Issue: Volume 6, Number 4
Date: April 2006
From: Mark J. Anderson, Stat-Ease, Inc. (http://www.statease.com)
"Statistics Made Easy" (tm) Blog http://statsmadeeasy.net

Dear Experimenter,

Here's another set of frequently asked questions (FAQs) about doing design of experiments (DOE), plus alerts to timely information and free software updates. If you missed the previous DOE FAQ Alert, please click on the links at the bottom of this page. If you have a question that needs answering, click the Search tab and enter the key words. This finds not only answers from previous Alerts, but also other documents posted to the Stat-Ease web site.

Feel free to forward this newsletter to your colleagues. They can subscribe by going to http://www.statease.com/doealertreg.html. If this newsletter prompts you to ask your own questions about DOE, please address them via mail to:[email protected].

This plain text message may be easier to read if you do not remove the line breaks. If you use Microsoft Outlook, press the bar labeled "Extra line breaks in this message were removed." In newer versions select "Restore line breaks."

Here's an appetizer to get this Alert off to a good start: http://www.amstat.org/publications/jse/v13n3/richardson.html — an in-class experiment that compares the flavor longevity of two different brands of chewing gum. Gum manufacturers seek the longest-lasting flavor — about 12 minutes is typical according to statistics cited by the authors. (After that time is up it goes under the classroom desk, so ideally the flavor could be stretched longer than the lecture and students would keep their gummy where their mouths are.)

I found a more sophisticated experiment on how long gum lasts at http://www.che.utexas.edu/cache/newsletters/fall2003_active.pdf.
It suggests a two-level factorial design on:
A. Flavor — Fruit Juice versus Double Mint
B. Gender — Female vs Male
C. Meal — Before vs After.
The author, Gerardine G. Botte (currently at Ohio University http://webche.ent.ohiou.edu/faculty/botte.html), suggested students at the University of Minnesota Duluth chew on this as homework for their Design of Engineering Experiments class. Many other fun ideas for DOE exercises are provided by Professor Botte. I wish I had her as a statistics teacher!

PS. Breaking news: Chewing gum makes you smarter and good-looking! Wrigley gum researchers hope to prove this by investing in unbiased (?) experimentation on these possible benefits to masticating their product. See http://tinyurl.com/papg8 for their publicity on this research initiative.

Here's what I cover in the body text of this DOE FAQ Alert (topics that delve into statistical detail are designated "Expert"):

1. FAQ: Why is there no intercept in models for mixture designs?
2. FAQ: Categorical factor in a response surface method (RSM)
3. Info Alert: Balloon car simulation (submitted by reader)
4. Submission: Photo of "RSM Simplified" book at Center Point
5. Events Alert: First European DOE User Meeting (2nd notice!)
6. Workshop Alert: "Crash Course on DOE for Sales & Marketing"

PS. Quote for the month: How to get the Net Generation engaged in statistics classes.

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1. FAQ: Why is there no intercept in models from mixture designs?

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Sincerely,

Mark

Mark J. Anderson, PE, CQE
Principal, Stat-Ease, Inc. (http://www.statease.com)
2021 East Hennepin Avenue, Suite 480
Minneapolis, Minnesota 55413 USA

PS. Quote for the month—how to get the Net Generation (see http://en.wikipedia.org/wiki/Generation_Y) engaged in statistics classes:

"Their fast-paced world of action movies, rapid-fire TV commercials and video games does not prepare today’s students to sit and absorb a lecture, especially on a supposedly dull subject like statistics. To capture the interest of these students, teaching must move away from lecture and listen to innovative activities that engage students in the learning process."

—R. Scheaffer (http://www.stat.ufl.edu/personnel/usrpages/scheaffer.shtml)

Trademarks: Design-Ease, Design-Expert and Stat-Ease are registered trademarks of Stat-Ease, Inc.

Acknowledgements to contributors:
—Students of Stat-Ease training and users of Stat-Ease software
—Fellow Stat-Ease consultants Pat Whitcomb, Shari Kraber and Wayne Adams (see http://www.statease.com/consult.html for resumes)
—Statistical advisor to Stat-Ease: Dr. Gary Oehlert (http://www.statease.com/garyoehl.html)
—Stat-Ease programmers, especially Tryg Helseth and Neal Vaughn (http://www.statease.com/pgmstaff.html)
—Heidi Hansel, Stat-Ease marketing director, and all the remaining staff

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