Which statistical term most specifically describes analytical precision?

Analytical precision refers to the consistency or repeatability of test results, often quantified by how much variation exists in those results when repeated measurements are taken. Among the options provided, the coefficient of variation is the most specific term that describes analytical precision as it measures the relative variability of the data in relation to the mean.

The coefficient of variation is calculated as the ratio of the standard deviation to the mean, expressed as a percentage. This makes it particularly useful because it allows for the comparison of precision between datasets that may have different units or different means. A lower coefficient of variation indicates greater precision in the analytical results, while a higher value suggests more variability.

In contrast, the standard deviation measures the absolute variability of the data from the mean but does not account for the size of the mean itself. The mean provides a central value of the data but does not give any information about variations or precision. Variance, similar to standard deviation, quantifies variability but is expressed in squared units, making it less intuitive when interpreting precision directly in the context of the original data.