The Problem isn’t that Polling is Unscientific. It’s that Democracy Itself is Unscientific

In the wake of Donald Trump’s surprising victory in the 2016 U.S. Presidential Election, there’s been a lot of discussion in the news about what might have gone wrong this year with public opinion polling, which clearly did not foresee this outcome.

Most polls showed Democratic nominee Hillary Clinton holding onto a slim but steady lead for most of the election cycle. During the week prior to the election, the Real Clear Politics polling average showed Clinton with roughly a 3 point lead in the national polls. Furthermore, on the morning of the election, most major forecasting sites pegged Clinton’s chances of winning at 85% or higher (My forecast and that of FiveThirtyEight were two exceptions. We each gave Trump slightly better chances, at around 25-30%).

But a Clinton victory was not to be. For whatever reason (and we will likely not have a definitive and satisfying answer to this for months), polls underestimated Trump’s support in several key regions of the country. Specifically, Clinton lost in Pennsylvania, Michigan, and Wisconsin, despite the fact that polling averages showed her up in these states by 1.9 points, 3.4 points, and 6.5 points, respectively. Clinton does seem poised to win the popular vote, if that’s any consolation to her supporters. But she’ll become the 5th presidential candidate in history to lose the Electoral College despite winning the popular vote.

Read more “The Problem isn’t that Polling is Unscientific. It’s that Democracy Itself is Unscientific”

How Did the Polls and Forecasters Get it all so Wrong?

Well, I guess I picked the wrong year to get interested in forecasting presidential elections.

As we all know by now, Republican nominee Donald Trump has been elected the 45th President of the United States, with 279 electoral votes and roughly 47% of the popular vote.

However, my statistical model, which was based on national and state-level polls, suggested Democratic nominee Hillary Clinton would be the likely winner. Going into election day, I estimated she had about a 75% chance of coming out on top.

forecast_11-8-16

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Are People with Mental Illness Dangerous? A Bayesian Approach to Tackling Stigma

As part of the ongoing effort to stop Donald Trump from becoming the Republican Presidential nominee, an ad was circulated on Facebook recently featuring pictures of his wife Malania posing nude. The pictures were from a 2000 photo shoot with GQ, and the ad was produced by an anti-Trump “Super PAC” called Make America Awesome.

Although the Super PAC apparently has no ties to his principle rival in the Republican Primary, Senator Ted Cruz of Texas, Mr. Trump was quick to go on the offensive. Read more “Are People with Mental Illness Dangerous? A Bayesian Approach to Tackling Stigma”