| ESI6247 Statistical Design Models | |
|
Hui Yang Industrial and Management Systems Engineering University of South Florida |
|
|
Textbook: “Experiments: Planning, Analysis and Parameter Design Optimization” (by C.F. Jeff Wu and Michael S. Hamada), second edition, 2009, John Wiley. |
|
|
Course Objectives: To be able to plan an experiment in such a way that the statistical analysis results in valid and objective conclusions. To learn a variety of experimental designs and be able to choose an optimal design for a specific experiment. To be able to perform the proper statistical analysis and draw valid conclusions from a specific experiment. |
|
|
Topics: |
|
|
|
Basic principles and introduction to regression analysis |
|
|
Experiments with a single factor, analysis of variance |
|
|
Experiments with more than one factor, blocking, Latin squares, analysis of variance and covariance, random effects models, other analysis techniques |
|
|
Factorial experiments at two levels, comparison with “one-factor-at-a-time” plans, analysis of location and dispersion, choice of optimal blocking schemes |
|
|
Fractional factorial experiments at two levels, maximum resolution and minimum aberration for choosing optimal designs, choice of optimal blocking schemes |
|
|
Response surface methodology for process optimization and improvement, steepest descent, Newton's method, conjugate gradient |
|
|
|
|
Matlab Tutorial |
|
|
http://www.mathworks.com/academia/student_center/tutorials/launchpad.html
http://www.math.ufl.edu/help/matlab-tutorial/
|
|
