**The Maths of Life and Death,**** **written by Kit Yates, who is a senior lecturer in the Department of Mathematical Sciences and co-director of the Centre for Mathematical Biology at the University of Bath, aims to show that ‘*maths is for everyone’ *and that mathematics is ‘*first and foremost, a practical tool to make sense of our complex world.*‘ This is a mission that I’m definitely on board with. I’m convinced that maths is the worst taught of all school subjects in England (due to the failure of central government policies to attract and reward good teachers), leaving a lot of people with the idea that maths isn’t for them. It’s frustrating to see people who are otherwise really smart refusing to even engage with an argument if it contains numbers or anything else ‘sciency’. Yates’s book, on the whole, definitely does a good job of explaining some basic mathematical concepts simply and clearly, and showing how they are relevant in the ‘real world’. The book is almost entirely focused on statistics, and the one chapter that strays into the realm of pure mathematics – on algorithms – will probably be less accessible for the average reader. However, having a solid understanding of some basic concepts in statistics is both vital and possible for everyone, and so I think this focus works well.

I have to say that most of the examples used in *The Maths of Life and Death *were already familiar to me, which is probably the result of my amateur enthusiasm for statistics rather than any undue repetition on Yates’s part, although there is a certain amount of crossover with Ben Goldacre’s *Bad Science. *Because I’m interested in medicine, I was already familiar with the material on medical statistics covered in chapter two, and with much of the epidemiological information in chapter seven (this, of course, is not Yates’s fault, but because this chapter focuses on controlling global pandemics, it makes for a rather chilling read in the wake of Covid-19). Chapter three, on the law, retells the story of the infamous Sally Clark case, where statistics were used to ‘prove’ that the chances of experiencing two stillbirths in the same family were 1 in 73 million, and so Clark must have murdered her two children; as Yates shows, this figure could only have been arrived at through multiple statistical errors. And I already knew about the ‘birthday problem’ in chapter four, which shows that in any school class it’s more likely than not that two children share the same birthday, although I loved hearing the story of how Yates used this fact to pitch his literary agent, Chris Wellbelove, while they were having drinks in a pub:

*I bet him the next round of drinks that I would be able to find two people, in the relatively quiet pub, who shared a birthday. After a quick scan of the room, he readily took me on and indeed offered to buy the next* two *rounds if I could find such a pair, so unlikely did he think the prospect of a match. Twenty minutes and a lot of baffled looks and superficial explanations later… I had found my pair of birthday-sharers and the drinks were on Chris.*

Yates’s prose is clear and straightforward, which is absolutely necessary for a book of this type. Occasionally, when he is trying to write about the bigger implications of statistics, it becomes a bit banal, but this isn’t the case most of the time. I also liked that he explained his calculations both in the text and through the use of diagrams – I found the text easier to follow, but others would probably prefer the diagrams, so this works for everyone. All in all, I’d recommend this book as an accessible and important introduction to understanding the use and abuse of statistics.

*I would like to thank Quercus for sending me a free copy of this book to review.*