Parametric Versus Nonparametric Tests
- David J. SheskinAffiliated withWestern Connecticut State University
A common distinction made with reference to statistical tests/procedures is the classification of a procedure as parametric versus nonparametric. This distinction is generally predicated on the number and severity of assumptions regarding the population that underlies a specific test. Although some sources use the term assumption free (as well as distribution free) in reference to nonparametric tests, the latter label is misleading, in that nonparametric tests are not typically assumption free. Whereas parametric statistical tests make certain assumptions with respect to the characteristics and/or parameters of the underlying population distribution upon which a test is based, nonparametrictests make fewer or less rigorous assumptions. Thus, as Marascuilo and McSweeney (1977) suggest, nonparametric tests should be viewed as assumption freer tests. Perhaps the most common assumption associated with parametric tests that does not apply to nonparametric tests is that data are derived from ...
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- Parametric Versus Nonparametric Tests
- Reference Work Title
- International Encyclopedia of Statistical Science
- pp 1051-1052
- Print ISBN
- Online ISBN
- Springer Berlin Heidelberg
- Copyright Holder
- Springer-Verlag Berlin Heidelberg
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