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3.80
Spring 2026
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.
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Spring 2026
Supervised Research II
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Spring 2026
For master's research, taken before a thesis director has been selected.
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Spring 2026
For master's research, taken before a thesis director has been selected.
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Spring 2026
For master's research, taken before a thesis director has been selected.
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Spring 2026
For master's research, taken before a thesis director has been selected.
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Spring 2026
For master's thesis, taken under the supervision of a thesis director.
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Spring 2026
For master's thesis, taken under the supervision of a thesis director.
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Spring 2026
For master's thesis, taken under the supervision of a thesis director.
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Spring 2026
For master's thesis, taken under the supervision of a thesis director.
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