……from Nate Silver @ FiveThirtyEight….
The media keeps misinterpreting data — and then blaming the data
You won’t be surprised to learn that I see a lot of similarities between hurricane forecasting and election forecasting — and between the media’s coverage of Irma and its coverage of the 2016 campaign. In recent elections, the media has often overestimated the precision of polling, cherry-picked data and portrayed elections as sure things when that conclusion very much wasn’t supported by polls or other empirical evidence.
As I’ve documented throughout this series, polls and other data did not support the exceptionally high degree of confidence that news organizations such as The New York Times regularly expressed about Hillary Clinton’s chances. (We’ve been using the Times as our case study throughout this series, both because they’re such an important journalistic institution and because their 2016 coverage had so many problems.) On the contrary, the more carefully one looked at the polling, the more reason there was to think that Clinton might not close the deal. In contrast to President Obama, who overperformed in the Electoral College relative to the popular vote in 2012, Clinton’s coalition (which relied heavily on urban, college-educated voters) was poorly configured for the Electoral College. In contrast to 2012, when hardly any voters were undecided between Obama and Mitt Romney, about 14 percent of voters went into the final week of the 2016 campaignundecided about their vote or saying they planned to vote for a third-party candidate. And in contrast to 2012, when polls were exceptionally stable, they were fairly volatile in 2016, with several swings back and forth between Clinton and Trump — including the final major swing of the campaign(after former FBI Director James Comey’s letter to Congress), which favored Trump.
By Election Day, Clinton simply wasn’t all that much of a favorite; she had about a 70 percent chance of winning according to FiveThirtyEight’s forecast, as compared to 30 percent for Trump. Even a 2- or 3-point polling error in Trump’s favor — about as much as polls had missed on average, historically — would likely be enough to tip the Electoral College to him. While many things about the 2016 election were surprising, the fact that Trump narrowly won1 when polls had him narrowly trailing was an utterly routine and unremarkable occurrence. The outcome was well within the “cone of uncertainty,” so to speak.
So if the polls called for caution rather than confidence, why was the media so sure that Clinton would win? I’ve tried to address that question throughout this series of essays — which we’re finally concluding, much to my editor’s delight.2
Probably the most important problem with 2016 coverage was confirmation bias — coupled with what you might call good old-fashioned liberal media bias. Journalists just didn’t believe that someone like Trump could become president, running a populist and at times also nationalist, racist and misogynistic campaign in a country that had twice elected Obama and whose demographics supposedly favored Democrats. So they cherry-picked their way through the data to support their belief, ignoring evidence — such as Clinton’s poor standing in the Midwest — that didn’t fit the narrative.
But the media’s relatively poor grasp of probability and statistics also played a part: It led them to misinterpret polls and polling-based forecasts that could have served as a reality check against their overconfidence in Clinton…..
More and link to the 10 other parts of this Nate Silver look at the 2016 election, media and polling….Here….Share on Facebook