DATA467

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DATA467 - Introduction to Applied Regression and Generalized Linear Models

Mathematics Undergraduate UA - UA General

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