987 resultados para Investigació -- Catalunya
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”compositions” is a new R-package for the analysis of compositional and positive data. It contains four classes corresponding to the four different types of compositional and positive geometry (including the Aitchison geometry). It provides means for computation, plotting and high-level multivariate statistical analysis in all four geometries. These geometries are treated in an fully analogous way, based on the principle of working in coordinates, and the object-oriented programming paradigm of R. In this way, called functions automatically select the most appropriate type of analysis as a function of the geometry. The graphical capabilities include ternary diagrams and tetrahedrons, various compositional plots (boxplots, barplots, piecharts) and extensive graphical tools for principal components. Afterwards, ortion and proportion lines, straight lines and ellipses in all geometries can be added to plots. The package is accompanied by a hands-on-introduction, documentation for every function, demos of the graphical capabilities and plenty of usage examples. It allows direct and parallel computation in all four vector spaces and provides the beginner with a copy-and-paste style of data analysis, while letting advanced users keep the functionality and customizability they demand of R, as well as all necessary tools to add own analysis routines. A complete example is included in the appendix
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En la parte I se pretende constatar los resultados de la Prueba de Acceso para mayores de 25 a??os. Realizar un seguimiento de los matriculados en los distintos centros universitarios y rastreo de sus resultados acad??micos. Parte II: conocimiento de las caracter??sticas m??s relevantes de los sujetos. En la parte I: todos los sujetos matriculados en la Prueba de Acceso para mayores de 25 a??os en el per??odo estudiado, 3728 sujetos. Parte II: se considera una poblaci??n de 395 matriculados en la Universidad, de los cuales cumplimentaron el cuestionario 131 sujetos (muestra). En la parte I se midieron las variables relacionadas con la Prueba de Acceso: matriculados, presentados, abandonos, aptos y las referentes a los resultados obtenidos en la Universidad (abandonos, traslados, titulados). En la parte II existen tres grandes grupos de variables: de identificaci??n, de selecci??n y motivaci??n hacia los estudios universitarios, de valoraci??n de la prueba, de decisi??n a la hora de elegir carrera, de valoraci??n de la Universidad y los estudios realizados, de autoconcepto y, por ??ltimo, las referentes a los factores que influyeron en los resultados acad??micos obtenidos. En la parte II se utiliz?? un cuestionario dise??ado para esta investigaci??n en el que se indagan cuestiones referentes a las variables se??aladas en el punto anterior. En la parte I se utilizaron las relaciones de matriculados, presentados y aptos en la prueba del Vicerrectorado de estudiantes. Expedientes de los alumnos que accedieron a trav??s de esta prueba localizados en los archivos de las Secretar??as de la universidad. Coeficientes de contingencia para ver la asociaci??n de algunas de las variables de estudio: motivos de estudio y carrera seleccionada, situaci??n laboral y motivos de estudio, nivel de preparaci??n de cara a la prueba y consideraciones acerca del grado de dificultad de la misma. S??lo un promedio del 18 por ciento de los sujetos presentados logran superar la Prueba de Acceso a la Universidad para mayores de 25 a??os. Entre estos sujetos la carrera m??s seleccionada a la hora de matricularse es la de Derecho, 67 por ciento la eligen. La extracci??n social de estas personas, dada por el nivel cultural y ocupacional de los padres, es de estratos bajos o medios. La mayor dificultad que encuentran a la hora de realizar estudios en la Universidad es la falta de tiempo para el estudio personal, manifestada por el 76 por ciento. La tasa de abandono de los estudios en este colectivo es alta un 60 por ciento. El porcentaje de los que logran terminar sus estudios es del 14 por ciento. Se constata: la necesidad de proceder a un an??lisis de la Prueba de Acceso, de la configuraci??n de los tribunales y de los criterios seguidos a la hora de fijar los ex??menes, de cara a adecuarlos a las exigencias de las posteriores ense??anzas universitarias. La necesidad de efectuar en otros distritos investigaciones de similares caracter??sticas para poder efectuar un estudio m??s completo y explicativo y, la posibilidad de un estudio de car??cter sociol??gico sobre este colectivo.
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We shall call an n × p data matrix fully-compositional if the rows sum to a constant, and sub-compositional if the variables are a subset of a fully-compositional data set1. Such data occur widely in archaeometry, where it is common to determine the chemical composition of ceramic, glass, metal or other artefacts using techniques such as neutron activation analysis (NAA), inductively coupled plasma spectroscopy (ICPS), X-ray fluorescence analysis (XRF) etc. Interest often centres on whether there are distinct chemical groups within the data and whether, for example, these can be associated with different origins or manufacturing technologies
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Presentation in CODAWORK'03, session 4: Applications to archeometry
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Developments in the statistical analysis of compositional data over the last two decades have made possible a much deeper exploration of the nature of variability, and the possible processes associated with compositional data sets from many disciplines. In this paper we concentrate on geochemical data sets. First we explain how hypotheses of compositional variability may be formulated within the natural sample space, the unit simplex, including useful hypotheses of subcompositional discrimination and specific perturbational change. Then we develop through standard methodology, such as generalised likelihood ratio tests, statistical tools to allow the systematic investigation of a complete lattice of such hypotheses. Some of these tests are simple adaptations of existing multivariate tests but others require special construction. We comment on the use of graphical methods in compositional data analysis and on the ordination of specimens. The recent development of the concept of compositional processes is then explained together with the necessary tools for a staying- in-the-simplex approach, namely compositional singular value decompositions. All these statistical techniques are illustrated for a substantial compositional data set, consisting of 209 major-oxide and rare-element compositions of metamorphosed limestones from the Northeast and Central Highlands of Scotland. Finally we point out a number of unresolved problems in the statistical analysis of compositional processes
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First discussion on compositional data analysis is attributable to Karl Pearson, in 1897. However, notwithstanding the recent developments on algebraic structure of the simplex, more than twenty years after Aitchison’s idea of log-transformations of closed data, scientific literature is again full of statistical treatments of this type of data by using traditional methodologies. This is particularly true in environmental geochemistry where besides the problem of the closure, the spatial structure (dependence) of the data have to be considered. In this work we propose the use of log-contrast values, obtained by a simplicial principal component analysis, as LQGLFDWRUV of given environmental conditions. The investigation of the log-constrast frequency distributions allows pointing out the statistical laws able to generate the values and to govern their variability. The changes, if compared, for example, with the mean values of the random variables assumed as models, or other reference parameters, allow defining monitors to be used to assess the extent of possible environmental contamination. Case study on running and ground waters from Chiavenna Valley (Northern Italy) by using Na+, K+, Ca2+, Mg2+, HCO3-, SO4 2- and Cl- concentrations will be illustrated
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The use of perturbation and power transformation operations permits the investigation of linear processes in the simplex as in a vectorial space. When the investigated geochemical processes can be constrained by the use of well-known starting point, the eigenvectors of the covariance matrix of a non-centred principal component analysis allow to model compositional changes compared with a reference point. The results obtained for the chemistry of water collected in River Arno (central-northern Italy) have open new perspectives for considering relative changes of the analysed variables and to hypothesise the relative effect of different acting physical-chemical processes, thus posing the basis for a quantitative modelling
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Kriging is an interpolation technique whose optimality criteria are based on normality assumptions either for observed or for transformed data. This is the case of normal, lognormal and multigaussian kriging. When kriging is applied to transformed scores, optimality of obtained estimators becomes a cumbersome concept: back-transformed optimal interpolations in transformed scores are not optimal in the original sample space, and vice-versa. This lack of compatible criteria of optimality induces a variety of problems in both point and block estimates. For instance, lognormal kriging, widely used to interpolate positive variables, has no straightforward way to build consistent and optimal confidence intervals for estimates. These problems are ultimately linked to the assumed space structure of the data support: for instance, positive values, when modelled with lognormal distributions, are assumed to be embedded in the whole real space, with the usual real space structure and Lebesgue measure
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Averiguar cu??les son las actitudes y opiniones de profesores y alumnos ante los problemas universitarios propios de su Facultad o Escuela, los objetivos de la Ense??anza Universitaria y sus problemas espec??ficos a la hora de ense??ar o aprender. 1448 alumnos que suponen el 5,39 por ciento de la poblaci??n, lo que posibilita trabajar a un nivel de confianza del 95 por ciento con un error muestral de 2,62; la muestra se seleccion?? por afijaci??n proporcional en facultades o escuelas y dentro de ??stas, por cursos. La muestra de profesores es de 148 sujetos, un 12,33 por ciento de la poblaci??n, lo que posibilita que a un nivel de confianza del 95 por ciento se trabaje con un error muestral de 7,98; la selecci??n de la muestra se realiz?? por departamentos y dentro de ellos se eligieron al azar los profesores. Se consideran las siguientes variables: -Contextuales: tipo de centro, ciudad, carrera, experiencia docente. -Personales: sexo, edad, suspensos, beca. -Actitudes hacia: evaluaci??n, organizaci??n y planificaci??n, alumnos, planes de estudio, ense??anza, recursos, instalaciones. -Opiniones sobre: la Universidad, el profesorado, los alumnos, la ense??anza. Problemas espec??ficos de profesores y alumnos en el ejercicio de su tarea. Desde la perspectiva de los profesores el objetivo primordial de la Universidad el formar profesionales, se??alando en segundo lugar la funci??n de elevar el nivel cultural; los estudiantes invierten el orden de estas funciones. Los profesores se??alan como uno de los mayores problemas la falta de recursos y la mala planificaci??n; los alumnos invierten nuevamente este orden. Los profesores proponen una elevaci??n de recursos y los alumnos vincular m??s los contenidos de las ense??anzas con las demandas actuales en el campo laboral. Los alumnos achacan sus principales dificultades a la falta de preparaci??n del profesor y los profesores a la falta de medios. Respecto a las metodolog??as los profesores prefieren la realizaci??n de actividades en peque??os grupos y los alumnos se inclinan por los trabajos de tipo pr??ctico. Se proponen actuaciones a tres niveles: Universidad: creaci??n de equipos de trabajo mixtos en los que se discutan los datos de esta investigaci??n para dise??ar estrategias de cambio. Cada centro: el mismo proceso. Organismos como el COIE y el ICE: actuaciones como las de orientaci??n a los alumnos o Formaci??n Pedag??gica del profesorado para paliar alguno de los problemas que plantean.
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Libro elaborado por un grupo de maestros de las escuelas rurales con el que se quiere aportar una visi??n distinta del entorno, trat??ndolo desde el medio rural se quiere dar una ayuda al maestro en su tarea de investigaci??n en el aula. Se contemplan los siguientes apartados: Situaci??n de mi localidad; medios de transportes y v??as de acceso; viviendas y edificios; poblaci??n; servicios y zonas de recreo; econom??a; cultura; geograf??a del entorno y ecolog??a del entorno. Cada apartado consta de los siguientes puntos: objetivos, contenidos, actividades y bibliograf??a para preescolar, ciclo inicial y ciclo medio.
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Hydrogeological research usually includes some statistical studies devised to elucidate mean background state, characterise relationships among different hydrochemical parameters, and show the influence of human activities. These goals are achieved either by means of a statistical approach or by mixing models between end-members. Compositional data analysis has proved to be effective with the first approach, but there is no commonly accepted solution to the end-member problem in a compositional framework. We present here a possible solution based on factor analysis of compositions illustrated with a case study. We find two factors on the compositional bi-plot fitting two non-centered orthogonal axes to the most representative variables. Each one of these axes defines a subcomposition, grouping those variables that lay nearest to it. With each subcomposition a log-contrast is computed and rewritten as an equilibrium equation. These two factors can be interpreted as the isometric log-ratio coordinates (ilr) of three hidden components, that can be plotted in a ternary diagram. These hidden components might be interpreted as end-members. We have analysed 14 molarities in 31 sampling stations all along the Llobregat River and its tributaries, with a monthly measure during two years. We have obtained a bi-plot with a 57% of explained total variance, from which we have extracted two factors: factor G, reflecting geological background enhanced by potash mining; and factor A, essentially controlled by urban and/or farming wastewater. Graphical representation of these two factors allows us to identify three extreme samples, corresponding to pristine waters, potash mining influence and urban sewage influence. To confirm this, we have available analysis of diffused and widespread point sources identified in the area: springs, potash mining lixiviates, sewage, and fertilisers. Each one of these sources shows a clear link with one of the extreme samples, except fertilisers due to the heterogeneity of their composition. This approach is a useful tool to distinguish end-members, and characterise them, an issue generally difficult to solve. It is worth note that the end-member composition cannot be fully estimated but only characterised through log-ratio relationships among components. Moreover, the influence of each endmember in a given sample must be evaluated in relative terms of the other samples. These limitations are intrinsic to the relative nature of compositional data
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Hungary lies entirely within the Carpatho-Pannonian Region (CPR), a dominant tectonic unit of eastern Central Europe. The CPR consists of the Pannonian Basin system, and the arc of the Carpathian Mountains surrounding the lowlands in the north, east, and southeast. In the west, the CPR is bounded by the Eastern Alps, whereas in the south, by the Dinaridic belt. (...)