Non-Parametric Statistical Methods and Data Transformations in Agricultural Pest Population Studies

Analyzing data from agricultural pest populations regularly detects that they do not fulfill the theoretical requirements to implement classical ANOVA. Box-Cox transformations and nonparametric statistical methods are commonly used as alternatives to solve this problem. In this paper, we describe th...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Cabrera Campos,Alcides, Guerra Bustillo,Caridad W, Herrera Villafranca,Magaly, Suris Campos,Moraima
Lenguaje:	English
Publicado:	Instituto de Investigaciones Agropecuarias, INIA 2012
Materias:	Kruskal-Wallis test negative binomial distribution Box-Cox transformations Thrips palmi Solanum tuberosum
Acceso en línea:	http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0718-58392012000300020
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:scielo:S0718-58392012000300020
record_format	dspace
spelling	oai:scielo:S0718-583920120003000202018-10-01Non-Parametric Statistical Methods and Data Transformations in Agricultural Pest Population StudiesCabrera Campos,AlcidesGuerra Bustillo,Caridad WHerrera Villafranca,MagalySuris Campos,Moraima Kruskal-Wallis test negative binomial distribution Box-Cox transformations Thrips palmi Solanum tuberosum Analyzing data from agricultural pest populations regularly detects that they do not fulfill the theoretical requirements to implement classical ANOVA. Box-Cox transformations and nonparametric statistical methods are commonly used as alternatives to solve this problem. In this paper, we describe the results of applying these techniques to data from Thrips palmi Karny sampled in potato (Solanum tuberosum L.) plantations. The X² test was used for the goodness-of-fit of negative binomial distribution and as a test of independence to investigate the relationship between plant strata and insect stages. Seven data transformations were also applied to meet the requirements of classical ANOVA, which failed to eliminate the relationship between mean and variance. Given this negative result, comparisons between insect population densities were made using the nonparametric Kruskal-Wallis ANOVA test. Results from this analysis allowed selecting the insect larval stage and plant middle stratum as keys to design pest sampling plans.info:eu-repo/semantics/openAccessInstituto de Investigaciones Agropecuarias, INIAChilean journal of agricultural research v.72 n.3 20122012-09-01text/htmlhttp://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0718-58392012000300020en10.4067/S0718-58392012000300020
institution	Scielo Chile
collection	Scielo Chile
language	English
topic	Kruskal-Wallis test negative binomial distribution Box-Cox transformations Thrips palmi Solanum tuberosum
spellingShingle	Kruskal-Wallis test negative binomial distribution Box-Cox transformations Thrips palmi Solanum tuberosum Cabrera Campos,Alcides Guerra Bustillo,Caridad W Herrera Villafranca,Magaly Suris Campos,Moraima Non-Parametric Statistical Methods and Data Transformations in Agricultural Pest Population Studies
description	Analyzing data from agricultural pest populations regularly detects that they do not fulfill the theoretical requirements to implement classical ANOVA. Box-Cox transformations and nonparametric statistical methods are commonly used as alternatives to solve this problem. In this paper, we describe the results of applying these techniques to data from Thrips palmi Karny sampled in potato (Solanum tuberosum L.) plantations. The X² test was used for the goodness-of-fit of negative binomial distribution and as a test of independence to investigate the relationship between plant strata and insect stages. Seven data transformations were also applied to meet the requirements of classical ANOVA, which failed to eliminate the relationship between mean and variance. Given this negative result, comparisons between insect population densities were made using the nonparametric Kruskal-Wallis ANOVA test. Results from this analysis allowed selecting the insect larval stage and plant middle stratum as keys to design pest sampling plans.
author	Cabrera Campos,Alcides Guerra Bustillo,Caridad W Herrera Villafranca,Magaly Suris Campos,Moraima
author_facet	Cabrera Campos,Alcides Guerra Bustillo,Caridad W Herrera Villafranca,Magaly Suris Campos,Moraima
author_sort	Cabrera Campos,Alcides
title	Non-Parametric Statistical Methods and Data Transformations in Agricultural Pest Population Studies
title_short	Non-Parametric Statistical Methods and Data Transformations in Agricultural Pest Population Studies
title_full	Non-Parametric Statistical Methods and Data Transformations in Agricultural Pest Population Studies
title_fullStr	Non-Parametric Statistical Methods and Data Transformations in Agricultural Pest Population Studies
title_full_unstemmed	Non-Parametric Statistical Methods and Data Transformations in Agricultural Pest Population Studies
title_sort	non-parametric statistical methods and data transformations in agricultural pest population studies
publisher	Instituto de Investigaciones Agropecuarias, INIA
publishDate	2012
url	http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0718-58392012000300020
work_keys_str_mv	AT cabreracamposalcides nonparametricstatisticalmethodsanddatatransformationsinagriculturalpestpopulationstudies AT guerrabustillocaridadw nonparametricstatisticalmethodsanddatatransformationsinagriculturalpestpopulationstudies AT herreravillafrancamagaly nonparametricstatisticalmethodsanddatatransformationsinagriculturalpestpopulationstudies AT suriscamposmoraima nonparametricstatisticalmethodsanddatatransformationsinagriculturalpestpopulationstudies
_version_	1714205315555131392

Non-Parametric Statistical Methods and Data Transformations in Agricultural Pest Population Studies

Ejemplares similares