ABSTRACT
The statistical measures like Entropy, Gini Index, Variance, and Coefficient of Variation (CV) are in use for decision-making. This chapter provides CV definition and its computation. It discusses CV for normalized data. The chapter presents properties of CV and its limitations. It also provides Interpretation aspects of CV. CV is positive when mean is positive and negative when mean is negative. While absolute CV is positive irrespective of mean being positive or negative. Absolute CV will be the same as CV when the mean is positive. CV is defined for numerical data. CV is not definable when mean is zero, it will be unbounded when the mean is approaching zero. The CV is a unit free index. Absolute CV (ACV) is always non-negative. In most of the applications, the data will be non-negative, hence CV is equivalent to ACV.
