Applied Regression Analysis. 3 credits

Catalog description

Introduces statistical modeling with a focus on regression. Topics include: Correlation, simple and multiple regression models, model fitting, variable selection, diagnostic tools, model validation, inference for regression parameters, and matrix forms for multiple regression. Additional topics covered include logistic regression and time series analysis with a focus on smoothing techniques and decomposition. A statistical software package is used extensively throughout the course. Notes: Students may not receive credit for both STAT 456 and STAT 526 . Cannot be used to satisfy requirements for MS in Statistical Science. Offered by Statistics . May not be repeated for credit.