The Power to See: A New Graphical Test of Normality
Many statistical procedures assume that the underlying data-generating process involves Gaussian errors. Among the popular tests for normality, only the Kolmogorov--Smirnov test has a graphical representation. Alternative tests, such as the Shapiro--Wilk test, offer little insight as to how the observed data deviate from normality. In this article, we discuss a simple new graphical procedure which provides simultaneous confidence bands for a normal quantile--quantile plot. These bands define a test of normality and are narrower in the tails than those related to the Kolmogorov--Smirnov test. Correspondingly, the new procedure has greater power to detect deviations from normality in the tails. Supplementary materials for this article are available online.
Year of publication: |
2013
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Authors: | Aldor-Noiman, Sivan ; Brown, Lawrence D. ; Buja, Andreas ; Rolke, Wolfgang ; Stine, Robert A. |
Published in: |
The American Statistician. - Taylor & Francis Journals, ISSN 0003-1305. - Vol. 67.2013, 4, p. 249-260
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Publisher: |
Taylor & Francis Journals |
Saved in:
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