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DOE: High variance and small effects in Minitab

I

Imai89

#1
Dear ladies and gentlemen,
I have a question, a colleague said that Minitab leads to wrong interpretations in DoE for high variance and small effects. He would have used 3 replications of the matrix. Since only the mean value is considered with DoEs, a significant effect is shown even though the variance were very high and therefore the effects were significant. Is this true, or is his statement from my colleague wrong? If so, how can this effect be countered? I think the variance is observed by the F-Value/p-Value?

Thank you very much!
Max
 
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#2
The issue does not originate with Minitab. All hypothesis testing, whether a t-test or the F-test in an ANOVA, is sensitive to sample size (replicates in DOE). Too few samples and the test is under powered and cannot see real differences. Too many samples and the test is over powered and can see differences that are of no practical importance. It sounds like your colleague's DOE was over powered with too many replicates. The correct approach is to design the experiment, determine the smallest difference that is of practical importance, then calculate the required number of samples/replicates to see that difference. Minitab can calculate this using the Power and Sample Size routine.
 
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