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BST 569 Linear Statistical Models 4.0 Credits

The objective of this course is to introduce students to linear regression models (computation, theoretical properties, model interpretation and application). Topics include: Review of basic concepts of matrix algebra that are particularly useful in linear regression, and basic R programing features; (weighted) least square estimation, inference and testing; regression diagnostics, outlier influence; and variable selection and robust regression. Knowledge of calculus 1, calculus 2, and linear algebra required.

College/Department: Dornsife School of Public Health
Repeat Status: Not repeatable for credit
Restrictions: Can enroll if major is BIOS.

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