Feedback

X

Think Bayes: Bayesian Statistics Made Simple

en

32 Ungluers have Faved this Work
Think Bayes is an introduction to Bayesian statistics using computational methods.

The premise of this book, and the other books in the Think X series, is that if you know how to program, you can use that skill to learn other topics.

Most books on Bayesian statistics use mathematical notation and present ideas in terms of mathematical concepts like calculus. This book uses Python code instead of math, and discrete approximations instead of continuous mathematics. As a result, what would be an integral in a math book becomes a summation, and most operations on probability distributions are simple loops.

The author thinks this presentation is easier to understand, at least for people with programming skills. It is also more general, because when we make modeling decisions, we can choose the most appropriate model without worrying too much about whether the model lends itself to conventional analysis. Also, it provides a smooth development path from simple examples to real-world problems.

Order print editions of Think Bayes from Green Tea Press

Why read this book? Have your say.

You must be logged in to comment.

Rights Information

Are you the author or publisher of this work? If so, you can claim it as yours by registering as an Unglue.it rights holder.

Downloads

This work has been downloaded 1736 times via unglue.it ebook links.
  1. 1736 - pdf (CC BY-NC) at Internet Archive.

Keywords

  • Bayesian statistical decision theory
  • Mathematics
  • Nonfiction
  • Statistics

Editions

edition cover
edition cover
edition cover
edition cover
edition cover
edition cover

Share

Copy/paste this into your site: