Bayesian Methods : An Analysis for Statisticians and Interdisciplinary Researchers

Thomas Leonard

ISBN 10: 0521004144 / ISBN 13: 9780521004145

Published by Cambridge University Press, 2001

About this Item

Druck auf Anfrage Neuware - Printed after ordering - This exposition of the Bayesian approach to statistics at a level suitable for final year undergraduate and Masters students is unique in presenting its subject with a practical flavor and an emphasis on mainstream statistics. It shows 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 new statistical methods, not available elsewhere. It will be essential reading for all statisticians, statistics students, and related interdisciplinary researchers.

Seller Inventory # 9780521004145

Bibliographic Details

• Title: Bayesian Methods : An Analysis for Statisticians and Interdisciplinary Researchers
• Publisher: Cambridge University Press
• Publication Date: 2001
• Language: English
• ISBN 10: 0521004144
• ISBN 13: 9780521004145
• Binding: Taschenbuch
• Condition: Neu

About this title

Synopsis

This exposition of the Bayesian approach to statistics at a level suitable for final year undergraduate and Masters students is unique in presenting its subject with a practical flavor and an emphasis on mainstream statistics. It shows 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 new statistical methods, not available elsewhere. It will be essential reading for all statisticians, statistics students, and related interdisciplinary researchers.

Book Description

This book describes the Bayesian approach to statistics at a level suitable for final year undergraduate and Masters students. The first chapter presents a comparison with traditional Fisherian methods. Subsequent chapters relate Bayesian methods to many areas of statistics, for instance, 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.