Think Bayes: Bayesian Statistics in Python (O'reilly)

Downey, Allen

ISBN 10: 149208946X / ISBN 13: 9781492089469

Verlag: O'Reilly Media, 2021

Beschreibung

Gut/Very good: Buch bzw. Schutzumschlag mit wenigen Gebrauchsspuren an Einband, Schutzumschlag oder Seiten. / Describes a book or dust jacket that does show some signs of wear on either the binding, dust jacket or pages.

Bestandsnummer des Verkäufers M0149208946X-V

Bibliografische Details

• Titel: Think Bayes: Bayesian Statistics in Python (O'reilly)
• Verlag: O'Reilly Media
• Erscheinungsjahr: 2021
• Sprache: Englisch
• ISBN-10: 149208946X
• ISBN-13: 9781492089469
• Einband: Softcover
• Auflage: 2. Auflage
• Zustand: very good

Über diesen Titel

Inhaltsangabe

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

Über die Autorin bzw. den Autor

Allen 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.