When Outliers Are Different

TL;DR

This paper investigates when outliers indicate qualitative differences in objects, proposing a statistical test based on power law distributions and applying it to astrophysical phenomena like gamma-ray bursts and fast radio bursts.

Contribution

It introduces a method to distinguish qualitative from quantitative outliers using power law distribution comparisons, with applications to astrophysical data.

Findings

SGR 1806-20 outburst is a qualitative outlier

FRB 200428 is a qualitative outlier in location

FRB 121102 is not a significant outlier in rotation measure

Abstract

When does the presence of an outlier in some measured property indicate that the outlying object differs qualitatively, rather than quantitatively, from other members of its apparent class? Historical examples include the many types of supernov\ae\ and short {\it vs.\/} long Gamma Ray Bursts. There may be only one parameter and one outlier, so that principal component analyses are inapplicable. A qualitative difference implies that some parameter has a characteristic scale, and hence its distribution cannot be a power law (that can have no such scale). If the distribution is a power law the objects differ only quantitatively. The applicability of a power law to an empirical distribution may be tested by comparing the most extreme member to its next-most extreme. The probability distribution of their ratio is calculated, and compared to data for stars, radio and X-ray sources, and the fluxes, fluences and rotation measures of Fast Radio Bursts. It is found with high statistical significance that the giant outburst of soft gamma repeater SGR 1806-20 differed qualitatively from its lesser outbursts and FRB 200428 differed qualitatively from other FRB (by location in the Galaxy), but that in some supernova remnant models of rotation measure FRB 121102 is not, statistically significantly, an outlier.