Design and analysis of experiments

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

• 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.

Resources

• Class notes 2015
• Class notes 2014
• Textbook, chapter 5
• Quizzes (with solutions): attempt these after you have watched the videos

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