3 resultados para Métodos e Procedimentos Estatísticos

em Repositório Institucional da Universidade Federal do Rio Grande do Norte


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The current study presents the characteristics of self-efficacy of students of Administration course, who work and do not work. The study was conducted through a field research, descriptive, addressed quantitatively using statistical procedures. Was studied a population composed of 394 students distributed in three Higher Education Institutions, in the metropolitan region of Belém, in the State of Pará. The sampling was not probabilistic by accessibility, with a sample of 254 subjects. The instrument for data collection was a questionnaire composed of a set of questions divided into three sections: the first related to sociodemographic data, the second section was built to identify the work situation of the respondent and the third section was built with issues related to General Perceived Self-Efficacy Scale proposed by Schwarzer and Jerusalem (1999). Sociodemographic data were processed using methods of descriptive statistics. This procedure allowed characterizing the subjects of the sample. To identify the work situation, the analysis of frequency and percentage was used, which allowed to classify in percentage, the respondents who worked and those that did not work, and the data related to the scale of self-efficacy were processed quantitatively by the method of multivariate statistics using the software of program Statistical Package for Social Sciences for Windows - SPSS, version 17 from the process of Exploratory Factor Analysis. This procedure allowed characterizing the students who worked and the students who did not worked. The results were discussed based on Social Cognitive Theory from the construct of self-efficacy of Albert Bandura (1977). The study results showed a young sample, composed the majority of single women with work experience, and indicated that the characteristics of self-efficacy of students who work and students who do not work are different. The self-efficacy beliefs of students who do not work are based on psychological expectations, whereas the students who work demonstrated that their efficacy beliefs are sustained by previous experiences. A student who does not work proved to be reliant in their abilities to achieve a successful performance in their activities, believing it to be easy to achieve your goals and to face difficult situations at work, simply by invest a necessary effort and trust in their abilities. One who has experience working proved to be reliant in their abilities to conduct courses of action, although know that it is not easy to achieve your goals, and in unexpected situations showed its ability to solve difficult problems

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Embora tenha sido proposto que a vasculatura retínica apresenta estrutura fractal, nenhuma padronização do método de segmentação ou do método de cálculo das dimensões fractais foi realizada. Este estudo objetivou determinar se a estimação das dimensões fractais da vasculatura retínica é dependente dos métodos de segmentação vascular e dos métodos de cálculo de dimensão. Métodos: Dez imagens retinográficas foram segmentadas para extrair suas árvores vasculares por quatro métodos computacionais (“multithreshold”, “scale-space”, “pixel classification” e “ridge based detection”). Suas dimensões fractais de “informação”, de “massa-raio” e “por contagem de caixas” foram então calculadas e comparadas com as dimensões das mesmas árvores vasculares, quando obtidas pela segmentação manual (padrão áureo). Resultados: As médias das dimensões fractais variaram através dos grupos de diferentes métodos de segmentação, de 1,39 a 1,47 para a dimensão por contagem de caixas, de 1,47 a 1,52 para a dimensão de informação e de 1,48 a 1,57 para a dimensão de massa-raio. A utilização de diferentes métodos computacionais de segmentação vascular, bem como de diferentes métodos de cálculo de dimensão, introduziu diferença estatisticamente significativa nos valores das dimensões fractais das árvores vasculares. Conclusão: A estimação das dimensões fractais da vasculatura retínica foi dependente tanto dos métodos de segmentação vascular, quanto dos métodos de cálculo de dimensão utilizados

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Forecast is the basis for making strategic, tactical and operational business decisions. In financial economics, several techniques have been used to predict the behavior of assets over the past decades.Thus, there are several methods to assist in the task of time series forecasting, however, conventional modeling techniques such as statistical models and those based on theoretical mathematical models have produced unsatisfactory predictions, increasing the number of studies in more advanced methods of prediction. Among these, the Artificial Neural Networks (ANN) are a relatively new and promising method for predicting business that shows a technique that has caused much interest in the financial environment and has been used successfully in a wide variety of financial modeling systems applications, in many cases proving its superiority over the statistical models ARIMA-GARCH. In this context, this study aimed to examine whether the ANNs are a more appropriate method for predicting the behavior of Indices in Capital Markets than the traditional methods of time series analysis. For this purpose we developed an quantitative study, from financial economic indices, and developed two models of RNA-type feedfoward supervised learning, whose structures consisted of 20 data in the input layer, 90 neurons in one hidden layer and one given as the output layer (Ibovespa). These models used backpropagation, an input activation function based on the tangent sigmoid and a linear output function. Since the aim of analyzing the adherence of the Method of Artificial Neural Networks to carry out predictions of the Ibovespa, we chose to perform this analysis by comparing results between this and Time Series Predictive Model GARCH, developing a GARCH model (1.1).Once applied both methods (ANN and GARCH) we conducted the results' analysis by comparing the results of the forecast with the historical data and by studying the forecast errors by the MSE, RMSE, MAE, Standard Deviation, the Theil's U and forecasting encompassing tests. It was found that the models developed by means of ANNs had lower MSE, RMSE and MAE than the GARCH (1,1) model and Theil U test indicated that the three models have smaller errors than those of a naïve forecast. Although the ANN based on returns have lower precision indicator values than those of ANN based on prices, the forecast encompassing test rejected the hypothesis that this model is better than that, indicating that the ANN models have a similar level of accuracy . It was concluded that for the data series studied the ANN models show a more appropriate Ibovespa forecasting than the traditional models of time series, represented by the GARCH model