[内容简介]
        Rebecca M. Warner’s Applied Statistics: From Bivariate Through Multivariate Techniques, Second Edition provides a clear introduction to widely used topics in bivariate and multivariate statistics, including multiple regression, discriminant analysis, MANOVA, factor analysis, and binary logistic regression. The approach is applied and does not require formal mathematics; equations are accompanied by verbal explanations. Students are asked to think about the meaning of equations. Each chapter presents a complete empirical research example to illustrate the application of a specific method. Although SPSS examples are used throughout the book, the conceptual material will be helpful for users of different programs. Each chapter has a glossary and comprehension questions. 
        [目录]
        Preface
        Acknowledgments
        About the Author
        Chapter 1. Review of Basic Concepts
        Chapter 2. Basic Statistics, Sampling Error, and Confidence Intervals
        Chapter 3. Statistical Significance Testing
        Chapter 4. Preliminary Data Screening
        Chapter 5. Comparing Group Means Using the Independent Samples t Test
        Chapter 6. One-Way Between-Subjects Analysis of Variance
        Chapter 7. Bivariate Pearson Correlation
        Chapter 8. Alternative Correlation Coefficients
        Chapter 9. Bivariate Regression
        Chapter 10. Adding a Third Variable: Preliminary Exploratory Analyses
        Chapter 11. Multiple Regression With Two Predictor Variables
        Chapter 12. Dummy Predictor Variables in Multiple Regression
        Chapter 13. Factorial Analysis of Variance
        Chapter 14. Multiple Regression With More Than Two Predictors
        Chapter 15. Moderation: Tests for Interaction in Multiple Regression
        Chapter 16. Mediation
        Chapter 17. Analysis of Covariance
        Chapter 18. Discriminant Analysis
        Chapter 19. Multivariate Analysis of Variance
        Chapter 20. Principal Components and Factor Analysis
        Chapter 21. Reliability, Validity, and Multiple-Item Scales
        Chapter 22. Analysis of Repeated Measures
        Chapter 23. Binary Logistic Regression
        Appendix A: Proportions of Area Under a Standard Normal Curve
        Appendix B: Critical Values for t Distribution
        Appendix C: Critical Values of F
        Appendix D: Critical Values of Chi-Square
        Appendix E: Critical Values of the Pearson Correlation Coefficient
        Appendix F: Critical Values of the Studentized Range Statistic
        Appendix G: Transformation of r (Pearson Correlation) to Fisher Z
        Glossary
        References
        Index