Having an occasion to read the ISO 15197 standard (for glucose meters) I notice the statements:
One of the reasons allowed to discard data is: “the blood-glucose monitoring system user recognizes that an error was made and documents the details”
This makes ISO a biased standard because in the real world there will be user error which generates outlier data.
And compounding things is this statement:
“Outlier data may not be eliminated from the data used in determining acceptable system accuracy, but may be excluded from the calculation of parametric statistics to avoid distorting estimates of central tendency and dispersion.”
The problem is outliers that are representative of what happens in the real world should not be thrown out to help statistics such as regression and precision from being distorted. Rather these statistics should not be used. An error grid is a perfectly adequate statistic to handle 100% of the data.