Fetal mortality: A descriptive statistical analysis to measure quantitative and qualitative variables
DOI:
https://doi.org/10.53591/iti.v12i12.173Keywords:
Fluctuations, fetal mortality, death, conceptionAbstract
The objective of this project is to establish whether there was an increase or a decrease in the fetal mortality rate, based on the place where their death was registered. In this way, the aim is to demonstrate the influence that the place of conception of a fetus may have on its mortality rate. The problem is that, in recent years, fetal deaths have suffered a worrying increase, the main fluctuations of which have been established mainly within certain cantons and suburban parishes. For the development of this project, the data will be compiled from the Excel database of the National Institute of Statistics and Census (INEC). All this information will be analyzed, and 3 qualitative and 3 quantitative variables will be extracted, these will be processed through statistical methods and, finally, they will be presented electronically through the use of the R-Studio software, a program that will allow the creation of contingency tables, frequency histogram and bar chart. From the results, it was obtained that the highest number of fetal deaths were registered in large cities such as Guayaquil, with the highest index being found in the northern area made up of the Tarqui parish. Furthermore, other factors such as the mother's month and age did not show any influence on fetal death. It is concluded that a fetal death can occur anywhere regardless of geographical factors, and that where there is a larger population there will also be a greater number of fetal deaths.
References
G. Castañeda-Casale, H. Márquez-González, y E. R. Rodr’iguez-Reyes, «Mortalidad perinatal en un hospital de segundo nivel de atención», Rev. Med. Inst. Mex. Seguro Soc., vol. 48, n.o 3, pp. 237-242, 2010.
J. Linares y R. Poulsen, «Muerte fetal in útero: Etiología y factores asociados en un hospital regional de Antofagasta, Chile», CIMEL Cienc. e Investig. Médica Estud. Latinoam., vol. 12, n.o 1, pp. 7-10, 2007.
H. Casanova, «Graficación Estadística y Visualización de Datos.», Ingeniería, vol. 21, n.o 3, pp. 54-75, 2017.
L. C. Torres, A. G. Rodríiguez, J. M. A. Cáceres, G. S. D. Veloz, M. K. B. Rivera, y R. M. A. Flores, «Análisis estadístico de correlación entre las dosis de eritropoyetina y el nivel de hemoglobina en pacientes con insuficiencia renal crónica», Rev. la Fac. Ciencias Médicas la Univ. Guayaquil, vol. 19, n.o 1, 2018.
L. Cevallos-Torres y M. Botto-Tobar, «Case study: Probabilistic estimates in the application of inventory models for perishable products in SMEs», en Problem-Based Learning: A Didactic Strategy in the Teaching of System Simulation, Springer, 2019, pp. 123-132.
C. Escalante y G. Arango, «Aspectos básicos del modelo de riesgo colectivo», Matemáticas Enseñanza Univ., vol. 12, n.o 2, pp. 3-15, 2004.
P. J. Ferrando y C. Anguiano-Carrasco, «El análisis factorial como técnica de investigación en psicología», Papeles del psicólogo, vol. 31, n.o 1, pp. 18-33, 2010.
M. N. Rodríguez y M. A. Ruiz, «Atenuación de la asimetría y de la curtosis de las puntuaciones observadas mediante transformaciones de variables: Incidencia sobre la estructura factorial», Psicológica Rev. Metodol. y Psicol. Exp., vol. 29, n.o 2, pp. 205-227, 2008.
M. Á. S. Ramos, «Uso metodológico de las tablas de contingencia en la ciencia política», Espac. públicos, vol. 8, n.o 16, pp. 60-84, 2005.
Downloads
Published
Issue
Section
License
Copyright (c) 2020 Cristopher D. Barreno, Moisés D. Gutiérrez
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
