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Design Diagnostics

 

See how to:

• Determine which designed experiment for a product, process, or behavior is most suitable for your needs based on what can be estimated, how precise the estimations are and the effect of leaving things out of the model

• Build and compare a Custom Design, Definitive Screening Design and an augmented Plackett-Burman-like Design for a product with two categorical and seven continuous factors

 

See how to:

• Compare three different designs

  • Us epower analysis to help determine which factors might be identified as useful for determining the probability of detecting a real signal

  • Identify which portion of the design space is below a certain variance

  • Plot the prediction variance surface as a function of the design factors

• Choose the most appropriate design

 

Design of Experiments