Non-Parametric Test / Nonparametric Test

Non-Parametric Test - A non-parametric test is used in place of its parametric conuterpart when certain assumptions about the underlying population are questionable (e.g. normality).

[Category=Data Quality ]

Source: iSixSigma, 07 February 2011 07:42:28, https:web.archive.org/web/20111109014246/http:www.isixsigma.com/index.php?option=com_glossary  

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Nonparametric Tests - All tests involving ranked data (data that can be put in order). Nonparametric tests are often used in place of their parametric counterparts when certain assumptions about the underlying population are questionable. For example, when comparing two independent samples, the Wilcoxon Mann-Whitney test does not assume that the difference between the samples is normally distributed, whereas its parametric counterpart, the two-sample t-test, does. Nonparametric tests can be, and often are, more powerful in detecting population differences when certain assumptions are not satisfied.

[Category=Quality ]

Source: American Society for Quality, 09 October 2010 16:42:57, http://www.asq.org/glossary/