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Department:
MATH
Course Number:
6263
Hours - Lecture:
3
Hours - Lab:
0
Hours - Recitation:
0
Hours - Total Credit:
3
Typical Scheduling:
Every fall semester
Basic theories of testing statistical hypotheses, including a thorough treatment of testing in exponential class families. A careful mathematical treatment of the primary techniques of hypothesis testing utilized by statisticians.
Course Text:
At the level of Lehmann & Romano, Testing Statistical Hypotheses, 3rd edition, Springer-Verlag
Topic Outline:
- Decision Theoretic Context, Geometry of the Risk Set, and Relationship to Classical Testing Criteria
- Univariate Testing:
- Neyman-Pearson lemma for simple versus simple hypotheses
- application to UMP tests for monotone likelihood ratio families
- exponential families of distributions
- generalized Neyman-Pearson lemma and application to UMPU single parameter tests
- locally best tests with applications to rank tests
- Testing in Multivariate Koopman Darmois Families
- similarity and completeness
- application to UMPU tests, including the one and two sample t-tests
- group invariance of statistical decision problems and its use in testing hypotheses
- UMPI tests including the general linear model
- Large Sample Properties: Pitman Efficiency, Applications to Distribution-Free Tests
- Sequential Testing: Optimality of the SPRT