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Chilean Journal of Agricultural Research
Instituto de Investigaciones Agropecuarias, INIA
ISSN: 0718-5820
EISSN: 0718-5839
Vol. 72, No. 3, 2012, pp. 440-443
Bioline Code: cj12067
Full paper language: English
Document type: Note
Document available free of charge

Chilean Journal of Agricultural Research, Vol. 72, No. 3, 2012, pp. 440-443

 en NON-PARAMETRIC STATISTICAL METHODS AND DATA TRANSFORMATIONS IN AGRICULTURAL PEST POPULATION STUDIES
Campos, Alcides Cabrera; Bustillo, Caridad W. Guerra; Villafranca, Magaly Herrera & Campos, Moraima Suris

Abstract

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 check for this species in other resources Karny sampled in potato ( Solanum tuberosum check for this species in other resources L.) plantations. The Χ2 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.

Keywords
Kruskal-Wallis test, negative binomial distribution, Box-Cox transformations, Thrips palmi, Solanum tuberosum

 
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