Quantitative Editor, @FiveThirtyEight | PhD, @LSEGovernment | 
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I ran some simulations to see whether the spread in the polls in October is larger than we'd expect. And based on sampling variability alone, it is -- way larger. The standard deviation of Biden's polls, for example, should be around 2, but it's actually 3.5.pic.twitter.com/aZ6YK2bMi5
But sampling variability isn't the only thing driving the spread. Once we account for house effects, the observed standard deviation is within the range we'd expect. And house effects are healthy! We *want* different pollsters making independent methodological decisions.pic.twitter.com/4JKhJgjl3s
What about the CNN and Quinnipiac polls? Turns out, once you account for house effects, they're exactly the kinds of normal outliers you'd expect to see in this kind of distribution of polls.pic.twitter.com/1BLyW2TURs
Super excited for my first morning story at @FiveThirtyEight! With a ton of thanks to @ellawinthrop and @jazzmyth for the beautiful charts, and @sfrostenson, @CopyCurmudgeon, @DataDhrumil, @NateSilver538, and @micahcohen for everything else!
Nice piece, but it left me wondering about mode effects ... another piece in the works?
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