1. The problem statement, all variables and given/known data Hello, I am using CasaXPS to model synthetic peak models for X-ray photoelectron spectroscopy data. I am fitting. The software has a lot of manuals online but they do not explain how they yield a Residual Standard Deviation, after each fit iteration. Most software use Chi-square or Reduced-Chi-squares, which I do not really understand either, but they are more widely used. For example, Whereas most softwares use Reduced Chi squares. Lastly, Name Block Id Data Set Position FWHM Area St Dev Area %At Conc % St.Dev. Goodness of Fit sp2 C1s 1-1 12 284.4560 1.1348 135.671 8.38179 54.79 286.976 sp3 C1s 1-1 285.0000 1.2000 89.8416 8.55699 36.28 286.976 sp2-Br C1s 1-1 285.6874 1.2000 14.7421 5.73433 5.95 286.976 C=P C1s 1-1 284.4843 0.9000 7.37342 2.8681 2.98 286.976 I get a report in which the "Goodness of Fit" equals 286.976, how do I transform this number into something statistically significant? The examples they use on the manuals also happen to have high numbers for "Goodness of Fit" Thanks a lot.