When the assumption of homocedasticidad in variableswith binomial distribution fails

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Published: Jul 4, 2012
Keywords:
homogeneity of variance, homocedasticidad, variables binomials, assumptions of ANOVA

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Edison Ramiro Vásquez
Universidad Nacional de Loja (UNL)

Abstract

The process of Monte Carlo simulation was usedto generate populations of random variables with Binomialdistribution with homogeneous or heterogeneous variance;for 5, 10 and 30 observations by experimental unit (n) andlikelihood of success of the event of 0.10, 0.20,..., 0, 90 (p). Itconsisted of experiments in randomized block design with 3, 5and 9 treatments (t); 4 and 8 replics (r); for each combinationt-r-n, generated 100 experiments. By way of a reference pointof discussion to have, included the variant of other 100experiments of variables with Normal distribution, with similarmean and variance of the experiments of data with Binomialdistribution. It was found that the behavior of the indicators:percentage of experiments in which there is a rejection of thehypothesis H0; the power in the ANOVA; minimum differencedetected in the experiment, as well as the number of differencesbetween treatments is similar within each alternative analysisthrough three variants; showing a marked influence the numberof observations per experimental unit and the number of replicsin these indicators.

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How to Cite
Ramiro Vásquez, E. (2012). When the assumption of homocedasticidad in variableswith binomial distribution fails. Cultivos Tropicales, 32(3), 63–68. Retrieved from https://ediciones.inca.edu.cu/index.php/ediciones/article/view/45
Issue
Vol. 32 No. 3 (2011)
Section
Original Article

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