Product Info

Report No: CCISE191202301-V01
Shenzhen Zhongjian Nanfang Testing Co., Ltd. Project No.: CCISE1912023
No. B-C, 1/F., Building 2, Laodong No.2 Industrial Park, Xixiang Road,
Bao’an District, Shenzhen, Guangdong, China
Telephone: [phone] Fax: [phone], E-mail: [e-mail] Page 66 of 171
15.7 Measurement Uncertainty
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 A 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 below Table.
Uncertainty Distributions
Normal
Rectangular
Triangular
U-Shape
Multi-plying Factor
1/k(b)
1/ 3
1/ 6
1/ 2
Standard Uncertainty for Assumed Distribution
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 probability within the specified
uncertainty range. For purpose of this document, a coverage factor two is used, which corresponds to
confidence interval of about 95 %. The DASY uncertainty Budget is shown in the following tables.