Spotting spurious correlations in health news

When it comes to diet and health, you might see one day that a certain food decreases life expectancy. Then on another day, a different study suggests that food increases life expectancy. It’s hard to know which to believe. David Epstein provides some guidance:

If you’ve watched a lot of NFL games, you’ve probably heard a commentator at some point trot out a stat like: “The Chicago Bears are undefeated in division games following a bye week when they wear their alternate jerseys.”

It is possible that the combination of extra rest and unusual attire gets the Bears amped for division rivals, thus improving their performance — just as it is possible that using the sauna precisely 9-12 times per month at a particular temperature protects against dementia (at first). It is far more likely, however, that given a large database of games and conditions, there will be loads of correlations that occur just by chance; the more you slice and dice the data, the more you’ll find.

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Cohort and age effects

I’m just gonna put this xkcd comic right here.

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Common statistical interpretation mistakes

Statistics is a game of subtleties, and you lose when you don’t pay attention to the details. Here are a handful of common mistakes when interpreting the numbers. In a nutshell: You get into trouble when you assume and ignore.

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Meat and cancer

Meat as a cause of cancer has been the news as of late. Aaron Carroll for the Upshot describes why we should make a note but not freak out about it.

This means that, if I buy what the W.H.O. is saying, if I decided today to start eating an extra three pieces of bacon every day for the next 30 years, my risk of getting colon cancer might go from 2.7 percent to 3.2 percent. In other words, if 200 people like me made that decision, one extra person might get cancer. The other 199 would be unaffected.

It's about understanding risk.

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