The outcome of the 2016 presidential election shocked many people – and they pointed their fingers at misleading polls that didn’t do a great job predicting what actually happened.
On Election Day, analyst Nate Silver’s FiveThirtyEight predicted that Clinton had a 71.4 percent chance of winning and ran the headline “Final Election Update: There’s a Wide Range of Outcomes, and Most of Them Come Up Clinton.” Economist David Rothschild’s PredictWise site gave Hillary Clinton an 89 percent chance that morning. And The New York Times’ The Upshot set her chances at 85 percent, suggesting that “Mrs. Clinton’s chance of losing is about the same as the probability that an N.F.L. kicker misses a 37-yard field goal” – a low probability event that happens only one or two times out of 10.
But when the votes were counted, expectations were upended and Donald Trump won. How did so many polls seemingly miss the target? As a behavioral scientist, I study people’s emotions and how they affect behavior – and I suspect emotions might have something to do with why the polls were so mistaken.
What’s behind bad predictions