Measuring method
46 Edition 01/2016 multi EA 4000
c … target content of the standard
m … sample mass
I
net
net integer
k
0
, k
1
, k
2
… calibration coefficient
The regression type (linear or quadratic) can be defined by the user. It is possible to select
individual measuring points or measured values for the calculation of the current calibration
(manual outlier selection). Individual standards can, where required, also be redetected or
additional measuring points added to the calibration.
The multiWin software offers the option to proceed with different calibration strategies
adapted to the analytical requirement and dependent on the measuring range and sample
matrix. With the multi EA 4000 multi point calibrations with variable sample volumes and
constant concentrations are performed.
5.5.2 Day factor
With the day factor it is possible to check and correct the calibration with a standard. All sub-
sequent measurement results are multiplied by this factor.
The day factor is calculated in accordance with the equation (7).
=
(7)
5.5.3 Method characteristics
Remaining standard deviation
The remaining standard deviation (remaining variance) expresses the dispersion of the inte-
gers around the regression function (regression precision).
Standard deviation of the method
The standard deviation of the method describes in a unique and general way the quality of
the calibration. For the unique evaluation of the quality the standard deviation of the method
must be used.
Method variation coefficient
The variation coefficient of the method (relative standard deviation of the method) should be
used for the comparison of different calibrations with different calibration ranges.
Correlation coefficient
The correlation coefficient compares the dispersion of the calibration measuring points of the
regression function with the total dispersion of the calibration. If all calibration measuring
points are on the calculated regression function, then the correlation coefficient is +1 or -1.
For positive correlation coefficients the regression function is increasing, for negative ones it
is decreasing.
Coefficient of determination
The square of the correlation coefficient is called the coefficient of determination.