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Statistical Graphics for Visualizing Multivariate Data
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Statistical Graphics for Visualizing Multivariate Data

  • William G. Jacoby - Michigan State University, USA, University of South Carolina, Colombia


February 1998 | 112 pages | SAGE Publications, Inc
Author William G. Jacoby explores a variety of graphical displays that are useful for visualizing multivariate data. The basic problem involves representing information that varies along several dimensions when the display medium (a computer screen or printed page) is inherently two-dimensional. In order to address this problem, Jacoby introduces the concepts of a "data space." He then explains several methods for coding information directly into the plotting symbols used to represent the observations. He next describes pictorial representations of three-dimensional space followed by a discussion of the scatterplot matrix as a way of "flattening out" the multiple dimensions of a multivariate data space. In addition, he examines conditioning plots (which are strategies for "looking into subregions" of the multidimensional data space), and presents the biplot as a technique for showing observations and variables together in a single display. He concludes with a discussion of some general ideas about data visualization. Statistical Graphics for Visualizing Multivariate Data will enable researchers to better explore the contents of a dataset, find the structure in their data, check the underlying assumptions of the statistical model they used, and better communicate the results of their analysis.

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Introduction
 
Multiple-Code Plotting Symbols in Scatterplots
 
Profile Plots
 
Three-Dimensional Plots for Trivariate Data
 
The Scatterplot Matrix
 
Conditioning Plots
 
The Biplot
 
Conclusions

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