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|MATH 50024 - COMPUTATIONAL STATISTICS|
(Slashed with MATH 40024) This course is about the use of computational tools to manage, explore, summarize, and visualize data, as well as the computational underpinnings of fitting statistical models. It uses mostly the statistical computation language R, but also other languages like Python and Matlab. It also covers: simulation and random number generation, computationally intensive methods like the bootstrap and permutation tests, Expectation-Maximization and related algorithms, and dimensionality reduction via matrix decomposition.
Prerequisite: Applied mathematics or pure mathematics major; and graduate standing.
3.000 Credit hours
3.000 Lecture hours
Schedule Types: Lecture
Mathematical Sciences Department
Must be enrolled in one of the following Levels:
Must be enrolled in one of the following Majors:
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