STAT 535 - Introduction to Bayesian Data Analysis
Class Session: Tuesday, January 16, 2018 - Monday, April 30, 2018
Credit: 3 semester hours of undergraduate/graduate credit
Prerequisites: STAT 511 and 515 or equivalent, or CSCE 582 [=STAT 582]
Instructor: Xiaoyan Lin
Principles of Bayesian statistics, including: one- and multi-sample analyses; Bayesian linear models; Monte Carlo approaches; prior elicitation; hypothesis testing and model selection; hierarchical models; selected advanced models; statistical packages such as WinBUGS and R.
Course will be delivered by Web conferencing utilizing Adobe Connect. Students may be present, either in person or online, for the class sessions on Tuesdays and Thursdays from 11:40 - 12:55 pm, or may view the class at a later time. USC Columbia students may attend classes in Wardlaw College room 116; all other students will view classes via the Internet. For students viewing the class live online, the Adobe Connect URL will be posted in Blackboard by the instructor prior to the first class meeting. Students viewing at a later time may visit the Web site video.sc.edu; click on the appropriate college/school and then your class link to view lectures. High-speed Internet access is required for Adobe Connect.
Course Delivery Type
A Web course is taught using one or more web delivery platforms such as Blackboard, Streaming Video, Adobe Connect etc. Students must have access to a high-speed Internet connection. More information will be provided by the instructor in the course syllabus.
(100% asynchronous - if course has any online or face-to-face meetings, live attendance will not be required. For any such sessions, there will be alternative ways to view or obtain the material covered).
Available online in Blackboard
Periodic assignments submitted through email.
. Video Streaming Assistance.
Information on technical requirements and getting started with video streaming can be found here.
Information is accurate as of October 17, 2018, 3:50 am (Subject to change)
Special Fee Notification
Students may be required to be proctored during online test completion. If students are unable to attend test proctoring sessions in person at the Distributed Learning office, additional fees may apply for online test proctoring if the course requires online testing.