Skip to main content

Prime Suspects - Andrew Granville and Jennifer Granville **

Every now and then someone comes up with the bright idea of doing popular science (or in this case, popular maths) using the graphic novel format. Although I'm not a great fan of the genre, because it so vastly reduces the number of words available, making it very difficult to put across complex or nuanced information, I can see why the concept appeals. But for me, this particular attempt, illustrated by Robert Lewis, falls down on addressing the audience appropriately.

More on that in a moment. What Andrew and Jennifer Granville attempt to do here is put across a fairly obscure bit of mathematics - the relationship between the distribution of the primes and the cycles of permutations - using a very abstracted story in the form of a murder mystery where each victim represents one of the mathematical examples. The authors also claim in their epilogue that their aims include drawing attention to how research is done, the role of women in mathematics today and the 'influence and conflict of deep and rigid abstraction' (no, I don't either).

What we get is a strange murder mystery story where a maths professor is called in to help a detective, making use of two of the professor's students. They are trying to link two similar cases with very different victims. All the characters are named after famous mathematicians and supposedly explain the mathematical ideas they put forward, but this is not done in a way that makes the maths particularly accessible, hindered as it is by the need to compress all the text into speech bubbles and to waste 95 per cent of the page on imagery.

Because the storyline is so abstracted from the mathematics, the images themselves contribute very little. It doesn't help that they vary hugely in quality - some are well drawn, others clearly hurriedly sketched, so that, for example, on page 15 Professor Gauss appears to have six foot long arms. The storyline itself is disjointed, jumping backwards and forwards in time and involving the main detective in a journey to Europe that seems primarily designed to give him something to do while the mathematicians get on with chipping away at the mathematics (and doing autopsies, because, of course, that's what mathematicians do).

If this really is supposed, as the authors say, to give insight into 'the role of student and adviser' it seems that one lesson we need to draw is that professors choose their research assistants by asking trivial questions of a class and then pretty much picking someone arbitrarily.

But I inevitably come back to the audience. Prime Suspects is far too abstruse to appeal to the general graphic novel reader, while the fan of popular maths titles will find the lack of opportunity to explain, explore and appreciate context extremely frustrating; meanwhile the mathematical message proves incredibly hard to follow. The illustrations are crammed with mathematical in-jokes, which makes me wonder if the authors' true audience was other mathematicians - not to inform, but to entertain. It's an interesting, but ultimately unsuccessful, attempt at the communication of maths and the world of academia to a wider audience.
Paperback 

Kindle 
Using these links earns us commission at no cost to you
Review by Brian Clegg

Comments

Popular posts from this blog

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

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