2.2 The uncertainty of the result of a measurement generally consists of several components which, in the CIPM approach, may be grouped into two categories according to the method used to estimate their numerical values:
NOTE - The difference between error and uncertainty should always be borne in mind. For example, the result of a measurement after correction (see subsection 5.2) can unknowably be very close to the unknown value of the measurand, and thus have negligible error, even though it may have a large uncertainty (see the Guide ).2.4 Basic to the CIPM approach is representing each component of uncertainty that contributes to the uncertainty of a measurement result by an estimated standard deviation, termed standard uncertainty with suggested symbol ui , and equal to the positive square root of the estimated variance ui2.
2.5 It follows from subsections 2.2 and 2.4 that an uncertainty component in category A is represented by a statistically estimated standard deviation si2 equal to the positive square root of the statistically estimated variance si2, and the associated number of degrees of freedom νi . For such a component the standard uncertainty is ui = si .
The evaluation of uncertainty by the statistical analysis of series of observations is termed a Type A evaluation (of uncertainty).
2.6 In a similar manner, an uncertainty component in category B is represented by a quantity uj , which may be considered an approximation to the corresponding standard deviation; it is equal to the positive square root of uj2, which may be considered an approximation to the corresponding variance and which is obtained from an assumed probability distribution based on all the available information (see section 4). Since the quantity uj2 is treated like a variance and uj like a standard deviation, for such a component the standard uncertainty is simply uj .
The evaluation of uncertainty by means other than the statistical analysis of series of observations is termed a Type B evaluation (of uncertainty).
2.7 Correlations between components (of either category) are characterized by estimated covariances [see Appendix A, Eq. (A-3)] or estimated correlation coefficients.