Sample size for estimation of the Pearson correlation coefficient in cherry tomato tests
Autor(a) principal: | |
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Data de Publicação: | 2017 |
Outros Autores: | , , , , |
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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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 |
|
_version_ |
1749140551741997056 |