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Think Bayes: Bayesian Statistics in Python
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Librairie Eyrolles - Paris 5e
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Think Bayes: Bayesian Statistics in Python

Think Bayes: Bayesian Statistics in Python

Allen Downey

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300 pages, parution le 27/05/2021
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Résumé

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.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 not many resources are 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 problemsAllen Downey is a Professor of Computer Science at the Olin College of Engineering. He has taught computer science at Wellesley College, Colby College and U.C. Berkeley. He has a Ph.D. in Computer Science from U.C. Berkeley and Master's and Bachelor's degrees from MIT. He is author of Think Python, Think Bayes, Think DSP, and a blog, Probably Overthinking It.

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Éditeur(s) O'Reilly
Auteur(s) Allen Downey
Parution 27/05/2021
Nb. de pages 300
EAN13 9781492089469

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