Issue: Volume 7, Number 7
Date: July 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
—Smart thinking to be born first
—Tips of icebergs and humps of whales
—Don't Juneau car problems never reproduce for the mechanic?

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

1. Announcement: Version 7.1.3 of Stat-Ease software released — it features an upgrade to the FDS design-evaluation plot
2. Newsletter Alert: July issue of the Stat-Teaser offers an enlightening article on preventing over-selection of effects
3. FAQ: Nominal versus ordinal choice for categorical factors
4. Info Alert: Publish your DOE success story — inspirational case-study articles sought for all industries!
5. Events Alert: Pharma in Philly & Statistics at Salt Lake
6. Workshop Alert: See when and where to learn about DOE

PS. Quote for the month: Issues with accuracy versus precision from financial wizards trying to pin down the true values of key statistics on economic well-being. (Page through to the end of this e-mail to enjoy the actual quote.)


1. Announcement: Version 7.1.3 of Stat-Ease software released — it features an upgrade to the FDS design-evaluation plot

Version 7.1.3 of Design-Expert® (DX) and Design-Ease® (DE) software is now posted at for a free fully-functional 45-day trial. This web site also provides patches to update older, licensed, versions of 7.1. The new release primarily addresses maintenance issues. However, it also includes a new tool for the "fraction of design space" (FDS) graph, which DOE guru Doug Montgomery says will be "very valuable in studying the potential performance of a design." It is simple
enough that even non-statisticians can see differences at a glance. The FDS plot can be applied to any type of experiment — mixture, process or combined mixture-process (mixing your cake and baking it too!). It provides very helpful visual perspective on choosing between alternative test matrices, particularly for
highly constrained experimental regions. See an example of the FDS plot and detail on tools posted at Pat Whitcomb, who leads our team of statistical experts,
recently developed an enhancement called fraction of paired design space ("FPDS"). The FPDS provides an approximate measure of the power of a design to detect a given difference somewhere within the experimental region. Users of V7.1.3 of Stat-Ease software can simply enter the response difference they hope to detect (the signal "delta") and what they anticipate for the standard deviation (the noise "sigma"). The program then calculates the fraction of the design space in which this difference can be found. If the answer is nil, one must adjust expectations! Ideally the FPDS will be high — perhaps 0.8 might be a good
benchmark. Pat will detail FPDS this September in Dortmund, Germany to ENBIS (European Network of Business and Industry Statistics). Watch for more information on this in the next issue of the DOE FAQ Alert.


2. Newsletter Alert: July issue of the Stat-Teaser offers an enlightening article on preventing over-selection of effects

Many of you will soon receive 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 July issue at It features an article by me titled "Bonferroni Draws the Line on Over-Selection of Effects." It shows how an unwary user can easily select too many effects from a half-normal plot. However, by making use of the Pareto plot in Stat-Ease software and paying heed to the Bonferroni-corrected threshold for statistical significance, experimenters can curb a natural bias for picking
smaller effects that may not be significant or of any importance as a practical matter. This issue of the Stat-Teaser also announces release of version 7.1 of Design-Ease software, including a handy order form.
Design-Ease keeps DOE simple for non-statisticians who only need factorial design tools, for example, Green Belts in Six Sigma.


3. FAQ: Nominal versus ordinal choice for categorical factors

-----Original Message-----
From: California
"With the aid of Stat-Ease software, I set up a general factorial design, which I understand is intended for categoric factors. Your software offers two choices for the contrasts — 'nominal' versus 'ordinal.' Which is appropriate and under what circumstances?"

Answer (from Stat-Ease Consultant Pat Whitcomb): "Nominal coding is the default for categoric (named) factors, such as black versus white. Ordinal can only be applied to factors with discrete numeric levels, for example, three temperatures in degrees C — 0 (freezing), 20 (ambient) and 100 (boiling hot). The choice of coding affects only the coefficients — not model significance or fit. For a two-level factor there is no difference between the two. That's the simple answer. Here's a bit more explanation on the statistical aspects. Nominal coding compares the average at each level of the factor to the overall mean, whereas ordinal coding breaks the same factor sum of squares into orders — linear contribution, quadratic contribution, etc, depending on the number of levels. For more detail, including examples showing the coding, go to Help and search on 'ordinal' for the topic titled 'Factor coding in factorial designs.' To reiterate, so far as model fit and optimization are concerned these coding choices make no difference. It comes down to personal preference for certain statisticians who may be accustomed to seeing coefficients one way versus the other. Of course it is always better to be explicit by entering the value for a numeric level, for example, the numbers 0, 20 and 100 instead of the words 'Low, 'Medium' and 'High.'"

(Learn more about factorial design 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.)


4. 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 for pharmaceutical. 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


5. Events Alert: Pharma in Philly & Statistics in Salt Lake City

Surprised at how many talks include DOE as a top tool for process improvement, I signed up to attend and exhibit Stat-Ease software at the Pharmaceutical Technology conference in Philadelphia, PA, this month — July 24-26. For more information on this event, see Also, see the latest software features demonstrated by Stat-Ease at booth 305 in the exhibition area of the Joint Statistical
Meetings (JSM) 2007 conference in Salt Lake City, UT, on July 29 through August 1. The American Statistical Association's section for Quality and Productivity is sponsoring a roundtable luncheon on July 31 that will be led by Stat-Ease Consultant Shari Kraber. Her topic for discussion will be "Tools for Planning and Properly Sizing a Factorial DOE." Under the auspices of the Women in Statistics committee, Shari will also head up a breakfast roundtable on August 1 that will delve into "The Statistician's Role Outside the Workplace." Click for a complete 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.


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

Seats are filling fast for the following DOE classes:

--> Experiment Design Made Easy (EDME)
(Detailed at
—August 21-23 (Minneapolis — Stat-Ease training center)
—September 18-20 (Philadelphia, PA — contact us for site)

--> Mixture Design for Optimal Formulations (MIX)
—August 7-9 (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 monthIssues with accuracy versus precision from financial wizards trying to pin down the true values of key statistics on economic well-being: "It is better to be roughly right than precisely wrong."
—John Maynard Keynes (quoted by Alan Greenspan in testimony on bias in the consumer price index — posted on the Internet at

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, #7-7 Jul 07 (see above)

Click here to add your name to the DOE FAQ Alert newsletter list server.

Statistics Made Easy®

DOE FAQ Alert ©2007 Stat-Ease, Inc.
All rights reserved.


Software      Training      Consulting      Publications      Order Online      Contact Us       Search

Stat-Ease, Inc.
2021 E. Hennepin Avenue, Ste 480
Minneapolis, MN 55413-2726
p: 612.378.9449, f: 612.378.2152