If a test result seems unusually inconsistent with other performance indicators, what is an appropriate next step?

If a test result seems unusually inconsistent with other performance indicators, what is an appropriate next step?

• A. Ignore the discrepancy and proceed with interpretation
• B. Immediately discard the result from all analyses
• C. Re-test to verify results, review the testing protocol for errors, and consider excluding extreme outliers if justified
• D. Rely on the athlete's reputation to override the data

Answer: (C)

When measurements don’t align with other indicators, you need to verify data quality before drawing conclusions. Re-testing helps confirm whether the result came from random error, instrument drift, or a one-off mistake. Reviewing the testing protocol checks for procedural issues—like improper calibration, timing, or warm-up—that could bias the result. Excluding extreme outliers should be considered only if there’s a clear justification and a predefined rule, to avoid bias or discarding valid data. Together, these steps protect the accuracy and reliability of the assessment, rather than ignoring the discrepancy, discarding data without verification, or relying on reputation over evidence.

When measurements don’t align with other indicators, you need to verify data quality before drawing conclusions. Re-testing helps confirm whether the result came from random error, instrument drift, or a one-off mistake. Reviewing the testing protocol checks for procedural issues—like improper calibration, timing, or warm-up—that could bias the result. Excluding extreme outliers should be considered only if there’s a clear justification and a predefined rule, to avoid bias or discarding valid data. Together, these steps protect the accuracy and reliability of the assessment, rather than ignoring the discrepancy, discarding data without verification, or relying on reputation over evidence.