Abstract
Parametric tests require some specific conditions about the distributions of scores in the populations of interest. When these conditions cannot be formally tested, researchers assume that they exist. The interpretation of the results derived from parametric tests relies heavily on these requirements not being seriously violated. When these assumptions are not made on solid grounds, the interpretation of test results is likely to become problematic. In situations where the use of parametric techniques is inappropriate, non-parametric or distribution-free statistical techniques may be used.
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© 2000 Springer Science+Business Media New York
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Marchevsky, D. (2000). Non-Parametric Tests. In: Critical Appraisal of Medical Literature. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-4205-6_27
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DOI: https://doi.org/10.1007/978-1-4615-4205-6_27
Publisher Name: Springer, Boston, MA
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