MATH154 PO - Computational Statistics

When Offered: Each fall.
Instructor(s): A. Castillo; G. Chandler; J. Hardin
Credit: 1

An introduction to computationally intensive statistical techniques. Topics may include: random variable generation, Markov Chain Monte Carlo, tree based methods (CART, random forests), kernel based techniques (support vector machines), optimization, other classification, clustering & network analysis, the bootstrap, dimension reduction techniques, LASSO and the analysis of large data sets. Theory and applications are both highlighted. Algorithms will be implemented using statistical software. Prerequisites: MATH 031 PO or MATH 032 PO; and MATH 058 PO.

Satisfies the following General Education Requirement(s), subject to conditions explained in the Degree Requirements section of this Catalog:
Area 5