Measurement Uncertainty: Reporting Results Honestly
Build a practical framework for repeatability, bias, calibration and uncertainty propagation.
Every result has uncertainty
A reported value combines the measurand, method, instrument, specimen and analyst. None is perfectly known.
Random and systematic components
Repeatability captures scatter under fixed conditions; bias shifts results away from the reference value.
Traceability and calibration
Traceable calibration links measurements to standards through an unbroken chain with stated uncertainties.
Propagation and reporting
Input uncertainties propagate through calculations. Coverage intervals should be reported with assumptions and confidence level.
Engineering takeaway
Use uncertainty to judge whether differences are meaningful, specifications are met and models are genuinely validated.