ABSTRACT
The coefficient of variation (CV) of a random variable (or that of the corresponding population), defined to be the ratio of the standard deviation to the mean of the corresponding population, has been used in wide-ranging applications in many areas of applied research including agro-biological, industrial, social, and economic research (Johnson et al. 1994, Chapter 15). In these applications, the random variable of interest is assumed to follow a Gaussian distribution that is symmetric and has support on the whole real number line (see Laubscher 1960, Singh 1993, Johnson et al. 1994, Chaubey et al. 2013). However, in many of these applications, the random variable may be more appropriately modeled by a distribution, which is positively skewed and is supported on the positive half. To model such situations, use of an inverse Gaussian (IG) distribution is often more justified compared to lognormal, gamma, and Weibull distributions (see Chhikara and Folks 1977, 1989, Kumagai et al. 1996, Takagi et al. 1997). More recently, Mudholkar and Natarajan (2002) discussed comparisons of shape of the IG distribution with the Gaussian distribution.
