Episode 119 - Advocating for Bayesian Inference with Brian Blais
Today’s guest is Brian Blais, a professor of Science at Bryant University. His approach to teaching statistical inference includes taking the Bayesian approach first instead of delegating it to an advanced or elective topic. We talk about the Bayesian vs Frequentist debate, how to navigate the disconnect between them, and the role of imagination when discovering truth.
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About Brian Blais
Brian Blais is a professor of Science at Bryant University and a research professor at the Institute for Brain and Neural Systems, Brown University. His main research interests involve the application of computational and statistical inference methods in areas of neuroscience, paleoclimate, and disease propagation. He has a broader interest in science education and the use skepticism in public discourse.
Twitter @bblais
Website https://bblais.github.io
Book (Amazon): Statistical Inference for Everyone
Book (free PDF Version): Statistical Inference for Everyone
Links
Brian Blais
Youtube: Statistical Heresies Talk, Slides
YouTube: Your Lack of Imagination can Kill You
Biography of ET Jaynes
ET Jaynes: Confidence Intervals vs Bayesian Intervals
Lindley: 1976 Thumbtack Paper
Tom Loredo: the optional stopping problem.
Theory that would Not Die (Bayes History)
Bayesian Analysis of Epidemics - Zombies, Influenza, and other Diseases
Related Episodes
Episode 105 on the Intuition of Bayes
Episode 98 on Bayesian Models in Political Forcasting
Episode 78 on Bayesian Thinking
Episode 22 on P-Hacking, one of the Pitfalls of Frequentist Methods in Practice
Episode 0 with our opening episode on how to Update Your Beliefs
