Data transformation in biological assays
Autor(a) principal: | |
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Data de Publicação: | 2021 |
Outros Autores: | |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Pesquisa Florestal Brasileira (Online) |
Texto Completo: | https://pfb.cnpf.embrapa.br/pfb/index.php/pfb/article/view/1916 |
Resumo: | The analysis of variance is the statistical test most used for comparison of three or more means simultaneously. Its application requires, however, the compliance to some assumptions, with main emphasis on normality of the data and homoscedasticity of variances. When such requirements are not met, one of the alternatives is the data transformation to enable the continuity of the experimental evaluation. With the proposition of the Tukey’s data transformation system, understood as a power transformation system, i.e. the application of nth root on a data set (X⅟n) this statistical procedure has methodologically evolved to ensure such solutions. In the present research we proposed a complement to this system, denominated here as transformation in four steps, with inclusion of two hypothesis tests to evaluate normality and homoscedasticity. This was applied on experimental data to evaluate the amount of radiation available at soil level within stands of Acacia mearnsii De Wild. We have proposed a model for data transformation to simultaneously obtain homoscedasticity and normality. The methodology was appropriate to ensure these two statistical aspects on the experimental data, allowing comparison of eight treatments by conventional analysis of variance. Index terms: Analysis of variance, homoscedasticity, normality. |
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Data transformation in biological assaysTransformação de dados em ensaios biológicosAnalysis of varianceAcacia mearnsiiRadiation Análise de variânciaAcacia mearnsiiRadiaçãoThe analysis of variance is the statistical test most used for comparison of three or more means simultaneously. Its application requires, however, the compliance to some assumptions, with main emphasis on normality of the data and homoscedasticity of variances. When such requirements are not met, one of the alternatives is the data transformation to enable the continuity of the experimental evaluation. With the proposition of the Tukey’s data transformation system, understood as a power transformation system, i.e. the application of nth root on a data set (X⅟n) this statistical procedure has methodologically evolved to ensure such solutions. In the present research we proposed a complement to this system, denominated here as transformation in four steps, with inclusion of two hypothesis tests to evaluate normality and homoscedasticity. This was applied on experimental data to evaluate the amount of radiation available at soil level within stands of Acacia mearnsii De Wild. We have proposed a model for data transformation to simultaneously obtain homoscedasticity and normality. The methodology was appropriate to ensure these two statistical aspects on the experimental data, allowing comparison of eight treatments by conventional analysis of variance. Index terms: Analysis of variance, homoscedasticity, normality.A análise de variância é o teste estatístico mais utilizado para a comparação de três ou mais médias simultaneamente. Sua aplicação exige, no entanto, o cumprimento de algumas condicionantes, com ênfase principal na normalidade dos dados e homoscedasticidade das variâncias. Quando tais requisitos não são atendidos, uma das alternativas é a transformação de dados para permitir a continuidade da avaliação experimental. Com a proposição do sistema de transformação de dados de Tukey, entendido como um sistema de transformação de potência, ou seja, a aplicação de enésima raiz em um conjunto de dados (X⅟n), este procedimento estatístico evoluiu metodologicamente para garantir tais soluções. No presente trabalho foi proposto um complemento a esse sistema, denominado aqui de transformação em quatro passos, com a inclusão de dois testes de hipóteses para avaliar a normalidade e homoscedasticidade. Isto foi aplicado em dados experimentais para avaliar a quantidade de radiação disponível ao nível do solo dentro de povoamentos de Acacia mearnsii De Wild. Um modelo para transformação de dados foi proposto para obter simultaneamente homoscedasticidade e normalidade. A metodologia foi apropriada para garantir esses dois aspectos estatísticos nos dados experimentais, permitindo a comparação de oito tratamentos pela análise de variância convencional.Embrapa Florestas2021-03-31info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/octet-streamhttps://pfb.cnpf.embrapa.br/pfb/index.php/pfb/article/view/191610.4336/2021.pfb.41e201901916Pesquisa Florestal Brasileira; v. 41 (2021)Pesquisa Florestal Brasileira; Vol. 41 (2021)1983-26051809-3647reponame:Pesquisa Florestal Brasileira (Online)instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa)instacron:EMBRAPAenghttps://pfb.cnpf.embrapa.br/pfb/index.php/pfb/article/view/1916/1629Copyright (c) 2021 Sylvio Péllico Netto, Alexandre Behlinghttps://creativecommons.org/licenses/by-nc-nd/4.0info:eu-repo/semantics/openAccessPéllico Netto, SylvioBehling, Alexandre2021-11-18T11:01:58Zoai:pfb.cnpf.embrapa.br/pfb:article/1916Revistahttps://pfb.cnpf.embrapa.br/pfb/index.php/pfb/PUBhttps://pfb.cnpf.embrapa.br/pfb/index.php/pfb/oaipfb@embrapa.br || revista.pfb@gmail.com || patricia.mattos@embrapa.br1983-26051809-3647opendoar:2021-11-18T11:01:58Pesquisa Florestal Brasileira (Online) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa)false |
dc.title.none.fl_str_mv |
Data transformation in biological assays Transformação de dados em ensaios biológicos |
title |
Data transformation in biological assays |
spellingShingle |
Data transformation in biological assays Péllico Netto, Sylvio Analysis of variance Acacia mearnsii Radiation Análise de variância Acacia mearnsii Radiação |
title_short |
Data transformation in biological assays |
title_full |
Data transformation in biological assays |
title_fullStr |
Data transformation in biological assays |
title_full_unstemmed |
Data transformation in biological assays |
title_sort |
Data transformation in biological assays |
author |
Péllico Netto, Sylvio |
author_facet |
Péllico Netto, Sylvio Behling, Alexandre |
author_role |
author |
author2 |
Behling, Alexandre |
author2_role |
author |
dc.contributor.author.fl_str_mv |
Péllico Netto, Sylvio Behling, Alexandre |
dc.subject.por.fl_str_mv |
Analysis of variance Acacia mearnsii Radiation Análise de variância Acacia mearnsii Radiação |
topic |
Analysis of variance Acacia mearnsii Radiation Análise de variância Acacia mearnsii Radiação |
description |
The analysis of variance is the statistical test most used for comparison of three or more means simultaneously. Its application requires, however, the compliance to some assumptions, with main emphasis on normality of the data and homoscedasticity of variances. When such requirements are not met, one of the alternatives is the data transformation to enable the continuity of the experimental evaluation. With the proposition of the Tukey’s data transformation system, understood as a power transformation system, i.e. the application of nth root on a data set (X⅟n) this statistical procedure has methodologically evolved to ensure such solutions. In the present research we proposed a complement to this system, denominated here as transformation in four steps, with inclusion of two hypothesis tests to evaluate normality and homoscedasticity. This was applied on experimental data to evaluate the amount of radiation available at soil level within stands of Acacia mearnsii De Wild. We have proposed a model for data transformation to simultaneously obtain homoscedasticity and normality. The methodology was appropriate to ensure these two statistical aspects on the experimental data, allowing comparison of eight treatments by conventional analysis of variance. Index terms: Analysis of variance, homoscedasticity, normality. |
publishDate |
2021 |
dc.date.none.fl_str_mv |
2021-03-31 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://pfb.cnpf.embrapa.br/pfb/index.php/pfb/article/view/1916 10.4336/2021.pfb.41e201901916 |
url |
https://pfb.cnpf.embrapa.br/pfb/index.php/pfb/article/view/1916 |
identifier_str_mv |
10.4336/2021.pfb.41e201901916 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
https://pfb.cnpf.embrapa.br/pfb/index.php/pfb/article/view/1916/1629 |
dc.rights.driver.fl_str_mv |
Copyright (c) 2021 Sylvio Péllico Netto, Alexandre Behling https://creativecommons.org/licenses/by-nc-nd/4.0 info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Copyright (c) 2021 Sylvio Péllico Netto, Alexandre Behling https://creativecommons.org/licenses/by-nc-nd/4.0 |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/octet-stream |
dc.publisher.none.fl_str_mv |
Embrapa Florestas |
publisher.none.fl_str_mv |
Embrapa Florestas |
dc.source.none.fl_str_mv |
Pesquisa Florestal Brasileira; v. 41 (2021) Pesquisa Florestal Brasileira; Vol. 41 (2021) 1983-2605 1809-3647 reponame:Pesquisa Florestal Brasileira (Online) instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa) instacron:EMBRAPA |
instname_str |
Empresa Brasileira de Pesquisa Agropecuária (Embrapa) |
instacron_str |
EMBRAPA |
institution |
EMBRAPA |
reponame_str |
Pesquisa Florestal Brasileira (Online) |
collection |
Pesquisa Florestal Brasileira (Online) |
repository.name.fl_str_mv |
Pesquisa Florestal Brasileira (Online) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa) |
repository.mail.fl_str_mv |
pfb@embrapa.br || revista.pfb@gmail.com || patricia.mattos@embrapa.br |
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