> If you are having trouble viewing this email view it online.
Vol: 11 | No: 2 | Mar/Apr'11
The DOE FAQ Alert

Circulation: Over 5500 worldwide

Which two (out of 16) reasons stand out as to why European researchers do not use statistical tools for design and analysis of experiments?
(For the answer, see section 5 below.)

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, click here.

Feel free to forward this newsletter to your colleagues. They can subscribe by going to this registration page.

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.

Also, Stat-Ease offers an interactive website—The Support Forum for Experiment Design. 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 to Design-Ease® and Design-Expert® software. Check it out and search for answers. Also, this being a forum, we encourage you to weigh in with answers!

To open yet another avenue of communications with fellow DOE aficionados, sign up for The Stat-Ease Professional Network on Linked In and start or participate in discussions with other software users.


Stats Made Easy Blog

StatsMadeEasy offers wry comments weekly from an engineer with a bent for experimentation and statistics. Simply enter your e-mail in the forwarding field at and get new StatsMadeEasy entries delivered directly to your inbox. Or click this link to:

Subscribe with Feedburner

“Your StatsMadeEasy Blog brightens up a dreary work day...”
—Applied Statistician, Florida Smiley Face

Topics discussed since the last issue of the DOE FAQ Alert (latest one first):

Also, see the new comments on my 1/9/11 blog-alert on “Statistics-driven scientific methods slammed again” and other recent posts.  Please do not be shy about adding your take about any news or views you see in StatsMadeEasy.  Thanks for paying attention.


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


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

1:  Software alert: Version 8.0.5 of Design-Expert software released with several new features (FREE update for licensed users of v8)
2:  Newsletter alert: The April issue of the Stat-Teaser reveals how v8 tools make analysis of a general-factorial experiment much easier
3:  FAQ: To complete my experiment, I had to change some of the specified factor levels in the response surface method (RSM) design for process optimization: Is that OK?
4:  Info alert: DOE helps optimize an injection-molding process
5:  Heads-up from a reader: 16 reasons why European researchers do not use the statistical tool for design and analysis of experiments
6:  Webinar Alert: How to Get Started with DOE
7:  Book giveaway: Winners of RSM text by Myers, Montgomery and Anderson-Cook
8:  Events alert: How to frame Quality by Design (QbD) space via Response Surface Methods (RSM) and mixture experiments
9:  Workshop alert: See when and where to learn about DOE
PS. Quote for the month: All statisticians are insane by definition, according to Einstein.
(Page down to the end of this e-zine to enjoy the actual quote.)

- Back to top -

1: Software alert: Version 8.0.5 of Design-Expert software released with several new features (FREE update for licensed users of v8)

Newly-released version 8.0.5 of Design-Expert software is posted at this download site for free trial evaluation. This web site also provides free patches to update older licensed versions of 8.0.

The release provides a number of valuable new features, including:

  • confidence interval (CI) added to numeric optimization—this facilitates finding a desirable setup within a quality-by-design (QbD) space
  • improved auto-scaling
  • clearer design-summary display
  • an XML “self-test” to validate that the software installed OK
  • an additional coloring option for graphical optimization that shades outside the limits, but inside the constraints as shown in the figure below

Graphical Optimization

Graphical optimization shown with most desirable parameters flagged and design-space framed with confidence intervals (CIs)—new feature allowed coloring in a yellow caution zone (outside the green QbD window).

View the ReadMe file for other features, installation tips, known ‘bugs,’ change history, and FAQs.

PS. Heads-up: If you want to receive notice when an update becomes available, go to Edit on the main menu of your program, select Preferences and, within the default General tab, turn on the “Check for updates on program start” option.

- Back to top -

2: Newsletter alert: The April issue of the Stat-Teaser reveals how v8 tools make analysis of a general-factorial experiment much easier

Many of you have received, or soon will, 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 March issue at this link.  It features my revisiting of a general factorial experiment featured in a book that I co-authored on DOE Simplified* that tested a claim by an insulated-mug maker that they “Keep Hot Drinks Hotter & Cold Drinks Colder Longer.”

This Stat-Teaser also provides a heads-up by Stat-Ease Consultant Shari Kraber on “Modern Alternatives to Traditional Designs.”

Thank you for reading our newsletter.  If you 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.  (Note: You will be notified via the DOE FAQ Alert on new newsletter posts.)  In any case, we appreciate you passing along hard copies and/or the link to the posting of the Stat-Teaser to your colleagues.

- Back to top -

3: FAQ: To complete my experiment, I had to change some of the specified factor levels in the response surface method (RSM) design for process optimization: Is that okay?

Original Question:

From a Principal Pharmaceutical Engineer:
“I recently performed a study using Design-Expert on tablet compression.  The screening study went very well, no problems encountered and the software produced pleasing responses.  I went on to perform an augmented central composite design (CCD) study to see if I had reached my upper and lower limits.  I found that on some of the variables, I could not use the CCD-specified limits, otherwise my tablet press went into alarm.  So what I did was modify the extremes as much as needed to manufacture a tablet that didn’t become defective.  I’m wondering what the repercussions are for not using the specific levels for the standard CCD?  I’ve essentially eliminated or modified some of the axial (star) points.  The resulting ANOVA presented acceptable model equations, but I may have to defend this in an upcoming presentation, so I just want to make sure I have something to say in anticipation of being challenged.  Any assistance that you can provide would be most appreciated.

As a side note, I have considered publishing my design study approach in a trade journal and would like to reference that I used Design-Expert.  Is this acceptable, or do you prefer not to have your company name or software mentioned in the article?  Do you have any preference to reviewing the article prior to me submitting it to the journal editor?”


From Stat-Ease Consultant Brooks Henderson:
  “You did the right thing by bringing the axial points in so that your process worked.  Just be sure that you type in the actual values you used for each run and Design-Expert will analyze what is there.  The repercussions for moving those axial points can be seen by going to the Evaluation node of the software, going to the graphs tab and viewing the contour plot.  The default axial values are for a ‘rotatable’ design, meaning the standard error of prediction is only dependent on distance from the center of the design, not direction.  If you have a rotatable design, the contour plot features symmetric circles around the center-point.  In 3D surface view, you see that this forms a flat-bottomed bowl—very good for prediction at the target-region of your experiment.
Design Evaluation for a Central Composite Design
Screen-shot from Design-Expert of design-evaluation for a central composite design constructed using the default settings.  (The 3D view is displayed via View, Pop-Out View.)

To compare the original design to the new one you actually ran, just create both designs and look at the differences in the contours, and, better yet, the 3D surface views.  From what you described, it’s doubtful that the necessary adustments you made to the CCD created any major problems for your experiment, but send your ‘dx*’ data file to so we can provide an informed opinion on this.

We appreciate being mentioned in journal articles, but when doing so please refer to “Design-Expert® software” and note that this is a registered trademark of Stat-Ease, Inc.  The trademark symbol is only needed in the first mention of Design-Expert.  If you would like us to review the article, just let us know—we’d be happy to do so.”

(Learn more about central composite designs by attending the two-day computer-intensive workshop “Response Surface Methods for Process Optimization.” Click on the title for a complete description.  Link from this page to the course outline and schedule.  Then, if you like, enroll online.)

- Back to top -

4: Info alert: DOE helps optimize an injection-molding process

Plastics Today features this case study of a DOE by RTP Company that enabled their clients to control surface resistivity of custom-engineered thermoplastics.  Check it out!

Also, take a look at this new post by Pharma QbD that provides a heads-up on “What to Look for in Statistical Software.”

- Back to top -

5: Heads-up from a Reader: 16 reasons why European researchers do not use the statistical tool for design and analysis of experiments

Our South African value-added-reseller Nico Laubscher (InduStat Pro) emailed me a ‘heads-up’ about a recently-published study of why engineers in Europe don’t use DOE for their research.*   Two causes (out of the 16 suggested in the survey) stood out for the low rate (less than 1 out of 5) of adoption for these powerful tools to design and analyze experiments:

• “low commitment by managers” and
• “poor statistical background.”

I feel sure these results apply all over the world, not just Europe.  Are any of you readers surprised by them?   Feel free to weigh in with your best idea on breaking the ice for DOE.

* Journal of Applied Statistics, Vol. 37, No. 12, December 2010, 1961–1977: “Why is not design of experiments widely used by engineers in Europe?” by Martín Tanco, et al of the Department of Industrial Management, TECNUN, University of Navarra, Spain. Stat-Ease International Marketing Director Heidi Hansel-Wolfe notes: “The first author on the paper, Martin Tanco, now works for our reseller in Uruguay, TECNIGOM Ltda. , and provides DOE training in South America.

- Back to top -

6: Webinar Alert: How to Get Started with DOE

Stat-Ease Consultant Brooks Henderson will present a webinar at the beginner level showing “How to Get Started with DOE” on Thursday, April 28 at 2 PM CDT USA.  He will incorporate his Whirley-Pop DOE and some tips from the past webinars.  If you are new to DOE, this webinar is for you!

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 web-conferencing vendor.

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

- Back to top -

7: Book giveaway: Winners of RSM text by Myers, Montgomery and Anderson-Cook

These lucky readers were selected at random from several dozen entrants for our latest book giveaway:

  • Tom Sutton, Professor, Mathematics Department & Distance Education, Mohawk College, Hamilton, Ontario
  • Nanette Clark, Program Manager for Color Binder, Z Corporation, Burlington, Massachusetts
  • John Kominsky, Vice President, Environmental Quality Management, Inc., Cincinnati, Ohio

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.


- Back to top -

8: Events alert: How to Frame Quality by Design (QbD) Space via Response Surface Methods (RSM) and Mixture Experiments

On May 17, I will be in Pittsburgh presenting a talk that details “How to Frame Quality by Design (QbD) Space via Response Surface Methods (RSM) and Mixture Experiments.”  The venue is the New and Proven Approaches to Continual Quality Improvement conference by the Institute for Continual Quality Improvement.  This is held concurrently with ASQ’s World Conference on Quality & Improvement, where Stat-Ease will exhibit.  We hope to see you in Pittsburgh!

Click here 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 reimbursement for travel expenses.  In any case, it never hurts to ask Stat-Ease for a speaker on this topic.

- Back to top -

9: Workshop Alert: See when and where to learn about DOE

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 complementary workshops that are offered on consecutive days.

All classes listed below will be held at the Stat-Ease training center in Minneapolis unless otherwise noted.

* Take both EDME and RSM in June to earn $395 off the combined tuition!

** Attend both SDOE and DELS to save $295 in overall cost.

*** Take both MIX and MIX2 to earn $395 off the combined tuition!

See this web page 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

- Back to top -

  Please do not send me requests to subscribe or unsubscribe—follow the instructions at the very end of this message. 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—all statisticians are insane by definition, according to Einstein:


Insanity: doing the same thing over and over again and expecting different results.”

—Albert Einstein

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, Wayne Adams and Brooks Henderson
—Statistical advisor to Stat-Ease: Dr. Gary Oehlert
Stat-Ease programmers led by Neal Vaughn
—Heidi Hansel Wolfe, Stat-Ease marketing director, Karen Dulski, and all the remaining staff that provide such supreme support!

DOE FAQ Alert ©2011 Stat-Ease, Inc.
All rights reserved.