DATA503

Active

Students have an opportunity to learn how to model a quantitative response in terms of a linear combination of predictors (or functions of predictors) for a specific data set; to discover and deal with potential problems such as violations of assumptions, and to draw inference and predict using this model. This is done using the R language in the R-studio environment. Topics include linear models, data analysis, least squares estimation, identifiability, orthogonality, inference, prediction, explanation, diagnostics, problems with the predictors, solutions to violations of assumptions, transformations, and dealing with missing data.

-