Quantile analysis: A method for characterizing data distributions

Robert A. Lodder, Gary M. Hieftje

Research output: Contribution to journalArticlepeer-review

26 Scopus citations

Abstract

Analyzing distributions of data represents a common problem in chemistry. Quantile-quantile (QQ) plots provide a useful way to attack this problem. These graphs are often used in the form of the normal probability plot, to determine whether the residuals from a fitting process are randomly distributed and therefore whether an assumed model fits the data at hand. By comparing the integrals of two probability density functions in a single plot, QQ plotting methods are able to capture the location, scale, and skew of a data set. This procedure provides more information to the analyst than do classical statistical methods that rely on a single test statistic for distribution comparisons.

Original languageEnglish
Pages (from-to)1512-1520
Number of pages9
JournalApplied Spectroscopy
Volume42
Issue number8
DOIs
StatePublished - 1988

ASJC Scopus subject areas

  • Instrumentation
  • Spectroscopy

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