The widespread misinterpretation ofp-values as error probabilities

DOI10.1080/02664763.2011.567245OpenAlexW2023524008MaRDI QIDQ5124943

Raymond Hubbard

Publication date: 30 September 2020

Published in: Journal of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/02664763.2011.567245

zbMATH Keywords

\(p\)-valuessignificance testFisherNeyman-Pearson\( \alpha\) levels\(p<\alpha\) criterion`data-adjusted' type I errors

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items (1)

What type of Type I error? Contrasting the Neyman-Pearson and Fisherian approaches in the context of exact and direct replications

Uses Software

• SPSS

Cites Work

• The logical foundations of statistical inference
• Could Fisher, Jeffreys and Neyman have agreed on testing? (With comments and a rejoinder).
• Testing precise hypotheses. With comments and a rejoinder by the authors
• Testing a Point Null Hypothesis: The Irreconcilability of P Values and Evidence
• Of what use are tests of significance and tests of hypothesis
• P-Values: Interpretation and Methodology
• Statistical Evidence
• P Values for Composite Null Models
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