Sometimes people looked up F-critical points in order to carry
out tests at specific levels as requested in the text. This is not wrong
but also not necessary. If P < 0.01 then you can reject the null at the
level 0.01. That's why you only need the P-value.
A P-value does not measure . After all, you must
assume is true to compute P. Instead it measures how often, when
the null is true, you would expect to see a test statistic as extreme as
the one you actually saw.
You need to interpret the output not just hand it in. Your
conclusions must be about real world things not just ``I reject .''
In one question the Tukey intervals all include 0 but the F test of
the hypothesis rejects the null. The interpretation is that while we
are confident that not all the means are equal we aren't quite sure which
ones differ from which; we are unable to name with adequate confidence
a specific pair which differ.
If then we
estimate using . The variance of this is
which is simply
Now plug in MSE for and take a square root to get the estimated
standard error of and use the interval (estimated standard error).