Chinese Female Poverty

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Ancestry
AfghanAfricanAlaska NativeAlaskan AthabascanAlbanianAleutAlsatianAmericanApacheArabArapahoArgentineanArmenianAssyrian/Chaldean/SyriacAustralianAustrianBahamianBangladeshiBarbadianBasqueBelgianBelizeanBermudanBhutaneseBlackfeetBolivianBrazilianBritishBritish West IndianBulgarianBurmeseCajunCambodianCanadianCape VerdeanCarpatho RusynCelticCentral AmericanCentral American IndianCherokeeCheyenneChickasawChileanChineseChippewaChoctawColombianColvilleComancheCosta RicanCreeCreekCroatianCrowCubanCypriotCzechCzechoslovakianDanishDelawareDominicanDutchDutch West IndianEastern EuropeanEcuadorianEgyptianEnglishEstonianEthiopianEuropeanFijianFilipinoFinnishFrenchFrench American IndianFrench CanadianGermanGerman RussianGhanaianGreekGuamanian/ChamorroGuatemalanGuyaneseHaitianHmongHonduranHopiHoumaHungarianIcelanderIndian (Asian)IndonesianInupiatIranianIraqiIrishIroquoisIsraeliItalianJamaicanJapaneseJordanianKenyanKiowaKoreanLaotianLatvianLebaneseLiberianLithuanianLumbeeLuxembourgerMacedonianMalaysianMalteseMarshalleseMenomineeMexicanMexican American IndianMongolianMoroccanNative HawaiianNavajoNepaleseNew ZealanderNicaraguanNigerianNorthern EuropeanNorwegianOkinawanOsageOttawaPaiutePakistaniPalestinianPanamanianParaguayanPennsylvania GermanPeruvianPimaPolishPortuguesePotawatomiPuebloPuerto RicanPuget Sound SalishRomanianRussianSalvadoranSamoanScandinavianScotch-IrishScottishSeminoleSenegaleseSerbianShoshoneSierra LeoneanSiouxSlavicSlovakSloveneSomaliSouth AfricanSouth AmericanSouth American IndianSoviet UnionSpaniardSpanishSpanish AmericanSpanish American IndianSri LankanSubsaharan AfricanSudaneseSwedishSwissSyrianTaiwaneseThaiTlingit-HaidaTohono O'OdhamTonganTrinidadian and TobagonianTsimshianTurkishU.S. Virgin IslanderUgandanUkrainianUruguayanUteVenezuelanVietnameseWelshWest IndianYakamaYaquiYugoslavianYumanYup'ikZimbabwean
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Race
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AfghanAfricanAlaska NativeAlaskan AthabascanAlbanianAleutAlsatianAmericanApacheArabArapahoArgentineanArmenianAssyrian/Chaldean/SyriacAustralianAustrianBahamianBangladeshiBarbadianBasqueBelgianBelizeanBermudanBhutaneseBlackfeetBolivianBrazilianBritishBritish West IndianBulgarianBurmeseCajunCambodianCanadianCape VerdeanCarpatho RusynCelticCentral AmericanCentral American IndianCherokeeCheyenneChickasawChileanChippewaChoctawColombianColvilleComancheCosta RicanCreeCreekCroatianCrowCubanCypriotCzechCzechoslovakianDanishDelawareDominicanDutchDutch West IndianEastern EuropeanEcuadorianEgyptianEnglishEstonianEthiopianEuropeanFijianFilipinoFinnishFrenchFrench American IndianFrench CanadianGermanGerman RussianGhanaianGreekGuamanian/ChamorroGuatemalanGuyaneseHaitianHmongHonduranHopiHoumaHungarianIcelanderIndian (Asian)IndonesianInupiatIranianIraqiIrishIroquoisIsraeliItalianJamaicanJapaneseJordanianKenyanKiowaKoreanLaotianLatvianLebaneseLiberianLithuanianLumbeeLuxembourgerMacedonianMalaysianMalteseMarshalleseMenomineeMexicanMexican American IndianMongolianMoroccanNative HawaiianNavajoNepaleseNew ZealanderNicaraguanNigerianNorthern EuropeanNorwegianOkinawanOsageOttawaPaiutePakistaniPalestinianPanamanianParaguayanPennsylvania GermanPeruvianPimaPolishPortuguesePotawatomiPuebloPuerto RicanPuget Sound SalishRomanianRussianSalvadoranSamoanScandinavianScotch-IrishScottishSeminoleSenegaleseSerbianShoshoneSierra LeoneanSiouxSlavicSlovakSloveneSomaliSouth AfricanSouth AmericanSouth American IndianSoviet UnionSpaniardSpanishSpanish AmericanSpanish American IndianSri LankanSubsaharan AfricanSudaneseSwedishSwissSyrianTaiwaneseThaiTlingit-HaidaTohono O'OdhamTonganTrinidadian and TobagonianTsimshianTurkishU.S. Virgin IslanderUgandanUkrainianUruguayanUteVenezuelanVietnameseWelshWest IndianYakamaYaquiYugoslavianYumanYup'ikZimbabwean
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Female Poverty
Income
Poverty
Unemployment
Labor Participation
Family Structure
Vehicle Availability
Education Level
Disability

Chinese Female Poverty
Exceptional

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.
Chinese Female Poverty
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%).
DemographicsRating | RankFemale 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

MeasurementChinese DataFemale Poverty Data
Minimum0.0087%3.4%
Maximum8.3%25.9%
Range8.3%22.5%
Mean1.7%10.8%
Median1.2%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 PercentileSample SizeFemale Poverty
[
0.0%
-
0.5%
]
0.0087%
53,055,74615.6%
[
0.0%
-
0.5%
]
0.059%
5,049,04311.1%
[
0.0%
-
0.5%
]
0.10%
1,538,2109.9%
[
0.0%
-
0.5%
]
0.14%
1,149,26610.7%
[
0.0%
-
0.5%
]
0.19%
529,05111.6%
[
0.0%
-
0.5%
]
0.22%
242,51910.2%
[
0.0%
-
0.5%
]
0.27%
241,73912.2%
[
0.0%
-
0.5%
]
0.31%
264,41011.0%
[
0.0%
-
0.5%
]
0.35%
172,81311.5%
[
0.0%
-
0.5%
]
0.39%
107,01610.5%
[
0.0%
-
0.5%
]
0.43%
144,77911.6%
[
0.0%
-
0.5%
]
0.47%
76,39521.7%
[
0.5%
-
1.0%
]
0.52%
117,21911.9%
[
0.5%
-
1.0%
]
0.56%
79,97814.8%
[
0.5%
-
1.0%
]
0.60%
263,9047.6%
[
0.5%
-
1.0%
]
0.64%
104,3839.5%
[
0.5%
-
1.0%
]
0.70%
114,4879.5%
[
0.5%
-
1.0%
]
0.72%
82,65614.3%
[
0.5%
-
1.0%
]
0.78%
454,77710.4%
[
0.5%
-
1.0%
]
0.82%
24,0957.0%
[
0.5%
-
1.0%
]
0.84%
151,35510.3%
[
0.5%
-
1.0%
]
0.89%
78,3549.3%
[
0.5%
-
1.0%
]
0.98%
40,3234.4%
[
1.0%
-
1.5%
]
1.00%
54,18212.3%
[
1.0%
-
1.5%
]
1.05%
13,29215.5%
[
1.0%
-
1.5%
]
1.09%
39,43712.4%
[
1.0%
-
1.5%
]
1.12%
22,8643.4%
[
1.0%
-
1.5%
]
1.17%
30,5086.8%
[
1.0%
-
1.5%
]
1.21%
77,4155.3%
[
1.0%
-
1.5%
]
1.27%
54,3623.7%
[
1.0%
-
1.5%
]
1.33%
27,73910.7%
[
1.0%
-
1.5%
]
1.37%
11,1387.4%
[
1.0%
-
1.5%
]
1.44%
50,14212.4%
[
1.5%
-
2.0%
]
1.57%
27,4234.2%
[
1.5%
-
2.0%
]
1.63%
45,3926.0%
[
1.5%
-
2.0%
]
1.67%
48,4944.9%
[
1.5%
-
2.0%
]
1.70%
18,8025.4%
[
1.5%
-
2.0%
]
1.77%
35,4938.4%
[
1.5%
-
2.0%
]
1.84%
41,5606.3%
[
1.5%
-
2.0%
]
1.87%
10,80117.7%
[
1.5%
-
2.0%
]
1.94%
46513.3%
[
1.5%
-
2.0%
]
1.95%
8,54316.7%
[
2.0%
-
2.5%
]
2.14%
63,4396.6%
[
2.0%
-
2.5%
]
2.19%
1,55523.2%
[
2.0%
-
2.5%
]
2.26%
1,50719.1%
[
2.0%
-
2.5%
]
2.28%
1,57616.2%
[
2.5%
-
3.0%
]
2.52%
1597.6%
[
2.5%
-
3.0%
]
2.61%
8,5716.0%
[
3.0%
-
3.5%
]
3.08%
1309.1%
[
3.0%
-
3.5%
]
3.23%
27916.9%
[
3.0%
-
3.5%
]
3.39%
3,62725.9%
[
3.0%
-
3.5%
]
3.50%
68614.0%
[
4.0%
-
4.5%
]
4.04%
4,13510.5%
[
4.0%
-
4.5%
]
4.14%
9,5713.6%
[
4.5%
-
5.0%
]
4.56%
5486.0%
[
5.5%
-
6.0%
]
5.98%
5,0654.4%
[
6.5%
-
7.0%
]
6.68%
8536.4%
[
8.0%
-
8.5%
]
8.28%
15722.2%