Fall 2020 - STAT 350 D100

Linear Models in Applied Statistics (3)

Class Number: 3804

Delivery Method: In Person

Overview

  • 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 11, 2020
    12:00 PM – 3:00 PM
    REMOTE LEARNING, Burnaby

  • Prerequisites:

    STAT 285, MATH 251, and one of MATH 232 or MATH 240.

Description

CALENDAR DESCRIPTION:

Theory and application of linear regression. Normal distribution theory. Hypothesis tests and confidence intervals. Model selection. Model diagnostics. Introduction to weighted least squares and generalized linear models. Quantitative.

COURSE DETAILS:

Course Details:

Lecture
: I will (hopefully) live-stream lectures Tuesdays and Fridays using either Zoom or Blackboard Collaborate Ultra through Canvas at SFU. The lectures will be recorded so that students in other time zones can watch at an appropriate time, but the lectures will only be online for one week.  I hope to have some students watching the live-stream so I can gauge student reaction and answer questions.    

Office hours: I will hold virtual office hours. These will not typically be one on one; instead students will be able to join a group conversation.  I will try my best to make myself available to students in other time zones.  Scheduling will not be clear until the course starts.  

Quizzes
: These are currently scheduled to be synchronous one hour long conducted through Zoom. This details will be discussed when the course starts.  

Project:
Instead of a final exam, students will complete a substantial project. This may include a challenging data analysis and also some theoretical development. Details provided during the semester.

Expectations:  Ideally, I would like to interact with students. Students in distant time zones will need to work out arrangements with me to discuss the course material through Zoom if they are not able to participate synchronously in lectures. Non-annotated lecture notes will be available through Canvas. 


Mode of teaching:
  • Lecture: synchronous, asynchronous
  • Tutorial: synchronous (TBA)
  • Midterm(s): synchronous; date: TBA
  • Remote invigilation (Zoom, Proctorio, or other approved software) will be used.  

Grading

  • Assignment 20%
  • Midterm(s) 40%
  • Final project 40%

NOTES:

Above grading is subject to change.

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:

Introducation to Linear Regression Analysis, 5th ed. by Montgomery, Peck, Vinning. Pulisher: Wiley

Available online for free through the SFU Library
ISBN: 978-0-470-54281-1

Department Undergraduate Notes:

Students with Disabilites:
Students requiring accommodations as a result of disability must contact the Centre for Accessible Learning 778-782-3112 or csdo@sfu.ca


Tutor Requests:
Students looking for a Tutor should visit http://www.stat.sfu.ca/teaching/need-a-tutor-.html. We accept no responsibility for the consequences of any actions taken related to tutors.

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).