“Nate Silver analyzes poll data on the influential FiveThiryEight blog at The New York Times. He crunches polls and other data in an electoral statistical model, and he claims that his work is guided by math, not left or right politics. Yet he’s become a whipping boy as election day approaches. His crime? Publishing the results of statistical models that predict President Obama has a 73.6 percent chance of defeating the Republican challenger, Mitt Romney.
“The pollsters tell us what’s happening now,” conservative columnist David Brooks told Politico, trashing Silver. “When they start projecting, they’re getting into silly land.” In the same article, MSNBC’s Joe Scarborough added, “And anybody that thinks that this race is anything but a tossup right now is such an ideologue, they should be kept away from typewriters, computers, laptops, and microphones for the next 10 days – because they’re jokes.”
David Brooks is mistaken and Joe Scarborough is wrong. Because while pollsters can’t project, statistical models can, and do … and they do some predictions very well.
We rely on statistical models for many decisions every single day, including, crucially: weather, medicine, and pretty much any complex system in which there’s an element of uncertainty to the outcome. In fact, these are the same methods by which scientists could tell Hurricane Sandy was about to hit the United States many days in advance.
Dismissing predictive methods is not only incorrect; in the case of electoral politics, it’s politically harmful.
It perpetuates the faux “horse race” coverage that takes election discussions away from substantive issues. Unfortunately, many of these discussions have become a silly, often unfounded, time-wasting exercise in fake punditry about who is 0.1 percent ahead. There may well be reasons to consider Ohio a toss-up state, but “absolute necessity for Romney to win the state if he wants to be president” (as Chris Cillizza argues) is not one of them.”
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