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Technical Advice: Quantile Plots to Check Assumptions

Summary: Six Sigma Black Belt consultants often insist on an Anderson-Darling test to confirm that data are normally distributed before performing any analysis. Unfortunately, the Anderson-Darling test is insensitive to deviations from normality in small sample sizes and overly sensitive to deviations in large sample sizes. Anderson-Darling also fails to suggest transformations that can place the data in a normal distribution. A normal probability plot, although subjective, can give a more accurate determination of normal distribution and suggest what kind of transformation can create a normal distribution out of data not normally distributed.

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  • Topics:
  • Keywords: Normal distribution, Sample size, Six Sigma, Transformation
  • Author: Vining, Geoff
  • Journal: Quality Engineering