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Math 671: Statistical Methods I

Mathematics

This course and its sequel, Math 672, cover linear statistical models for regression, analysis of variance, and experimental design. The courses seek to blend theory and application. Topics in this course include simple and multiple linear regressions, model diagnostics, model selection and validation, generalized linear models, nonlinear regression, and neural networks. SAS or R will be used to apply these methods with real data.

3 Credits

Prerequisites

Instruction Type(s)

  • Seminar: Seminar for Math 671

Subject Areas

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