“Statistical insights into public opinion and politics” (my talk for the Columbia Data Science Society this Wed 9pm)

7pm in Fayerweather 310:

Why is it more rational to vote than to answer surveys (but it used to be the other way around)? How does this explain why we should stop overreacting to swings in the polls? How does modern polling work? What are the factors that predict election outcomes? What’s good and bad about political prediction markets? How do we measure political polarization, and what does it imply for our politics? We will discuss these and other issues in American politics and more generally how we can use data science to learn about the social world.

People can read the following articles ahead of time if they would like.

Short:
https://slate.com/news-and-politics/2018/11/midterms-blue-wave-statistics-data-analysis.html
http://www.slate.com/articles/news_and_politics/politics/2016/08/why_trump_clinton_won_t_be_a_landslide.html
https://slate.com/news-and-politics/2016/08/dont-be-fooled-by-clinton-trump-polling-bounces.html
http://www.slate.com/articles/news_and_politics/moneybox/2016/07/why_political_betting_markets_are_failing.html

Longer:
http://www.stat.columbia.edu/~gelman/research/published/what_learned_in_2016_5.pdf
http://www.stat.columbia.edu/~gelman/research/published/swingers.pdf

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