Bayesian estimation on the presidential election.

From the "Random Samples" section of the Oct. 17 Science Magazine:

In the winner-take-all world of politics, candidates know that even a modest lead in the polls can spell almost certain victory. Sheldon Jacobson, an operations research specialist at the University of Illinois, Urbana-Champaign, and colleagues, including a group of students, have attempted to quantify that insight for the current United States presidential election, putting their predictions for the Electoral College on a Web site, election08.cs.uiuc.edu. Using a statistical method known as Bayesian estimation, they combined an analysis of results from the 2004 Bush-versus-Kerry contest with current state-by-state polls for Obama versus McCain to produce probabilities for each candidate of carrying each state. They then converted the estimates into a probability distribution for the total number of Electoral College votes a candidate might receive. In Indiana, for example, polls as of 4 October gave McCain a slight 2.5% lead. But given that Bush carried Indiana in 2004 by 20.7%, a Bayesian calculation indicates McCain's chance of winning the state's 11 Electoral College votes at about 87%. Most states are now in the bag for one candidate or the other; only a handful are truly in Bayesian play. Current calculations give McCain no chance of victory. "However," Jacobson cautions, "if the polls move, then so will our forecasts."