Nate Silver's The Signal and the Noise (our Spotlight pick for September's Best Books of the Month) is "a timely and readable reminder that statistics are only as good as the people who wield them," as our reviewer Darryl Campbell put it. In this exclusive Q&A, Nate explains the success of weather forecasters and gamblers. Scroll down and watch a video of Silver discussing the book.
Why do you think statistics books continue to capture the popular imagination, from Freakonomics to Moneyball?
We encounter so much information today that people are naturally curious about what in the heck we should do with all of it. And we’re becoming less trusting of institutions that mediate information, like the news media. We have all this data, and we want to learn for ourselves what it all means.
A little bit of math and statistics and probability and logic helps us with our information-processing goals. But what’s great about books like Moneyball and Freakonomics is that they make statistics approachable. Subjects like English and history are taught in very hands-on ways--you read great books, discuss the ideas and characters, and it’s easy to understand their relevance. Whereas math is taught in very abstract and technical ways--even though it’s just as relevant to our everyday lives, and just as intuitive if it’s taught well.
Books like Freakonomics and Moneyball help to bridge that gap. They’re sort of making up for the calculus teacher that had you memorize one too many derivatives and turned you off to the subject as a result. Not that there’s anything wrong with calculus.
Politics and baseball, the two subjects you are best known for, are just part of the book. Why was it important to include so many different fields--economics, earth and life sciences, games, even terrorism?
One thing that baseball fans know is to be wary of small sample sizes. If you show up at the ballpark, and the catcher gets three hits that day, that doesn’t really tell you very much about how good he really is. It takes a long time--hundreds of at-bats--for the signal to emerge since there’s so much luck in the game.
But in the same way, I thought, perhaps baseball is an exceptional case. Are there Moneyball-like success stories in other fields in which statistics and analysis and prediction is pertinent?
In fact, I found that there are entire disciplines in which our analysis has failed to produce much progress, at least as measured by our ability to make reliable predictions. Finance and economics are obvious examples of this, for instance. Economists have literally tens of thousands of data series to mine--more statistics than baseball geeks do. But they still aren’t able to predict recessions more than a few months in advance.