Fall 2021 - STAT 852 G100

Modern Methods in Applied Statistics (4)

Class Number: 5078

Delivery Method: In Person

Overview

  • Course Times + Location:

    Sep 8 – Dec 7, 2021: 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 50%
  • Projects 50%

NOTES:

Above grading is subject to change.

Final Presentations will be held: Monday, December 13th, 10:30-3:30 in BLU9655

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 on-line 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 on-line through the SFU Library

eBook: ISBN 978-0-387-78189-1
Hardcover: ISBN 978-0-387-78188-4

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 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 (caladmin@sfu.ca or 778-782-3112) as early as possible in order to prepare for the fall 2021 term.