DATA467
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DATA467 - Introduction to Applied Regression and Generalized Linear Models
Course Description
An applied course in linear regression, analysis of variance, and generalized linear models for students who have completed a course in basic statistical methods. Emphasis is on practical methods of data analysis and their interpretation, using statistical software such as R. Course content includes model building; linear regression; regression and residual diagnostics; basic experimental designs such as one-factor and two-factor ANOVA; block designs and random-effects models; introduction to exponential families and generalized linear models, including logistic and Poisson regression. Some emphasis will be devoted to matrix representations and efficient computational techniques.
Min Units
3
Max Units
3
Repeatable for Credit
No
Grading Basis
GRD - Regular Grades A, B, C, D, E
Career
Undergraduate
Enrollment Requirements
017877
Name
Lecture
Workload Hours
3
Optional Component
No
Typically Offered Main Campus
Fall, Spring
Typically Offered Distance Campus
Fall, Spring
Typically Offered UA Online Campus
Spring
Typically Offered Phoenix Campus
Not Offered
Typically Offered South Campus
Not Offered
Typically Offered Community Campus
Not Offered