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, please click on the links at the bottom of this page. If you have a question that needs answering, click the Search tab and enter the key words. This finds not only answers from previous Alerts, but also other documents posted to the Stat-Ease web 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:StatHelp@StatEase.com.
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 on down):
1. Newsletter Alert: December issue of the Stat-Teaser details DOE for sales and marketing, plus power from factorial designs
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/news0712.pdf. It features an article by me titled "A Crash Course on DOE for Sales and Marketing," which details a workshop developed by Paul Selden, author of "Sales Process Engineering" (ASQ Quality Press).* This issue of the Stat-Teaser also provides part 2 of a primer on power titled "When Power is Too Low in Factorial Designs." It demonstrates a design which lacks sufficient power and discusses how it should be dealt with. 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. Also, it would be great (in my opinion!) if you forward the link from my DOE FAQ Alert, especially for this issue, which should be of particular interest to your sales and marketing colleagues.
*(For a complete description of "A Crash Course on DOE for Sales and Marketing" contact me directly at email@example.com.)
2. FAQ: Problems analyzing a two-by-two factorial design
>Diagnostic graphs cannot be created because the model is over specified. All degrees of freedom are in the model and none are assigned to the residual (error). Also the ANOVA had no calculated p-values because without residual error there is nothing to test against. To fix the problem, return to the Effects or Model button and assign at least one term to error.<
However, this did not stop me — I proceeded to [Model Graphs] and got a nice interaction plot, only it was missing the handy least-significant-difference (LSD) bars. What am I doing wrong?"
Answer (from Stat-Ease Consultant Wayne Adams):
>If only two factors are tested, the two main effects can be estimated and tested statistically. However, if the interaction is also estimated, that leaves no room for error. Thus none of the three effects can be tested. We recommend replicating this experiment to provide estimation of pure error. Then the interaction and error can both be estimated and all effects tested statistically.<
Two-factor experiments need to have some extra runs in order to produce a meaningful ANOVA. This applies no matter how many levels the factors have. For example, a three-by-three design, such as three suppliers that each provide three types of material, would be just as troublesome for statistical analysis. Replication is a good way to get these extra runs. Once the experiment has three factors, the extra runs are not necessary (but replication is still a good idea)."
To recap, the user from Chicago ran only the four combinations, unreplicated, of two factors each at two levels. This design can estimate the overall mean, the two main effects and the two-factor interaction (2FI). The 2FI created the biggest effect so the user picked it. However, hierarchy is advised for polynomial modeling, as discussed in prior DOE FAQ Alerts (for example see #3 at http://www.statease.com/news/faqalert3-4.html). This puts the two main effects into the model for support of the 2FI. But that leaves no estimate of error. (In other words, all three effects can be estimated but not the error.) Things go downhill from there for the statistical analysis and diagnostics. Luckily the user realized something must not be right about the interaction graph, because it showed no LSD bars. I suppose one might say this was a comedy of no error.
(Learn more about design and analysis of two-level factorials 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.)
3. Webinar Alert: 10 Ways to Mess Up an Experiment & 8 Ways to Clean It Up
You are invited to attend a free web conference by Stat-Ease on "10 Ways to Mess Up an Experiment & 8 Ways to Clean It Up" at 8 AM Central USA Time on Tuesday, February 5 and again at 11 AM Wednesday, February 6. I plan to present this talk and keep it relatively basic. It is intended for actual experimenters and applied statisticians who are looking for practical advice. The presentation will be based on contributions from my colleague Shari Kraber and independent consultant Jeff Hybarger. Attendance may be limited for one or both of these two one-hour webinar sessions. Contact our Communications Specialist, Karen Dulski, via firstname.lastname@example.org 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.
4. Reader Response: Advantages of actual replication
From: Matthew L. Barrows, Process Engineering Manufacturing Technologist and Six Sigma Master Black Belt, Monsanto, Luling, Louisiana
Response (from Matthew):
5. Reader Contribution: Designed experiment solves welding problem
From: David W. Gore, P.E., Associate Professor, Middle Tennessee State University
See the article on "University And Industry Collaboration to Solve Welding Quality Problem Using Design Of Experiments (DOE)" at http://www.statease.com/pubs/CIEC_paper_Gore&Langston.pdf and illustrations at http://www.statease.com/pubs/MTSUposterdoe.pdf.
6. Events alert: Lean Six Sigma Conference, European DOE User Meeting
At the 2008 ASQ Lean Six Sigma Conference, held February 11-12 in Phoenix, Stat-Ease Consultant Pat Whitcomb will explain "How to Plan and Analyze a Verification DOE." Conference details are posted at http://www.asq.org/conferences/six-sigma/index.html. Stat-Ease will offer an exhibit. Pat's talk, which garnered an "extremely overwhelming" positive review, is described at http://www.asq.org/conferences/six-sigma/program/session-g4.html. The Second European DOE User Meeting will be held March 10-12 in Berlin, 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 when it is available, send an e-mail to Heidi Hansel via email@example.com.
Click http://www.statease.com/events.html for a list of upcoming appearances by Stat-Ease professionals. We hope to see you sometime in the near future!
7. Workshop Alert: See when and where to learn about DOE
Seats are filling fast for the following DOE classes:
—> Experiment Design Made Easy (EDME)
—> Mixture Design for Optimal Formulations (MIX)
—> Response Surface Methods for Process Optimization (RSM)
—> DOE for DFSS: Variation by Design (DDFSS)
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 firstname.lastname@example.org.
I hope you learned something from this issue. Address your general questions and comments to me at: Mark@StatEase.com.
Mark J. Anderson, PE, CQE
PS. Quotes for the month—See the light :
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