Time: July 8, 2013 to July 12, 2013
Location: MIT Campus
Street: 77 Mass Ave
Website or Map: http://web.mit.edu/profession…
Event Type: short, course, experiment, design, analyzing, experimental, data
Organized By: MIT Professional Education
Latest Activity: May 13, 2013
This one-week program is planned for persons interested in the design, conduct and analysis of experiments in the physical, chemical, biological, medical, social, psychological, economic, engineering or industrial sciences. The course will examine how to design experiments, carry them out, and analyze the data they yield.
Various designs are discussed and their respective differences, advantages, and disadvantages are noted. In particular, factorial and fractional factorial designs are discussed in greater detail. These are designs in which two or more factors are varied simultaneously; the experimenter wishes to study not only the effect of each factor, but also how the effect of one factor changes as the levels of other factors change. The latter is generally referred to as an interaction effect among factors.
The fractional factorial design has been chosen for extra-detailed study in view of its considerable record of success over the last thirty years. It has been found to allow cost reduction, increase efficiency of experimentation, and often reveal the essential nature of a process. In addition, it is readily understood by those who are conducting the experiments, as well as those to whom the results are reported.
The program will be elementary in terms of mathematics. The course includes a review of the modest probability and statistics background necessary for conducting and analyzing scientific experimentation. With this background, we first discuss the logic of hypothesis testing and, in particular, the statistical techniques generally referred to as Analysis of Variance. A variety of software packages are illustrated, including Excel, SPSS, JMP, and other more specialized packages.
Throughout the program we emphasize applications, using real examples from the areas mentioned above, including such relatively new areas as experimentation in the social and economic sciences.
We discuss Taguchi methods and compare and contrast them with more traditional techniques. These methods, originating in Japan, have engendered significant interest in the United States.
Applicants need only have interest in experimentation. No previous training in probability and statistics is required, but any experience in these areas will be useful.
All participants receive a copy of the text, Experimental Design: with applications in management, engineering and the sciences, Duxbury Press, 2002, co-authored by Paul D. Berger and Robert E. Maurer, in addition to extensive PowerPoint-style notes.