July 31, 2010, Saturday, 211

SYS 421

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Linear Statistical Models
Credits: 4
Semesters Offered: Fall
Cross-Listed As: None
Prerequisites: SYS 360, APMA 312
Corequisites: Lab (included)

This is a useful course for Systems Engineering majors. For majors only.

[edit] Description

From the Undergraduate Record:

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.


[edit] See Also

[edit] External Links

Systems and Information Engineering Courses
SYS 202 - SYS 204 - SYS 234 - SYS 257 - SYS 321 - SYS 323 - SYS 334 - SYS 355 - SYS 360 - SYS 362 - SYS 421 - SYS 444 - SYS 453 - SYS 454 - SYS 455 - SYS 532V - SYS 534V - SYS 544 -