Immigrants from Bangladesh vs Immigrants from Guyana Community Comparison

The statistical analysis conducted on geographies consisting of 119,695,177 people shows a moderate positive correlation between the proportion of Immigrants from Guyana within Immigrant from Bangladesh communities in the United States with a correlation coefficient (R) of 0.421. On average, for every 1% (one percent) increase in Immigrants from Bangladesh within a typical geography, there is an increase of 0.370% in Immigrants from Guyana. To illustrate, in a geography comprising of 100,000 individuals, a rise of 1,000 Immigrants from Bangladesh corresponds to an increase of 370.5 Immigrants from Guyana.

When considering income, the most significant differences between Immigrants from Bangladesh and Immigrants from Guyana communities in the United States are seen in wage/income gap (20.9% compared to 18.4%, a difference of 14.1%), median male earnings ($51,642 compared to $50,321, a difference of 2.6%), and per capita income ($41,709 compared to $40,742, a difference of 2.4%). Conversely, both communities are more comparable in terms of median household income ($80,722 compared to $80,324, a difference of 0.50%), median earnings ($45,532 compared to $45,204, a difference of 0.73%), and householder income ages 25 - 44 years ($90,448 compared to $89,586, a difference of 0.96%).

When considering poverty, the most significant differences between Immigrants from Bangladesh and Immigrants from Guyana communities in the United States are seen in female poverty among 18-24 year olds (21.8% compared to 19.3%, a difference of 12.6%), married-couple family poverty (7.5% compared to 6.7%, a difference of 12.5%), and male poverty (14.1% compared to 13.2%, a difference of 6.5%). Conversely, both communities are more comparable in terms of single father poverty (16.3% compared to 16.5%, a difference of 1.3%), child poverty under the age of 16 (19.8% compared to 19.4%, a difference of 2.1%), and child poverty among boys under 16 (19.9% compared to 19.5%, a difference of 2.4%).

When considering unemployment, the most significant differences between Immigrants from Bangladesh and Immigrants from Guyana communities in the United States are seen in unemployment among ages 16 to 19 years (21.5% compared to 25.5%, a difference of 18.6%), unemployment among ages 30 to 34 years (6.4% compared to 7.2%, a difference of 12.2%), and unemployment among ages 35 to 44 years (5.3% compared to 6.0%, a difference of 12.2%). Conversely, both communities are more comparable in terms of unemployment among women with children ages 6 to 17 years (8.8% compared to 8.9%, a difference of 0.92%), unemployment among seniors over 65 years (5.7% compared to 5.6%, a difference of 1.6%), and unemployment among women with children under 18 years (6.4% compared to 6.5%, a difference of 2.2%).

When considering labor participation, the most significant differences between Immigrants from Bangladesh and Immigrants from Guyana communities in the United States are seen in in labor force | age 16-19 (30.0% compared to 27.3%, a difference of 10.2%), in labor force | age 20-24 (70.6% compared to 69.3%, a difference of 2.0%), and in labor force | age 45-54 (80.7% compared to 81.5%, a difference of 0.94%). Conversely, both communities are more comparable in terms of in labor force | age 25-29 (83.0% compared to 83.0%, a difference of 0.020%), in labor force | age 20-64 (77.9% compared to 78.1%, a difference of 0.21%), and in labor force | age 30-34 (83.6% compared to 83.8%, a difference of 0.21%).

When considering family structure, the most significant differences between Immigrants from Bangladesh and Immigrants from Guyana communities in the United States are seen in births to unmarried women (30.9% compared to 35.0%, a difference of 13.2%), single mother households (6.9% compared to 7.6%, a difference of 10.0%), and divorced or separated (11.0% compared to 11.6%, a difference of 6.0%). Conversely, both communities are more comparable in terms of average family size (3.36 compared to 3.40, a difference of 1.2%), single father households (2.1% compared to 2.1%, a difference of 2.4%), and family households (63.9% compared to 65.5%, a difference of 2.6%).

When considering vehicle availability, the most significant differences between Immigrants from Bangladesh and Immigrants from Guyana communities in the United States are seen in 4 or more vehicles in household (3.9% compared to 3.4%, a difference of 14.7%), no vehicles in household (25.8% compared to 29.5%, a difference of 14.5%), and 3 or more vehicles in household (12.5% compared to 11.2%, a difference of 11.4%). Conversely, both communities are more comparable in terms of 1 or more vehicles in household (74.3% compared to 70.6%, a difference of 5.3%), 2 or more vehicles in household (38.8% compared to 35.0%, a difference of 10.8%), and 3 or more vehicles in household (12.5% compared to 11.2%, a difference of 11.4%).

When considering education level, the most significant differences between Immigrants from Bangladesh and Immigrants from Guyana communities in the United States are seen in doctorate degree (1.8% compared to 1.3%, a difference of 37.9%), professional degree (4.4% compared to 3.7%, a difference of 21.3%), and master's degree (15.5% compared to 13.4%, a difference of 15.1%). Conversely, both communities are more comparable in terms of kindergarten (96.8% compared to 96.8%, a difference of 0.010%), 1st grade (96.8% compared to 96.8%, a difference of 0.010%), and nursery school (96.9% compared to 96.9%, a difference of 0.020%).

When considering disability, the most significant differences between Immigrants from Bangladesh and Immigrants from Guyana communities in the United States are seen in disability age under 5 (0.85% compared to 1.0%, a difference of 22.6%), ambulatory disability (6.2% compared to 6.7%, a difference of 8.1%), and self-care disability (2.6% compared to 2.8%, a difference of 5.1%). Conversely, both communities are more comparable in terms of disability age 65 to 74 (23.6% compared to 23.6%, a difference of 0.070%), disability age 5 to 17 (5.2% compared to 5.2%, a difference of 0.83%), and disability age 35 to 64 (10.9% compared to 11.1%, a difference of 1.9%).