For a identical normal populations, repeating an experiment produces p<=0.2 20% of the time, and produces p<=0.005 0.5% of the time.
A coin comes up on the same side 3 times in a row vs 8 times in a row...I have no idea why we should shrug and consider the plausibility of coin bias in these two cases about the same.
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EDIT: I he means that in the case of an actual difference in the populations, p=0.2 and p=0.005 are both pretty likely outcomes.
When the populations are the same, p=0.2 and p=0.005 are quite different happenings.
This is because p-value methods doesn't worry very much about type II errors.
For a identical normal populations, repeating an experiment produces p<=0.2 20% of the time, and produces p<=0.005 0.5% of the time.
A coin comes up on the same side 3 times in a row vs 8 times in a row...I have no idea why we should shrug and consider the plausibility of coin bias in these two cases about the same.
---
EDIT: I he means that in the case of an actual difference in the populations, p=0.2 and p=0.005 are both pretty likely outcomes.
When the populations are the same, p=0.2 and p=0.005 are quite different happenings.
This is because p-value methods doesn't worry very much about type II errors.