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Statistics in Plain English is a straightforward, conversational introduction to statistics. It starts with a brief overview of a statistic that describes what the statistic does and when to use it, followed by a detailed step-by-step explanation of how the statistic works and exactly what information it provides.
Timothy C. Urdan is a Professor at Santa Clara University. He received his Ph.D. from the Combined Program in Education and Psychology at the University of Michigan, his Master's degree in Education from Harvard University, and his B.A. in Psychology from University of California, Berkeley. He conducts research on student motivation, classroom contexts, and teacher identity. He serves on the editorial boards of several journals and is the coeditor of the Advances in Motivation and Achievement book series. He is a fellow of the American Psychological Association and lives in Berkeley, California.
1. Introduction to Social Science Research Principles and Terminology, 2. Measures of Central Tendency, 3. Measures of Variability, 4. The Normal Distribution, 5. Standardization and z Scores, 6. Standard Errors, 7. Statistical Significance, Effect Size, and Confidence Intervals, 8. t Tests, 9. One-Way Analysis of Variance, 10. Factorial Analysis of Variance, 11. Repeated-Measures Analysis of Variance, 12. Correlation, 13. Regression, 14. Nonparametric Statistics, 15. Factor Analysis and Reliability Analysis: Data Reduction Techniques, 16. Person-Centered Analysis, Appendix A. Area Under the Normal Curve Beyond Z, Appendix B. Critical Values of the t Distributions, Appendix C. Critical Values of the F Distributions, Appendix D. Critical Values of the Studentized Range Statistic (for Tukey HSD Tests), Appendix E: Table of the Fischer's Z Transformations for Correlation Coefficients, Appendix F. Critical Values of the Mann-Whitney U Statistic, Appendix G. Critical Values for Wilcoxon Signed-Rank Test, Appendix H. Critical Values of the X2 Distributions
