The Power of Simulation In Design of Experiments (2026-US-30MP-2885)

When designing an experiment, you might not be ready to run the experiment and collect the real data for the results. The Simulate Responses feature in JMP allows you to create data to mimic a real-world response, as a stand-in for the data until the experiment has been completed.

This presentation discusses the benefits of simulation when creating a designed experiment; it also includes a demonstration of how to use the new Advanced Options for simulating responses in JMP 19. The Advanced Options enable you to ensure that the underlying model for the simulation obeys the well-known statistical principles of effect sparsity, effect hierarchy, and model heredity. We present three case studies, showing how the options may be appropriate for different scenarios, including screening experiments and optimization experiments.

The presentation also highlights other areas of JMP that use simulation, including a demonstration of how to use JMP to perform an empirical power analysis for a designed experiment. The demonstration shows Easy DOE, Definitive Screening Design and Fit Definitive Screening, and Custom Design.