Which rule would you use to identify a significant random error in a QC chart?

The 13s rule is used to identify significant random errors in a quality control (QC) chart. This rule states that if a single control result exceeds the mean plus three standard deviations or falls below the mean minus three standard deviations, it signals that a random error may have occurred.

In the context of quality control, the 13s rule is particularly effective for detecting outliers that could indicate a problem with the testing process. A result that is more than three standard deviations away from the mean suggests that the test result is highly unlikely to be due to random chance alone, thereby marking it as an outlier that warrants further investigation.

In contrast, other rules like the 41s and 22s rules focus on detecting trends or patterns in the data rather than isolated significant errors. The 10× rule is typically used to indicate a systematic error when ten consecutive control results are found on one side of the mean. Therefore, it is the specificity of the 13s rule in identifying individual random errors that makes it the most appropriate choice for this situation.