Bayes' Theorem Examples: A Visual Introduction For Beginners

It helped me understand what it means to think probabilistically. Takes pain to explain it in a simple language. The part on using Bayes for everyday decision making was brilliant. Using Odds instead of probabilities. It has useful links to blogs and videos throughout the book. Brilliant effort for the price. Thanks.

The booklet is easy to understand, and requires very little prior knowledge of the subject. Everything is explained in a visual manner.If you have even a basic understanding of the subject (from a class at your school, for example), then it is little more than a 10-minute review. However, this disclaimer is put forward right at the beginning of the booklet, and it is a little hard to argue with such a forthright attempt.

This book is one of the best introductory texts for those who want to learn Bayes's theorem and it's applications. The best part is it gives an idea of the profundity of the subject by listing practical applications of the theorem, while keeping the narrative simple and light.

It is definitely worth purchasingWhat an amazing book. It was such a pleasure reading the lucid and practical perspective of the content..... SUPERRRR

Never thought such a complex subject can be thought in such a simple layman language , loved it.

Beautifully explained

Served my purpose admirably.

Good book! This is a good book to understand Bayes theorem. All the problems posed have solutions and shown in terms of the formula and the visual diagram. This requires practicing with day-to-day examples from your real life. Identifying the four elements is the key. I applied to a few situations in business and could validate the outcome. There is no magic to tell you the future, but definitely gives you the confidence to take your hypothesis forward.

There is such a thing as an introduction to a subject... but this booklet (and it is small) is vying for the "Idiots guide" title. It is poorly written, some of examples are inane... and then although the book claims to be "packed with visual examples" -- some of these so-called visual examples are formulas written long-hand!And the book is so poorly formatted, e.g., pages with a single paragraph on them, no clear delineation of sections... It is a paper written on a web-based medium, but then printed...Don't waste your time with this.

A neat explanation of an important theorem used for answering questions of the form 'what is the probability of A being true given that B is true?'. The text is built around three examples that are analysed three times over in increasing detail. This short work shows why 'common sense' thinking can get you into deep trouble when looking at issues of probability. The maths is basic. Provided that you understand what a percentage (or a normalised value) is, you are likely to be fully equipped to understand this text. An excellent piece of writing that shows how maths does not have to be scary.

I've bumped into Bayes Theorem a few times, but never really found a structured approach to analysing the usual world problems such as 'a test shows...what's the probability that...'.This book does just that and takes you through a step by step process for classifying and approaching simple problems involving Bayes Rule. There are some excellent resources on the web (e.g. Google: Arbital guide to Bayes Rule with it's interesting waterfall diagram) but they never quite did it for me, mainly because they seemed to skip steps used to break apart such problems. This book, on the other hand, leads you through each step in explicit and detailed fashion. Essentially, it works by teaching you to map a problem onto simple diagrams and then onto the formal expression of the Theorem itself. This worked really well for me.So if you're willing to work through the examples piece by piece, you should pick up this wonderful little theorem in no time at all.

I enjoyed this book which in its straightforward, if slightly repetitive, style made Bayesian theory come to life. I would recommend it to anyone beginning a deeper exploration of stats but who wasn't yet confident enough to go to one of the many standard texts out there. The use of links to interesting and informative web pages was very helpful.I only have a few minor criticisms:1. The impression I gained from Dan Morris was that the use of Bayesian Theory was relatively new. Not true. I had the vague notion that it had some history and after looking up "Statistics and the Bayesian Mind" by Thomas Griffiths at the Royal Statistical Society was reminded that work had been done in the 1940s on the distribution of V1 and V2 rocket attacks on England during the latter half of World War 2. Bayesian theory was used to disprove the notion that these flying bombs were being used to target poorer, working class areas. [The paper itself makes interesting reading because it takes further then notion which Dan Morris starts to explore in the book, of human cognition and how we draw inferences from limited amounts of data which may (or may not) be true.]2. I would have liked to have seen more examples or been given examples to try myself.3. You would think a statistician would know the difference between countable and uncountable numbers but like many people Dan Morris doesn't understand when to use "number" and when to use "amount". Trivial, but annoying to a physicist!

If you’re looking for a book to explain Bayes in worked examples, be prepared to spend some time checking and correcting for arithmetical error in the illustrations. I can’t give page number references, because the paperback has none, however there’s some obvious basic multiplication errors in section 2.Basic errors in a beginners guide is a poor way to introduce a topic to anyone trying to learn. Fine perhaps if you’re just reading along, but if you’re keen to understand and work the examples then errors in the proofs just undermine confidence all round.Not the best introduction, Allen B Downey does a much better job, and so far no errors.