Course Department: 
Course Frequency: 
Annually, spring
Course Description: 

This course provides a thorough examination of the theory and practice of ordinary least squares (OLS) regression modeling.  Model interpretation and a conceptual understanding of confounding, mediation, and effect modification are emphasized.  Specific topics include analysis of variance (ANOVA), derivation of parameter estimates, correlation, prediction, dummy variables, contrasts, testing general hypotheses, analysis of covariance (ANCOVA), multicollinearity, regression diagnostics, techniques for handling model misspecification (incorrect functional form, heteroskedasticity), and model-building strategies.  Students will work extensively with data sets and the R statistical software package.  Prerequisites: Mathematics 136 and one of Biology 275, Economics 249, Math 220, Psychology 200, Sociology 226, or Mathematics 376.  One unit.

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