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Dear Experimenter, To open another avenue of communication with fellow DOE and Stat-Ease fans, sign up for The Stat-Ease Professional Network on LinkedIn. A recent posting features: Guide for a Beginner. Please weigh in with your opinions on this topic!
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Topics in the body text of this DOE FAQ Alert are headlined below (the "Expert" ones, if any, delve into statistical details):
| 1: | FAQ: How to change which factors get plotted on a 3D model graph | ||
| 2: | FAQ: Is it really necessary to use coded equations for predictive modeling? | ||
| 3: | Info alert: Video demonstrates how to select effects from the improved half-normal plot in version 10 of Design-Expert® software (DX10) | ||
| 4: | Events alert: “The Extraordinary Power of Designed Experiments” | ||
| 5: | Workshop alert: See when and where to learn about DOE | ||
P.S. Quote for the month: A straight-on pitch for improving your odds for success. (Page down to the end of this e-zine to enjoy the actual quote.)
1: FAQ: How to change which factors get plotted on a 3D model graph
Original question from a Quality Manager:
“How do I change which two factors show up in the 3D plot?”
“There is a Factors Tool on the screen. Right-click on any factor shown on the tool and you can select an axis from the list as shown in the screen shot below.”
Screen shot illustrating how a right click on the factors tool brings up the option to select it for an axis
(Learn more about 3D graphs 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.)
2: FAQ: Is it really necessary to use coded equations for predictive modeling?
Original question from a Chemical Research Engineer:
“I have a question on using the models for prediction. We did DOE the way you taught us in your workshop at Edison, NJ—collected the data and fit a model that predicts the effect of factors on the response. However, we get two equations that work in terms of coded versus actual factors. Before learning about DOE we always used models that worked with actual factor levels. Should we be using the coded one? If so, then we need to convert the factors from actual to coded. That complicates things. Therefore, it is very tempting to simply just plug in the actual data into the model in actual factor levels. Your thoughts?”
“It’s much easier to use the equation in terms of actual factors since you can just plug in the values used in your experiment. If your model is hierarchical, then both equations will give you identical predictions. Be sure to use the Point Prediction node in the software if you want to be able to get predicted values quickly at various locations in your design space. In general, we recommend using model graphs and numerical optimization rather than trying to play around with the equations, but if you need to use an equation, feel free to go with the equation in actual factors.”
P.S. You will see in the answer to FAQ 1 posted in the DOE FAQ Alert v9, n5 (May 2009) posted here, a similar view from Stat-Ease Consultant Shari Kraber—her also favoring the actual equation for ease of use by engineers. However, Shari points out the advantages of coded equations for interpretation of coefficients. Check this out for a more complete picture of the pros and cons of the two types of predictive equations presented by Stat-Ease software. —Mark
(Learn more about factor coding 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.)
3: Info alert: Video demonstrates how to select effects from the improved half-normal plot in version 10 of Design-Expert software (DX10)
Stat-Ease Consultant Brooks Henderson posted this video showing how to select effects in DX10. As you will see, this is now easier than ever before with the advent of a new feature that positions the reference line more intelligently.
4: Events alert: “The Extraordinary Power of Designed Experiments”
Stat-Ease Consultant Pat Whitcomb will participate in a panel discussion of “The Extraordinary Power of Designed Experiments” at the 2016 Joint Statistical Meetings (JSM) in Chicago, Illinois, July 30 - August 4. Register for this conference here. If you make it, please stop by booth 207 to see the latest that Stat-Ease has to offer for the tools of DOE.
Those of you on the other side of the Atlantic can catch up with Pat at ENBIS 16 in Sheffield, UK, September 11-15. See him at the Stat-Ease exhibit there and attend his talk on “A Synergistic Blend of Multivariate Analysis Methods with Design of Experiments Tools.”
Back in the USA in Minneapolis, the home of Stat-Ease, see a number of our staff at SCIX, where one of our Consultants will co-teach a one-day workshop on Introduction to DOE and Chemometrics with CAMO Software on Tuesday, September 20. I plan to give a talk on quality by design (QbD) on “Managing Uncertainty in Design Space” and spend some time at booth 100 organized by CAMO, where we will be displaying our programs; Unscrambler X and Design-Expert; respectively. Register for the SCIX conference here.
Click here for these and other upcoming appearances by Stat-Ease professionals.
P.S. 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.
5: Workshop alert: See when and where to learn about DOE
You can do no better for quickly advancing your DOE skills than attending a Stat-Ease workshop. In these intensive classes, our expert instructors provide you with a lively and extremely informative series of lectures interspersed by valuable hands-on exercises with one-on-one coaching. Enroll at least 6 weeks prior to the date so your place can be assured—plus get a 10% “early-bird” discount. Also, take advantage of a $400 discount when you take two complementary workshops that are offered on consecutive days.
- Experiment Design Made Easy (EDME)
- August 10-11, New Jersey
- September 20-21, Minneapolis*
- Response Surface Methods for Process Optimization (RSM)
- September 22-23, Minneapolis*
* Take both EDME and RSM to earn $400 off the combined tuition!
- Mixture and Combined Designs for Optimal Formulations (MIXC)
- July 19-21, Minneapolis
See this web page for complete schedule and site information on all Stat-Ease workshops open to the public. To enroll, scroll down to the workshop of your choice and click on it, or contact the Client Specialist, Rachel, at workshops@statease.com or 612-746-2030. 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 workshops@statease.com.
I hope you learned something from this issue. Address your general questions and comments to me at: mark@statease.com.
Please do not send me requests to subscribe or unsubscribe—follow the instructions at the end of this message.
Sincerely,
Mark
Mark J. Anderson, PE, CQE
Principal, Stat-Ease, Inc.
2021 East Hennepin Avenue, Suite 480
Minneapolis, Minnesota 55413 USA
P.S. Quote for the month—What works for baseball serves for experimenters:
"Luck is the residue of design.”
—Branch Rickey, the baseball executive who signed on Jackie Robinson to break major league baseball’s color barrier.
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, Brooks Henderson and Martin Bezener
—Statistical advisor to Stat-Ease: Dr. Gary Oehlert
—Stat-Ease programmers led by Neal Vaughn
—Heidi Hansel Wolfe, Stat-Ease sales and marketing director,
and all the remaining staff that provide such supreme support!
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