How did media get election wrong? A hurricane has the answer

This, FiveThirtyEight’s Nate Silver writes today, was a “ridiculous” and “dangerous” tweet from the Associated Press a couple of weeks ago when Hurricane Irma hit Florida.

AP deleted the tweet the next morning but Silver says it’s a fine example of the problem the media has covering hurricanes and any other story that involves the concept of probability.

Indeed, there’s a fairly widespread perception that meteorologists performed poorly with Irma, having overestimated the threat to some places and underestimated it elsewhere. Even President Trump chimed in to say the storm hadn’t been predicted well, tweeting that the devastation from Irma had been “far greater, at least in certain locations, than anyone thought.”

In fact, the Irma forecasts were pretty darn good: Meteorologists correctly anticipated days in advance that the storm would take a sharp right turn at some point while passing by Cuba. The places where Irma made landfall — in the Caribbean and then in Florida — were consistently within the cone of uncertainty.

The forecasts weren’t perfect: Irma’s eye wound up passing closer to Tampa than to St. Petersburg after all, for example. But they were about as good as advertised. And they undoubtedly saved a lot of lives by giving people time to evacuate in places like the Florida Keys.

The media keep misinterpreting data and then blame the data, says Silver.

It’s not just hurricanes. It was also Hillary Clinton.

Contrary to popular belief and the belief in the media, polls did not support the claim of a sure victory by the Democrat.

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 campaign undecided 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.

The polls called for caution, rather than confidence? So why wasn’t it reported that way?

Confirmation bias is one reason.

“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,” says Silver.

But there’s another: Journalists don’t understand probability and statistics.

And people associate numbers with precision.

A 70-percent chance of winning an election is interpreted as a candidate having a 70-to-30-percent lead in the polls. That’s not how it works.

“News organizations reporting under deadline pressure need to be more comfortable with a world in which our understanding of developing stories is provisional and probabilistic — and will frequently turn out to be wrong,” Silver concludes.