Teaching Advanced Regression
Ended Nov 7, 2023
1 credit
Full course description
Term: Fall 2023
Date: November 7th, 2023
Time: 12:00pm - 1:00pm
Location: Online Only
Instructors: Kate Miller & Jennifer Van Mullekom
Presented By: Statistical Applications & Innovations Group (SAIG)
Description:
A solid foundation in ordinary least squares (OLS) regression will take students a long way in their careers. Yet, many will someday encounter situations that OLS cannot readily handle. Perhaps the response distribution is non-normal. Or perhaps the predictors are highly correlated or outnumber the observations. Or maybe there are so many possible models that they need a principled way to select the best one. In these situations, familiarity with advanced regression techniques is critical. This webinar will guide you in using JMP and JMP Pro to teach several advanced regression methods: generalized linear models, stepwise regression, and regularized regression. Emphasis will be on JMP Pro’s Generalized Regression platform.
NOTE: Participants will also have to register with JMP for this event. In order to do that, complete the PDN registration and then visit the Canvas site for the JMP registration information.