Analysis of Variance and Covariance: How to Choose and Construct Models for the Life Sciences [Hardcover]

A concise, systematic introduction to the principles of analysis of variance for post-graduates and professionals.A concise introduction to the principles of analysis of variance and covariance with worked examples. It bridges the gap between statistical theory and practical data analysis by presenting a comprehensive set of tables for all standard models of analysis of variance and covariance. An essential reference for post-graduates and professionals.A concise introduction to the principles of analysis of variance and covariance with worked examples. It bridges the gap between statistical theory and practical data analysis by presenting a comprehensive set of tables for all standard models of analysis of variance and covariance. An essential reference for post-graduates and professionals.Analysis of variance (ANOVA) is a core technique for analysing data in the Life Sciences. This reference book bridges the gap between statistical theory and practical data analysis by presenting a comprehensive set of tables for all standard models of analysis of variance and covariance with up to three treatment factors. The book will serve as a tool to help post-graduates and professionals define their hypotheses, design appropriate experiments, translate them into a statistical model, validate the output from statistics packages and verify results. The systematic layout makes it easy for readers to identify which types of model best fit the themes they are investigating, and to evaluate the strengths and weaknesses of alternative experimental designs. In addition, a concise introduction to the principles of analysis of variance and covariance is provided, alongside worked examples illustrating issues and decisions faced by analysts.Preface; Introduction to analysis of variance; Introduction to model structures; Part I. Model Structures: 1. One-factor designs; 2. Nested designs; 3. Fully replicated factorial designs; 4. Randomised block designs; 5. Split plot designs; 6. Repealsg