Is Thomas Bayes the true ‘winner’ of the US election?


  • Date: 12 November 2012
  • Copyright: Portrait appears courtesy of Wikipedia.

Last week’s US presidential election brought to attention the mathematical predictions of New York Times blogger Nate Silver who used Bayesian analysis to forecast the general election results.

thumbnail image: Is Thomas Bayes the true ‘winner’ of the US election?

In 2008, Nate Silver developed a Bayesian model and is now famous for correctly predicting 49 of 50 states, as well as every Senate race. For this election, Silver predicted all 50 states correctly despite receiving criticisms that his predictions would not work or that some states such as Texas and California are easy to forecast, however, these criticisms were few. Charles Hogg from the International Society of Bayesian Analysis is delighted that Silver has brought Bayesian analysis to a wider audience.

From the blog Stats Chat, Professor Thomas Lumley points out ‘journalists and scientists have difficulty communicating with each other. In political journalism, the journalist gets access to insider information from multiple sources, cross-checks it, evaluates it for reliability, and tells us things we didn’t know. In data-based journalism there aren’t inside secrets. Anyone could put together these information sources, and quite a few people did. It doesn’t take any of the skills and judgment that journalists learn; it takes different skills and different sorts of judgment.’

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