then you will need a sum of fith row field. Fourth row is the difference between found and calculated y. Just define Cells for your regression parameters (a and b), write down you experimental values (x and y in two rows) in the third row calculate the y-values based on your regression arameters. The whole thing is relativly easy to do in excel if the solver module is installed. This regression is then based on the relative deviation (or their squares). Using the absolute deviations (comparable to the SDs above) in the example above the line would go through the 10 -point.īy using the 1/x weighting the deviation at a certain point is divided by the value and you woulfd get something similar to the RSD.
100 the SD would be 10 and the RSD still 10% and for 10000 SD 1000 and RSD 10% respectively.įor regression usually the squares of the deviation (calcfound) are minimized.
1 the SD could be 0.1 and the RSD would be 10%. If you did a calibration over more than one order of magnitude, unweighted regression would over-represent the higher values.įor all your Calibration points you have a SD and a RSD (for one injection it ist still there, but cannot be determined).
