Product Info

MORLAB
Shenzhen Morlab Communications Technology Co., Ltd.
FL1-3, Building A, FeiYang Science Park, No.8 LongChang Road,
Block67, BaoAn District, ShenZhen , GuangDong Province, P. R. China
Tel: [phone] Fax: [phone]
Http://www.morlab.cn E-mail: [e-mail]
REPORT No.：SZ21070039S02
Page 50 of 53
18. Uncertainty Assessment
The component of uncertainly may generally be categorized according to the methods used to
evaluate them. The evaluation of uncertainly by the statistical analysis of a series of observations is
termed a Type An evaluation of uncertainty. The evaluation of uncertainty by means other than the
statistical analysis of a series of observation is termed a Type B evaluation of uncertainty. Each
component of uncertainty, however evaluated, is
represented by an estimated standard deviation,
termed standard uncertainty, which is determined by the positive square root of the estimated
variance.
A Type A evaluation of standard uncertainty may be based on any valid statistical method for treating
data. This includes calculating the standard deviation of the mean of a series of independent
observations; using the method of least squares to fit a curve to the data in order to estimate the
parameter of the curve and their standard deviations; or carrying out an analysis of variance in order
to identify and quantify random effects in certain kinds of measurement.
A type B evaluation of standard uncertainty is typically based on scientific judgment using all of the
relevant information available. These may include previous measurement data, experience, and
knowledge of the behavior and properties of relevant materials and instruments, manufacture’s
specification, data provided in calibration reports and uncertainties assigned to reference data taken
from handbooks. Broadly speaking, the uncertainty is either obtained from an outdoor source or
obtained from an assumed distribution, such as the normal distribution, rectangular or triangular
distributions indicated in table below.
Uncertainty Normal Rectangular Triangular U-Shape
Multi-plying Factor
(a)
1/k
(b)
1/√3 1/√6 1/√2
Standard Uncertainty for Assumed Distribution
(a) standard uncertainty is determined as the product of the multiplying factor and the estimated
range of variations in the measured quantity
(b) κ is the coverage factor
The combined standard uncertainty of the measurement result represents the estimated standard
deviation of the result. It is obtained by combining the individual standard uncertainties of both Type A
and Type B evaluation using the usual “root-sum-squares” (RSS) methods of combining standard
deviations by taking the positive square root of the estimated variances.
Expanded uncertainty is a measure of uncertainty that defines an interval about the measurement
result within which the measured value is confidently believed to lie. It is obtained by multiplying the
combined standard uncertainty by a coverage factor. Typically, the coverage factor ranges from 2 to 3.
Using a coverage factor allows the true value of a measured quantity to be specified with a defined