What’s New?

Quantile Regression in Practice
An American Statistical Association Council of Chapters Traveling Course
 
The SSO will be hosting a half-day course titled “Quantile Regression in Practice”, taught by Dr. Yonggang Yao, Principal Research Statistician at SAS Institute Inc. 
 
WHERE:   The Senate Room (608 Robertson Hall) at Carleton University
 
WHEN:   Wednesday, November 15, 8:00 AM -12:00 noon
 
REGISTRATION:
 
Pre-registration and payment is mandatory, as there is limited seating available in the room. 

SSO member price:    \$43.00   (\$40 + \$3.00 Eventbrite fee)
SSO non-member price:    \$53.60   (\$50 + \$3.60 Eventbrite fee) 
Student price:    \$27.11   (\$25 + \$2.11 Eventbrite fee)
 
 
ABOUT THE COURSE:
 
Quantile regression is a modern statistical methodology for modeling quantiles of a response variable conditional on explanatory covariates.This tutorial provides an overview of quantile regression methodology with examples from a variety of fields, including treatment effect analysis, uncertainty measurement, value-at-risk analysis, and extreme value analysis.  The presentation is appropriate for data analysts and statisticians who are interested in more flexible methods for heterogeneous data analysis. Basic familiarity with linear regression, histograms, and basic distribution functions is assumed.
The presentation will be in English.
 
ABOUT THE INSTRUCTOR: 
 
Dr. Yonggang Yao is a principal research statistician developer at SAS. He joined SAS in 2008 after receiving a PhD degree in statistics from The Ohio State University. His research interests are in applications on quantile regression, robust regression, and statistical learning. He has developed two SAS procedures, PROC QUANTSELECT and PROC HPQUANTSELECT for quantile regression model selection in standard and distributed computing environments. He is also the key supporting developer for two other SAS procedures, PROC QUANTREG for quantile regression and PROC ROBUSTREG for robust regression. He has given short courses on quantile regression at SAS Global Forum, the Joint Statistical Meetings, and other statistical meetings.