Think Bayes
If you know how to program with Python and also know a little about probability, you're ready to tackle Bayesian statistics. With this book, you'll learn how to solve statistical problems with Python code instead of mathematical notation, and use discrete probability distributions instead...
| Autor principal: | |
|---|---|
| Formato: | Libro electrónico |
| Idioma: | Inglés |
| Publicado: |
Sebastopol, California :
O'Reilly & Associates
2013.
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| Edición: | 1st edition |
| Materias: | |
| Ver en Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009629475406719 |
Tabla de Contenidos:
- 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
