Can the experimental study of religion be advanced using a Bayesian predictive framework?

Abstract

We propose a Bayesian framework as an important theoretical and methodological tool to improve the scientific study of religion. At a theoretical level, the Bayesian predictive processing framework has the potential to provide a unifying account of religious beliefs and experience by stressing the central role of error monitoring and error correction in belief maintenance. At a methodological level, Bayesian statistics are needed to provide the extraordinary evidence for the extraordinary theoretical claims regarding the causes and consequences of religion.