Vol. 21, No. 5 - September/October 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:
Jeff Bezos’s views on experimentation—pro and con.

(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.
In a pickle: How to design a mixture experiment with only two microbials at a time

Original question from a Food Scientist:
“We have done our screening and have identified 5 antimicrobials that could work to extend the shelf-life of one of our products. We would like to run a mixture design to help us determine the best antimicrobial combinations and amounts in the product. When I set up the design, the software is formulating with a combination of all 5 antimicrobials. I wanted to know if there is a way or how I can write a constraint that will only design a maximum of two antimicrobials in the pickle at a time. The water amount will float to achieve 100% ingredients in the finished product.”

First off, if you can see your way clear to allowing all 5 antimicrobials (AMs) for experimental purposes only, you will be best off, IMO. This will provide a predictive model most expeditiously and solidly. Assuming you see two-component synergism and/or antagonism this will be evident by the two-letter terms in the coded model being significant with the signs being positive or negative; respectively. Then when you do the numeric optimization, systematically do what-ifs on two of the AM's at a time by setting all others equal to zero.

If you really must only put in two antimicrobials, do a combined design of three mixture components—AM1, AM2 and water, with the two AMs specified by the 10 possible combinations (5 take 2) laid out as a categorical factor.

(Learn more about combined designs by attending the next distance-learning or in-person presentation of Mixture Design for Optimal Formulations.)
2021 Online DOE Summit
The Stat-Ease 2021 Online DOE Summit will be presented September 28-29 from 10am to 2pm US Central Time. It features an impressive lineup of experts providing valuable briefings on cutting-edge statistical tools, methodology and inspiring case studies:
  • (Keynote Day 1) Martin Bezener (President & CTO, Stat-Ease): 
    Stat-Ease® 360 Widens the Horizon of Its World-Class DOE Software
  • Gregory Hutto (Wing Operations Analyst, US Air Force): 
    The Tooth Fairy in Experimental Design: White Lies We Tell Our Software
  • Drew Landman (Professor, Old Dominion University):
    An I-Optimal Split-Plot Design for eVTOL Tilt-Rotor Performance Characterization
  • Jason Pandolfo (Research Scientist, Quaker Chemical):
    Using Logistic Regression to Predict the Stability of Metalworking Fluid Emulsions in Varying Water Quality Conditions

  • (Keynote Day 2) Hank Anderson (VP Software Development, Stat-Ease):
    Python Integration with Stat-Ease 360 - A Tutorial
  • Oliver Thunich (Statistics Consultant, STATCON GmbH):
    Adjusting a DOE to Unpredictable Circumstances
  • Steven Mullen (Senior Scientist, Cook Medical):
    Improving Process Understanding of an IVF Cell Culture Incubator via Response Surface Methodology
  • Gregory Perrine (Research Scientist, Georgia-Pacific):
    Debonder Formulation Optimization Using a KCV Mixture/Process Design in Paper Handsheets
Free webinars—Sign up now to take Advantage
This coming October 13, I will present "Breakthrough DOE Tools for Elastomer Science and Technology". For a description and link to the free registration, follow this link.

On November 10, Martin Bezener will provide a briefing on space-filling designs and Gaussian-process modeling for deterministic computer experiments—new tools coming with the release of Stat-Ease 360. More details and a registration link for this enlightening talk will be posted soon to our Events/Webinars webpage.

Click here to view the times, descriptions and registration links for all upcoming live webinars. Sign up now to advance your DOE know-how!
Sharpen up on DOE—Enroll before classes fill

You can do no better for quickly advancing your DOE skills than attending a Stat-Ease workshop. Our expert instructors provide you with a lively and extremely informative series of lectures interspersed by valuable hands-on exercises. Enroll early to ensure your spot! See this web page for the complete schedule of upcoming Stat-Ease courses. To enroll in the workshop that suits you best, click Register on that webpage, or click here to contact us.
PS If you lead a group of 6 or more colleagues, save money and customize content via a private workshop. For a quote, please contact us
“Our success at Amazon is a function of how many experiments we do per year, per month, per week, per day. [However,] it's not an experiment if you know it's going to work.”
—Jeff Bezos
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