ESI6247 Statistical Design Models

ESI6247 Statistical Design Models
Hui Yang
Textbook: “Experiments: Planning, Analysis and Parameter Design Optimization” (by C.F. Jeff Wu and Michael S. Hamada), second edition, 2009, John Wiley.

SYLLABUS: Syllabus
Grading Policy
	2 Exams - 35 pts each Quizzes/homework - 30 pts 1 Comprehensive Final Exam - 35 pts The top two scores from the three exams will be added to and the total quiz/homework score to obtain the total grade for the course (out of a total of 100 pts). No make-up exams unless previous arrangements have been made. Students will be expected to attend class and prepare assignments. Habitual failure to do so will result in a reduced grade. An incomplete grade will only be given when a student misses a portion of the semester because of illness or accident. Cheating on examinations, plagiarism and other forms of academic dishonesty are serious offenses and may subject the student to penalties ranging from failing grades to dismissal. Grading scale will be used: A: 90+; B: 80+; C: 70+; D: 60+, F: <60 (College of Engineering Rule: Only grades of C or better will be accepted in all Math, Science, and Engineering courses).

TOPICS:
Statistics Review
-	Notes for statistics prerequisites
-	Confidence interval and hypothesis testing
-	Statistical measures
-	Central limit theorem (CLT)
-	Combination and permutation
-	Chi-square distribution and Chi-square test
-	t distribution and t test
-	F distribution and F test
-	Degree of freedom

Chapter 1 Basic Experimental Design and Regression Analysis (Note)
-	Breast cancer mortality
	data program
-	Air pollution
	data program (regression, best subset selection)
	Injection Molding (http://youtu.be/YA8X8egacfM)

Chapter 2 Experiments with a Single factor (Note)
-	Pulp experiment
	data program
-	Composite experiment
	data program

Chapter 3 Experiments with More Than One Factor (Note)
-	Sewage Experiment
	data program
-	Girder Experiment
	data program
-	Bolt Experiment
	data program
-	Wear Experiment (Latin square design)
	program
-	Starch Experiment (ANCOVA)
	data program
-	Drill Experiment (Transformation of responses)
	data program

Chapter 4 Full Factorial Experiments at Two Levels (Note)
-	Adapted Epitaxial Layer Growth Experiment
	data program (factorial effects, interaction plot, main effect plot, half normal plot & lenth method)
-	Revisiting Original Epitaxial Layer Growth Experiment
	data program

Chapter 5 Fractional Factorial Experiments at Two Levels (Note)
-	Leaf Spring Experiment
	data program (factorial effects & half normal plot & lenth method, interaction plots)

Chapter 10 Response Surface Methodology (Note)
-	Taylor Series
	program (one dimension, two dimension)
-	Performance Optimization
	program (steepest descent, newton's method, conjugate gradient)

Chapter 11 Robust Parameter Design
-	Layer Growth Experiment
	data (crossarray, response) program (interaction plots, location_dispersion_modeling, responsemodeling1, responsemodeling2)
-	Leaf Spring Experiment
	data (leafspring) program (location_dispersion_modeling)

Chapter 13 Experiments for Reliability
	program (simulation, visualization, degradation_estimation, reliability_estimation)
	data (luminosity)

Matlab Tutorials
	http://www.mathworks.com/academia/student_center/tutorials/launchpad.html http://www.math.ufl.edu/help/matlab-tutorial/ http://www.math.utah.edu/lab/ms/matlab/matlab.html http://users.ece.gatech.edu/~bonnie/book/TUTORIAL/tutorial.html http://www.engin.umich.edu/group/ctm/ http://www.math.mtu.edu/~msgocken/intro/intro.html http://www.math.siu.edu/matlab/tutorials.html http://www.cyclismo.org/tutorial/matlab/ http://www.cs.ubc.ca/spider/cavers/MatlabGuide/guide.html http://www.duke.edu/~hpgavin/matlab.html http://amath.colorado.edu/computing/Matlab/Tutorial/