What can psychology's statistics reformers learn from the error-statistical perspective?. (November 2020)

• Record Type: Journal Article
• Authors: Haig, Brian D.
• Is Part Of: Methods in psychology. Volume 2(2020)
• Publication Date: 2020-11
• Subjects: The error-statistical perspective -- The new statistics -- Bayesian statistics -- Falsificationism -- Hierarchy of models -- Philosophy of statistics; Psychology -- Periodicals; 150.5
• DOI: 10.1016/j.metip.2020.100020
• Languages: English
• ISSNs: 2590-2601

Abstract

Abstract: In this article, I critically evaluate two major contemporary proposals for reforming statistical thinking in psychology: The recommendation that psychology should employ the "new statistics" in its research practice, and the alternative proposal that it should embrace Bayesian statistics. I do this from the vantage point of the modern error-statistical perspective, which emphasizes the importance of the severe testing of knowledge claims. I also show how this error-statistical perspective improves our understanding of the nature of science by adopting a workable process of falsification and by structuring inquiry in terms of a hierarchy of models. Before concluding, I briefly discuss the importance of the philosophy of statistics for improving our understanding of statistical thinking.