Introduction to Bayesian data analysis lecture slides and supplementary content for the Penn State University Center for Astrostatistics (CASt) 20th Summer School in Statistics for Astronomers | Center for Astrostatistics, June 2025
In addition to the slides and supplementary content, this repo contains a recent tutorial article by instructor Tom Loredo and Duke University statistician Robert Wolpert. The ADS entry for the tutorial is:
- Bayesian inference: more than Bayes's theorem - Astrophysics Data System (Loredo & Wolpert 2024)
Also included is a brief, nontechnical note (unpublished) on the AIC, BIC, and DIC model selection criteria:
- Understanding information criteria for model selection (Loredo 2010)
Additionally, there is a tutorial note on handling correlated noise in time series modeling via generalized least squares, using an AR(1) hidden Markov model; it also briefly describes how to handle correlated noise in nonparametric bootstrap analysis of time series data:
- Notes on correlated noise and dependent data resampling (Loredo 2015)
Recorded lectures (available through July; requires passcode provided to summer school attendees via Slack):
- Lecture 1 (1h 15m)
- Lecture 2 (1h 22m)
- Extra topics (27m)