Estimate and Prediction with Cubic Regression Model Applied to a Health Problem

Diego Cardona

Universidad del Rosario

Miller Rivera

Universidad del Rosario

Javier González
Edwin Cárdenas

Corporación Universitaria, CUN

The article corresponds to a research project carried out at the School of Administration of the Universidad del Rosario, aimed at strengthening the use of inferential linear, nonlinear and multiple regression methods in decision-making processes by creating didactic materials aimed at students, teachers and researchers. This article shows the advantages of the third order polynomic regression model and its application in administration and science, through the development of a real case applied to health, in which the percentage of women who consume more than 20 cigarettes per day is estimated according to age. As part of the research project begun during the second half of 2012, diverse didactic guides have been published, including research documents such as: “An Approach using the Aleatorical Variable in Decision-Making Processes that Imply Conditions of Risk and Uncertainty” (“Una aproximación de la variable aleatoria a procesos de toma de decisión que implican condiciones de riesgo e incertidumbre”), “Application of Poisson Tails in ‘Decision-making Processes’ for Managing Medical Services” (“Aplicación de cola de Poisson en la gestión de servicios médicos”) and statistical inference guides for linear and nonlinear regression methods.

Keywords: statistical inference, non-linear regression, cubic model, estimate, prediction
Published
2014-12-01
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https://plu.mx/plum/a/?doi=10.16925/in.v9i17.828