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Summer 2021
Oct 22, 2021
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Information Select the desired Level or Schedule Type to find available classes for the course.

MATH 50015 - APPLIED STATISTICS
(Slashed with MATH 40015) Course is based on classical linear regression techniques with an emphasis on real data using the principles of sound data analysis. Close attention is given to issues of interpretation, diagnostics, outliers and influential points, goodness of fit and model selection. Topics include simple and multiple linear regression, transformation and modifications of covariates and responses, design matrices, variable selection and logistic regression. Prerequisite: Applied mathematics or pure mathematics major; and graduate standing.
3.000 Credit hours
3.000 Lecture hours

Levels: Graduate
Schedule Types: Lecture

Mathematical Sciences Department

Restrictions:
Must be enrolled in one of the following Levels:     
      Graduate
Must be enrolled in one of the following Majors:     
      Applied Mathematics
      Pure Mathematics

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