Minitab Inc.

A certified Six Sigma Black Belt, Karen's approach to training derives from her extensive industry experience and her background in academic instruction. She has trained thousands of technical employees including Six Sigma Master Black Belts, Black Belts, and Green Belts, at large and small companies throughout the United States. The breadth of her own experiences as a quality professional, combined with over 20 years teaching experience and an in-depth understanding of mathematics and statistics, make her an excellent trainer. Her classes develop proficiency in the use of Minitab Statistical Software and an understanding of the statistical concepts and tools essential to the success of quality improvement initiatives like Six Sigma. Participants in Karen's training programs learn from a real-world expert how to use Minitab for quality improvement in the manufacturing and service industries, including the proper application of statistical quality techniques like Gage R&R and Capability Analysis. She has extensive consulting and training experience in Experimental Design and Taguchi Robust Design methodologies. Karen has worked as a statistical trainer, consultant and technical writer for a variety of companies, including the DaimlerChrysler Quality Institute, Hollingsworth & Vose, the Ford Design Institute, and MSX International. She has conducted training for Minitab Inc. since 2000. She has taught mathematics and statistics at the university level for the General Motors Technical Education Program, Wayne State University, and Oakland University. Karen has a B.S. in Applied Mathematics, an M.S. in Applied Statistics and an M.S. in Mathematics, all from Oakland University. She also completed graduate study in Pure Mathematics at Wayne State University. Karen is available on a contract basis to provide Minitab training.

Kurt brings to his work as a Minitab Trainer both a wide range of experience and an appreciation for the many fields in which statistics can be applied. He began his career as a Research Statistician for the Center for Disease Control (CDC), where he provided researchers with experimental designs and analyses for genetic experiments and other biological projects. While working for the CDC, he also gained experience in statistical software development. He then began working in the manufacturing industry as a Statistician for the Kellogg Company in Battle Creek, Michigan, where he became an expert in statistical process control and used it to develop standard operating procedures for setting specifications. He also strengthened Kellogg's research and development culture by establishing a more statistically robust procedure for product improvement.

Luis has more than seven years of experience applying statistics to improve the quality of consumer products at global companies such as Colgate-Palmolive, Unilever Research, and PepsiCo. He has designed and analyzed experiments in a variety of product categories and worked in many areas, including clinical research, fabric development, product development, product claims development, and consumer/sensory sciences. As a multi-lingual statistician (English, Spanish, and Portuguese), Luis has helped international laboratories implement experimental designs and statistical methods of analyses. He has also taught scientists, engineers, and clinicians how to design and analyze their own experiments and studies, and established corporate statistical guidelines for product claims.

Scott Kowalski is a Technical Training Specialist at Minitab Inc. His main role is teaching statistics with MINITAB to corporations in the United States, Canada and Mexico. Scott is also involved in software development at Minitab Inc. Before joining Minitab Inc., he worked for two years in academics: one year for Stetson University and one year for the University of Central Florida, where, in addition to teaching, he was the Associate Director of the Statistics Institute. Scott received his B.S., M.S. and Ph.D. in Statistics from the University of Florida. His concentration was on design of experiments and response surface methodology. His dissertation and continued research focuses on designing industrial experiments with hard to change factors. Scott is a member of ASQ and the American Statistical Association. In addition, he is on the Editorial Review Board for the Journal of Quality Technology.