I recently finished reading Suzanne Buffam’s, A Pillow Book. This is a book of non-fiction poetry about thoughts and musings that may enter the mind as one drifts off to sleep, ranging from the historical consideration of pillows to comprehensive lists of sleeping aids. I’ve spent more than a few nights drifting off to sleep considering […]

One of the unique features of Bayesian statistical and computational modelling is the prior distribution. A prior distribution is both conceptually and formally necessary to do any sort of Bayesian modelling. If we are estimating the values of model parameters (e.g., regression coefficients), we do this by updating our prior beliefs about the parameter values […]

I see four benefits to the use of Bayesian inference:  Inclusion of prior information.  Regularization.  Handling models with many parameters or latent variables.  Propagation of uncertainty. Another selling point is a purported logical coherence – but I don’t really buy that argument so I’ll forget that, just as I’ll also set aside philosophical objections against […]

The #BayesInPsych Digital Event kicked off yesterday and as the leading Guest Editor of the special issue of Psychonomic Bulletin & Review, I take this opportunity to provide more context for this week’s posts. The simple act of deciding which among competing theories is most likely—or which is most supported by the data—is the most […]

Your brilliant PhD student ran an experiment last week that investigated whether chanting the words “unicorns, Brexit, fairies” repeatedly every morning before dawn raises people’s estimates of the likelihood that they will win the next lottery in comparison to a control group that instead chants “reality, reality, reality”. The manipulation seems to have worked, as […]