Applied Statistics: From Bivariate Through Multivariate Techniques / Edition 2

Applied Statistics: From Bivariate Through Multivariate Techniques / Edition 2

by Rebecca M. Warner
     
 

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ISBN-10: 141299134X

ISBN-13: 9781412991346

Pub. Date: 04/10/2012

Publisher: SAGE Publications

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

Overview

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.

Product Details

ISBN-13:
9781412991346
Publisher:
SAGE Publications
Publication date:
04/10/2012
Edition description:
Second Edition
Pages:
1208
Sales rank:
140,123
Product dimensions:
7.90(w) x 10.10(h) x 2.30(d)

Table of Contents

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

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