Issue: Volume 9, Number 1
Date: January 2009
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, see below.

==> Tip: Get immediate answers to questions about DOE via the Search feature on the main menu of the Stat-Ease® web site. This not only pores over previous alerts, but also the wealth of technical publications posted throughout the 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* (beginning with the most recent one):

—Minneapolis most literate: Readers of the purple prose?
—Trying to remember what the prof taught in stats? A few Zzzs may help!
—Search for extraterrestrial intelligence (SETI)
—Let us be grateful to people who make us happy
* Need a feed from StatsMadeEasy to Microsoft's Outlook? See

Also, Stat-Ease offers an interactive web site — its Support Forum for Experiment Design at Whereas this monthly e-zine shares one-on-one communications with Stat-Ease StatHelp, anyone can post questions and answers to the Forum, which is open for everyone to see (with moderation). Check it out and weigh in!

Here's the most recent post (perhaps still unanswered) to be found in the DOE "Analysis" section. Feel free to contribute to this discussion thread.*

From: Brad Evans (Registered Member)
"I have a 2^(8-4) Res IV with three center points. Five of the factors are equally spaced, but three of them don't have the center point at the midpoint of the factorial points....If I select one of the factors with the center points not at the midpoint, the model does NOT include curvature. I think I know WHY but any explanation would be helpful..."

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

1. Newsletter Alert: December issue of the Stat-Teaser features "Getting a Taste for Mixture Design via In-Class Experiments"
2. Released: Version 7.1.6 of Stat-Ease software for DOE
3. FAQ: Numerical optimization results differ somewhat
4. Reader Response: Applying a selection procedure to a mixture model
5. Webinar alert (3rd): An Introduction to Mixture Design for Optimal Formulations
6. Info Alert: Publish your DOE success story — inspirational case-study articles sought for all industries!
7. Events Alert: ASQ Lean Six Sigma talk — "Friend or Foe? How to Use Graphical Diagnostics for Scoping Out Discrepant Data"
8. Workshop Alert: Designed Experiments for Life Sciences (DELS) coming to Washington, DC

P.S. Quote for the month: Humorous example of an inverse relationship in response to a quiz.


1. Newsletter Alert: December issue of the Stat-Teaser features "Getting a Taste for Mixture Design via In-Class Experiments"

Many of you have received a printed copy of the latest Stat-Teaser, but others, by choice or because you reside outside of North America, will get your only view of the December issue at It features an article by me on "Getting a Taste for Mixture Design via In-Class Experiments," which reports how a professor of food science put his students to work on a mutlticomponent taste test.

Also, this issue of the Stat-Teaser introduces Dr. James Alloway, Jr. — our newest contract trainer. I featured Jim's Black Box DOE toy in the September 14th StatsMadeEasy blog — see

Thank you for reading our Stat-Teaser newsletter. If you do get the hard copy, but find it just as convenient to read what we post to the Internet, consider contacting us to be taken off our mailing list, thus conserving resources. However, we do appreciate you passing around hard copies of the Stat-Teaser, so do not feel obliged to forego this.


2. Released: Version 7.1.6 of Stat-Ease software

Free, fully-functional downloads of Design-Ease® and Design-Expert® software, both now at version 7.1.6, are posted at for evaluation. This web site also provides free patches to update older, licensed versions of 7.1. The new release primarily addresses maintenance issues. View the ReadMe file for installation tips, known 'bugs,' change history, and FAQs.


3. FAQ: Numerical optimization results differ somewhat

-----Original Question-----
Packaging coatings developer
"I am analyzing the results of a mixture design set up by Design-Expert Version 7.1. After analyzing the responses, I selected criteria for the optimization and the numerical search tool found the most desirable solutions. Then I forwarded the design (saved with all the analysis) to a colleague who uses the same version of Design-Expert. When he ran the optimization it gave him different solutions than mine. Knowing that, I re-opened the design from my own computer and discovered again new solutions. Do you know why? Can I trust these predictions?"

From: (from Programmer Tryg Helseth)
"The optimization searches are run from a random starting point so you will get slightly different results each time. Since the old results are not saved new ones will be generated if you reopen an old file. As a practical matter, the top-ranked solution may change very little if at all."

Follow-up by Statistical Consultant Wayne Adams:
"As Tryg mentioned, the numerical solutions list is created using the models generated for each of the responses. The models are searched for trades-offs that best meet the simultaneous goals you have established. The search starts with a random set of points in addition to the actual experiment points. Different random starts, depending on the complexity of the process can produce different solutions all of which will meet (and hopefully exceed) the worst case requirements.

I suspect that several of the desirability scores are maxed out at 1. This indicates the goals were not pushed enough to truly find the optimal settings. In this case you will do well to tighten up on targets, extend the maximum and minimum goals and set goals on the component settings. This will cause the numerical search to converge on a most desirable outcome."

(Learn more about searching out most desirable product recipes by attending the three-day computer-intensive workshop "Mixture Design for Optimal Formulations." For a complete description of this class, see Link from this page to the course outline and schedule. Then, if you like, enroll online.)


4. Reader Response: Applying a selection procedure to a mixture model

-----Original Message-----
Norman Draper, Professor Emeritus, Department of Statistics
University of Wisconsin - Madison
Re: December's FAQ #2: Two models suggested by Design-Expert:
Now what? (See

"Applying a selection procedure to a mixture model is a doubtful technique, because of the dependency between the variables. Whatever variables remain, the mixture restriction makes it possible to rewrite the model in terms of variables that have been (perhaps) eliminated. Of course it might work out properly in a specific case but in general it is better to retain the model that has all the mixture terms of a specific order, e.g. first or second."


5. Webinar alert (3rd): An Introduction to Mixture Design for Optimal Formulations

You are invited to attend a free web conference by me on "An Introduction to Mixture Design for Optimal Formulations." This free conference, which I will keep at a beginner level statistically, will be broadcast on Wednesday, January 21 at 2 PM USA Central Time* (CT). I will repeat my webinar on Thursday, January 22 at 8 AM. It is aimed at product formulators who at best may be using standard factorial designs, or worse yet, the one-variable-at-a-time method. Keeping it simple and making it fun, I will introduce tools of multicomponent mixture design, modeling and statistic analysis. My hope is to generate interest in these powerful DOE methods for quickly converging on the sweet spot — where all desired product attributes are achieved.

Stat-Ease webinars vary somewhat in length depending on the presenter and the particular session — mainly due to breaks for questions: Plan for 45 minutes to 1.5 hours, with 1 hour being the target median.

When developing these one-hour educational sessions, our presenters often draw valuable material from Stat-Ease DOE workshops. Attendance may be limited, so sign up as soon as you see your way clear by contacting our Communications Specialist, Karen, via If you can be accommodated, she will send you the link for the WebConnect and dial-in for ConferenceNow voice via telephone (toll-free access extends worldwide, but not to all countries).

*(To determine the time in your zone of the world, try using this link: Note that we are based in Minneapolis, which appears on the city list that you must manipulate to calculate the time correctly. It seems that figuring out the clock on international communications is even more complicated than statistics! Good luck!)


6. Info Alert: Publish your DOE success story — inspirational case-study articles sought for all industries!

Stat-Ease is searching for individuals or teams willing to share their success stories. Anyone who has designed an experiment that has led to improvements in their products or processes is invited to contact us. Don't worry if it didn't go perfectly, as long as you learned something about the subject of interest. Perhaps you saved the company some money, or were able to make a product that met or surpassed customer requirements.

We can team you up with a technical writer who will coordinate the creation of the magazine article. You provide the interesting information and the technical writer provides the format. Plus, the technical writer does the work of submitting your case study to the appropriate magazines or journals. The article is published with your name as author.

If you are interested in publishing your story, please contact Heidi via or call her 612.746.2033. See our current collection of DOE case studies and articles at We are especially in need of applications from the life sciences. Factor details can be coded for secrecy sake, so confidentiality need not be compromised.

"Another company had end-users completely locked up. Before the story* ran, those
users didn't know we even existed. We gained ten new clients — a very significant
number in this small market." — Jennifer Borkovich, Engineer

*"Design of Experiments Increase Hot-Ink Roller Impressions (and Perceptions)" published in the May 2000 issue of American Ink Maker and in a web exclusive for PCI Magazine.

(Jennifer was quoted by technical writer Richard Burnham in an inspiring and informative article "Engineers as Credible Marketers" published by The Business to Business Marketer — see


7. Events alert: ASQ Lean Six Sigma talk — "Friend or Foe? How to Use Graphical Diagnostics for Scoping Out Discrepant Data"

I will be exhibiting for Stat-Ease at the 2009 ASQ Lean Six Sigma Conference in Phoenix on March 2-3 and giving a talk titled "Friend or Foe? How to Use Graphical Diagnostics for Scoping Out Discrepant Data." See my abstract and learning outcomes at To sign up for this conference by the American Society for Quality, go to, Click for a list of upcoming 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.


8. Workshop alert: Designed Experiments for Life Sciences (DELS) coming to Washington, DC

Seats are filling fast for the following DOE classes. If possible, enroll at least 4 weeks prior to the date so your place can be assured. However, do not hesitate to ask whether seats remain on classes that are fast approaching!

—> Experiment Design Made Easy (EDME)
(Detailed at
> February 24-26 (Minneapolis, MN)

—> Mixture Design for Optimal Formulations (MIX)
> February 3-5 (Minneapolis)

—> Response Surface Methods for Process Optimization (RSM)
> March 10-12 (Minneapolis)

—> Designed Experiments for Life Sciences (DELS)
> March 3-4 (Dulles, Washington D.C.)

—> DOE for DFSS: Variation by Design (DDFSS)
> May 5-6 (Minneapolis)

See for complete 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 Elicia at 612.746.2038. 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 — Humorous example of an inverse relationship in response to a quiz:

"In high school the teacher announced: 'Billy, you cheated on your test.' 'Oh, no!,' Billy responded. 'I would never cheat!' The teacher countered: 'Well, you have 100 percent wrong on the true/false test.' Now, you wonder, how do you get 100 percent wrong on a true/false quiz? It seems Bill was seated across the table from the brightest guy in class and had copied all of his answers...upside down!"
—Christy of Menomonie, Wisconsin writing to Saint Paul Pioneer Bulletin Board of 12-15-08 about a ne'er-do-well schoolmate.

Trademarks: Stat-Ease, Design-Ease, Design-Expert and Statistics Made Easy 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 Wolfe, Stat-Ease sales and 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, #7-7 Jul 07, #7-8 Aug 07, #7-9 Sep 07, #7-10 Oct 07, #7-11 Nov 07, #7-12 Dec 07, #8-1 Jan 08, #8-2 Feb 08, #8-3 Mar 08, #8-4 Apr 08, #8-5 May 08, #8-6 June 08, #8-7 July 08, #8-8 Aug 08, #8-9 Sep 08, #8-10 Oct 08, #8-11 Nov 08, #8-12 Dec 08, #9-1 Jan 09 (see above)

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