Calculate the coefficient of variation (CV) to measure relative variability in any data set. Used in finance, quality control, and scientific research.
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The coefficient of variation (CV) is a standardized measure of dispersion that expresses standard deviation as a percentage of the mean. Unlike standard deviation alone, CV allows meaningful comparison of variability between data sets with different units or scales.
Formula: CV = (Standard Deviation ÷ Mean) × 100%
A high CV (typically above 30%) indicates that the data has high variability relative to the mean. In finance, a high CV for an investment's returns signals higher risk per unit of expected return.
Use sample CV (n-1 in denominator) when your data is a sample drawn from a larger population — this is the most common case. Use population CV (n) only when you have data for the entire population.
CV is technically negative when the mean is negative, which can happen with financial returns during bear markets. In practice, CV is usually reported as an absolute value, so negative CVs are typically expressed as positive numbers.
For laboratory measurements, a CV below 10% is generally acceptable. For biological assays, below 15% is typical. For financial data, CVs of 20–50% are common for equity returns.
Standard deviation measures absolute variability in the same units as the data. CV measures relative variability as a percentage of the mean, making it unit-free. This allows comparison between data sets with different means or units.
Yes — relative standard deviation (RSD) is another name for the coefficient of variation. Both are calculated as standard deviation divided by the mean, typically expressed as a percentage.