Catalog Entries |
Summer 2021
Apr 26, 2024 |
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| MATH 40015 - APPLIED STATISTICS |
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(Slashed with MATH 50015) 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. Students with statistics courses from other disciplines should consult with the Department of Mathematical Sciences for possible prerequisite overrides. Prerequisite: (MATH 21001 with a minimum C grade OR MATH 21002 with a minimum C grade) AND (MATH 12022 with a minimum B grade OR MATH 20011 with a minimum C grade OR MATH 30011 with a minimum B grade OR MATH 40012 with a minimum C grade).
3.000 Credit hours 3.000 Lecture hours Levels: Undergraduate Schedule Types: Lecture Mathematical Sciences Department |
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