On central tendency and dispersion measures for intervals and hypercubes

TL;DR

This paper introduces a geometrical method for deriving central tendency and dispersion measures for interval-valued data, enhancing the statistical analysis of data with inherent uncertainty.

Contribution

It presents a novel geometrical approach to compute summary statistics for interval-valued datasets, addressing the challenge of data uncertainty.

Findings

Developed a new geometrical framework for interval data analysis

Provided formulas for central tendency and dispersion measures

Improved understanding of variability in interval-valued data

Abstract

The uncertainty or the variability of the data may be treated by considering, rather than a single value for each data, the interval of values in which it may fall. This paper studies the derivation of basic description statistics for interval-valued datasets. We propose a geometrical approach in the determination of summary statistics (central tendency and dispersion measures) for interval-valued variables.