Apr 13, 2024  
Graduate Catalog | 2021-2022 
    
Graduate Catalog | 2021-2022 Previous Edition

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GRAD 8101 - 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 6101  
Most Recently Offered (Day): Spring 2019, Spring 2020, Spring 2021
Most Recently Offered (Evening): Course has not been offered at this time in the past 3 years


Schedule of Classes




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