Design of Experiments (DOE) II: Applied DOE for Test and Evaluation

Course Description

This course provides lectures and case studies on the application of Design of Experiments (DOE) in Test and Evaluation (T&E) and in producing high quality products. The course includes the perspectives of both statisticians and Department of Defense testers on how DOE can be effectively applied to test design and overall system evaluation. Beginning with a basic overview of statistics principles and hypothesis testing, the course will then concentrate on test designs, analyzing data from tests, and how to handle difficulties that arise in test plans. Specific difficulties of interest will include limited live tests, combining live and virtual test data, working with very large test spaces, and analyzing systems with nonlinear responses.

Available Classroom Sections

Start Date End Date Registration Deadline Format Location Cost CRN
Section Details Sep 20, 2016 Sep 22, 2016 Sep 20, 2016 Classroom Atlanta, GA $1,250 16069
Section Details Sep 19, 2017 Sep 21, 2017 Sep 19, 2017 Classroom Atlanta, GA $1,250 17030
View previous sections
View Previous Sections
CRN Start date End date Format Location Cost
14198 Aug 26, 2014 Aug 28, 2014 Classroom Atlanta, GA $1,250
15296 Sep 22, 2015 Sep 24, 2015 Classroom Atlanta, GA $1,250

Special Discounts

GTRI employees are eligible for a discount on this course.  If you are a GTRI employee, please go to https://webwise.gtri.gatech.edu/departments/tmd/training-development and look under “GT Professional Development” for a coupon code to use when checking out.

Note: Coupon codes must be applied during checkout and cannot be redeemed after your checkout is complete. Only one coupon code can be used per shopping cart.

Prerequisites

Who Should Attend

Engineers, scientists and managers who want to apply DOE to test design

How You Will Benefit

  • Review of basic statistics principles such as mean, variance, power, confidence intervals, factors, and design templates.
  • Learn to select the best design for a test.
  • Learn how to create a test hypothesis based on requirements.
  • Understand parameterization and when to use it.
  • Understand proper use of modeling and simulation (test selection and data result purposes)
  • Learn to use the course skills in up to three test case studies (missile testing, radar susceptibility, intelligent vehicle)

Content

  • Basic statistics principles
  • Selecting the best design for a test
  • Creating a test hypothesis based on requirements
  • Parameterization
  • Proper use of modeling and simulation
  • Test cases: Missile testing, radar susceptibility and intelligent vehicle

For Course-Related Questions

Please contact the course administrator: Steven Gordon

Instructors