Sample size for estimation of the Pearson correlation coefficient in cherry tomato tests

Detalhes bibliográficos
Autor(a) principal: Sari,Bruno Giacomini
Data de Publicação: 2017
Outros Autores: Lúcio,Alessandro Dal’Col, Santana,Cinthya Souza, Krysczun,Dionatan Ketzer, Tischler,André Luís, Drebes,Lucas
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Ciência Rural
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-84782017001000206
Resumo: ABSTRACT: The aim of this study was to determine the required sample size for estimation of the Pearson coefficient of correlation between cherry tomato variables. Two uniformity tests were set up in a protected environment in the spring/summer of 2014. The observed variables in each plant were mean fruit length, mean fruit width, mean fruit weight, number of bunches, number of fruits per bunch, number of fruits, and total weight of fruits, with calculation of the Pearson correlation matrix between them. Sixty eight sample sizes were planned for one greenhouse and 48 for another, with the initial sample size of 10 plants, and the others were obtained by adding five plants. For each planned sample size, 3000 estimates of the Pearson correlation coefficient were obtained through bootstrap re-samplings with replacement. The sample size for each correlation coefficient was determined when the 95% confidence interval amplitude value was less than or equal to 0.4. Obtaining estimates of the Pearson correlation coefficient with high precision is difficult for parameters with a weak linear relation. Accordingly, a larger sample size is necessary to estimate them. Linear relations involving variables dealing with size and number of fruits per plant have less precision. To estimate the coefficient of correlation between productivity variables of cherry tomato, with a confidence interval of 95% equal to 0.4, it is necessary to sample 275 plants in a 250m² greenhouse, and 200 plants in a 200m² greenhouse.
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spelling Sample size for estimation of the Pearson correlation coefficient in cherry tomato testsSolanum lycopersicum var. cerasiformesamplingresamplingbootstrap.ABSTRACT: The aim of this study was to determine the required sample size for estimation of the Pearson coefficient of correlation between cherry tomato variables. Two uniformity tests were set up in a protected environment in the spring/summer of 2014. The observed variables in each plant were mean fruit length, mean fruit width, mean fruit weight, number of bunches, number of fruits per bunch, number of fruits, and total weight of fruits, with calculation of the Pearson correlation matrix between them. Sixty eight sample sizes were planned for one greenhouse and 48 for another, with the initial sample size of 10 plants, and the others were obtained by adding five plants. For each planned sample size, 3000 estimates of the Pearson correlation coefficient were obtained through bootstrap re-samplings with replacement. The sample size for each correlation coefficient was determined when the 95% confidence interval amplitude value was less than or equal to 0.4. Obtaining estimates of the Pearson correlation coefficient with high precision is difficult for parameters with a weak linear relation. Accordingly, a larger sample size is necessary to estimate them. Linear relations involving variables dealing with size and number of fruits per plant have less precision. To estimate the coefficient of correlation between productivity variables of cherry tomato, with a confidence interval of 95% equal to 0.4, it is necessary to sample 275 plants in a 250m² greenhouse, and 200 plants in a 200m² greenhouse.Universidade Federal de Santa Maria2017-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-84782017001000206Ciência Rural v.47 n.10 2017reponame:Ciência Ruralinstname:Universidade Federal de Santa Maria (UFSM)instacron:UFSM10.1590/0103-8478cr20170116info:eu-repo/semantics/openAccessSari,Bruno GiacominiLúcio,Alessandro Dal’ColSantana,Cinthya SouzaKrysczun,Dionatan KetzerTischler,André LuísDrebes,Lucaseng2017-09-05T00:00:00ZRevista
dc.title.none.fl_str_mv Sample size for estimation of the Pearson correlation coefficient in cherry tomato tests
title Sample size for estimation of the Pearson correlation coefficient in cherry tomato tests
spellingShingle Sample size for estimation of the Pearson correlation coefficient in cherry tomato tests
Sari,Bruno Giacomini
Solanum lycopersicum var. cerasiforme
sampling
resampling
bootstrap.
title_short Sample size for estimation of the Pearson correlation coefficient in cherry tomato tests
title_full Sample size for estimation of the Pearson correlation coefficient in cherry tomato tests
title_fullStr Sample size for estimation of the Pearson correlation coefficient in cherry tomato tests
title_full_unstemmed Sample size for estimation of the Pearson correlation coefficient in cherry tomato tests
title_sort Sample size for estimation of the Pearson correlation coefficient in cherry tomato tests
author Sari,Bruno Giacomini
author_facet Sari,Bruno Giacomini
Lúcio,Alessandro Dal’Col
Santana,Cinthya Souza
Krysczun,Dionatan Ketzer
Tischler,André Luís
Drebes,Lucas
author_role author
author2 Lúcio,Alessandro Dal’Col
Santana,Cinthya Souza
Krysczun,Dionatan Ketzer
Tischler,André Luís
Drebes,Lucas
author2_role author
author
author
author
author
dc.contributor.author.fl_str_mv Sari,Bruno Giacomini
Lúcio,Alessandro Dal’Col
Santana,Cinthya Souza
Krysczun,Dionatan Ketzer
Tischler,André Luís
Drebes,Lucas
dc.subject.por.fl_str_mv Solanum lycopersicum var. cerasiforme
sampling
resampling
bootstrap.
topic Solanum lycopersicum var. cerasiforme
sampling
resampling
bootstrap.
description ABSTRACT: The aim of this study was to determine the required sample size for estimation of the Pearson coefficient of correlation between cherry tomato variables. Two uniformity tests were set up in a protected environment in the spring/summer of 2014. The observed variables in each plant were mean fruit length, mean fruit width, mean fruit weight, number of bunches, number of fruits per bunch, number of fruits, and total weight of fruits, with calculation of the Pearson correlation matrix between them. Sixty eight sample sizes were planned for one greenhouse and 48 for another, with the initial sample size of 10 plants, and the others were obtained by adding five plants. For each planned sample size, 3000 estimates of the Pearson correlation coefficient were obtained through bootstrap re-samplings with replacement. The sample size for each correlation coefficient was determined when the 95% confidence interval amplitude value was less than or equal to 0.4. Obtaining estimates of the Pearson correlation coefficient with high precision is difficult for parameters with a weak linear relation. Accordingly, a larger sample size is necessary to estimate them. Linear relations involving variables dealing with size and number of fruits per plant have less precision. To estimate the coefficient of correlation between productivity variables of cherry tomato, with a confidence interval of 95% equal to 0.4, it is necessary to sample 275 plants in a 250m² greenhouse, and 200 plants in a 200m² greenhouse.
publishDate 2017
dc.date.none.fl_str_mv 2017-01-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-84782017001000206
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-84782017001000206
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/0103-8478cr20170116
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv text/html
dc.publisher.none.fl_str_mv Universidade Federal de Santa Maria
publisher.none.fl_str_mv Universidade Federal de Santa Maria
dc.source.none.fl_str_mv Ciência Rural v.47 n.10 2017
reponame:Ciência Rural
instname:Universidade Federal de Santa Maria (UFSM)
instacron:UFSM
instname_str Universidade Federal de Santa Maria (UFSM)
instacron_str UFSM
institution UFSM
reponame_str Ciência Rural
collection Ciência Rural
repository.name.fl_str_mv
repository.mail.fl_str_mv
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