In QA/QC data validation, which scenario would be flagged as an anomaly?

• A. A missing data point due to instrument downtime.
• B. A single anomalous reading outside the expected QA limits.
• C. A recently calibrated value that matches prior data.
• D. A consistent series within QA limits.

Answer: (B)

In QA/QC data validation, an anomaly is a data point that falls outside the predefined QA limits or expected range, signaling something unusual that needs investigation. A single reading outside the expected QA limits best fits this idea because it violates the acceptance criteria and stands out as not following the established pattern. It could point to a temporary instrument hiccup, a sampling issue, or a transient condition that should be checked. In contrast, a missing data point due to instrument downtime is a gap, not an out-of-range value; a recently calibrated result that matches prior data is what you’d expect after proper calibration; and a consistent series within QA limits reflects normal, compliant data.