Applied Statistics - From Bivariate Through Multivariate Techniques

Informationen zum Autor Rebecca M. Warner received a B.A. from Carnegie-Mellon University in Social Relations in 1973 and a Ph.D. in Social Psychology from Harvard in 1978. She has taught statistics for more than 25 years: from Introductory and Intermediate Statistics to advanced topics seminars in Multivariate Statistics, Structural Equation Modeling, and Time Series Analysis. She is currently a Full Professor in the Department of Psychology at the University of New Hampshire. She is a Fellow in the Association for Psychological Science and a member of the American Psychological Association, the International Association for Relationships Research, the Society of Experimental Social Psychology, and the Society for Personality and Social Psychology. She has consulted on statistics and data management for the World Health Organization in Geneva and served as a visiting faculty member at Shandong Medical University in China. Klappentext 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. New to the Second Edition - Includes new chapters on Moderation (Chapter 15) and Mediation (Chapter 16), extending the range of statistical tools covered - Updates all SPSS screen shots and output to ISBM SPSS version 19 - Provides many new references, including for the analysis of data with many zeroes, and problems that can arise when standardized regression coefficients are compared across groups - Offers an expanded glossary of helpful key terms. Zusammenfassung Complete with examples! questions and graphics this text introduces readers to areas in bivariate and multivariate statistics. Inhaltsverzeichnis 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 R...

List 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

Product details

• Authors: Rebecca M. Warner
• Publisher: Sage Publications Ltd
• Languages: English
• Product format: Hardback
• Released: 30.06.2012
• EAN: 9781412991346
• ISBN: 978-1-4129-9134-6
• No. of pages: 1208
• Subjects: Natural sciences, medicine, IT, technology > Mathematics > Probability theory, stochastic theory, mathematical statistics; Social sciences, law, business > Sociology > Sociological theories