Abstract
In this research, we will investigate several different approaches and methods to displaying multivariate data. Emphasis will be placed on end-user-customization tools and flexibility in dynamic and interactive displays. Specifically, we will highlight the use of motion charts using Markus Gesmann’s googleVis package in R. We will demonstrate the visualization of time-series data and also the results of multidimensional scaling and principal component analysis using this tool. The goals of these displays are ease of usability and interpretation, dynamic customization options, and the ability to display multivariate data in a meaningful way. In addition we will explore partial least squares path modeling using data collected from the Knight Foundation and Gallup during the years 2008–2010 to illustrate the attachment of people to their communities in a new and innovative way.
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