, independent of the other variable's influence.

to the effect of one independent variable on the dependent variable, ignoring the influence of the other independent variable.

In a Two-Way ANOVA, the "main effect" refers to the individual impact of each independent variable (or factor) on the dependent variable, ignoring the influence of the other factor(s). It shows whether there is a significant difference in the dependent variable across the levels of a single factor, irrespective of the other factor(s) in the analysis.