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Bayesian Methods for Statistical Analysis
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  • Title: Bayesian Methods for Statistical Analysis
  • Author(s) Borek Puza
  • Publisher: ANU Press (September 15, 2017)
  • License(s): Creative Commons
  • Paperback: 698 pages
  • eBook: PDF (697 pages, 6.4 MB)
  • Language: English
  • ISBN-10/ASIN: 1921934255
  • ISBN-13: 978-1921934254
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Book Description

Bayesian methods for statistical analysis is a book on statistical methods for analysing a wide variety of data. The book consists of 12 chapters, starting with basic concepts and covering numerous topics, including Bayesian estimation, decision theory, prediction, hypothesis testing, hierarchical models, Markov chain Monte Carlo methods, finite population inference, biased sampling and nonignorable nonresponse.

The book contains many exercises, all with worked solutions, including complete computer code. It is suitable for self-study or a semester-long course, with three hours of lectures and one tutorial per week for 13 weeks.

About the Authors
  • Dr Borek Puza teaches Statistics in the Research School of Finance, Actuarial Studies and Statistics. He has a BSc in Mathematics and a Graduate Diploma, Masters and PhD in Statistics.
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