T

#### TheMoth

0 intercept than letting XL calculate it. This seems wrong: the least squares

regression should be the best fit of the data. I compared LINEST and the

Regression tool in the Data Analysis Tool Pak and they yield the same answer.

I suspected that XL adds a (0,0) to the data set because the total df in the

ANOVA output is one larger for the fixed intercept, but testing that with RSQ

yielded a different value. The stats (below) all favor the fixed intercept;

even the calculated slope is closer to 1 and the confidence limits are

tighter:

Stat b=calc b=0

Intercept -0.02048 0

Rsq 0.9929 0.9991

std Err 0.2318 0.2306

Slope 1.0045 1.0020

std Err 0.0093 0.0033

L 95.0% 0.9861 0.9955

U 95.0% 1.0230 1.0085

Thanks in advance for any input.