Pregrado Estadística
URI permanente para esta colecciónhttp://hdl.handle.net/11634/178
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Ítem Un modelo de Áreas Pequeñas para la Estimación del Promedio de Costos de Compra y Arrendamiento de Vivienda en Cada Unidad de Planeación Zonal de Bogotá(Universidad Santo Tomás, 2025-02-17) Rozo Álvarez, Angela Lucia; Tellez Pinerez, Cristian Fernando; Universidad Santo Tomás; https://scienti.minciencias.gov.co/cvlac/visualizador/generarCurriculoCv.do?cod_rh=0000016463; https://scienti.minciencias.gov.co/cvlac/visualizador/generarCurriculoCv.do?cod_rh=0001664845; https://orcid.org/0000-0003-3869-1831; https://orcid.org/0000-0001-5902-8460This research presents the estimates of the average costs of purchasing and renting housing in each Zonal Planning Unit of Bogota through the estimation in small areas, as well as data from the Multipurpose Survey 2021. It was estimated that the UPZs with the highest average cost are the Chapinero cluster: Chico Lago and El Refugio, Usaquén: Country Club and Santa Barbara and Usaquén. Additionally, the results are in line with the city's real estate structure in that the city's most prominent zones in the real estate sector are geographically consistent with those with the highest average.Ítem Evaluación y Optimización de la Inversión en Medios Publicitarios(Universidad Santo Tomás, 2024-06-09) Contreras Rodriguez, Nicolás; Sierra, Javier Mauricio; Universidad Santo Tomás; https://scienti.minciencias.gov.co/cvlac/visualizador/generarCurriculoCv.do?cod_rh=0001567974; https://scholar.google.com/citations?hl=es&user=WPVb1csAAAAJ; https://orcid.org/0009-0003-5914-4156In a volatile economic environment, many financial institutions have seen considerable fluctuations in their share prices following the launch of digital advertising campaigns. in their share prices following the launch of digital advertising campaigns. While these campaigns increase brand recognition, they are often associated with significant volatility in the market. This phenomenon underscores the importance of strategically aligning marketing efforts with financial objectives to mitigate risks and take advantage of opportunities. financial objectives in order to mitigate risks and take advantage of opportunities. Marketing in the banking sector is crucial not only for attracting new customers, but also for maintaining the loyalty of current and improving loyalty of existing customers and improve brand perception. Marketing investments can directly influence share price. directly influence stock prices. This study will analyze how investments in different advertising media specifically impact the stock performance of financial institutions. stock performance of financial institutions. Detailed data will be collected on advertising investments and stock prices. and stock prices will be collected. This data will be analyzed to forecast and optimize the long-term impact. long-term impact. In addition, optimization methods will be applied to determine the best allocation of the advertising portfolio and minimize risk. portfolio and minimize risk. A crucial aspect is the sensitivity and robustness of the model. Various approaches and techniques will be tested to ensure that the final recommendations are reliable and practical. Various methodologies will be evaluated to provide a holistic view. The results will provide valuable insights on how to maximize the return on marketing investment and improve financial performance through a well-planned strategy. In summary, the aim is to link marketing efforts with stock performance from a statistical point of view, offering practical data-driven recommendations to improve the effectiveness of advertising investments and strengthen the competitive position in the marketplace, as well as statistical results and procedures.Ítem Aplicación de Machine Learning para la Estimación de la Rotación de Empleados en el Sector BPO(Universidad Santo Tomás, 2024) Rey Guanumen, Camilo Andres; Sierra, Javier Mauricio; Universidad Santo Tomás; https://scienti.minciencias.gov.co/cvlac/visualizador/generarCurriculoCv.do?cod_rh=0001567974; https://scholar.google.es/citations?hl=es&user=WPVb1csAAAAJ; https://orcid.org/0009-0003-5914-4156This study uses applications of statistical techniques and Machine Learning for the study of employee turnover Business Process Outsourcing, in Human Resources terms, BPO (Business Process Outsourcing) involves In terms of Human Resources, BPO (Business Process Outsourcing) involves outsourcing certain outsourcing certain functions and processes related to human talent management to a company specialized in this service. This may include activities such as such as recruitment and selection, payroll administration, benefits management, training and development, HR benefits management, training and development, performance management, among others. Throughout this the variables that affect this phenomenon will be studied and a Machine Learning model will be created to Machine Learning model for the prediction of employee turnover will be created, with the objective of the costs associated with employee turnover and the negative effects it has at the organizational level. at the organizational level. Translated with DeepL.com (free version)Ítem Modelo Gam Espacial para la Tasa de Suicidio en los Departamentos de Colombia (2014-2019)(Universidad Santo Tomás, 2024) Sánchez Cardona, Brahian; Bermudez Rubio, Dagoberto; Universidad Santo Tomás; https://scienti.minciencias.gov.co/cvlac/visualizador/generarCurriculoCv.do?cod_rh=0000014678; https://orcid.org/0000-0002-2651-5665This study aims to analyze the behavior of suicide rates in Colombia by depart ment between 2014 and 2019 using a spatiotemporal beta model. This model seeks to capture both spatial and temporal dependencies, providing a clear view of the factors influencing suicide rates. Recognizing that the suicide rate follows a beta distribution, the analysis considers the separable space-time correlation. Socio economic information by department is included to understand how these factors affect variations in suicide rates at the regional level. The results show significant relationships between spatial effects and socioeconomic factors, while the temporal effect varies in its importance. This study helps identify spatiotemporal patterns in suicide rates, providing valuable information for the formulation of public policies and intervention strategies in Colombia.Ítem Predicciones del Número de Pasajeros de la Ruta 330 del SITP Utilizando Técnicas de Machine Learning: Random Forest y Silverkyte(Universidad Santo Tomás, 2024) Mesa Cantillo, Yanela Alexandra; Moreno Lopez, Edna Carolina; Universidad Santo Tomás; https://scienti.minciencias.gov.co/cvlac/visualizador/generarCurriculoCv.do?cod_rh=0001381730; https://scholar.google.es/citations?hl=es&user=3HPuekUAAAAJ; https://orcid.org/0000-0002-1364-0096This study utilizes data provided by Transmilenio, which includes access records to the services of the Integrated Public Transport System (SITP) corresponding to route 330 from the years 2020 to 2023. Various factors that could influence the users’ decision to use the SITP, such as holidays, weekends, and vacation periods, were analyzed. The main objective of this work is to understand the future demand for the use of the Integrated Public Transport System (SITP) through the analysis of passenger number data. Additionally, other relevant variables such as holidays, weekends, and vacation periods will be included to improve the model’s predictions.Ítem Aplicación del Algoritmo de Expectación-Maximización con Bootstrap para la Imputación de Indicadores en Modelos de Regresión Beta Multinivel Bayesianos con Enlace Logit: Un Análisis de Panel para Explicar la Relación del Gasto Público en Educación, el Factor Productivo Nacional y el Factor Demográfico sobre la Pobreza en Educación del 2015 al 2023(Universidad Santo Tomás, 2024) Montoya Casas, Michael Stibenson; Pacheco López, Mario José; Universidad Santo Tomás; https://scienti.minciencias.gov.co/cvlac/visualizador/generarCurriculoCv.do?cod_rh=0000775479; https://scholar.google.es/citations?hl=es&user=a5SEoPgAAAAJ; https://orcid.org/0000-0003-4752-703XIn 2015, the United Nations (UN) established 17 Sustainable Development Goals (SDGs), with the primary aim of eradicating poverty, ensuring prosperity, and protecting the environment. These goals have a follow-up and evaluation agenda until 2030. Using official national data, historical variables were identified related to education poverty indicators, public spending on education, demographic factors (population density and migration), and per capita gross domestic product (GDP) at the departmental level. To analyze education poverty data at the departmental level between 2015 and 2018, the Expectation-Maximization with Bootstrap algorithm was applied, improving the robustness of the model due to the lack of historical data. Subsequently, a Multilevel Beta Regression model with logit link was used to assess the relationship between education poverty and variables such as public spending, demographic factors, and economic production at the departmental level from 2015 to 2023. The results showed no significant relationship between population density and education poverty, while the relationship between public spending and education poverty proved to be significant and relevant. Furthermore, national economic production had a positive and important relationship with education poverty indicators. The study also highlighted inequality in access to education in peripheral departments of the country. Although public spending is higher in areas with worse indicators, the focus and control of resources still need improvement. Finally, it was demonstrated that the imputation through the EMB algorithm better captured trends and relevant information about the educational context in Colombia.Ítem Construcción de Modelos Predictivos para Clasificar Transacciones Legitimas o Fraudulentas Utilizando Algoritmos de Aprendizaje Automático(Universidad Santo Tomás, 2024-02-06) Blanco Soler, Sergio Alfredo; Rubriche Cardenas, Juan Carlos; Universidad Santo Tomás; https://scienti.minciencias.gov.co/cvlac/visualizador/generarCurriculoCv.do?cod_rh=0001343533; https://scienti.minciencias.gov.co/cvlac/visualizador/generarCurriculoCv.do?cod_rh=0001425785; https://orcid.org/0000-0001-6812-2838In the current era, the nature of transactions has evolved dramatically, shifting from traditional face-to-face interactions between cardholders and merchants to digital transactions through various channels, such as mobile applications, virtual banking, digital wallets, and electronic payment systems. This diversification has increased susceptibility to various forms of fraud, such as phishing, skimming, fraud by acquaintances, impersonation, and theft. These challenges have driven the need to implement more advanced tools than traditional rules to detect and prevent fraud. In this work, we address this challenge by proposing an approach based on supervised machine learning models. These models aim to detect fraudulent transactions in real-time or near real-time, minimizing false positives and alerting or declining transactions with a high likelihood of fraud.Ítem Estimación de la Tasa de Suicidio en Colombia por Departamento para el Período 2014-2019 Mediante Regresión Beta Clásica, Semi-paramétrica y Bayesiana(Universidad Santo Tomás, 2024-01-31) Jiménez Jiménez, Michelle Vanesa; Bermúdez Rubio, Dagoberto; Universidad Santo Tomás; https://scienti.minciencias.gov.co/cvlac/visualizador/generarCurriculoCv.do?cod_rh=0000014678; https://orcid.org/0000-0002-2651-5665This thesis examines suicide rates in Colombia, disaggregated by departments, during the period from 2014 to 2019. The estimation of these rates was conducted using generalized linear models and generalized additive models, addressing aspects of location, scale, and shape. It is noteworthy that the response variable, the suicide rate, assumes a beta distribution, so specifically, GLM, GAMLSS, and Bayesian beta models were employed for analysis. Additionally, Bayesian models were incorporated to enhance the analysis with an adaptive perspective based on observed and prior data. Socioeconomic information by department was included, allowing an understanding of these factors in the variations of suicide rates at the regional level. The aim is to comprehend the contextual determinants of suicide rates in ColombiaÍtem Extensión del Algoritmo ClustImpute para Variables Cualitativas y Mixtas: Una Aplicación al Capítulo de Cultivos de Bogotá D.C. del III Censo Nacional Agropecuario(Universidad Santo Tomás, 2023) Rojas Pulido, William Camilo; Pacheco Lopéz, Mario José; Universidad Santo Tomás; https://scienti.minciencias.gov.co/cvlac/visualizador/generarCurriculoCv.do?cod_rh=0000775479; https://scholar.google.com/citations?hl=es&user=a5SEoPgAAAAJ; https://orcid.org/0000-0003-4752-703XIn the current Colombian context marked by demographic, economic, and environmental changes, coupled with the significant role of the agricultural sector in the economy, the implementation of the III National Agricultural Census in 2014 emerges as a crucial tool to comprehend the multifaceted variables impacting this sector. With an operational coverage of 98.9%, this census provided detailed and updated information on the agricultural sector nationwide, including municipalities, indigenous territories, lands of black communities, and national parks. However, data analysis presents challenges such as the existence of 4% of records with missing data, which are addressed through statistical approaches like missing value imputation. Focusing on the Cultivation chapter in Bogotá, this work proposes the application of an extended version of the ClustImpute algorithm. By combining imputation techniques with the k-means method, this algorithm aims to address both quantitative and qualitative variables present in the census, offering an innovative alternative to conventional imputation methods. The ultimate goal is to provide a more comprehensive and reliable data analysis to contribute to the understanding and improvement of policies and efforts related to rural development and the quality of life in rural areas in Bogotá and, consequently, throughout the country.Ítem Estudio para la Proyección de Llamadas Recibidas en un Centro de Experiencia Telefónica de una Entidad Financiera(Universidad Santo Tomás, 2023-10-05) Ruiz Cotrino, Juan Pablo; Sánchez Segura, Deniz Andrea; https://scienti.minciencias.gov.co/cvlac/visualizador/generarCurriculoCv.do?cod_rh=0001657362; https://scholar.google.com/citations?hl=es&user=NO0xayoAAAAJ; https://orcid.org/0000-0001-9573-6704Currently, many companies worldwide use various communication channels to respond to customer inquiries and reach out to potential clients to offer products. Among these channels is telephone contact, as it is widely used by the majority of the population, enabling companies to expand their reach and the benefits they can offer. To facilitate this contact, there are several call centers that act as a link between the company and the end customer. However, one of the major challenges in operating these centers is determining call flows during a specific period, as it is difficult to predict when they will significantly increase or decrease. Additionally, the exact number of agents working is not always known, making it challenging to assess response effectiveness. Consequently, customers may experience dissatisfaction due to extended wait times and a lack of availability to address their calls. On the other hand, the organization also has uncertainties about agent distribution, such as how many agents are needed each day to ensure the highest level of service, when during the day call volumes decrease to schedule agent breaks, and to determine the average duration of each call.Ítem Modelo de Clasificación para los Anuncios en Tres Portales de Empleo de Colombia según la CIUO-08(Universidad Santo Tomás, 2023-10-04) Leon Rocha, Laura Nathalia; Pacheco López, Mario José; Universidad Santo Tomás; https://scienti.minciencias.gov.co/cvlac/visualizador/generarCurriculoCv.do?cod_rh=0000775479; https://scholar.google.com/citations?hl=es&user=a5SEoPgAAAAJ; https://orcid.org/0000-0003-4752-703XThe International Standard Classification of Occupations (ISCO) is a tool adopted by the International Conference of Labor Statisticians, which allows different types of jobs to be grouped through the activities and tasks of each of them. This work provides an overview of Machine Learning models for classification processes and Natural Language Processing (NLP) by implementing the Topic Modeling textual analysis tool in the descriptions of advertisements in three job portals in Colombia, with the aim of classifying them according to the ISCO to one digit. The classification methods Ada Boost, Naive Bayes, Random Forest, Knn, Decision Trees and Support Vector Machines are used to find the one that best fits the data and to properly order the ads. The Random Forest model was the one that had the greatest success in the nine binary models (one for each ISCO class), given that, for an advertisement, there are different professions that meet the requirements of the position.Ítem Determinación de Factores Causales de Deserción Escolar en el Municipio de Zipaquirá Mediante un Modelo de Regresión Logit(Universidad Santo Tomás, 2023-08-28) Rentería Guzmán, Matthew Enrique; Fonseca Gómez, Lida Rubiela; Beltrán Cortés, Oscar Javier; Universidad Santo Tomás; https://scienti.minciencias.gov.co/cvlac/visualizador/generarCurriculoCv.do?cod_rh=0000125977; https://scienti.minciencias.gov.co/cvlac/visualizador/generarCurriculoCv.do?cod_rh=0001823744; https://scholar.google.com/citations?hl=es&user=uwl_sDgAAAAJ; https://scholar.google.com/citations?hl=es&user=kg-6NCsAAAAJ; https://orcid.org/0000-0002-3597-728XSchool dropout is a problem that affects the development of a nation, since it affects the future of children, adolescents and young adults, since it increases the difficulty in obtaining stable and/or well-paid jobs. The study of the characteristics of school dropout has been the subject of permanent research carried out by the Ministry of National Education (MEN) whose advances and setbacks at the national level have been disclosed through technical reports such as its technical notes. The Zipaquirá Secretary of Education is no stranger to the issue of desertion, which is why it used to seek to measure this situation through the SIMPADE platform that worked until 2019. From 2020 to date, it does not have an adequate system to measure desertion, a situation which has had an impact on annual enrollment and other indicators. The present study seeks to identify the factors that most influence school dropout in the municipality of Zipaquirá, both in private and official schools, through the application of a Logit model to determine these factors.Ítem Aplicación de un Modelo Multinomial Logístico con Categorías Ordinales y Binarias para Estudiar los Homicidios Producidos en el Valle del Cauca Durante los Años 2016 al 2019(Universidad Santo Tomás, 2023-09-19) Novoa Acosta, Johnny Alexander; Bermúdez Rubio, Dagoberto; https://scienti.minciencias.gov.co/cvlac/visualizador/generarCurriculoCv.do?cod_rh=0000014678; https://orcid.org/0000-0002-2651-5665Homicide is a problem that has been latent in Valle del Cauca for many decades and has greatly permeated the history of this department; Located in the Colombian Pacific. Homicides (or also called intentional deaths or violent deaths) are events that are carried out for many reasons; that are associated with the settling of accounts, quarrels, theft, etc. This social situation, being so important, draws the attention of the national and international media every year due to its homicide rates and rates, which are sometimes worrying. For this reason, in this research an ordinal logistic multinomial model with different categories is implemented to analyze and characterize the violent deaths that occurred in the department of Valle del Cauca, Colombia, during the short period between 2016 and 2019. of schooling (illiterate, primary, secondary, technical/technologist and higher education) reached by the victims; It is proposed to model and identify the factors associated with these deaths and understand their influence and incidence in the region. Data from official sources are collected and relevant variables such as demographic, socioeconomic and geographical characteristics of the municipalities of Valle del Cauca are considered. These data areused to develop and fit the model, which allows one to examine the relationships between the predictor variables. The ordinal logistic multinomial model uses classical inferential statistical techniques and generalized linear models to estimate model parameters and provide uncertainty measures. for these estimates. The analysis of the results contributes to a better understanding of the factors associated with violent deaths in the region and provides valuable information for the design of social policies and crime prevention and control strategies in Valle del Cauca.Ítem Porcentaje Promedio de Horas Dedicadas al Cuidado de Adultos Mayores No Remunerados: Una Propuesta de Estimación Mediante una Estrategia de Muestreo Asistida por un Modelo de Regresión Beta en Bogotá-Colombia(Universidad Santo Tomás, 2023-09-19) Pascagaza Páez, Laura Viviana; Téllez Piñerez, Cristian Fernando; Rubriche Cárdenas, Juan Carlos; Pacheco López, Mario José; Universidad Santo Tomás; https://scienti.minciencias.gov.co/cvlac/visualizador/generarCurriculoCv.do?cod_rh=0000016463; https://scienti.minciencias.gov.co/cvlac/visualizador/generarCurriculoCv.do?cod_rh=0001343533; https://scienti.minciencias.gov.co/cvlac/visualizador/generarCurriculoCv.do?cod_rh=0000775479; https://scholar.google.com/citations?hl=es&user=PJ6JUFwAAAAJ; https://scholar.google.com/citations?hl=es&user=a5SEoPgAAAAJ; https://orcid.org/0000-0003-3869-1831; https://orcid.org/0000-0001-6812-2838; https://orcid.org/0000-0003-4752-703XUnpaid care is a topic of global interest that is made up of different aspects such as age, gender, economy, health status, among others; where it is generally women who assume the role of caregiver, sacrificing quality time for themselves, hindering the opportunity to be part of the workforce and causing deterioration in their health status. An estimate was made of the average proportion of time that Bogotá caregivers dedicate per week to caring for the elderly without remuneration, applying a sampling strategy assisted by a Beta regression model called BREG. The estimated average proportion of hours dedicated to caring for the elderly was 42.3% with a margin of error of 0.46%. Age, sex, health condition, hours spent watching television per week, type of occupancy of the home by the household, time spent traveling to the nearest medical center, time spent eating outside the home with friends or family and resorting to other people when they have economic problems were the significant variables for the construction of the model. A BREG estimate of the estimated mean proportion of hours dedicated to caring for the elderly was obtained with greater relative efficiency than the Horvitz–Thompson estimator. Unpaid care is an opportunity to improve existing public policies for the elderly and to create new government policies to reduce the physical and emotional burden of caregivers.Ítem Imputación de Valores Faltantes de Variables de Razón y/o Proporción Mediante Modelos de Regresión Beta Cero-uno Inflados(Universidad Santo Tomás, 2023-09-18) Parada, Adely Margarita; Pacheco López, Mario José; Universidad Santo Tomás; https://scienti.minciencias.gov.co/cvlac/visualizador/generarCurriculoCv.do?cod_rh=0000775479; https://scienti.minciencias.gov.co/cvlac/visualizador/generarCurriculoCv.do?cod_rh=0001815236; https://scholar.google.com/citations?hl=es&user=a5SEoPgAAAAJ; https://orcid.org/0000-0003-4752-703X; https://orcid.org/0000-0001-5513-0804In the data collected in recent decades, it is common to encounter the presence of missing values for multiple reasons, which can lead researchers to use incorrect strategies to handle them, resulting in incorrect inferences. This problem is much more common in ratio and proportion variables, as most multiple imputation methods do not take into account the nature of these types of variables. In the literature, there are models for this type of variable, such as Beta regression models, which can be used to construct multiple imputation models. Given this need, the present work proposes to develop a function in the R software that uses multiple imputation methods with inflated zero-one Beta regression models to allow for the correct implementation of imputation for proportion and/or ratio variables.Ítem Análisis de Modelos para la Mezcla de Marketing desde la Perspectiva de Regresión Múltiple para una E-Wallet entre los Años 2019 y 2022(Universidad Santo Tomás, 2023-02-05) Pinzón Camacho, Cristian Camilo; Pacheco Lopéz, Mario José; Universidad Santo Tomás; https://scienti.minciencias.gov.co/cvlac/visualizador/generarCurriculoCv.do?cod_rh=0000775479; https://scholar.google.com/citations?hl=es&user=a5SEoPgAAAAJ; https://orcid.org/0000-0003-4752-703XIn marketing, the appropriate allocation of resources in the different ways of making yourself known to end users has become a difficult calculation to work out and understand. Even more so, in recent times, with the emergence of new dynamics through digital channels that increase the complexity of the problem. Statistics has generated several mechanisms to address this type of analytical problems, trying to explain the real behavior of the variable of interest. The marketing mix model has adequate procedures to expose the combinations that increase the performance of the efforts made by an advertiser consigned in several variables. This work attempts a strategy that helps to define which variables, transformations and model, based on regression, allow to find the best combination, giving optimal results of the model that are sufficient to predict the most convenient marketing mix.Ítem Propuesta de un Método de Imputación Múltiple para Variables de Tasas y Proporciones(Universidad Santo Tomás, 2023-02-03) Avila León, Mario; Pacheco López, Mario José; Universidad Santo Tomás; https://scienti.minciencias.gov.co/cvlac/visualizador/generarCurriculoCv.do?cod_rh=0000775479; https://scholar.google.com/citations?hl=es&user=a5SEoPgAAAAJ; https://orcid.org/0000-0003-4752-703XMissing data analysis is oriented to the investigation and application of statistical methods, that allow working with data sets, with missing information. By means of statistical estimation processes, the missing values in a database (or sample), can be replaced with values obtained in this process; and achieve a database with complete information. Something ideal for a researcher; having the complete data is a guarantee to consider all the information of the sample. For this reason, obtaining a good estimate of the missing values, allows to improve the analysis; on the contrary, replacing the missing values with biases in their estimation can generate inadequate valuations in an analysis. The methods and processes for missing data, imputation improve their power according to the behavior of the data and the information observed. Therefore, imputation methods can be applied to variables that meet some conditions to ensure an adequate estimation. This paper, proposes to estimate missing values for ratio or rate variables, with a Beta regression model.Ítem Obesidad Mórbida en Adultos Mayores de 60 Años a partir de un Modelo de Lógica Difusa(Universidad Santo Tomás, 2022) Cruz Suta, María Alejandra; Romero, Gil Robert; Universidad Santo Tomás; https://scienti.minciencias.gov.co/cvlac/visualizador/generarCurriculoCv.do?cod_rh=0000157060; https://scienti.minciencias.gov.co/cvlac/visualizador/generarCurriculoCv.do?cod_rh=0001676363; https://scholar.google.com/citations?hl=es&user=LUEZqaYAAAAJ; https://orcid.org/0000-0001-8602-6890Morbid obesity is a disease that has been growing over the years, becoming a world-class problem. In adults over 60 years old, who due to their pace and quality of life suffer from chronic diseases, overweight can prevent their treatment to be managed as planned, that is why, through a logical difusion model, rules are developed to evaluate organic factors that increase the probability that a person over 60 years old suffers from metabolic syndrome.Ítem Una Aplicación del Modelo Beta para Analizar la Relación entre el Índice de Satisfacción ACSI con Variables del Sector Bancario(Universidad Santo Tomás, 2023-02-01) Cala Betancourt, Audrey Valentina; Tellez Piñerez, Cristian Fernando; https://scienti.minciencias.gov.co/cvlac/visualizador/generarCurriculoCv.do?cod_rh=0000016463; https://scholar.google.com/citations?hl=es&user=PJ6JUFwAAAAJ; https://orcid.org/0000-0003-3869-1831Through the use of a multivariate econometric model measured annually, a study was carried out in which the ACSI model (American Customer Satisfaction Index) is taken into account, which reveals the customer satisfaction index compared to an economic sector, this model contains latent variables. such as service satisfaction, repurchase intention, perceived quality, general expectations, and recommendation; Initially, some possible variables that can influence the banking sector were inquired about and thus be able to compare them against the satisfaction index, which was obtained from the "Banking Sector" database authorized by the company "Customer Index Value" (CIV) and to be able to generate the database with which said analysis was carried out. For the following, five (5) banks are taken into account, for each bank, the satisfaction index measured by the ACSI model is obtained together with some variables that influence the banking sector, such as interest rates per product, among others. Finally, a beta linear regression model is applied with the variable of interest and the auxiliary variables, where the main focus is to find the relationship that the satisfaction index may have compared to the other variables that were worked on and thus be able to conclude if these variables influence directly on the customer satisfaction index.Ítem Implementación de Modelos en la Estimación de Contagios para Covid-19 en Bogotá(Universidad Santo Tomás, 2021-08-01) Santiago Villabon, Hans David; Pineda Rios, Wilmer Dario; Universidad Santo Tomás; https://scienti.minciencias.gov.co/cvlac/visualizador/generarCurriculoCv.do?cod_rh=0001454199; https://orcid.org/ 0000-0001-7774-951XCovid-19 (SARS-CoV-2) or also known as Coronavirus is a pandemic disease that broke out at the end of 2020, the disease had an accelerated spread around the world, in the city of Bogotá the first case of Covid-19 on February 26, 2020, in a 19-year-old woman who came from Milan, Italy, from that moment on, different prevention and protection measures began to be carried out, however the efforts did not completely stop the accelerated spread of the disease throughout the Colombian capital, that is why the project seeks to analyze and estimate through different statistical methods and data analysis the behavior of this disease in the city of Bogotá from its first case in February 2020 until As reported in mid-June 2021.