Information Theory: a tutorial introduction

Information Theory: a tutorial introduction - James V. Stone ***

Information theory is central to the technology that we use every day - apart from anything else, in the technology that brings you this review (though ironically not in the book being reviewed as it doesn't appear to have an ebook version). As in his Bayes' Rule, James Stone sets out to walk a fine line between a title for the general reader and a textbook. And like that companion title the outcome is mixed, though here the textbook side largely wins.

The opening chapter 'What is information?' walks the line very well. It gradually builds up the basics that will be required to understand information theory and though it would work better if it had a little more context (for example, more about Claude Shannon as a person) to anchor it, the general reader will, with perhaps a few pages that needs re-reading, find it approachable and providing more depth than a popular science title usually would. I like the way that Stone uses variants of a photograph, for instance, to demonstrate what is happening with different mechanisms for compressing data. Unfortunately, though, this is pretty much where that general reader gets off, until we get to chapter 9.

The main bulk of the book, pages 21 to 184, cross that line and plonk solidly into textbook territory - they may cover the topic rather more lightly than a traditional textbook, but they simply don't work to inform without requiring the kind of investment of mind and mathematics that a textbook does - and, with a few brief exceptions, the writing style feels no different from the better textbooks I have from university. At chapter 9, the subject is brought round to information in nature, and there we get enough application and context to make what we learn seem more approachable again, though not to the same level as the equivalent part of Bayes' Rule. It's also a shame that (unless I missed it) there is no mention of Omega, Greg Chaitin's remarkable non-computable number.

So where Bayes' Rule is suited to popular science readers who want to stretch themselves and put in some extra effort, Information Theory can only really be regarded as a readable introductory textbook - it doesn't work in a popular science context. (Why then am I reviewing it? The author kindly provided the title for review in the hope that it would work for popular science readers.) If you are about to take a university course encompassing information theory - or are contemplating doing so - I can, however, heartily recommend this title as an introduction.

Paperback:

Using these links earns us commission at no cost to you

Buy direct from the author here.

Review by Brian Clegg

Comments

The Genetic Book of the Dead: Richard Dawkins ****

When someone came up with the title for this book they were probably thinking deep cultural echoes - I suspect I'm not the only Robert Rankin fan in whom it raised a smile instead, thinking of The Suburban Book of the Dead . That aside, this is a glossy and engaging book showing how physical makeup (phenotype), behaviour and more tell us about the past, with the messenger being (inevitably, this being Richard Dawkins) the genes. Worthy of comment straight away are the illustrations - this is one of the best illustrated science books I've ever come across. Generally illustrations are either an afterthought, or the book is heavily illustrated and the text is really just an accompaniment to the pictures. Here the full colour images tie in directly to the text. They are not asides, but are 'read' with the text by placing them strategically so the picture is directly with the text that refers to it. Many are photographs, though some are effective paintings by Jana Lenzová. T

Everything is Predictable - Tom Chivers *****

There's a stereotype of computer users: Mac users are creative and cool, while PC users are businesslike and unimaginative. Less well-known is that the world of statistics has an equivalent division. Bayesians are the Mac users of the stats world, where frequentists are the PC people. This book sets out to show why Bayesians are not just cool, but also mostly right. Tom Chivers does an excellent job of giving us some historical background, then dives into two key aspects of the use of statistics. These are in science, where the standard approach is frequentist and Bayes only creeps into a few specific applications, such as the accuracy of medical tests, and in decision theory where Bayes is dominant. If this all sounds very dry and unexciting, it's quite the reverse. I admit, I love probability and statistics, and I am something of a closet Bayesian*), but Chivers' light and entertaining style means that what could have been the mathematical equivalent of debating angels on

David Spiegelhalter Five Way interview

Professor Sir David Spiegelhalter FRS OBE is Emeritus Professor of Statistics in the Centre for Mathematical Sciences at the University of Cambridge. He was previously Chair of the Winton Centre for Risk and Evidence Communication and has presented the BBC4 documentaries Tails you Win: the Science of Chance, the award-winning Climate Change by Numbers. His bestselling book, The Art of Statistics , was published in March 2019. He was knighted in 2014 for services to medical statistics, was President of the Royal Statistical Society (2017-2018), and became a Non-Executive Director of the UK Statistics Authority in 2020. His latest book is The Art of Uncertainty . Why probability? because I have been fascinated by the idea of probability, and what it might be, for over 50 years. Why is the ‘P’ word missing from the title? That's a good question. Partly so as not to make it sound like a technical book, but also because I did not want to give the impression that it was yet another book

Search This Blog