Bayesian Versus Orthodox Statistics: Which Side Are You On?

Dienes, Zoltan

doi:10.1177/1745691611406920

Cited by 938Statistical Methods and Bayesian InferenceMeta-analysis and systematic reviewsProbability and Statistical Research

Bayesian Versus Orthodox Statistics: Which Side Are You On?

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Dienes, Zoltan·2011·Perspectives on Psychological Science

DOI 10.1177/1745691611406920

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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.

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A Bayesian approach might be more appropriate than Fisherian statistics as the Fisher approach is not appropriate with limited data.
“In terms of statistics, a Bayesian approach might be more appropriate than Fisherian statistics [56] as the Fisher approach is not appropriate with limited data [48].”
From Agile science: creating useful products for behavior change in the real world (2016) · cites this paper as [56]

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Authors: Dienes, Z.
Affiliations: University of Sussex (GB)
Corresponding author: Dienes, Zoltan
ORCID: Dienes, Zoltan
Venue: Perspectives on Psychological Science
Publisher: SAGE Publications
Published: 2011-05
Volume: 6
Issue: 3
Pages: 274-290
ISSN: 1745-6916 (ISSN-L)
1745-6924
DOI: 10.1177/1745691611406920
OpenAlex: W2055754299
Cited by: 938
References: 60
Citations by year: 2026: 25 · 2025: 35 · 2024: 39 · 2023: 46 · 2022: 64 · 2021: 99 · 2020: 87 · 2019: 84 · 2018: 98 · 2017: 82 · 2016: 76 · 2015: 68 · 2014: 48 · 2013: 42 · 2012: 33
FWCI: 6.30
Type: journal article
Language: en
Open access: green
figshare.com
Licence: cc-by
journals.sagepub.com/page/policies/text-and-data-mining-license (tdm)
Locations: Perspectives on Psychological Science (publishedVersion)
PubMed (publishedVersion)
Figshare (submittedVersion, cc-by)
Topics: Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
Physical Sciences › Mathematics › Statistics and Probability › Probability and Statistical Research
Keywords: Bayesian inference, significance testing, null hypothesis significance testing, multiple comparisons, stopping rules

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Bayesian Versus Orthodox Statistics: Which Side Are You On?

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