Hi Jerry,

I usually have somewhere around 375 data points, which goes up by 1 each
week, as I am tracking a stock closing, but only on a weekly basis. Yes, it
is the 6th degree polynomial that I add to the graph. I tried to figure out
the individual data points represented by the graph, using the formula
provided by the graph, but the "point" was not very accurate and I am given
the understanding that this was due to rounding errors and the precion of
Excel, prior to Office 2003.

Maybe this has all changed? I had also run across a third party add-on that
was claiming to have increased the accuracy, but did not purchase it and have
not heard anyone else mention it or vouch for it. But if I could find a way
to figure out the individual points represented by the graph, I would be
interested in doing that.

Thanks for your help.


--
David


"Jerry W. Lewis" wrote:

If by "6th degree", you mean a 6th degree polynomial, then you should be
conserned about whether you have sampled a wide enough range of data to be
able to reliably estimate the parameters. Even with independent parameters
and/or adequate data range, validation of the formula could be interesting.
Remember the famous quote of von Neumann "With four parameters I can fit an
elephant, and with five I can make him wiggle his trunk."

Jerry

"David" wrote:

I just started reading your thread and have become interested. I was at one
time trying to create data points from an anaysis of Stock closiings, that
are represented by a regression (6th degree) line. I was not able to use the
formula supplied in previous versions of Excel, prior to Ver 2003. But I
would be interested in trying this again, since i have the new version. I
would like to actually create data points as respesented by the regression
line, fi that is possible?

Thanks,
--
David


"Mitch" wrote:

I need to run regression analyses (linear & nonlinear) on many data sets. I
have observed that the resulting equations generated in a chart trend line
and that generated by the linest() function are frequently very different. I
have read Tushar Mehta's explanation of the problem, but need advice on which
is more accurate.