Summary: This advanced course presents strategies and methods, using JMP, for designing experiments to screen many factors in an optimal study, as well as several specialized analytical tools that respect the limited information available in such experiments. This course is designed to help scientists and engineers choose an appropriate technique for their particular situation.
Duration: 14 hours of content.
Modalities:
- live online with instructor -- This course is available periodically (but infrequently) in our public course schedule. The public courses are an opportunity to learn this content with a live instructor, but they are currently only offered in English and at times most convenient to a US audience (because most of our instructors are in US time zones). Don't see what you are looking for? Let us know.
- through a third-party training vendor -- Any course in our JMP Curriculum could be taught by a licensed training vendor, including through the training department at your own company. Contact your JMP representative to learn more.
Prerequisites: Before attending this advanced course, you should complete the JMP®: Classic Design of Experiments or JMP®: Custom Design of Experiments course or have equivalent experience.
This course is not an introduction to design of experiments.
Learning Objectives:
- Assess the complexity of the situation in terms of the number of factors and the number and nature of terms in the model as a guide to selecting a method to design the screening experiment and analyze the empirical evidence.
- Recognize situations that benefit from a screening experiment.
- Make a fractional factorial design or Plackett-Burman design.
- Make an orthogonal or near-orthogonal array or a definitive screening design.
- Make a Bayesian D-optimal design or split-plot design with custom design.
- Identify situations where each of the screening designs might be most useful.
- Identify likely effects in the response using the effect screening emphasis and tools in the Fit Least Squares platform or the Screening platform.
- Select a model using the Stepwise platform with forward selection or All Possible Models under the heredity restriction.
Course Outline:
Need for Screening
- What is screening?
- Important principles in screening.
- Classic screening solutions.
Combinatorial Screening Designs
- Orthogonal or near-orthogonal screening designs.
- Definitive screening designs.
- Custom screening designs.
Model Selection in Screening
- Screening platform.
- Forward stepwise regression.
- All-subsets with heredity restrictions.
- Fit definitive screening platform.