[untog]

Nate was the outlier in that respect. But it’s true that the polls aren’t weren’t all that inaccurate in 2016: a bunch of important swing states were within the margin of error and Trump won some important states by very small margins.

The mistake in 2016, IMO was a) the extrapolation that came from those polls and b) people paying way too much attention to national polls, which have very little connection to electoral outcomes, given the electoral college.

Also perhaps c) the larger public not “getting” statistics in the way they’ve been presented. The NYT had, if I recall, Clinton at 90% chance of winning. That still means that in one of every ten flips of a coin is a Trump win. But people read “90% chance” as “definite win”. I don’t actually know what anyone should or could do about that.

[bonzini]

What Nate Silver got right in 2016 were the correlations in the Rust Belt, which were traditionally considered Democrat. 538's model predicted that losing one of those states would likely mean losing all of them for Clinton, because for example the polling errors were likely correlated. And indeed losing there is what cost her the election

[ordinaryperson]

Silver's 2012 book "The Signal and the Noise" discusses our inability to rationally process probability, pointing out that commercial weather forecasts (e.g. Accuweather) never list a probably of rain under 20-25%. A 5% chance of rain is a mathematical possibility but people "feel" like 5% = "will never happen" and get angry if it rains.

Nobel Prize winner Daniel Kahneman's life's work is about this, what he calls "System 1" and "System 2" of our brain, where System 1 is a fast responder that provides insta-feedback but is largely incapable of processing mathematical inputs. His 2011 book "Thinking Fast and Slow" summarizes his work well.

I'm not sure popular media can be trained to frame statistical probabilities in a way that doesn't provide people with the certainty they crave. But who knows?

[FrojoS]

I think it’s a confusion between the likelihood of winning, no matter by how many votes, and the predicted percentage of votes per candidate. The latter is more commonly presented to readers from polls. So it’s not too surprising if it gets mixed up with the former, which is used by Nate et al and uses also percent as the unit.

Say a national poll predicts 55% of votes for Clinton, 40% for Trump. Whereas 538 predicts 70% chance of winning for Clinton and 30% for Trump. It’s easy to confuse the two and think the second prediction is much better for Clinton when it might be much worse.

[rsynnott]

> But people read “90% chance” as “definite win”. I don’t actually know what anyone should or could do about that.

538 are aware of the problem, and combating it with a cartoon fox (and better visualisations).

[perryizgr8]

I don't know if this statement is serious. How does a cartoon fox make me think differently about the numbers?

[tomjakubowski]

Like the coyote in El Viaje Misterioso de Nuestro Jomer, the cartoon fox tells you only just enough to light the path towards statistical enlightenment. You must walk it yourself.

[rsynnott]

I was mostly joking; the real improvement is the better visualisations. The cartoon fox is just there as a reminder.