Errors in the Regression Equation:
There is always some error associated with the measurement of any signal. Earlier, we saw how this affected replicate measurements, and could be treated statistically in terms of the mean and standard deviation.
The same phenomenon applies to each measurement taken in the course of constructing a calibration curve, causing a variation in the slope and intercept of the calculated regression line. This can be reduced - though never completely eliminated - by making replicate measurements for each standard.
Even with this precaution, we still need some way of estimating the likely error (or uncertainty) in the slope and intercept, and the corresponding uncertainty associated with any concentrations determined using the regression line as a calibration function.