Introduction to Neutrosophic Statistics

TL;DR

This paper introduces neutrosophic statistics, a new approach for analyzing data with indeterminacy, ambiguity, or incompleteness, extending traditional statistical methods to handle uncertain and vague information.

Contribution

It develops the concept of neutrosophic statistics, providing a framework to analyze populations with indeterminate or ambiguous data, and presents practical examples illustrating its application.

Findings

Framework for neutrosophic data analysis

Handling of indeterminate population data

Application examples demonstrating utility

Abstract

Neutrosophic Statistics means statistical analysis of population or sample that has indeterminate (imprecise, ambiguous, vague, incomplete, unknown) data. For example, the population or sample size might not be exactly determinate because of some individuals that partially belong to the population or sample, and partially they do not belong, or individuals whose appurtenance is completely unknown. Also, there are population or sample individuals whose data could be indeterminate. In this book, we develop the 1995 notion of neutrosophic statistics. We present various practical examples. It is possible to define the neutrosophic statistics in many ways, because there are various types of indeterminacies, depending on the problem to solve.