Correlation of Error Sources

Correlations can exist between measurement process errors for a given variable or parameter.  In the case of a multivariate uncertainty analysis, cross-correlations can also exist between the measurement process errors for different variables or parameters.  If a correlation exists between process uncertainties, or between component uncertainties, it can affect the way in which they are combined.  This, in turn, will impact how the overall measurement uncertainty is computed. 

The Correlation Coefficient Worksheet is a straightforward tool for correlating error sources for direct measurement, and multivariate measurement analyses.  Two error sources are dependent (i.e., correlated) if one exerts an influence over the other or if both are consistently influenced by a common agency.  For example, measurement errors are dependent if the measurements are made with the same measuring device and measuring parameter.

Compensating Biases

A negative correlation coefficient is entered if the bias or error of one measured variable offsets the bias or error of another measured variable.  For instance, if the same measuring parameter is used to measure the inside diameter of a sleeve and the outside diameter of a shaft that fits into the sleeve, any error or bias in the two measurements will not affect the quality of fit. In other words, the measurement biases offset each other.