Hungarian vs Chinese Community Comparison

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Hungarian
Race
Ancestry
AfghanAfricanAlaska NativeAlaskan AthabascanAlbanianAleutAlsatianAmericanApacheArabArapahoArgentineanArmenianAssyrian/Chaldean/SyriacAustralianAustrianBahamianBangladeshiBarbadianBasqueBelgianBelizeanBermudanBhutaneseBlackfeetBolivianBrazilianBritishBritish West IndianBulgarianBurmeseCajunCambodianCanadianCape VerdeanCarpatho RusynCelticCentral AmericanCentral American IndianCherokeeCheyenneChickasawChileanChippewaChoctawColombianColvilleComancheCosta RicanCreeCreekCroatianCubanCypriotCzechCzechoslovakianDanishDelawareDominicanDutchDutch West IndianEastern EuropeanEcuadorianEgyptianEnglishEstonianEthiopianEuropeanFijianFilipinoFinnishFrenchFrench American IndianFrench CanadianGermanGerman RussianGhanaianGreekGuamanian/ChamorroGuatemalanGuyaneseHaitianHmongHonduranHungarianIcelanderIndian (Asian)IndonesianInupiatIranianIraqiIrishIroquoisIsraeliItalianJamaicanJapaneseJordanianKenyanKiowaKoreanLaotianLatvianLebaneseLiberianLithuanianLuxembourgerMacedonianMalaysianMalteseMarshalleseMenomineeMexicanMexican 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 TobagonianTurkishU.S. Virgin IslanderUgandanUkrainianUruguayanVenezuelanVietnameseWelshWest IndianYakamaYaquiYugoslavianYumanYup'ikZimbabwean
Immigration
NonimmigrantsImmigrantsAfghanistanAfricaAlbaniaArgentinaArmeniaAsiaAustraliaAustriaBahamasBangladeshBarbadosBelarusBelgiumBelizeBoliviaBosnia and HerzegovinaBrazilBulgariaBurma/MyanmarCambodiaCameroonCanadaCaribbeanCentral AmericaChileChinaColombiaCongoCosta RicaCroatiaCubaCzechoslovakiaDenmarkDominicaDominican RepublicEastern AfricaEastern AsiaEastern EuropeEcuadorEgyptEl SalvadorEnglandEritreaEthiopiaEuropeFijiFranceGermanyGhanaGreeceGrenadaGuatemalaGuyanaHaitiHondurasHong KongHungaryIndiaIndonesiaIranIraqIrelandIsraelItalyJamaicaJapanJordanKazakhstanKenyaKoreaKuwaitLaosLatin AmericaLatviaLebanonLiberiaLithuaniaMalaysiaMexicoMicronesiaMiddle AfricaMoldovaMoroccoNepalNetherlandsNicaraguaNigeriaNorth AmericaNorth MacedoniaNorthern AfricaNorthern EuropeNorwayOceaniaPakistanPanamaPeruPhilippinesPolandPortugalRomaniaRussiaSaudi ArabiaScotlandSenegalSerbiaSierra LeoneSingaporeSomaliaSouth AfricaSouth AmericaSouth Central AsiaSouth Eastern AsiaSouthern EuropeSpainSri LankaSt. Vincent and the GrenadinesSudanSwedenSwitzerlandSyriaTaiwanThailandTrinidad and TobagoTurkeyUgandaUkraineUruguayUzbekistanVenezuelaVietnamWest IndiesWestern AfricaWestern AsiaWestern EuropeYemenZaireZimbabweAzores
Chinese
Race
Ancestry
AfghanAfricanAlaska NativeAlaskan AthabascanAlbanianAleutAlsatianAmericanApacheArabArapahoArgentineanArmenianAssyrian/Chaldean/SyriacAustralianAustrianBahamianBangladeshiBarbadianBasqueBelgianBelizeanBermudanBhutaneseBlackfeetBolivianBrazilianBritishBritish West IndianBulgarianBurmeseCajunCambodianCanadianCape VerdeanCarpatho RusynCelticCentral AmericanCentral American IndianCherokeeCheyenneChickasawChileanChineseChippewaChoctawColombianColvilleComancheCosta RicanCreeCreekCroatianCrowCubanCypriotCzechCzechoslovakianDanishDelawareDominicanDutchDutch West IndianEastern EuropeanEcuadorianEgyptianEnglishEstonianEthiopianEuropeanFijianFilipinoFinnishFrenchFrench American IndianFrench CanadianGermanGerman RussianGhanaianGreekGuamanian/ChamorroGuatemalanGuyaneseHaitianHmongHonduranHopiHoumaIcelanderIndian (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
Immigration
NonimmigrantsImmigrantsAfghanistanAfricaAlbaniaArgentinaArmeniaAsiaAustraliaAustriaBahamasBangladeshBarbadosBelarusBelgiumBelizeBoliviaBosnia and HerzegovinaBrazilBulgariaBurma/MyanmarCabo VerdeCambodiaCameroonCanadaCaribbeanCentral AmericaChileChinaColombiaCongoCosta RicaCroatiaCubaCzechoslovakiaDenmarkDominicaDominican RepublicEastern AfricaEastern AsiaEastern EuropeEcuadorEgyptEl SalvadorEnglandEritreaEthiopiaEuropeFijiFranceGermanyGhanaGreeceGrenadaGuatemalaGuyanaHaitiHondurasHong KongHungaryIndiaIndonesiaIranIraqIrelandIsraelItalyJamaicaJapanJordanKazakhstanKenyaKoreaKuwaitLaosLatin AmericaLatviaLebanonLiberiaLithuaniaMalaysiaMexicoMicronesiaMiddle AfricaMoldovaMoroccoNepalNetherlandsNicaraguaNigeriaNorth AmericaNorth MacedoniaNorthern AfricaNorthern EuropeNorwayOceaniaPakistanPanamaPeruPhilippinesPolandPortugalRomaniaRussiaSaudi ArabiaScotlandSenegalSerbiaSierra LeoneSingaporeSomaliaSouth AfricaSouth AmericaSouth Central AsiaSouth Eastern AsiaSouthern EuropeSpainSri LankaSt. Vincent and the GrenadinesSudanSwedenSwitzerlandSyriaTaiwanThailandTrinidad and TobagoTurkeyUgandaUkraineUruguayUzbekistanVenezuelaVietnamWest IndiesWestern AfricaWestern AsiaWestern EuropeYemenZaireZimbabweAzores
Social Comparison
Social Comparison
Income
Poverty
Unemployment
Labor Participation
Family Structure
Vehicle Availability
Education Level
Disability

Social Comparison

Hungarians

Chinese

Good
Exceptional
6,572
SOCIAL INDEX
63.2/ 100
SOCIAL RATING
149th/ 347
SOCIAL RANK
9,296
SOCIAL INDEX
90.4/ 100
SOCIAL RATING
23rd/ 347
SOCIAL RANK

Chinese Integration in Hungarian Communities

The statistical analysis conducted on geographies consisting of 63,408,587 people shows a strong positive correlation between the proportion of Chinese within Hungarian communities in the United States with a correlation coefficient (R) of 0.754. On average, for every 1% (one percent) increase in Hungarians within a typical geography, there is an increase of 0.148% in Chinese. To illustrate, in a geography comprising of 100,000 individuals, a rise of 1,000 Hungarians corresponds to an increase of 148.0 Chinese.
Hungarian Integration in Chinese Communities

Hungarian vs Chinese Income

When considering income, the most significant differences between Hungarian and Chinese communities in the United States are seen in householder income over 65 years ($61,673 compared to $77,465, a difference of 25.6%), householder income under 25 years ($50,247 compared to $58,162, a difference of 15.8%), and median household income ($86,920 compared to $98,496, a difference of 13.3%). Conversely, both communities are more comparable in terms of median male earnings ($57,309 compared to $56,872, a difference of 0.77%), per capita income ($45,426 compared to $46,098, a difference of 1.5%), and median earnings ($47,795 compared to $48,836, a difference of 2.2%).
Hungarian vs Chinese Income
Income MetricHungarianChinese
Per Capita Income
Excellent
$45,426
Exceptional
$46,098
Median Family Income
Excellent
$105,609
Exceptional
$116,188
Median Household Income
Good
$86,920
Exceptional
$98,496
Median Earnings
Excellent
$47,795
Exceptional
$48,836
Median Male Earnings
Exceptional
$57,309
Exceptional
$56,872
Median Female Earnings
Average
$39,510
Exceptional
$41,461
Householder Age | Under 25 years
Tragic
$50,247
Exceptional
$58,162
Householder Age | 25 - 44 years
Excellent
$97,544
Exceptional
$104,264
Householder Age | 45 - 64 years
Excellent
$103,913
Exceptional
$116,156
Householder Age | Over 65 years
Good
$61,673
Exceptional
$77,465
Wage/Income Gap
Tragic
29.0%
Average
25.9%

Hungarian vs Chinese Poverty

When considering poverty, the most significant differences between Hungarian and Chinese communities in the United States are seen in married-couple family poverty (5.3% compared to 3.6%, a difference of 45.7%), child poverty among boys under 16 (16.5% compared to 11.9%, a difference of 38.9%), and child poverty under the age of 5 (17.9% compared to 13.1%, a difference of 37.1%). Conversely, both communities are more comparable in terms of receiving food stamps (11.0% compared to 9.8%, a difference of 12.8%), seniors poverty over the age of 65 (9.7% compared to 8.3%, a difference of 16.3%), and single father poverty (18.5% compared to 15.4%, a difference of 19.8%).
Hungarian vs Chinese Poverty
Poverty MetricHungarianChinese
Poverty
Good
12.2%
Exceptional
9.5%
Families
Good
8.8%
Exceptional
6.5%
Males
Average
11.1%
Exceptional
8.7%
Females
Good
13.2%
Exceptional
10.4%
Females 18 to 24 years
Good
19.8%
Exceptional
16.2%
Females 25 to 34 years
Poor
14.1%
Exceptional
11.0%
Children Under 5 years
Poor
17.9%
Exceptional
13.1%
Children Under 16 years
Average
16.2%
Exceptional
11.9%
Boys Under 16 years
Average
16.5%
Exceptional
11.9%
Girls Under 16 years
Average
16.6%
Exceptional
12.3%
Single Males
Tragic
13.8%
Exceptional
11.0%
Single Females
Fair
21.1%
Exceptional
16.1%
Single Fathers
Tragic
18.5%
Exceptional
15.4%
Single Mothers
Poor
29.9%
Exceptional
24.6%
Married Couples
Fair
5.3%
Exceptional
3.6%
Seniors Over 65 years
Exceptional
9.7%
Exceptional
8.3%
Seniors Over 75 years
Exceptional
11.2%
Exceptional
9.1%
Receiving Food Stamps
Excellent
11.0%
Exceptional
9.8%

Hungarian vs Chinese Unemployment

When considering unemployment, the most significant differences between Hungarian and Chinese communities in the United States are seen in unemployment among seniors over 75 years (10.1% compared to 5.9%, a difference of 70.7%), unemployment among seniors over 65 years (5.3% compared to 4.2%, a difference of 25.8%), and unemployment among ages 65 to 74 years (5.5% compared to 4.4%, a difference of 23.7%). Conversely, both communities are more comparable in terms of unemployment among women with children ages 6 to 17 years (9.3% compared to 9.3%, a difference of 0.63%), male unemployment (5.2% compared to 4.9%, a difference of 5.0%), and unemployment among youth under 25 years (11.4% compared to 10.7%, a difference of 6.4%).
Hungarian vs Chinese Unemployment
Unemployment MetricHungarianChinese
Unemployment
Exceptional
5.0%
Exceptional
4.7%
Males
Excellent
5.2%
Exceptional
4.9%
Females
Exceptional
4.9%
Exceptional
4.5%
Youth < 25
Excellent
11.4%
Exceptional
10.7%
Age | 16 to 19 years
Exceptional
17.1%
Exceptional
16.0%
Age | 20 to 24 years
Good
10.2%
Exceptional
9.4%
Age | 25 to 29 years
Fair
6.8%
Exceptional
6.1%
Age | 30 to 34 years
Average
5.5%
Exceptional
5.1%
Age | 35 to 44 years
Good
4.6%
Exceptional
4.3%
Age | 45 to 54 years
Good
4.5%
Exceptional
4.0%
Age | 55 to 59 years
Average
4.8%
Exceptional
4.4%
Age | 60 to 64 years
Average
4.9%
Exceptional
4.0%
Age | 65 to 74 years
Tragic
5.5%
Exceptional
4.4%
Seniors > 65
Tragic
5.3%
Exceptional
4.2%
Seniors > 75
Tragic
10.1%
Exceptional
5.9%
Women w/ Children < 6
Fair
7.8%
Exceptional
6.8%
Women w/ Children 6 to 17
Tragic
9.3%
Tragic
9.3%
Women w/ Children < 18
Excellent
5.3%
Exceptional
4.9%

Hungarian vs Chinese Labor Participation

When considering labor participation, the most significant differences between Hungarian and Chinese communities in the United States are seen in in labor force | age 16-19 (39.8% compared to 38.6%, a difference of 3.2%), in labor force | age 20-64 (79.2% compared to 80.7%, a difference of 1.9%), and in labor force | age 45-54 (82.7% compared to 84.1%, a difference of 1.8%). Conversely, both communities are more comparable in terms of in labor force | age 25-29 (84.6% compared to 84.3%, a difference of 0.34%), in labor force | age 30-34 (84.5% compared to 85.0%, a difference of 0.57%), and in labor force | age 35-44 (84.2% compared to 85.1%, a difference of 1.0%).
Hungarian vs Chinese Labor Participation
Labor Participation MetricHungarianChinese
In Labor Force | Age > 16
Tragic
63.8%
Tragic
64.7%
In Labor Force | Age 20-64
Tragic
79.2%
Exceptional
80.7%
In Labor Force | Age 16-19
Exceptional
39.8%
Exceptional
38.6%
In Labor Force | Age 20-24
Exceptional
76.3%
Exceptional
77.3%
In Labor Force | Age 25-29
Average
84.6%
Poor
84.3%
In Labor Force | Age 30-34
Fair
84.5%
Excellent
85.0%
In Labor Force | Age 35-44
Fair
84.2%
Exceptional
85.1%
In Labor Force | Age 45-54
Fair
82.7%
Exceptional
84.1%

Hungarian vs Chinese Family Structure

When considering family structure, the most significant differences between Hungarian and Chinese communities in the United States are seen in single father households (2.2% compared to 2.0%, a difference of 10.1%), single mother households (5.7% compared to 5.2%, a difference of 9.9%), and divorced or separated (12.0% compared to 11.2%, a difference of 7.0%). Conversely, both communities are more comparable in terms of currently married (48.8% compared to 49.5%, a difference of 1.4%), married-couple households (49.1% compared to 50.4%, a difference of 2.6%), and births to unmarried women (31.2% compared to 30.2%, a difference of 3.3%).
Hungarian vs Chinese Family Structure
Family Structure MetricHungarianChinese
Family Households
Exceptional
64.9%
Exceptional
68.1%
Family Households with Children
Good
27.6%
Tragic
26.0%
Married-couple Households
Exceptional
49.1%
Exceptional
50.4%
Average Family Size
Tragic
3.18
Exceptional
3.34
Single Father Households
Exceptional
2.2%
Exceptional
2.0%
Single Mother Households
Exceptional
5.7%
Exceptional
5.2%
Currently Married
Exceptional
48.8%
Exceptional
49.5%
Divorced or Separated
Good
12.0%
Exceptional
11.2%
Births to Unmarried Women
Good
31.2%
Excellent
30.2%

Hungarian vs Chinese Vehicle Availability

When considering vehicle availability, the most significant differences between Hungarian and Chinese communities in the United States are seen in 4 or more vehicles in household (6.4% compared to 8.8%, a difference of 38.3%), no vehicles in household (9.9% compared to 8.2%, a difference of 20.6%), and 3 or more vehicles in household (19.8% compared to 23.9%, a difference of 20.4%). Conversely, both communities are more comparable in terms of 1 or more vehicles in household (90.3% compared to 91.9%, a difference of 1.7%), 2 or more vehicles in household (56.5% compared to 60.1%, a difference of 6.4%), and 3 or more vehicles in household (19.8% compared to 23.9%, a difference of 20.4%).
Hungarian vs Chinese Vehicle Availability
Vehicle Availability MetricHungarianChinese
No Vehicles Available
Excellent
9.9%
Exceptional
8.2%
1+ Vehicles Available
Excellent
90.3%
Exceptional
91.9%
2+ Vehicles Available
Excellent
56.5%
Exceptional
60.1%
3+ Vehicles Available
Good
19.8%
Exceptional
23.9%
4+ Vehicles Available
Good
6.4%
Exceptional
8.8%

Hungarian vs Chinese Education Level

When considering education level, the most significant differences between Hungarian and Chinese communities in the United States are seen in no schooling completed (1.6% compared to 1.5%, a difference of 8.1%), doctorate degree (1.9% compared to 1.8%, a difference of 7.7%), and master's degree (15.6% compared to 14.6%, a difference of 6.8%). Conversely, both communities are more comparable in terms of 8th grade (97.0% compared to 96.9%, a difference of 0.060%), 9th grade (96.2% compared to 96.3%, a difference of 0.070%), and 5th grade (98.0% compared to 98.1%, a difference of 0.080%).
Hungarian vs Chinese Education Level
Education Level MetricHungarianChinese
No Schooling Completed
Exceptional
1.6%
Exceptional
1.5%
Nursery School
Exceptional
98.5%
Exceptional
98.6%
Kindergarten
Exceptional
98.5%
Exceptional
98.5%
1st Grade
Exceptional
98.4%
Exceptional
98.5%
2nd Grade
Exceptional
98.4%
Exceptional
98.5%
3rd Grade
Exceptional
98.3%
Exceptional
98.4%
4th Grade
Exceptional
98.2%
Exceptional
98.3%
5th Grade
Exceptional
98.0%
Exceptional
98.1%
6th Grade
Exceptional
97.8%
Exceptional
97.9%
7th Grade
Exceptional
97.2%
Exceptional
97.1%
8th Grade
Exceptional
97.0%
Exceptional
96.9%
9th Grade
Exceptional
96.2%
Exceptional
96.3%
10th Grade
Exceptional
95.3%
Exceptional
95.5%
11th Grade
Exceptional
94.2%
Exceptional
94.6%
12th Grade, No Diploma
Exceptional
92.8%
Exceptional
93.6%
High School Diploma
Exceptional
90.8%
Exceptional
92.0%
GED/Equivalency
Exceptional
87.4%
Exceptional
89.0%
College, Under 1 year
Average
65.6%
Exceptional
68.3%
College, 1 year or more
Average
59.5%
Exceptional
62.2%
Associate's Degree
Average
46.7%
Exceptional
48.5%
Bachelor's Degree
Good
38.3%
Good
38.5%
Master's Degree
Good
15.6%
Fair
14.6%
Professional Degree
Excellent
4.6%
Average
4.5%
Doctorate Degree
Good
1.9%
Fair
1.8%

Hungarian vs Chinese Disability

When considering disability, the most significant differences between Hungarian and Chinese communities in the United States are seen in disability age under 5 (1.5% compared to 1.1%, a difference of 35.7%), disability age 5 to 17 (5.8% compared to 4.7%, a difference of 24.6%), and disability age 18 to 34 (7.1% compared to 6.3%, a difference of 13.0%). Conversely, both communities are more comparable in terms of disability (12.2% compared to 12.2%, a difference of 0.18%), male disability (12.0% compared to 12.1%, a difference of 0.87%), and female disability (12.5% compared to 12.3%, a difference of 1.2%).
Hungarian vs Chinese Disability
Disability MetricHungarianChinese
Disability
Tragic
12.2%
Tragic
12.2%
Males
Tragic
12.0%
Tragic
12.1%
Females
Tragic
12.5%
Fair
12.3%
Age | Under 5 years
Tragic
1.5%
Exceptional
1.1%
Age | 5 to 17 years
Tragic
5.8%
Exceptional
4.7%
Age | 18 to 34 years
Tragic
7.1%
Exceptional
6.3%
Age | 35 to 64 years
Fair
11.4%
Exceptional
10.3%
Age | 65 to 74 years
Exceptional
22.4%
Exceptional
21.7%
Age | Over 75 years
Exceptional
46.5%
Tragic
48.7%
Vision
Good
2.1%
Exceptional
2.0%
Hearing
Tragic
3.4%
Tragic
3.7%
Cognitive
Exceptional
16.5%
Exceptional
15.9%
Ambulatory
Tragic
6.3%
Tragic
6.5%
Self-Care
Average
2.5%
Tragic
2.6%