I suggest you do the following: Run the data points in Mathematica using Fit to obtain a least-square fit function. Then integrate the difference. The code below just makes up a table of points corresponding randomly to the function $\displaystyle 0.1 x^2$. I then run Fit to obtain a least-square fit I cal myFunction. I then plot the function y=x, y=myFunction, and also the list of points I generated. Finally, I use Integrate to integrate the area between myFunction and x in the range 0 to 5. I use Abs below to get the total area if the calib curve dips below y=x. If you're not familiar with this, try and get someone there to help you with the details.

Code:

myList = Table[{xval, 0.1 xval^2 +
RandomReal[{-0.5, 0.5}]}, {xval, 0,
5, 0.1}];
ListPlot[myList]
myFunction = Fit[myList, {1 + x + x^2 + x^3}, x]
Show[{ListPlot[myList], Plot[{x, myFunction}, {x, 0, 5}]}]
Integrate[Abs[x - myFunction], {x, 0, 5}]