Quantitative Revolution

We’re going through an interesting sort of revolution in America. One after another, various disciplines are realizing (or, it’s coming out publicly that they have realized) that math is useful for stuff.

Wherever there is data available, a scientific, quantitative approach allows people to do two things. First, they can use existing data to develop a model which fits all the available observations. Next, they can in turn use the model to predict future behavior. And if people can make predictions, they can try to make decisions. Influence outcomes. Optimize certain results.

An obvious place for such an approach is the world of high finance, a discipline which is totally steeped in numbers and data – and completely focused on the very quantitative problem of maximizing a return and minimizing loss – but for a long time apparently ignored statistical modeling. People successfully applied statistical analysis, and ended up doing very well…but there was a backlash. Here’s an interview where a reporter complains that trying to optimize stock market gains somehow mis-values the stock market, at least according to his conception of value.

Geez. Those…those…physicists. They use models based on data of past performance, then try and predict future performance…and worst of all, they keep getting their predictions right!

(I want to note that if someone has a problem with the idea that these “quants” have privatized tremendous gains and socialized tremendous losses, that’s not a problem with their approach. It’s an issue with the goals of their models, and whether those goals are morally justified is a separate question from whether the approach works to satisfy the goals.)

We also have a ton of data available in the world of professional sports. Commentators make it their business to know – and inform viewers – whether or not this is the guy who gets on base with a ground-rule double on an overcast Tuesday more than any other player with an odd jersey number when the pitcher throws a 96-mile-an-hour fastball. In fact, this revolution I’m referring to might even be called the Moneyball effect. After all, that movie brought this idea forward in the popular consciousness.

Most recently – and certainly most dramatically – we have people who build statistical models on political poll data. Despite a constant media barrage insisting that the 2012 election was a dead-heat horse-race fifty-fifty hyphenated-adjective toss-up, these poll wonks stubbornly viewed their data scientifically, constructed careful algorithmic models, and predicted a much more certain, though far less entertaining, outcome. There was quite a backlash against these predictive models, at first, though the backlash seems to have been driven by either ideological preconceptions or a misunderstanding of the statistics: a poll showing two candidates with a 51-49% split doesn’t mean that the likelihood of each candidate winning is 51% or 49%. In true Hari Seldon-like fashion, the models aren’t predicting what single voters do or making decisions for us; but with an aggregate of people, they can make astonishingly good predictions. In many ways, this was the biggest story to come out of the 2012 American elections: scientific thinking and mathematical methods actually work!

This notion seems revolutionary, in each field it has touched so far. That appearance is what I find most surprising! Science has given humanity an entire body of knowledge. We can predict the behavior of quantum particles. We can determine whether there are planets orbiting other stars. We can forecast snowfall to within a few inches of accuracy a week in advance. We can find out what the feathers on a dinosaur look like. We can reconstruct Pangaea in a computer. And all the predictive mathematical models that allow scientists to do those things also give us cell phones, Angry Birds, medications, contact lenses, and all sorts of other goodies. Science isn’t just something that happens in isolated labs – it gets out into the world. And quantitative thinking isn’t magical wizardry – it is a tool that anyone with the will to apply themselves can learn.

This is a lesson that I hope we take to heart.

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