Think Bayes : Bayesian Statistics in Python

Allen B. Downey

ISBN 10: 149208946X / ISBN 13: 9781492089469

Editore: O'reilly Media Jun 2021, 2021

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Neuware - 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.

Codice articolo 9781492089469

Dati bibliografici

• Titolo: Think Bayes : Bayesian Statistics in Python
• Editore: O'reilly Media Jun 2021
• Data di pubblicazione: 2021
• Lingua: Inglese
• ISBN 10: 149208946X
• ISBN 13: 9781492089469
• Rilegatura: Taschenbuch
• Edizione: seconda edizione
• Condizione: Neu
• Dimensioni: 230 L x 174 A x 19 P (millimetri) 230 millimetri di larghezza per 174 millimetri di altezza per 19 millimetri di profondità
• Peso: 586 grammi

Descrizione articolo

Riassunto

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 there aren't many resources 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 problems

Informazioni sull?autore

Allen Downey is a Professor of Computer Science at 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 the author of Think Python, Think Bayes, Think DSP, and a blog, Probably Overthinking It.