How do random and systematic errors contribute to overall measurement uncertainty

What is a significant contributor to measurement uncertainty?

According to A2LA R205 section 6, a significant contributor is defined as any source of uncertainty that causes the CMC Uncertainty to increase by five percent (5 %) or more.

This definition is unique to A2LA. Confirm with your accreditation body that 5 % is acceptable. Although not written, some accreditation bodies recommend a 10 % increase makes the uncertainty a significant contributor. Others want all potential sources of uncertainty included no matter the percentage of contribution.

Finally, consider the percentage as relative to the CMC Uncertainty, not as an absolute value.

What are the most significant sources of uncertainty in laboratory measurements?

The most significant sources of uncertainty vary with each type of test, measurement, and measurement system. However, some of the most common sources of uncertainty that significantly affect measurement results include:

• Repeatability,
• Reproducibility,
• Resolution,
• Drift or Stability,
• Bias,
• Reference Standard Uncertainty,
• Environmental Contributors, and
• Method-specific Contributors.

Every test and measurement is different. Likewise, the most significant contributors will not be the same.

Some tests and measurements will be heavily influenced by repeatability and reproducibility. Some will be significantly affected by drift or bias while others are significantly impacted by instrument resolution or environmental factors.

The only way to know which sources are the most significant is to evaluate measurement uncertainty and calculate the percentage of the total variance (i.e. Factor Analysis) each source of uncertainty has on the combined standard measurement uncertainty.

How to calculate the most significant sources of uncertainty?

To determine the most significant sources of uncertainty, conduct a Factor Analysis to calculate the proportion or percentage of the total variance. The sources of uncertainty with higher percentages will be the most significant.

Follow the instructions below to calculate the percentage of total variance:

1. Calculate the variance – square each standard measurement uncertainty.
2. Calculate total variance – square the combined standard measurement uncertainty.
3. Divide each variance by the total variance.
4. Multiply the result by 100 to convert it to a percentage.
5. Find the uncertainties with the higher percentages.

How do random and systematic errors contribute to overall measurement uncertainty?

They both contribute to the total combined measurement uncertainty. Each error source is converted to a standard deviation equivalent (i.e. standard uncertainty) and combined in quadrature using the square root of the sum of squares (RSS) method to calculate the combined standard uncertainty. Then, the uncertainty can be expanded to a desired confidence interval by multiplying the combined uncertainty by a coverage factor.

According to the GUM (JCGM 100:2008), Recommendation INC-1 (1980) replaced the terms random and systematic uncertainties with Type A and Type B uncertainty.

Random uncertainties would be best associated with Type A uncertainty, where the magnitude of uncertainty is evaluated by statistical methods (typically ANOVA).

Systematic Uncertainty would be best associated with Type B Uncertainty, where the magnitude of uncertainty is evaluated by techniques other than statistical means (but not always). Systematic is defined as “of a system.” Therefore, you would want to evaluate sources of uncertainties that are “of the system” and not associated with random uncertainties.