Explorers Series

Unearth the possibilities in your data

Lecture & Lunch

Combining Predictive Analytics and Experimental Design to Optimize Results

Date: August 20, 2019
Time: 9:00 am - 1:00 pm
Location: Crowne Plaza Cleveland at Playhouse Square, 1260 Euclid Ave., Cleveland, OH 44115
Registration & Lunch: Free

Can you afford to miss insights hiding within information you might already have? Organizations are today collecting more data than ever. And while some companies may be satisfied with a predictive model that “just works,” they could do so much more to improve understanding, optimize parameters and make better predictions by combining predictive modeling with design of experiments (DOE).

Join us to learn about an alternative way to think about experimental design. Using observational sources of data, you can harness the power of predictive modeling to identify suggested relationships among factors that warrant further testing and exploration with design of experiments. It’s an iterative process that guides your line of questioning and efficiently delivers process knowledge to inform decision makers.

You will learn how to:

  • Get the most from large and messy data, even with missing information.
  • Use modern screening approaches to find the right potential drivers of performance.
  • Compare the potential drivers of performance to pick the best ones for further experimentation.
  • Select the right types of experiments to optimize results at the lowest cost.

Register now to attend in Cleveland.

  Please subscribe me to JMP Newswire, the monthly newsletter for JMP users.
  Yes, you may send me emails occasionally about JMP products and services. I understand that I can withdraw my consent at any time by clicking the opt-out link in the emails.

JMP is a division of SAS Institute Inc. Your information will be handled in accordance with the SAS Privacy Statement.

Jerry Fish
Jerry Fish

Jerry Fish is a Systems Engineer at JMP, where he helps customers find hidden insights in data that result in quantifiable improvement. Before joining JMP, he held positions that concentrated on fundamental problem solving, simulations, statistics, quality and process improvements over a 35-year career.

Back to Top