Bayesian statistics

Federica Giardina is a public health researcher currently working as an assistant professor in Biostatistics at Radboud University Medical Center (Radboud UMC) in Nijmegen (the Netherlands). She uses Bayesian methods to answer questions in infectious disease epidemiology. Bayesian statistics allows the user to specify prior information to the chosen model. This method is useful, for example, when working with datasets with partially missing data, as is often the case in public health records.

Federica will introduce the Stan programming language (https://mc-stan.org/) with examples of modeling performed with the rstan package.

It's a short introduction, a sweet taste if you like, of a very broad topic that we have been anxious to learn about. Please join us!