At the planet’s most prestigious school, during an event designed to make sense of the most consequential upset in a year full of them, the world’s most prominent statistician admitted that his research and reporting, which millions of readers had turned to for reason during an unreasonable time, may have been open to misinterpretation.
“It’s not intuitive, for people, to have numbers convey uncertainty,” pioneering data
Throughout the exhausting 2016 presidential race, millions followed the mathematical election forecasting popularized by Silver, whose previous precision had made him the darling of the political data world (and the sports world before that). Silver’s polling models correctly predicted the electoral outcomes of forty-nine states in the 2008 election, and in 2012 he called them all. So when his FiveThirtyEight formulas consistently showed Hillary Clinton as about a 3–1 favorite to defeat Donald Trump for most of the political season, onlookers took that to mean America’s first female presidency was all but a lock.
With two weeks to go, Silver had Clinton at 86 percent likely to win, while his previous employers at The New York Times had the Democrat’s odds pegged at 93 percent. Her lead persisted in both until election night, when the Times had Clinton’s odds at 85 percent and FiveThirtyEight measured them to be 71 percent. When Donald Trump clinched his shocking Electoral College victory on November 8, those who had come to believe that the odds were impossibly against
Had the experts made a
Neither, to hear Silver tell it. The mistake that nonquantitative thinkers made, he argues, was presuming fate from a tool meant only to calculate likelihood. They misread the numbers they were looking at. As his Times counterpart Amanda Cox put it in describing her own election night model, “It’s really