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What exactly do researches do to that inflate the risk of Type 1 errors. ie. why...

What exactly do researches do to that inflate the risk of Type 1 errors. ie. why do p values underestimate the true risk of Type 1 errors?

Math   Statistics-And-Probability   
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Answer #1

As a statistican, we always consider a true hypothesis. A particular test is applied based on true hypothesis and gave a conclusion. If test is reject under the true hypothesis then this is a Type 1 error which is more serious than other error. So, inflate the risk of Type I error is the increased chance that any one of the effects will be smaller than you think for true hypothesis. p-value is used as an alternative concept for rejection points to provide the smallest level of significance at which the null hypothesis would be rejected.

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