Multivariate map: Difference between revisions

Revision as of 09:03, 8 November 2020

Revision as of 09:04, 8 November 2020

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==Methods==

There are a variety of ways in which separate variables can be mapped simultaneously, which generally fall into a few approaches:

[[File:Bivariate.png|thumb|right|A multilayeredmulti-layered thematic map, displaying minority proportion as a choropleth, and family size as a proportional symbol]]

* A ''multi-layered thematic map'' portrays the variables as separate map layers, using different [[thematic map]] techniques. An example would be showing one variable as a [[choropleth map]], with another variable shown as [[Proportional symbol map|proportional symbols]] on top of the choropleth.

* A ''correlated symbol map'' represents two or more variables in the same thematic map layer, using the same [[visual variable]], designed in such a way as to show the relative combination of the two variables.

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* A ''chart map'' represents each geographic feature with a [[Chart | statistical chart]], often a [[pie chart]] or [[bar chart]], which can include a number of variables.

[[File:2016 US Presidential Election Pie Charts.png|thumb|right|300px|A multivariate symbol map of the 2016 U.S. presidential election, using a combination proportional and chart symbol]]

Data classification and graphic representation of the classified data are two important processes involved in constructing a bivariate map. The number of classes should be possible to deal with by the reader. A rectangular legend box is divided into smaller boxes where each box represents a unique relationship of the variables.