Design of Experiments

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Introduction to Design of Experiments

taught by Jim Rutledge

Aim of Course:

This online course, "Introduction to Design of Experiments" will teach you how to use experiments to gain maximum knowledge at minimum cost. For processes of any kind that have measurable inputs and outputs, Design of Experiments (DOE) methods guide you in the optimum selection of inputs for experiments, and in the analysis of results. Full factorial as well as fractional factorial designs are covered - see the course outline below for additional details.

Course Program:

WEEK 1: Foundations of DOE

  • What is experimental design
  • Why use DOE
  • Measure of quality (Cp Cpk, dpm)
  • DOE key concepts
    • Interactions
    • Coding
    • Confounding/aliasing
    • Robustness
    • Randomization

WEEK 2: Simple Designs and Their Analysis

  • DOE 12-step checklist example
  • Calculating effects
  • Interaction plots
  • Marginal means plot of effects
  • Pareto chart of effects
  • Prediction equations
  • Using Excel based DOE KISS software

WEEK 3: Design Types

  • Full factorial designs
  • Fractional factorial designs
    • Design resolution
    • Aliasing pattern
    • Fold-over
  • Plackett-Burman designs
  • Box-Behnken designs
  • Box-Wilson (central composite) designs
  • Taguchi designs

WEEK 4: Practice Conducting and Analyzing Experimental Data

  • Multiple regression
  • Normal probability plot
  • Importance of analyzing interactions
  • Taguchi's signal to noise ratios
  • Variance reduction analysis
  • Practice planning, executing, and analyzing an experiment


Homework in this course consists of short answer questions to test concepts, guided data analysis problems using software, and guided data modeling problems using software.

In addition to assigned readings, this course also has discussion tasks, and an end of course data modeling project.

Introduction to Design of Experiments

Who Should Take This Course:

All six-sigma practitioners, scientists, engineers, and technicians who are interested in performing experiments that maximize process knowledge with a minimum amount of resources. Managers who are responsible for delivering products "on time" and "on budget" will also benefit from this course by learning what their employees should be doing. This course will stress the application of DOE rather than statistical theory. While design of experiments has been very successfully applied in research and development, that is not the only application. The techniques presented also apply to manufacturing, quality control, and even marketing.



You should be familiar with introductory statistics.  Try these self tests to check your knowledge.

Organization of the Course:

This course takes place online at the Institute for 4 weeks. During each course week, you participate at times of your own choosing - there are no set times when you must be online. Course participants will be given access to a private discussion board. In class discussions led by the instructor, you can post questions, seek clarification, and interact with your fellow students and the instructor.

At the beginning of each week, you receive the relevant material, in addition to answers to exercises from the previous session. During the week, you are expected to go over the course materials, work through exercises, and submit answers. Discussion among participants is encouraged. The instructor will provide answers and comments, and at the end of the week, you will receive individual feedback on your homework answers.

Time Requirement:
About 15 hours per week, at times of  your choosing.

Students come to the Institute for a variety of reasons. As you begin the course, you will be asked to specify your category:

  1. You may be interested only in learning the material presented, and not be concerned with grades or a record of completion.
  2. You may be enrolled in PASS (Programs in Analytics and Statistical Studies) that requires demonstration of proficiency in the subject, in which case your work will be assessed for a grade.
  3. You may require a "Record of Course Completion," along with professional development credit in the form of Continuing Education Units (CEU's).  For those successfully completing the course,  CEU's and a record of course completion will be issued by The Institute, upon request.
This course is also recognized by the Institute for Operations Research and the Management Sciences (INFORMS) as helpful preparation for the Certified Analytics Professional (CAP®) exam, and can help CAP®analysts accrue Professional Development Units to maintain their certification .

Course Text:

Understanding Industrial Designed Experiments by Schmidt et al should be orderedor by calling Air Academy Press at 1-800-748-1277. The text comes with software that will be used in the course. We recommend ordering through the publisher, to be sure you get the correct edition and software.


The course makes use of an Add-In to Microsoft Excel. The Excel Add-In comes with the course text. The Add-In should function with Excel 2000 and above, note however, the course notes are written with examples from Excel 2003.

Introduction to Design of Experiments

February 09, 2018 to March 09, 2018February 08, 2019 to March 08, 2019

Course Fee: $589