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May 18, 2024
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GRAD 6101 - Linear Regression
Linear regression models, and the ordinary least squares (OLS) estimators that are often used to estimate them, are robust tools employed by social scientists to both explain and predict social phenomena. Moreover, basic linear regression and OLS are part of the foundation one must have to understand more sophisticated variants of the linear model (e.g., time series, structural equations), as well as non-linear models (e.g., logistic regression, multinomial logit, Poisson regression). As such, the class has two primary purposes: 1) conveying a basic understanding of the linear regression model so that students are able to both employ the technique in their own research and comprehend research employing the technique; and 2) provide a strong foundation in the underlying model such that they will have little difficulty in future classes that move beyond the OLS framework.
Credit Hours: (3)
Prerequisite(s): GRAD 6100 or equivalent.
Cross-listed Course(s): GRAD 8101
Repeatability: May not be repeated for credit.
Schedule of Classes
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