The progression of X's is not clear. For 30.07 to 38.83 by 0.01, there
are only 877 points, yet you indicate that you have 1049 points.

Fitting a 6th degree polynomial to this narrow a range of x-values is a
very difficult numerical problem. Assuming the obvious 877 points, the
condition number for X'X is ~ 6.8E+32. For pre-2003 LINEST to give
meaningful coefficients for anything higher than a cubic would be a
numerical accident.

The chart polynomial trendline is numerically better than LINEST, and
has the potential to give reasonable results here. You might also try
R, the free open-source implementation of the S statistical programming
language
http://www.r-project.org
LINEST in Excel 2003 or later may also give reasonable results.

Since you seem to be more interested in interpolation than the actual
coefficient values, you may be OK. Prediction within this range should
be much more numerically stable than the coefficient estimates themselves.

Jerry

KevinW wrote:

....

Just to be clear, I am -not- trying to find the 'best fit' for a plot
of scattered data. Rather, I am trying to find an equation to describe
an existing line. I scanned and digitized a Larson-Miller curve I will
be using extensively for my thesis. The data points are very close
together. I'd like to be able to enter a value and return the
corresponding value from the curve. As long as the answer is the same
as the original curve, then I'm happy with the equation for the line.

Digitizing and inputing the curve into Excel is probably more accurate
than trying to manually read values over and over from a hardcopy
plot.

Here is an example of my data;

Row X Y
1) 30.07 62.08
2) 30.08 62.08
3) 30.09 62.08
4) 30.09 61.96
5) 30.10 61.96
6) 30.11 61.83
7) 30.12 61.83
8) 30.13 61.71
..(snip 1000 data points)....
1047) 38.81 6.25
1048) 38.82 6.25
1049) 38.83 6.24