Which test compares means among three or more groups?

• A. One-way ANOVA
• B. Independent samples t-test
• C. Chi-square test
• D. Pearson correlation

Answer: (A)

When you have three or more groups and you want to know whether their average scores differ, you use a one-way ANOVA. This method tests the overall null hypothesis that all group means are equal. It does this by comparing the variability between the group means to the variability within each group; if the between-group variability is large relative to the within-group variability, the result is statistically significant, suggesting that not all means are the same.

Using one-way ANOVA avoids the problem of inflating Type I error that would occur if you ran multiple pairwise t-tests among groups. If the overall test is significant, you typically follow up with post hoc tests to identify which specific groups differ.

Other options don’t fit this scenario: a t-test compares exactly two groups, a chi-square test handles categorical data, and Pearson correlation measures the strength of a linear relationship between two continuous variables.