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Applying Contemporary Statistical Techniques explains why traditional statistical methods are often inadequate or outdated when applied to modern problems. Wilcox demonstrates how new and more powerful techniques address these problems far more effectively, making these modern robust methods understandable, practical, and easily accessible. * Assumes no previous training in statistics * Explains how and why modern statistical methods provide more accurate results than conventional methods* Covers the latest developments on multiple comparisons * Includes recent advances in risk-based methods * Features many illustrations and examples using data from real studies * Describes and illustrates easy-to-use s-plus functions for applying cutting-edge techniques * Covers many contemporary ANOVA (analysis of variance) and regression methods not found in other books

Applying Contemporary Statistical Techniques Explains Why Traditional Statistical Methods Are Often Inadequate Or Outdated When Applied To Modern Problems. Wilcox Demonstrates How New And More Powerful Techniques Address These Problems Far More Effectively, Making These Modern Robust Methods Understandable, Practical, And Easily Accessible.

highlights:

• Assumes No Previous Training In Statistics

• Explains When And Why Modern Methods Provide More Accurate Results

• Provides Simple Descriptions Of When And Why Conventional Methods Can Be Highly Unsatisfactory

• Covers The Latest Developments On Multiple Comparisons

• Includes Recent Advances In Risk-based Methods

• Features Many Illustrations And Examples Using Data From Real Studies

• Describes And Illustrates Easy-to-use S-plus Functions For Applying Cutting-edge Techniques

the Book Is Quite Unique In That It Offers A Lot Of Up-to-date Statistical Tools. No Other Book At This Level Comes Close In This Aspect.
Xuming He -university Of Illinois, Urbana

1. Introduction......Page 3 2. Probability and Related Concepts......Page 19 3. Summarizing Data......Page 56 4. Sampling Distributions and Confidence Intervals......Page 93 5. Hypothesis Testing......Page 141 6. Least Squares Regression and Pearson's Correlation......Page 173 7. Basic Bootstrap Methods......Page 207 8.Comparing Two Independent Groups......Page 236 9. One-Way ANOVA......Page 284 10, Two-Way ANOVA......Page 328 11. Comparing Dependent Groups......Page 360 12. Multiple Comparisons......Page 406 13. Robust and Exploratory Regression......Page 456 14. More Regression Methods......Page 515 15. Rank-Based and Nonparametric Methods......Page 554 Appendix A......Page 606 Appendix B......Page 611 Appendix C......Page 637 References......Page 643 Index......Page 655 Preface 3 1. Introduction 3 2. Probability and Related Concepts 19 3. Summarizing Data 56 4. Sampling Distributions and Confidence Intervals 93 5. Hypothesis Testing 141 6. Least Squares Regression and Pearson's Correlation 173 7. Basic Bootstrap Methods 207 8.Comparing Two Independent Groups 236 9. One-Way ANOVA 284 10, Two-Way ANOVA 328 11. Comparing Dependent Groups 360 12. Multiple Comparisons 406 13. Robust and Exploratory Regression 456 14. More Regression Methods 515 15. Rank-Based and Nonparametric Methods 554 Appendix A 606 Appendix B 611 Appendix C 637 References 643 Index 655 The goals of this book are to describe the basics of applied statistical methods in a manner that takes into account the many insights from the last half century, to describe contemporary approaches to commonly encountered statistical problems, to provide an intuitive sense of why modern methods-developed after the year 1960-have substantial advantages over conventional techniques, and to make these new methods practical and accessible.