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# NIST TN 1297: 4. Type B Evaluation of Standard Uncertainty

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4.1 A Type B evaluation of standard uncertainty is usually based on scientific judgment using all the relevant information available, which may include

- previous measurement data,
- experience with, or general knowledge of, the behavior and property of relevant materials and instruments,
- manufacturer's specifications,
- data provided in calibration and other reports, and
- uncertainties assigned to reference data taken from handbooks.

Some examples of Type B evaluations are given in subsections 4.2 to 4.6.

4.2 Convert a quoted uncertainty that is a stated multiple of an estimated standard deviation to a standard uncertainty by dividing the quoted uncertainty by the multiplier.

4.3 Convert a quoted uncertainty that defines a "confidence interval" having a stated level of confidence (see subsection 5.5), such as 95 or 99 percent, to a standard uncertainty by treating the quoted uncertainty as if a normal distribution had been used to calculate it (unless otherwise indicated) and dividing it by the appropriate factor for such a distribution. These factors are 1.960 and 2.576 for the two levels of confidence given (see also the last line of Table B.1 of Appendix B).

4.4 Model the quantity in question by a normal distribution and estimate lower and upper limits a- and a+ such that the best estimated value of the quantity is (a+ + a-)/2 (i.e., the center of the limits) and there is 1 chance out of 2 (i.e., a 50 percent probability) that the value of the quantity lies in the interval a- to a+. Then uj ≈ 1.48 a where a = (a+ - a-)/2 is the half-width of the interval.

4.5 Model the quantity in question by a normal distribution and estimate lower and upper limits a- and a+ such that the best estimated value of the quantity is (a+ + a-)/2 and there is about a 2 out of 3 chance (i.e., a 67 percent probability) that the value of the quantity lies in the interval a- to a+. Then uj ≈ a, where a = (a+ - a-)/2.

4.6 Estimate lower and upper limits a- and a+ for the value of the quantity in question such that the probability that the value lies in the interval a- to a+ is, for all practical purposes, 100 percent. Provided that there is no contradictory information, treat the quantity as if it is equally probable for its value to lie anywhere within the interval a- to a+; that is, model it by a uniform or rectangular probability distribution. The best estimate of the value of the quantity is then (a+ + a-)/2 with uj  = a/

If the distribution used to model the quantity is triangular rather than rectangular, then uj  = a/