The map below shows majority race by area in Enterprise, as self-identified on the US census. Darker shades indicate a larger racial majority in that neighborhood. This page also contains data and maps on Enterprise racial diversity and diversity scores. Click here to scroll to diversity data.
The majority race in Enterprise overall is white, making up 93.9% of residents. The next most-common racial group is other at 6.0%. There are more white people in the central areas of the city. People who identify as other are most likely to be living in the northeast places. The data below shows how many people identify themselves as each of the following races, which most Americans base on their family's national origin:
Race in Enterprise
Self-Identified Race |
Enterprise, UT Population |
|---|---|
White |
93.9% |
Hispanic |
0.1% |
Black |
0.0% |
Asian |
0.0% |
Native American |
0.0% |
Other |
6.0% |
Diversity and Diversity Scores for Enterprise, UT
The map below shows diversity in Enterprise. Areas in green are more diverse, while areas in red are much less diverse. Diversity, in this case, means a mixture of people with different race and ethnicity living close to one another. For example, all-black and all-white areas in the city would both be considered lacking diversity.
Enterprise Diversity Score
11.4
More diverse than 23% of US cities
Enterprise has a diversity score of 11.4: the chance, in percent, that two residents picked at random belong to different racial or ethnic groups, from ACS race counts. A place where everyone shares one group scores 0, and an even mix of the six groups in the chart above scores the maximum, 83.3. Enterprise is less diverse than other US cities, more diverse than 23% of them. Within Enterprise's proper boundaries, the most diverse area is northeast Enterprise, and the least diverse areas are in central Enterprise.
Source: BestNeighborhood calculations from the U.S. Census Bureau, American Community Survey (ACS) 2020-2024 5-year estimates (race and Hispanic origin); proprietary data mapping and analysis. Special thanks to the University of Virginia.