ABSTRACT
The technological growth in the storage systems and high-performance computing gave the opportunity to design the computational strategies to calculate required statistics and then information processing for making decisions to address the real-world problems preferably just in time. The computational methods should sink with various natural topological configurations of data management systems, communication systems, which avoid frequent visits of voluminous raw data. This chapter provides the computation of Coefficient of Variation (CV) when data are at a distributed location, which is known as computation of CV for pooled data. As CV is meaningful to compute only for continuous variables that are of ratio type, there is a need for developing some meaningful transformations such that CV computations can be employed to arrive at meaningful recommendations and apt inference engines. Computation of CV requires computation of mean and standard deviation. The chapter demonstrates computation of Coefficient of Variation for a distributed data restricting to one pass methodology.
