Skip to main content

I Think You'll Find It's a Bit More Complicated Than That - Ben Goldacre *****

I was somewhat unnerved when Ben Goldacre's latest arrived in the post. I generally love his work, but this is a positive doorstep of a book at 474 pages, so I recoiled a little - but I shouldn't have worried, because as always it's readable, entertaining and enlightening. I got through the whole thing in two days, admittedly helped by spending six hours reading it on two train journeys, which, as a result, flew by.

What we have a selection of Goldacre's writing on bad science and the like since around 2003 (though it's not particularly chronological, more ordered by topic). A lot of the entries are taken from his Guardian Bad Science column, so if you are a fan of that, some will seem familiar. However there was plenty enough for me that I had not seen before - and even revisiting old favourites brought a smile, rather than a feeling of 'not again.'

Topics include all the usual Goldacre targets: quacks and pseudo-science, badly reported experiments, journalists totally misleading the public about what a scientific paper says and much more. You can enjoy, for instance, him laying into individuals and companies that make outrageous claims, but also highlighting heavy handed litigation to suppress criticism, newspaper headlines like 'Suicides Linked to Mobile Phone Masts' (guess what - they weren't) and even a piece on the Romney, Hythe and Dymchurch railway. I particularly liked the article 'The Caveat in Paragraph 19' which pointed out something I'd been aware of for a long time without really quantifying, which was the way bad newspaper science often makes outrageous claims up front, then has someone qualified far into the article - well after many stop reading - saying 'but actually there is no evidence for this.'

I Think You'll Find works well as a dip-in book, but I happily read it end to end. What says it all about the quality of this book is that when I got to page 403 and discovered that the remaining pages were notes and index I was really disappointed. I wanted more, and I rarely like long books. That's not a bad sign. Recommended for all the journalists, politicians, purveyors of woo and scientists in your life - but, frankly, for everyone else too. Lovely stuff.


Paperback 

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

Comments

Popular posts from this blog

Models of the Mind - Grace Lindsay *****

This is a remarkable book. When Ernest Rutherford made his infamous remark about science being either physics or stamp collecting, it was, of course, an exaggeration. Yet it was based on a point - biology in particular was primarily about collecting information on what happened rather than explaining at a fundamental level why it happened. This book shows how biologists, in collaboration with physicists, mathematicians and computer scientists, have moved on the science of the brain to model some of its underlying mechanisms. Grace Lindsay is careful to emphasise the very real difference between physical and biological problems. Most systems studied by physics are a lot simpler than biological systems, making it easier to make effective mathematical and computational models. But despite this, huge progress has been made drawing on tools and techniques developed for physics and computing to get a better picture of the mechanisms of the brain. In the book we see this from two directions

The Ten Equations that Rule the World - David Sumpter ****

David Sumpter makes it clear in this book that a couple of handfuls of equations have a huge influence on our everyday lives. I needed an equation too to give this book a star rating - I’ve never had one where there was such a divergence of feeling about it. I wanted to give it five stars for the exposition of the power and importance of these equations and just two stars for an aspect of the way that Sumpter did it. The fact that the outcome of applying my star balancing equation was four stars emphasises how good the content is. What we have here is ten key equations from applied mathematics. (Strictly, nine, as the tenth isn’t really an equation, it’s the programmer’s favourite ‘If… then…’ - though as a programmer I was always more an ‘If… then… else…’ fan.) Those equations range from the magnificent one behind Bayesian statistics and the predictive power of logistic regression to the method of determining confidence intervals and the kind of influencer matrix so beloved of social m

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 i