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MATH 416 - Numerical Simulations for Probabilistic Models

Description
Efficient generation of random variables; statistical analysis and validation techniques; variance reduction; Markov Chain Monte Carlo methods; applications include complex systems, financial models, and Bayesian computation. Credit not granted for both MATH 416 and MATH 516. Required preparation must include probability and statistics and programming experience. Class Notes: Online delivery with at least one opportunity each week for students to interact synchronously with the instructor at the original time identified above. The Instructor will define the synchronous interaction. Enrollment Requirements: Course Prerequisite: STAT 360; CPT S 121, CPT S 251, or MATH 300.
Credits
3
Attributes
Credit not granted for both 400 and 500 level. Cooperative: Open to UI degree-seeking students. VC Originating in Pullman
Recent Professors
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Recent Semesters
Fall 2020, Fall 2018
Offered
MWF, TuTh
Avg. Sections
1