Fall 2024 - STAT 652 G100
Statistical Learning and Prediction (3)
Class Number: 3034
Delivery Method: In Person
Overview
-
Course Times + Location:
Sep 4 – Dec 3, 2024: Tue, 1:30–2:20 p.m.
Location: TBASep 4 – Dec 3, 2024: Thu, 12:30–2:20 p.m.
Location: TBA
-
Instructor:
Owen Ward
1 778 782-7782
-
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.
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
SFU’s Academic Integrity website http://www.sfu.ca/students/academicintegrity.html is filled with information on what is meant by academic dishonesty, where you can find resources to help with your studies and the consequences of cheating. Check out the site for more information and videos that help explain the issues in plain English.
Each student is responsible for his or her conduct as it affects the university community. Academic dishonesty, in whatever form, is ultimately destructive of the values of the university. Furthermore, it is unfair and discouraging to the majority of students who pursue their studies honestly. Scholarly integrity is required of all members of the university. http://www.sfu.ca/policies/gazette/student/s10-01.html