The map below shows majority race by area in Mount Ross, 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 Mount Ross racial diversity and diversity scores. Click here to scroll to diversity data.
The majority race in Mount Ross overall is white, making up 88.7% of residents. The next most-common racial group is other at 4.9%. 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 southeast 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 Mount Ross
Self-Identified Race |
Mount Ross, NY Population |
|---|---|
White |
88.7% |
Hispanic |
4.0% |
Black |
1.0% |
Asian |
1.4% |
Native American |
0.0% |
Other |
4.9% |
Diversity and Diversity Scores for Mount Ross, NY
The map below shows diversity in Mount Ross. 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.
Mount Ross Diversity Score
20.8
More diverse than 47% of US cities
Mount Ross has a diversity score of 20.8: 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. Mount Ross is about average for diversity versus other US cities, more diverse than 47% of them. Within Mount Ross's proper boundaries, the most diverse area is southeast Mount Ross, and the least diverse areas are in central Mount Ross.
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.