Common Errors in Statistics

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Praise for the First Edition highlights its broad appeal to anyone interacting with statistics, regardless of their expertise. The book serves as a guide for those who define good statistical practice, making it a valuable reference for statisticians and researchers alike. Readers have found it highly informative and enjoyable, with particular commendation for its readability. Now in its Second Edition, this guide provides a mathematically rigorous yet accessible foundation for understanding statistical procedures and solutions. It analyzes common mistakes, debunks myths, and assists readers in selecting the most effective statistical techniques for their tasks. Targeted at both new academics and professionals, it covers essential topics such as research planning, hypothesis formulation, sample size specification, assumption checking, p-value interpretation, model building, data mining, and Bayes' Theorem. The extensively revised Second Edition includes additional charts and graphs, two new chapters—Interpreting Reports and Which Regression Method?—and sections on practical versus statistical significance and nonuniqueness in multivariate regression. It also incorporates material from the authors' online courses and addresses unbalanced designs and alternative modeling methods. Emphasizing the value of statistics when applied correctly, this book is an essential resource for students and professionals in research, industry,