Upcoming workshop dates:

• Session 1: Friday Feb 8, 12:30-2:20pm, Clearihue C112
• Session 2: Friday Feb 15, 12:30-2:20pm, Clearihue C112

This is a hands-on workshop on Bayesian inference and MCMC (Markov Chain Monte Carlo) algorithms. All of the material will be posted here, including "Session 0", which contains installation instructions and recommended review to be completed before the first session.

Click here to register: https://goo.gl/forms/cPfks6wnZRTmupGu2

Everyone is welcome! Open to students, postdocs, staff and faculty.

The overall goal of the workshop is to have everyone leave with an understanding of the basic concepts of Bayesian inference and specifically, how MCMC works. In particular, participants will leave with a working, ready-for-research implementation of the emcee python package, arguably the most popular MCMC package for astronomy.

The plan of the two specific sessions are:

• Session 1: Introduction to Bayesian inference (vs. frequentist approaches), introduce the basic MCMC concepts. Implementing a basic MCMC solution to a simple fitting problem using the python package “emcee”.
• Session 2: Advanced concepts such as testing for convergence, considering multi-modal solutions, and comparing different sampling algorithms. Discussion on how to interpret and critique MCMC results in papers.

The format will be a bit of lecture followed by a lot of hands-on computer work and discussion, with helpers roaming around to debug (let me know if you can be a helper).