Fall 2026 - STAT 852 G100
Modern Methods in Applied Statistics (4)
Class Number: 6136
Delivery Method: In Person
Overview
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Course Times + Location:
Sep 9 – Dec 6, 2026: Wed, 2:30–4:20 p.m.
BurnabySep 9 – Dec 6, 2026: Fri, 8:30–10:20 a.m.
Burnaby
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Instructor:
Lin Zhang
lza177@sfu.ca
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Prerequisites:
STAT 830 and STAT 853 or permission of instructor.
Description
CALENDAR DESCRIPTION:
An advanced treatment of modern methods of multivariate statistics and non-parametric regression. Topics may include: (1) dimension reduction techniques such as principal component analysis, multidimensional scaling and related extensions; (2) classification and clustering methods; (3) modern regression techniques such as generalized additive models, Gaussian process regression and splines.
COURSE DETAILS:
Course Outline:
- Problems with high dimensions,
- Variable selection: stepwise, shrinkage, LASSO, and penalized likelihood
- Modern regression techniques: Splines, trees, generalized additive models
- Ensemble learning methods
- Classification and clustering methods
- Dimension reduction techniques: Principal components and multidimensional scaling
Grading
- Project proposal 10%
- Project 1 50%
- Project 2 40%
NOTES:
Above grading is subject to change.
Materials
REQUIRED READING:
The Elements of Statistical Learning: Data Mining, Inference, and Prediction (2nd ed.) by Trevor Hastie, Robert Tibshirani, Jerome Friedman. Publisher: Springer
Book is available online through the SFU Library
eBook: ISBN 978-0-387-84858-7
Hardcover: ISBN 978-0-387-84857-0
RECOMMENDED READING:
Modern Multivariate Statistical Analysis: Regression, Classification, and Manifold Learning. by Alan J. Izenman. Publisher: Springer
Book is available for free online through the SFU Library
eBook: ISBN 978-0-387-78189-1
Hardcover: ISBN 978-0-387-78188-4
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:
- SFU’s Academic Integrity Policy: S10-01 Policy
- SFU’s Academic Integrity website, which includes helpful videos and tips in plain language: Academic Integrity at SFU
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.