Ep 12: Andrew Gelman on Data, Modeling, and Uncertainty Amidst the Forking Paths

A conversation with Andrew Gelman, professor of statistics and political science and director of the Applied Statistics Center at Columbia University. Andrew is the author of a number of books on topics such as Bayesian Data Analysis, how stats should be taught, and voting patterns in politics. Our conversation topics included:

  • Forking paths in data analysis
  • To what extent to prior beliefs determine study outcomes
  • Data integrity in the era of COVID
  • Unreliable friends and modeling uncertainty

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