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You can ignore the warnings. Note that I plug in df=16, so that 16+2+2=20 actually corresponds to n1=n2=10. But the density must integrate to 1. Correct would be:
The computation in
dd()
isn't correct. Two issues:In
dd()
, you usedf + 2
, butconvert.d.to.t()
also doesdf + 2
, so in essence this is done twice.You cannot just convert d to t and then plug t into
dt()
. You need to use the change of variables technique:https://en.wikipedia.org/wiki/Probability_density_function#Dependent_variables_and_change_of_variables
So, let's say n1=n2=10 and true d is 0.5. At the moment:
You can ignore the warnings. Note that I plug in df=16, so that 16+2+2=20 actually corresponds to n1=n2=10. But the density must integrate to 1. Correct would be:
So, you need to multiply by
sqrt(n1*n2/(n1+n2))
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