Understanding and Applying Basic Statistical Methods Using R

PREFACE

The goal of this book is to introduce basic statistical principles, techniques, and concepts in a relatively simple and concise manner. The book is designed for a one-semester course aimed at nonstatisticians. Numerous illustrations are provided using data from a wide range of disciplines. Answers to the exercises are in Appendix A. More detailed answers to all of the exercises and data sets for the exercises can be downloaded from www.wiley.com/go/Wilcox/Statistical_Methods_R.

There are, of course, basic methods that are routinely taught in the typical introductory course, which are covered here. A primary motivation for the book is to include a description of modern insights and advances that are relevant to basic techniques in terms of dealing with nonnormality, outliers, heteroscedasticity (unequal variances), and curvature. There is a growing awareness of the practical importance of these advances, they are explained in more advanced books, but at the moment, they are not covered in the typical introductory text. Put simply, when comparing groups of individuals, or when studying the association among variables, modern advances provide the opportunity to get a much deeper and more accurate understanding of data. This is due in part to a better understanding of when routinely taught methods perform well and when they can be highly unsatisfactory. In addition, many new methods have been developed to deal with the shortcomings of standard techniques, some of which are ...