Abstract
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.
Footnotes
The author declares no competing financial interests.
This work was supported National Institutes of Health Grants T32-EY-007110 and EY-11379 to R.T.B.
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