The map below shows majority race by area in Mad River, 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 Mad River racial diversity and diversity scores. Click here to scroll to diversity data.
The majority race in Mad River overall is white, making up 86.4% of residents. The next most-common racial group is hispanic at 5.1%. There are more white people in the central areas of the city. People who identify as hispanic are most likely to be living in the east 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 Mad River
Self-Identified Race |
Mad River, CA Population |
|---|---|
White |
86.4% |
Hispanic |
5.1% |
Black |
0.9% |
Asian |
0.0% |
Native American |
3.0% |
Other |
4.6% |
Diversity and Diversity Scores for Mad River, CA
The map below shows diversity in Mad River. 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.
Mad River Diversity Score
24.7
More diverse than 54% of US cities
Mad River has a diversity score of 24.7: 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. Mad River is about average for diversity versus other US cities, more diverse than 54% of them. Within Mad River's proper boundaries, the most diverse area is east Mad River, and the least diverse areas are in central Mad River.
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.