A brief look into Bayesian statistics in cardiology data analysis

Abstract

ABSTRACT Bayesian statistics assesses probabilistically all sources of uncertainty involved in a statistical study and uses Bayes’ theorem to sequentially update the information generated in the different phases of the study. The characteristics of Bayesian inference make it particularly useful for the treatment of cardiological data from experimental or observational studies including different sources of variability, and complexity. This paper presents the basic concepts of Bayesian statistics associated with the estimation of parameters and derived quantities, new data prediction, and hypothesis testing. The latter in the context of model or theory selection.

Keywords

• Posterior distribution
• Prior distribution
• Predictive distribution
• Bayesian probability
• Bayes’ theorem