Análisis bayesiano. Conceptos básicos y prácticos para su interpretación y uso

Mario Enrique Rendón-Macías, Alberto Riojas-Garza, Daniela Contreras-Estrada, José Darío Martínez-Ezquerro

Resumen


La estadística bayesiana se basa en la probabilidad subjetiva, trabaja con la actualización de la evidencia considerando los conocimientos adquiridos previos a una investigación, más la evidencia obtenida con esta. La interpretación de los resultados requiere la especificación de las hipótesis por contrastar y su probabilidad a priori antes del estudio. La evidencia del estudio se mide con el factor Bayes (razón de la compatibilidad de los datos bajo las hipótesis propuestas). La conjunción de las probabilidades a priori de las hipótesis con el factor Bayes permite calcular la probabilidad a posteriori de cada una. La hipótesis con mayor grado de certidumbre en su actualización es la aceptada para la toma de la decisión. En esta revisión se muestran tres ejemplos de hipótesis por contrastar: diferencia de promedios, correlación y asociación.


Palabras clave


Estadística de Bayes; Análisis bayesiano; Probabilidad subjetiva

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DOI: http://dx.doi.org/10.29262/ram.v65i3.512

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