Simon Fraser University
Engaging the World

Course Outlines

Fall 2026 - STAT 652 G100

Statistical Learning and Prediction (3)

Class Number: 6112

Delivery Method: In Person

Overview

  • Course Times + Location:

    Sep 9 – Dec 6, 2026: Tue, 1:30–2:20 p.m.
    Burnaby

    Sep 9 – Dec 6, 2026: Thu, 12:30–2:20 p.m.
    Burnaby

  • Prerequisites:

    STAT 302 or STAT 305 or STAT 350 or STAT 604 or STAT 605 or ECON 333 or equivalent.

Description

CALENDAR DESCRIPTION:

An introduction to the essential modern supervised and unsupervised statistical learning methods. Topics include review of linear regression, classification, statistical error measurement, flexible regression and classification methods, clustering and dimension reduction. Open only to graduate students in departments other than Statistics and ActSci. Students with credit for STAT 452 may not take this course for further credit.

COURSE DETAILS:

Outline:

1. Statistical Learning and Prediction
2. Measuring prediction error
3. Linear regression essentials and extensions
4. Classification: Predicting categorical data
5. Variable selection in linear regression
6. Non-linear regression methods
7. Trees and ensembles
8. Additional modern prediction methods
9. Unsupervised learning: clustering and dimension reduction

Grading

  • Assignment 10%
  • Midterm Exam 25%
  • Class Project 25%
  • Final Project 40%

NOTES:

Above grading is subject to change.

Materials

REQUIRED READING:

An Introduction to Statistical Learning with Applications in R. Gareth James, Daniela Witten, Trevor Hastie and Robert Tibshirani (2013). New York: Springer. 

Book is available for free online through the SFU Library
ISBN-13: 978-1461471370.

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.