Sequential Analysis
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Course Description
This course will survey the history of sequential analysis from its origin in the 1940s via its continuing role in clinical trials to current activity in machine learning. Subject to the limitations of time, the following topics will be discussed: parametric and semi-parametric hypothesis testing from Wald to sequential clinical trials; fixed precision estimation; change-point detection and estimation; iterative stochastic algorithms and machine learning; anytime-valid inference; optimal stopping, dynamic programming, and stochastic control; multi-armed bandits; applications. Prerequisites: for 223, Stats 200 or equivalent; for 323, Stats 300A and 310A.
Cross Listed Courses
Grading Basis
ROP - Letter or Credit/No Credit
Min
3
Max
3
Course Repeatable for Degree Credit?
No
Course Component
Lecture
Enrollment Optional?
No
Does this course satisfy the University Language Requirement?
No
Programs
STATS323
is a
completion requirement
for:
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