James V. Stone

For anyone needing an introduction (or a refresher) on Bayes' Theorem, Bayes Rule is a fine choice. The book is comprised of seven brief chapters, discussing not only Bayes' Theorem, history, and application, but basic probability as well. Most of the nine separate Appendices at the end of the book (Glossary; Mathematical Symbols; The Rules of Probability; Probability Density Functions; The Binomial Distribution; The Gaussian distribution; Least-Squares Estimation; Reference Priors; and MatLab Code) are also quite valuable. The References section is good, though limited to books published up to 2012 owing to this volume's own 2013 publication date.… (más)

Eggzellent stuff!

What a great intro to a subject I found fascinating and is widely applicable: Digital communications, computing, neuro-science and other biological sciences, linguistics (a favourite) and then there's my secret application that made me want to read the book in the first place...but you won't find it in the book.

There is a proper glossary of technical terms, something that long term readers of my reviews know I think is essential and yet all too frequently absent. There are also appendices on various topics in probability and statistics that are relevant and you may be unfamiliar with or in need of a quick refresher about. This is also good textbook writing, in my view, as is including XKCD cartoons (with permission). The latter are even relevant!

I found it straightforward to follow what was going on despite having been solidly rebuffed by my previous encounters with the subject. I think this is mainly because some opaque terminology is properly and thoroughly defined and explained and put into a practical context as soon as possible.

I strongly recommend this if you ever have a need to learn the basics of the subject and thanks to whomever recommended it to me!
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Information Theory A Tutorial Introduction is a thrilling foray into the world of Information Theory by James V Stone. It starts with the basics of telling you what information is and is not. Now, although this is a tutorial of this subject, Information Theory is a subtle and difficult concept. Other people might get it, but for me, it is taking a while to understand even with this book.

The book is divided into chapters and further subdivided into sections. At the end of each section are Key Concepts. This makes it easier to digest the main idea of that section. The book contains plenty of examples and calculations that you can follow along with.

My main sticking point with the idea of Information is mostly the concept of Entropy. Rather than measuring information directly, it measures the amount of uncertainty inherent in a message. So the book talks about Probability Distribution Functions, Shannon Uncertainty, Error Correction Codes and so on. It doesn’t really start where Claude Shannon did, but Shannon didn’t have to introduce that much background to the people he was writing for.

The appendices contain a glossary, a grounding in Logarithms, a collection of pertinent equations and so on. The book is enjoyable, but as I mentioned before I might have to read it again to understand all of what is in this Theory.… (más)

Bayes’ Rule: A Tutorial Introduction to Bayesian Analysis is a book that delivers what it promises on the cover. James V Stone really went out of his way to repetitively state and restate the theory and application of Bayes’ Rule. Along with tons of examples, there is also a lesson on re-framing questions to make them more applicable to what the person wants to know.

For instance, just for the sake of argument, let’s say that Smallpox wasn’t eradicated back in the 1970s and is still alive and well. If a patient comes into a doctor’s office and has spots or a rash on their person, what is the chance that they have Smallpox given the symptoms? We can use Bayesian Analysis to figure it out if we know those values. It’s actually pretty neat. Of course, you have to know the numbers.

The book has lots of pictures, plenty of equations, a MatLab program you can copy down and a lot of other things going for it. Despite its length, it does cover the subject pretty well, and it doesn’t meander too far into other ideas or situations. It talks about biased coins, the probability of something being said given a particular waveform, binomial distributions, and other such wonderful topics. In addition, the book explains the terms used really well, has a great glossary at the end and contains a bibliography and suggestions for further reading.

So if you are interested in this matter this book is really well done, although it does get a bit heavy-handed telling you where you can skip some portions.… (más)