## Using the Calibration Function:

The main aim of deriving a calibration equation is obviously to determine
the concentration of analyte in various samples (our ‘unknowns’)
from the corresponding mesaured value of the instrument response.
Mathematically, this requires an *interpolation* of the measurement
(signal or response) through the calibration function. This obviously
involves substituting the measured response (*y _{0}*) into
the regression line and solving for the concentration (

*x*).

_{0}The problem now is that we have uncertainty in both the measured value
*y _{0}*

*and*the parameters of our calibration function (

*i.e.*the slope and intercept of the regression line.) As with any other experimental measurement, the uncertainty in the measured value can be reduced by performing replicate determinations; we therefore additionally need to take into account the number of such replicates in determining the uncertainty in the interpolated sample concentration.