Meaning
Estimation of error based on external data sources accounts for the margins of uncertainty that cannot be derived from a current series of repeated tests. Type b uncertainty is determined using professional judgement or manufacturer specifications. This method is used for variables that cannot be easily repeated, such as the fixed resolution of a digital scale or the stated accuracy of a chemical reagent.
It provides a way to incorporate known systematic errors into a formal uncertainty budget.
Information Source
Calibration records for laboratory equipment serve as the foundation for these estimates. If a sensor is certified to be accurate within one percent, that figure becomes the basis for the type b uncertainty of all measurements taken with that device. Other sources include technical handbooks or published physical constants that carry their own stated margins of error.
Probability Distribution
Assigning a value requires the assumption of a specific shape for the error, such as a rectangular or triangular distribution. A rectangular distribution is used when any value within a range is equally likely, whereas a triangular distribution suggests the true value is more likely to be near the center. These choices determine the standard uncertainty value that will be combined with other components.
Systematic Bias
Fixed offsets in a measurement system that do not change between repeated tests are captured here. Unlike statistical variations, type b uncertainty cannot be reduced by simply taking more measurements. Improving this aspect of the measurement requires the use of higher precision instruments or more frequent recalibration against primary standards.
This component often dominates the total uncertainty budget when using highly repeatable but uncalibrated testing equipment.
