The map below shows majority race by area in McAlester, 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 McAlester racial diversity and diversity scores. Click here to scroll to diversity data.
The majority race in McAlester overall is white, making up 64.3% of residents. The next most-common racial group is other at 14.6%. There are more white people in the southeast areas of the city. People who identify as other are most likely to be living in the southwest 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 McAlester
Self-Identified Race |
McAlester, OK Population |
|---|---|
White |
64.3% |
Hispanic |
7.1% |
Black |
4.4% |
Asian |
0.7% |
Native American |
9.0% |
Other |
14.6% |
Diversity and Diversity Scores for McAlester, OK
The map below shows diversity in McAlester. 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.
McAlester Diversity Score
55.1
More diverse than 90% of US cities
McAlester has a diversity score of 55.1: 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. McAlester is much more diverse than other US cities, more diverse than 90% of them. Within McAlester's proper boundaries, the most diverse area is northwest McAlester, and the least diverse areas are in southeast McAlester.
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.