Maestría en Matemática Aplicada
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Item Modelo matemático para determinar la calidad de servicio en el transporte público urbano en la ciudad de Ambato(Universidad Técnica de Ambato. Facultad de Ingeniería en Sistemas, Electrónica e Industrial. Maestría en Matemática Aplicada, 2021) Toscano Ramos, Orlando Ruben; Benalcázar Palacios, Freddy GeovannyThis research is quantitative, descriptive and correlational. The objective was to build a mathematical model that allows determining the quality of the urban public transport service in the city of Ambato in the period 2020 - 2021. The data were obtained through the survey technique with its instrument the questionnaire, the same as applied to 400 users who use public transport in the city of Ambato. To achieve the objectives proposed in the research, the binary logistic regression model was applied, which helps to classify and predict the quality of the urban public transport service in the city of Ambato The variables involved in this research were: as a dependent variable the quality of the service and as predictive or independent variables: the waiting time, the treatment of the user, the current state of the units and the way of driving of the carrier. For the processing and analysis of the data, the Microsoft Excel 2016 program and the free software RStudio version 4.0.1 were used. It is concluded that the constructed logistic regression model correctly adjusts to the predictor variables, the decision frontier yielded by the model was 0.6142 or 61.42%, which is used to determine the quality of the safe and unsafe service. The model correctly classifies 308 observations, of which 205 observations are classified as safe, representing 51.25% of the total data, while 103 observations were classified as unsafe, which is equivalent to 25.75%. With the analysis carried out, it was determined that the urban public transport of the city of Ambato is moderately safe, for which the pertinent authorities should place emphasis on improving the quality of the service.Item Diseño de un modelo matemático para estimar la deserción estudiantil mediante técnicas de análisis multivariado en una institución de educación superior tecnológica(Universidad Técnica de Ambato. Facultad de Ingeniería en Sistemas, Electrónica e Industrial. Maestría en Matemática Aplicada, 2021) Vinueza López, Cristina Nataly; Loza Aguirre, Edison FernandoEXECUTIVE SUMMARY In this research, a logistic regression model was used to estimate student dropout from the IST Luis A. Martínez Agronómico. The data of 849 students registered in the institute between 2018 and 2020 was used to build the model. The independent variables considered for the model were: gender, marital status, age, career, repetition, occupation and economic status. We used the KDD methodology to estimate the mathematical model, which allows generating information from a database with the records to be studied. In the evaluated period, 82.45 percent of the students did not dropout but 17.55 percent did it. In the study, four logistic regression models were established, the first one includes all the independent variables but only the ‘career’ variable was significant. The ‘age’ and ‘gender’ variables were eliminated (higher p-value) for generating a second logistic regression model, where the ‘repetition’ and ‘career’ variables were considered significant. Subsequently, the highest p-value variables, ‘marital status’ and ‘economic status’ were eliminated for obtaining a third logistic regression model wherein the ‘repetition’ and ‘career’ variables were the only significant ones. Finally, it was chosen the logistic regression model 4, which only includes the career and repetition variables as the only significant ones. The null hypothesis was rejected because the coefficients Beta 1 and Beta 2 of the variables ‘career’ and ‘repetition’ aren´t zero. The logistic regression model 4 correctly classified 83 percent of the training data and 79 percent of the test data. Additionally, we build a prediction model based on decision trees, which established ‘career’ as a unique explanatory variable. The F1_Score value of the logistic regression model 4 was higher than the F1_Score value of the decision tree model.Item Modelado matemático predictivo para la sostenibilidad de los emprendimientos productivos(Universidad Técnica de Ambato. Facultad de Ingeniería en Sistemas, Electrónica e Industrial. Maestría en Matemática Aplicada, 2021) Luzuriaga Jaramillo, Héctor Alberto; Ponsot Balaguer, Ernesto AntonioExecutive Summary Models that explain and predict failure and success are very valuable to entrepreneurs in the production sector. The implementation of an explanatory and predictive mathematical - statistical model is presented for the study of the sustainability of productive enterprises in the Cevallos, Quero, Mocha, Patate and Tisaleo cantons of the province of Tungurahua, Ecuador. A logistic regression model is proposed and adjusted on a sample of 1546 entrepreneurs. The variable selection method is stepwise which, following the parsimonious principle, incorporates only the variables that are significant. The deviance goodness-of-fit test suggests that such a model fits the data appropriately. Several hypotheses are checked and discussed, the most important result being the demonstration that there are factors that can be used to explain the success of productive entrepreneurs. These are: Instruction, time of the undertaking, staff, canton and if it has been suspended.