Physics 201 | Last taught Spring 2023
This course covers methods for analyzing experimental data. Students will learn a Bayesian framework for statistical inference, modern computational methods such as Markov-chain Monte Carlo techniques, and the application to problems in particle physics, biophysics, condensed matter, applied physics, astrophysics, and other fields. The course emphasizes an intuitive, principled approach to data analysis and will involve discussions of ethics and reproducible research.