Department of Mathematics

1702.372 Statistical Design of Experiments II

Catalog Description

1702.372 Statistical Design of Experiments II                                                                                           3 s.h.

Prequisite: 1702.371 Statistical Design of Experiments II

Students will be exposed to advanced techniques and theories in statistical design of experiments. Applications from a wide variety of disciplines will be considered in detail. Students will learn the theoretical aspects of statistical design as well as the application of complex techniques to realistic situations. Optimization of experimental design techniques will also be covered.


Students will:
a) Use the material presented in Statistical Design of Experiments I to explore theoretical and practical aspects of statistical    design in more detail.
b) Learn complex statistical design techniques not covered in Statistical Design of Experiments I. these techniques are useful for complex or constrained experimental systems.
c) Make liberal use of computers.
d) Be exposed to a wide range of complex applications in areas including engineering, business and the physical and social sciences.
e) Objectives in relation to student outcome (con't)
f) Be required to write a paper on an application or theoretical aspect of their choice.

I.    Statistical techniques will be reviewed and introduced using the basics covered in Statistical Design of Experiments II. Design techniques for complex and constrained systems will be presented along with criteria for development of optimal techniques.

a) Advanced model building
b) Regression techniques
c) Analysis of variance in complex systems
d) Constrained systems
e) Complex response surfaces
f) Development of optimality criteria
g) D optimal designs

II. Applications
Rigorous and detailed applications will be covered. Students will develop design techniques for specific commercial applications as mini-projects for the course.

a) Detailed analysis of two or three practical applications
b) Mini-projects that apply complex statistical techniques to commercial problems.