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Can I read What Can Psychology's Statistics Reformers Learn from the Error-statistical Perspective? on EtoBox?
What Can Psychology's Statistics Reformers Learn from the Error-statistical Perspective? by Haig, Brian D. is a Social Sciences article available to read on EtoBox.
What is What Can Psychology's Statistics Reformers Learn from the Error-statistical Perspective? about?
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. ☆ This article is based on an invited commentary on Deborah Mayo's book, Statistical inference as severe testing: How to get beyond the statistics wars (Cambridge University Press, 2018), which appeared at https://statmodeling.stat.colombia.edu/2019/04/12 It is adapted with permission. I thank Mayo for helpful feedback on an earlier draft.
Who reads What Can Psychology's Statistics Reformers Learn from the Error-statistical Perspective??
It is typically read by researchers, students, and practitioners in Social Sciences.
- Author
- Haig, Brian D.
- Publisher
- Elsevier ; Elsevier BV (ISSN 2590-2601)
- Published
- 2020
- Language
- EN
- Field
- Social Sciences