Exploratory Graphical Techniques for Ranked Data,
Abstract
Graphical methods are critically needed to display frequency distributions for fully ranked data. Fully ranked data occur, for example, when judges are asked to rank n items, possibly with pseudoranks, in order of preference. Each observation is a permutation of the n distinct pseudoranks, and the resulting set of frequencies is a function on S(n), the symmetric group of n elements. Because S(n) does not have a natural linear ordering, graphical methods such as histograms and bar graphs cannot be used to display frequency distributions for ranked data. Other existing graphical methods for rankings include multidimensional scaling, minimal spanning trees, and nearest neighbor graphs as discussed by Diaconis (1988). Cohen and Mallows (1980) propose graphical methods based on multi-dimensional scaling and biplots. Cohen (1990) presents alternate exploratory data techniques for ranked data.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jan 01, 1992
- Accession Number
- ADP007103
Entities
People
- Georgia L. Thompson
Organizations
- Southern Methodist University