Bayesian Methods - An Analysis for Statisticians and Interdisciplinary Researchers

Bayesian statistics directed towards mainstream statistics. How to infer scientific, medical, and social conclusions from numerical data.

List of contents

1. Introductory statistical concepts; 2. The discrete version of Bayes' theorem; 3. Models with a single unknown parameter; 4. The expected utility hypothesis and its alternatives; 5. Models with several unknown parameters; 6. Prior structures, posterior smoothing, and Bayes-Stein estimation; Guide to worked examples; Guide to self-study exercises.

Summary

Describes the Bayesian approach to statistics at a level suitable for final year undergraduate and Masters students as well as statistical and interdisciplinary researchers. It is unusual in presenting Bayesian statistics with an emphasis on mainstream statistics, showing how to infer scientific, medical, and social conclusions from numerical data.

Product details

• Authors: John S. J. Hsu, John S.J. Hsu, Thomas Leonard
• Assisted by: R. Gill (Editor)
• Publisher: Cambridge University Press
• Languages: English
• Product format: Hardback
• Released: 31.12.2017
• EAN: 9780521594172
• ISBN: 978-0-521-59417-2
• No. of pages: 348
• Dimensions: 183 mm x 260 mm x 23 mm
• Weight: 850 g
• Series: Cambridge Series in Statistical and Probabilistic Mathematics; Cambridge Series in Statistica; Cambridge Series in Statistical and Probabilistic Mathematics
• Subject: Natural sciences, medicine, IT, technology > Mathematics > Probability theory, stochastic theory, mathematical statistics