Bayesian data analysis

doi:10.1002/wcs.72

Bayesian data analysis

2010-04-28

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AI

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John K. Kruschke *

DOI：10.1002/wcs.72

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Bayesian methods have garnered huge interest in cognitive science as an approach to models of cognition and perception. On the other hand, Bayesian methods for data analysis have not yet made much headway in cognitive science against the institutionalized inertia of 20th century null hypothesis significance testing (NHST). Ironically, specific Bayesian models of cognition and perception may not long endure the ravages of empirical verification, but generic Bayesian methods for data analysis will eventually dominate. It is time that Bayesian data analysis became the norm for empirical methods in cognitive science. This article reviews a fatal flaw of NHST and introduces the reader to some benefits of Bayesian data analysis. The article presents illustrative examples of multiple comparisons in Bayesian analysis of variance and Bayesian approaches to statistical power. (C) 2010 John Wiley & Sons, Ltd. WIREs Cogn Sci 2010 1 658-676

Keywords:

SAMPLE-SIZE DETERMINATION

MODELING INDIVIDUAL-DIFFERENCES

STATISTICAL-INFERENCE

MULTIPLE COMPARISONS

SIMULATION

Bayesian data analysis

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