Course Announcement, Spring 2008
STP 527:
Large-Sample
Statistical
Inference |
 |
Instructor: Dr. Sharon Lohr, 965-4440,
sharon.lohr@asu.edu
Time: 9:15 - 10:30 AM, Tuesday and Thursday
Location: Agriculture 181
Line #: 31772
Credits: 3
Topics:
We shall cover topics in statistical inference that are central to
theoretical and applied statistics.
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Convergence in probability and distribution. Order relations and rates of convergence.
Multivariate central limit theorem and delta method. Limiting distributions of sample quantiles.
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Consistency and asymptotic efficiency.
Finite-sample and asymptotic comparison of tests and confidence intervals. Relative efficiency. Power and sample size.
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Robustness of statistical procedures to violations of assumptions.
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Multivariate maximum likelihood estimators and asymptotic properties. Fisher information. Wald and likelihood ratio tests.
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Bootstrap and other resampling methods for inference.
The course will concentrate on statistical theory, but all results
will be motivated by applications. The target audiences are:
(1) students who want to do research in statistics,
(2) students who would like to go beyond STP 427 to learn about
classical and recently developed methods for statistical inference.
Prerequisites:
STP 421, STP 427 and STP 526 or consent of instructor.
Text: Lehmann, E. L. (1999). Elements of
Large-Sample Theory.
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Last Modified on 27 October 2007