Quantile Analysis: A Method for Characterizing Data Distributions

Abstract

Analyzing distributions of data represents a common problem in analytical 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 if 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 classical statistical methods that rely on a single test statistic for distribution comparisons.

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Document Details

Document Type
Technical Report
Publication Date
Jul 11, 1988
Accession Number
ADA198215

Entities

People

  • Gary M. Hieftje
  • Robert A. Lodder

Organizations

  • Indiana University

Tags

Communities of Interest

  • Ground and Sea Platforms
  • Weapons Technologies

DTIC Thesaurus Topics

  • Analytical Chemistry
  • Chemical Analysis
  • Chemistry
  • Computational Science
  • Data Analysis
  • Data Science
  • Deoxyribonucleic Acids
  • Distribution Functions
  • Gaussian Distributions
  • Information Processing
  • Information Science
  • Liquid Chromatography
  • Mathematical Models
  • Military Research
  • Order Statistics
  • Scattering
  • Spectra

Fields of Study

  • Mathematics

Readers

  • Regression Analysis.
  • Statistical inference.