Algorithm predicts winner of the 2016 U.S. Presidential election

In predicting the winner of the 2016 U.S. presidential election, Eric Schulman and Daniel Debowy again demonstrate the power of statistics — and demonstrate that the power of statistics can be divorced from other qualities of statistics. They created an algorithm (in other words: a mathematical recipe) that accurately, thoughtlessly produces a possibly-meaningless prediction that’s based entirely on genuine facts.

Schulman and Debowy have prepared a new study, called “WHO WILL WIN THE 2016 U.S. PRESIDENTIAL ELECTION?” They have also created a related Facebook page, for everyone who would like to analyze or bloviate.

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Here are key snippets of the new study:

The Annals of Improbable Research U.S. Presidential Election Algorithm (Debowy and Schulman 2003) correctly predicted the outcome of the 2004, 2008, and 2012 United States presidential elections. Now that the 2016 campaign for U.S. President has officially started, we apply our proven algorithm to 22 potential Republican candidates and 14 potential Democratic candidates for this election.

ABSTRACT. Our 2003 algorithm for determining the winners of United States presidential elections correctly ascertained the winner of each of the 56 U.S. presidential elections between 1789 and 2000 and correctly predicted the winners of the 2004, 2008, and 2012 U.S. presidential elections. In this paper we apply the algorithm to 22 potential Republican candidates and 14 potential Democratic candidates for the 2016 U.S. presidential election. The Republican candidate with the highest presidential electability is James R. Perry, who suspended his campaign on September 11, 2015. Two Democratic candidates are tied with the highest electability: Lincoln D. Chafee, who ended his campaign on October 23, 2015, and Edmund G. Brown, Jr., who has not declared that he is running.