JMP Statistical Developer Ryan Lekivetz (@Ryan_Lekivetz) recently shared details and answered questions about how and why you can use covariates to build better designs using JMP; this was part of our Developer Tutorial series. JMP Systems Engineer Tom Donnelly (@tom_donnelly) was on hand during Ryan's webinar to share user situations where covariates are in play. The video and resources from the webinar are now available.
Starting Nov. 4 (and continuing Nov. 11 and 18) JMP Statistical Developer Clay Barker (@clay_barker) will present the next three Developer Tutorials. One of Clay’s key contributions to JMP Pro is in the area of generalized regression variable selection techniques that specifically address modeling correlated and high-dimensional data that include more variables than observations.
I spoke with Clay when scheduling his first session, where he will discuss how to use JMP Pro’s Generalized Regression to make the most of your designed experiment. He’ll make sense of some of the related statistics.
Clay made his way to a statistics PhD through sports – a slam dunk for the JMP team! The game clock is still running for JMP Pro 17, where he and the JMP Development Team are enhancing generalized regression.
See the video of Clay's Nov. 4 Tutorial (and get slides and JMP Pro Journal) where he:
- Shares his expertise about capabilities he has helped develop in JMP Pro.
- Explains what the Generalized Regression capabilities aim to achieve for users designing experiments.
- Describes how and why JMP Pro techniques (aka platforms) use specific statistical approaches.
- Discusses which capabilities might be most statistically useful for certain situations.
- Answered questions.
Want to see some of Clay’s Discovery Summit presentations?
