A p value can be interpreted as a (conditional) risk that a decision to reject H

Question

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 level.

Explanation / Answer

One of the common error is choosing an alpha after the analysis is done.

Supoose a statisiticl test is performed to check if weight of 2 independent groups differe significantly and thre calculated p value is 0.049 , so the research can then select an alpha of 0.05 in ored to prove the claim . However if the alpha level was set before the study at say 0.01 , then we would have failed to reject the null hypothesis

also , it is important to know the alpha that is usually set in the field of the study with the prior experience and results

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