Communications for Statistical Applications and Methods

The Korean Statistical Society (한국통계학회)
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Relationship between the Sample Quantiles and Sample Quantile Ranks

표본분위수와 표본분위의 관계

  • Ahn, Sung-Jin (Department of Information Statistics, RINS & RICIC, Gyeongsang National University)
  • 안성진 (경상대학교 기초과학연구소 및 컴퓨터정보통신 연구소, 정보통계 학과)
  • Received : 20110800
  • Accepted : 20110900
  • Published : 2011.11.30
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Abstract

Quantiles and quantile ranks(or plotting positions) are widely used in academia and industry. Sample quantile methods and sample quantile methods implemented in some major statistical software are at least seven, respectively. Small looking differences between the methods can make big differences in outcomes that result from decisions based on them. We discussed the characteristics and differences of the basic plotting position using the empirical cumulative probability and the six plotting positions derived from the suggestion of Blom (1958). After discussing the characteristics and differences of seven quantile methods used in the some major statistical software, we suggested a general expression covering all seven quantile methods. Using the insight obtained from the general expression, we proposed four propositions that make it possible to find the plotting position method that correspond to each of the seven quantile methods. These correspondences may help us to understand and apply quantile methodology.

분위수와 분위(또는 타점위치)는 학계에서나 산업계에서 널리 사용되고 있다. 그런데 통계 소프트웨어에 구현되어 있는 표본 분위수 계산방법들과 표본 분위 계산방법들은 각각 적어도 일곱 가지가 있다. 분위수들이나 분위들을 정의하는 방법들 간의 사소해 보이는 차이가 그 값을 토대로 이루어지는 결정의 큰 차이를 가져올 수 있다. 이 논문에서는 경험적 누적확률을 사용한 기본 타점위치 방법과 Blom (1958)의 제안을 토대로 파생된 여섯 가지 타점위치 방법의 특징과 차이점을 논의하였다. 또 통계소프트웨어에 구현되어 있는 일곱 가지 표본분위수 계산방법들의 특징과 차이점들을 논의한 후 이들을 망라하는 하나의 일반식을 제시하였다. 이 논문에서는 이 일반식으로부터 얻어지는 통찰을 토대로 표본분위수에 대응되는 표본분위를 구하는 방법을 제안하였고, 이 제안을 각 표본분위수 방법에 적용하여 대응되는 표본분위 방법을 도출하였다. 이런 대응관계는 표본분위수와 표본분위에 대한 종합적 이해와 적용에 도움을 줄 수 있을 것이다.

Keywords

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