PHYSICS 366: Statistical Methods in Astrophysics

Course notes and resources for Stanford University graduate course Physics 366.

Course Description

This course is intended to provide an introduction to modern statistical methodology, and its applications to problems in astrophysics and cosmology, and is aimed at graduate students intending to do research in this area. We strongly encourage most first and second year students working in KIPAC to take the course. Our goal is to provide a background that will be directly relevant to the kind of problems that typical KIPAC students will encounter in their research.

Course Objectives

Our goal is that students taking this course will:


Start by looking at the Overview to understand how this course works, and Getting Started to get up and running with Python and Jupyter, if needed. Enrolled students should also read the Assignments page to see what is expected.

The course content can be browsed here in static HTML format. This is sufficient for the notes, but to do the tutorials you will need to download them in Jupyter notebook format from the GitHub repository.

Notes and tutorials are listed in reasonable order below, but a better way to navigate the course may be through this nifty dependency graph (via Mermaid).




All materials Copyright 2015, 2017, 2019, 2021 Adam Mantz, Phil Marshall and Claire Hébert, and distributed for copying and extension under the GPLv2 License, unless otherwise noted. If you have any feedback for us, please write us an issue.