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Nonparametric Statistics Behavioral Sciences by Sidney Siegel
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JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range of content in a trusted digital archive. We use information technology and tools to increase productivity and facilitate new forms of scholarship. The title of thesetests parametric-suggests the centralimportance of the population,or its parameters,in their use and Thesetestsalso use theoperationsof arithinterpretation. The t and F tests withobservations are the mostfamiliarand widelyused of the parametric correlationcoeffitests,and thePearsonproduct-moment cient and its associated significancetest are the most familiarparametricapproachesto assessingassociation. More recently, nonparametric or "distribution-free" statistical tests have gained prominence. As their title suggests, these tests do not make numerous or stringent assumptionsabout the population. In addition, most nonparametric tests may be used with non-numerical data, and it is for this reason that many of them are often referred to as "ranking tests" or "order tests.