Think Bayes
 Author/Creator
 Downey, Allen, author.
 Language
 English.
 Edition
 First edition.
 Publication
 Beijing : O'Reilly, 2013.
 Physical description
 xv, 190 pages : illustrations ; 24 cm
Access
Available online

Stacks

Unknown
QA279.5 .D698 2013

Unknown
QA279.5 .D698 2013
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Contents/Summary
 Publisher's Summary
 If you know how to program with Python and also know a little about probability, you'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 you'll begin to apply these techniques to realworld 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 book'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 realworld problems, such as interpreting SAT scores, simulating kidney tumors, and modeling the human microbiome.
(source: Nielsen Book Data)
Subjects
Bibliographic information
 Publication date
 2013
 Responsibility
 Allen B. Downey.
 Note
 "Bayesian statistics in Python"Cover.
 Includes index.
 ISBN
 9781449370787 (Pbk.)
 1449370780 (Pbk.)