Departamento De Estadistica

En el presente estudio se analiza la relación existente entre el Rendimiento o resultado organizacional y los Puntos Calientes en una carrera de pregrado en la Universidad del Bío-Bío en Chile. Dadas las competencias de aspectos organizacionales ya adquiridas por los estudiantes de la carrera ingeniería comercial, la población muestreada estuvo constituida por los 260 estudiantes de los tres últimos niveles de la carrera. De ésta se obtuvo una muestra probabilística de 154 individuos correspondiente al 60% de la población. Para lograr los objetivos se aplicó un instrumento de 26 ítems que está estructurado en base a las dimensiones que constituyen el Modelo Gratton. El análisis del modelo Gratton mostró el surgimiento de Puntos Calientes principalmente de la relación entre el propósito vivificante y la capacidad productiva, dadas por las competencias, habilidades y destrezas, que llevarán a las personas a ser más productivas.

Bivariate count data arise in several different disciplines and the bivariate Poisson distribution is commonly used to model them. This paper proposes and studies a computationally convenient goodness-of-fit test for this distribution, which is based on an empirical counterpart of a system of equations. The test is consistent against fixed alternatives. The null distribution of the test can be consistently approximated by a parametric bootstrap and by a weighted bootstrap. The goodness of these bootstrap estimators and the power for finite sample sizes are numerically studied. It is shown that the proposed test can be naturally extended to the multivariate Poisson distribution.

Global climate change will have a greater impact on ectotherms in tropical and subtropical communities than at higher latitudes, because ambient temperatures are closer to the upper thermal limits of species. Amphibian species are highly dependent on external weather conditions, and the effect of global warming on these has been evaluated recently. The Great Chilean frog (Calyptocephalella gayi) is an endemic, monotypic species and genus whose conservation status is considered Vulnerable because of high extraction pressure for human consumption, lack of regulatory measures and comprehension by its consumers. Their populations have also declined due to the loss and destruction of their habitats. C. gayi has not been considered as an object of physiological study, so this large species is not known as one that can adapt to current environmental changes. In this study we analyze the thermoregulatory capacity and thermal efficiency of C. gayi to determine its potential for climatic adaptation.

This paper studies goodness-of-fit tests for the bivariate Poisson distribution. Specifically, we propose and study several Cramér-von Mises type tests based on the empirical probability generating function. They are consistent against fixed alternatives for adequate choices of the weight function involved in their definition. They are also able to detect local alternatives converging to the null at a certain rate. The bootstrap can be used to consistently estimate the null distribution of the test statistics. A simulation study investigates the goodness of the bootstrap approximation and compares their powers for finite sample sizes. Extensions for testing goodness-of-fit for the multivariate Poisson distribution are also discussed.

Bivariate count data arise in several different discipline s and the bivariate Poisson distribution is commonly used to model them. This paper proposes and studies a computationally convenient goodness-of-fit test for this distribution, which is based o n an empirical counterpart of a system of equations. The test is consistent against fixed alternative s. The null distribution of the test can be consistently approximated by a parametric bootstrap and by a weighted bootstrap. The goodness of these bootstrap estimators and the power for finite sample sizes are numerically studied. It is shown that the proposed test can be naturally extended to the multivariate Poisson distribution

A two-dimensional mathematical model, based on the finite-difference method of calculating heat transfer, has been developed to simulate the temperature in a cylindrical storage silo containing malting barley. To validate the model, a real silo approximately 23.5 meters high and 6.3 meters in diameter was used, unlike the other investigations related to the subject, which have used tower silos with at most 3.76 meters in diameter and 5.5 meters in height. These two scenarios are quite different, since it is known that climatological variables are very different as height increases. The model has been programmed in Visual Basic for applications in Excel, compatible with microcomputers, which enables a good display for computer simulation of temperature and an excellent report of results, through linked graphs. The study allows to conclude that the model predicted the temperature with a standard error of approximately between 6.6 and 12.4%, depending on the depth. In addition, the simulation of temperatures can be done without the need to consider the weather station, because statistically, the seasons of the year turned out to be not significant for the temperature of the stored barley.