9780521865623 - Analysis of Variance and Covariance: How to Choose and Construct Models for the Life Sciences von Doncaster, C. Patrick; Davey, Andrew J. H. (6 Ergebnisse)

Zustand: New.

Zustand: New. In.

Zustand: Gut. Zustand: Gut | Seiten: 304 | Sprache: Englisch | Produktart: Bücher | Analysis of variance (ANOVA) is a core technique for analysing data in the Life Sciences. In this reference book, the gap between statistical theory and practical data analysis is bridged by presenting a comprehensive set of tables for all standard models of analysis of variance and covariance with up to three treatment factors. This 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.

Hardcover. Zustand: Brand New. 1st edition. 287 pages. 9.00x6.25x0.75 inches. In Stock.

Zustand: New. A concise, systematic introduction to the principles of analysis of variance for post-graduates and professionals. Num Pages: 304 pages, 62 b/w illus. 95 tables. BIC Classification: PSB. Category: (P) Professional & Vocational; (U) Tertiary Education (US: College). Dimension: 230 x 159 x 19. Weight in Grams: 606. . 2007. 1st Edition. hardcover. . . . . Books ship from the US and Ireland.

Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Analysis of variance (ANOVA) is a core technique for analysing data in the Life Sciences. In this reference book, the gap between statistical theory and practical data analysis is bridged by presenting a comprehensive set of tables for all standard models of analysis of variance and covariance with up to three treatment factors. This 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.