Which test compares three or more means?

Which test compares three or more means?

• A. ANOVA
• B. t-test
• C. Regression
• D. Correlation

Answer: (A)

To determine whether three or more means differ, you use ANOVA. It compares the variability between the group means to the variability within each group. If the between-group differences are large relative to within-group variability, you get a large F-statistic and a small p-value, indicating that at least one group mean is different from the others. This approach lets you test all group means at once without inflating the overall chance of a false positive. This is different from a t-test, which compares only two means at a time and would raise the risk of Type I error if used repeatedly with three groups. Regression and correlation focus on relationships between variables rather than comparing multiple group means, so they aren’t the right tools for testing whether several group means are equal. If ANOVA shows a significant result, follow-up post-hoc tests (like Tukey or Bonferroni) help identify which specific pairs of means differ.

To determine whether three or more means differ, you use ANOVA. It compares the variability between the group means to the variability within each group. If the between-group differences are large relative to within-group variability, you get a large F-statistic and a small p-value, indicating that at least one group mean is different from the others. This approach lets you test all group means at once without inflating the overall chance of a false positive.

This is different from a t-test, which compares only two means at a time and would raise the risk of Type I error if used repeatedly with three groups. Regression and correlation focus on relationships between variables rather than comparing multiple group means, so they aren’t the right tools for testing whether several group means are equal. If ANOVA shows a significant result, follow-up post-hoc tests (like Tukey or Bonferroni) help identify which specific pairs of means differ.