Count Bayesie's Recommended Books in Probability and Statistics

My book on probability and statistics is out July 2019!

My book on probability and statistics is out July 2019!

Bayesian Statistics the Fun Way is out soon!

If you enjoy reading this blog I really think you’ll love my book “Bayesian Statistics the Fun Way” published by No Starch. The book is designed so that anyone can dive in and learn the basics of Bayesian statistics. Even if the math in this blog is sometimes a bit too much for you, all you need to get started is basic high school algebra. The book starts with a tour of probability as logic, the move on to conditional probabilities and Bayes’ theorem, the on to parameter estimation and hypothesis testing. It includes completely reworked posts from this blog and a ton of new content! If you order from No Starch you can get a free ebook with your print copy (or just order to ebook) or you can order on Amazon, or pick it up at your local book store!

Other great books I recommend

A question I often get is "How did you learn all this stuff?" and the honest answer is: reading. This page is a list of books I've read over the years. I've broken them down by category to help you find what you may need, this includes various mathematical prerequisites.

After “Bayesian Statistics the Fun Way”

These books are great next steps in your journey to learn Bayesian statistics!

By Richard McElreath

So, unlike most of my recommendations, I actually haven’t gotten a chance to read this yet, but it’s absolutely next on my list. I’m currently working through the lectures online and everything so far seems really excellent. Everyone who has read this book has told me it’s amazing and I really think this is the next logical step after “Bayesian Statistics the Fun Way”. The amount of supporting materials that McElreath has on the linked site is phenomenal and I know it has an update coming soon.

Bayesian Analysis with Python

By Osvaldo Martin

I had been wanting to read this book for a long time as Osvaldo had been working on at the same time I was writing my book. This is a really great introduction to using PyMC3, a probabilistic programming frame work for Python, to perform Bayesian Data Analysis. Probabilistic programming is an essential part of advanced Bayesian analysis. This is another great next step to go after “Bayesian Statistics the Fun Way”

Advanced Bayesian Statistics

Once you have a solid foundation in Bayesian stats these are some really excellent books to help you dive really deep into Bayesian probability and statistics.

Probability Theory: The Logic of Science

By E.T. Jaynes

This is the book on Bayesian analysis. I really recommend getting a strong foundation in probability and statistics before diving in, only because you'll enjoy it that much more. Jaynes doesn't assume that Bayesian analysis is just an evolution of Classical statistics, but rather starts from first principles and builds it up as a form of logic. This is one of the most important books I have read, period. It is also in that category of books that are never truly "finished" because you could easily spend a life time on a single chapter.

Bayesian Data Analysis

By Andrew Gelman, et al.

This is a tremendous work on theoretical statistics if, as Andrew Gelman phrased it, “theoretical statistics was the theory of applies statistics”. This book used to be recommend by anyone doing Bayesian analysis because it was really the only major, comprehensive work on the subject. This book is brilliant, but it is also fairly challenging. Everyone doing Bayesian stats should have a copy of this on their desk. I use mine very frequently. That said, this is not a book you sit and read cover to cover easily. McElreath’s and Martin’s books are better places to get introduce into serious Bayesian stats. However nothing changes this books place as a true classic!