Data Analysis for Research Designs covers the analytical techniques for the analysis of variance (ANOVA) and multiple regression/correlation (MRC), emphasizing single-degree-of-freedom comparisons so that students focus on clear research planning. This text is designed for advanced undergraduates and graduate students of the behavioral and social sciences who have an understanding of algebra and statistics.

 Preface

    

  1. Introduction

  2. Principle of Research Design

  3. Overview of Design and Analysis

  4. Basic Concepts in Statistical Analysis

  5. Basic Statistical Concepts in Correlation and Regresssion

  6. Basic Statistical Concepts in ANOVA

  7. The Correlational Analysis of Experimental Data

  8. Significance and Hypothesis Testing

  9. General Coding of Experiments for MRC Analysis

  10. Overall Analysis of the Single-Factor Design

  11. Detailed Analysis of the Single-Factor Design

  12. Correction for Multiple Comparisons

  13. Introduction to the Two-Factor Design

  14. The Analysis of Main Effects and Simple Effects

  15. The Analysis of Interaction Comparisons: The Interaction Contrast

  16. The Within-Subjects Single-Factor Design

  17. The Mixed Two-Factor Design

  18. Detailed Analysis of the Mixed Factorial Design

  19. Higher-Order Factorial Designs

  20. Nonexperimental Research

  21. Other Applications of MRC to Nonexperimental Research

  22. Analysis of Covariance

  23. Analysis of Trend

  24. Unequal Sample Sizes

  25. Epilogue

    

  References

  Appendix

  Answers to the Exercises

  Author Index

  Subject Index