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Vol: 13 | No: 1 | Jan/Feb'13
The DOE FAQ Alert

Heads-up (below!)
Advice for quantitative types tempted to pick stocks based on prior performance.

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 previous DOE FAQ Alerts 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 pores not only 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: Design Selection, Question: “…what would happen if I change a design…”

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 “Power Calculations for Mixture Designs.”

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

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:  Newsletter Alert: January issue of the Stat-Teaser details a fun and educational mixture design on an orange drink
2:  FAQ: Do I need a rationale for applying a response transformation?
3:  Expert FAQ: Why does Design-Expert® request that users maintain model hierarchy?
4:  Webinar alert: How to get started with Design-Expert software
5:  Events alert: Appearances in New Orleans, Charlotte and our home area (Minnesota)
6:  Workshop alert: Classes in California coming soon—take advantage!

PS. Quote for the month: Trying to get the jump on Wall Street in 2013—words of wariness.
(Page down to the end of this e-zine to enjoy the actual quote.)

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1: Newsletter alert: January issue of the Stat-Teaser details a fun and educational mixture design on an orange drink

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 September issue at this link.  It features a report by me on an educational experiment by food-science students at North Carolina State University (NCSU).  They managed to hit the spot with their orange drink concocted via powerful statistical tools for mixture design, analysis and optimization.

This Stat-Teaser also provides a report by Stat-Ease Consultant Brooks Henderson on a follow-up optimization to the experiment on instant noodles detailed in the last newsletter issue.  Now he and his colleagues are enjoying very cheap and easily prepared, yet surprisingly tasty, lunches (never mind the nutritional value!).  They can dig in on the noodles with great gusto knowing their process achieved confirmation via the handy confirmation node tool now provided by Design-Expert.  Check it out!

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.

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2: FAQ: Do I need a rationale for applying a response transformation?

Original Question:

From an R&D Engineer:
“Thank you for having the Real Life DOE webinar.  It was nice to see how your software can simplify things.  Does there need to be a rationale for a response transformation, or does it suffice that the data can be modeled better empirically in the new metric?”


You are welcome, Jim.  You ask a good question.  Following the direction provided by the Box-Cox plot serves the purpose of simply modeling the results as best one can.  However in certain circumstances, perhaps mainly academic, researchers apply a mechanistic model via first principles (subject-matter knowledge) and then transforms (usually via log) to facilitate fitting of the coefficients.  For example, Box & Draper in Chapter 12 of their landmark text (1987) Empirical Model-Building and Response Surfaces lay out a chemical-process example that adheres to pre-existing models for reactivity.  Nevertheless, the answer to your question is yes—so long as the response transformation provides a better fit there is no need to have a rationale for the type of transformation used.


(Learn more about transformations 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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3: Expert-FAQ: Why does Design-Expert request that users maintain model hierarchy?

Original Question:

From a Simulation Consultant:
“Why does Design-Expert require hierarchy by default when I do a backward regression? Douglas Montgomery in his book Design and Analysis of Experiments (and its supplemental materials) says that hierarchy is not always a good idea.  Moreover, I have several examples where the non-hierarchical model fits the data better than the hierarchical model (e.g., in terms of RMSE).  Also, a general-purpose statistical package that I have doesn’t require hierarchy by default.”


From Stat-Ease Consultant Wayne Adams:
“To convert between coded and actual models, hierarchy must be supported.  Otherwise the coded model provides a different prediction than the actual model.

Furthermore, second-order models that lack linear terms, for example Y=f(B, AB), may lead unsophisticated users to conclude, incorrectly, that the missing factor (A in this example) had no effect.  Even though a factor (A) does not produce a significant main effect in a case like this, it is involved in one (or perhaps more) significant interactions.  Thus, that factor does create an effect, but it depends on the settings of the factors with which it interacts.

While there are circumstances where a better RMSE result can be obtained by using a reduced model, the general conclusion will be the same with maintenance of hierarchy.  Nevertheless, advanced users such as you should feel free to click “No” to hierarchy if the particular circumstance warrants doing so.”

(Learn more about modeling by attending the two-day computer-intensive workshop Response Surface Methods for Process Optimization.  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: Webinar alert: How to Get Started with Design-Expert® Software

On Wednesday, February 20, at 8 AM CST* Stat-Ease Consultant Shari Kraber will detail How to Get Started with Design-Expert® Software in a free webinar geared toward novices.  Her presentation will demonstrate how to plan, design and analyze a powerful multifactor test. She will also provide a ‘heads-up’ on mistakes made by unsuspecting beginners that lead to DOE failures. The goal of this webinar is to set you up for success using Stat-Ease software for your experiments!

Shari will reprise this webinar on Wednesday, March 20 at 12 PM (noon).  There will be a final encore at 9 PM USA-CST on Monday, March 25—this time particularly for those on other side of the globe (India, AustralAsia, Far East) from our headquarters in Minneapolis, Minnesota, USA.
Space is limited.  Reserve your Webinar seat now at by clicking one of the links below:

  1. February 20 (8 AM CST) session
  2. March 20 (12 PM Noon CST) session
  3. March 25 (9 PM CST) session

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.

Again, attendance may be limited, so sign up soon via the link above.  Direct any questions you may have to our Communications Specialist, Karen Dulski, via  However, if this relates to audiovisual issues, please first research help provided online by 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.)

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5: Events alert: Appearances in New Orleans, Charlotte and our home area (Minnesota)

If you will be going to the upcoming American Statistical Association Conference on Statistical Practice starting February 21 in New Orleans, please stop by the Stat-Ease exhibit and see me.  Let’s talk up DOE!

Wayne Adams will travel to Charlotte, NC on February 25 to take the point for Stat-Ease at the Annual National Test & Evaluation (T&E) Conference sponsored by the National Defense Industrial Association (NDIA).  He will be flying our flag at a tabletop exhibit and speak on “Comparing Worst Case Scenarios to the Operational Envelope Using Factorial Designs.”  To see when he will talk and what else is on the agenda for this conference, click here.

Stat-Ease Consultant Brooks Henderson (replacing Shari Kraber) will lay out “Quality by Design (QbD) for Everyone” at the Minnesota ASQ Professional Development Summit in Brooklyn Center on February 26.  See the conference website here.  Please stop by the Stat-Ease booth if you get the chance.

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.

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6: Workshop alert: Classes in California coming soon—take advantage!

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 to earn $395 off the combined tuition!

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

*** 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—Trying to get the jump on Wall Street in 2013—words of wariness:

Our brains are wired for narrative, not statistical uncertainty.  And so we tell ourselves simple stories to explain complex things we don't--and, most importantly, can't--know.  The truth is that we have no idea why stock markets go up or down on any given day, and whatever reason we give is sure to be grossly simplified, if not flat out wrong.”

Chris Anderson, editor-in-chief of Wired magazine, commenting on Nassim Nicholas Taleb exploration of randomness in his book The Black Swan.

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!

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DOE FAQ Alert ©2013 Stat-Ease, Inc.
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