In clinical chemistry, one often hears that there are two contributions to error – systematic error and random error. Random error is often estimated by taking the SD of a set of observations of the same sample. But does the SD estimate random error? And are repeatability and reproducibility forms of random error? (Recall that repeatability = within run imprecision and reproducibility = long term (or total) imprecision.

**Example 1** – An assay with linear drift with 10 observations run one after the other.

The SD of these 10 observations = 1.89. But if one sets up a regression with Y=drift + error, the error term is 0.81. Hence, the real random error is much less than the estimated SD random error because the observations are contaminated with a bias (namely drift). So here is a case where repeatability doesn’t measure random error by taking the SD, one has to investigate further.

**Example 2** – An assay with calibration (drift) bias using the same figure as above (Ok I used the same numbers but this doesn’t matter).

Assume that in the above figure, each N is the average of a month of observations, corresponding to a calibration. Each subsequent month has a new calibration.

Clearly, the same argument applies. There is now calibration bias which inflates the apparent imprecision so once again, the real random error is much less than what one measures by taking the SD.