Issue: Volume 10, Number 2 (Circulation: Over 5500 worldwide)
Date: February 2010
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:

Also, Stat-Ease offers an interactive web site—the Support Forum for Experiment Design at Anyone (after gaining approval for registration) can post questions and answers to the Forum, which is open for all to see (with moderation). Furthermore, the Forum provides program help for Design-Ease® and Design-Expert® software. Check it out and search for answers. If you come up empty, do not be shy: Ask your question! Also, this being a forum, we encourage you to weigh in!

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):

—Tiny rotifers defeat the Red Queen
—Getting straight to the point via the word for today
—Apples and oranges comparison of diets?
—Marketing researchers go curb mining for treasure in the trash

*Need a feed or e-mail updates from StatsMadeEasy? Go to It's easy!

"Your StatsMadeEasy blogs brighten up a dreary workday!"
—Applied Statistician, Florida

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

1. Upgrade Alert: V8 of Design-Expert software released!
2. FAQ: How to interpret added detail on center-point curvature offered by new version of Stat-Ease software
3. FAQ: What to do if curvature at center point of two-level factorial design becomes significant
4. Expert FAQ: If center points go off target, then what?
5. Webinar Alert: DOE Made Easy and More Powerful via Version 8 of Design-Expert Software
6. Events Alert: Third European DOE User Meeting
7. Workshop Alert: Newly developed class—Advanced Formulations: Combining Mixture & Process Variables

P.S. Quote for the month: Dirty secret of science. (Page down to the end of this ezine to enjoy the actual quote.)


1. Upgrade Alert: V8 of Design-Expert software released!

Version 8 of Design-Expert software ("DX8") is now available for trial use, outright purchase or upgrade. See the announcement at This newsletter provides details on many exciting new features, as well as pricing for new or upgraded licenses (see order form on the last page). A free, fully-functional update—DX8.01—is now posted for trial download from Give v8 a try!

This web site also provides free patches to update v8.0 licenses. The new release primarily addresses maintenance issues. View the ReadMe file for installation tips, known issues, the change history, and FAQs.

"Congratulations! I want to compliment you on Design-Expert 8. This software is absolutely wonderful. In fact, it is so good that I don't want to go back to v7 even though I have that software on my computer, too. If you ask what the difference is, my answer is that it is easy to use with everything at one's fingertips. Thanks for all you do at Stat-Ease to make product development easier and less costly."
—Harlan Faller, Senior Technologist

PS. Those of you who still use v6 of Design-Expert now is the time to make the leap to v8 by taking advantage of a limited-time offer for an economical upgrade. Starting from a listing of "what's new" in v8 at you can trace back all the added features of V7.1 and V7, if you like. However, think of a small black and white television versus a state-of-art flat-panel high-definition fast-refresh color TV. That is the leap you will achieve by upgrading to Design-Expert version 8. Why hold back on investing in DOE software with a price that pales in comparison to the value of more effective experimentation? Go for the top of the line! —Mark


2. FAQ: What to do if curvature at center point of two-level factorial design becomes significant

-----Original Question-----
Graduate researcher in chemistry
"I downloaded the new version of Design-Expert v8 to analyze my experiment. It is a fractional two-level design on 5 factors with two center points. Two factors are categoric so, given the four combinations of these, your software provided a total of 8 center points (2x4=8). When I analyzed my design, v8 showed me two analyses of variance (ANOVA)—adjusted versus unadjusted. How should I interpret the side-by-side statistics?"

Answer (from Stat-Ease Consultant Shari Kraber):
"The ANOVA printed in blue adjusts for curvature. It tests the factorial points separately from the center points, thus telling you whether the curvature is statistically significant. If so, predictions in the center of the design space will be off: Curvature can be tested, but not modeled from a two-level factorial with center points. Therefore, we comment in the annotated view that the adjusted model should not be used for prediction—it is only appropriate for the diagnostics. The unadjusted model (printed in black) incorporates curvature into an overall lack of fit test. The focus on curvature alone is thus obscured. However, the resulting model becomes more appropriate for prediction.

Ideally an experimenter finds that curvature is insignificant, which alleviates any concerns over the difference between the models that our software adjusts or leaves unadjusted for curvature."

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


3. FAQ: What to do if curvature at center point of two-level factorial design becomes significant

-----Original Question-----
Material Scientist, Personal Care
"Attached* please find a simple design of which the center point gives the highest value. However, the model failed to predict this trend. Would you mind telling me what mistake I have made?"

Answer (from Stat-Ease Consultant Shari Kraber):
"Center points can tell you if curvature is present in your system, but the two-factor interaction model is only capable of fitting a twisted plane—not a peak. For that you need a response surface method (RSM) design that provides extra runs to estimate the A^2 and B^2 terms. The analysis did show that the curvature was very significant, which is what I would expect from this set of data."

*(Note: Users of Stat-Ease software are free to e-mail data files to for review by DOE consultants.)

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


4. Expert FAQ: If center points go off target, then what?

-----Original Question-----
Graduate researcher in forensic science
"I have mailed you in the past regarding my experimental design, and I really appreciate your help. I am writing up my PhD thesis, having used factorial design and Design-Expert for part of my project, and I'm trying to go through the software and calculate the effects, sum of squares (SS), F statistics, etc. by hand (Excel, actually) so I am sure I know what is happening (in an effort to avoid being accused of using the 'magic black box'!).

I have done a full 2^5 factorial design, unreplicated. I added 11 center points to the design, but without realizing the importance of having the center points exactly at x=0 for each level, my center points were actually skewed (coded levels A-E for 11 centers are: -0.33, -0.429, -0.33, -0.13, -0.33).

When I create a full 2^5 design (with 0 replicates, 1 block and 11 center points) in Design-Expert and then manually change the coded levels for each center point, I can't figure out how your software is calculating the effects. They are slightly different than those calculated if I don't include the 'center' points. For instance, factor A's effect without center points is 13.86, but when the skewed center points are added, the A effect is 13.56.

1. Would it be possible to explain how Design-Expert is calculating these effects? I'm sure it has something to do with the skewed center points, but I can't figure out what...
2. I was also expecting that the SS for lack of fit (LoF) for the design including the center points would be the same as the Residual in the design without center points. However, this isn't the case with my skewed center points. Would it be possible to explain how DX6 is calculating the SS LoF with my skewed center points?

Thanks so much for your help, once again. I have attached my DX files (one with centers, one without) if they're of any use to make things clearer."

Answer (from Stat-Ease Consultant Wayne Adams):
Design-Expert calculates sum of squares and effects using matrix algebra regression methods that can be found in any regression text book. When a factorial design is created with true center points the sum of squares, rather than going to a typical model term, instead calculate a curvature term.* However, if the center points are not actually at the center then their sum of squares are distributed amongst the standard model terms.

As a work-around, you can get a pseudo-curvature test by fitting a polynomial model rather than a factorial model. If a squared (quadratic) term shows as significant, but aliased, then you have curvature to deal with.

To fit a polynomial model, go to the design layout, right-click at the top of each response, choose Edit Info and change the option from factorial to "analyze as polynomial." Then, when you analyze your data and get to the Model selection, manually add all of the quadratic terms. The A^2 term will test significant if there is curvature. (Due to aliasing, all the other squared terms will be set to a zero sum of squares).

*In our new version 8 this is done for the adjusted model only as explained in FAQ 1.


5. Webinar Alert: DOE Made Easy and More Powerful via Version 8 of Design-Expert Software

Keeping it simple and making it fun, Stat-Ease will introduce an array of statistical methods for design of experiments (DOE) made easy and more powerful via version 8 of Design-Expert software:

—Two-level factorials for process screening, characterization and verification
—Response surface methods (RSM) for process optimization
—Multicomponent mixture design for optimal formulation.

I will kick off the first in a series of free webinars by working through case studies on factorial design on Wednesday, March 24 at 2 PM USA Central Time* (CT). I will repeat this presentation on Thursday, March 25 at 8 AM.

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 soon by contacting our Communications Specialist, Karen Dulski, via If you can be accommodated, she will provide immediate confirmation and, in timely fashion, the link with instructions for our new web-conferencing vendor: GotoWebinar (see

*(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. Events Alert: Third European DOE User Meeting

(1st Alert) The Third European DOE User Meeting will be held June 1-2 in Lucerne, Switzerland, with pre- and post-conference workshops held on May 31 and June 3. It's sponsored by Stat-Ease, CQ Consultancy (Belgium) and Statcon (Germany). Come to increase your understanding of design of experiments (DOE) techniques, learn of successful real-life applications of DOE, and also attend presentations specific to Stat Ease software and its features. To receive more information as this meeting shapes up, send an e-mail to Heidi Hansel Wolfe via If you would like to present a case study, ask her for details on how to become a speaker.

(2nd Alert) I will give a talk on "Optimal Verification Testing with Graphical Effects Analysis" and man the Stat-Ease exhibit at the National Defense Industrial Association (NDIA) National Test and Evaluation (T&E) Conference in San Diego on March 1-4. For details, see Click for a list of upcoming appearances by Stat-Ease professionals. We hope to see you sometime in the near future!


7. Workshop Alert: Newly developed class—Advanced Formulations: Combining Mixture & Process Variables

(1st Alert) Our Stat-Ease consulting staff, led by Pat Whitcomb, has developed a new workshop on Advanced Formulations: Combining Mixture & Process Variables — see the course outline posted at and how if fits into our flow of DOE training at

This premier class is geared up for formulators who are already well-versed on mixture design, as well as applied statisticians who want to expand their arsenal of tools. 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! Also, take advantage of a $395 discount when you take two classes that are offered on consecutive days.

—> Experiment Design Made Easy (EDME)
(Detailed at
> March 25-26 (Philadelphia, PA area)
> April 27-28 (Minneapolis, MN)

—> Designed Experiments for Life Sciences (DELS)
> February 23-24 (Minneapolis)

—> Mixture Design for Optimal Formulations (MIX)
> March 2-3 (Minneapolis)
> May 18-19 (Minneapolis)

—> Advanced Formulations: Combining Mixture & Process Variables (MIX2)
> May 20-21 (Minneapolis)

—> Response Surface Methods for Process Optimization (RSM)
> April 29-30 (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—Dirty secret of science:

"Experiments rarely tell us what we expect. That's the dirty secret of science."

—Kevin Dunbar, Director of the Laboratory for Complex Thinking and Reasoning, University of Toronto Scarborough.

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 marketing director, Karen Dulski, 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, #9-10 Oct 09, #9-11 Nov 09, #9-12 Dec 09, #10-1 Jan 10, #10-2 Feb 10 (see above)

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