Where n is the number of calibration samples.
And the relative
standard error of estimate: These important parameters indicate the accuracy possible near the centre of
the calibration curve.
Once the calibration has been done, and before the first analysis, it is time
to optimise the calibration curve.
The first step is to choose the order and to select any interfering elements.
Generally it is better to use no interference corrections unless these are known
and there is an obvious and significant improvement in the statistical
The BEC should be small and positive. If necessary adjust the weights
to achieve this.
If the standard error of estimate is too high, do one or more of the
- increase the number of calibration samples
- reduce the weight of outliers
- repeat the calibration with more measurements on each sample
- reduce the concentration ranges or the number of families of different
- change the calibration function or mode.
Finally the success of the calibration - the order selected, any interference
corrections, etc. - should be checked with one or more validation samples, i.e.
samples of known composition not included in the calibration.