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Nonparametric statistical tests for the continuous data: the basic concept and the practical use

Conventional statistical tests are usually called parametric tests. Parametric tests are used more frequently than nonparametric tests in many medical articles, because most of the medical researchers are familiar with and the statistical software packages strongly support parametric tests. Parametr...

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Detalles Bibliográficos
Autor principal: Nahm, Francis Sahngun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Korean Society of Anesthesiologists 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4754273/
https://www.ncbi.nlm.nih.gov/pubmed/26885295
http://dx.doi.org/10.4097/kjae.2016.69.1.8
Descripción
Sumario:Conventional statistical tests are usually called parametric tests. Parametric tests are used more frequently than nonparametric tests in many medical articles, because most of the medical researchers are familiar with and the statistical software packages strongly support parametric tests. Parametric tests require important assumption; assumption of normality which means that distribution of sample means is normally distributed. However, parametric test can be misleading when this assumption is not satisfied. In this circumstance, nonparametric tests are the alternative methods available, because they do not required the normality assumption. Nonparametric tests are the statistical methods based on signs and ranks. In this article, we will discuss about the basic concepts and practical use of nonparametric tests for the guide to the proper use.