John,
If memory serves r can be used to get the standard deviation of the
slope. It is equal to the m*tan(arccos(r))/square-root of (N-2), where m is
the determined slope and N the number of observations. I have always wondered
about the sanity of the guy who found this relationship. It value contains
al the usual statements about the problems associated with stasticial data.
As far as r is concerned I tell my students if it isn't at least 0.99xx
they probably don't have a good fit. We always graph our data since that tells
us much more about the experiment than r. Some social scientists are happy with
r's above 0.6, but they have a much hard science then we do.
I just spent today having my students write their own least squares
line fit worksheet using MathCad since I haven't found a single program that
does it all. Vernier's Windows MPLI data handeling program is the first I have
seen that gives the standard deviation of the slope which is really what you
need most often in the physics undergrad labs, but it is closely coupled to
the MPLI data gathering boards. It also contains some powerful function fitting
routines.
I hope this helps.
Gary