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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:
Bivariate mapping is a comparatively recent graphical method. A bivariate [[choropleth map]] uses color to solve a problem of representation in four dimensions; two spatial dimensions — longitude and latitude — and two statistical variables. Take the example of mapping population density and average daily maximum temperature simultaneously. Population could be given a colour scale of black to green, and temperature from blue to red. Then an area with low population and low temperature would be dark blue, high population and low temperature would be cyan, high population and high temperature would be yellow, while low population and high temperature would be dark red. The eye can quickly see potential relationships between these variables.▼
[[File:Bivariate.png|thumb|
* 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 ''multivariate [[Dot distribution map | dot density map]]'' mixes dots of different colors in each district, typically representing separate subgroups of the overall population.
* A ''multivariate symbol map'' represents two or more variables in the same thematic map layer, using distinct [[visual variables]] for each variable. For example, a layer of cities might be symbolized with circles of [[Proportional symbol map|proportional size]] representing its total population, and the hue of each circle representing the predominant source type of its electric power, akin to a nominal [[choropleth map]].
* 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 map of the 2016 U.S. presidential election, using a combination proportional and chart symbol]]
▲[[File:Bivariate.png|thumb|left|Example of a bivariate thematic map, displaying minority proportion as a choropleth, and family size as a proportional 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.
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