Categorical and Nonparametric Data Analysis

<p>Now in its second edition this book provides a focused comprehensive overview of both categorical and nonparametric statistics offering a conceptual framework for choosing the most appropriate test in various scenarios. The book’s clear explanations and <i>Exploring the Concept</i> boxes help reduce reader anxiety. Problems inspired by actual studies provide meaningful illustrations of these techniques. Basic statistics and probability are reviewed for those needing a refresher with mathematical derivations placed in optional appendices.</p><p>Highlights include the following:<br>• Three chapters co-authored with Edgar Brunner address modern nonparametric techniques along with accompanying R code.<br>• Unique coverage of both categorical and nonparametric statistics better prepares readers to select the best technique for particular research projects.<br>• Designed to be used with most statistical packages clear examples of how to use the tests in SPSS R and Excel foster conceptual understanding.<br>• <em>Exploring the Concept</em> boxes integrated throughout prompt students to draw links between the concepts to deepen understanding.<br>• Fully developed Instructor and Student Resources featuring datasets for the book's problems and a guide to R and for the instructor PowerPoints author's syllabus and answers to even-numbered problems.</p><p>Intended for graduate or advanced undergraduate courses in categorical and nonparametric statistics taught in psychology education human development sociology political science and other social and life sciences.</p>