Think Bayes: Bayesian Statistics in Python

Downey, Allen B.

ISBN 10: 1449370780 / ISBN 13: 9781449370787

Published by O'Reilly Media, 2013

About this Item

This copy has clearly been enjoyedâ expect noticeable shelf wear and some minor creases to the cover. Binding is strong, and all pages are legible. May contain previous library markings or stamps.

Seller Inventory # DBV.1449370780.A

Bibliographic Details

• Title: Think Bayes: Bayesian Statistics in Python
• Publisher: O'Reilly Media
• Publication Date: 2013
• Language: English
• ISBN 10: 1449370780
• ISBN 13: 9781449370787
• Binding: Soft cover
• Condition: acceptable

About this title

Synopsis

If you know how to program with Python and also know a little about probability, youâ??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 of continuous mathematics. Once you get the math out of the way, the Bayesian fundamentals will become clearer, and youâ??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 Downey, this bookâ??s computational approach helps you get a solid start.

• Use your existing programming skills to learn and understand Bayesian statistics
• Work with problems involving estimation, prediction, decision analysis, evidence, and hypothesis testing
• Get started with simple examples, using coins, M&Ms, Dungeons & Dragons dice, paintball, and hockey
• Learn computational methods for solving real-world problems, such as interpreting SAT scores, simulating kidney tumors, and modeling the human microbiome.

About the Author

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.