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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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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
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author Nahm, Francis Sahngun
author_facet Nahm, Francis Sahngun
author_sort Nahm, Francis Sahngun
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description 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.
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spelling pubmed-47542732016-02-16 Nonparametric statistical tests for the continuous data: the basic concept and the practical use Nahm, Francis Sahngun Korean J Anesthesiol Statistical Round 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. The Korean Society of Anesthesiologists 2016-02 2016-01-28 /pmc/articles/PMC4754273/ /pubmed/26885295 http://dx.doi.org/10.4097/kjae.2016.69.1.8 Text en Copyright © the Korean Society of Anesthesiologists, 2016 http://creativecommons.org/licenses/by-nc/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Statistical Round
Nahm, Francis Sahngun
Nonparametric statistical tests for the continuous data: the basic concept and the practical use
title Nonparametric statistical tests for the continuous data: the basic concept and the practical use
title_full Nonparametric statistical tests for the continuous data: the basic concept and the practical use
title_fullStr Nonparametric statistical tests for the continuous data: the basic concept and the practical use
title_full_unstemmed Nonparametric statistical tests for the continuous data: the basic concept and the practical use
title_short Nonparametric statistical tests for the continuous data: the basic concept and the practical use
title_sort nonparametric statistical tests for the continuous data: the basic concept and the practical use
topic Statistical Round
url 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
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