Cargando…

T test as a parametric statistic

In statistic tests, the probability distribution of the statistics is important. When samples are drawn from population N (µ, σ(2)) with a sample size of n, the distribution of the sample mean X̄ should be a normal distribution N (µ, σ(2)/n). Under the null hypothesis µ = µ(0), the distribution of s...

Descripción completa

Detalles Bibliográficos
Autor principal: Kim, Tae Kyun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Korean Society of Anesthesiologists 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4667138/
https://www.ncbi.nlm.nih.gov/pubmed/26634076
http://dx.doi.org/10.4097/kjae.2015.68.6.540
_version_ 1782403788540215296
author Kim, Tae Kyun
author_facet Kim, Tae Kyun
author_sort Kim, Tae Kyun
collection PubMed
description In statistic tests, the probability distribution of the statistics is important. When samples are drawn from population N (µ, σ(2)) with a sample size of n, the distribution of the sample mean X̄ should be a normal distribution N (µ, σ(2)/n). Under the null hypothesis µ = µ(0), the distribution of statistics [Formula: see text] should be standardized as a normal distribution. When the variance of the population is not known, replacement with the sample variance s(2) is possible. In this case, the statistics [Formula: see text] follows a t distribution (n-1 degrees of freedom). An independent-group t test can be carried out for a comparison of means between two independent groups, with a paired t test for paired data. As the t test is a parametric test, samples should meet certain preconditions, such as normality, equal variances and independence.
format Online
Article
Text
id pubmed-4667138
institution National Center for Biotechnology Information
language English
publishDate 2015
publisher The Korean Society of Anesthesiologists
record_format MEDLINE/PubMed
spelling pubmed-46671382015-12-02 T test as a parametric statistic Kim, Tae Kyun Korean J Anesthesiol Statistical Round In statistic tests, the probability distribution of the statistics is important. When samples are drawn from population N (µ, σ(2)) with a sample size of n, the distribution of the sample mean X̄ should be a normal distribution N (µ, σ(2)/n). Under the null hypothesis µ = µ(0), the distribution of statistics [Formula: see text] should be standardized as a normal distribution. When the variance of the population is not known, replacement with the sample variance s(2) is possible. In this case, the statistics [Formula: see text] follows a t distribution (n-1 degrees of freedom). An independent-group t test can be carried out for a comparison of means between two independent groups, with a paired t test for paired data. As the t test is a parametric test, samples should meet certain preconditions, such as normality, equal variances and independence. The Korean Society of Anesthesiologists 2015-12 2015-11-25 /pmc/articles/PMC4667138/ /pubmed/26634076 http://dx.doi.org/10.4097/kjae.2015.68.6.540 Text en Copyright © the Korean Society of Anesthesiologists, 2015 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
Kim, Tae Kyun
T test as a parametric statistic
title T test as a parametric statistic
title_full T test as a parametric statistic
title_fullStr T test as a parametric statistic
title_full_unstemmed T test as a parametric statistic
title_short T test as a parametric statistic
title_sort t test as a parametric statistic
topic Statistical Round
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4667138/
https://www.ncbi.nlm.nih.gov/pubmed/26634076
http://dx.doi.org/10.4097/kjae.2015.68.6.540
work_keys_str_mv AT kimtaekyun ttestasaparametricstatistic