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Ten Key Statistical Concepts Every Engineer Should Know

Here are ten key concepts every engineer should understand:

  1. All data contain variation. This variation is a fact of life. Sometimes the variation is small -- sometimes it is large.
  2. The only way to know the size of your measurement variation is to make a few repeated measurements. Differences in your repeated measurements show you the size of your measurement variation. If you see no differences, you need a more precise measurement tool.
  3. Measurement systems can be inadequate for your uses. Even very expensive systems in good working order may not provide accurate and/or precise measurements in your situation.
  4. You need to perform a Measurement System Analysis to determine if your measurement system is adequate for your uses. If you don't perform this study, or have someone perform it for you, you can be wasting your time measuring noise.
  5. Statistics relies on consistency. If the results you get today are not related to the results you will get if you repeat your work tomorrow, then Statistics can't help you.
  6. Consistent behavior is called "In Control" behavior. Statistics only works if you are "In Control."
  7. Statistical Process Control," or "SPC" for short, helps you determine if you are in control.
  8. Experimental factors, like temperature and time, can "interact" -- they can work together to make things better or to make things worse.
  9. Nature works through factor interactions. Knowing the effect of each factor alone does not tell the story -- you also need to know how the factors interact.
  10. Design of Experiments looks for factor interactions, while One-Factor-At-A-Time experimentation does not. In fact, One-Factor-At-A-Time prevents you from discovering important interactions.

Objective Design of Experiments workshops cover all of these points in a practical manner. You learn to apply these concepts easily in your daily work. We will help you be successful!



"Objective Design of Experiments judges its success on the success of those it has trained."
John Raffaldi, www.microen.com


"Objective Design of Experiments has expended great effort to ensure concepts are clearly conveyed without the use of obscure jargon or the need for extensive calculations. After all, that's what computers and software are for -- to do the hard work!"
Bob Johnson,
DSM Desotech




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