STAT_V 405 - 203

Bayesian Statistics

Bayesian approaches to statistical inference: probabilistic modelling, Bayesian inference workflows, approximation of posterior distributions supported by modelling languages, analysis of Bayesian procedures and posterior approximation methods. [3-0-1] Prerequisites: One of MATH_V 302, STAT_V 302, or MATH_V 418, and either STAT_V 305 or STAT_V 460.

Section
STAT_V 405 -203
Campus
Vancouver
Delivery Mode
In person
Term
2025-26 Winter Term 2 (UBC-V)
Instructional Format
Lecture
Credits
3.00
Start Date
End Date
Days
Tuesday, Thursday
Start Time
09:30 am
End Time
11:00 am
Instructor(s)
  • Charles Margossian
  • Alexandre Bouchard-Cote

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Vancouver, BC Canada V6T 1Z4

Okanagan Campus
3333 University Way
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