A researcher conducts a two-way ANOVA to examine the effects of education level (high school, college, graduate) and employment status (employed, unemployed) on income. The ANOVA output shows $p$-values of $0.012$ for education level, $0.18$ for employment status, and $0.045$ for the interaction. Based on these results, what should the researcher conclude?

Suppose you are conducting a two-way ANOVA to examine the effects of teaching method and school type on student performance. If a significant interaction between teaching method and school type is found, what should be your next steps in analyzing the data?

Which statement best captures the primary conceptual distinction between a one-factor ANOVA and a two-factor ANOVA with interaction?

Suppose you conduct a two-way ANOVA on a dataset and then multiply every value in the dataset by a constant factor of $2$. What effect does this transformation have on the $F$-statistics and $p$-values in the ANOVA results?

Given a two-way ANOVA summary where MS_interaction = 0.0336 and MS_error = 0.0103, compute the F-statistic for the interaction and state the correct conclusion at alpha = 0.05 (use that the calculated p-value ≈ 0.056).