Using humour, extraordinary clarity, and carefully placed explanations and examples, Thompson leads readers to the cutting edge of interpreting research outcomes and teaches how to make the statistical decisions that result in better research. Through the use of the general linear model to show how different statistical methods are related to each other, Thompson conceptually integrates the book's coverage of 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 tips for the best analytic strategies for a particular design or research question, advice on how to correct for statistical bias, and attention to thorny issues such as the limitations of statistical significance tests and the importance of various effect size indices and confidence intervals. In addition, Thompson maintains a website offering data and program syntax files for many of the research examples, additional data sets to provide extra practice opportunities, electronic overheads that can be downloaded and printed by instructors or students, and links to related resources.