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Issue:
Volume 8, Number 4
Date:
April 2008
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 http://www.statease.com/doealertreg.html. If this newsletter prompts you to ask your own questions about DOE, please address them via mail to:[email protected].
For an assortment of appetizers to get this Alert off to a good
start, see these new blogs at http://statsmadeeasy.net (beginning with the most recent one):
—Box seminar from 1996 remains visionary
—Thomas Edison & Henry Ford would've loved the new hybrid cars
—How to explain a statistical interval confidently
—Random thoughts on taxing calculations
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: March issue of the Stat-Teaser brings back a classic DOE on microwave popcorn done as a science project
2. FAQ: How is it that a design with center points can show curvature but not have significant lack of fit?
3. New Domain: StatEase.biz features DOE for sales & marketing
4. Webinar Alert: The difference between repeats and replicates
5. Reader Response: Enlightening elaboration on combining components by expert (and author) on mixture design
6. Events alert: ASQ World Conference on Quality & Improvement
7. Workshop alert: See when and where to learn about DOE
PS. Quote for the month: a very smart comment (sarcastic?) by Irish playwright George Bernard Shaw. (Page
through to the end of this e-mail to enjoy the actual quote.)
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1. Newsletter Alert: March issue of the Stat-Teaser brings back a classic DOE on microwave popcorn done as a science project
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 September issue at http://www.statease.com/news/news0803.pdf. It features an article by me titled "Popcorn Experiment Remains Fresh for Featuring Factorial Screening," backed up by how a "Follow-Up Study Reveals More Secrets for Making Popcorn." Thank you for reading the Stat-Teaser newsletter. If you do 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. However, we do appreciate you passing around hard copies of the Stat-Teaser, so do not feel obliged to forego this.
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2. FAQ: How is it that a design with center points can show curvature but not have significant lack of fit?
-----Original Message-----
From: Minnesota
"How is it that a design with center points can show curvature but not have significant lack of fit?
Answer:
By default when analyzing results from two-level factorials we separate out the curvature effect from that caused by lack of fit (LOF). In an example from our "Experiment Design Made Easy" workshop, the analysis by Design-Expert® software reveals significant curvature (p<0.001) with insignificant LOF (p>0.7).
However, if you go back to the Effects List (offered on the floating tool for Effects) and double-click Curvature to take it out of the model, then the LOF becomes much more significant (p<0.1). It turns out that the factorial model fits the outer points of the design (a cube in this case of three factors), but it falls significantly below the center points, as one sees immediately in the 3D view of the surface with actual points projected (I call this the 'lollipop' graph!). For more details on center points and curvature, refer to FAQ #2 in the April 2005 DOE FAQ Alert posted at http://www.statease.com/news/faqalert5-4.html.
(Learn more about curvature by attending the three-day computer-intensive workshop "Experiment Design Made Easy." See http://www.statease.com/clas_edme.html for a description of this class and then link from this page to the course outline and schedule. Then, if you like, enroll online.)
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3. New Domain: StatEase.biz features DOE for sales & marketing
If you are a sales or marketing professional, or you have colleagues who work in this vital business field, click through to this new Stat-Ease domain: http://www.StatEase.biz. It details "A Crash Course on DOE for Sales and Marketing" — a workshop developed by Paul Selden, author of "Sales Process Engineering" (ASQ Quality Press). The use of multifactor experiment designs remains underutilized in this arena, thus vital interactions of sales and marketing variables await discovery by those who adopt these statistical methods.
Those of you technical professionals who know the value of DOE for process development can refer your business colleagues to this site for a heads-up on these highly efficient and wonderfully effective methods for experimentation. We would appreciate this, but more importantly, it will ultimately put money in your pocket due to increasing sales and profits.
"He who has a product to sell and goes and whispers in a well is not so apt to get the dollars as one who climbs up a tree and hollers."
— Author unknown
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4. Webinar alert: The difference between repeats and replicates
You are invited to attend a free web conference by Stat-Ease on "The difference between repeats and replicates in DOE" at 8 AM in the Central USA Time Zone on Tuesday, May 13. It will be presented again at 12 PM (noon) on Wednesday, May 14. Watch for more details from the talk's author, Consultant Wayne Adams,* to be posted at this Stat-Ease webinar page,which includes postings from prior presentations: http://www.statease.com/webinar.html.
When developing these educational sessions, our presenters often draw valuable material from Stat-Ease DOE workshops. Attendance may be limited for one or both of these two one-hour webinar sessions. Contact our Communications Specialist, Karen, via [email protected] to sign up. If you can be
accommodated, she will send you the link for the WebConnect and dial-in for ConferenceNow voice via telephone. Toll-free access extends worldwide, but not to all countries.
*For a ‘heads-up’ on this tricky issue, consider the advice from consultant Pat Whitcomb for FAQ #1 in the November, 2004 DOE FAQ Alert:
"Another question might be can I repeat the measurement rather than replicate the DOE run? The answer is yes, but in this case you enter the average of the repeated measures, not the individual results. Independent measurements will reduce the measurement system component of the total process variation... Only with knowledge of the variance components and the costs of replicating the DOE run and/or repeating the measure can one decide which is the best option."
(See http://www.statease.com/news/faqalert4-11.html for Pat's complete answer, included a sample calculation on variance components. Wayne's webinar will address this and much more.)
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5. Reader Response: Enlightening elaboration on combining components by expert (and author) on mixture design
-----Original Comment-----
From: Wendell Smith, author of "Experimental Design for Formulation" (detailed and made available for e-commerce purchase at http://www.statease.com/prodbook.html)
"Regarding your FAQ #3 in the March DOE FAQ Alert, I totally agree with you that combining components only on the basis of their similar effects might be an oversimplification. It seems to me that the answer to the questioner's inquiry is that if two components have similar gradients in an effects direction of interest, then one might consider combining them after due consideration of subject-matter knowledge. Deciding whether two components have similar gradients on the basis of similar coefficients would probably work most of the time, but not necessarily all the time.
Two components could have different coefficients but similar gradients depending upon the effects direction of interest (orthogonal, Cox, or Piepel) and the center of interest. As an example, consider the model Y-hat=10A + 20B + 80C for a three-component mixture, with a center of interest s={0.2,0.6,0.2}. If one inputs this as a simulation model in Design-Expert and compares the gradients in the Cox-effects directions through the center of interest 's,' one can see graphically that the gradients for A and B are identical although the coefficients are quite different.
On the other hand, if the model were Y-hat=10A + 10B + 80C with the same center of interest 's,' then now the gradient in the Cox-effect direction of B is twice that of A in its Cox-effect direction, and one would probably not want to combine them. (If the center of interest were s={1/3,1/3,1/3}, then the gradients in the Cox-effects directions (now equivalent to the orthogonal-effects direction) would be the same).
It is also well to keep in mind that two components could have similar effects (again, depending upon how "effect" is defined) for entirely different reasons. The range for one component might be large but the gradient small, while the range for another component might be small but the gradient large."
(Learn more about mixture design by attending the three-day computer-intensive workshop "Mixture Design for Optimal Formulations." For a complete description of this class, see http://www.statease.com/clas_mix.html. Link from this page to the course outline and schedule. Then, if you like, enroll online.)
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6. Events alert: ASQ World Conference on Quality & Improvement
See the Stat-Ease exhibit in Booth 319 at the 2008 World Conference on Quality & Improvement (WCQI) of the American Society of Quality (ASQ) in Houston, Texas, on May 5-7. Details on this event can be found at http://wcqi.asq.org/. On Monday night that week, the Chemical and Process Industries Division (CPID) offers an open meeting that will feature talks of a more technical nature than those generally given at WCQI. One will be by given me on how to "Reduce Variation via Response Surface Methods." Contact me via [email protected] for more information.
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7. 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!
—> Experiment Design Made Easy (EDME)
(Detailed at http://www.statease.com/clas_edme.html)
> April 29 - May 1 (Minneapolis, MN)
—> Mixture Design for Optimal Formulations (MIX)
(http://www.statease.com/clas_mix.html)
> June 10-12 (Minneapolis)
—> Response Surface Methods for Process Optimization (RSM)
(http://www.statease.com/clas_rsm.html)
> September 23-25 (Minneapolis)
—> DOE for DFSS: Variation by Design (DDFSS)
(http://www.statease.com/clas_ddfss.html)
> November 11-12 (Minneapolis)
See http://www.statease.com/clas_pub.html 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 [email protected].
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I hope you learned something from this
issue. Address your general questions and comments to me at: [email protected].
Sincerely,
Mark
Mark J. Anderson, PE, CQE
Principal, Stat-Ease, Inc. (http://www.statease.com)
2021 East Hennepin Avenue, Suite 480
Minneapolis, Minnesota 55413 USA
PS. Quote for the month—a very smart comment (sarcastic?) by Irish playwright George Bernard Shaw:
"It is the mark of a truly intelligent person to be moved by statistics."
— George Bernard Shaw
PPS. The old-fashioned alternative to DOE is often referred to as
OFAT, or one factor at a time. However, I recently came across
another acronym for this: COST, or changing only a single thing.
—MJA
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 http://www.statease.com/consult.html
for resumes)
—Statistical advisor to Stat-Ease: Dr. Gary Oehlert (http://www.statease.com/garyoehl.html)
—Stat-Ease programmers, especially Tryg Helseth and Neal Vaughn
(http://www.statease.com/pgmstaff.html)
—Heidi Hansel, Stat-Ease marketing director, and all the remaining
staff
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