Which test is appropriate when comparing means across more than two independent groups?

Which test is appropriate when comparing means across more than two independent groups?

• A. Paired t-test
• B. One-way ANOVA
• C. Chi-square test
• D. Wilcoxon signed-rank test

Answer: (B)

When you have more than two independent groups and you want to know if their means differ, one-way ANOVA is the appropriate method. It tests whether the average outcome is the same across all groups by comparing variability between group means to variability within the groups. If the between-group differences are large relative to within-group variation, you get a large F statistic and a significant result, indicating that at least one group mean differs. After a significant ANOVA, you’d usually follow up with post hoc tests to identify exactly which groups differ. The other options aren’t suitable here: a paired t-test handles two related samples, a chi-square test deals with categorical data, and the Wilcoxon signed-rank test is for two related samples (a nonparametric alternative for paired data); for independent groups with a nonparametric approach, Kruskal-Wallis would be used instead.

When you have more than two independent groups and you want to know if their means differ, one-way ANOVA is the appropriate method. It tests whether the average outcome is the same across all groups by comparing variability between group means to variability within the groups. If the between-group differences are large relative to within-group variation, you get a large F statistic and a significant result, indicating that at least one group mean differs. After a significant ANOVA, you’d usually follow up with post hoc tests to identify exactly which groups differ. The other options aren’t suitable here: a paired t-test handles two related samples, a chi-square test deals with categorical data, and the Wilcoxon signed-rank test is for two related samples (a nonparametric alternative for paired data); for independent groups with a nonparametric approach, Kruskal-Wallis would be used instead.