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Perspect Psychol Sci. 2011 May;6(3):274-90. doi: 10.1177/1745691611406920.

Bayesian Versus Orthodox Statistics: Which Side Are You On?

Author information

1
School of Psychology, University of Sussex, Brighton, United Kingdom dienes@sussex.ac.uk.

Abstract

Researchers are often confused about what can be inferred from significance tests. One problem occurs when people apply Bayesian intuitions to significance testing-two approaches that must be firmly separated. This article presents some common situations in which the approaches come to different conclusions; you can see where your intuitions initially lie. The situations include multiple testing, deciding when to stop running participants, and when a theory was thought of relative to finding out results. The interpretation of nonsignificant results has also been persistently problematic in a way that Bayesian inference can clarify. The Bayesian and orthodox approaches are placed in the context of different notions of rationality, and I accuse myself and others as having been irrational in the way we have been using statistics on a key notion of rationality. The reader is shown how to apply Bayesian inference in practice, using free online software, to allow more coherent inferences from data.

KEYWORDS:

Bayes; evidence; likelihood principle; significance testing; statistical inference

PMID:
26168518
DOI:
10.1177/1745691611406920

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