The course will cover most of the material in the text, Chapters 1-15. The students will be required to use statistical computer software to complete many homework assignments and the project.
This graduate level course covers the following topics:
- Understanding basic design principles
- Working in simple comparative experimental contexts
- Working with single factors or one-way ANOVA in completely randomized experimental design contexts
- Implementing randomized blocks, Latin square designs and extensions of these
- Understanding factorial design contexts
- Working with two level, 2k, designs
- Implementing confounding and blocking in 2k designs
- Working with 2-level fractional factorial designs
- Working with 3-level and mixed-level factorials and fractional factorial designs
- Simple linear regression models
- Understanding and implementing response surface methodologies
- Understanding robust parameter designs
- Working with random and mixed effects models
- Understanding and implementing nested and split-plot and strip-plot designs
- Using repeated measures designs, unbalanced AOV and ANCOVA
Dr. James L Rosenberger is the primary author of these course materials and has taught this course for many semesters in residence and online.
This course uses Examity for proctored exams. For more information view O.3 What is a proctored exam? in the student orientation.
For most assignments the Minitab GLM or SAS Proc GLM and Proc Mixed commands will satisfy the computing requirements. Minitab Design Of Experiments (DOE) commands are also utilized extensively.
Students should already feel comfortable using SAS at a basic level, be a quick learner of software packages, or able to figure out how to do the required analyses in another package of their choice. Students who have no experience with programming or are anxious about being able to manipulate software code are strongly encouraged to take the one-credit courses in SAS in order to establish this foundation before taking courses that rely on this software.
SAS will be supported and sample programs will be supplied but you will be required to do some programing on your own. Due to different software applications, software versions and platforms there may be issues with running code. Students must be proactive in seeking advice and help from appropriate sources including documentation resources, other students, the teaching assistant, instructor or helpdesk.
Montgomery, D. C. (2019). Design and Analysis of Experiments, 10th Edition, John Wiley & Sons.