© 2001 – Psychology Press
Built around a problem solving theme, this book extends the intermediate and advanced student's expertise to more challenging situations that involve applying statistical methods to real-world problems. Data relevant to these problems are collected and analyzed to provide useful answers.
Building on its central problem-solving theme, a large number of data sets arising from real problems are contained in the text and in the exercises provided at the end of each chapter. Answers, or hints to providing answers, are provided in an appendix.
Concentrating largely on the established SPSS and the newer S-Plus statistical packages, the author provides a short, end-of-chapter section entitled Computer Hints that helps the student undertake the analyses reported in the chapter using these statistical packages.
"Students and researchers in psychology and other behavioral sciences, as well as those interested in related applications of statistics, could find this book a useful resource because of its mathematical display boxes, computer hints, easy-to-read narrative, and glossary of statistical terms, along with its practical advise and valuable insights."
—The American Statistician
"The author's illustrations of even complex statistical ideas via eloquent interpretations of the data results in the examples are outstanding features of this book…. Basic linear algebra is enough to read this book. Biostatisticians and health researchers should have this book in their collections."
—Journal of Statistical Computation and Simulation
Contents: Preface. Statistics in Psychology: Data, Models, and a Little History. Graphical Methods of Displaying Data. Analysis of Variance I: The One-Way Design. Analysis of Variance II: Factorial Designs. Analysis of Repeated Measure Designs. Simple Linear Regression and Multiple Regression Analysis. Analysis of Longitudinal Data. Distribution-Free and Computationally Intensive Methods. Analysis of Categorical Data I: Contingency Tables and the Chi-Square Test. Analysis of Categorical Data II: Log-Linear Models and Logistic Regression. Appendices: Statistical Glossary. Answers to Selected Exercises.