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Think Bayes /
Annotation
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Sebastopol, CA :
O'Reilly,
©2013.
|
| Temas: | |
| Acceso en línea: | Texto completo (Requiere registro previo con correo institucional) |
MARC
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| 082 | 0 | 4 | |a 519.54202855133 |2 23 |
| 049 | |a UAMI | ||
| 100 | 1 | |a Downey, Allen. | |
| 245 | 1 | 0 | |a Think Bayes / |c Allen B. Downey. |
| 260 | |a Sebastopol, CA : |b O'Reilly, |c ©2013. | ||
| 300 | |a 1 online resource (1 volume) : |b illustrations | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 347 | |a text file | ||
| 588 | 0 | |a Online resource; title from title page (Safari, viewed November 12, 2013). | |
| 504 | |a Includes bibliographical references and index. | ||
| 520 | 8 | |a Annotation |b If you know how to program with Python and also know a little about probability, youre 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 of continuous mathematics. Once you get the math out of the way, the Bayesian fundamentals will become clearer, and youll begin to apply these techniques to real-world problems. 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 books computational approach helps you get a solid start. Use your existing programming skills to learn and understand Bayesian statisticsWork with problems involving estimation, prediction, decision analysis, evidence, and hypothesis testingGet started with simple examples, using coins, M & Ms, Dungeons & Dragons dice, paintball, and hockeyLearn computational methods for solving real-world problems, such as interpreting SAT scores, simulating kidney tumors, and modeling the human microbiome. | |
| 505 | 0 | |a Bayes's theorem -- Computational statistics -- Estimation -- More estimation -- Odds and addends -- Decision analysis -- Prediction -- Observer bias -- Two dimensions -- Approximate Bayesian computation -- Hypothesis testing -- Evidence -- Simulation -- A hierarchical model -- Dealing with dimensions. | |
| 590 | |a O'Reilly |b O'Reilly Online Learning: Academic/Public Library Edition | ||
| 650 | 0 | |a Bayesian statistical decision theory. | |
| 650 | 6 | |a Théorie de la décision bayésienne. | |
| 650 | 1 | 7 | |a Bayesian statistical decision theory |x Data processing. |2 bisacsh |
| 650 | 7 | |a Bayesian statistical decision theory |2 fast | |
| 776 | 0 | 8 | |i Print version: |a Downey, Allen. |t Think Bayes. |b First edition. |d Sebastopol, CA : O'Reilly, 2013 |w (DLC) 2015431605 |
| 856 | 4 | 0 | |u https://learning.oreilly.com/library/view/~/9781491945407/?ar |z Texto completo (Requiere registro previo con correo institucional) |
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