NOTE 3 The indeterminate article ”a” instead of the specific article ”the” is used in combination with ”real value” because there may be many values that fit the definition of a certain amount. How to guide: If the result of a measurement depends on the values of quantities other than the measured value, errors in the measured values of these quantities contribute to the error of the measurement result. See also the guide`s commentary on B.2.22 and B.2.3. Note 2 As only a finite number of measurements can be made, it is possible to determine only one estimate of the accidental error. Systematic error tends to systematically displace all measures, so that during a series of measures, the average is constantly superseded or varied predictably. The causes may be known or unknown, but should always be corrected if they exist. For example, no device can be perfectly calibrated, so if a group of measurements systematically differs from the value of a standard reference sample, the values should be adjusted. Systematic error can only be corrected if the ”real value” (for example. B the value assigned to a calibration or reference sample) is known.
Repeatability and reproducibility are included in the definition of accuracy and are used to describe the variability of the measurement method. In general, reproducibility implies more effects on variability than repeatability. It is defined as the resulting variation of a measurement process when performed in different instruments, operators, environments and periods (measurement conditions). On the other hand, repeatability refers to the variation that occurs even when effort is needed to keep the device, operator and environment constant and shorten the measurement period. Note 1 Given the series of values n as a sample of a distribution, q ̅ ̅ is an unbiased estimate of the average q and s2 (qk) is an unbiased estimate of the variance 2 of that distribution. NOTE 2 The value of a quantity can be expressed in more than one way. The comprehensive formal process for determining the uncertainty of a measure is an important process that identifies all the essential variables in the process and the environment and assesses their effects on measurement. This process goes beyond the scope of this material, but it is described in the ISO guide for the expression of uncertainty in Measurement (GUM) and in the US national standard ANSI/NCSL Z540-2. However, there are measures to estimate uncertainty, such as standard deviations. B, which are entirely based on the analysis of experimental data, as all the main sources of variability in the collection of the data set have been experimented.
Uncertainty in a given measure is the confidence interval around the measured value, so the measured value is sure not to be outside that specified interval. Uncertainties can also be expressed with a probability. In this case, the measured value has the probability of being within the confidence interval.