Simon Fraser University
Engaging the World

Course Outlines

Summer 2026 - PHYS 887 G100

Special Topics VII (1)

Bayesian Inference for Physics Data Analysis

Class Number: 4260

Delivery Method: In Person

Overview

  • Course Times + Location:

    May 4 – May 15, 2026: Mon, Tue, Wed, Thu, Fri, 9:30–11:00 a.m.
    Burnaby

Description

COURSE DETAILS:

The goal of the course is to introduce students to the basics of Bayesian inference methods at the graduate level. Apart from being an intellectually unified and satisfying approach to data analysis, the course will connect to new ideas on machine learning.

This is a one-credit course, with 13 hours of lecture, delivered as  (8 x 1.5 + 1 x 1) hr.  The tentative plan is to schedule these over two weeks in May, for example starting May 4 or 11.  

There will be two problem sets.  The first will be due the second Monday (Tuesday if there is a holiday); the second will be due after the lectures are done.

COURSE-LEVEL EDUCATIONAL GOALS:

Tentative Outline:

1.  Intro to inference, estimation of a single parameter from data

2.  More on one-parameter inference, central-limit theorem

3.  Distributions with fat tails; curve fitting

4.  Inferring multiple parameters; covariance; normal equations

5.  Functions of random variables (“error propagation” as a special case)

6.  Numerical methods (sampling one variable)

7.  Markov Chain Monte Carlo (MCMC); Hamiltonian Monte Carlo (HMC)

8.  Model selection 1:  odds ratios, priors

9.  Model selection 2:  overlaps with machine learning (AIC vs BIC, double descent, diffusion)

Grading

  • TBA 100%

Materials

MATERIALS + SUPPLIES:

Primary text

• D. S. Sivia and J. Skilling, Data Analysis:  A Bayesian tutorial (2nd. ed., Oxford, 2006)

REQUIRED READING NOTES:

Your personalized Course Material list, including digital and physical textbooks, are available through the SFU Bookstore website by simply entering your Computing ID at: shop.sfu.ca/course-materials/my-personalized-course-materials.

Graduate Studies Notes:

Important dates and deadlines for graduate students are found here: http://www.sfu.ca/dean-gradstudies/current/important_dates/guidelines.html. The deadline to drop a course with a 100% refund is the end of week 2. The deadline to drop with no notation on your transcript is the end of week 3.

Registrar Notes:

ACADEMIC INTEGRITY: YOUR WORK, YOUR SUCCESS

At SFU, you are expected to act honestly and responsibly in all your academic work. Cheating, plagiarism, or any other form of academic dishonesty harms your own learning, undermines the efforts of your classmates who pursue their studies honestly, and goes against the core values of the university.

To learn more about the academic disciplinary process and relevant academic supports, visit: 


RELIGIOUS ACCOMMODATION

Students with a faith background who may need accommodations during the term are encouraged to assess their needs as soon as possible and review the Multifaith religious accommodations website. The page outlines ways they begin working toward an accommodation and ensure solutions can be reached in a timely fashion.