In July this year, my friend and long-term collaborator Michael Lee visited the grave of Thomas Bayes at Bunhill Fields in London. When Michael showed me the photo I was shocked. This is what Bayes’ tomb looks like in 2023: Overgrown with moss and generally in a sorry state, this is hardly a worthy monument to the man who pioneered…
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This is a DeepL-assisted translation of an article for the Dutch magazine Skepter (Wagenmakers, 2023). I am grateful to the editor, Hans van Maanen, for his efforts in rewriting my original draft. The painting is a self-portrait by René Magritte called ‘La Clairvoyance’ (1936 – proposed by van Maanen to accompany the article). TLDR; Can psychology students really anticipate the appearance…
read moreTL;DR When implementing order-restrictions in JAGS, only the “ones trick” appears to yield the correct result. Consider two unknown chances, $\theta_1$ and $\theta_2$, that are assigned independent beta priors: $\theta_1 \sim \text{beta}(1,1)$ and $\theta_2 \sim \text{beta}(1,1)$. Let’s visualize the joint posterior by executing JAGS code (Plummer, 2003) and plotting the samples that are obtained from the MCMC algorithm. This is…
read moreRecently we completed a multi-year Odyssey in order to obtain Bayes factors for partial correlations. The result is now available as a preprint. Instead of delving into the finer details of Bayes factors and posterior distributions, we will provide a concrete demonstration. Specifically, we will use Bayes factors for partial correlations to address a perennial question that has tormented children…
read moreTL;DR We just preprinted a manuscript on how to teach the correlation coefficient with rectangles and squares. Check out the cool pictures. Suggestions for improvement are welcome. Abstract The equation for the Pearson correlation coefficient can be represented in a scatter plot as the difference in area between concordant and discordant rectangles, scaled by an area that represents the maximum possible…
read moreIn the previous post I discussed the problem of old evidence and wrote “It is highly likely that my argument is old, or even beside the point. I am not an expert on this particular problem.” Sure enough, Andrew Fowlie kindly attended me to the following book chapter by Roger Rosenkrantz: Rosenkrantz, R. D. (1983). Why Glymour is a Bayesian. In…
read moreTo my shame and regret, I only recently found the opportunity to read the book “Bayesian philosophy of science” (BPS), by Jan Sprenger and Stephan Hartmann. It turned out to be a wonderful book, both in appearance, typesetting, and in contents. The book confirmed many of my prior beliefs ;- ) but it also made me think about the…
read moreRecently I was asked to introduce Bayesian inference in three minutes flat. In 10 slides, available at https://osf.io/68y75/, I made the following points: Bayesian inference is “common sense expressed in numbers” (Laplace) We start with at least two rival accounts of the world, aka hypotheses. These hypotheses make predictions, the quality of which determines their change in plausibility: hypotheses that…
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