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Visual Revelations: Defeating Deception: Escaping the Shackles of Truthiness by Learning to Think like a Data Scientist

In the months leading up to Election Day 2012, we were torn between two very different kinds of outcome predictions. On the one hand were partisans, usually Republicans, telling us about the imminent defeat of President Obama. They based their prognostications on experience, inside information from “experts” and talking heads from Fox News. On the other side were “the Quants,” represented most visibly by Nate Silver, whose predictions were based on a broad range of polls, historical data, and statistical models. The efficacy of the former method was attested to by snarky experts, armed with anecdotes and feigned fervor, who amplified the deeply held beliefs of their colleagues. The other side relied largely on the stark beauty of unadorned facts. Augmenting their bona fides was a history of success in predicting the outcomes of previous elections, and, perhaps even more convincing, was remarkable prior success, using the same methods, in predicting the outcome of a broad range of sporting events. It would be easy to say that the apparent supporters of an anecdote-based approach to political prediction did not really believe their own hype, but were just defeating deception: Escaping the shackles of truthiness by learning to think like a data scientist