>The appropriate amount of precision to conclude with, given all of the fuzzy inputs, is something like 'well, we can't tell who's going to win - it's close, al

>The appropriate amount of precision to conclude with, given all of the fuzzy inputs, is something like 'well, we can't tell who's going to win - it's close, although this one candidate's chances look slightly better'. It's not 'Candidate A's chances improved from 74.6% yesterday to 76.5% today'. Your post shows a horrible misunderstanding of how this all works. When you have sketchy data, you don't just disregard it -- it's still telling you something and the role of statistics here is to extract, from amidst all the noise, that information. Just because something is hard doesn't mean it's not worth the attempt. >His results are also completely unverifiable. Kind of. But how his methodology performs over all, over a wide range of elections, is verifiable. Wikipeida mentions this: >The accuracy of his November 2008 presidential election predictions—he correctly predicted the winner of 49 of the 50 states—won Silver further attention and commendation. The only state he missed was Indiana, which went for Barack Obama by 1%. He also correctly predicted the winner of all 35 Senate races that year. Whether his models perform like this consistently is a very real way that the methodology can be verified.