Course by tag

Open Science Hypothesis Testing

This three-day course discusses the evaluation of theory-based hypotheses using p-values, the Bayes factor, and information criteria. Contemporary phenomena will be covered, like publication bias; questionable research practices; the replication crisis; the statistical evaluation of replication studies; and studies in which multiple data sets are used to evaluate the same research question. The course will be non-technical in nature, that is, it is targeted at students and researchers who want to use the approaches presented for the evaluation of their own data.

A gentle introduction to Bayesian Estimation

This course introduces all the essential ingredients needed to start Bayesian estimation and inference. We discuss specifying priors, obtaining the posterior, prior/posterior predictive checking, sensitivity analyses, and the usefulness of a specific class of priors called shrinkage priors. We propose strategies for reproducibility and reporting standards, outlining the WAMBS-checklist (when to Worry and how to Avoid the Misuse of Bayesian Statistics). We have prepared many exercises to enable students to get hands-on experience.