How can one relate the coefficient of variation (C.V) to Data Envelopment Analysis.I think there should be a way of relating them, since they measure efficiency.
Hi,
In some cases, it may be most relevant to describe the relative variation within a sample or population. Normally, the Coefficient of Variation is calculated by the following formula:
CV% = Standard Deviation / Mean
In another way, knowing the sample SD is really not very informative unless we also know the sample mean. Thus, low Coefficient of Variations (CVs) indicate relatively little variation within the sample, and higher CVs indicate more variation. In addition, because units will cancel out in this equation, CV is a unitless expression. This is actually advantageous when comparing relative variation between parameters that are described using different scales or distinct types of measurements.
Note, however, that in situations where the mean value is zero or very close to zero, the CV could approach infinity and will not provide useful information. A similar warning applies in cases when data can be negative. The CV is most useful and meaningful only for positively valued data. A variation on the CV is its use as applied to a statistic rather than to individual variation.
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