Issue: Volume 7, Number 6
Date: June 2007
From: Mark J. Anderson, Stat-Ease, Inc., Statistics Made Easy® Blog

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 If this newsletter prompts you to ask your own questions about DOE, please address them via mail

For an assortment of appetizers to get this Alert off to a good start, see these new blogs at
—Estimates of the age of the earth vary astronomically
—Say it ain’t so, Joe—Mauer lays it down on the job
—Percentages puzzling to many people
—Experimentation uncovers most desirable time to embark on morning commute

Topics in the body text of this DOE FAQ Alert are headlined below (the "Expert" ones, if any, delve into statistical details).

1. FAQ: Responses that cannot be easily quantified
2. Expert-FAQ: Non-orthogonal design matrices
3. Info Alert: Case study authors wanted—gain name recognition for you and your company by achieving publication
4. Event Alert: Technical talks on DOE—speakers available!
5. Workshop Alert: See when and where to learn about DOE

PS. Quote for the month: From Saint Paul. (Page through to the end of this e-mail to enjoy the actual quote.)

PPS. Coincidentally, St. Paul is quoted by Lynne Hare, Director of Applied Statistics at Kraft Foods, in an excellent brief on statistics as one of ten quality basics in the current issue (June '07) of "Quality Progress" (pp 28-29). See bullets below.


1. FAQ: Responses that cannot be easily quantified

-----Original Message-----
"I am currently using Design-Expert® version 7 software to assess growth of a bacterium under different conditions. I gather that results of the experiment need to be numerical. Is it possible for results to be expressed by other means, for example as a positive or negative result entered as 1 or 0, respectively? Do I need to express growth results as a bacterium count, or can I express results on a scale such as 2 for much growth and 1 for minimal growth?"

Answer (from Stat-Ease Consultant Wayne Adams): "Yes, the responses must be numeric so a model can be fitted for predictive purposes and statistically validated. Actual counts would be best, but if this cannot be easily done, measure the amount of bacteriological growth with a rating scale. The more discrete levels you can assign the better, assuming an expert can discern the difference between ranks on a consistent basis. For greater accuracy and precision, take a series of photographs and create a template for rating according to the scale. Have the same person(s), preferably someone experienced in the field, rate the growth—the more observers, the better to reduce measurement error by the power of averaging. It's best that the actual experimenter not do the rating—keep the observers blind to the factor settings to avoid bias. Also, randomly present the material to the observer(s) to counteract any aging effects on the experimental samples."

More from me:
Stat-Ease Consultant Shari Kraber wrote up a case study that applied a rating scale of 1 to 5 on the comfort of chairs. See I've seen many successful experiments, including ones under my supervision, that depended on five to ten point ratings of appearance. When done in conjunction with a statistically-designed test matrix, these semiquantitative measures often produce surprisingly precise results that can be extremely useful. —Mark

(Learn more about entry-level aspects of DOE by attending the three-day computer-intensive workshop "Experiment Design Made Easy." See for a description of this class and then link from this page to the course outline and schedule. Then, if you like, enroll online.)


2. FAQ: Non-orthogonal design matrices

-----Original Question-----
From: Switzerland
"I introduced an experimental design which was not orthogonal (independent variables were correlated) in your Design-Expert software and I got a predictive model. How do I assess the individual effects?"

Answer (from Stat-Ease Consultant Wayne Adams): "Go to the design evaluation node in Design-Expert and view the variance inflation factor (VIF) results for the terms in your selected model. The ideal VIF is 1, which indicates orthogonality, that is, no correlation of that term with any others. As a rough rule, only if VIF's increase to 10 or more should you have cause for alarm that coefficients will be poorly estimated due to multicollinearity."

More from me:
Evidently none of the VIF's in this user's design exceeded 2, so there was no reason to worry. FYI, response surface method (RSM) designs generally will be slightly non-orthogonal—some more so than others. For example, if for the sake of convenience,* you run a face-centered central composite design (FCD), the main effects and two-factor interaction terms all have VIFs of 1, but the squared terms in the quadratic model are inflated to 1.82. That is not ideal, but acceptable. —Mark

(Learn more about design evaluation by attending the three-day computer-intensive workshop "Response Surface Methods for Process Optimization." For description of this class, see and then link from this page to the course outline and schedule. If you like, enroll online.)


3. Info Alert: Case study authors wanted—gain name recognition for you and your company by achieving publication

Gain technical recognition in your company and scientific field by writing up your DOE success story for publication in a technical magazine and/or Internet web site. We can put you in touch with technical writers who specialize in articles like this and know how to get them placed. Rename proprietary factors if needed to maintain confidentiality. A thirty-minute interview, some e-mails, a review, and it's done! For more information, contact Heidi Hansel at


4. Events Alert: Technical talks on DOE—speakers available!

Click for a list of appearances by Stat-Ease professionals. We hope to see you sometime in the near future!

PS. Do you need a speaker on DOE for a learning session within your company or technical society at regional, national, or even international levels? If so, contact me. It may not cost you anything if Stat-Ease has a consultant close by, or if a web conference will be suitable. However, for presentations involving travel, we appreciate reimbursements for airfare, hotel and meals—expenses only. In any case, it never hurts to ask Stat-Ease for a speaker on this topic. Contact if you have an event coming up with an open slot for a presentation.


5. Workshop Alert: See when and where to learn about DOE

See for schedule and site information on all Stat-Ease workshops open to the public. To enroll, click the "register online" link on our web site or call Stat-Ease at 612.378.9449. If spots remain available, bring along several colleagues and take advantage of quantity discounts in tuition. Or consider bringing in an expert from Stat-Ease to teach a private class at your site.*

*Once you achieve a critical mass of about 6 students, it becomes very economical to sponsor a private workshop, which is most convenient and effective for your staff. For a quote, e-mail


I hope you learned something from this issue. Address your general questions and comments to me at:



Mark J. Anderson, PE, CQE
Principal, Stat-Ease, Inc. (
2021 East Hennepin Avenue, Suite 480
Minneapolis, Minnesota 55413 USA

PS. Quote for the month"Test all things; hold fast what is good."
—Paul, 1 Thes. 5:14-22.

PPS. Lynne Hare provides* this quote by St. Paul:
"We see through a glass, darkly."

The context is distinguishing effects that are 'fuzzed' by random variation. Here are some pithy points by Lynne.
—"Confidence intervals estimate parameters in the shadows of uncertainty."
—"Regression analysis finds a line or curve through ordered pairs of data with a built-in reality check based on random variation."
—"The analysis of variance sorts real effects and interactions from noise."

*("Quality Progress," June 2007, pp 28-29)
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
—Stat-Ease consultants Pat Whitcomb, Shari Kraber and Wayne Adams (see for resumes)
—Statistical advisor to Stat-Ease: Dr. Gary Oehlert (
—Stat-Ease programmers, especially Tryg Helseth and Neal Vaughn (
—Heidi Hansel, Stat-Ease marketing director, and all the remaining staff


Interested in previous FAQ DOE Alert e-mail newsletters?
To view a past issue, choose it below.

#1 Mar 01, #2 Apr 01, #3 May 01, #4 Jun 01, #5 Jul 01 , #6 Aug 01, #7 Sep 01, #8 Oct 01, #9 Nov 01, #10 Dec 01, #2-1 Jan 02, #2-2 Feb 02, #2-3 Mar 02, #2-4 Apr 02, #2-5 May 02, #2-6 Jun 02, #2-7 Jul 02, #2-8 Aug 02, #2-9 Sep 02, #2-10 Oct 02, #2-11 Nov 02, #2-12 Dec 02, #3-1 Jan 03, #3-2 Feb 03, #3-3 Mar 03, #3-4 Apr 03, #3-5 May 03, #3-6 Jun 03, #3-7 Jul 03, #3-8 Aug 03, #3-9 Sep 03 #3-10 Oct 03, #3-11 Nov 03, #3-12 Dec 03, #4-1 Jan 04, #4-2 Feb 04, #4-3 Mar 04, #4-4 Apr 04, #4-5 May 04, #4-6 Jun 04, #4-7 Jul 04, #4-8 Aug 04, #4-9 Sep 04, #4-10 Oct 04, #4-11 Nov 04, #4-12 Dec 04, #5-1 Jan 05, #5-2 Feb 05, #5-3 Mar 05, #5-4 Apr 05, #5-5 May 05, #5-6 Jun 05, #5-7 Jul 05, #5-8 Aug 05, #5-9 Sep 05, #5-10 Oct 05, #5-11 Nov 05, #5-12 Dec 05, #6-01 Jan 06, #6-02 Feb 06, #6-03 Mar 06, #6-4 Apr 06, #6-5 May 06, #6-6 Jun 06, #6-7 Jul 06, #6-8 Aug 06, #6-9 Sep 06, #6-10 Oct 06, #6-11 Nov 06, #6-12 Dec 06, #7-1 Jan 07, #7-2 Feb 07, #7-3 Mar 07, #7-4 Apr 07, #7-5 May 07, #7-6 Jun 07 (see above)

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