Enter the mean and the standard deviation of a population or sample into the calculator to determine the coefficient of variation.
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Coefficient of Variation Formula
The following equation can be used to calculate the coefficient of variation of a data set, usually a population or sample.
C = (σ / μ) * 100
- Where C is the coefficient of variation (%)
- σ is the standard deviation
- μ is mean or average
To calculate the coefficient of variation, divide the standard deviation by the mean, then multiply by 100 to display as a percentage.
Coefficient of Variation
The coefficient of variation is very similar to the standard deviation. In short, it measures how much a data set varies across a population. It’s different because it’s then normalized to the population mean, which means the coefficient could be applied to a different mean to yield a new standard deviation.
How to calculate coefficient of variation?
How to calculate coefficient of variation.
- First, determine the standard deviation.
Calculate the standard deviation of the data set.
- Next, determine the mean.
Calculate the mean or average of the data set.
- Finally, calculate the coefficient of variation.
Using the formula above, calculate the coefficient of variation.
FAQ
Why is the coefficient of variation important in statistical analysis?
The coefficient of variation is important because it provides a dimensionless measure of variability relative to the mean. This allows for the comparison of variability across data sets with different units or scales, making it a valuable tool for comparing the relative dispersion of data sets.
Can the coefficient of variation be negative?
No, the coefficient of variation cannot be negative because it is derived from the standard deviation and the mean, both of which are non-negative values. A negative coefficient of variation would not make sense in the context of measuring variability.
How does the coefficient of variation compare to the standard deviation?
While both the coefficient of variation and standard deviation measure the spread of data points in a data set, the key difference is that the coefficient of variation normalizes the standard deviation by the mean. This normalization allows for comparison between data sets with different means, which is not possible with standard deviation alone.
