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Dec 07, 2025
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STAT 410 - Generalized Linear Models
Studies the use of explanatory, confirmatory, and predictive linear models in data-driven decision making. Includes supervised learning methods (simple linear regression, multiple linear regression, logistic regression, Poisson regression, and random forests), model selection methods (information criteria, cross-validation), and unsupervised learning methods (principal component analysis) using statistical computing packages.
Prerequisite(s)/Corequisite(s): (Prereq: STAT 250 or MATH 320 or STAT 310 or STAT 320 or STAT 325 or STAT 330 or STAT 335 with a C- or better)
Typically Offered: Spring term only
Units: 4
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