Simon Fraser University
Engaging the World

Course Outlines

Fall 2025 - STAT 452 D100

Statistical Learning and Prediction (3)

Class Number: 7102

Delivery Method: In Person

Overview

  • Course Times + Location:

    Sep 3 – Dec 2, 2025: Tue, 1:30–2:20 p.m.
    Burnaby

    Sep 3 – Oct 11, 2025: Thu, 12:30–2:20 p.m.
    Burnaby

    Oct 12 – Oct 22, 2025: Thu, 12:30–2:20 p.m.
    Burnaby

    Oct 23 – Dec 2, 2025: Thu, 12:30–2:20 p.m.
    Burnaby

  • Exam Times + Location:

    Dec 9, 2025
    Tue, 3:30–6:30 p.m.
    Burnaby

  • Prerequisites:

    STAT 260 and one of STAT 302 or STAT 305 or STAT 350 or ECON 333 or equivalent, with a minimum grade of C-.

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. Quantitative.

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

This course is part of the University Accreditation Program and meets specific requirements set by the Canadian Institute of Actuaries (CIA). Please consult the CIA website for full details on CIA accreditation.

Grading

  • Assignment 10%
  • Midterm Exam 25%
  • Class Project 25%
  • Final Exam 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 Libarary
ISBN-13: 978-1461471370.

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.

Department Undergraduate Notes:

Students with Disabilities:
Students requiring accommodations as a result of disability must contact the Centre for Accessible Learning 778-782-3112 or caladmin@sfu.ca.  


Tutor Requests:
Students looking for a tutor should visit https://www.sfu.ca/stat-actsci/all-students/other-resources/tutoring.html. We accept no responsibility for the consequences of any actions taken related to tutors.

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.