![]() ![]() In this case, standard error in percent is suggested to be superior. CVs are not an ideal index of the certainty of measurement when the number of replicates varies across samples because CV is invariant to the number of replicates while the certainty of the mean improves with increasing replicates.Unlike the standard deviation, it cannot be used directly to construct confidence intervals for the mean.This is often the case if the values do not originate from a ratio scale. When the mean value is close to zero, the coefficient of variation will approach infinity and is therefore sensitive to small changes in the mean.In contrast, the actual value of the CV is independent of the unit in which the measurement has been taken, so it is a dimensionless number.įor comparison between data sets with different units or widely different means, one should use the coefficient of variation instead of the standard deviation. The coefficient of variation is useful because the standard deviation of data must always be understood in the context of the mean of the data. ![]() It is defined as the ratio of the standard deviation σ or GCV by inverting the corresponding formula.Ĭomparison to standard deviation Advantages In probability theory and statistics, the coefficient of variation ( COV), also known as Normalized Root-Mean-Square Deviation (NRMSD), Percent RMS, and relative standard deviation ( RSD), is a standardized measure of dispersion of a probability distribution or frequency distribution. ![]()
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