Spring 2022 - STAT 675 G100

Applied Discrete Data Analysis (3)

Class Number: 6734

Delivery Method: In Person

Overview

  • Course Times + Location:

    Jan 10 – Apr 11, 2022: Mon, 10:30 a.m.–12:20 p.m.
    Burnaby

    Jan 10 – Apr 11, 2022: Wed, 10:30–11:20 a.m.
    Burnaby

  • Exam Times + Location:

    Apr 20, 2022
    Wed, 12:00–3:00 p.m.
    Burnaby

  • Prerequisites:

    STAT 302 or STAT 305 or STAT 650 or ECON 333 or permission of instructor. Open only to graduate students in departments other than Statistics and Actuarial Science.

Description

CALENDAR DESCRIPTION:

Introduction to standard methodology for analyzing categorical data including chi-squared tests for two- and multi-way contingency tables, logistic regression, and loglinear (Poisson) regression. Students with credit for STAT 402 or 602 may not take this course for further credit.

COURSE DETAILS:

Course Outline:

This course introduces students to the most important methods for analyzing categorical data. The focus of the course is twofold: classical methods in categorical data analysis, such as chi-squared tests, and logistic and loglinear (Poisson) regression techniques.

  1. Introduction and review: likelihood methods and R
  2. Analysis with binary variables 
  3. Analysis with multicategory variables 
  4. Analysis with count response 
  5. Model selection and evaluation
  6. Further topics

Grading

  • Assignments 20%
  • Midterms 50%
  • Project 30%

NOTES:

Graduate students in STAT 675 will be graded separately from students in STAT 475 using standards appropriate to graduate level course work.

Above grading is subject to change.

Materials

REQUIRED READING:

Required Text:

Analysis of Categorical Data with R.,
by: Christopher R. Bilder and Thomas M. Loughin. Publisher: CRC Press

Book is available through the SFU Bookstore


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 SPRING 2022

Teaching at SFU in spring 2022 will involve primarily in-person instruction, with safety plans in place.  Some courses will still be offered through remote methods, and if so, this 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 spring 2022 term.