# Estimate error of predicted value obtained by linear regression model

I have measured 2 parameters, r and p. Each parameter was measured in three technical replicates (n=3) per sample. r is measured directly. p is measured indirectly; the data obtained is output voltages of a measurement instrument. To correlate these with p, I produced a calibration curve by measuring samples of known p. I then calculated a linear regression and obtained a formula
$p(V) = m*V +b$ in which V is the measured voltage. But this regression was calculated using the mean of the three measurements.

1) How do I calculate a linear regression that takes into account the error of each measurement?

To obtain values of p for my samples I entered the measured voltages in the formula.

2) How do I calculate the error of a value predicted by linear regression?