This course is designed for analysts, statisticians, modelers, and other professionals who have experience and knowledge in regression analysis and who want to learn available procedures in SAS/STAT software for robust regression. The two procedures addressed in the course are the ROBUSTREG procedure and the QUANTREG procedure.

This course includes practice data.

• use PROC ROBUSTREG to fit a regression model less sensitive to outliers
• use PROC QUANTREG to fit a quantile regression model.

Who should attend

Formats available	Standard duration
e-Learning:	3.5 hours/180 day license	System Requirements

Before attending this course, you should

• be familiar with DATA step programming.
• be familiar with basic SAS procedures for producing summary statistics and graphs, such as the MEANS and SGPLOT procedures. You can gain this experience by completing the SAS Programming 1: Essentials course.
• have basic knowledge of and experience with linear regression models (PROC REG). You can gain this experience by completing the Statistics 1: Introduction to ANOVA, Regression, and Logistic Regression course.

This course addresses SAS/STAT software.

• describing different estimation methods in robust parameter estimations
• illustrating robust diagnostics that identify outliers
• comparing estimation methods in PROC ROBUSTREG

• describing the quantile regression model
• explaining the results generated in PROC QUANTREG