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Stat-Ease Webinars Stat-Ease is proud to offer free webinars to those interested in Design of Experiments (DOE). Presented on a regular basis, topics range from beginner to advanced levels. Material may be new or drawn from our ever-popular DOE workshops. See the list of upcoming and past webinars below. If you attended one of our presentations (or just wish you had) we invite you to download a copy of it for your review. Stat-Ease is your resource for all things DOE. If there is a particular subject you are interested in and don't see below, send us an e-mail and let us know. If there is enough interest, we may present your topic in a future webinar. Thank you for visiting Stat-Ease. We appreciate your interest! ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Upcoming Webinars “The difference between repeats and replicates in DOE” Basic to Intermediate Level In this presentation examples will be used to illustrate the differences between replicates, duplicates, and repeats, as well as the reasons for using each. Cost-based decision selection of one versus another will also be discussed. This is a practical presentation
with a dash of technical spice thrown in for flavor.
For a heads-up on this tricky issue, consider this advice from consultant Pat Whitcomb for FAQ #1 in the November, 2004 DOE FAQ Alert: "Another question might be can I repeat the measurement rather than replicate the DOE run? The answer is yes, but in this case you enter the average of the repeated measures, not the individual results. Independent measurements will reduce the measurement system component of the total process variation... Only with knowledge of the variance components and the costs of replicating the DOE run and/or repeating the measure can one decide which is the best option." (See http://www.statease.com/news/faqalert4-11.html for Pat's complete answer, including a sample calculation on variance components. Wayne's webinar will address this and much more.) Data files and PowerPoint presentaton can be downloaded as the WinZip archive: 08-May-Webinar.zip
The webinar is presented by Wayne Adams. Attendance may be limited for one or both of these two one-hour webinar sessions. Contact our Communications Specialist, Karen Dulski, to sign up. If space is available, she will send you the WebConnect link and telephone dial-in information for ConferenceNow. Click here to view instructions online (54 KB). Toll-free access extends worldwide, but not to all countries. Past Webinars "Multiple response optimization with Design-Expert" (4.91 MB) Intermediate Level The optimization module in Design-Expert searches for combinations of factor levels that simultaneously satisfy the requirements placed on each of the responses and factors. Discover how to get the most out of the optimization module in order to find the "sweet spot" for your product or an operating window for your process. Learn how to fine-tune your search by adding weights and importance settings to your basic criteria. A case study will be used to illustrate all of the features of Design-Expert's optimization module. "10 Ways to Mess Up an Experiment & 8 Ways to Clean It Up" (1.04 MB) Basic Level This basic presentation is intended for actual experimenters and applied statisticians who are looking for practical advice. It's all about design of experiments itself and how to do it more effectively. Mark says, "Here's how this presentation came about. After decades in the trenches, primarily working on injection-momlding process improvement, Stat-Ease's client, Jeff Hybarger, established his consultancy and wrote "'The Ten Most Common Designed Experiment Mistakes" as a white paper that documented his DOE 'chops.' Stat-Ease published the article in its Stat-Teaser newsletter. Design Product News picked it up in their June/July 2007 issue. The Fall Technical Conferecne of applied statisticians invited Jeff to talk about it. He bowed out due to scheduling conflicts so I edited and presented "The Ten Most Common Designed Experiment Mistakes." For this webinar I summarized these 10 ways to mess up an experiment and recapped 8 ways to clean them up. This latter part stems from a talk developed by Consultant Shari Kraber with my collaboration. It was originally presented under the title of the "8 keys to DOE."" "Sizing Mixture (RSM) Designs for Adequate Precision via Fraction of Design Space (FDS)" (1.04 MB) Advanced Level We begin with a review of power calculations to determine if a factorial design has enough runs to detect effects. Power, however, is not the appropriate tool to evaluate mixture and response surface designs. This presentation shows how to use the fraction of design space (FDS) tool (only in DX7.1+) to properly size these more powerful designs. The use of FDS is also dependent on the experimenter’s design objectives—precision, prediction, or detecting a change. All three objectives are discussed. "A Factorial Design Planning Process" (261 KB) Intermediate Level This talk outlines a four-step process for planning a factorial design. A substantial part of this process is to evaluate the power of the design, which is based on detecting a specific change in the response versus the process variation present in the system. Via a case study, this talk addresses the issue of replicating runs versus repeating the measurement to increase the power of the design.
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