Vol. 21, No. 4 - July/August 2021
Dear Experimenter,

I am happy to share another answer or two from our statistical consulting team to frequently asked questions (FAQs) about design of experiments (DOE), as well as timely alerts for events, publications, and software updates. Check it out! Feel free to get back to me via mark@statease.com with further questions or comments: I would really appreciate hearing from you!

Please do not send me requests to subscribe or unsubscribe, follow the instructions at the end of this message.

Mark J. Anderson, PE, CQE
Engineering Consultant, Stat-Ease, Inc.

PS Quote for the day:

The secret to making breakthrough discoveries from a Nobel laureate.

(Page down to the end of this e-zine to enjoy the actual quote.)
StatsMadeEasy Blog
My wry look at all things statistical and/or scientific with an engineering perspective.
Factorial center points do little to increase power: Now what?

Original question from a PhD student of pharmaceutical technology:
“I would like to do an experiment with three factors at two levels with a signal-to-noise [S/N] ratio of 1.5, which only produces a power of 36.9%. However, even if I specify 6 center points to bring the total runs up to 14, the power increases only slightly to 48.3%. Is there something else I can do to improve the power?”

Answer from Stat-Ease Consultant Shari Kraber:
“Center points [CPs] do not help very much to increase the power to detect effects because they are in the middle of the design space with no leverage. A much better alternative will be to replicate the entire design from 8 runs to 16 runs. Then, if you want to check for curvature, add 3 or 4 center points.”

PS by Mark: I was curious to see the relative impacts of these options—easily assessed with Design-Expert® software’s built-in power-calculator.
  • Going with the 16-run option of the replicated 2^3 produces a power of 78.6% at 1.5 S/N—far more than the 48.3% the experimenter would have gained by investing runs in center points.
  • Adding 4 CPs to increase the total runs to 20 pushes the power to 80.4%—over the top of the 80% guideline. Furthermore, this design element provides a pathway for augmenting to a central-composite design for response-surface-method optimization.
However, I do have a further suggestion. When replication of a full factorial becomes necessary for power, consider adding another factor instead (in this case going to a 2^4): It will be essentially free. Who knows, perhaps that next most likely factor might lead to a breakthrough discovery. – Mark
(Learn more about power by attending the next distance-learning or in-person presentation of Modern DOE for Process Optimization.)
2021 Online DOE Summit
Register now to attend the Stat-Ease 2021 Online DOE Summit, presented September 28-29 from 10am to 2pm US Central Time. See our impressive lineup of experts and their intriguing topics. Register at no cost!
PS Do you need a speaker on DOE for a learning session within your company or professional society at regional, national, or international levels? If so, please get back to me. – Mark
Free webinarsSign up now to take advantage
Check out these highly educational presentations coming soon from our world-class DOE experts:
  • August 18—“The Difference Between Repeats and Replicates in DOE” by Pat Whitcomb
  • September 16—“New-User Intro to Design-Expert Software” by Richard Williams
Click here to view the times, descriptions and registration links for these upcoming live webinars. Sign up now to advance your DOE know-how!
Sharpen up on DOE—Enroll before classes fill

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“Discovery consists of seeing what everybody has seen and thinking what nobody has thought.”
—Albert von Szent-Gyorgyi, Nobel Prize winning biochemist
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