Chinese Female Poverty
COMPARE
Chinese
Select to Compare
Female Poverty
Chinese Female Poverty
10.4%
POVERTY | FEMALES
100.0/ 100
METRIC RATING
2nd/ 347
METRIC RANK
Chinese Female Poverty Correlation Chart
The statistical analysis conducted on geographies consisting of 64,802,428 people shows a slight positive correlation between the proportion of Chinese and poverty level among females in the United States with a correlation coefficient (R) of 0.064 and weighted average of 10.4%. On average, for every 1% (one percent) increase in Chinese within a typical geography, there is an increase of 0.20% in poverty level among females.
It is essential to understand that the correlation between the percentage of Chinese and poverty level among females does not imply a direct cause-and-effect relationship. It remains uncertain whether the presence of Chinese influences an upward or downward trend in the level of poverty level among females within an area, or if Chinese simply ended up residing in those areas with higher or lower levels of poverty level among females due to other factors.
Demographics Similar to Chinese by Female Poverty
In terms of female poverty, the demographic groups most similar to Chinese are Thai (10.5%, a difference of 0.65%), Immigrants from Taiwan (10.5%, a difference of 1.4%), Immigrants from India (9.9%, a difference of 5.2%), Filipino (10.9%, a difference of 5.4%), and Immigrants from Ireland (11.0%, a difference of 5.8%).
| Demographics | Rating | Rank | Female Poverty |
| Immigrants from India | 100.0 /100 | #1 | Exceptional 9.9% |
| Chinese | 100.0 /100 | #2 | Exceptional 10.4% |
| Thais | 100.0 /100 | #3 | Exceptional 10.5% |
| Immigrants from Taiwan | 100.0 /100 | #4 | Exceptional 10.5% |
| Filipinos | 100.0 /100 | #5 | Exceptional 10.9% |
| Immigrants from Ireland | 99.9 /100 | #6 | Exceptional 11.0% |
| Assyrians/Chaldeans/Syriacs | 99.9 /100 | #7 | Exceptional 11.0% |
| Immigrants from South Central Asia | 99.9 /100 | #8 | Exceptional 11.1% |
| Bulgarians | 99.9 /100 | #9 | Exceptional 11.1% |
| Immigrants from Hong Kong | 99.9 /100 | #10 | Exceptional 11.2% |
| Maltese | 99.9 /100 | #11 | Exceptional 11.2% |
| Bhutanese | 99.9 /100 | #12 | Exceptional 11.3% |
| Immigrants from Lithuania | 99.9 /100 | #13 | Exceptional 11.3% |
| Lithuanians | 99.8 /100 | #14 | Exceptional 11.4% |
| Latvians | 99.8 /100 | #15 | Exceptional 11.4% |
Chinese Female Poverty Correlation Summary
| Measurement | Chinese Data | Female Poverty Data |
| Minimum | 0.0087% | 3.4% |
| Maximum | 8.3% | 25.9% |
| Range | 8.3% | 22.5% |
| Mean | 1.7% | 10.8% |
| Median | 1.2% | 10.4% |
| Interquartile 25% (IQ1) | 0.60% | 6.6% |
| Interquartile 75% (IQ3) | 2.2% | 13.3% |
| Interquartile Range (IQR) | 1.6% | 6.7% |
| Standard Deviation (Sample) | 1.7% | 5.2% |
| Standard Deviation (Population) | 1.7% | 5.1% |
Correlation Details
| Chinese Percentile | Sample Size | Female Poverty |
[ 0.0% - 0.5% ] 0.0087% | 53,055,746 | 15.6% |
[ 0.0% - 0.5% ] 0.059% | 5,049,043 | 11.1% |
[ 0.0% - 0.5% ] 0.10% | 1,538,210 | 9.9% |
[ 0.0% - 0.5% ] 0.14% | 1,149,266 | 10.7% |
[ 0.0% - 0.5% ] 0.19% | 529,051 | 11.6% |
[ 0.0% - 0.5% ] 0.22% | 242,519 | 10.2% |
[ 0.0% - 0.5% ] 0.27% | 241,739 | 12.2% |
[ 0.0% - 0.5% ] 0.31% | 264,410 | 11.0% |
[ 0.0% - 0.5% ] 0.35% | 172,813 | 11.5% |
[ 0.0% - 0.5% ] 0.39% | 107,016 | 10.5% |
[ 0.0% - 0.5% ] 0.43% | 144,779 | 11.6% |
[ 0.0% - 0.5% ] 0.47% | 76,395 | 21.7% |
[ 0.5% - 1.0% ] 0.52% | 117,219 | 11.9% |
[ 0.5% - 1.0% ] 0.56% | 79,978 | 14.8% |
[ 0.5% - 1.0% ] 0.60% | 263,904 | 7.6% |
[ 0.5% - 1.0% ] 0.64% | 104,383 | 9.5% |
[ 0.5% - 1.0% ] 0.70% | 114,487 | 9.5% |
[ 0.5% - 1.0% ] 0.72% | 82,656 | 14.3% |
[ 0.5% - 1.0% ] 0.78% | 454,777 | 10.4% |
[ 0.5% - 1.0% ] 0.82% | 24,095 | 7.0% |
[ 0.5% - 1.0% ] 0.84% | 151,355 | 10.3% |
[ 0.5% - 1.0% ] 0.89% | 78,354 | 9.3% |
[ 0.5% - 1.0% ] 0.98% | 40,323 | 4.4% |
[ 1.0% - 1.5% ] 1.00% | 54,182 | 12.3% |
[ 1.0% - 1.5% ] 1.05% | 13,292 | 15.5% |
[ 1.0% - 1.5% ] 1.09% | 39,437 | 12.4% |
[ 1.0% - 1.5% ] 1.12% | 22,864 | 3.4% |
[ 1.0% - 1.5% ] 1.17% | 30,508 | 6.8% |
[ 1.0% - 1.5% ] 1.21% | 77,415 | 5.3% |
[ 1.0% - 1.5% ] 1.27% | 54,362 | 3.7% |
[ 1.0% - 1.5% ] 1.33% | 27,739 | 10.7% |
[ 1.0% - 1.5% ] 1.37% | 11,138 | 7.4% |
[ 1.0% - 1.5% ] 1.44% | 50,142 | 12.4% |
[ 1.5% - 2.0% ] 1.57% | 27,423 | 4.2% |
[ 1.5% - 2.0% ] 1.63% | 45,392 | 6.0% |
[ 1.5% - 2.0% ] 1.67% | 48,494 | 4.9% |
[ 1.5% - 2.0% ] 1.70% | 18,802 | 5.4% |
[ 1.5% - 2.0% ] 1.77% | 35,493 | 8.4% |
[ 1.5% - 2.0% ] 1.84% | 41,560 | 6.3% |
[ 1.5% - 2.0% ] 1.87% | 10,801 | 17.7% |
[ 1.5% - 2.0% ] 1.94% | 465 | 13.3% |
[ 1.5% - 2.0% ] 1.95% | 8,543 | 16.7% |
[ 2.0% - 2.5% ] 2.14% | 63,439 | 6.6% |
[ 2.0% - 2.5% ] 2.19% | 1,555 | 23.2% |
[ 2.0% - 2.5% ] 2.26% | 1,507 | 19.1% |
[ 2.0% - 2.5% ] 2.28% | 1,576 | 16.2% |
[ 2.5% - 3.0% ] 2.52% | 159 | 7.6% |
[ 2.5% - 3.0% ] 2.61% | 8,571 | 6.0% |
[ 3.0% - 3.5% ] 3.08% | 130 | 9.1% |
[ 3.0% - 3.5% ] 3.23% | 279 | 16.9% |
[ 3.0% - 3.5% ] 3.39% | 3,627 | 25.9% |
[ 3.0% - 3.5% ] 3.50% | 686 | 14.0% |
[ 4.0% - 4.5% ] 4.04% | 4,135 | 10.5% |
[ 4.0% - 4.5% ] 4.14% | 9,571 | 3.6% |
[ 4.5% - 5.0% ] 4.56% | 548 | 6.0% |
[ 5.5% - 6.0% ] 5.98% | 5,065 | 4.4% |
[ 6.5% - 7.0% ] 6.68% | 853 | 6.4% |
[ 8.0% - 8.5% ] 8.28% | 157 | 22.2% |