The map below shows majority race by area in Grass Range, 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 Grass Range racial diversity and diversity scores. Click here to scroll to diversity data.
The majority race in Grass Range overall is white, making up 95.0% of residents. The next most-common racial group is other at 2.3%. There are more white people in the north areas of the city. People who identify as other are most likely to be living in the central 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 Grass Range
Self-Identified Race |
Grass Range, MT Population |
|---|---|
White |
95.0% |
Hispanic |
0.8% |
Black |
0.0% |
Asian |
0.1% |
Native American |
2.0% |
Other |
2.3% |
Diversity and Diversity Scores for Grass Range, MT
The map below shows diversity in Grass Range. 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.
Grass Range Diversity Score
9.7
More diverse than 18% of US cities
Grass Range has a diversity score of 9.7: 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. Grass Range is much less diverse than other US cities, more diverse than 18% of them. Within Grass Range's proper boundaries, the most diverse area is central Grass Range, and the least diverse areas are in north Grass Range.
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.