This website hosts the course materials and labs for PHYS/ASTR 7730, Statistical and Computational Methods in Physics and Astronomy, taught by Yao-Yuan Mao at the University of Utah, starting from Spring 2024.


This course is scheduled to be offered again in Spring 2025.

Course Description#

This course will discuss a few widely applicable statistical and computational methods of analyzing and modeling phenomena in astrophysics, biophysics, and physics in general. The learning objective is to apply the methods learned in this course to connect experimental or observational data with underlying physical processes through numerical simulations and statistical analyses. Topics that will be covered in this course include stochastic process simulations, Monte Carlo methods, Bayesian analysis, and basic machine learning algorithms. This is a graduate-level course. The course will use Python as the programming language for demonstration and use many examples in physics and astronomy. Students are assumed to be comfortable in programming and have an introductory-level knowledge in physics.


No required course prerequisites, but students are expected to be comfortable in coding (preferably in Python) to be able to complete assignments and projects independently.

Spring 2024 Course Information#


  • Meeting Time & Days: 3:00–4:45 pm on Mondays & Wednesdays

  • Meeting Location: South Physics (PHYS) 205

  • Credit Hours: 4

Instructor Information#

  • Instructor: Yao-Yuan Mao

  • Instructor Office: INSCC 314

  • Instructor Email: yymao@astro.utah.edu

  • Office hours: 1:45–2:45 pm on Mondays