Key Takeaways: Rounding Uncertainty & Results The 2-Digit Rule: Per JCGM 100:2008 (GUM) and ILAC P14, expanded uncertainties must be reported to a maximum of two significant digits. Consistency Requirement: Measurement results must be rounded to match the final decimal place of the rounded uncertainty to avoid audit nonconformities. Core Rounding Methods: Laboratories typically […]
Short Answer: Measurement repeatability is a statistical evaluation of variability in replicate measurement results on the same or similar object over a short period of time under the same measurement conditions, including the same procedure, operators, measuring system, operating conditions and location. Official VIM Definitions Related to Measurement Repeatability Measurement Repeatability According […]
Short answer: According to the proceedings from the 96th meeting of the CIPM (2007), CMC uncertainty is a calibration and measurement capability available to customers under normal conditions: As published in the BIPM key comparison database (KCDB) of the CIPM MRA or as described in the laboratory’s scope of accreditation granted by an ILAC-MRA signatory. […]
Short answer: Calibration uncertainty is calculated by combining the CMC uncertainty, UUT resolution, and UUT repeatability using the square root of the sum of squares (RSS) method per the JCGM 100:2008 section 5.1.2 and ILAC P14 section 5.3. The combined uncertainty is expanded to a 95.45 % confidence interval using an appropriate coverage factor (k), […]
Short answer: Calibration uncertainty is the measurement uncertainty expressed in calibration reports at a 95 % confidence interval, where k=2, with two significant digits. It is calculated by combining the laboratory’s CMC uncertainty with the Unit Under Test (UUT) resolution and repeatability per ILAC P14. Calibration Uncertainty Reporting Requirements Per ILAC P14 Section […]
Short answer: The effective degrees of freedom formula is the Welch-Satterthwaite formula given in section G.4.1 of the JCGM 100:2008: νeff = uc4(y) / Σ[ui4(y) / νi]
Short answer: Convert each source of uncertainty to a standard uncertainty (i.e. standard deviation) and combine them using the square root of the sum of squares formula (known as the RSS method) per section 5 of the JCGM 100:2008. According to the JCGM 100:2008 section 5.1.2, the “combined standard uncertainty is the positive square root […]
Short answer: Each uncertainty is converted to a standard deviation equivalent (i.e. standard uncertainty) and combined using the square root of the sum of squares formula (known as the RSS method) per section 5 of the JCGM 100:2008. In the image below, you will see this explained in the JCGM 100:2008, section 5.1.2. According […]
Short Answer: Some uncertainties are assumed to be normally distributed based on: Observations from the statistical evaluation of data, Information associated with the measurement uncertainty, Expertise with specific uncertainties, evaluation techniques, and data types, or Recommendations from the GUM, methods, guidance, and regulatory documents. If a normal distribution is not appropriate, then another probability distribution […]
Short Answer: To choose the right probability distribution for each source of uncertainty, refer to sections 4.2 and 4.3 of the JCGM 100:2008. It includes criteria-based recommendations for selecting the right probability distributions. Otherwise, use a histogram, expertise, or published studies to find the right probability distribution. Probability Distribution Recommendations from the GUM (JCGM 100:2008) […]
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