Learning to love Bayesian statistics
Date: This event took place live on May 18 2016
Presented by: Allen B. Downey
Duration: Approximately 60 minutes.
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Bayesian methods are well-suited for many applications because they provide concrete guidance for making decisions under uncertainty. But myths about the Bayesian approach continue to slow its adoption. In this webcast I unpack these myths and explain the pros and cons of Bayesian methods compared to classical statistics. I also suggest ways to get started learning Bayesian statistics.
About Allen B. Downey
Allen Downey is a Professor of Computer Science at Olin College of Engineering. He has taught at Wellesley College, Colby College and U.C. Berkeley. He has a Ph.D. in Computer Science from U.C. Berkeley and Master's and Bachelor's degrees from MIT.