<P> In probability theory and statistics, the coefficient of variation (CV), also known as relative standard deviation (RSD), is a standardized measure of dispersion of a probability distribution or frequency distribution . It is often expressed as a percentage, and is defined as the ratio of the standard deviation σ (\ displaystyle \ \ sigma) to the mean μ (\ displaystyle \ \ mu) (or its absolute value, μ (\ displaystyle \ mu)). The CV or RSD is widely used in analytical chemistry to express the precision and repeatability of an assay . It is also commonly used in fields such as engineering or physics when doing quality assurance studies and ANOVA gauge R&R . In addition, CV is utilized by economists and investors in economic models and in determining the volatility of a security . </P> <P> The coefficient of variation (CV) is defined as the ratio of the standard deviation σ (\ displaystyle \ \ sigma) to the mean μ (\ displaystyle \ \ mu):: c v = σ μ (\ displaystyle c_ (\ rm (v)) = (\ frac (\ sigma) (\ mu))) It shows the extent of variability in relation to the mean of the population . The coefficient of variation should be computed only for data measured on a ratio scale, as these are the measurements that can only take non-negative values . The coefficient of variation may not have any meaning for data on an interval scale . For example, most temperature scales (e.g., Celsius, Fahrenheit etc .) are interval scales that can take both positive and negative values, whereas the Kelvin temperature can never be less than zero, which is the complete absence of thermal energy . Hence, the Kelvin scale is a ratio scale . While the standard deviation (SD) can be derived on both the Kelvin and the Celsius scale (with both leading to the same SDs), the CV is only relevant as a measure of relative variability for the Kelvin scale . </P>

What does the coefficient of variation tell us