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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...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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The Korean Society of Anesthesiologists
2015
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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 |
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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 |