Bayes Theorem Examples

by Scott Hartshorn

Bayes theorem describes the probability of an event based on other information that might be relevant. Essentially, you are estimating a probability, but then updating that estimate based on other things that you know. This book is designed to give you an intuitive understanding of how to use Bayes Theorem. It starts with the definition of what Bayes Theorem is, but the focus of the book is on providing examples that you can follow and duplicate. Most of the examples are calculated in Excel, which is useful for updating probability if you have dozens or hundreds of data points to roll in.

Genres: Science, Nonfiction, Technology

Kindle Edition

First published January 22, 2016

Reviews

[Sundar · Rating 4 out of 5]

After being impressed with the author's other guide on Probability (my review), I bought this ebook too with high hopes. It seemed to follow a different approach here, directly starting with the equation instead of intuition. I was losing hope when the author followed it up with the intuition for the components.

Bayes Theorem can be counter-intuitive for most people and the author has done a good job of driving the intuition as well as solve problems in this space. In order to make the learning durable, it's best to start applying as soon as one completes the book.

[Roberto Rigolin F Lopes · Rating 3 out of 5]

Practical, simple and straight to the point introduction to Bayes theorem. You can even download all the examples to play with numbers. Our intuition fails miserably when several occurrences of the same event happens; quite useful theorem.

[Brent · Rating 4 out of 5]

Good Succinct Review

This book gives a very good and quite succinct review of Bayes' Theorem with useful and easily understood examples laid out in tables and graphs showing both inputs and outputs. Several examples are shown using Excel (which are easily translatable to other spreadsheet programs). Useful for anyone who has heard of Bayes' Theorem but isn't quite sure what it is or whether it might be useful to them.

[Rodrigo · Rating 5 out of 5]

Scott’s book offers a fantastic introduction to Bayes’ Theorem. It simplifies complex ideas so effectively that even children can grasp them. Scott’s engaging writing style and the relatable examples he uses make the book a captivating read, especially for statistics enthusiasts. You’ll likely breeze through it in no time!

[Robert · Rating 3 out of 5]

Good introduction

Solid introduction. Likely requires a couple readings or an accompaniment; or, reader could follow offline and do the exercises. Overall: good.

[Darko Doko · Rating 5 out of 5]

Easy examples but have to it alone..or read some more

[Dwayne Roberts · Rating 3 out of 5]

Pretty good. The book would be improved with some editing. Misspelled words and missing punctuation distract. Also I expected a discussion of the Monte Hall problem, and was surprised at its absence.

[Kenneth E Mayer · Rating 5 out of 5]

Great summary of Bayes Theorem

This was a pretty good summary of Bayes. It took me about 90 minutes to go through the book. The excel sheets from the web are helpful.

[Bálint · Rating 2 out of 5]

First example is absolutely fantastic, then it speeds up and I lost track, so I can't comment on those. More typos than expected, but not that big deal.

[Vyacheslav Ilnytskyy · Rating 1 out of 5]

Awful. Standard examples from the internet, where authors explanation and interpretation is vague and confusing

[Mark Schulz · Rating 5 out of 5]

Bayes for beginners

A clear introduction to applications of Bayes theorem with recommended readings for those who want to dive deeper. Think Bayes is now a great read to follow this.