STAT 3301: Regression and Statistical Computing

4 Credits

This is a second course in statistics for students that have completed a calculus-based introductory course. Students will learn to analyze data with the multiple linear regression model. This will include inference, diagnostics, validation, transformations, and model selection. Students will also design and perform Monte Carlo simulation studies to improve their understanding of statistical concepts like coverage probability, Type I error probability, and power. This will allow students to understand the impacts of model misspecification and the quality of approximate inference. prereq: Stat 3021 and (CSci 1113 or CSci 1133), and co-requisite (CSci 2033 or Math 2142 or Math 2243 or Math 2373)

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All Instructors

B+ Average (3.220)Most Common: A (35%)

This total also includes data from semesters with unknown instructors.

133 students
  • 2.92


  • 3.52


  • 3.16


  • 3.03


  • 3.09



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