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Robust Regression Techniques in SAS/STAT®
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. Learn How To use PROC ROBUSTREG to fit a regression model less sensitive to outliers use PROC QUANTREG to fit a quantile regression model.Who Should Attend Analysts, statisticians, and modelers Prerequisites 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(R) Programming I: Essentials course. have basic knowledge of and experience with linear regression models (PROC REG). You can gain this experience by completing the Statistics I: Introduction to ANOVA, Regression, and Logistic Regression course.SAS Products Covered SAS/STAT Course Outline Robust Regression Using the ROBUSTREG Procedure describing different estimation methods in robust parameter estimations illustrating robust diagnostics that identify outliers comparing estimation methods in PROC ROBUSTREGQuantile Regression Using the QUANTREG Proceduredescribing the quantile regression model explaining the results generated in PROC QUANTREG
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