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

Related links:

Andrew Gelman at Columbia University

Andrew Gelman – The Statistical Crisis in Science (Dec 2014)

CDC – Excess Deaths Associated with COVID-19 (Jul 2020)

E.T. Jaynes – Probability Theory (Chapter 5 for quote)

David Shor – Interview with New York Magazine (Jul 2020)

Katie Herzog – Discussion on Cancel Culture with The Filter (Jul 2020)

Nassim Taleb – Uncertainty (Mar 2020)

Matt Asher – Unreliable Friend Distribution (May 2013)

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