processes indeed show a correlation between the average value and the amount of variation around it, accurate sensor devices need to be designed in such a way that the coefficient of variation is close to zero, i.e., yielding a constant absolute error over their working range. In actuarial science, the CV is known as unitized risk. In Industrial Solids Processing, CV is particularly important to measure the degree of homogeneity of a powder mixture. Comparing the calculated CV to a specification will allow to define if a sufficient degree of mixing has been reached. Laboratory measures of intra-assay and inter-assay CVs CV measures are often used as quality controls for quantitative laboratory assays. While intra-assay and inter-assay CVs might be assumed to be calculated by simply averaging CV values across CV values for multiple samples within one assay or by averaging multiple inter-assay CV estimates, it has been suggested that these practices are incorrect and that a more complex computational process is required. It has also been noted that CV values are not an ideal index of the certainty of a measurement when the number of replicates varies across samples − in this case standard error in percent is suggested to be superior. If measurements do not have a natural zero point then the CV is not a valid measurement and alternative measures such as the intraclass correlation coefficient are recommended. As a measure of economic inequality The coefficient of variation fulfills the requirements for a measure of economic inequality. If x (with entries xi) is a list of the values of an economic indicator (e.g. wealth), with xi being the wealth of agent i, then the following requirements are met: Anonymity – cv is independent of the ordering of the list x. This follows from the fact that the variance and mean are independent of the ordering of x. Scale invariance: cv(x) = cv(αx) where α is a real number. Population independence – If {x,x} is the list x appended to itself, then cv({x,x}) = cv(x). This follows from the fact that the variance and mean both obey this principle. Pigou–Dalton transfer principle: when wealth is transferred from a wealthier agent i to a poorer agent j (i.e. xi > xj) without altering their rank, then cv decreases and vice versa. cv assumes its minimum value of zero for complete equality (all xi are equal). Its most notable drawback