Stat-Ease | The DOE FAQ Alert Vol. 12 No. 6

PS. Quote for the month: The key to science provided by one of the top physicists of all time.
(Page down to the end of this e-zine to enjoy the actual quote.)

From a Manufacturing Engineer:
“I have a question about confidence intervals (CI) versus prediction intervals (PI). I have looked at the book and the online forum. I'm still confused. I had thought that the CI was used for the averages of any future observations, so the mean of future observations would land within the CI. I was also thinking that only a single, individual future observation would fall within the PI, so single observations would land within the PI. Is this accurate? The book makes it seem as though only the PI is used for future observations.”

“You are not alone in your troubles understanding what a CI versus PI really mean.

P.S. from Mark: For further details, see this two-part series by Stephen N. Luko and Dean V. Neubauer for ASTM Standardization News on confidence intervals versus prediction intervals. Also, learn how Design-Expert® software generates appropriate prediction intervals by following this link to FAQ 4 in the Sep/Oct'11 DOE FAQ Alert, which tells users “what to make of multiple confirmation runs.”

2: FAQ: How to interpret big day-by-day differences blocked out in the experiment design

From a Six Sigma Master Black Belt:
“Someone brought results from their DOE to me to analyze. The lab equipment requires set up each day, so they blocked the runs accordingly. It turned out that day-to-day differences were big, which leads to these two questions:

“Those are exactly the things we teach in our class to determine whether the blocking was ‘significant' or not. You are right in making your comparisons. We don’t print an F-value because one of the ANOVA assumptions is that the residuals are randomly distributed. By restricting the randomization in blocking, that assumption is invalid. However, it doesn’t stop us from using it as a rule of thumb. We usually say that if you divide the Block mean square by the residual mean square and the ratio is 4 to 1 or higher, then the block effect was sizeable.”

3: Webinar alert: Learn some tricks of the trade from Real-life DOE—Encore for India and AustralAsia

On Monday, December 3 at 9 PM USA-CST* I will reveal some tricks of our trade for Real-Life DOE to our friends on the other side of the globe. If you are just beginning with factorial screening and characterization experiments, this webinar is for you! More advanced practitioners might also glean an “aha!” as well, and/or follow up afterward with suggestions that I can share via the DOE FAQ Alert.

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 karen@statease.com. 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.)

4: Events alert: Look forward to the 2013 schedule of Stat-Ease talks and exhibits

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

5: Workshop alert: Get a Stat-Ease workshop on your 2013 training budget: Tool up!

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 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 workshops@statease.com.

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@statease.com.

Sincerely,

PS. Quote for the month—The key to science provided by one of the top physicists of all time:

"
If it disagrees with experiment, it’s wrong. And that simple statement is the key to science. It doesn’t make a difference how beautiful your guess is, it doesn’t matter how smart you are, who made the guess, or what his name is. If it disagrees with experiment, it’s wrong. That’s all there is to it."

—Richard Feynman

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!