Quantile Functions

  • N. Unnikrishnan Nair
  • P. G. Sankaran
  • N. Balakrishnan
Part of the Statistics for Industry and Technology book series (SIT)


A probability distribution can be specified either in terms of the distribution function or by the quantile function. This chapter addresses the problem of describing the various characteristics of a distribution through its quantile function. We give a brief summary of the important milestones in the development of this area of research. The definition and properties of the quantile function with examples are presented. In Table 1.1, quantile functions of various life distributions, representing different data situations, are included. Descriptive measures of the distributions such as location, dispersion and skewness are traditionally expressed in terms of the moments. The limitations of such measures are pointed out and some alternative quantile-based measures are discussed. Order statistics play an important role in statistical analysis. Distributions of order statistics in quantile forms, their properties and role in reliability analysis form the next topic in the chapter. There are many problems associated with the use of conventional moments in modelling and analysis. Exploring these, and as an alternative, the definition, properties and application of L-moments in describing a distribution are presented. Finally, the role of certain graphical representations like the Q-Q plot, box-plot and leaf-plot are shown to be useful tools for a preliminary analysis of the data.


Order Statistic Residual Life Quantile Function Life Testing Experiment Pitman Closeness 
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© Springer Science+Business Media New York 2013

Authors and Affiliations

  • N. Unnikrishnan Nair
    • 1
  • P. G. Sankaran
    • 1
  • N. Balakrishnan
    • 2
  1. 1.Department of StatisticsCochin University of Science and TechnologyCochinIndia
  2. 2.Department of Mathematics and StatisticsMcMasters UniversityHamiltonCanada

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