Distinguish between one-way ANOVA and repeated-measures ANOVA.

• A. One-way ANOVA compares dependent groups; repeated-measures accounts for within-subject correlation across time/conditions.
• B. They are identical tests used in different fields.
• C. One-way ANOVA compares independent groups; repeated-measures accounts for within-subject correlation across time/conditions.
• D. Repeated-measures is used only for cross-sectional data.

Answer: (C)

The design distinction between between-subjects and within-subjects ANOVA is what’s being tested. One-way ANOVA is used when you’re comparing means across several groups that are independent from each other, so each subject appears in only one group. The variability you see within each group is what’s used to test whether the group means differ.

Repeated-measures ANOVA is used when the same subjects are measured under multiple conditions or across multiple time points. Because the measurements come from the same people, they are not independent — there’s a within-subject correlation. Repeated-measures explicitly accounts for this correlation, partitioning variance into within-subject and between-subject components, which helps control error and can increase statistical power.

So the best statement captures that one-way ANOVA compares independent groups, while repeated-measures accounts for within-subject correlation across time or conditions. The other options either misstate the independence of the groups, claim the tests are identical, or incorrectly describe when repeated-measures is used.