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Vol: 12 | No: 1 | Jan/Feb'12
The DOE FAQ Alert

Heads-up (below!)
See amazing video of robot baking cookies
(Follow link in the PS in topic 2)

Prime Alert
Due to the shut down on February 29 of our current List Server, your subscription may be interrupted: This Alert (Jan-Feb) will be the last going out with them.  If you do not see the March-April issue by May 1, pull this DOE FAQ Alert back on screen and click here to re-subscribe.  Or find this registration link by going to our home page, choosing Publications from the top links, going to the one for DOE FAQ Alert and scrolling down to where it says “Click here to add your name to the DOE FAQ Alert newsletter list server.”

Thank you for your persistence in continuing as a subscriber.  We have used the current list server since I began writing the DOE FAQ Alert in April of 2000—nearly a dozen years ago, so this is a landmark change.  I hope it goes seamlessly but just in case it does not, please remain Alert (pun intended!).

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.

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 this registration page.

Also, Stat-Ease offers an interactive web site—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 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 with answers! The following Support Forum topic provides a sampling of threads that developed since my last Alert:

  • Area: Design Selection, Topic: The best design for my experiment....., Question: “Currently, I am carrying out an experiment on medical scaffold (which is a compound) and I need a DOE that would best represent my data in a presentation as it is needed to convince the people that what I have come up with is the best and nothing less.”

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. A recent thread features a poll by Consultant Brooks Henderson: “How many DOEs did you set up and start experimenting on in 2011?”

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

Also see the new comments about my 10/30/11 blog on “Pareto distribution makes a handy ‘screw driver.’” 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 8.0.7 of Design-Expert software released (free update for licensed users of v8)
2:  Newsletter alert: January issue of the Stat-Teaser features an experiment aimed at developing cookies that taste good despite variations in the time and temperature of baking
3:  FAQ: Results within block, for example—curvature, appear quite different
4:  Info alert: DOE for Non-Manufacturing
5:  Webinar alert: Basics of RSM for process optimization (part 2 of 2)—Encore!
6:  Conference alert: 4th European DOE Meeting June 27-28 in Vienna—save the date!
7:  Events alert: Statistical conference in Orlando, QbD meeting in Mumbai, and much more
8:  Workshop alert: Classes coming to California this March
PS. Quote for the month: Misplaced trust in scientific findings
(Page down to the end of this e-zine to enjoy the actual quote.)


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1: Software Alert: Version 8.0.7 of Design-Expert software released (free update for licensed users of v8)

Newly-released version 8.0.7 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 primarily provides maintenance of existing features.  View the ReadMe file for details on this update, installation tips, known ‘bugs,’ change history, and FAQs.

PS. Reminder: 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.

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2: Newsletter Alert: January issue of the Stat-Teaser features an experiment aimed at developing cookies that taste good despite variations in the time and temperature of baking

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 January issue at this link. It features an article by me on how “Sophisticated DOE tools produce tasty cookies time after time” for Design For Six Sigma (DFSS) guru Andy Sleeper (Successful Statistics, LLC). It was great that Andy allowed me to share this fun and enlightening case study on the application of POE (propagation of error) tools in Design-Expert software.

This Stat-Teaser also provides a very helpful primer by Consultant Shari Kraber on “Practical Aspects of Algorithmic Design of Physical Experiments, from an Engineer’s Perspective.”

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.

PS. Re baking cookies, check out this riveting video of an MIT robot trying its ‘hand’ at whipping up a batch.

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3: FAQ: Results within block, for example—curvature, appear quite different

Original Question:

From a Process Engineer:
“Hello!  I’m analyzing my first factorial DOE with blocking and center points.  I am seeking some feedback on my analysis, and have a few questions:

Since the Block Mean Square value is large compared to the Residual Mean Square value, I am under the impression that the effect of blocking is significant.  I am not surprised by this since the process was not running as smoothly on Day 1 as Day 2 for an unknown reason.

I ran three center points per block.  The ANOVA analysis reveals that the curvature is significant.  Since the curvature MS value is on the same order as the block MS value, is it possible that there is a block-related issue that makes the curvature seem more significant than it really is, or are these effects completely independent in the analysis?  Since we encountered some problems with the process on Day 1, the standard deviation of parts measured within individual runs was generally larger on this day.  The curvature was significantly less in the second block, with all three points seeming to follow the linear model (on the 2FI graph, they’re between the two lines at the middle value on the x axis).

My interpretation of this situation is that the actual amount of curvature cannot fully be determined at this time due to the behavior of the equipment on Day 1.  Since R1 must be minimized, the best conditions are the high level of factor A and the low level of Factor B, even with the curvature.  If curvature is as large as suggested by the lower 2 center points on the graph, the implication is that the system is not as sensitive to a slight decrease in Factor A and slight increase in Factor B as the linear model would suggest.  The curvature, however, does not significantly impact the selection of optimal factors within this design space.

Is this an appropriate way to approach curvature in this situation?  If the curvature in block 1 were more pronounced, suggesting that there is likely a minimum R1 value between the high and low factor levels, I would fill in the runs necessary to make it a 3-level factorial design or an RSM design.”


From Stat-Ease Consultant Wayne Adams:
“Start by looking at the Graph Columns node.  This is the data without any adjustments plotted in a scatterplot.  Set the X-axis to factor A, the Y Axis to the response and then the color by to block.  It appears to me that there is very little block effect and very little curvature. 

If you are concerned that the data is not representative of the population, then the “bad” block should probably be discarded.  The remaining data can be analyzed and shows A and B to be significant.  Curvature is statistically significant within Block 2, but it is not a very big effect (probably unimportant) and doesn’t really challenge the conclusion that A and B have significant effects on the model.

Color by block option for Graph Columns
Color by Block option for Graph Columns node in Design-Expert software (example from workshop)

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

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4: Info Alert: DOE for Non-Manufacturing

“Design of Experiments for Non-Manufacturing Processes: Benefits, Challenges and Some Examples” by Jiju Antony; Doug Montgomery; Shirley Coleman; myself and Rachel Silvestrini was published in the Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture last November (vol. 225, no. 11, pp 2078-2087).  It refers to my white paper on “DOE for Non-Manufacturing”.

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5: Webinar Alert: Basics of RSM for process optimization (part 2 of 2)—Encore!

Response Surface Methods (RSM) can lead you to the peak of process performance.  In this intermediate-level webinar presented on Wednesday, February 22 at 10:30 AM CT,* Stat-Ease Consultant Brooks Henderson will present a second round of education on response surface methods (RSM) for optimizing processes.

If you are new to RSM, this webinar is for you!  If you missed part 1, do not worry—we posted the recorded presentation by Consultant Shari Kraber here.

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 from our web-conferencing vendor GotoWebinar.

*(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!)

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6: Conference Alert: 4th European DOE Meeting June 27-28 in Vienna—save the date!

Block off the last week of June for the Fourth European Design of Experiments (DOE) User Meeting and Workshops.  Watch for details coming on our web site, via the next DOE FAQ Alert and in e-mailed announcements.

The meeting will focus on DOE, with a special emphasis on Design-Expert software.  Both the theoretical and practical aspects of DOE will be addressed, including the latest developments in the field.  The two meeting days will include lectures by keynote speakers and other DOE experts, case study presentations by DOE practitioners, and an opportunity to consult with experts about your DOE applications.  Optional pre- and/or post-meeting workshops will be presented to give you the skills to apply what you have learned.  Oh, and let’s not overlook the opportunity for breaking away to spend time in Vienna—a magnificent city of world culture.

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7: Events Alert: Statistical conference in Orlando, QbD meeting in Mumbai, and much more

Break away to Orlando, FL on February 16-18 to attend an electronic poster presentation by Consultant Shari Kraber on “Using DOE with Tolerance Intervals” at the inaugural Statistical Practice Conference, sponsored by the American Statistical Association (ASA).  For details, click here.

If you work in a defense industry, come to the National Test and Evaluation Conference on March 12-15 at Hilton Head, SC, and hear my talk on “Practical Aspects for Designing Statistically Optimal Experiments.”  The sponsor, the National Defense Industrial Association (NDIA), provides information on this “T&E” technical meeting at this link.

Shari returns to Minnesota in April (actually sooner—we hope) for the 1st Annual Professional Development Summit held in Brooklyn Center on April 2-3.  She will present a talk on the “Top Ten Modern-Day Statistical Tools for Quality Professionals.”  See details posted on the Summit at this site posted by the Minnesota Section of the American Society of Quality (ASQ)—the sponsor.

Stat-Ease Consultant Pat Whitcomb travels halfway around the world to give a workshop on DOE for QbD at the Quality by Design India 2012 conference in Mumbai, India on April 11-13.  It is affiliated with CPhI India—an annual event for API, generics, fine chemicals and bio-pharmaceuticals industries in the subcontinent.  For more information contact Stat-Ease.

Back here in the States, Stat-Ease will exhibit to members of the American Association of Pharmaceutical Scientists (AAPS) who attend the 2012 National Biotechnology Conference in San Francisco on May 21-23. Register here for the post-conference Short Course on “Practical Essentials of Design of Experiments (DoE) toward Robust Bioanalysis,” where Shari will provide an “Introduction to Design-Expert for DOE Analysis.”

Down the California coast a few weeks later, June 4-7, you can see Design-Expert software demonstrated by Consultant Wayne Adams for the 29th Quality and Productivity Research Conference.  While there, attend a new talk by Pat Whitcomb on “How to Design Experiments when Categoric Mixture Components Go to Zero.”  Click here for more details and link to the conference flyer.

Click here for a list of other upcoming appearances by Stat-Ease professionals.  We hope to see you sometime in the near future!

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8: Workshop Alert: Classes coming to California this March

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 February to earn $395 off the combined tuition!

** Take both SDOE and DEAO to earn $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

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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—Misplaced trust in scientific findings:

The non-scientific mind has the most ridiculous ideas of the precision of laboratory work, and would not be surprised to learn that… the bulk of it does not exceed the precision of an upholsterer who comes to measure a window for a pair of curtains.

—Charles S. Peirce, an American chemist who introduced blinded, controlled randomized experiments in 1884 (before Fisher!).  Read about this pioneering study in Shuffle the deck, flip that coin: randomization comes to medicine posted by The National Center for Biotechnology Information (NCBI).

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!

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