Simon Fraser University
Engaging the World

Course Outlines

Fall 2025 - STAT 852 G100

Modern Methods in Applied Statistics (4)

Class Number: 7156

Delivery Method: In Person

Overview

  • Course Times + Location:

    Sep 3 – Dec 2, 2025: Tue, Thu, 10:30 a.m.–12:20 p.m.
    Burnaby

  • 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:

  1. Problems with high dimensions,
  2. Variable selection: stepwise, shrinkage, LASSO, and penalized likelihood
  3. Modern regression techniques: Splines, trees, generalized additive models
  4. Ensemble learning methods
  5. Classification and clustering methods
  6. Dimension reduction techniques: Principal components and multidimensional scaling

Grading

  • Assignments 35%
  • Midterm Project 25%
  • Final Project 40%

NOTES:

Above grading is subject to change.

Final Presentations will be held: TBA

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

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.