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JMP - Design of Experiments (JMDOE)
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This two-day-training gives an overview over so-called modern or optimal methods of Design of Experiments. The classical methods and the concepts of sequential experimentation are extend by the use of JMPs Custom Designer. The Custom Designer provides optimal designs for situatons where classic design of experiments does not seem to fit any more.

Using interactive exercises you will learn how to work with the Custom Designer in JMP. As part of the training multiple examples will be given to provide a deep understanding of where and how to use optimal designs.

Content:

  • One-factor designs with categoric and continuous factors
  • Non-equal spaced factor settings
  • Evaluation of design quality based on expected prediction error
  • Optimality-critirea
  • Designs for two factors, interactions and block-effects
  • Split-Plot designs

Requirements:

Participants should have a basic understanding of how to work with JMP, statistical hypothesis tests, ANOVA and Regression. The required topics are discussed in the courses Explorative Data Analysis with JMP and ANOVA and Regression with JMP. Knowledge of the basic concepts of DoE - like discussed in the course Classic Design of Experiments with JMP - are useful but not required.