Which type of error is reduced by using a best-fit line on a calibration curve?

• A. Random error
• B. Instrumental error
• C. Systematic error
• D. Methodological error

Answer: (A)

Random errors cause scatter in calibration data because measurements fluctuate from one reading to the next. A best-fit line uses all the data to define the most probable linear relationship between signal and concentration, minimizing the deviations of individual points from the line. That smoothing effect makes the predicted concentrations less affected by the random noise in any single measurement, effectively reducing random error.

Systematic error, on the other hand, would bias all measurements in a uniform direction (shifting the line up or down or changing its slope). A regression line cannot remove that kind of bias; you’d need to correct the instrument or the calibration method to address it.