Inspection Strategy under Indeterminacy Based on Neutrosophic Coefficient of Variation

Abstract

The existing sampling plans which use the coefficient of variation (CV) are designed under classical statistics. These available sampling plans cannot be used for sentencing if the sample or the population has indeterminate, imprecise, unknown, incomplete or uncertain data. In this paper, we introduce the neutrosophic coefficient of variation (NCV) first. We design a sampling plan based on the NCV. The neutrosophic operating characteristic (NOC) function is then given and used to determine the neutrosophic plan parameters under some constraints. The neutrosophic plan parameters such as neutrosophic sample size and neutrosophic acceptance number are determined through the neutrosophic optimization solution. We compare the efficiency of the proposed plan under the neutrosophic statistical interval method with the sampling plan under classical statistics. A real example which has indeterminate data is given to illustrate the proposed plan.

Inference about the Ratio of the Coefficients of Variation of Two Independent Symmetric or Asymmetric Populations

“…In this section, the accuracy of the given theoretical results is studied and analyzed by different simulated datasets. For the populations X and Y, we respectively simulated different samples from symmetric distribution (normal) and asymmetric distributions (gamma and beta) with different CV values, (2,5) , which are equivalent to γ ∈ {1, 2, 1.5, 2.5}. Figures 1-3 show the plots of probability density function (PDF) for the considered distributions.…”

“…The division of the standard deviation to the mean of population, CV = σ µ , is called as coefficient of variation (CV) which is an applicable statistic to evaluate the relative variability. This free dimension parameter can be widely used as an index of reliability or variability in many applied sciences such as agriculture, biology, engineering, finance, medicine, and many others [1][2][3]. Since it is often necessary to relate the standard deviation to the level of the measurements, the CV is a widely used measure of dispersion.…”

A Cross-Sectional Comparative Study of Morbidity and Mortality of COVID-19 Disease in four Cities of Northern Khorasan Province using Ratio of Coefficient of Variation

“…[ 4 ] CV is a free parameter used in many sciences such as agriculture, biology, engineering, finance, medicine, and many others to indicate reliability or variability. [ 5 6 7 ] In many cases, relating standard deviation to the level of measurement is of great importance to researchers. For this reason, CV is widely used to measure dispersion.…”

Improved Confidence Interval and Hypothesis Testing for the Ratio of the Coefficients of Variation of Two Uncorrelated Populations

“…The coefficient of variation (CV) is obtained by dividing the population standard deviation by the population mean, CV = σ/µ, being an applicable and suitable statistic for evaluating relative variability. The CV is a free parameter that is used in many areas, such as agronomy, biology, engineering, finance, medicine and others, as an indicator of reliability or variability [1][2][3]. In many cases, relating standard deviation to the level of measurement is of great importance to researchers.…”