Spring 2021 - STAT 831 G100
Statistical Theory II (4)
Class Number: 8021
Delivery Method: In Person
Course Times + Location:
We, Fr 4:30 PM – 6:20 PM
REMOTE LEARNING, Burnaby
Prerequisites:STAT 830 or permission from the instructor.
Advanced mathematical statistics for PhD students. Topics in probability theory including densities, expectation and random vectors and matrices are covered. The theory of point estimation including unbiased and Bayesian estimation, conditional distributions, variance bounds and information. The theoretical framework of hypothesis testing is covered. Additional topics that may be covered include modes of convergence, central limit theorems for averages and medians, large sample theory and empirical processes.
This course will cover measure theoretic probability, random variables, expectation, product spaces, independence, derivatives, conditional probability, characteristic functions, and limit theorems. While rigorous proof is emphasized as the way to understand the material, the material is based on a course that has been taught to students in statistics, mathematics, engineering and science for many years. Course work will be based on homework assignments.
Mode of Teaching: Both synchronous and asynchronous
- Problems Sets 100%
A FIRST LOOK AT RIGOROUS PROBABILITY THEORY
BY ROSENTHAL, JEFFREY S.
PUBLISHER: WORLD SCIENTIFIC PUBLISHING CO PTE LTD
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.
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 2021
Teaching at SFU in spring 2021 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 (firstname.lastname@example.org or 778-782-3112).