The new concepts of measurement error's regularities and effect characteristics. (October 2018) - Ye, Xiaoming
Highlights: Error's regularity and randomness depend on the perspectives of observing error. Error cannot be classified according its regularity and randomness. The influence characteristics of error depend on the method of repeated measurement. Error cannot be classified according its influence characteristics. Both function model and random model can be used to process the same error. Abstract: In several literatures, the authors give a new thinking of measurement theory system based on error non-classification philosophy, which completely overthrows the existing measurement concept system of precision, trueness and accuracy. In this paper, by focusing on the issues of error's regularities and effect characteristics, the authors will do a thematic interpretation, and prove that the error's regularities actually come from different cognitive perspectives, are also unable to be used for classifying errors, and that the error's effect characteristics actually depend on artificial condition rules of repeated measurement, and are still unable to be used for classifying errors. Thus, from the perspectives of error's regularities and effect characteristics, the existing error classification philosophy is still incorrect; and an uncertainty concept system, which must be interpreted by the error non-classification philosophy, naturally becomes the only way out of measurement theory.