Course Description
Finite sample optimality of statistical procedures; Decision theory: loss, risk, admissibility; Principles of data reduction: sufficiency, ancillarity, completeness; Statistical models: exponential families, group families, nonparametric families; Point estimation: optimal unbiased and equivariant estimation, Bayes estimation, minimax estimation; Hypothesis testing and confidence intervals: uniformly most powerful tests, uniformly most accurate confidence intervals, optimal unbiased and invariant tests. Prerequisites: undergraduate probability (at the level of STATS 118 or MATH 151 or MATH 136). Recommended: STATS 200.
Grading Basis
ROP - Letter or Credit/No Credit
Min
3
Max
3
Course Repeatable for Degree Credit?
No
Course Component
Discussion
Enrollment Optional?
Yes
Course Component
Lecture
Enrollment Optional?
No
Does this course satisfy the University Language Requirement?
No
Schedule
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Courses
STATS300A is a antirequisite for:
STATS300A is a prerequisite for:
Programs
STATS300A is a completion requirement for:
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