(This article was originally published at Statistical Modeling, Causal Inference, and Social Science, and syndicated at StatsBlogs.)
Probability and Statistics in the Study of Voting and Public Opinion
Elections have both uncertainty and variation and hence represent a natural application of probability theory. In addition, opinion polling is a classic statistics problem and is featured in just about every course on the topic. But many common intuitions about probability, statistics, and voting are flawed. Some examples of widely-held but erroneous beliefs: votes should be modeled by the binomial distribution; sampling distributions and standard errors only make sense under random sampling; poll averaging is a simple problem in numerical analysis; survey sampling is a long-settled and boring area of statistics. In this talk, we discuss some challenging problems in probability and statistics that arise from the study of opinion and elections.
I’ll be speaking at the Applied Probability and Risk Seminar, 1:10-2:10pm in 303 Mudd Hall, Columbia University.
P.S. I discussed work from these papers:
http://www.stat.columbia.edu/~gelman/research/published/hansen_paper_2.pdf
http://www.stat.columbia.edu/~gelman/research/published/blocs.pdf
http://www.stat.columbia.edu/~gelman/research/published/STS027.pdf
http://www.stat.columbia.edu/~gelman/research/published/gelmankatzbafumi.pdf
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