Spring 2021 - STAT 460 D100

Bayesian Statistics (3)

Class Number: 3344

Delivery Method: In Person

Overview

  • Course Times + Location:

    Jan 11 – Apr 16, 2021: Tue, 10:30 a.m.–12:20 p.m.
    Burnaby

    Jan 11 – Apr 16, 2021: Fri, 10:30–11:20 a.m.
    Burnaby

  • Exam Times + Location:

    Apr 17, 2021
    Sat, 3:30–6:30 p.m.
    Burnaby

  • Prerequisites:

    STAT 330 and 350.

Description

CALENDAR DESCRIPTION:

The Bayesian approach to statistics is an alternative and increasingly popular way of quantifying uncertainty in the presence of data. This course considers comparative statistical inference, prior distributions, Bayesian computation, and applications. Quantitative.

COURSE DETAILS:

Course Outline:

1. The basics:
      the Bayesian paradigm
      comparative statistical inference
2. Priors:
      conjugate priors
      prior elicitation
      reference priors
      improper priors
      discrete mass priors
3. Computations:
      quadrature
      importance sampling
      Markov chain Monte Carlo
4. Other topics as time permits: 
      testing via Bayes factors
      interval and point estimation
      elementary decision theory
      hierarchical models
      Dirichlet process
5. Applications


Mode of Teaching:

  • Lecture: Mixed (Synchronous and Asynchronous)
  • Exams: Synchronous

Grading

  • Assignments 25%
  • Midterm 25%
  • Final Exam 50%

NOTES:

Above grading is subject to change.

Materials

MATERIALS + SUPPLIES:

Access to high-speed internet, webcam.

RECOMMENDED READING:

Bayesian Data Analysis, 3rd Edition (Gelman, Carlin, Stern, Dunson, Vehtari, and Rubin)

Department Undergraduate Notes:

Students with Disabilities:
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 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 (caladmin@sfu.ca or 778-782-3112).