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1. The Power of Statistical Tests. 2. A Simple and General Model for Power Analysis. 3. Power Analyses for Minimum-Effect Tests. 4. Using Power Analyses. 5. Correlation and Regression. 6. t -Tests and the One-Way Analysis of Variance. 7. Multi-Factor ANOVA Designs. 8. Studies with Multiple Observations for Each Subject: Repeated-Measures and Multivariate Analyses. 9. The Implications of Power Analyses. Appendix A. Translating Statistics into F and Calculating the Percentage of Variance Explained. Appendix B. One Stop F Table. Appendix C. One Stop PV Table. Appendix D. Working With the Noncentral F Distribution. Appendix E. The df Err Needed for Power = .80 ( Alpha = 0.05) in Tests of Traditional Null Hypothesis. Appendix F. The dfErr Needed for Power = .80 (Alpha = 0.05) in Tests of the Hypothesis That Treatments Account for 1% or Less in the Variance of Outcomes.

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