STAT3032: Regression and Correlated Data

4 Credits

This is a second course in statistics with a focus on linear regression and correlated data. The intent of this course is to prepare statistics, economics and actuarial science students for statistical modeling needed in their discipline. The course covers the basic concepts of linear algebra and computing in R, simple linear regression, multiple linear regression, statistical inference, model diagnostics, transformations, model selection, model validation, and basics of time series and mixed models. Numerous datasets will be analyzed and interpreted using the open-source statistical software R. prereq: STAT 3011 or STAT 3021

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B Average (3.157)Most Common: A (31%)

This total also includes data from semesters with unknown instructors.

2322 students
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  • 4.35


  • 4.24


  • 3.99


  • 4.36



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