Spring 2020 - STAT 675 G100
Applied Discrete Data Analysis (3)
Class Number: 4021
Delivery Method: In Person
Course Times + Location:
Tu 10:30 AM – 11:20 AM
AQ 3005, Burnaby
Th 9:30 AM – 11:20 AM
AQ 3005, Burnaby
Exam Times + Location:
Apr 18, 2020
12:00 PM – 3:00 PM
TAKE HOME-EXAM, Burnaby
Prerequisites:STAT 302 or STAT 305 or STAT 650 or BUEC 333 or permission of instructor. Open only to graduate students in departments other than Statistics & Actuarial Science.
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.
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.
- Introduction and review: likelihood methods and R
- Analysis with binary variables
- Analysis with multicategory variables
- Analysis with count response
- Model selection and evaluation
- Further topics
- Assignments 10%
- Midterms 40%
- Final Exam 50%
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.
Analysis of Categorical Data with R., by: Christopher R. Bilder and Thomas M. Loughin. Publisher: CRC Press
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.
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
ACADEMIC INTEGRITY: YOUR WORK, YOUR SUCCESS