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Banishing “Black/White Thinking”: A Trio of Teaching Tricks

Literally hundreds of statisticians have rightly called for an end to statistical significance testing (Amrhein et al., 2019; Wasserstein et al., 2019). But the practice of arbitrarily thresholding p values is not only deeply embedded in statistical practice, it is also congenial to the human mind....

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Detalles Bibliográficos
Autor principal: Born, Richard T.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Society for Neuroscience 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6900463/
https://www.ncbi.nlm.nih.gov/pubmed/31776176
http://dx.doi.org/10.1523/ENEURO.0456-19.2019
Descripción
Sumario:Literally hundreds of statisticians have rightly called for an end to statistical significance testing (Amrhein et al., 2019; Wasserstein et al., 2019). But the practice of arbitrarily thresholding p values is not only deeply embedded in statistical practice, it is also congenial to the human mind. It is thus not sufficient to tell our students, “Don’t do this.” We must vividly show them why the practice is wrong and its effects detrimental to scientific progress. I offer three teaching examples I have found to be useful in prompting students to think more deeply about the problem and to begin to interpret the results of statistical procedures as measures of how evidence should change our beliefs, and not as bright lines separating truth from falsehood.