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Understanding one-way ANOVA using conceptual figures
Analysis of variance (ANOVA) is one of the most frequently used statistical methods in medical research. The need for ANOVA arises from the error of alpha level inflation, which increases Type 1 error probability (false positive) and is caused by multiple comparisons. ANOVA uses the statistic F, whi...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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The Korean Society of Anesthesiologists
2017
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5296382/ https://www.ncbi.nlm.nih.gov/pubmed/28184262 http://dx.doi.org/10.4097/kjae.2017.70.1.22 |
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author | Kim, Tae Kyun |
author_facet | Kim, Tae Kyun |
author_sort | Kim, Tae Kyun |
collection | PubMed |
description | Analysis of variance (ANOVA) is one of the most frequently used statistical methods in medical research. The need for ANOVA arises from the error of alpha level inflation, which increases Type 1 error probability (false positive) and is caused by multiple comparisons. ANOVA uses the statistic F, which is the ratio of between and within group variances. The main interest of analysis is focused on the differences of group means; however, ANOVA focuses on the difference of variances. The illustrated figures would serve as a suitable guide to understand how ANOVA determines the mean difference problems by using between and within group variance differences. |
format | Online Article Text |
id | pubmed-5296382 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | The Korean Society of Anesthesiologists |
record_format | MEDLINE/PubMed |
spelling | pubmed-52963822017-02-09 Understanding one-way ANOVA using conceptual figures Kim, Tae Kyun Korean J Anesthesiol Statistical Round Analysis of variance (ANOVA) is one of the most frequently used statistical methods in medical research. The need for ANOVA arises from the error of alpha level inflation, which increases Type 1 error probability (false positive) and is caused by multiple comparisons. ANOVA uses the statistic F, which is the ratio of between and within group variances. The main interest of analysis is focused on the differences of group means; however, ANOVA focuses on the difference of variances. The illustrated figures would serve as a suitable guide to understand how ANOVA determines the mean difference problems by using between and within group variance differences. The Korean Society of Anesthesiologists 2017-02 2017-01-26 /pmc/articles/PMC5296382/ /pubmed/28184262 http://dx.doi.org/10.4097/kjae.2017.70.1.22 Text en Copyright © the Korean Society of Anesthesiologists, 2017 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 Understanding one-way ANOVA using conceptual figures |
title | Understanding one-way ANOVA using conceptual figures |
title_full | Understanding one-way ANOVA using conceptual figures |
title_fullStr | Understanding one-way ANOVA using conceptual figures |
title_full_unstemmed | Understanding one-way ANOVA using conceptual figures |
title_short | Understanding one-way ANOVA using conceptual figures |
title_sort | understanding one-way anova using conceptual figures |
topic | Statistical Round |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5296382/ https://www.ncbi.nlm.nih.gov/pubmed/28184262 http://dx.doi.org/10.4097/kjae.2017.70.1.22 |
work_keys_str_mv | AT kimtaekyun understandingonewayanovausingconceptualfigures |