Research Design and Statistical Analysis

This fully updated fourth edition of Research Design and Statistical Analysis provides comprehensive coverage of the design principles and statistical concepts necessary to make sense of real data. The guiding philosophy is to provide a strong conceptual foundation so that readers can generalize to new situations they encounter in their research, including new developments in data analysis.

Key features include:

Emphasis on basic concepts such as sampling distributions, design efficiency, and expected mean squares, relating the research designs and data analyses to the statistical models that underlie the analyses. Detailed instructions on performing analysis using both R and SPSS. Pedagogical exercises mapped to key topic areas to support students as they review their understanding and strive to reach their higher learning goals.

Incorporating the analyses of both experimental and observational data, and with coverage that is broad and deep enough to serve a two-semester sequence, this textbook is suitable for researchers, graduate students and advanced undergraduates in psychology, education, and other behavioral, social, and health sciences.

The book is supported by a robust set of digital resources, including data files and exercises from the book in an Excel format for easy import into R or SPSS; R scripts for running example analysis and generating figures; and a solutions manual.

PART 1: Foundations of Research Design and Data Analysis  1. Planning the Research  2. Describing the Data  3. Basic Concepts in Probability  4. Developing the Fundamentals of Hypothesis Testing Using the Binomial Distribution  5. Further Development of the Foundations of Statistical Inference  6. The t Distribution and Its Applications  7. Integrated Analysis I  PART 2: Between-Participants Designs  8. Between-Participants Designs: One Factor  9. Multi-Factor Between-Participants Designs  10. Contrasting Means in Between-Subjects Designs  11. Integrated Analysis II  PART 3: Repeated-Measures Designs  12. Comparing Experimental Designs and Analyses  13. One-Factor Repeated-Measures Designs   
14. Multi-Factor Repeated-Measures and Mixed Designs  15. Nested and Counterbalanced Variables in Repeated-Measures Designs  16. Integrated Analysis III  PART 4: Correlation and Regression  17. An Introduction to Correlation and Regression  18. More About Correlation  19. More About Bivariate Regression  20. Introduction to Multiple Regression  21. Inference, Assumptions, and Power in Multiple Regression  22. Additional Topics in Multiple Regression  23. Regression with Qualitative and Quantitative Variables  24. ANCOVA as a Special Case of Multiple Regression  25. Integrated Analysis IV  PART 5: Epilogue  26. Some Final Thoughts, Suggestions, and Cautions  APPENDICES  Appendix A: Notation and Summation Operations  Appendix B: Expected Values and Their Applications  Appendix C: Statistical Tables
Answers to Selected Exercise