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Apr 20, 2024
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2016-2018 Undergraduate Catalog [ARCHIVED CATALOG]
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MT 3410 - Statistical Learning
(3)
Spring semester
This course is an introduction to the field of Statistical Learning. Necessary probability and statistical understanding will be developed, including data and descriptive statistics, basic probability and Bayes Theorem, some probability distributions, hypothesis testing, regression, and Monte Carlo simulation. Students will work on relevant applications, learning and utilizing many important modeling and prediction methods, including: regression and classification methods, resampling methods, tree-based methods, support vector machines, clustering and neural networks. Students will do all computing in R, an open-source software environment for statistical computing and graphics. Tutorials and some class time will be devoted to developing the necessary skills in R.
Prerequisite: A grade of C or better in MT 1810 .
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