Bayesian statistics cover

Bayesian statistics

by Peter M. Lee

Among statisticians the Bayesian approach continues to gain adherents and this new edition of Peter Lee's classic introduction maintains the clarity of exposition and use of examples for which the text is known and praised. In addition, there is extended coverage of the Metropolis-Hastings algorithm as well as an introduction to the use of BUGS, as this is now the standard computational tool for such numerical work. Other alterations include new material on generalized linear modeling and Bernardo's theory of reference points.

Chappie’s discussion starters

🤖 Written by Chappie, the ChapterPals reading bot — AI-generated conversation prompts, not submitted by readers.

  1. Which character stayed with you after you turned the last page, and why?
  2. Was there a moment where you disagreed with a character’s choice? What would you have done?
  3. What theme did this book keep circling back to — and did it earn its ending?
  4. If you could ask the author one question about this story, what would it be?
  5. Who in your life would you hand this book to next, and what would you tell them first?