Introduction to Design of Experiments

Introduction to Design of Experiments

This course will teach you the application of DOE rather than statistical theory, and teaches full and fractional factorial designs, Plackett-Burman, Box-Behnken, Box-Wilson and Taguchi designs.

This course will teach you the application of DOE rather than statistical theory, and teaches full and fractional factorial designs, Plackett-Burman, Box-Behnken, Box-Wilson and Taguchi designs.

$589 | Enroll Now
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Overview

This course 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.
CAP Credit Eligible
Expert Instructors
Teacher Assistant Support

Learning Outcomes

At the conclusion of this course you will be familiar with the foundations of experimental design.  You will learn about interactions, coding and randomization, how to choose appropriate designs, and how to conduct experiments and analyze your results.

  • Explain the key concepts of DOE, and why it is used
  • Calculate treatment effects
  • Produce plots from the results of experiments
  • Specify fractional and full factorial designs
  • Specify specialized designs, e.g. Taguchi, Box-Wilson, others
  • Use Excel-based software to design experiments and analyze data

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.

Instructors

Dr.Jim Rutledge

Dr. Jim Rutledge

Dr. Jim Rutledge is currently the President of Data Vision, a company that performs statistical consulting and training. Dr. Rutledge has over fifteen years of teaching and consulting experience. He specializes in teaching powerful statistical tools to non-statisticians; he has instructed over 1000 scientists, engineers, managers, and college students. Previously, he served as an Assistant Professor at the United States Air Force Academy and has extensive research and consulting experience in healthcare issues. Dr. Rutledge was recently invited by the National Academy of Sciences to give a presentation on Design of Experiments to Biomedical Engineering Materials and Applications members. ...

See Instructor Bio

Course Syllabus

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

Class Dates

2021

Nov 19, 2021 to Dec 17, 2021

2022

Feb 11, 2022 to Mar 11, 2022

Aug 19, 2022 to Sep 16, 2022

2023

No classes scheduled at this time.

Send me reminder for next class

Prerequisites

Introductory Statistics

We assume you are versed in statistics or have the equivalent understanding of topics covered in our Statistics 1 and Statistics 2 courses. but do not require them as eligibility to enroll in this course. Please review the course description for each of our introductory statistics courses, estimate which best matches your level of understanding of the material covered in these courses, then take the short assessment test for that course. If you can not answer more than half of the questions correctly, we suggest you take our Statistics 1 and Statistics 2 courses prior to taking this course.

What Our Students Say​

Both the instructor and the teaching assistant were approachable, helpful, and knowledgeable about the subject matter, and provided constructive feedback about discussion board posts and assignment submissions. My textbook will even be a valuable resource for future projects.

Dennis Fuster
Kremers Urban Pharmaceuticals

This class was very interesting and practical. I learned how to structure experiments to be able to isolate the effects that the input variables have on the response variable. It was also interesting seeing the application of linear regression analysis in a little different way than I experienced in the linear regression class I took just before this. I appreciated the text and will keep it for reference.

Robert Wells
Director Business Intelligence' Adventist Healthcare

Frequently Asked Questions

Can I transfer or withdraw from a course?

We have a flexible transfer and withdrawal policy that recognizes circumstances may arise to prevent you from taking a course as planned. You may transfer or withdraw from a course under certain conditions.

  • Students are entitled to a full refund if a course they are registered for is canceled.
  • You can transfer your tuition to another course at any time prior to the course start date or the drop date, however a transfer is not permitted after the drop date.
  • Withdrawals on or after the first day of class are entitled to a percentage refund of tuition.

Please see this page for more information.

Who are the instructors at the Institute?

The Institute has more than 60 instructors who are recruited based on their expertise in various areas in statistics. Our faculty members are:

  • Authors of well-regarded texts in their area;
  • Advisory board members;
  • Senior faculty; and
  • Educators who have made important contributions to the field of statistics or online education in statistics.

The majority of our instructors have more than five years of teaching experience online at the Institute.

Please visit our faculty page for more information on each instructor at The Institute for Statistics Education.

Please see our knowledge center for more information.

What type of courses does the Institute offer?

The Institute offers approximately 80 courses each year. Topics include basic survey courses for novices, a full sequence of introductory statistics courses, bridge courses to more advanced topics. Our courses cover a range of topics including biostatistics, research statistics, data mining, business analytics, survey statistics, and environmental statistics.

Please see our course search or knowledge center for more information.

Do your courses have for-credit options?

Our courses have several for-credit options:

  • Continuing education units (CEU)
  • College credit through The American Council on Education (ACE CREDIT)
  • Course credits that are transferable to the INFORMS Certified Analytics Professional (CAP®)

Please see our knowledge center for more information.

Is the Institute for Statistics Education certified?

The Institute for Statistics Education is certified to operate by the State Council of Higher Education for Virginia (SCHEV). For more information visit: https://www.schev.edu/

Please see our knowledge center for more information.

Visit our knowledge base and learn more.

FAQs + Knowledge Base

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Additional Course Information

Organization of 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 Requirements

This is a 4-week course requiring 10-15 hours per week of review and study, at times of your choosing.

Homework

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.

Course Text

Understanding Industrial Designed Experiments by Schmidt et al is available as an e-book, or hard cover from Amazon.

Please order a copy of your course textbook prior to course start date.

Software

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 www.sigmazone.com.  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.

Software Uses and Descriptions | Available Free Versions
To learn more about the software used in this course, or how to obtain free versions of software used in our courses, please read our knowledge base article “What software is used in courses?” 

Course Fee & Information

Enrollment
Courses may fill up at any time and registrations are processed in the order in which they are received. Your registration will be confirmed for the first available course date unless you specify otherwise.

Transfers and Withdrawals
We have flexible policies to transfer to another course or withdraw if necessary.

Group Rates
Contact us to get information on group rates.

Discounts
Academic affiliation?  In most courses you are eligible for a discount at checkout.

New to Statistics.com?  Click here for a special introductory discount code.  

Invoice or Purchase Order
Add $50 service fee if you require a prior invoice, or if you need to submit a purchase order or voucher, pay by wire transfer or EFT, or refund and reprocess a prior payment.

Options for Credit and Recognition

This course is eligible for the following credit and recognition options:

No Credit
You may take this course without pursuing credit or a record of completion.

Mastery or Certificate Program Credit
If you are enrolled in mastery or certificate program that requires demonstration of proficiency in this subject, your course work may be assessed for a grade.

CEUs and Proof of Completion
If you require a “Record of Course Completion” along with professional development credit in the form of Continuing Education Units (CEU’s), upon successfully completing the course, CEU’s and a record of course completion will be issued by The Institute upon your request.

INFORMS-CAP
This course is 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.

Supplemental Information

There is no supplemental content for this course.

Miscellaneous

There is no additional information for this course.

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Introduction to Design of Experiments
$589 | Enroll Now
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