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CSI 972 - Mathematical Statistics I |
Focuses on theory of estimation, exploring method of moments, least squares, maximum likelihood, and maximum entropy methods. Details methods of minimum variance unbiased estimation. Other topics include sufficiency and completeness of statistics, Fisher information, Cramer-Rao bounds, Bhattacharyya bounds, asymptotic consistency and distributions, statistical decision theory, minimax and Bayesian decision rules, and applications to engineering and scientific problems.
3.000 Credit hours 3.000 Lecture hours Levels: Graduate Schedule Types: Lecture Computational & Data Sciences Department Course Attributes: Graduate - Advanced |