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[[File:Black Hispanic Bivariate Map.png|thumb|400px|Bivariate choropleth map comparing the Black (blue) and Hispanic (red) populations in the United States, 2010 census; shades of purple show significant proportions of both groups.]]
A '''bivariate map''' displays two [[Variable (mathematics)|variables]] on a single [[map]] by combining two different sets of graphic symbols or colors. Bivariate mapping is an important technique in [[cartography]]. It is a variation of simple [[choropleth map]] that portrays two separate phenomena simultaneously. The main objective is to accurately and graphically illustrate the [[Correlation and dependence|relationship]] between two spatially distributed variables. It has potential to reveal relationships between variables more effectively than a side-by-side comparison of the corresponding univariate maps.
[[File:Bivariate.png|thumb|Example of a bivariate thematic map, displaying minority concentration and family size]]▼
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|Example of a bivariate thematic map, displaying minority concentration and family size]]
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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