On testing the equality between interquartile ranges

Luca Greco (), George Luta and Rand Wilcox
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Luca Greco: University Giustino Fortunato
George Luta: Georgetown University
Rand Wilcox: University of Southern California

Computational Statistics, 2024, vol. 39, issue 5, No 19, 2873-2898

Abstract: Abstract The interquartile range is a statistical measure well suited to describe the variability of the data at hand, both at the population level and for sample data. The interquartile range is particularly useful when the distribution of the data is asymmetric or irregularly shaped. Here, the use of the interquartile range is investigated when the main aim is to compare the variability of two distributions using two independent random samples, without the need to make any distributional assumptions. Several techniques are compared through numerical studies and real data examples, with a particular attention given to the use of sample quantiles based on the Harrel-Davis estimator or the quantile regression.

Keywords: Bootstrap; Contingency table; Harrel-Davis estimator; LRT; Non-parametric; Quantiles (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s00180-023-01415-8

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