Experimental Design

Dr. Paul D. Berger has been teaching Experimental Design at the Massachusetts Institute of Technology for over 40 years and continues to do so. He had an academic appointment for 37 years at Boston University and has had an academic appointment for the last 10 years at Bentley University. He is currently the Director of Bentley University’s Master of Science in Marketing Analytics (MSMA) program, in which he also teaches Experimental Design, as well as Marketing Research and Statistics. He is the author of over 200 peer-reviewed articles and conference proceedings, as well as six texts, his latest in 2015, co-authored with Michael Fritz, Improving the User Experience Through Practical Data Analytics. His research has been incorporated into Government-agency reports and presented at conferences worldwide. In 2015, he taught his Experimental Design class at a Deakin University in Melbourne, Australia. Professor Berger continues to provide consulting services in thearea of Experimental Design and Quantitative Methods/Statistics in general to numerous companies. His clients have included companies such as Duracell®, Gillette®, Texas Instruments, and many others; in addition, Professor Berger has provided consulting services internationally, including in China, Japan, India, and Argentina.Dr. Robert E. Maurer has more than 35 years of industrial experience at Bell Telephone Laboratories. For most of that period, in collaboration with the National Security Agency, he worked on protecting domestic radio and satellite communications, and ultimately led the development and deployment of the largest (in terms of the amount of traffic protected) communications-security system ever installed by anyone anywhere at the time. After that, he collaborated with Walter G. Deeley, the Deputy Director for Communications Security at NSA, to demonstrate the feasibility of a secure-voice terminal (STU 3) for classified point-to-point communications. Finally, he led the AT&T STU 3 development program. In his last assignment, he was responsible for process and product design and manufacture of a several-hundred-million-dollar product line of hybrid integrated circuits. Through his initiative and guidance, the disciplines of statistical process control and experimental design were deployed throughout his organization, leading to improved quality and reduced cost. Dr. Maurer has more than 35 years of experience teaching in the areas of statistical communication theory at the Graduate School of Engineering at Northeastern University and a variety of quantitative courses at the Questrom School of Management at Boston University. He has published numerous papers and hold patents in the communications and encryption areas. Dr. Maurer earned his Bachelor and Master of Science and Doctoral degrees in Electric Engineering from Northeastern University, and an MBA from Boston University.Dr. Giovana B. Celli is a consultant for Brazilian and Canadian companies and is currently a Postdoctoral Researcher at the Department of Food Science at Cornell University. She has been working as food technologist and researcher for over eight years, and has developed several products currently on the market. She has also mentored and co-advised several students and researchers on design of experiments and has served as an invited reviewer for various pharmaceutical and food-related journals. Dr. Celli earned her Bachelor degree in Pharmacy and Master degree in Food Technology from Universidade Federal do Paraná (Brazil) and Doctoral degree in Biological Engineering from Dalhousie University (Canada). She met Dr. Berger at the Professional Education course in Design and Analysis of Experiments, at MIT.

• 1. Introduction to experimental design.- 2. One-factor designs and the analysis of variance.- 3. Some further considerations on one-factor design and ANOVA.- 4. Multiple-comparison testing.- 5. Orthogonality, orthogonal decomposition, and their role in modern experimental design.- 6.- Two-factor cross-classification designs.- 7. Nested, or hierarchical, designs.- 8. Designs with three or more factors: Latin-square and related designs.- 9. Two-level factorial designs.- 10. Confounding/blocking in 2k designs.- 11. Two-level fractional-factorial designs.- 12. Designs with factors at three levels.- 13. Introduction to Taguchi methods.- 14. Simple regression.- 15. Multiple and step-wise regression.- 16. Introduction to Response-Surface Methodology.- 17. Introduction to mixture design and triangular surfaces.- 18. Literature on experimental design and discussion.