Stat664    Syllabus    Spring 2016

Design of Experiments I, CRN#11020

2:00-3:15PM, Tue. & Thurs.

J.C. Wang (
Office: 5503 Everett
Office Hours: 1:30pm-4:00pm W and by appointment
Course Homepage:

Course Objectives
Students will gain in-depth understanding of principles of planning experiments and analyzing experimental data.
Course Outcomes
Upon completion of this course, students should be able:
  • To correctly explain the three basic principles of experimental planning.
  • To formulate the degrees-of-freedom decomposition and the sums-of-square decomposition of one- or two-factor standard designs.
  • To correctly determine the error term(s) in random-effects, mixed-effects or nested design models.
Prerequisites & Corequisites
Prerequisite: STAT 6620
Course Materials
Textbook: Design of Experiments STAT6640, Western Michigan University, McGraw Hill Create Textbook (selected chapters from Applied Linear Statistical Models by Kutner, Nachtsheim, Neter). ISBN-13: 978-1-121-84935-8, ISBN-10: 1-121-84935-0.
Class Notes: Class notes will also be used and followed closely.
There will be 3 homework assignments, due February 11, March 24, and April 21, respectively, at the beginning of the classes of these dates. Homework assignments submitted after the respective due dates will not be accepted. You are encouraged to discuss with classmates general strategies for solving problems. However, any assignment turned in should be substantially your own work.

There will be a final project (due date: April 21 at the beginning of class).

Computer Use
The use of computer softwares is important in planning experiments, analyzing experimental data, and presenting analysis outcomes. You are required to use one of three statistical softwares: R, SAS, or Minitab. Some problems may require the use of a specific software package.
Grading Policy:
Two 80-minute tests at 15% each (February 16, March 29)
final exam 20% (2:45-4:45 Thursday, April 28)
homework 40%
project 10%

Grading Scale
below 50 50-55 56-60 61-70 71-75 76-84 85-89 90 or more

Incomplete Grades
University & Deparmental policy will be followed for incomplete grades.
Academic Integrity
You are responsible for making yourself aware of and understanding the policies and procedures in the Catalog that pertain to Academic Honesty (accessible online at goWMU → catalog → Academic Policies → Students Rights and Responsibilities → Student Academic Conduct). These policies cover cheating, fabrication, falsification and forgery, multiple submission, plagiarism, complicity and computer misuse. You should consult with your instructor if you are uncertain about an issue of academic honesty prior to the submission of an assignment or exam.

Use of Email:
The only email address that should be used for communication between WMU students and WMU faculty and staff is the email address associated with a BroncoNet ID.  This email address typically takes the form ""  An example is  Students cannot automatically forward email from this address to other addresses.  Students can access this email account or get instructions for obtaining a BroncoNet ID at

Tentative Topics

  1. Design of Experiments
    1. Controlled Experiments Versus Observational Studies
    2. Principles of Planning Experiments
  2. Review: Theory Review and Preparation
    1. Univariate/Multivariate Normal Distributions
    2. Central/Noncentral Chi-square Distributions
    3. Central/Noncentral F Distributions
    4. Some Important Results from Sampling Normal Distributions
  3. Review: One-way ANOVA Models
    1. Models and Assumptions
    2. Estimations
    3. Diagnostics of Model Assumptions
    4. ANOVA Table
    5. Follow-up Studies
    6. Sensitivity of Model Assumptions and Alternative Test Procedures
    7. Orthogonal Polynomials and Trend Analysis
    8. Simultaneous Inferences
  4. Two-way ANOVA Models
    1. Equal Sample Sizes Case (Chapter 19)
    2. Single Replicate Case (Chapter 20)
    3. Randomized Complete Block Experiments (Chapter 21)
    4. Unbalanced Case, i.e., Unequal Sample Size Case (Chapter 23)
  5. Multi-way ANOVA Models (Chapter 24)
  6. Variance Component Models (Chapter 25)
    1. Random Effects Models
    2. Mixed Effects Models
  7. Nested Designs, Split-Plot Designs, and Partially Nested Designs (Chapter 26)
  8. Repeated Measure Designs (Chapter 27)
  9. Balanced Incomplete Block Designs, Latin Square Designs, Graeco-Latin Square Designs, Youden Designs (Chapter 28)
  10. Screening and Exploratory Experiments: Two-Level Factorial and Fractional Factorial Designs (Chapter 29)
  11. Other Topics (if time permitted)
    1. Response Surface Methodology (Chapter 30)
    2. Experiments with Mixtures — Two-, Three-Components Experiments