MATH 416 - Mathematical Statistics

Building on the material learned in MATH 316, students examine the theoretical underpinning of statistical results. Topics include estimation theory, confidence intervals, and tests of hypotheses (including an introduction to Bayesian and nonparametric estimation). More specifically, students explore sufficiency, maximum likelihood techniques, minimum variance principles, uniformly most powerful tests, pivotal quantities, test inversions, and asymptotic evaluation with the choice of topics determined by the instructor. While the primary focus is on the theory of statistics, students will learn to conduct and evaluate these approaches via simulation using software. Students may find MATH 416 a useful companion to the application-focused MATH 354.

Credits: 1.00
When Offered: Spring semester only, in alternate years

Corequisite: None
Prerequisites: MATH 316 and MATH 354
Major/Minor Restrictions: None
Class Restriction: None
Area of Inquiry: Natural Sciences & Mathematics
Liberal Arts CORE: None
Formerly: MATH 317

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