Issue: Volume 9, Number 9
Date: September 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 to:

For an assortment of appetizers to get this Alert off to a good start, follow this link,* (-> new web site!), and see a number of new blogs (listed below, beginning with the most recent one):

—Making random decisions on the basis of a coin flip
—Are you happy? If so, be careful not to laugh: It may trigger gelotophobia!
—Regions with aging populations are experiencing higher death rates!

*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 ezine—the DOE FAQ Alert—shares one-on-one communications with Stat-Ease StatHelp, anyone (after gaining approval for registration) can post questions and answers to the Forum, which is open for all to see (with moderation). Check it out and weigh in!

The most recent materials posted are two announcements from Stat-Ease Programmer Tryg Helseth to the SOFTWARE SUPPORT "Network Issues (LAN versions)" section, which provide details on installing Design-Expert® software on a network and achieving annual license renewals.

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

1. FAQ: How do you know when to transform a response?
2. FAQ: Power issues with ruggedness testing
3. Info Alert: Published applications of DOE ranging from food science to corrosion inhibition
4. Book Giveaway: Winners announced
5. Webinar Alert (3rd): Problems Analyzing Historical Data
6. Events Alert: Introduction to Experimental Design & Automated Assay Optimization (AAO) FX Software
7. Workshop Alert: See when and where to learn about DOE
8. A heads-up on web-based statistics training:

P.S. Quote for the month: Senior economist takes a shot (?) at statisticians while commenting about our current recession.


1. FAQ: How do you know when to transform a response?

-----Original Question-----
A German engineer
"Your help has been very useful. I was just wondering if you could tell me if there was a certain way you went about analyzing response surface method (RSM) data with Design-Expert or if you just have so much experience with it that you knew which transformations to do."

Answer (from Stat-Ease Consultant Shari Kraber):
"Some years ago, transformations used to be done by trial and error. Now the Box-Cox diagnostic plot* does the math for us and can quickly direct us to the best transformation. Here's what I generally do:

1. Choose the highest-order suggested model (sometimes two are advised by Design-Expert) and change the selection to apply a backwards model reduction.

2. Verify the model adequacy by looking over the analysis of variance (ANOVA) p-values and the adjusted and predicted R-squared values.

3. Check all diagnostics for abnormalities — especially the Box-Cox plot, which may advise a specific transformation.

4. If indicated, go to the Transform menu and apply the one recommended by Box-Cox. Then follow steps 1-3 again. Assess the adjusted and predicted R-squares — they should get at least a little higher with a good response transformation."

PS. Amazingly enough, in some cases you can get a better fit with a simpler model after a successful transformation. For example, see from Table 10-6* of "RSM Simplified" by Anderson & Whitcomb how applying a log to response data from a design and analysis of computer experiment (DACE) on the wing design for a lightweight fighter jet.

(Learn more about RSM and transformations by attending the computer-intensive workshop "Response Surface Methods for Process Optimization." See for a description of this class and link from this page to the course outline and schedule. Then, if you like, enroll online.)

*Chapter 10 of this book is posted as a free sampler at


2. FAQ: Power issues with ruggedness testing

-----Original Question-----
An analytical method developer
"I took your "Experiment Design Made Easy" class in April and have been using Design-Expert since with good results. I now have run a resolution III ruggedness design on a calorimetric method. We tested 7 factors in 8 runs and asked five judges to rate the color density. I then averaged the judges scores for each run and entered the responses into the Design-Expert. I had originally assumed that the signal-to noise (S/N) ratio would be no less than 3. However, the variability in ratings may have dropped the S/N much lower. The results show that there is no effect seen for the range of factors tested. I have a basic question then about the Res III design. I set this up to achieve a power at 95% based on a S/N that was not realistic (as borne out in the subsequent experimental data). What do I then say about my design and results?"

Answer (from Stat-Ease Consultant Shari Kraber):
"Given that you found nothing statistically significant, concluding that your test method is rugged MIGHT be valid, but your eight-run design did not provide enough power to be very confident in stating this conclusion. We suspect that many eight-run designs used to 'prove' ruggedness are, in reality, not powerful enough to detect anything but a really huge effect. In your case (and many others, we presume) the method should not be declared rugged to the factor variations until more data can be collected — preferably via a foldover, which provides more power and higher resolution (IV) of effects — a win-win."

For more details see the Powerpoint slides for Shari's webinar on "How to Plan and Analyze a Verification DOE" that she presented last October (10/08). You will find this and other webinar materials posted at I also recommend an earlier webinar on "A Factorial Design Planning Process" developed by Shari and Consultant Pat Whitcomb. It delves into issues of power that are very enlightening for any experimenter. Also, see my article on "Struggle for Power vs. Resolution vs. Simplicity in an ASTM Standard" in December 2005 Stat-Teaser posted at It details a ruggedness test situation much like the one in this FAQ.

(Learn more about power for two-level factorial design by attending the computer-intensive workshop "Experiment Design Made Easy." For a complete description of this class, see Link from this page to the course outline and schedule. Then, if you like, enroll online.)


3. Info Alert: Published applications of DOE ranging from food science to corrosion inhibition

See (not available) for the details on how a food scientist at Rich Products applied mixture design of experiments to optimize the recipe for a new line of bread dough. Food Quality published this story in June (original link is not available ).
You will get greater depth on this work via the original manuscript at The Society of Automotive Engineers (SAE) detail how "DOE helps improve robustness of vehicle coating" in their online Off-Highway Engineering publication at The work was done by a paint chemist at Henkel. For a more complete write-up, see the original manuscript we posted at The Chemical and Process Industries Division* (CPID) of the American Society for Quality (ASQ) posted Pat Whitcomb's presentation on "Sizing Mixture (RSM) Designs" — see They also published an article by me and Pat on "Making Use of Mixture Design to Optimize Olive Oil — A Case Study." See this at

*The Chemical and Process Industries Division (CPID) is one of the oldest divisions in American of Society of Quality (ASQ). Chartered in 1952, CPID has approximately 1500 members. The purpose of CPID is assist in solutions to problems unique to our industries by offering a support system of fellow practitioners and resources.


4. Book Giveaway: Winners announced

These lucky readers were drawn at random from over two dozen entrants to a drawing for three first editions of "RSM Simplified, Optimizing Processes Using Response Surface Methods for Design of Experiments" by Anderson & Whitcomb*:
-> Hristo Iontchev, Statistician, San Francisco Bay Area
-> Despina Stefan, Scientist, General Mills, Minneapolis
-> Forrest Hentz, Coatings Technology Manager, Rio Tinto, Denver
Congratulations to these three winners and condolences to the others who entered into this drawing. Keep watching for more great books to be given away in the future.

*(This very economical and informative how-to softcover primer on RSM, and its companion — "DOE Simplified," are available via e-commerce at


5. Webinar alert (3rd): Problems Analyzing Historical Data

You are invited to attend a free web conference by Stat-Ease developed by Consultant Pat Whitcomb and me (the presenter) on "Problems Analyzing Historical Data." This free conference, which will be kept to an intermediate level statistically, will be broadcast on Tuesday, September 15 at 2 PM USA Central Time* (CT). I will repeat the webinar on Wednesday, September 16 at 8 AM. It is aimed at those who need help in trying to make any sense out of pre-existing data using regression modeling. As I will point out, there are many perils and pitfalls to watch for when working with happenstance data. 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 approximated one-hour educational sessions, our presenters often draw valuable material from Stat-Ease DOE workshops. Attendance may be limited, so sign up soon by contacting our Communications Specialist, Karen Dulski, via If you can be accommodated, she will e-mail instructions on how to connect for 'video' (Microsoft Powerpoint slides via the internet) and audio.

*(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 for international communications is even more complicated than statistics! Good luck!)


6. Events Alert: Introduction to Experimental Design & Automated Assay Optimization (AAO) FX Software

Introduction to Experimental Design & AAO FX Software is a 3-1/2 day course designed to provide assay developers with a foundation in statistical design of experiments (DOE) and the use of Automated Assay Optimization (AAO) FX software to apply DOE using the Beckman Coulter Biomek(R) FX Laboratory Automation Workstation. Design-Expert software is used to setup your assay DOE; Automated Assay Optimization (AAO) FX software is used to translate your DOE into corresponding Biomek® FX methods and finally, the assay results are analyzed using Design-Expert software. This course, will be presented on October 19-22 in Brea, CA by Pat Whitcomb (Stat-Ease) and Lisa Fan (Beckman Coulter). Click for more details.

(Second Notice) Pat Whitcomb will deliver a talk (co-authored by Wayne Adams) on practical considerations for optimal design at the annual conference of the European Network for Business and Industrial Statistics (ENBIS), which will be held September 20-24 in Goteborg, Sweden. For details on this event, see 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.


7. Workshop Alert: See when and where to learn about DOE via computer-intensive two-day workshops

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
> November 3-4* (Minneapolis, MN)

—> Mixture Design for Optimal Formulations (MIX)
> October 27-28* (Minneapolis)

—> Response Surface Methods for Process Optimization (RSM)
> December 1-2* (Minneapolis)

—> Designed Experiments for Life Sciences (DELS)
> November 10-11 (Cambridge, MA)

—> DOE for DFSS: Variation by Design (DDFSS)
> November 17-18 (Minneapolis)

*Now condensed to two days (formerly a three-day workshop)

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


8. A heads-up on web-based statistics training: offers 80+ online courses in statistics, with courses in engineering statistics, SPC, regression, forecasting, and many other topics. Classes include hands-on assignments with feedback, as well as online discussions with distinguished instructors. There is no need to be online at any particular time. See for more information.


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 —Senior economist takes a shot (?) at statisticians while commenting about our current recession:

"It's going to be a recovery only a statistician can love."

—Mark Vitner, Wells Fargo senior economist.

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, led by Neal Vaughn and Tryg Helseth (
—Heidi Hansel Wolfe, Stat-Ease sales and marketing director, and all the remaining staff that provide such supreme support!


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, #9-01 Jan 09, #9-02 Feb 09, #9-03 Mar 09, #9-04 Apr 09, #9-05 May 09, #9-06 June 09, #9-07 July 09, #9-08 Aug 09, #9-09 Sep 09 (see above)

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