Webinar: Problems/Opportunities Regressing Historical Data

Before embarking on expensive designed experiments for process improvement, it often pays to mine existing data via straightforward regression modeling. The output may be gold, or it might be ‘garbage in – garbage out’, but why not try? This webinar lays out problems that Lean Six Sigma professionals should be on guard against when trying to make something out of historical records. It provides case studies that cover the range from good-to-bad-to-ugly (but useful).

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Mark Anderson
Mark Anderson

About Mark J Anderson, PE, CQE, MBA

Mark is an Engineering Consultant at Stat-Ease, Inc. Prior to joining the firm, he spearheaded an award-winning quality improvement program for an international manufacturer, generating millions of dollars in profit. He offers a diverse array of experience in process development, quality assurance, marketing, purchasing, and general management. Mark is also the lead author of three books, DOE Simplified: Practical Tools for Effective Experimentation, 3rd Edition, RSM Simplified: Optimizing Processes Using Response Surface Methods for Design of Experiments, 2nd Edition, and Formulation Simplified: Finding the Sweet Spot through Design and Analysis of Experiments with Mixtures and has published numerous articles on design of experiments (DOE). He is also a guest lecturer at the University of MN Chemical Engineering & Materials Science department and the Ohio State University Fisher College of Business.

Professional Credentials:

  • Professional (Chemical) Engineer (PE), #015059 MN
  • Certified Quality Engineer (CQE), #20446

Education:
Bachelor of Chemical Engineering, University of Minnesota, 1975, High Distinction
MBA, University of Minnesota, 1980, Beta Gamma Sigma (honorary academic society)