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Legend:  = Applied Session,
 = Theme Session,
 = Presenter
FRY = Fairmont Royal York, ICH = InterContinental Hotel, TCC = Metro Toronto Convention Center
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CE_12C
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Sun, 8/8/04, 8:15 AM - 4:15 PM
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FRY-British Columbia
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Methods for Designing and Analyzing Mixture Experiments (1 Day Course) - Continuing Education - Course
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ASA, Section on Physical and Engineering Sciences
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Instructor(s): Greg F. Piepel, Battelle/Pacific Northwest National Laboratory, John A. Cornell, University of Florida
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Mixture experiments involve changing the proportions of product components and observing the changes in the product's characteristics. Mixture component proportions cannot be varied independently (as in factorial experiments) because they must sum to 1.0 for each run in the experiment. Mixture experiments are very useful in many product development areas, including foods, materials, fertilizers, textile fibers, drugs, and many others.
The short course will provide an overview of methods used in designing mixture experiments and analyzing the resulting data. Topics to be covered include: (1) designs for simplex-shaped and irregular-shaped regions (the latter resulting from additional constraints on the component proportions), (2) various types of mixture models for fitting mixture data, (3) graphical techniques for interpreting component effects, (4) including process variables and/or a total amount variable in mixture experiments, and (5) graphical and analytic methods for developing mixtures with optimum properties. Numerous examples will be used to illustrate the topics discussed.
The course is designed for anyone (statistician or non-statistician) wanting to know about statistical methods for designing mixture experiments and analyzing the resulting data. Prerequisites are an understanding of elementary statistics concepts and some previous exposure to experimental design and least squares regression.
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