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A one-way repeated measures ANOVA is used when the same participants are measured under three or more conditions or at multiple time points. It accounts for within-subject variability, reducing error variance compared to between-groups designs. This makes it more powerful when examining changes over time. An independent samples t-test (A) is appropriate for comparing two independent groups, not repeated measures. Chi-square (C) analyzes categorical data rather than continuous means. Pearson correlation (D) examines associations between two variables but does not test group mean differences. In repeated measures, assumptions include sphericity, which requires equal variances of the differences between time points. Violations may be corrected using Greenhouse-Geisser or Huynh-Feldt adjustments. On the EPPP, test-takers should know which designs align with which statistical tests, recognizing that repeated measures ANOVA is the extension of paired t-tests when more than two related means are compared.