Which outcome is assessed in a two-way ANOVA?

A two-way ANOVA is a statistical test used to determine the impact of two independent categorical variables on a continuous dependent variable. The correct answer indicates that both main effects and interaction effects are assessed in this analysis.

Main effects refer to the individual influence of each independent variable on the dependent variable. For example, if one independent variable is treatment type and the other is gender, the main effect for treatment type would assess how treatment type alone affects the outcome, while the main effect for gender would evaluate how gender alone influences the outcome.

Interaction effects consider how the two independent variables work together to influence the dependent variable. This means looking at whether the effect of one independent variable differs depending on the level of the other variable. For instance, the interaction effect might show that a specific treatment is more effective for one gender than the other, indicating that the outcome is not just a simple additive effect of the two variables.

Assessing both main effects and interaction effects allows researchers to understand the separate and combined influences of the independent variables, leading to more comprehensive insights into the data being analyzed. This capability makes the two-way ANOVA a powerful tool in experimental design and analysis.