Difference between revisions of "Design and analysis of experiments"

Revision as of 11:23, 4 January 2016

This is a work in progress. It will be completed by the end of the day on 04 January 2016.

Learn the basic terminology of experiments: responses, factors, outcomes, real-world units vs coded units, confounding
Analyze and interpret data from an experiment with 2, 3 or more factors by hand
Use R to do the analysis, and interpret the various plots, such as the Pareto plot
Analyze and interpret data from an experiment with 3 or more factors
Recognize when to use a fractional factorial, to go mostly the same results as from a full factorial
Understand when to use screening experiments
Use the concepts of response surface methods to systematically reach an optimum
What you can do when you make a mistake, or hit against constraints.

Don't accept what is often believed to be true: always experiment.
In case you've been wondering how the trade-off table was constructed.
You must cover steps 16, 21 and 22 of the detailed software tutorial to master this section of the course.

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