How do you calculate standard deviation on a CV?
The coefficient of variation is the standard deviation divided by the mean and is calculated as follows: In this case µ is the indication for the mean and the coefficient of variation is: 32.5/42 = 0.77. This means that the size of the standard deviation is 77% of the size of the mean.
Should I use standard deviation or coefficient of variation?
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. For comparison between data sets with different units or widely different means, one should use the coefficient of variation instead of the standard deviation.
How is the coefficient of variation related to the standard deviation?
Coefficient of Variation (CV) If you know nothing about the data other than the mean, one way to interpret the relative magnitude of the standard deviation is to divide it by the mean. This is called the coefficient of variation. For example, if the mean is 80 and standard deviation is 12, the cv = 12/80 =.15 or 15%.
How is the coefficient of variation related to the SD?
Several other useful measures of dispersion are related to the SD: Variance: The variance is just the square of the SD. For the IQ example, the variance = 14.42 = 207.36. Coefficient of variation: The coefficient of variation (CV) is the SD divided by the mean.
What is the standard deviation of the CV?
For example, if the mean is 80 and standard deviation is 12, the cv = 12/80 = .15 or 15%. If the standard deviation is .20 and the mean is .50, then the cv = .20/.50 = .4 or 40%.
When to use a CV vs.a SD?
CV should only be used for ratio scales for things like mass or length that have a non-arbitrary zero point. If the data is on a ratio scale, CV and SD are both acceptable, but must be interpreted differently. In your example, both A and B have identical SD, indicating their variation is the same in an absolute sense.