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A-Square - A-squared is the test statistic for the Anderson-Darling Normality test. It is a measure of how closely a dataset follows the normal distribution. The null hypothesis for this test is that the data is normal. So if you get an A-squared that is fairly large, then you will get a small p-value and thus reject the null hypothesis. Small A-squared values imply large p-values, thus you cannot reject the null hypothesis.
[Category=Data Quality ]
Source: iSixSigma, 29 December 2010 09:02:28, https:web.archive.org/web/20111109014246/http:www.isixsigma.com/index.php?option=com_glossary
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