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Partiallyrankeddatareferstothesituationinwhichthereare p distinctobjects; howevereachjudgespeciesonly rst s ( s < p ) choices. The group theoretic formulation for partially ranked data analysis was set up byCritchlow (1985). We propose a graphical method for partially ranked data by quantifying objects and judges.In a plot for judges, the interpoint distances can be interpreted as Spearman or Kendall distances between tworankings given by respective judges. Similarly, we also construct a plot for objects with a sensible relationship tothe previous plot for judges. This study extends the Han and Huh (1995) quantication method of fully rankeddata using Gabriel’s (1971) biplot technique for multivariate data matrix.Keywords: Partially ranked data, quantication, row plot, column plot, Biplot. 1. Introduction Partially ranked data are one of the most popular types of survey data. For example, potential buyersorder dierent brands of personal computers in terms of which one each buyer species only rstthrough

Graphical Representation of Partially Ranked Data