Statistics 500
The course covers concepts and methods for regression analysis and applications. Topics include estimation, inference, interpretation of results, diagnostics, lack of fit, robust procedures, weighting and transformations, and model selection. The response variable could be continuous, binary or counts. More advanced techniques (splines, principal components analysis, and shrinkage estimators including ridge regression and Lasso) will also be covered. While there will be some theory, the emphasis will be on applications and data analysis.
Prerequisites
Please view the course schedule for current advisory and/or enforced prerequisites.
Program Year
P1
P2
P3
School
Course Number
500
Course Name
Statistical Learning I: Regression
Credits
3