Saturday 29 October, 12.15pm until 1.15pm, Lecture Theatre 2 Lunchtime Debates
Warning: may contain graphic images of data.
From Hans Rosling’s surprise hit TV show The Joy of Stats to visual snapshots of the numbers in the news, there seems to be a new love affair with statistics, especially when they come in a graphic form that can be grasped intuitively. It doesn’t take a maths degree to see that a straight line sloping upwards suggests a relationship between the height and age of schoolchildren, for example, or that a large blob represents more murders than a smaller blob. We are ready, perhaps too ready, to give credence to statistics, which appear to manifest the mysterious labours of the mathematically literate in transparent, self-explanatory form. We too rarely question the assumptions that underlie the figures, and too often forget that an evident correlation between two things – US oil production and the quality of rock ‘n’ roll, for example – does not necessarily mean there’s a causal relationship. And we are often beguiled into believing that the past automatically predicts the future – a graph which shows anything increasing exponentially in the past can only spell doom for the future.
We need statistics. By collecting lots of simple information in numerical form we can see patterns that may help us understand problems and spot underlying causes. But this is where things get tricky. If the number of Elvis Presley impersonators continues to increase as it did from 1957 (170 worldwide) to 2007 (over 85,000 worldwide) one in three of us will be Elvis impersonators by 2019. Is this likely? Public health and economics, among other disciplines, rely on modelling human behaviour the same way animal behaviour, or the behaviour of water molecules, can be modelled: by looking at what they’ve done so far. Not surprisingly, this leaves the predicted future looking very much like the past. But people are not data points, and both individuals and societies can behave in unpredictable ways. You can calculate your probability of living to be 100 (one in six of the current UK population) but that’s an educated estimate of the odds, not a guarantee. Are we in danger of turning statistical modelling from a useful analytical tool to the new astrology?
Listen to session audio:
journalist, writer & broadcaster; presenter, Futureproofing and other BBC Radio 4 programmes; author, Big Data: does size matter?
director, lifestyle economics, Institute of Economic Affairs; author, The Art of Suppression
actuary; founder, First Actuarial
We have a difficult relationship with statistics. On one level, we seem to have replaced the 10 Commandments with the 10 Statistics – running our lives taking into account the need to limit our alcohol units, eat our 5 a day, read to our children, pay down our debts and reduce our stress levels. At another level, people show a cynicism of statistics which whilst not new (lies, damned lies….) does perhaps show a deeper level of mistrust than has existed previously.Hilary Salt, Independent, 6 November 2011
Activists, neo-prohibitionists and anti-capitalists are much happier blaming the corporations and the institutions, man, than looking at the real factors behind excessive drinking and alcoholism.Chris Snowden, Velvet Glove, Iron Fist, 22 September 2011
The scientisation of uncertainty presents huge problems for policy. It suggests that policy problems can be solved by throwing more science at them.Jack Stilgoe, Responsible Innovation, 7 September 2011
Today, Cancer Research UK scientists have published research showing that taller people seem to be have a higher risk of cancer. This may seem alarming, but tall people needn’t be too worried about these results.Jess Harris, Cancer Research UK, 22 July 2011
There has never been a randomised trial to test the carcinogenicity of bacon, so it seems reasonable to ask how strong is the evidence that you shouldn’t eat it? It turns out to be surprisingly flimsy.DC's Improbable Science blog, 4 May 2009
None of us are going to last for ever. Our prospects depend on our sex, our age, our lifestyle, our genes, and many other personal factors both known and unknown. Even with all this information we're all uncertain about the exact date of our death, but by looking at large groups of people who are like us, we can count how many die each year and so get an idea of the risks we face and how long we might live.Understanding Uncertainty blog, 2 July 2008