SYS 421 - Linear Statistical Models

This course shows how to use linear statistical models for analysis in engineering and science. The course emphasizes the use of regression models for description, prediction, and control in a variety of applications. Building on multiple regression, the course also covers principal component analysis, analysis of variance and covariance, logistic regression, time series methods, and clustering. Course lectures concentrate on the theory and practice of model construction while laboratories provide a series of open-ended problem solving situations that illustrate the applicability of the models. (Y)

Prerequisites & Notes
Prerequisite: SYS 360, APMA 312, and major in systems engineering.

Credits: 4

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