A Primer on p-Value Thresholds and α-Levels – Two Different Kettles of Fish

Norbert Hirschauer, Sven Grüner, Oliver Mußhoff, Claudia Becker

Published: 01.06.2021  〉 Volume 70 (2021), Number 2, 123-133  〉 Resort: Articles 
Submitted: 08.10.2020   〉 Feedback to authors after first review: 15.12.2020   〉 Accepted: 11.01.2021

ABSTRACT

It has often been noted that the “null-hypothesis-significance-testing” (NHST) framework is an inconsistent hybrid of Neyman-Pearson’s “hypothesis testing” and Fisher’s “significance testing” that almost inevitably causes misinterpretations. To facilitate a realistic assessment of the potential and the limits of statistical inference, we briefly recall widespread inferential errors and outline the two original approaches of these famous statisticians. Based on the understanding of their irreconcilable perspectives, we propose “going back to the roots” and using the initial evidence in the data in terms of the size and the uncertainty of the estimate for the purpose of statistical inference. Finally, we make six propositions that hopefully contribute to improving the quality of inferences in future research.
CONTACT AUTHOR
PROF. DR. NORBERT HIRSCHAUER
Martin-Luther-Universität Halle-Wittenberg
Institut für Agrar- und Ernährungswissenschaften
06120 Halle (Saale), Karl-Freiherr-von-Fritsch-Str. 4
e-mail: norbert.hirschauer@landw.uni-halle.de
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