#43 Election Forecasting and Polling

Hugo speaks with Andrew Gelman about statistics, data science, polling, and election forecasting. Andy is a professor of statistics and political science and director of the Applied Statistics Center at Columbia University and this week we’ll be talking the ins and outs of general polling and election forecasting, the biggest challenges in gauging public opinion, the ever-present challenge of getting representative samples in order to model the world and the types of corrections statisticians can and do perform. "Chatting with Andy was an absolute delight and I cannot wait to share it with you!"-Hugo 

 Links from the show 

FROM THE INTERVIEW

• Andrew's Blog 
• Andrew on Twitter 
• We Need to Move Beyond Election-Focused Polling (Gelman and Rothschild, Slate)
• We Gave Four Good Pollsters the Same Raw Data. They Had Four Different Results (Cohn, The New York Times).
• 19 things we learned from the 2016 election (Gelman and Azari, Science, 2017)
• The best books on How Americans Vote (Gelman, Five Books)
• The best books on Statistics (Gelman, Five Books)
• Andrew's Research 

FROM THE SEGMENTS

Statistical Lesson of the Week (with Emily Robinson at ~13:30)

• The five Cs (Loukides, Mason, and Patil, O'Reilly)

Data Science Best Practices (with Ben Skrainka~40:40)

• Oberkampf & Roy’s Verification and Validation in Scientific Computing provides a thorough yet very readable treatment 
• A comprehensive framework for verification, validation, and uncertainty quantification in scientific computing (Roy and Oberkampf, Science Direct)

 Original music and sounds by The Sticks.

Episode source