Introduction to Design of Experiments

Introduction to Design of Experiments

taught by Jim Rutledge

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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.
Organization of the Course:

Options for Credit and Recognition:

Course Text:

Understanding Industrial Designed Experiments by Schmidt et al should be ordered online, or by calling Six Sigma Products Group at 1-866-352-2845.


The course makes use of Quantum XL, an add-in to Microsoft Excel.  A 30-day trial version of the add-in can be downloaded from  The add-in should function with Excel 2002 and above, note however, the course notes are written with examples from Excel 2010.

NOTE:  Do not start your trial prematurely - you'll need it throughout the 4-week course.



March 13, 2020 to April 10, 2020

Introduction to Design of Experiments


March 13, 2020 to April 10, 2020

Course Fee: $589

Do you meet course prerequisites? What about book & software? (Click here to learn more)

We have flexible policies to transfer to another course, or withdraw if necessary (modest fee applies)

Group rates: Click here to get information on group rates. 

First time student or academic? Click here for an introductory offer on select courses. Academic affiliation?  You may be eligible for a discount at checkout.

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The Institute for Statistics Education is certified to operate by the State Council of Higher Education in Virginia (SCHEV).

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