Question: 19. A p value can be interpreted as a (conditional) risk that a decision to reject H0 is a Type I error, but the p

19. A p value can be interpreted as a (conditional) risk that a decision to reject H0 is a Type I error, but the p values reported in research papers are valid indications of the true risk of Type I error only if the data meet the assumptions for the test and the researcher has followed the rules that govern the use of significance tests. Identify one of the most common researcher behaviors that make the actual risk of Type I error much higher than the "nominal" risk of Type I error that is set by choosing an alpha test?

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