The Scientist’s Toolkit: Understanding the numbers

21 11 2009

Let’s say you’re reading a newspaper over the weekend. Let’s say you spot a front-page headline in this newspaper, all direly big, that says something along the lines of, “EATING YOGHURT DOUBLES YOUR RISK OF BRAIN CANCER!”

Assuming you pay attention, and go on to read the article, should you immediately stop eating yoghurt? After all, “doubling” is an awful lot. But when you read the small print in this kind of article, you’re likely to find out that 1) the baseline risk (i.e. the number of people, out of 1,000, who will get this illness in their lifetime) is extremely low; and 2) the correlation between eating yoghurt and brain cancer adds up to a slightly higher, but still extremely low risk. Let’s say that the number of people who will typically get brain cancer is something like 0.25 per thousand, or one person per four thousand. In the yoghurt-eating contingent, it is found that 0.5 people per thousand will go on to develop brain cancer, or one in two thousand – basically, one extra person per four thousand yoghurt eaters. The newspapers are perfectly entitled to report this as “RISK DOUBLES!”, and usually do.

Now, chances are that you didn’t make a vow to stay away from yoghurt when you read this article, because you’ve read too many like it, and possibly even muttered something about damned lies and statistics before you turned the page. That’s a shame, because we need statistics. Yes, they can be represented all kinds of ways, and some of those ways are more informative and useful than others, but it is statistics that we turn to when we need to know if a study or a programme worked, or whether crime rates really have changed, or if we should start excluding yoghurt from our diets. You need the toolkit to go up close and understand what the numbers are telling you.

There are some excellent resources online , for starters, try the Open University’s Statistics and the Media. And I recommend it so frequently, I feel like a broken record, but pick up Ben Goldacre’s Bad Science too – hilarious, fun to read, and the best simple primer on how to read, understand and criticise a science study that I’ve ever read.




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