Blog: Too much driving makes you fat?
Dave Leggett | 17 June 2011
Two sets of time series data moving in the same direction does not mean that you have a basis for making deductions about a relationship between the two variables or about causation, however good the data fit or plausible the causation theory is. Back in neolithic times I did a course in econometrics that involved pounding a calculator to get things like regression lines and some of it stuck. Causation - that variable X going up/down is causing variable Y to go up/down - is a tricky one, to put it mildly.
Some examples illustrate the data difficulties. With a decrease in the number of pirates (the Blackbeard variety rather than the guys off Somalia), there has been an increase in global warming over the same period. Therefore, global warming is caused by a lack of pirates. [coincidence in trends, nothing more]
The more firemen fighting a fire, the bigger the fire is observed to be. Therefore firemen cause fire. [causation reversed]
And a personal favourite. Sleeping with one's shoes on at night is strongly correlated with waking up with a headache. Therefore, sleeping with one's shoes on causes headaches. [we're missing something and I think we know what the missing piece of jigsaw might be with that one...]
I saw a daily chart in The Economist recently (a trusted source, usually) that charted average miles driven in the US (gone up over recent decades) and obesity rates (also up over the same period). Conclusion drawn: Americans are spending more time behind the wheel when they could otherwise be getting some exercise (what? like running for the bus? get real...) and that's leading to obesity. Hang on a minute, I thought, that seems like a bit of a leap when you think about all the factors that are behind obesity and the limitation of just looking at vehicle miles driven.
Anyway, the chaps at Freakonomics have duly demolished it.
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