Statistics Win in U.S. Election

Neuroscientist Sam Wang says that predicting vote winners is easy if you understand median-based statistics, probabilities and some Bayesian statistics















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Nate Silver took a big share of the spotlight for blogging statisticians. Was that an annoyance or a blessing?
He certainly made this whole activity more high profile. In the 2008 election, he gave color commentary and made poll aggregation interesting. There were a number of us doing it in 2004, and our approach generally was to put up the poll aggregates and not talk about them. He made the innovation of giving a play-by-play  — he’s got a background in sports — and he made it fun.

What might change the ability of this kind of method to predict winners?
The profession of polling is changing. As people become less accessible through landline phones, it becomes more of a challenge to reach people — either by mobile phone or through the Internet. How well [pollsters] succeed will determine the quality of the data feed.

The other thing that is going to come up is whether the data feed continues to be of high quality. There may be a day that these data feeds become dominated by partisan organizations, or other organizations that would seek to control the flow of information. If that happens, then there’s a question as to the integrity of the entire data set. Generally speaking, it all depends on having a source of high-quality data.

Do you see it as a victory for maths?
I do think that, in principle, it should get journalists and pundits to think twice about dismissing people who have a good quantitative understanding of political races. I think it was a good showcase for the kinds of contributions that poll aggregation can make.

This article is reproduced with permission from the magazine Nature. The article was first published on November 14, 2012.



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  1. 1. Germanicus 09:33 AM 11/22/12

    Is there any hope for systematic, broad-based Populist Reform?

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