## Book description

If you know how to program with Python, and know a little about probability, you’re ready to tackle Bayesian statistics. This book shows you how to use Python code instead of math to help you learn Bayesian fundamentals. Once you get the math out of the way, you’ll be able to apply these techniques to real-world problems.

## Publisher resources

## Table of contents

- Preface
- 1. Bayes’s Theorem
- 2. Computational Statistics
- 3. Estimation
- 4. More Estimation
- 5. Odds and Addends
- 6. Decision Analysis
- 7. Prediction
- 8. Observer Bias
- 9. Two Dimensions
- 10. Approximate Bayesian Computation
- 11. Hypothesis Testing
- 12. Evidence
- 13. Simulation
- 14. A Hierarchical Model
- 15. Dealing with Dimensions
- Index
- Colophon
- Copyright

## Product information

- Title: Think Bayes
- Author(s):
- Release date: September 2013
- Publisher(s): O'Reilly Media, Inc.
- ISBN: 9781449370787

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