Advanced Design of Experiments

Advanced Design of Experiments

Aim of Course: This course moves beyond the basic Design of Experiments techniques to cover some special but important topics, including some recent advances. A variety of response surface designs will be covered: single vs. sequential designs, space-filling designs, Draper-Lin designs, and Hoke, hybrid and other small designs. The course will cover conditional effects and how to deal with them, as well as Analysis of Means (ANOM). You'll learn when standard designs won't work, and what to do in those cases.
Course Program:

SESSION 1: Conditional Effects - What to Do When Standard Designs Won't Work

  • Conditional effects
    • What they are
    • The importance of computing them when interactions exist
    • Designs for which they should and should not be computed
  • What to do when standard designs won't work because of:
    • Constraints on the region of operability
      • examples
    • Debarred observations
      • examples

SESSION 2: Analysis of Means (ANOM)

  • Advantages of ANOM relative to Analysis of Variance (ANOVA)
  • ANOM with single factor, factorial, and fractional factorial designs
  • ANOM applied to designs with blocking
  • ANOM references, including the new ANOM book by Nelson, Wludyka, and Copeland

SESSION 3: Hard-to-Change Factors and Restricted Randomization

  • Consequences of ignoring restricted randomization in analyzing data
  • Proper analysis of data
  • Related issue: Should factors be reset?

SESSION 4: Modern Approaches to Constructing Response Surface Designs

  • Single design versus standard sequential approach
  • Uniform and other space-filling designs
  • Economical Response Surface designs
    • Draper-Lin designs
    • Other small designs (hybrid, Hoke)
  • Published case studies
    • Analysis of a Draper-Lin design application gone wrong

Advanced Design of Experiments

Who Should Take This Course:
Engineers, industrial statisticians, quality control and six-sigma statisticians, anyone who designs experiments and needs to know the latest techniques for gaining maximum information at minimum cost.
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. No credit - You may be interested only in learning the material presented, and not be concerned with grades or a record of completion.
  2. Certificate - 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. CEUs and/or proof of completion - 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.
  4. Digital Badge - Courses evaluated by the American Council on Education have a digital badge available for successful completion of the course.  
  5. Other options - Specializations, INFORMS CAP recognition, and academic (college) credit are available for some courses
Course Text:

The required text for this course is Modern Experimental Design by Thomas P. Ryan, and it can be ordered from Wiley by clicking here. Wiley typically offers customers up to 15% discount on this book (and all other statistics titles): enter the code aff15 in the Promotion Code field when prompted during checkout and click the Apply Discount button. (If you are located in Asia, the web procedure for your location may not accept this discount – try calling your regional Wiley representative.).


Participants should have access to software that can produce experiment designs and analyze the resulting data. Design-Expert will be used throughout the couse. Minitab and JMP are also illustrated, as each has some specific capabilities that will be useful for the course. For information on obtaining software for use during this course click here.


All courses have already commenced.

Advanced Design of Experiments


All courses have already commenced.

Course Fee: $499

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: Email jdobbins "at" 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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