PLAD 8310
Regression Analysis
Course Description
This course introduces regression analysis in political science. It covers linear regression, the ordinary least squares (OLS) estimator, interpretation of results, and regression diagnostics. The course also introduces generalized linear models (GLMs), maximum likelihood estimation (MLE), and regression analysis with binary outcomes. A separate section of the course focuses on implementation of regression analysis in R programming language.
Instructors
Zachary Johnson
Spring 2026
we 10:15am - 11:30am
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Rating
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Difficulty
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GPA
Kirill Zhirkov
Spring 2026
tu 2:00pm - 4:30pm
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Rating
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Difficulty
3.83
GPA
To Announced
Spring 2025
TBA
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Rating
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Difficulty
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GPA
To Be Announced
Spring 2025
TBA
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Rating
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Difficulty
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GPA
Shawna Metzger
Spring 2021
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Rating
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Difficulty
3.65
GPA
Jonathan Kropko
Spring 2019
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Rating
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Difficulty
3.84
GPA
Shawn Treier
Spring 2013
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Rating
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Difficulty
3.84
GPA
Jee Park
Spring 2012
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Rating
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Difficulty
3.75
GPA
Michele Claibourn
Fall 2010
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Rating
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Difficulty
3.75
GPA