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What is a coefficient of variation (CV)?
What is a coefficient of variation (relative standard deviation)?
What is the coefficient of variation of a data set?
Why is the coefficient of variation important?
In probability theory and statistics, the coefficient of variation (CV), 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.
Jan 16, 2021 · Coefficient of variation is the standard deviation divided by the mean; it summarizes the amount of variation as a percentage or proportion of the total. It is useful when comparing the amount of variation for one variable among groups with different means, or among different measurement variables.
The coefficient of variation (CV) is a relative measure of variability that indicates the size of a standard deviation in relation to its mean. It is a standardized, unitless measure that allows you to compare variability between disparate groups and characteristics. It is also known as the relative standard deviation (RSD).
The coefficient of variation (relative standard deviation) is a statistical measure of the dispersion of data points around the mean. The metric is commonly used to compare the data dispersion between distinct series of data.
The coefficient of variation CV is defined as the ratio of the standard deviation to the arithmetic mean for a set of observations; in other words: $$ CV = \frac {S} {\bar {x}} \cdot 100 $$ for a sample, where: S : is the standard deviation of the sample, and. \ ( { \bar {x} } \) : is the arithmetic mean of the sample, or:
Variance is a measure of dispersion, meaning it is a measure of how far a set of numbers is spread out from their average value. It is the second central moment of a distribution, and the covariance of the random variable with itself, and it is often represented by , , , , or . [1]
Coefficient of variation. Quartile coefficient of dispersion. Relative mean difference, equal to twice the Gini coefficient.
