MATH 454 Statistics for Risk Modeling
Covers analytic methods for risk modeling including statistical learning, generalized linear models, time series models, principal components analysis, decision trees, and cluster analysis. These analytic methods will be applied to examples using the R statistical computing language.
Prerequisite: C- or better in MATH 321 or permission of the department chairperson.