Data Analysis and Linear Regression Models

Catalog description

Basic exploratory data analysis including data summarization and graphical techniques. Linear regression analysis for single and multiple predictors including categorical predictors. Emphasis on model fitting, interpretation, and inference. Assessing goodness of fit, exploring common regression pitfalls, and employing remedial measures. Extending linear regression models to binary and count responses. R statistical software will be used for analysis. Offered as STAT 325 and STAT 425 . Prereq: ( STAT 302 or STAT 312 ) and ( MATH 201 or MATH 307 ).