``Outstanding....Represents a new era in the learning and reporting of statistics in the behavioral sciences. Thompson focuses on analytic thinking rather than mathematical number-crunching, unlike others who emphasize calculations at the expense of critical thinking.`` -Robin K. Henson,
Department of Technology and Cognition, University of North Texas
``This book treats many important topics that are ignored in most statistics books. Examples include the limitations of statistical significance tests, the importance of effect size indices, the important role of distribution shapes in determining ceilings on linear relationships, problems of capitalization on sampling error in stepwise regression, and many, many others.``
-Frank L. Schmidt,
College of Business, University of lowa
``There are a lot of quite simple introductory statistics texts out there (`too cold!`), and a large number of really comprehensive ones, perhaps best digested over two semesters (`too hot!`)....I found Thompson`s treatment and coverage to be `just right!```
-Bruce Thyer,
College of Social Work, Florida State University
``This book will encourage both students and experienced researchers to`think through` the process, critically examine their hypotheses, and choose the statistical method best suited to their theory.``
-Victoria Rodlin,
Statistical Consultant (former faculty, Department of Psychology, California State University, Fullerton)
``One of the most readable serious statistics books I have seen.``
-Kenneth A. Wallston,
School of Nursing, Vanderbilt University
WITH HUMOR, EXTRAORDINARY CLARITY, AND CAREFULLY PACED EXPLANATIONS AND EXAMPLES, BRUCE THOMPSON shows readers how to use the latest techniques for interpreting research outcomes as well as how to make statistical decisions that result in better research. Utilizing the general linear model to demonstrate how different statistical methods are related to each other, Thompson integrates a broad array of methods involving only a single dependent variable, ranging from classical and robust location descriptive statistics, through effect sizes, and on through ANOVA, multiple regression, loglinear analysis and logistic regression. Special features include SPSS and Excel demonstrations that offer opportunities, in the book`s datasets and on Thompson`s website, for further exploration of statistical dynamics.
