Think Bayes
Bayesian statistical methods are becoming more common and more important, but not many resources are available to help beginners. Based on undergraduate classes taught by author Allen Downey, this book's computational approach helps you get a solid start.
Use your existing programming skills to learn and understand Bayesian statistics; Work with problems involving estimation, prediction, decision analysis, evidence, and hypothesis testing; Get started with simple examples, using coins, M&Ms, Dungeons & Dragons dice, paintball, and hockey; Learn computational methods for solving real-world problems, such as interpreting SAT scores, simulating kidney tumors, and modeling the human microbiome.
Table of contents
- Bayess Theorem
- Computational Statistics
- Estimation
- More Estimation
- Odds and Addends
- Decision Analysis
- Prediction
- Observer Bias
- Approximate Bayesian Computation
- Hypothesis Testing
- Evidence
- Simulation
- A Hierarchical Model
- Dealing with Dimensions
| Pages : | 213 |
| Size : | 2.9 MB |
| File type : | |
| Downloads: | 62 |
| Created: | 2022-02-03 |
| License: | CC BY-NC |
| Author(s): | Allen Downey |
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