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MSAN 601 - Linear Regression Analysis (2)

This course is an intensive introduction to linear models, with a focus on both principles and practice.  Examples from finance, business, marketing and economics are emphasized. Large data sets are used frequently.  Topics include simple and multiple linear regression; weighted, generalized, and outlier-resistant least squares regression; interaction terms; transformations; regression diagnostics and addressing violations of regression assumptions; variable selection techniques like backward elimination and forward selection, and logit/probit models. Statistical packages include R and SAS.