How to Read Numbers - Tom Chivers and David Chivers *****

This is one of my favourite kinds of book - it takes on the way statistics are presented to us, points out flaws and pitfalls, and gives clear guidance on how to do it better. The Chivers brothers' book isn't particularly new in doing this - for example, Michael Blastland and Andrew Dilnot did something similar in the excellent 2007 title The Tiger that Isn't - but it's good to have an up-to-date take on the subject, and How to Read Numbers gives us both some excellent new examples and highlights errors that are more common now.

The relatively slim title (and that's a good thing) takes the reader through a whole host of things that can go wrong. So, for example, they explore the dangers of anecdotal evidence, tell of study samples that are too small or badly selected, explore the easily misunderstood meaning of 'statistical significance', consider confounders, effect size, absolute versus relative risk, rankings, cherry picking and more.

This is all done in a light, approachable style that makes the book a delight to read. Just occasionally the jokes are a little heavy-handed (as when they gave examples based on people buying their book), but it's all nicely balanced, informative and laser-accurate in pinpointing the errors we see day after day from the media. The book finishes with a 'statistical style guide' for journalists, which should be printed out and placed on every desk in a media outlet.

Off the top of my head, the only major issue they don't address is spurious accuracy - though this is indirectly covered in asking for statistics to be given with confidence intervals. Overall, an excellent addition to the armoury of good use of statistics. I suspect a self-selecting readership will result in the Chivers brothers largely preaching to the converted - but if even a few media sources take the hint it will be well worth it, and even if they don't, it gives readers the tools to recognise misuse of statistics in many cases.

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Review by Brian Clegg

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