Size is
certainly the most important thing in a statistical parameter, for
the reasons discussed above. However, practically, you need a combination
of size and relative accuracy together before you can say much about
your analysis. Consider the following possibilities:
-
A
relatively large statistic
that is relatively accurate (compared
to some range or benchmark like zero):
-
This is fine, because the statistic
is accurate enough. You can proceed to interpret the size.
-
An example may be a moderate correlation
of, say, .35 with p < .01. The accuracy frees you to interpret
the size.
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Remember that a big statistic is not necessarily good – a big decline in patient health in a drug ...