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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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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Society for Neuroscience
2019
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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 |
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author | Born, Richard T. |
author_facet | Born, Richard T. |
author_sort | Born, Richard T. |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-6900463 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Society for Neuroscience |
record_format | MEDLINE/PubMed |
spelling | pubmed-69004632019-12-09 Banishing “Black/White Thinking”: A Trio of Teaching Tricks Born, Richard T. eNeuro Commentary 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. Society for Neuroscience 2019-12-05 /pmc/articles/PMC6900463/ /pubmed/31776176 http://dx.doi.org/10.1523/ENEURO.0456-19.2019 Text en Copyright © 2019 Born http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution and reproduction in any medium provided that the original work is properly attributed. |
spellingShingle | Commentary Born, Richard T. Banishing “Black/White Thinking”: A Trio of Teaching Tricks |
title | Banishing “Black/White Thinking”: A Trio of Teaching Tricks |
title_full | Banishing “Black/White Thinking”: A Trio of Teaching Tricks |
title_fullStr | Banishing “Black/White Thinking”: A Trio of Teaching Tricks |
title_full_unstemmed | Banishing “Black/White Thinking”: A Trio of Teaching Tricks |
title_short | Banishing “Black/White Thinking”: A Trio of Teaching Tricks |
title_sort | banishing “black/white thinking”: a trio of teaching tricks |
topic | Commentary |
url | 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 |
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