I am not a number – I’m a statistic

Number nine

Today’s post is brought to you by the number 9 (it’s my favourite)

It’s very annoying being treated impersonally, as ‘call number 18 in a queue’, or as a poorly defined Amazon customer (no I don’t want more baby toys, I only bought one for my friend). But we all exist as impersonal datapoints on many, many spreadsheets all over the place.

I’ve ranted with my friends about the strange decisions taken by insurance companies: why is insuring my car against fire and theft MORE expensive than comprehensive cover?? How is Catford classified as a flood plain?

But gradually I achieved (for me) a zen-like level of calm – I remembered that really I’m just a statistic. In this particular case, a woman in her twenties with a very old Ford Fiesta. And my friend is simply a Catford resident whose neighbours have made several claims for flooding (probably burst pipes, rather than Biblical inundations of south London). We’re all statistics.

Statistics and probabilities control our lives in rather strange ways. My favourite example of this was a news article that described some research showing that a particular behaviour ‘increased the risk of death’. Someone witty commented underneath, pointing out that ‘surely everyone’s risk of death is already 100%?’

Yup, statistics are clever but they are also counter-intuitive, and often misleading. Statistics are about patterns in data, where one point on a graph means nothing except in its relationships with all the others scattered around it.

But people don’t work that way. I don’t think of myself as a point on a graph – I know I’m unique (and obviously very important and special!). It annoys me that the type of people who insure their cars against fire and theft tend to be risky bets for insurance companies – I know I don’t fit into that group, but I also know that’s all Direct Line have to go on.

What I love about this is that really the risk of me claiming on my insurance is always just a vague estimate – it would be almost impossible to calculate the real risk, because so many variables would have to be taken into account (my terrible parking skills vs. the superficially reassuring length of time for which I’ve held my license without claiming). So this statistic isn’t just average, it’s definitely wrong. The question is, how wrong?

Sometimes these predictions go hilariously wrong. For example, I’ve noticed recently that I’ve been getting a LOT of unsolicited catalogues through my letterbox. And because they only have my address, marital status and gender to go on, some of them are pretty far off their target market. Some have decided that I’m an elderly lady in need of elasticated trousers and argyle sweaters, while others send gardening catalogues (I live in a flat). Their predictions veer off more wildly when they spell my name wrong (Mr Neil Barrie does not live at this address).

But vague stats can also be scary – like when you read that your chance of getting cancer in your lifetime is roughly 1 in 3 (in the UK). Actually, for most of your life, your chance of being diagnosed at a given age is usually much, much lower (especially when you’re very young). And as we learn more about the genes that influence each person’s risk, the ‘1 in 3’ stat looks like an increasingly blunt tool. But it’s still true, and the message is important.

Statistics are really powerful – helping us to spot the patterns in data that are at the heart of scientific analysis. As nerds everywhere know, ‘the plural of anecdotes is not data’ – and statistics are the only way we can fight off the bias of the human mind, which is generally a bit too ready to spot patterns where none exist (Jesus in a slice of toast, for example).

But really stats are just another tool – you need to know how to use them. My favourite illustration of this is from the movie Anchorman, which features the now legendary male perfume Sex Panther – “60% of the time, it works every time.”  This is almost as meaningless as Head & Shoulders shampoo’s claim that it gives you “up to 100% dandruff free hair” – over 100% would really be impressive.

So what does all this prove? Statistically, not much – but I hope my collection of anecdotes has at least been entertaining. Overall, it’s not how big (or small) your stats are, it’s what you do with them that counts. We shouldn’t be offended at our transformation into datapoints. In a way it’s strangely poetic, proof that every one of us does make at least a small difference to the world we live in – although perhaps not always a statistically significant one.

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