*Choose Index below for a list of all words and phrases defined in this glossary.*

**Anderson-Darling Normality Test** - After you have plotted data for Normality Test, Check for P-value.

P-value < 0.05 = not normal.

normal = P-value >= 0.05

Note: Similar comparison of P-Value is there in Hypothesis Testing.

If P-Value > 0.05, Fail to Reject the H0

The Anderson-Darling test is used to test if a sample of data came from a population with a specific distribution. It is a modification of the Kolmogorov-Smirnov (K-S) test and gives more weight to the tails than does the K-S test. The K-S test is distribution free in the sense that the critical values do not depend on the specific distribution being tested. The Anderson-Darling test makes use of the specific distribution in calculating critical values. This has the advantage of allowing a more sensitive test and the disadvantage that critical values must be calculated for each distribution.

[Category=Data Quality ]

*Source: iSixSigma, 30 December 2010 08:17:07, https: web.archive.org/web/20111109014246/http:www.isixsigma.com/index.php?option=com_glossary *

Data Quality Glossary. A free resource from GRC Data Intelligence. For comments, questions or feedback: dqglossary@grcdi.nl