One of the most useful indicators relative dispersion is coefficient variation. The characteristics variation have contributed to its widespread use in scientific and academic disciplines, with real life applications. traditional estimators are based on conventional moments; therefore, these highly affected by presence extreme values. In this article, we develop some novel calibration-based for...

This study examined if, among families whose children were enrolled in the Ferst Foundation for Childhood Literacy, there was a relationship between the home literacy environment, measured by a scale survey, and the length of time enrolled in the program. Participants were a stratified random sampling from the population of parents in the State of Georgia whose children were enrolled in the Fer...

In this article we have considered the problem of estimating the population mean   Y in the stratified random sampling using the information of an auxiliary variable x which is correlated with y and suggested improved exponential ratio estimators in the stratified random sampling. The mean square error (MSE) equations for the proposed estimators have been derived and it is shown that the prop...

The main objective of this study is to come to know the fact that which level of the three levels of managers (Top, Middle and Low Level) has more participation in applying e-commerce in the organization. Another purpose of the study is to know that how many people are employed as IT personal in the Indian small and medium enterprises? In this study we used Stratified Random Sampling to collect...

This article develops a method of ratio estimate in fuzzy sense. By both the simple random sampling and stratified random sampling, we can obtain the ratio estimate in usual statistical sense. However, the sampling data may be ambiguous in some uncertain circumstance. To solve such kind of problem, we probe into the simple random sampling and stratified random sampling in fuzzy sense, obtain th...

Recent research advocates applying sampling to accelerate microarchitecture simulation. Simple random sampling offers accurate performance estimates (with a high quantifiable confidence) by taking a large number (e.g., 10,000) of short performance measurements over the full length of a benchmark. Simple random sampling does not exploit the often repetitive behaviors of benchmarks, collecting ma...