4 Day Course
Monday, July 22| 9:00 a.m. - 12:30 p.m. ET
Tuesday, July 23 | 9:00 a.m. - 12:30 p.m. ET
Wednesday, July 24 | 9:00 a.m. - 12:30 p.m. ET
Thursday, July 25 | 9:00 a.m. - 12:30 p.m. ET
This course teaches you techniques for fitting statistical models to identify important variables. Manual, graphical, and automated variable selection techniques are presented, along with advanced modeling methods. The demonstrations include modeling both designed and undesigned data. Techniques are illustrated using both JMP software and JMP Pro software. Note that JMP Pro software is needed for the advanced techniques covered in the second half of this course.
Learn how to:
- Identify a subset of predictors as important using a statistical model.
- Validate statistical models using cross-validation, holdback validation, and information-theoretic criteria.
- Perform stepwise and all subsets regression.
- Select important predictors using graphical methods and decision trees.
- Perform penalized regression for Gaussian and non-Gaussian responses.
- Use the Generalized Regression platform to identify important predictors.
Who Should Attend:
Analysts, researchers, technicians, or anyone filling similar roles, who want to determine which predictors in a large set are important in predicting a response
Duration: 4 half-day sessions