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This came in a mass email:

Statistical Horizons is excited to present Applied Bayesian Data Analysis taught by Dr. Roy Levy on Thursday, February 18–Saturday, February 20. In this seminar, you will get both a practical and theoretical introduction to Bayesian methods in just 3 days.

Topics include:
Model construction
Specifying prior distributions
Graphical representation of models
Practical aspects of Markov chain Monte Carlo (MCMC) estimation
Model comparisons
Evaluating hypotheses and data-model fit
Each day will follow this schedule:
10:00am-2:00pm ET: Live lecture via Zoom
4:00pm-5:00pm ET: Live “office hour” via Zoom (Thursday and Friday only)

I don’t know Statistical Horizons, Dr. Roy Levy, and I have no idea whether this course is any good. It could be wonderful, or not; I just don’t know.

But what makes me happy is the list of topics that they’re covering. Back when I was a student, if there were a short course on Bayesian statistics, it would’ve been all about the theory of optimal estimators, Jeffreys priors, crap like that. But now its all so . . . applied. And relevant. They even have something on evaluating fit of model to data, a topic that never would’ve come up in the bad old days. I’m so happy to see this! Even more so because I don’t know this group, which implies that this Bayesian data analysis perspective is in places I hadn’t even been aware of.


  1. Mikhail Шubin says:

    +1, wonderful list of topics, something I would be happy to teach myself.

    Topics look applied, but not too much applied (i.e. not “how to run linear regression in R and never ever thing about that coefficients mean, because Ecclesiastes 1:18”)

  2. I do know Roy fairly well. He was a student of my good friend Bob Mislevy, and has been doing work with Bayesian Analysis in educational settings for a number of years. I’ve team taught workshops with him in the past, and he does an excellent job.

    And yes, a lot of statistics I’ve been doing in the college of ed is much more focused on practical data analysis than theory.

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