Workshop

Statistics for Astrophysics: Bayesian Workflow

Francesca Capel

This mini-course offers a hands-on introduction to the principles and practices of Bayesian data analysis, with a focus on building and evaluating models that address real scientific questions. We begin with the foundations of Bayesian statistics and explore Markov chain Monte Carlo (MCMC) methods for posterior inference. Participants will learn how to translate a scientific problem into a statistical model, and how to critically assess model performance through diagnostics and validation techniques. The take-away is an iterative, transparent analysis workflow that supports robust and reproducible scientific inference.