Lecture, three hours; discussion, one hour. Limited to Master of Applied Statistics students. Introduction to state-of-art applications of linear model for understanding systems and predicting outcomes. Topics include review of statistical inference, properties of least-squares estimates, interpreting linear model, prediction and confidence intervals, model building, diagnostics, and bootstrapping. Letter grading.

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Course

Instructor
Mahtash Esfandiari
Previously taught
23F 22F 21F 20F 19F 18F

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