List of all IE courses

Information
3 Credits
Available winter term
Lecture

Prerequisites
ST 314, or one course in engineering statistics with instructor approval
Contact
David Kim
541.737.8858
424 Rogers Hall

Course Description

A first course in design of experiments for graduate engineering students. Topics covered included a review of basic statistical inference, analysis of variance, factorial experiments, blocking, two-level factorial experiments, and random factors, and nesting.

Topics

  • Review of probability, statistics, and hypothesis testing
  • Introduction to design of experiments – single factor experiments
  • Complete block designs, factorial designs
  • 2k factorial designs
  • Experiments with random factors, nested and split-plot designs

Learning Outcomes

The student, upon completion of this course, will be able to:

  1. Describe (verbally/written) the basic principles of experimental design: randomization, replication, and blocking.
  2. Apply a systematic process for designing and conducting an experiment for a given application and objective of experimentation. This should involve selection of response variables, the selection and characterization of factors, levels, and ranges, the choice of experimental design, data collection, and statistical analysis
  3. Implement various statistical analyses of the data from a designed experiment in a software package of choice.
  4. Describe (verbally/written) the general ANOVA procedure including the decomposition of the sum of squares, the calculation of mean squares, hypothesis testing and sampling distributions, and model adequacy checking.
  5. Review the various types of experimental designs covered in class and describe a situation where the design is appropriate.