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Undergraduate Record 2024-2025
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STAT 4130 - Applied Multivariate Statistics
Effective Date 08/01/2022
This course develops fundamental methodology to the analysis of multivariate data using computational tools. Topics include multivariate normal distribution, multivariate linear model, principal components and factor analysis, discriminant analysis, clustering, and classification. Prerequisite: A prior course in mathematical statistics, a prior course in linear algebra, and a prior course in programming.
Requisites Students must have completed STAT 3120 & ONE of STAT 3110, MATH 3350, MATH 3351, APMA 3080 & ONE of STAT 1601, STAT 1602, STAT 3080, STAT 3250, CS 1110, CS 1111, CS 1112, CS 1113
Credits: 3
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