Fall 2021 - STAT 452 D100
Statistical Learning and Prediction (3)
Class Number: 5080
Delivery Method: In Person
Course Times + Location:
Tu 10:30 AM – 12:20 PM
REMOTE LEARNING, Burnaby
Fr 10:30 AM – 11:20 AM
REMOTE LEARNING, Burnaby
Exam Times + Location:
Dec 19, 2021
12:00 PM – 3:00 PM
REMOTE LEARNING, Burnaby
Prerequisites:STAT 302 or STAT 305 or STAT 350 or ECON 333 or equivalent, with a minimum grade of C-.
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.
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
Mode of Teaching
- Lecture: Synchronous/Asynchronous
- Tutorial: Synchronous/Asynchronous
- Quizzes and Midterm: Synchronous; Date: TBA
- Final exam: Synchronous; date: TBA
- Remote invigilation (Zoom, or other approved software) will be used.
This course is accredited under the Canadian Institute of Actuaries (CIA) University Accreditation Program (UAP). Details of required courses and grades at Simon Fraser University are available here (https://www.cia-ica.ca/membership/university-accreditation-program-home/accredited-universities/accredited-university-detail?pav_universityid=236ca8c4-60e5-e511-80b9-00155d111030).
In addition to the specific university’s internal policies on conduct, including academic misconduct, candidates pursuing credits for writing professional examinations shall also be subject to the Code of Conduct and Ethics for Candidates in the CIA Education System and the associated Policy on Conduct and Ethics for Candidates in the CIA Education System. For more information, please visit Obtaining UAP Credits (https://www.cia-ica.ca/membership/university-accreditation-program-home/information-for-candidates/obtaining-uap-credits).
- Assignment 10%
- Individual Project 1 10%
- Individual Final Project 15%
- Midterm Test 30%
- Final 35%
Above grading is subject to change.
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 on-line through the SFU Libarary
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 email@example.com
Students looking for a tutor should visit hhttps://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.
ACADEMIC INTEGRITY: YOUR WORK, YOUR SUCCESS
SFU’s Academic Integrity web site 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
TEACHING AT SFU IN FALL 2021
Teaching at SFU in fall 2021 will involve primarily in-person instruction, with approximately 70 to 80 per cent of classes in person/on campus, with safety plans in place. Whether your course will be in-person or through remote methods will be clearly identified in the schedule of classes. You will also know at enrollment whether remote course components will be “live” (synchronous) or at your own pace (asynchronous).
Enrolling in a course acknowledges that you are able to attend in whatever format is required. You should not enroll in a course that is in-person if you are not able to return to campus, and should be aware that remote study may entail different modes of learning, interaction with your instructor, and ways of getting feedback on your work than may be the case for in-person classes.
Students with hidden or visible disabilities who may need class or exam accommodations, including in the context of remote learning, are advised to register with the SFU Centre for Accessible Learning (firstname.lastname@example.org or 778-782-3112) as early as possible in order to prepare for the fall 2021 term.