Think Bayes: Bayesian Statistics in Python
by: Allen B. Downey
Publisher finelybook 出版社: O’Reilly Media; 2nd edition (June 8,2021)
Language 语言: English
Print Length 页数: 338 pages
ISBN-10: 149208946X
ISBN-13: 9781492089469
Book Description
If you know how to program,you’re ready to tackle Bayesian statistics. With this book,you’ll learn how to solve statistical problems with Python code instead of mathematical formulas,using discrete probability distributions rather than continuous mathematics. Once you get the math out of the way,the Bayesian fundamentals will become clearer and you’ll begin to apply these techniques to real-world problems.
Bayesian statistical methods are becoming more common and more important,but there aren’t many resources available to help beginners. Based on undergraduate classes taught by author Allen B. Downey,this book’s computational approach helps you get a solid start.
• Use your programming skills to learn and understand Bayesian statistics
• Work with problems involving estimation,prediction,decision analysis,evidence,and Bayesian hypothesis testing
• Get started with simple examples,using coins,dice,and a bowl of cookies
• Learn computational methods for solving real-world problems Copyright
Table of Contents
Preface
Chapter 1. Probability
Chapter 2. Bayes’s Theorem
Chapter 3. Distributions
Chapter 4. Estimating Proportions
Chapter 5. Estimating Counts
Chapter 6. Odds and Addends
Chapter 7. Minimum,Maximum,and Mixture
Chapter 8. Poisson Processes
Chapter 9. Decision Analysis
Chapter 10. Testing
Chapter 11. Comparison
Chapter 12. Classification
Chapter 13. Inference
Chapter 14. Survival Analysis
Chapter 15. Mark and Recapture
Chapter 16. Logistic Regression
Chapter 17. Regression
Chapter 18. Conjugate Priors
Chapter 19. MCMC
Chapter 20. Approximate Bayesian Computation
Index
About the Author
Colophon
