DEPARTMENT OF STATIS TICS
COLLEGE OF ARTS & SCIENCES
330.972.6886 (TELEPHONE)
Course Description
3470:675
Response Surface Methodology
3 credits
Prerequisite: 3470:461/561 Applied Statistics and 3470:462/562 Applied Regression
and ANOVA or equivalent.
Course Description: First and second order response designs, efficient experimental
plans, methods for the analysis, and optimization of response functions.
Course Topics:
Regression models
Least squares estimation
Regression sums of squares and inferences
Lack of fit
First order surfaces
Two-level factorial designs
Fractional factorials
Simplex designs
Plackett-Burman designs
Steepest ascent
Second order models and surfaces
Locating the optimum response
Ridge analysis
Central composite designs
Box-Behnken designs
Small composite designs
Hybrid designs
Other designs for 2nd order models
Rotatability
Uniform precision
Orthogonality
Orthogonal blocking
Design optimality criteria
Mixture experiments and models
Simplex centroid designs
Simplex lattice designs
Extreme vertices designs
Designs with both mixture and process variables
Multiple response optimization
Use of statistical software for all of the above
Optimization project with report and presentation
Fall 2014