Difference between revisions of "Design and analysis of experiments"

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===Videos from 2014===
===Videos from 2014===
[[Design_and_analysis_of_experiments_(2014)|See the webpage from 2014]]
[[Design_and_analysis_of_experiments_(2014)|See the webpage from 2014]]
 
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===Videos from 2013===
===Videos from 2013===

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.

Learning outcomes

  • 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.

Extended readings/practice

Resources

Tasks to do first Quiz Solution
Watch videos AAA Quiz Solution
Watch videos BBB Quiz Solution
Watch videos CCC Quiz Solution
Watch videos DDD Quiz Solution
Watch videos EEE Quiz Solution
Watch videos FFF Quiz Solution

Class videos from prior years

Videos from 2015

00:00 | No video | Script

Videos from 2014

See the webpage from 2014

Videos from 2013

See the webpage from 2013

Software codes for this section

Code to show how to build and plot a least squares model in R

Try this code in a web-browser