Simon Fraser University
Engaging the World

Course Outlines

Fall 2020 - STAT 852 G100

Modern Methods in Applied Statistics (4)

Class Number: 3820

Delivery Method: In Person

Overview

  • Course Times + Location:

    Sep 9 – Dec 8, 2020: TBA, TBA
    Burnaby

    Sep 9 – Dec 8, 2020: TBA, TBA
    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

Mode of teaching:

Lecture: asynchronous (recorded)
Office hours: synchronous, time TBD

Grading

  • Assignments 50%
  • Project 1 20%
  • Project 2 30%

NOTES:

Above grading is subject to change.

Final Presentations will be held: Monday, Dec 14, 10:30-3:30, Location TBA, likely online.

Materials

MATERIALS + SUPPLIES:

Access to high-speed internet, webcam

Additional required software: Access to R, either installed or online (e.g., through Jupyter notebooks)

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 2020

Teaching at SFU in fall 2020 will be conducted primarily through remote methods. There will be in-person course components in a few exceptional cases where this is fundamental to the educational goals of the course. Such course components will be clearly identified at registration, as will course components that will be “live” (synchronous) vs. at your own pace (asynchronous). Enrollment acknowledges 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. To ensure you can access all course materials, we recommend you have access to a computer with a microphone and camera, and the internet. In some cases your instructor may use Zoom or other means requiring a camera and microphone to invigilate exams. If proctoring software will be used, this will be confirmed in the first week of class.

Students with hidden or visible disabilities who believe they may need class or exam accommodations, including in the current context of remote learning, are encouraged to register with the SFU Centre for Accessible Learning (caladmin@sfu.ca or 778-782-3112).