STAT 341 Spring 2013 Bayesian Statistics (Q)

The probability of an event can be defined in two ways: (1) the long-run frequency of the event, or (2) the belief that the event will occur. Classical statistical inference is built on the first definition given above, while Bayesian statistical inference is built on the second. This course will introduce the student to methods in Bayesian statistics. Topics covered include: prior distributions, posterior distributions, conjugacy, and Bayesian inference in single-parameter, multi-parameter, and hierarchical models. The computational issues associated with each of these topics will also be discussed.
Class Format: lecture
Requirements/Evaluation: evaluation will be based on homework and exams
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Prerequisites: Statistics 201 and Mathematics 211, or permission of instructor
Enrollment Preference: Juniors and Seniors, Math Majors
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Divisional Attributes: Division III,Quantitative and Formal Reasoning
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Enrollment Limit: none
Expected Enrollment: 10
Class Number: 3242
CLASSES ATTR INSTRUCTORS TIMES CLASS NUMBER
STAT341-01(S) LEC Bayesian Statistics (Q) Division 3: Science and MathematicsQuantitative and Formal Reasoning Wendy Wang
MWF 10:00 AM-10:50 AM Bronfman 104 3242
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