WARNING: This post is about chess. If you don’t play chess you might want to skip this post. During a week-long family vacation I engaged obsessively in both the highest and the lowest form of human intellectual activity. Obviously the highest form is chess endgame study composition; the lowest form surely is online “bullet” chess. Miraculously, my bullet chess adventures…
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As regular readers of this blog already know, Bayes factors rule! In practice, however, the calculation of Bayes factors is seriously hampered by computational difficulties. In a new paper, we revive two theorems put forth by Alan Turing and Jack Good and propose a step-by-step approach to use them as a check for the calculation of Bayes factors. According to…
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I am thrilled to report that, after considerable discussion, the University of Amsterdam has agreed to ban the teaching of p-values for first-year students at the Faculty of Social and Behavioural Sciences. The new policy will take effect at the start of the new academic year, and its introduction was facilitated by the fact that I am taking over from…
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Inspired by a recent article on Ockham’s razor, this post shows how a simple set of polyhedral dice can clarify the basic idea underlying Bayes factors (or likelihood ratios). The ideas may be used in a classroom demonstration, and each of the lessons below could be discovered by the students themselves. Meet the Family Our polyhedral dice are a family…
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Klaas Sijtsma is an experienced psychometrician and former rector magnificus of Tilburg University. In “Never waste a good crisis”, Sijtsma discusses academic fraud (and in particular the infamous Stapel case, the fallout of which he had to deal with as dean of the School of Social and Behavioral Sciences at Tilburg University) and questionable research practices (henceforth QRPs). Importantly, Sijtsma…
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In the previous post I asked the following question: Here is a test of your Bayesian intuition: Suppose you assign a binomial chance parameter θ a beta(2,2) prior distribution. You anticipate collecting two observations. What is your expected posterior distribution? NB. ChatGPT 3.5, Bard, and the majority of my fellow Bayesians get this wrong. The answer will be revealed in…
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Here is a test of your Bayesian intuition: Suppose you assign a binomial chance parameter θ a beta(2,2) prior distribution. You anticipate collecting two observations. What is your expected posterior distribution? NB. ChatGPT 3.5, Bard, and the majority of my fellow Bayesians get this wrong. The answer will be revealed in the next post.
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Since 2017, Dora Matzke and I have been teaching the master course “Bayesian Inference for Psychological Science”. Over the years, the syllabus for this course matured into a book (and an accompanying book of answers) titled “Bayesian inference from the ground up: The theory of common sense”. The current plan is to finish the book in the next few months,…
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