Contents
Can you have a negative coefficient of variation?
If the mean is negative, the coefficient of variation will be negative while the relative standard deviation (as defined here) will always be positive. The COEFFICIENT OF VARIATION command divides by the mean rather than the absolute value of the mean.
Can a coefficient of variation be 0?
That is, it shows the variability, as defined by the standard deviation, relative to the mean. The coefficient of variation should typically only be used for data measured on a ratio scale. That is, the data should be continuous and have a meaningful zero.
Is this what one call a non-parametric CV?
And, is this what one may call a non-parametric CV? The coefficient of variation is not strongly associated with the normal distribution at all. It is most obviously pertinent for distributions like the lognormal or gamma. See e.g. this thread.
Is the coefficient of variation dependent on normality?
The paper is from 2010. So my question is: has there been any recent “advancements” in terms of a coefficient of variation statistic that is not dependent upon the normality assumption? And, is this what one may call a non-parametric CV? The coefficient of variation is not strongly associated with the normal distribution at all.
Is the coefficient of variation the same as the CV?
As Peter and John said, this normalization is done as when calculating the coefficient of variation (CV), which equals SD/Mean. The SD is in in the same units as the original data. In contrast, the CV is a unitless ratio. Your choice 1 (IQR/Median) is analogous to the CV.
Which is a better alternative to coefficient of variation?
There are many others as well. This paper presents two good robust alternatives for the coefficient of variation. One is the interquartile range divided by the median, that is: They compare them and conclude generaly speaking the second is a little less variable and probably better for most applications.