Think Bayes: Bayesian Statistics in Python

This book teaches Bayesian statistics through Python code,using discrete probability distributions and focusing on real-world problems. It is ideal for beginners with programming skills who want to learn and understand Bayesian methods.

\n Format: Paperback / softback
\n Length: 300 pages
\n Publication date: 28 May 2021
\n Publisher: O'Reilly Media, Inc, USA
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Are you ready to take on the world of Bayesian statistics? With this comprehensive book, you'll learn how to solve statistical problems using Python code, bypassing complex mathematical formulas. Instead, you'll delve into discrete probability distributions, offering a fresh perspective on statistical analysis. Once you master the math, the Bayesian fundamentals will become more accessible, and you'll be able to apply these techniques to real-world problems.

Bayesian statistical methods are gaining prominence and significance, yet there are limited resources available for beginners. This book, based on undergraduate classes taught by author Allen B. Downey, offers a computational approach to help you get a solid start. By leveraging your programming skills, you'll gain a deep understanding of Bayesian statistics and be able to work with problems involving estimation, prediction, decision analysis, evidence, and Bayesian hypothesis testing.

Begin with simple examples, such as coins, dice, and a bowl of cookies, to grasp the fundamentals of Bayesian statistics. Then, progress to more complex real-world problems, learning computational methods to solve them effectively. Whether you're a data scientist, statistician, or simply interested in learning more about statistical analysis, this book is your ultimate guide. So, why wait? Unlock the power of Bayesian statistics and embark on a journey of discovery with this essential resource.

\n Weight: 578g\n
Dimension: 176 x 233 x 20 (mm)\n
ISBN-13: 9781492089469\n
Edition number: 2 ed\n