Mongolian vs Immigrants from Northern Africa Community Comparison

The statistical analysis conducted on geographies consisting of 125,007,235 people shows a slight negative correlation between the proportion of Immigrants from Northern Africa within Mongolian communities in the United States with a correlation coefficient (R) of -0.073. On average, for every 1% (one percent) increase in Mongolians within a typical geography, there is a decrease of 0.027% in Immigrants from Northern Africa. To illustrate, in a geography comprising of 100,000 individuals, a rise of 1,000 Mongolians corresponds to a decrease of 26.6 Immigrants from Northern Africa.

When considering income, the most significant differences between Mongolian and Immigrants from Northern Africa communities in the United States are seen in median family income ($114,553 compared to $108,161, a difference of 5.9%), householder income ages 45 - 64 years ($111,602 compared to $105,430, a difference of 5.9%), and per capita income ($49,173 compared to $46,531, a difference of 5.7%). Conversely, both communities are more comparable in terms of median female earnings ($42,542 compared to $42,084, a difference of 1.1%), householder income under 25 years ($52,540 compared to $53,185, a difference of 1.2%), and median earnings ($51,038 compared to $49,648, a difference of 2.8%).

When considering poverty, the most significant differences between Mongolian and Immigrants from Northern Africa communities in the United States are seen in female poverty among 18-24 year olds (21.6% compared to 19.7%, a difference of 9.7%), receiving food stamps (10.5% compared to 11.0%, a difference of 5.2%), and child poverty under the age of 16 (15.2% compared to 15.8%, a difference of 4.4%). Conversely, both communities are more comparable in terms of single father poverty (15.3% compared to 15.3%, a difference of 0.64%), single female poverty (20.2% compared to 20.0%, a difference of 0.84%), and single mother poverty (27.7% compared to 28.0%, a difference of 1.2%).

When considering unemployment, the most significant differences between Mongolian and Immigrants from Northern Africa communities in the United States are seen in unemployment among women with children under 6 years (6.5% compared to 7.4%, a difference of 14.6%), unemployment among women with children under 18 years (5.0% compared to 5.4%, a difference of 8.8%), and unemployment among ages 35 to 44 years (4.3% compared to 4.5%, a difference of 5.2%). Conversely, both communities are more comparable in terms of unemployment among seniors over 65 years (5.1% compared to 5.2%, a difference of 1.5%), male unemployment (5.1% compared to 5.2%, a difference of 1.6%), and unemployment among ages 25 to 29 years (6.2% compared to 6.3%, a difference of 1.6%).

When considering labor participation, the most significant differences between Mongolian and Immigrants from Northern Africa communities in the United States are seen in in labor force | age 16-19 (35.3% compared to 35.9%, a difference of 1.8%), in labor force | age 20-24 (73.3% compared to 74.6%, a difference of 1.8%), and in labor force | age > 16 (66.1% compared to 66.6%, a difference of 0.82%). Conversely, both communities are more comparable in terms of in labor force | age 35-44 (84.8% compared to 84.8%, a difference of 0.020%), in labor force | age 45-54 (83.3% compared to 83.3%, a difference of 0.070%), and in labor force | age 30-34 (85.3% compared to 85.2%, a difference of 0.16%).

When considering family structure, the most significant differences between Mongolian and Immigrants from Northern Africa communities in the United States are seen in single mother households (5.8% compared to 6.2%, a difference of 6.8%), births to unmarried women (27.9% compared to 29.5%, a difference of 5.7%), and single father households (2.1% compared to 2.1%, a difference of 4.4%). Conversely, both communities are more comparable in terms of currently married (46.4% compared to 46.5%, a difference of 0.080%), married-couple households (46.3% compared to 46.0%, a difference of 0.76%), and average family size (3.20 compared to 3.22, a difference of 0.78%).

When considering vehicle availability, the most significant differences between Mongolian and Immigrants from Northern Africa communities in the United States are seen in no vehicles in household (13.1% compared to 12.6%, a difference of 4.1%), 4 or more vehicles in household (5.8% compared to 5.6%, a difference of 2.7%), and 3 or more vehicles in household (18.1% compared to 17.8%, a difference of 1.9%). Conversely, both communities are more comparable in terms of 1 or more vehicles in household (87.0% compared to 87.4%, a difference of 0.54%), 2 or more vehicles in household (52.8% compared to 52.3%, a difference of 0.93%), and 3 or more vehicles in household (18.1% compared to 17.8%, a difference of 1.9%).

When considering education level, the most significant differences between Mongolian and Immigrants from Northern Africa communities in the United States are seen in doctorate degree (2.8% compared to 2.1%, a difference of 30.3%), professional degree (6.1% compared to 5.1%, a difference of 21.2%), and master's degree (19.4% compared to 17.1%, a difference of 13.6%). Conversely, both communities are more comparable in terms of nursery school (97.9% compared to 97.8%, a difference of 0.080%), kindergarten (97.9% compared to 97.8%, a difference of 0.080%), and 2nd grade (97.8% compared to 97.7%, a difference of 0.080%).

When considering disability, the most significant differences between Mongolian and Immigrants from Northern Africa communities in the United States are seen in vision disability (1.9% compared to 2.0%, a difference of 4.3%), ambulatory disability (5.5% compared to 5.7%, a difference of 3.6%), and disability age 65 to 74 (21.8% compared to 22.4%, a difference of 2.7%). Conversely, both communities are more comparable in terms of hearing disability (2.7% compared to 2.8%, a difference of 0.53%), disability age over 75 (46.3% compared to 46.7%, a difference of 0.84%), and male disability (10.3% compared to 10.4%, a difference of 1.2%).