Immigrants from Germany vs Indian (Asian) Community Comparison

The statistical analysis conducted on geographies consisting of 432,009,311 people shows a moderate negative correlation between the proportion of Indians (Asian) within Immigrant from Germany communities in the United States with a correlation coefficient (R) of -0.413. On average, for every 1% (one percent) increase in Immigrants from Germany within a typical geography, there is a decrease of 0.114% in Indians (Asian). To illustrate, in a geography comprising of 100,000 individuals, a rise of 1,000 Immigrants from Germany corresponds to a decrease of 113.8 Indians (Asian).

When considering income, the most significant differences between Immigrants from Germany and Indian (Asian) communities in the United States are seen in householder income ages 25 - 44 years ($95,913 compared to $119,496, a difference of 24.6%), median household income ($86,764 compared to $105,262, a difference of 21.3%), and median family income ($105,507 compared to $125,312, a difference of 18.8%). Conversely, both communities are more comparable in terms of wage/income gap (27.5% compared to 26.4%, a difference of 4.1%), householder income over 65 years ($62,544 compared to $70,238, a difference of 12.3%), and householder income under 25 years ($51,190 compared to $58,239, a difference of 13.8%).

When considering poverty, the most significant differences between Immigrants from Germany and Indian (Asian) communities in the United States are seen in child poverty under the age of 5 (17.4% compared to 13.4%, a difference of 29.3%), female poverty among 25-34 year olds (13.9% compared to 11.2%, a difference of 24.4%), and child poverty among boys under 16 (16.2% compared to 13.3%, a difference of 21.9%). Conversely, both communities are more comparable in terms of married-couple family poverty (4.7% compared to 4.8%, a difference of 2.6%), female poverty among 18-24 year olds (20.3% compared to 19.6%, a difference of 3.4%), and male poverty (10.9% compared to 10.4%, a difference of 5.3%).

When considering unemployment, the most significant differences between Immigrants from Germany and Indian (Asian) communities in the United States are seen in unemployment among women with children under 6 years (7.9% compared to 6.3%, a difference of 26.2%), unemployment among women with children ages 6 to 17 years (9.2% compared to 7.7%, a difference of 19.3%), and unemployment among seniors over 75 years (9.2% compared to 8.0%, a difference of 15.0%). Conversely, both communities are more comparable in terms of unemployment among youth under 25 years (11.5% compared to 11.5%, a difference of 0.030%), female unemployment (5.1% compared to 5.1%, a difference of 0.44%), and male unemployment (5.2% compared to 5.2%, a difference of 0.65%).

When considering labor participation, the most significant differences between Immigrants from Germany and Indian (Asian) communities in the United States are seen in in labor force | age 16-19 (39.1% compared to 31.9%, a difference of 22.7%), in labor force | age 20-24 (76.2% compared to 71.9%, a difference of 6.0%), and in labor force | age > 16 (63.9% compared to 65.5%, a difference of 2.5%). Conversely, both communities are more comparable in terms of in labor force | age 25-29 (84.4% compared to 84.7%, a difference of 0.36%), in labor force | age 35-44 (83.9% compared to 84.8%, a difference of 1.1%), and in labor force | age 30-34 (84.3% compared to 85.4%, a difference of 1.3%).

When considering family structure, the most significant differences between Immigrants from Germany and Indian (Asian) communities in the United States are seen in births to unmarried women (32.8% compared to 25.3%, a difference of 29.7%), divorced or separated (12.4% compared to 10.2%, a difference of 21.5%), and single mother households (6.1% compared to 5.1%, a difference of 20.3%). Conversely, both communities are more comparable in terms of currently married (47.8% compared to 48.0%, a difference of 0.33%), family households (64.3% compared to 65.1%, a difference of 1.3%), and family households with children (27.0% compared to 27.6%, a difference of 2.2%).

When considering vehicle availability, the most significant differences between Immigrants from Germany and Indian (Asian) communities in the United States are seen in no vehicles in household (8.7% compared to 14.1%, a difference of 61.1%), 2 or more vehicles in household (57.9% compared to 53.1%, a difference of 9.0%), and 3 or more vehicles in household (20.8% compared to 19.1%, a difference of 9.0%). Conversely, both communities are more comparable in terms of 4 or more vehicles in household (6.8% compared to 6.4%, a difference of 5.5%), 1 or more vehicles in household (91.4% compared to 86.0%, a difference of 6.2%), and 3 or more vehicles in household (20.8% compared to 19.1%, a difference of 9.0%).

When considering education level, the most significant differences between Immigrants from Germany and Indian (Asian) communities in the United States are seen in doctorate degree (2.1% compared to 2.9%, a difference of 39.9%), no schooling completed (1.8% compared to 2.5%, a difference of 39.7%), and professional degree (4.9% compared to 6.5%, a difference of 34.5%). Conversely, both communities are more comparable in terms of 12th grade, no diploma (92.0% compared to 91.5%, a difference of 0.52%), ged/equivalency (86.7% compared to 87.1%, a difference of 0.55%), and nursery school (98.3% compared to 97.6%, a difference of 0.67%).

When considering disability, the most significant differences between Immigrants from Germany and Indian (Asian) communities in the United States are seen in disability age under 5 (1.4% compared to 1.0%, a difference of 42.0%), disability age 35 to 64 (11.9% compared to 8.9%, a difference of 34.3%), and disability age 18 to 34 (7.2% compared to 5.5%, a difference of 30.3%). Conversely, both communities are more comparable in terms of disability age over 75 (46.7% compared to 46.5%, a difference of 0.47%), cognitive disability (17.0% compared to 16.8%, a difference of 0.78%), and self-care disability (2.5% compared to 2.3%, a difference of 7.3%).