9780521594172 - Bayesian Methods: An Analysis for Statisticians and Interdisciplinary Researchers (Cambridge Series in Statistical and Probabilistic Mathematics) von Leonard, Thoma... (6 Ergebnisse)

Zustand: Very Good. Former library copy. Pages intact with possible writing/highlighting. Binding strong with minor wear. Dust jackets/supplements may not be included. Includes library markings. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good.

Hardcover. Zustand: Good. Ex-library. Text unmarked, sound binding.

Zustand: New. In.

Zustand: New. Bayesian statistics directed towards mainstream statistics. How to infer scientific, medical, and social conclusions from numerical data. Series: Cambridge Series in Statistical and Probabilistic Mathematics. Num Pages: 348 pages, 69 b/w illus. 27 tables 150 exercises. BIC Classification: PBT. Category: (P) Professional & Scholarly; (U) Tertiary Education (US: College). Dimension: 253 x 177 x 21. Weight in Grams: 844. . 1999. Illustrated. hardcover. . . . . Books ship from the US and Ireland.

Zustand: Sehr gut. Zustand: Sehr gut | Seiten: 348 | Sprache: Englisch | Produktart: Bücher | Bayesian statistics directed towards mainstream statistics. How to infer scientific, medical, and social conclusions from numerical data.

Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book describes the Bayesian approach to statistics at a level suitable for final year undergraduate and Masters students. It is unusual in presenting Bayesian statistics with a practical flavor and an emphasis on mainstream statistics, showing how to infer scientific, medical, and social conclusions from numerical data. The authors draw on many years of experience with practical and research programs and describe many statistical methods, not readily available elsewhere. A first chapter on Fisherian methods, together with a strong overall emphasis on likelihood, makes the text suitable for mainstream statistics courses whose instructors wish to follow mixed or comparative philosophies. The other chapters contain important sections relating to many areas of statistics such as the linear model, categorical data analysis, time series and forecasting, mixture models, survival analysis, Bayesian smoothing, and non-linear random effects models. The text includes a large number of practical examples, worked examples, and exercises. It will be essential reading for all statisticians, statistics students, and related interdisciplinary researchers.