Educational Attainment in McDonald, Washington County, Pennsylvania (Borough)

Educational Attainment#1

Highest level of education among people aged 25 years and older.
Scope: population of Washington County and McDonald
McDonald
Washington County
0%10%20%30%40%50%CountHigher Degree1H.S. Diploma2No H.S. Diploma229.532404%37.475613%29.532404%29.5%36058.818704%54.278622%58.818704%58.8%71711.648893%8.245765%11.648893%11.6%142
Count number of people in category
1Post-Secondary Degree 2H.S. = High School

Relative Educational Attainment#2

Highest level of education among people aged 25 years and older, as percentage more or less than Washington County at large.
Scope: population of Washington County and McDonald
-40%-20%-0%+20%+40%%ref.Higher Degree1H.S. Diploma2No H.S. Diploma2-21.195676%-21.195676%-21.2%29.532%29.5%37.476%37.5%8.364402%8.364402%+8.4%58.819%58.8%54.279%54.3%41.271215%41.271215%+41.3%11.649%11.6%8.246%8.25%
% percentage with given level in McDonald
ref. percentage with given level in Washington County
1Post-Secondary Degree 2H.S. = High School

Detailed Educational Attainment#3

Highest level of education among people aged 25 years and older.
Scope: population of Washington County and McDonald
McDonald
Washington County
0%10%20%30%40%CountDoctorate1Professional1Master's1Bachelor's1Associate's1Some CollegeHigh School2Some H.S.3Less than H.S.3None0.574241%0.888016%0.574241%0.6%70.000000%0.000000%0.0%1.391225%08.121411%7.322094%8.121411%8.1%9913.863823%18.535985%13.863823%13.9%1696.972929%9.338294%6.972929%7.0%8516.324856%15.437348%16.324856%16.3%19942.493847%38.841274%42.493847%42.5%5187.875308%5.720975%7.875308%7.9%962.871206%1.628702%2.871206%2.9%350.902379%0.896089%0.902379%0.9%11
Count number of people in category
1Degree 2Diploma or equivialent 3H.S. = High School

Detailed Relative Educational Attainment#4

Highest level of education among people aged 25 years and older, as percentage more or less than Washington County at large.
Scope: population of Washington County and McDonald
-100%0%+100%%ref.Doctorate1Professional1Master's1Bachelor's1Associate's1Some CollegeHigh School2Some H.S.3Less than H.S.3None-35.334353%-35.334353%-35.3%0.574%0.57%0.888%0.89%-100.000000%-100.000000%-100.0%0.000%0%1.391%1.39%10.916507%10.916507%+10.9%8.121%8.12%7.322%7.32%-25.205901%-25.205901%-25.2%13.864%13.9%18.536%18.5%-25.329735%-25.329735%-25.3%6.973%6.97%9.338%9.34%5.749101%5.749101%+5.7%16.325%16.3%15.437%15.4%9.403846%9.403846%+9.4%42.494%42.5%38.841%38.8%37.656747%37.656747%+37.7%7.875%7.88%5.721%5.72%76.288010%76.288010%+76.3%2.871%2.87%1.629%1.63%0.701974%0.701974%+0.7%0.902%0.90%0.896%0.90%
% percentage with given level in McDonald
ref. percentage with given level in Washington County
1Degree 2Diploma or equivialent 3H.S. = High School

Educational Attainment Sex Ratio#5

Percentage more likely men or women are to have various highest levels of education among people aged 25 years and older.
Scope: population of Washington County and McDonald
More Females More Males
Washington County
McDonald
20%0%20%FMHigher Degree1H.S. Diploma2No H.S. Diploma2-28.198447%-0.194133%-28.198447%28%33.118%33.1%25.833%25.8%-0.916967%6.976799%6.976799%7%56.866%56.9%60.833%60.8%33.118280%7.124509%33.118280%33%10.016%10.0%13.333%13.3%
F females in category as a percentage of all females
M males in category as a percentage of all males
1Post-Secondary Degree 2H.S. = High School

Detailed Educational Attainment Sex Ratio#6

Percentage more likely men or women are to have various highest levels of education among people aged 25 years and older.
Scope: population of Washington County and McDonald
More Females More Males
Washington County
McDonald
0%500%1,000%FMDoctorate1Master's1Bachelor's1Associate's1Some CollegeHigh School2Some H.S.3Less than H.S.3None1,000.000000%39.369057%1,000.000000%> 1000%0.000%0%1.167%1.17%-102.948304%-18.251167%-102.948304%103%10.824%10.8%5.333%5.33%20.361111%9.360724%20.361111%20%12.601%12.6%15.167%15.2%-132.633279%-19.383723%-132.633279%133%9.693%9.69%4.167%4.17%41.240079%3.534133%41.240079%41%13.570%13.6%19.167%19.2%-3.909532%-2.693717%-3.909532%4%43.296%43.3%41.667%41.7%-35.702746%-0.847831%-35.702746%36%9.047%9.05%6.667%6.67%1,000.000000%11.222742%1,000.000000%> 1000%0.000%0%5.833%5.83%-16.316640%-16.316640%16%64.806937%0.969%0.97%0.833%0.83%
F females in category as a percentage of all females
M males in category as a percentage of all males
1Degree 2Diploma or equivialent 3H.S. = High School

Bachelor's Degrees By Age#7

Percentage of age cohort whose highest degree is a Bachelor's.
Scope: population of Washington County and McDonald
McDonald
Washington County
0%5%10%15%20%25%B.X.Total65+45-6435-4425-3415.704388%10.578584%15.704388%15.7%684335.865922%18.890201%5.865922%5.9%2135822.761194%24.323324%22.761194%22.8%6126811.875000%25.284932%11.875000%11.9%19160
B.X. number of people with a Bachelor's degree
Total number of people in age cohort

Relative Bachelor's Degrees By Age#8

Percentage of population whose highest degree is a Bachelor's, as a percentage more or less than Washington County at large.
Scope: population of Washington County and McDonald
60%40%20%0%20%40%%ref.65+45-6435-4425-3448.454541%48.454541%48.5%15.704%15.7%10.579%10.6%-68.947277%-68.947277%68.9%5.866%5.87%18.890%18.9%-6.422353%-6.422353%6.4%22.761%22.8%24.323%24.3%-53.035271%-53.035271%53.0%11.875%11.9%25.285%25.3%
% percentage in McDonald with a Bachelor's degree
ref percentage in Washington County with a Bachelor's degree

Bachelor's Degrees Sex Ratio By Age#9

Percentage more likely men or women are to have their highest degree be a Bachelor's.
Scope: population of Washington County and McDonald
More Females More Males
Washington County
McDonald
100%0%100%FM65+45-6435-4425-34182.511211%55.282534%182.511211%182.5%8.095%8.10%22.870%22.9%39.240506%7.065169%39.240506%39.2%5.000%5.00%6.962%6.96%-121.052632%-6.121160%-121.052632%121.1%31.343%31.3%14.179%14.2%-2.000000%-13.084124%-2.000000%2.0%12.000%12.0%11.765%11.8%
F female degree holders as a percentage of all females
M male degree holders as a percentage of all males

Median Earnings by Educational Attainment#10

Among population 25 years old and over with earnings.
Scope: population of Washington County and McDonald
McDonald
Washington County
$0k$20k$40k$60kCount%Graduate Degree1Bachelor's DegreeSome CollegeH.S. Diploma2No H.S. Diploma2Total$37,440.000000$66,580.000000$37,440.000000$37.4k1068.696%8.70%$30,750.000000$52,665.000000$30,750.000000$30.8k16913.864%13.9%$40,161.000000$36,578.000000$40,161.000000$40.2k28423.298%23.3%$24,960.000000$30,403.000000$24,960.000000$25.0k51842.494%42.5%$16,016.000000$23,261.000000$16,016.000000$16.0k14211.649%11.6%$30,219.000000$38,973.000000$30,219.000000$30.2k1,219100.000%100%
Count number of people with given highest level of educational attainment
% percentage of people with given highest level of educational attainment
1or professional degree 2H.S. = High School

Median Earnings by Educational Attainment#11

By sex among population 25 years old and over with earnings.
Scope: population of Washington County and McDonald
Female Male
Washington County
McDonald
Shaded bar tips show excess over facing bar.
$50k$0k$50kFMGraduate Degree1Some CollegeH.S. Diploma2Total$-36,190.000000$-55,929.000000$-36,190.000000$36.2k$36,190.000000$11,935.000000$55,929.000000$34,748.000000$48,125.000000$48.1k6739$-33,500.000000$-28,719.000000$-33,500.000000$33.5k$33,500.000000$7,426.000000$28,719.000000$17,012.000000$40,926.000000$40.9k144140$-24,583.000000$-22,711.000000$-24,583.000000$24.6k$24,583.000000$774.000000$22,711.000000$17,397.000000$25,357.000000$25.4k268250$-26,629.000000$-30,122.000000$-26,629.000000$26.6k$26,629.000000$8,490.000000$30,122.000000$19,023.000000$35,119.000000$35.1k619600
F females with given highest level of educational attainment
M males with given highest level of educational attainment
1or professional degree 2H.S. = High School

Employment by Educational Attainment#12

Percentage of population that is employed by highest level of educational attainment among the population aged 25 to 64 years old.
Scope: population of Washington County and McDonald
McDonald
Washington County
0%20%40%60%80%CountBachelor's Degree1Some College2H.S. Diploma3No H.S. Diploma385.064935%83.253355%85.064935%85.1%13181.451613%75.522677%81.451613%81.5%20266.229508%67.627123%66.229508%66.2%20241.772152%41.977848%41.772152%41.8%33
Count employed people with given educational attainment aged 25 to 64 years old
1or higher 2two or four year institution 3H.S. = High School

Lacking High School Diploma By Race#13

Percent of racial or ethnic group lacking a high school diploma (or equivalent).
Scope: population of Washington County and McDonald
Female Male
Washington County
McDonald
Shaded bar tips show excess over facing bar.
10%0%10%20%MFWhite1BlackHispanic2-10.490694%-7.690834%-10.490694%10.5%10.490694%3.538083%7.690834%0.173482%14.028777%14.0%7862-0.000000%-14.414894%0.000000%0.0%0.000000%0.000000%14.414894%4.598093%0.000000%0.0%00-0.000000%-12.855377%0.000000%0.0%0.000000%7.142857%12.855377%13.752162%7.142857%7.1%20
M number of males in category
F number of females in category
1non-Hispanic 2excluding black and Asian Hispanics

College Graduates By Race#14

Percent of racial or ethnic group with a bachelor's degree or higher.
Scope: population of Washington County and McDonald
Female Male
Washington County
McDonald
Shaded bar tips show excess over facing bar.
100%50%0%MFWhite1BlackHispanic2-20.981387%-27.534884%-20.981387%21.0%20.981387%2.399907%27.534884%1.684785%23.381295%23.4%130124-0.000000%-16.467532%-4.596297%0.000000%0.0%0.000000%0.000000%16.467532%0.000000%0.0%00-0.000000%-100.000000%-20.288248%-3.073927%-100.000000%100.0%0.000000%20.288248%0.000000%0.0%021
M number of males in category
F number of females in category
1non-Hispanic 2excluding black and Asian Hispanics

Educational Attainment by County Subdivision in the Pittsburgh Area

There are 460 county subdivisions in the Pittsburgh Area. This section compares McDonald to the 50 most populous county subdivisions in the Pittsburgh Area and to those entities that contain or substantially overlap with McDonald. The least populous of the compared county subdivisions has a population of 11,197.

No H.S. Diploma by County Subdivision#15

Percent of population 25 years of age and older without a high school diploma (or equivalent).
Scope: population of McDonald, selected other county subdivisions in the Pittsburgh Area, and entities that contain McDonald
0%5%10%Count#McDonaldMcKeesportWashingtonUnited States of AmericaUnited StatesNorth Union TownshipN UnionNew KensingtonMiddle Atlantic715700Tract 715700McDonaldNortheastButlerDerry TownshipDerryPennsylvaniaFort Cherry School DistrictFort CherryWilkinsburgWhitehallWashington CountyWashingtonPittsburghHopewell TownshipHopewellGreensburgWest Deer TownshipW DeerHempfield TownshipHempfieldPittsburgh Metro AreaPittsburghZIP Code 15057ZIP 15057MunhallRobinson TownshipRobinsonUnity TownshipUnityPenn Hills TownshipPenn HlsNorth Fayette TownshipN FayetteBaldwinCecil TownshipCecilLower BurrellWest MifflinRoss TownshipButler TownshipButlerCenter TownshipCtrSouth Fayette TownshipS FayetteShaler TownshipShalerScott TownshipScottMoon TownshipRostraver TownshipRostraverMonroevillePlumNorth Strabane TownshipN StrabanePenn TownshipBethel ParkNorth Huntingdon TownshipN HuntingdonElizabeth TownshipElizabethRichland TownshipRichlandMcCandless TownshipMcCandlessCranberry TownshipCranberryMurrysvilleHampton TownshipHamptonSouth Park TownshipS PkJefferson HillsJefferson HlsAdams TownshipAdamsPeters TownshipPetersMount Lebanon TownshipMt LebanonUpper St. Clair TownshipUpper St. ClairFranklin ParkPine Township13.935970%13.935970%13.9%22213.745428%13.745428%13.7%1,879113.102099%13.102099%13.1%1,205213.020590%13.020590%13.0%27,818,38027.8M12.479966%12.479966%12.5%1,168312.421834%12.421834%12.4%1,172412.313400%12.313400%12.3%3,505,1913.51M11.648893%11.648893%11.6%14211.648893%11.648893%11.6%14211.614335%11.614335%11.6%4,487,0854.49M10.908131%10.908131%10.9%1,033510.696587%10.696587%10.7%1,144610.459911%10.459911%10.5%925,686926k10.128644%10.128644%10.1%6229.211661%9.211661%9.2%1,06878.658663%8.658663%8.7%91688.245765%8.245765%8.2%12,25712.3k8.043576%8.043576%8.0%16,40616.4k97.739130%7.739130%7.7%712107.388471%7.388471%7.4%737117.301011%7.301011%7.3%643127.148505%7.148505%7.1%2,260137.130926%7.130926%7.1%120,640121k7.119651%7.119651%7.1%7677.016473%7.016473%7.0%575146.941165%6.941165%6.9%735156.896773%6.896773%6.9%1,073166.765076%6.765076%6.8%2,099176.577684%6.577684%6.6%685186.396191%6.396191%6.4%927196.077348%6.077348%6.1%517205.862312%5.862312%5.9%499215.671885%5.671885%5.7%837225.637439%5.637439%5.6%1,354235.636235%5.636235%5.6%718245.507623%5.507623%5.5%466255.441079%5.441079%5.4%573265.338744%5.338744%5.3%1,171275.249464%5.249464%5.2%686285.169841%5.169841%5.2%866295.119920%5.119920%5.1%412304.869736%4.869736%4.9%1,043314.837339%4.837339%4.8%968324.716532%4.716532%4.7%495334.364142%4.364142%4.4%628344.315126%4.315126%4.3%1,027354.016913%4.016913%4.0%912363.965778%3.965778%4.0%394373.450863%3.450863%3.5%276383.276003%3.276003%3.3%680393.194067%3.194067%3.2%646403.192710%3.192710%3.2%473413.067020%3.067020%3.1%405422.955466%2.955466%3.0%292432.824360%2.824360%2.8%224442.373068%2.373068%2.4%215452.271945%2.271945%2.3%330461.930306%1.930306%1.9%457471.324503%1.324503%1.3%176481.026905%1.026905%1.0%100490.730994%0.730994%0.7%6050
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older without a high school diploma (or equivalent).

Bachelor's Degrees by County Subdivision#16

Percent of population 25 years of age and older with a bachelor's degree or higher..
Scope: population of McDonald, selected other county subdivisions in the Pittsburgh Area, and entities that contain McDonald
0%20%40%60%Count#Pine TownshipFranklin ParkMount Lebanon TownshipMt LebanonUpper St. Clair TownshipUpper St. ClairPeters TownshipPetersAdams TownshipAdamsMcCandless TownshipMcCandlessCranberry TownshipCranberryMurrysvilleRichland TownshipRichlandHampton TownshipHamptonMoon TownshipRobinson TownshipRobinsonSouth Fayette TownshipS FayetteBethel ParkNorth Strabane TownshipN StrabaneScott TownshipScottRoss TownshipJefferson HillsJefferson HlsPittsburghCecil TownshipCecilMonroevilleNorth Fayette TownshipN FayettePlumShaler TownshipShalerZIP Code 15057ZIP 15057South Park TownshipS PkPenn TownshipNortheastMiddle AtlanticNorth Huntingdon TownshipN HuntingdonGreensburgCenter TownshipCtrWhitehallPittsburgh Metro AreaPittsburghUnity TownshipUnityWest Deer TownshipW DeerHempfield TownshipHempfieldWilkinsburgUnited States of AmericaUnited StatesButler TownshipButlerPennsylvaniaPenn Hills TownshipPenn HlsWashington CountyWashingtonMunhallBaldwinRostraver TownshipRostraverHopewell TownshipHopewellLower BurrellElizabeth TownshipElizabethNew Kensington715700Tract 715700McDonaldWest MifflinFort Cherry School DistrictFort CherryMcDonaldWashingtonButlerNorth Union TownshipN UnionDerry TownshipDerryMcKeesport72.843567%72.843567%72.8%5,979170.384062%70.384062%70.4%6,854268.861668%68.861668%68.9%16,30316.3k368.550572%68.550572%68.6%9,109460.984509%60.984509%61.0%8,858558.763797%58.763797%58.8%5,324657.527581%57.527581%57.5%11,94111.9k756.998764%56.998764%57.0%11,52811.5k852.480594%52.480594%52.5%7,775952.250563%52.250563%52.3%4,1791050.836804%50.836804%50.8%6,7131149.800012%49.800012%49.8%8,3421247.728775%47.728775%47.7%5,0541346.871142%46.871142%46.9%4,9361445.546218%45.546218%45.5%10,84010.8k1545.192949%45.192949%45.2%4,7431643.587389%43.587389%43.6%5,6961743.209260%43.209260%43.2%10,37810.4k1842.894969%42.894969%42.9%3,4021940.731207%40.731207%40.7%83,07783.1k2039.155989%39.155989%39.2%3,3312138.668410%38.668410%38.7%8,2822238.419435%38.419435%38.4%4,0012336.130128%36.130128%36.1%7,2302436.008024%36.008024%36.0%7,8982535.069154%35.069154%35.1%3,77835.050607%35.050607%35.1%3,4632634.933982%34.933982%34.9%5,0272734.780899%34.780899%34.8%13,437,26113.4M33.644618%33.644618%33.6%9,577,4379.58M33.487491%33.487491%33.5%7,6032833.042607%33.042607%33.0%3,2962932.880274%32.880274%32.9%2,7823032.857548%32.857548%32.9%3,4763132.546256%32.546256%32.5%550,613551k31.932125%31.932125%31.9%4,9683231.702055%31.702055%31.7%2,7923330.903052%30.903052%30.9%9,7703430.714162%30.714162%30.7%3,5613530.315023%30.315023%30.3%64,767,78764.8M29.963105%29.963105%30.0%3,8173629.333279%29.333279%29.3%2,595,9502.60M29.058562%29.058562%29.1%9,0163728.137320%28.137320%28.1%41,82541.8k26.430750%26.430750%26.4%2,1663826.371352%26.371352%26.4%3,8223925.885423%25.885423%25.9%2,0834025.586957%25.586957%25.6%2,3544125.281955%25.281955%25.3%2,1524224.992451%24.992451%25.0%2,4834323.624801%23.624801%23.6%2,2294422.559475%22.559475%22.6%27522.559475%22.559475%22.6%27522.003117%22.003117%22.0%3,2474520.159583%20.159583%20.2%1,23819.271814%19.271814%19.3%30717.951506%17.951506%18.0%1,6514616.282999%16.282999%16.3%1,5424713.505716%13.505716%13.5%1,2644812.837775%12.837775%12.8%1,3734912.267740%12.267740%12.3%1,67750
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older with a bachelor's degree or higher..

Very Advanced Degrees by County Subdivision#17

Percent of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).
Scope: population of McDonald, selected other county subdivisions in the Pittsburgh Area, and entities that contain McDonald
0%5%10%Count#Franklin ParkMount Lebanon TownshipMt LebanonUpper St. Clair TownshipUpper St. ClairHampton TownshipHamptonPine TownshipPittsburghMurrysvilleMcCandless TownshipMcCandlessPeters TownshipPetersMoon TownshipUnity TownshipUnityCranberry TownshipCranberryMonroevilleRoss TownshipRichland TownshipRichlandBethel ParkNortheastMiddle AtlanticAdams TownshipAdamsPittsburgh Metro AreaPittsburghNorth Strabane TownshipN StrabaneUnited States of AmericaUnited StatesPennsylvaniaShaler TownshipShalerSouth Fayette TownshipS FayetteScott TownshipScottCecil TownshipCecilGreensburgRostraver TownshipRostraverWilkinsburgNorth Fayette TownshipN FayetteMunhallHempfield TownshipHempfieldSouth Park TownshipS PkWhitehallRobinson TownshipRobinsonPenn Hills TownshipPenn HlsWashington CountyWashingtonPenn TownshipElizabeth TownshipElizabethCenter TownshipCtrHopewell TownshipHopewellLower BurrellNew KensingtonJefferson HillsJefferson HlsNorth Huntingdon TownshipN HuntingdonZIP Code 15057ZIP 15057Butler TownshipButlerPlumBaldwinWest Deer TownshipW DeerWashingtonButlerWest MifflinNorth Union TownshipN Union715700Tract 715700McDonaldMcKeesportDerry TownshipDerryMcDonaldFort Cherry School DistrictFort Cherry13.134114%13.134114%13.1%1,279112.929250%12.929250%12.9%3,061212.409693%12.409693%12.4%1,64938.436198%8.436198%8.4%1,11447.614522%7.614522%7.6%62557.432194%7.432194%7.4%15,15915.2k67.080661%7.080661%7.1%1,04976.966325%6.966325%7.0%1,44686.781411%6.781411%6.8%98594.871351%4.871351%4.9%816104.769251%4.769251%4.8%742114.697157%4.697157%4.7%950124.440190%4.440190%4.4%951134.221834%4.221834%4.2%1,014144.201050%4.201050%4.2%336154.105042%4.105042%4.1%977164.085016%4.085016%4.1%1,578,2061.58M3.884861%3.884861%3.9%1,105,8831.11M3.741722%3.741722%3.7%339173.600869%3.600869%3.6%60,91960.9k3.439733%3.439733%3.4%361183.336158%3.336158%3.3%7,127,6737.13M3.299391%3.299391%3.3%291,991292k3.250661%3.250661%3.3%713193.228563%3.228563%3.2%340203.221610%3.221610%3.2%421213.044552%3.044552%3.0%259222.957393%2.957393%3.0%295232.758792%2.758792%2.8%222242.682422%2.682422%2.7%311252.669483%2.669483%2.7%278262.489323%2.489323%2.5%204272.479836%2.479836%2.5%784282.469636%2.469636%2.5%244292.438794%2.438794%2.4%258302.408159%2.408159%2.4%255312.356013%2.356013%2.4%731322.279241%2.279241%2.3%3,3882.251564%2.251564%2.3%324332.194263%2.194263%2.2%218342.021038%2.021038%2.0%171352.000000%2.000000%2.0%184361.985432%1.985432%2.0%169371.907790%1.907790%1.9%180381.866095%1.866095%1.9%148391.814658%1.814658%1.8%412401.596584%1.596584%1.6%1721.562132%1.562132%1.6%199411.544151%1.544151%1.5%309421.483475%1.483475%1.5%215431.226297%1.226297%1.2%108441.141677%1.141677%1.1%105451.024287%1.024287%1.0%97460.955479%0.955479%1.0%141470.758628%0.758628%0.8%71480.574241%0.574241%0.6%70.574241%0.574241%0.6%70.548647%0.548647%0.5%75490.448808%0.448808%0.4%48500.439422%0.439422%0.4%70.407100%0.407100%0.4%25
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).

Under-Education Sex Ratio by County Subdivision#18

Percentage more likely men are than women to not have a high school diploma (or equivalent) among people aged 25 years and older.
Scope: population of McDonald, selected other county subdivisions in the Pittsburgh Area, and entities that contain McDonald
Female
Male
2x1x0x1xFM#PetersShalerAdamsLower BurrellN StrabaneCtrWhitehallRostraverTract 715700McDonaldMunhallMcDonaldMt LebanonWest MifflinFort CherryNew KensingtonWilkinsburgHempfieldDerryMcKeesportPine TownshipUnityN UnionUnited StatesPennsylvaniaS FayetteNortheastZIP 15057WashingtonMiddle AtlanticPenn TownshipBaldwinPittsburghMoon TownshipPlumMurrysvillePenn HlsWashingtonButlerPittsburghN FayetteElizabethBethel ParkCecilMonroevilleUpper St. ClairW DeerButlerJefferson HlsMcCandlessHamptonN HuntingdonRoss TownshipGreensburgRobinsonS PkHopewellScottCranberryRichlandFranklin Park-1.000000x-1.000000x1.982039x1.982039x1.98x1.545%1.55%3.063%3.06%1-1.000000x-1.000000x1.552208x1.552208x1.55x4.210%4.21%6.535%6.53%2-1.000000x-1.000000x1.512764x1.512764x1.51x1.894%1.89%2.865%2.87%3-1.000000x-1.000000x1.429753x1.429753x1.43x4.856%4.86%6.943%6.94%4-1.000000x-1.000000x1.427362x1.427362x1.43x3.889%3.89%5.551%5.55%5-1.000000x-1.000000x1.405987x1.405987x1.41x4.637%4.64%6.520%6.52%6-1.000000x-1.000000x1.355787x1.355787x1.36x7.478%7.48%10.138%10.1%7-1.000000x-1.000000x1.337913x1.337913x1.34x4.379%4.38%5.859%5.86%8-1.000000x-1.000000x1.331183x1.331183x1.33x10.016%10.0%13.333%13.3%-1.000000x-1.000000x1.331183x1.331183x1.33x10.016%10.0%13.333%13.3%-1.000000x-1.000000x1.321989x1.321989x1.32x6.071%6.07%8.026%8.03%9-1.000000x-1.000000x1.314658x1.314658x1.31x12.088%12.1%15.891%15.9%-1.000000x-1.000000x1.310561x1.310561x1.31x1.685%1.69%2.208%2.21%10-1.000000x-1.000000x1.309286x1.309286x1.31x4.977%4.98%6.517%6.52%11-1.000000x-1.000000x1.290542x1.290542x1.29x8.846%8.85%11.416%11.4%-1.000000x-1.000000x1.279801x1.279801x1.28x10.987%11.0%14.062%14.1%12-1.000000x-1.000000x1.249216x1.249216x1.25x8.344%8.34%10.424%10.4%13-1.000000x-1.000000x1.243946x1.243946x1.24x6.384%6.38%7.942%7.94%14-1.000000x-1.000000x1.214660x1.214660x1.21x9.690%9.69%11.770%11.8%15-1.000000x-1.000000x1.207679x1.207679x1.21x12.567%12.6%15.177%15.2%16-1.000000x-1.000000x1.141684x1.141684x1.14x0.684%0.68%0.781%0.78%17-1.000000x-1.000000x1.130306x1.130306x1.13x6.490%6.49%7.336%7.34%18-1.000000x-1.000000x1.120959x1.120959x1.12x11.824%11.8%13.254%13.3%19-1.000000x-1.000000x1.109070x1.109070x1.11x12.369%12.4%13.719%13.7%-1.000000x-1.000000x1.094514x1.094514x1.09x10.006%10.0%10.952%11.0%-1.000000x-1.000000x1.087339x1.087339x1.09x5.225%5.23%5.682%5.68%20-1.000000x-1.000000x1.074442x1.074442x1.07x11.216%11.2%12.051%12.1%-1.000000x-1.000000x1.073596x1.073596x1.07x6.866%6.87%7.372%7.37%-1.000000x-1.000000x1.071245x1.071245x1.07x7.973%7.97%8.541%8.54%-1.000000x-1.000000x1.059800x1.059800x1.06x11.972%12.0%12.688%12.7%-1.000000x-1.000000x1.040383x1.040383x1.04x4.281%4.28%4.453%4.45%21-1.000000x-1.000000x1.029151x1.029151x1.03x6.309%6.31%6.493%6.49%22-1.000000x-1.000000x1.015146x1.015146x1.02x7.080%7.08%7.187%7.19%-1.000000x-1.000000x1.010004x1.010004x1.01x5.143%5.14%5.195%5.19%23-1.000000x-1.000000x1.006305x1.006305x1.01x4.823%4.82%4.853%4.85%24-1.000014x-1.000014x1.00x1.000000x1.000000x3.193%3.19%3.193%3.19%25-1.008684x-1.008684x1.01x1.000000x1.000000x6.792%6.79%6.733%6.73%26-1.018234x-1.018234x1.02x1.000000x1.000000x13.217%13.2%12.980%13.0%27-1.038960x-1.038960x1.04x1.000000x1.000000x11.113%11.1%10.697%10.7%28-1.054084x-1.054084x1.05x1.000000x1.000000x8.249%8.25%7.826%7.83%29-1.086419x-1.086419x1.09x1.000000x1.000000x6.842%6.84%6.298%6.30%30-1.105460x-1.105460x1.11x1.000000x1.000000x4.147%4.15%3.752%3.75%31-1.132717x-1.132717x1.13x1.000000x1.000000x4.563%4.56%4.029%4.03%32-1.135043x-1.135043x1.14x1.000000x1.000000x6.447%6.45%5.680%5.68%33-1.138629x-1.138629x1.14x1.000000x1.000000x5.164%5.16%4.535%4.54%34-1.165296x-1.165296x1.17x1.000000x1.000000x1.419%1.42%1.218%1.22%35-1.184230x-1.184230x1.18x1.000000x1.000000x7.893%7.89%6.665%6.67%36-1.191524x-1.191524x1.19x1.000000x1.000000x6.102%6.10%5.121%5.12%37-1.209319x-1.209319x1.21x1.000000x1.000000x3.075%3.08%2.543%2.54%38-1.270679x-1.270679x1.27x1.000000x1.000000x3.640%3.64%2.864%2.86%39-1.279586x-1.279586x1.28x1.000000x1.000000x3.416%3.42%2.670%2.67%40-1.291642x-1.291642x1.29x1.000000x1.000000x4.505%4.51%3.488%3.49%41-1.296113x-1.296113x1.30x1.000000x1.000000x6.295%6.29%4.856%4.86%42-1.304698x-1.304698x1.30x1.000000x1.000000x8.186%8.19%6.274%6.27%43-1.371760x-1.371760x1.37x1.000000x1.000000x7.980%7.98%5.818%5.82%44-1.372742x-1.372742x1.37x1.000000x1.000000x3.393%3.39%2.472%2.47%45-1.422764x-1.422764x1.42x1.000000x1.000000x9.058%9.06%6.366%6.37%46-1.679137x-1.679137x1.68x1.000000x1.000000x6.460%6.46%3.847%3.85%47-2.300755x-2.300755x2.30x1.000000x1.000000x4.416%4.42%1.919%1.92%48-2.427134x-2.427134x2.43x1.000000x1.000000x4.789%4.79%1.973%1.97%49-2.643304x-2.643304x2.64x1.000000x1.000000x1.483%1.48%0.561%0.56%50
F percentage of females in category
M percentage of males in category
# rank of county subdivision out of 50 by male-to-female sex ratio

Over-Education Sex Ratio by County Subdivision#19

Percentage more likely men are than women to have a professional or doctorate degree (e.g., MBA, PhD, or MD) among people aged 25 years and older.
Scope: population of McDonald, selected other county subdivisions in the Pittsburgh Area, and entities that contain McDonald
Female
Male
0x5x10xFM#McDonaldTract 715700McDonaldDerryLower BurrellRichlandMcKeesportZIP 15057WhitehallHopewellN StrabaneElizabethButlerS PkWest MifflinUnityPine TownshipUpper St. ClairMt LebanonPenn TownshipHempfieldFort CherryNew KensingtonN HuntingdonCranberryBaldwinMurrysvilleRoss TownshipWilkinsburgMcCandlessPetersWashingtonFranklin ParkPittsburghPennsylvaniaW DeerHamptonScottS FayetteMonroevilleUnited StatesMiddle AtlanticNortheastGreensburgMoon TownshipPittsburghCecilButlerCtrBethel ParkShalerAdamsJefferson HlsRostraverPlumPenn HlsN UnionWashingtonMunhallN FayetteRobinson-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%0.904%0.90%-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%1.167%1.17%-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%1.167%1.17%-1.000000x-1.000000x5.335330x5.335330x5.34x0.145%0.14%0.773%0.77%1-1.000000x-1.000000x4.424405x4.424405x4.42x0.749%0.75%3.313%3.31%2-1.000000x-1.000000x4.195896x4.195896x4.20x1.668%1.67%6.998%7.00%3-1.000000x-1.000000x4.142305x4.142305x4.14x0.227%0.23%0.939%0.94%4-1.000000x-1.000000x3.760285x3.760285x3.76x0.670%0.67%2.519%2.52%-1.000000x-1.000000x3.501723x3.501723x3.50x1.156%1.16%4.047%4.05%5-1.000000x-1.000000x3.033869x3.033869x3.03x1.002%1.00%3.039%3.04%6-1.000000x-1.000000x2.907647x2.907647x2.91x1.764%1.76%5.130%5.13%7-1.000000x-1.000000x2.776795x2.776795x2.78x1.209%1.21%3.357%3.36%8-1.000000x-1.000000x2.751751x2.751751x2.75x0.853%0.85%2.346%2.35%9-1.000000x-1.000000x2.747368x2.747368x2.75x1.350%1.35%3.708%3.71%10-1.000000x-1.000000x2.680211x2.680211x2.68x0.543%0.54%1.456%1.46%11-1.000000x-1.000000x2.576396x2.576396x2.58x2.712%2.71%6.988%6.99%12-1.000000x-1.000000x2.408624x2.408624x2.41x4.529%4.53%10.910%10.9%13-1.000000x-1.000000x2.390630x2.390630x2.39x7.507%7.51%17.946%17.9%14-1.000000x-1.000000x2.330320x2.330320x2.33x7.964%7.96%18.560%18.6%15-1.000000x-1.000000x2.289886x2.289886x2.29x1.386%1.39%3.175%3.17%16-1.000000x-1.000000x2.256635x2.256635x2.26x1.534%1.53%3.462%3.46%17-1.000000x-1.000000x2.131238x2.131238x2.13x0.260%0.26%0.554%0.55%-1.000000x-1.000000x2.072311x2.072311x2.07x1.272%1.27%2.635%2.64%18-1.000000x-1.000000x2.038929x2.038929x2.04x1.211%1.21%2.469%2.47%19-1.000000x-1.000000x1.978141x1.978141x1.98x3.176%3.18%6.283%6.28%20-1.000000x-1.000000x1.910738x1.910738x1.91x1.036%1.04%1.980%1.98%21-1.000000x-1.000000x1.846175x1.846175x1.85x5.036%5.04%9.297%9.30%22-1.000000x-1.000000x1.750758x1.750758x1.75x3.143%3.14%5.503%5.50%23-1.000000x-1.000000x1.707474x1.707474x1.71x2.071%2.07%3.537%3.54%24-1.000000x-1.000000x1.703524x1.703524x1.70x5.237%5.24%8.922%8.92%25-1.000000x-1.000000x1.668074x1.668074x1.67x5.138%5.14%8.571%8.57%26-1.000000x-1.000000x1.652123x1.652123x1.65x1.736%1.74%2.868%2.87%-1.000000x-1.000000x1.636144x1.636144x1.64x9.992%9.99%16.348%16.3%27-1.000000x-1.000000x1.634496x1.634496x1.63x2.765%2.77%4.520%4.52%-1.000000x-1.000000x1.629829x1.629829x1.63x2.534%2.53%4.130%4.13%-1.000000x-1.000000x1.623772x1.623772x1.62x0.943%0.94%1.531%1.53%28-1.000000x-1.000000x1.622133x1.622133x1.62x6.534%6.53%10.599%10.6%29-1.000000x-1.000000x1.596146x1.596146x1.60x2.524%2.52%4.029%4.03%30-1.000000x-1.000000x1.591763x1.591763x1.59x2.523%2.52%4.015%4.02%31-1.000000x-1.000000x1.556689x1.556689x1.56x3.522%3.52%5.482%5.48%32-1.000000x-1.000000x1.526215x1.526215x1.53x2.660%2.66%4.060%4.06%-1.000000x-1.000000x1.502828x1.502828x1.50x3.134%3.13%4.710%4.71%-1.000000x-1.000000x1.486326x1.486326x1.49x3.316%3.32%4.929%4.93%-1.000000x-1.000000x1.485812x1.485812x1.49x2.459%2.46%3.654%3.65%33-1.000000x-1.000000x1.468207x1.468207x1.47x3.925%3.93%5.763%5.76%34-1.000000x-1.000000x1.398688x1.398688x1.40x6.228%6.23%8.711%8.71%35-1.000000x-1.000000x1.365883x1.365883x1.37x2.588%2.59%3.535%3.53%36-1.000000x-1.000000x1.293502x1.293502x1.29x0.895%0.89%1.158%1.16%37-1.000000x-1.000000x1.292650x1.292650x1.29x1.780%1.78%2.301%2.30%38-1.000000x-1.000000x1.260941x1.260941x1.26x3.662%3.66%4.617%4.62%39-1.000000x-1.000000x1.215685x1.215685x1.22x2.942%2.94%3.577%3.58%40-1.000000x-1.000000x1.164008x1.164008x1.16x3.462%3.46%4.030%4.03%41-1.000000x-1.000000x1.092916x1.092916x1.09x1.788%1.79%1.954%1.95%42-1.000000x-1.000000x1.034381x1.034381x1.03x2.712%2.71%2.805%2.81%43-1.072148x-1.072148x1.07x1.000000x1.000000x1.595%1.59%1.488%1.49%44-1.180307x-1.180307x1.18x1.000000x1.000000x2.532%2.53%2.145%2.15%45-1.301386x-1.301386x1.30x1.000000x1.000000x0.849%0.85%0.652%0.65%46-1.407989x-1.407989x1.41x1.000000x1.000000x1.328%1.33%0.943%0.94%47-1.511966x-1.511966x1.51x1.000000x1.000000x2.977%2.98%1.969%1.97%48-1.536489x-1.536489x1.54x1.000000x1.000000x3.216%3.22%2.093%2.09%49-2.396983x-2.396983x2.40x1.000000x1.000000x3.345%3.34%1.395%1.40%50
F percentage of females in category
M percentage of males in category
# rank of county subdivision out of 50 by male-to-female sex ratio

Educational Attainment by County Subdivision in Pennsylvania

There are 2,574 county subdivisions in Pennsylvania. This section compares McDonald to the 50 most populous county subdivisions in Pennsylvania and to those entities that contain or substantially overlap with McDonald. The least populous of the compared county subdivisions has a population of 27,333.

No H.S. Diploma by County Subdivision#20

Percent of population 25 years of age and older without a high school diploma (or equivalent).
Scope: population of McDonald, selected other county subdivisions in Pennsylvania, and entities that contain McDonald
0%10%20%30%Count#ReadingLancasterAllentownYorkHarrisburgChesterNorristownPhiladelphiaWilkes-BarreScrantonMcDonaldUnited States of AmericaUnited StatesErieWilliamsportBethlehemMiddle AtlanticBristol TownshipBristol715700Tract 715700McDonaldNortheastAltoonaUpper Darby TownshipUpper DarbyPennsylvaniaFort Cherry School DistrictFort CherryWarminster TownshipWarminsterYork TownshipBensalem TownshipBensalemWashington CountyWashingtonRidley TownshipRidleyManheim TownshipManheimPittsburghFalls TownshipFallsHempfield TownshipHempfieldPittsburgh Metro AreaPittsburghZIP Code 15057ZIP 15057Penn Hills TownshipPenn HlsLower Paxton TownshipLower PaxtonSpring TownshipSpgLower Macungie TownshipLower MacungieHampden TownshipHampdenRoss TownshipShaler TownshipShalerMillcreek TownshipMillcreekMiddletown TownshipMiddletownAbington TownshipAbingtonMonroevillePlumUpper Merion TownshipUpper MerionCheltenham TownshipCheltenhamBethel ParkNorth Huntingdon TownshipN HuntingdonMcCandless TownshipMcCandlessHaverford TownshipHaverfordNorthampton TownshipNorthamptonCranberry TownshipCranberryState CollegeLower Merion TownshipLower MerionRadnor TownshipRadnorLower Makefield TownshipLower MakefieldMount Lebanon TownshipMt LebanonTredyffrin TownshipTredyffrin34.584042%34.584042%34.6%17,27317.3k124.307408%24.307408%24.3%8,932221.725192%21.725192%21.7%15,92515.9k321.603181%21.603181%21.6%5,541421.226461%21.226461%21.2%6,504520.735207%20.735207%20.7%4,191619.454765%19.454765%19.5%4,346717.390838%17.390838%17.4%180,039180k816.790421%16.790421%16.8%4,319915.146168%15.146168%15.1%7,5541013.935970%13.935970%13.9%22213.020590%13.020590%13.0%27,818,38027.8M12.909782%12.909782%12.9%8,3841112.811733%12.811733%12.8%2,2451212.551332%12.551332%12.6%4,2791312.313400%12.313400%12.3%3,505,1913.51M12.060100%12.060100%12.1%4,5031411.648893%11.648893%11.6%14211.648893%11.648893%11.6%14211.614335%11.614335%11.6%4,487,0854.49M10.743639%10.743639%10.7%3,2811510.463617%10.463617%10.5%5,7621610.459911%10.459911%10.5%925,686926k10.128644%10.128644%10.1%6229.749015%9.749015%9.7%2,350178.805520%8.805520%8.8%1,812188.506291%8.506291%8.5%3,664198.245765%8.245765%8.2%12,25712.3k8.175269%8.175269%8.2%1,793208.116386%8.116386%8.1%2,279218.043576%8.043576%8.0%16,40616.4k227.248333%7.248333%7.2%1,718237.148505%7.148505%7.1%2,260247.130926%7.130926%7.1%120,640121k7.119651%7.119651%7.1%7676.765076%6.765076%6.8%2,099256.244529%6.244529%6.2%2,140266.213218%6.213218%6.2%1,193276.020431%6.020431%6.0%1,326285.958474%5.958474%6.0%1,234295.637439%5.637439%5.6%1,354305.338744%5.338744%5.3%1,171315.198402%5.198402%5.2%1,952325.180883%5.180883%5.2%1,677335.076142%5.076142%5.1%2,000344.869736%4.869736%4.9%1,043354.837339%4.837339%4.8%968364.625530%4.625530%4.6%982374.539848%4.539848%4.5%1,141384.315126%4.315126%4.3%1,027394.016913%4.016913%4.0%912403.276003%3.276003%3.3%680413.231313%3.231313%3.2%1,060423.210741%3.210741%3.2%880433.194067%3.194067%3.2%646442.970218%2.970218%3.0%373452.533015%2.533015%2.5%1,007462.517303%2.517303%2.5%411471.954874%1.954874%2.0%454481.930306%1.930306%1.9%457491.838552%1.838552%1.8%38450
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older without a high school diploma (or equivalent).

Bachelor's Degrees by County Subdivision#21

Percent of population 25 years of age and older with a bachelor's degree or higher..
Scope: population of McDonald, selected other county subdivisions in Pennsylvania, and entities that contain McDonald
0%20%40%60%Count#Lower Merion TownshipLower MerionTredyffrin TownshipTredyffrinRadnor TownshipRadnorState CollegeLower Makefield TownshipLower MakefieldMount Lebanon TownshipMt LebanonMcCandless TownshipMcCandlessCranberry TownshipCranberryUpper Merion TownshipUpper MerionHaverford TownshipHaverfordCheltenham TownshipCheltenhamHampden TownshipHampdenNorthampton TownshipNorthamptonLower Macungie TownshipLower MacungieAbington TownshipAbingtonManheim TownshipManheimBethel ParkRoss TownshipPittsburghMillcreek TownshipMillcreekMonroevilleMiddletown TownshipMiddletownLower Paxton TownshipLower PaxtonPlumShaler TownshipShalerSpring TownshipSpgZIP Code 15057ZIP 15057NortheastYork TownshipMiddle AtlanticNorth Huntingdon TownshipN HuntingdonPittsburgh Metro AreaPittsburghHempfield TownshipHempfieldUnited States of AmericaUnited StatesUpper Darby TownshipUpper DarbyPennsylvaniaPenn Hills TownshipPenn HlsWashington CountyWashingtonWarminster TownshipWarminsterBensalem TownshipBensalemBethlehemPhiladelphiaRidley TownshipRidley715700Tract 715700McDonaldFalls TownshipFallsErieScrantonNorristownFort Cherry School DistrictFort CherryWilliamsportLancasterMcDonaldHarrisburgAltoonaWilkes-BarreAllentownBristol TownshipBristolYorkChesterReading76.926173%76.926173%76.9%30,58230.6k176.228095%76.228095%76.2%15,92115.9k272.720034%72.720034%72.7%11,87311.9k369.804109%69.804109%69.8%8,766468.941612%68.941612%68.9%16,01116.0k568.861668%68.861668%68.9%16,30316.3k657.527581%57.527581%57.5%11,94111.9k756.998764%56.998764%57.0%11,52811.5k856.820537%56.820537%56.8%12,06312.1k955.840751%55.840751%55.8%18,31818.3k1052.059046%52.059046%52.1%13,08413.1k1150.077257%50.077257%50.1%10,37110.4k1249.916083%49.916083%49.9%13,68113.7k1349.194098%49.194098%49.2%10,83510.8k1446.736041%46.736041%46.7%18,41418.4k1545.621283%45.621283%45.6%12,81012.8k1645.546218%45.546218%45.5%10,84010.8k1743.209260%43.209260%43.2%10,37810.4k1840.731207%40.731207%40.7%83,07783.1k1940.237017%40.237017%40.2%15,10915.1k2038.668410%38.668410%38.7%8,2822137.980784%37.980784%38.0%12,29412.3k2237.572221%37.572221%37.6%12,87612.9k2336.130128%36.130128%36.1%7,2302436.008024%36.008024%36.0%7,8982535.550232%35.550232%35.6%6,8262635.069154%35.069154%35.1%3,77834.780899%34.780899%34.8%13,437,26113.4M33.900282%33.900282%33.9%6,9762733.644618%33.644618%33.6%9,577,4379.58M33.487491%33.487491%33.5%7,6032832.546256%32.546256%32.5%550,613551k30.903052%30.903052%30.9%9,7702930.315023%30.315023%30.3%64,767,78764.8M29.462291%29.462291%29.5%16,22416.2k3029.333279%29.333279%29.3%2,595,9502.60M29.058562%29.058562%29.1%9,0163128.137320%28.137320%28.1%41,82541.8k28.131093%28.131093%28.1%6,7813228.042439%28.042439%28.0%12,07912.1k3327.287927%27.287927%27.3%9,3033426.349720%26.349720%26.3%272,786273k3524.895130%24.895130%24.9%5,4603622.559475%22.559475%22.6%27522.559475%22.559475%22.6%27521.774534%21.774534%21.8%5,1613721.735984%21.735984%21.7%14,11614.1k3821.568352%21.568352%21.6%10,75710.8k3921.227450%21.227450%21.2%4,7424020.159583%20.159583%20.2%1,23819.973749%19.973749%20.0%3,5004119.838894%19.838894%19.8%7,2904219.271814%19.271814%19.3%30718.214158%18.214158%18.2%5,5814316.978290%16.978290%17.0%5,1854415.721339%15.721339%15.7%4,0444515.372023%15.372023%15.4%11,26811.3k4614.443730%14.443730%14.4%5,3934711.708059%11.708059%11.7%3,0034810.315654%10.315654%10.3%2,085499.228151%9.228151%9.2%4,60950
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older with a bachelor's degree or higher..

Very Advanced Degrees by County Subdivision#22

Percent of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).
Scope: population of McDonald, selected other county subdivisions in Pennsylvania, and entities that contain McDonald
0%5%10%15%20%Count#Lower Merion TownshipLower MerionRadnor TownshipRadnorState CollegeMount Lebanon TownshipMt LebanonTredyffrin TownshipTredyffrinLower Makefield TownshipLower MakefieldCheltenham TownshipCheltenhamHaverford TownshipHaverfordPittsburghUpper Merion TownshipUpper MerionMcCandless TownshipMcCandlessNorthampton TownshipNorthamptonLower Macungie TownshipLower MacungieManheim TownshipManheimAbington TownshipAbingtonHampden TownshipHampdenMillcreek TownshipMillcreekCranberry TownshipCranberryMonroevilleRoss TownshipBethel ParkNortheastBethlehemMiddle AtlanticYork TownshipPhiladelphiaPittsburgh Metro AreaPittsburghLower Paxton TownshipLower PaxtonUnited States of AmericaUnited StatesMiddletown TownshipMiddletownPennsylvaniaShaler TownshipShalerWilliamsportSpring TownshipSpgLancasterHempfield TownshipHempfieldUpper Darby TownshipUpper DarbyHarrisburgPenn Hills TownshipPenn HlsWashington CountyWashingtonWarminster TownshipWarminsterScrantonBensalem TownshipBensalemNorth Huntingdon TownshipN HuntingdonAllentownErieZIP Code 15057ZIP 15057PlumNorristownFalls TownshipFallsRidley TownshipRidleyWilkes-BarreAltoonaBristol TownshipBristolYork715700Tract 715700McDonaldChesterReadingMcDonaldFort Cherry School DistrictFort Cherry23.473777%23.473777%23.5%9,332116.665646%16.665646%16.7%2,721216.164994%16.164994%16.2%2,030312.929250%12.929250%12.9%3,061412.252226%12.252226%12.3%2,559511.031691%11.031691%11.0%2,562610.078383%10.078383%10.1%2,53378.331301%8.331301%8.3%2,73387.432194%7.432194%7.4%15,15915.2k97.362223%7.362223%7.4%1,563106.966325%6.966325%7.0%1,446116.443374%6.443374%6.4%1,766126.206583%6.206583%6.2%1,367136.114890%6.114890%6.1%1,717145.997462%5.997462%6.0%2,363155.577016%5.577016%5.6%1,155164.703063%4.703063%4.7%1,766174.697157%4.697157%4.7%950184.440190%4.440190%4.4%951194.221834%4.221834%4.2%1,014204.105042%4.105042%4.1%977214.085016%4.085016%4.1%1,578,2061.58M4.062537%4.062537%4.1%1,385223.884861%3.884861%3.9%1,105,8831.11M3.780737%3.780737%3.8%778233.720350%3.720350%3.7%38,51538.5k243.600869%3.600869%3.6%60,91960.9k3.466589%3.466589%3.5%1,188253.336158%3.336158%3.3%7,127,6737.13M3.333436%3.333436%3.3%1,079263.299391%3.299391%3.3%291,991292k3.250661%3.250661%3.3%713272.750671%2.750671%2.8%482282.708192%2.708192%2.7%520292.514559%2.514559%2.5%924302.479836%2.479836%2.5%784312.458823%2.458823%2.5%1,354322.441174%2.441174%2.4%748332.356013%2.356013%2.4%731342.279241%2.279241%2.3%3,3881.999585%1.999585%2.0%482351.944901%1.944901%1.9%970361.827088%1.827088%1.8%787371.814658%1.814658%1.8%412381.607050%1.607050%1.6%1,178391.599864%1.599864%1.6%1,039401.596584%1.596584%1.6%1721.544151%1.544151%1.5%309411.383231%1.383231%1.4%309421.147582%1.147582%1.1%272431.025898%1.025898%1.0%225440.940792%0.940792%0.9%242450.903762%0.903762%0.9%276460.838288%0.838288%0.8%313470.814847%0.814847%0.8%209480.574241%0.574241%0.6%70.574241%0.574241%0.6%70.549179%0.549179%0.5%111490.454500%0.454500%0.5%227500.439422%0.439422%0.4%70.407100%0.407100%0.4%25
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).

Under-Education Sex Ratio by County Subdivision#23

Percentage more likely men are than women to not have a high school diploma (or equivalent) among people aged 25 years and older.
Scope: population of McDonald, selected other county subdivisions in Pennsylvania, and entities that contain McDonald
Female
Male
2x1x0x1x2xFM#RadnorShalerAltoonaTract 715700McDonaldMcDonaldMt LebanonCheltenhamFort CherryFallsHempfieldBristolChesterWilliamsportUpper DarbyHaverfordNorristownSpgManheimUnited StatesRidleyWilkes-BarrePennsylvaniaPhiladelphiaNortheastHarrisburgZIP 15057WashingtonYorkLancasterScrantonLower PaxtonMiddle AtlanticAllentownReadingEriePittsburghPlumLower MerionLower MacungieMillcreekPenn HlsLower MakefieldAbingtonMiddletownPittsburghUpper MerionBensalemBethlehemBethel ParkMonroevilleWarminsterHampdenMcCandlessN HuntingdonRoss TownshipNorthamptonYork TownshipState CollegeTredyffrinCranberry-1.000000x-1.000000x2.099713x2.099713x2.10x1.674%1.67%3.514%3.51%1-1.000000x-1.000000x1.552208x1.552208x1.55x4.210%4.21%6.535%6.53%2-1.000000x-1.000000x1.377463x1.377463x1.38x9.131%9.13%12.578%12.6%3-1.000000x-1.000000x1.331183x1.331183x1.33x10.016%10.0%13.333%13.3%-1.000000x-1.000000x1.331183x1.331183x1.33x10.016%10.0%13.333%13.3%-1.000000x-1.000000x1.314658x1.314658x1.31x12.088%12.1%15.891%15.9%-1.000000x-1.000000x1.310561x1.310561x1.31x1.685%1.69%2.208%2.21%4-1.000000x-1.000000x1.302837x1.302837x1.30x3.987%3.99%5.194%5.19%5-1.000000x-1.000000x1.290542x1.290542x1.29x8.846%8.85%11.416%11.4%-1.000000x-1.000000x1.245559x1.245559x1.25x6.496%6.50%8.092%8.09%6-1.000000x-1.000000x1.243946x1.243946x1.24x6.384%6.38%7.942%7.94%7-1.000000x-1.000000x1.234755x1.234755x1.23x10.818%10.8%13.358%13.4%8-1.000000x-1.000000x1.213737x1.213737x1.21x18.847%18.8%22.876%22.9%9-1.000000x-1.000000x1.200927x1.200927x1.20x11.676%11.7%14.021%14.0%10-1.000000x-1.000000x1.170881x1.170881x1.17x9.690%9.69%11.346%11.3%11-1.000000x-1.000000x1.163929x1.163929x1.16x2.997%3.00%3.489%3.49%12-1.000000x-1.000000x1.149116x1.149116x1.15x18.104%18.1%20.803%20.8%13-1.000000x-1.000000x1.138058x1.138058x1.14x5.830%5.83%6.635%6.64%14-1.000000x-1.000000x1.128376x1.128376x1.13x7.656%7.66%8.639%8.64%15-1.000000x-1.000000x1.109070x1.109070x1.11x12.369%12.4%13.719%13.7%-1.000000x-1.000000x1.107613x1.107613x1.11x7.776%7.78%8.613%8.61%16-1.000000x-1.000000x1.098731x1.098731x1.10x16.045%16.0%17.629%17.6%17-1.000000x-1.000000x1.094514x1.094514x1.09x10.006%10.0%10.952%11.0%-1.000000x-1.000000x1.090163x1.090163x1.09x16.700%16.7%18.206%18.2%18-1.000000x-1.000000x1.074442x1.074442x1.07x11.216%11.2%12.051%12.1%-1.000000x-1.000000x1.074404x1.074404x1.07x20.537%20.5%22.065%22.1%19-1.000000x-1.000000x1.073596x1.073596x1.07x6.866%6.87%7.372%7.37%-1.000000x-1.000000x1.071245x1.071245x1.07x7.973%7.97%8.541%8.54%-1.000000x-1.000000x1.071003x1.071003x1.07x20.882%20.9%22.365%22.4%20-1.000000x-1.000000x1.066005x1.066005x1.07x23.550%23.6%25.105%25.1%21-1.000000x-1.000000x1.060972x1.060972x1.06x14.714%14.7%15.611%15.6%22-1.000000x-1.000000x1.060439x1.060439x1.06x6.073%6.07%6.440%6.44%23-1.000000x-1.000000x1.059800x1.059800x1.06x11.972%12.0%12.688%12.7%-1.000000x-1.000000x1.046856x1.046856x1.05x21.252%21.3%22.248%22.2%24-1.000000x-1.000000x1.035486x1.035486x1.04x34.011%34.0%35.218%35.2%25-1.000000x-1.000000x1.033360x1.033360x1.03x12.706%12.7%13.130%13.1%26-1.000000x-1.000000x1.015146x1.015146x1.02x7.080%7.08%7.187%7.19%-1.000000x-1.000000x1.006305x1.006305x1.01x4.823%4.82%4.853%4.85%27-1.000000x-1.000000x1.004780x1.004780x1.00x2.527%2.53%2.540%2.54%28-1.003763x-1.003763x1.00x1.000000x1.000000x6.031%6.03%6.009%6.01%29-1.004148x-1.004148x1.00x1.000000x1.000000x5.209%5.21%5.187%5.19%30-1.008684x-1.008684x1.01x1.000000x1.000000x6.792%6.79%6.733%6.73%31-1.023727x-1.023727x1.02x1.000000x1.000000x1.977%1.98%1.931%1.93%32-1.035622x-1.035622x1.04x1.000000x1.000000x5.160%5.16%4.982%4.98%33-1.052588x-1.052588x1.05x1.000000x1.000000x5.307%5.31%5.042%5.04%34-1.054084x-1.054084x1.05x1.000000x1.000000x8.249%8.25%7.826%7.83%35-1.058332x-1.058332x1.06x1.000000x1.000000x4.754%4.75%4.492%4.49%36-1.071908x-1.071908x1.07x1.000000x1.000000x8.793%8.79%8.203%8.20%37-1.127042x-1.127042x1.13x1.000000x1.000000x13.260%13.3%11.765%11.8%38-1.132717x-1.132717x1.13x1.000000x1.000000x4.563%4.56%4.029%4.03%39-1.138629x-1.138629x1.14x1.000000x1.000000x5.164%5.16%4.535%4.54%40-1.198302x-1.198302x1.20x1.000000x1.000000x10.561%10.6%8.813%8.81%41-1.201433x-1.201433x1.20x1.000000x1.000000x6.467%6.47%5.383%5.38%42-1.270679x-1.270679x1.27x1.000000x1.000000x3.640%3.64%2.864%2.86%43-1.291642x-1.291642x1.29x1.000000x1.000000x4.505%4.51%3.488%3.49%44-1.296113x-1.296113x1.30x1.000000x1.000000x6.295%6.29%4.856%4.86%45-1.483006x-1.483006x1.48x1.000000x1.000000x3.794%3.79%2.558%2.56%46-1.543785x-1.543785x1.54x1.000000x1.000000x10.576%10.6%6.851%6.85%47-1.583597x-1.583597x1.58x1.000000x1.000000x3.691%3.69%2.330%2.33%48-1.864980x-1.864980x1.86x1.000000x1.000000x2.352%2.35%1.261%1.26%49-2.300755x-2.300755x2.30x1.000000x1.000000x4.416%4.42%1.919%1.92%50
F percentage of females in category
M percentage of males in category
# rank of county subdivision out of 50 by male-to-female sex ratio

Over-Education Sex Ratio by County Subdivision#24

Percentage more likely men are than women to have a professional or doctorate degree (e.g., MBA, PhD, or MD) among people aged 25 years and older.
Scope: population of McDonald, selected other county subdivisions in Pennsylvania, and entities that contain McDonald
Female
Male
0x5x10xFM#McDonaldTract 715700McDonaldFallsSpgZIP 15057ChesterLower PaxtonHampdenMt LebanonAltoonaHempfieldFort CherryMillcreekYorkN HuntingdonLower MerionCranberryNorthamptonCheltenhamAllentownYork TownshipHarrisburgWilliamsportBethlehemUpper MerionLower MacungieScrantonAbingtonRoss TownshipRadnorMcCandlessTredyffrinState CollegeReadingWashingtonPittsburghPennsylvaniaHaverfordManheimMonroevilleUpper DarbyMiddletownUnited StatesLower MakefieldMiddle AtlanticNortheastRidleyPittsburghPhiladelphiaWilkes-BarreBethel ParkShalerErieBensalemWarminsterPlumBristolPenn HlsLancasterNorristown-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%0.904%0.90%-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%1.167%1.17%-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%1.167%1.17%-1.000000x-1.000000x4.527755x4.527755x4.53x0.431%0.43%1.951%1.95%1-1.000000x-1.000000x4.463017x4.463017x4.46x1.023%1.02%4.566%4.57%2-1.000000x-1.000000x3.760285x3.760285x3.76x0.670%0.67%2.519%2.52%-1.000000x-1.000000x2.925530x2.925530x2.93x0.289%0.29%0.845%0.84%3-1.000000x-1.000000x2.577340x2.577340x2.58x1.995%2.00%5.142%5.14%4-1.000000x-1.000000x2.391170x2.391170x2.39x3.375%3.37%8.069%8.07%5-1.000000x-1.000000x2.330320x2.330320x2.33x7.964%7.96%18.560%18.6%6-1.000000x-1.000000x2.275075x2.275075x2.28x0.566%0.57%1.288%1.29%7-1.000000x-1.000000x2.256635x2.256635x2.26x1.534%1.53%3.462%3.46%8-1.000000x-1.000000x2.131238x2.131238x2.13x0.260%0.26%0.554%0.55%-1.000000x-1.000000x2.131062x2.131062x2.13x3.068%3.07%6.537%6.54%9-1.000000x-1.000000x2.096978x2.096978x2.10x0.531%0.53%1.114%1.11%10-1.000000x-1.000000x2.038929x2.038929x2.04x1.211%1.21%2.469%2.47%11-1.000000x-1.000000x2.019563x2.019563x2.02x15.984%16.0%32.281%32.3%12-1.000000x-1.000000x1.978141x1.978141x1.98x3.176%3.18%6.283%6.28%13-1.000000x-1.000000x1.977378x1.977378x1.98x4.409%4.41%8.719%8.72%14-1.000000x-1.000000x1.967952x1.967952x1.97x6.982%6.98%13.741%13.7%15-1.000000x-1.000000x1.966185x1.966185x1.97x1.102%1.10%2.166%2.17%16-1.000000x-1.000000x1.963703x1.963703x1.96x2.593%2.59%5.092%5.09%17-1.000000x-1.000000x1.944570x1.944570x1.94x1.712%1.71%3.329%3.33%18-1.000000x-1.000000x1.936361x1.936361x1.94x1.892%1.89%3.664%3.66%19-1.000000x-1.000000x1.922101x1.922101x1.92x2.827%2.83%5.434%5.43%20-1.000000x-1.000000x1.884402x1.884402x1.88x5.140%5.14%9.687%9.69%21-1.000000x-1.000000x1.837949x1.837949x1.84x4.437%4.44%8.155%8.15%22-1.000000x-1.000000x1.825579x1.825579x1.83x1.392%1.39%2.541%2.54%23-1.000000x-1.000000x1.766814x1.766814x1.77x4.407%4.41%7.786%7.79%24-1.000000x-1.000000x1.750758x1.750758x1.75x3.143%3.14%5.503%5.50%25-1.000000x-1.000000x1.709689x1.709689x1.71x12.575%12.6%21.499%21.5%26-1.000000x-1.000000x1.703524x1.703524x1.70x5.237%5.24%8.922%8.92%27-1.000000x-1.000000x1.674402x1.674402x1.67x9.300%9.30%15.572%15.6%28-1.000000x-1.000000x1.661960x1.661960x1.66x11.969%12.0%19.892%19.9%29-1.000000x-1.000000x1.652203x1.652203x1.65x0.347%0.35%0.573%0.57%30-1.000000x-1.000000x1.652123x1.652123x1.65x1.736%1.74%2.868%2.87%-1.000000x-1.000000x1.634496x1.634496x1.63x2.765%2.77%4.520%4.52%-1.000000x-1.000000x1.629829x1.629829x1.63x2.534%2.53%4.130%4.13%-1.000000x-1.000000x1.591202x1.591202x1.59x6.501%6.50%10.344%10.3%31-1.000000x-1.000000x1.573118x1.573118x1.57x4.820%4.82%7.582%7.58%32-1.000000x-1.000000x1.556689x1.556689x1.56x3.522%3.52%5.482%5.48%33-1.000000x-1.000000x1.529988x1.529988x1.53x1.971%1.97%3.015%3.02%34-1.000000x-1.000000x1.528639x1.528639x1.53x2.662%2.66%4.070%4.07%35-1.000000x-1.000000x1.526215x1.526215x1.53x2.660%2.66%4.060%4.06%-1.000000x-1.000000x1.504436x1.504436x1.50x8.883%8.88%13.364%13.4%36-1.000000x-1.000000x1.502828x1.502828x1.50x3.134%3.13%4.710%4.71%-1.000000x-1.000000x1.486326x1.486326x1.49x3.316%3.32%4.929%4.93%-1.000000x-1.000000x1.473488x1.473488x1.47x0.837%0.84%1.233%1.23%37-1.000000x-1.000000x1.398688x1.398688x1.40x6.228%6.23%8.711%8.71%38-1.000000x-1.000000x1.341930x1.341930x1.34x3.216%3.22%4.316%4.32%39-1.000000x-1.000000x1.284280x1.284280x1.28x0.830%0.83%1.066%1.07%40-1.000000x-1.000000x1.260941x1.260941x1.26x3.662%3.66%4.617%4.62%41-1.000000x-1.000000x1.215685x1.215685x1.22x2.942%2.94%3.577%3.58%42-1.000000x-1.000000x1.210953x1.210953x1.21x1.452%1.45%1.759%1.76%43-1.000000x-1.000000x1.097790x1.097790x1.10x1.744%1.74%1.915%1.91%44-1.000000x-1.000000x1.069450x1.069450x1.07x1.937%1.94%2.072%2.07%45-1.072148x-1.072148x1.07x1.000000x1.000000x1.595%1.59%1.488%1.49%46-1.167430x-1.167430x1.17x1.000000x1.000000x0.902%0.90%0.772%0.77%47-1.180307x-1.180307x1.18x1.000000x1.000000x2.532%2.53%2.145%2.15%48-1.211423x-1.211423x1.21x1.000000x1.000000x2.748%2.75%2.269%2.27%49-1.361579x-1.361579x1.36x1.000000x1.000000x1.595%1.60%1.172%1.17%50
F percentage of females in category
M percentage of males in category
# rank of county subdivision out of 50 by male-to-female sex ratio

Educational Attainment by County Subdivision in the Northeast

There are 5,785 county subdivisions in the Northeast. This section compares McDonald to the 50 most populous county subdivisions in the Northeast and to those entities that contain or substantially overlap with McDonald. The least populous of the compared county subdivisions has a population of 91,133.

No H.S. Diploma by County Subdivision#25

Percent of population 25 years of age and older without a high school diploma (or equivalent).
Scope: population of McDonald, selected other county subdivisions in the Northeast, and entities that contain McDonald
0%5%10%15%20%25%Count#BronxPatersonTown of HartfordHartfordNew BedfordElizabethNewarkProvidenceTown of BridgeportBridgeportSpringfieldAllentownTown of WaterburyWaterburyLynnLowellBrooklynQueensRochesterSyracuseBrocktonTown of RamapoRamapoPhiladelphiaYonkersBuffaloTown of New HavenNew HvnLakewood TownshipLakewoodWorcesterTown of IslipBostonJersey CityMcDonaldUnited States of AmericaUnited StatesManhattanErieManchesterTown of BabylonBabylonMiddle Atlantic715700Tract 715700McDonaldNortheastStaten IslandQuincyTown of StamfordStamfordPennsylvaniaTown of HempsteadHempsteadAlbanyFort Cherry School DistrictFort CherryWoodbridge TownshipWoodbridgeTown of North HempsteadN HempsteadTown of BrookhavenBrookhavenWashington CountyWashingtonPittsburghEdison TownshipEdisonToms River TownshipToms RivTown of GreeceGreeceTown of HuntingtonHuntingtonTown of GreenburghGreenburghPittsburgh Metro AreaPittsburghZIP Code 15057ZIP 15057CambridgeTown of Oyster BayOyster BayTown of AmherstAmherstTown of SmithtownSmithtown28.837398%28.837398%28.8%261,022261k128.603478%28.603478%28.6%26,13726.1k227.891028%27.891028%27.9%20,66020.7k327.365251%27.365251%27.4%17,71917.7k426.935430%26.935430%26.9%21,72121.7k526.717922%26.717922%26.7%47,54047.5k623.799210%23.799210%23.8%25,05225.1k723.641452%23.641452%23.6%22,13122.1k822.848722%22.848722%22.8%21,31921.3k921.725192%21.725192%21.7%15,92515.9k1020.889554%20.889554%20.9%14,52214.5k1120.689714%20.689714%20.7%12,22712.2k1220.275184%20.275184%20.3%14,22014.2k1320.017506%20.017506%20.0%351,046351k1419.344706%19.344706%19.3%315,505316k1519.239011%19.239011%19.2%25,40825.4k1619.000219%19.000219%19.0%16,47316.5k1718.575453%18.575453%18.6%11,40711.4k1817.423749%17.423749%17.4%12,58512.6k1917.390838%17.390838%17.4%180,039180k2016.804756%16.804756%16.8%22,98023.0k2116.749688%16.749688%16.7%27,74127.7k2216.300427%16.300427%16.3%13,24113.2k2316.179368%16.179368%16.2%7,1442415.555125%15.555125%15.6%18,48418.5k2514.649584%14.649584%14.6%32,58832.6k2614.325556%14.325556%14.3%63,64263.6k2714.106563%14.106563%14.1%25,82725.8k2813.935970%13.935970%13.9%22213.020590%13.020590%13.0%27,818,38027.8M12.996284%12.996284%13.0%160,845161k2912.909782%12.909782%12.9%8,3843012.589518%12.589518%12.6%9,6163112.329428%12.329428%12.3%18,13418.1k3212.313400%12.313400%12.3%3,505,1913.51M11.648893%11.648893%11.6%14211.648893%11.648893%11.6%14211.614335%11.614335%11.6%4,487,0854.49M11.118888%11.118888%11.1%36,06336.1k3311.019146%11.019146%11.0%7,6953410.953993%10.953993%11.0%9,8073510.459911%10.459911%10.5%925,686926k10.384134%10.384134%10.4%54,23054.2k3610.256196%10.256196%10.3%6,1453710.128644%10.128644%10.1%6229.010786%9.010786%9.0%6,625388.911497%8.911497%8.9%14,26914.3k398.603165%8.603165%8.6%28,07628.1k408.245765%8.245765%8.2%12,25712.3k8.043576%8.043576%8.0%16,40616.4k417.965713%7.965713%8.0%5,836427.603506%7.603506%7.6%4,953437.434661%7.434661%7.4%5,274447.370929%7.370929%7.4%10,45510.5k457.208489%7.208489%7.2%4,660467.130926%7.130926%7.1%120,640121k7.119651%7.119651%7.1%7675.858411%5.858411%5.9%4,275475.758981%5.758981%5.8%11,95012.0k484.592814%4.592814%4.6%3,835494.565854%4.565854%4.6%3,74450
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older without a high school diploma (or equivalent).

Bachelor's Degrees by County Subdivision#26

Percent of population 25 years of age and older with a bachelor's degree or higher..
Scope: population of McDonald, selected other county subdivisions in the Northeast, and entities that contain McDonald
0%20%40%60%Count#CambridgeTown of GreenburghGreenburghManhattanEdison TownshipEdisonTown of AmherstAmherstTown of North HempsteadN HempsteadTown of HuntingtonHuntingtonTown of Oyster BayOyster BayTown of StamfordStamfordBostonTown of SmithtownSmithtownJersey CityQuincyPittsburghTown of HempsteadHempsteadAlbanyZIP Code 15057ZIP 15057NortheastWoodbridge TownshipWoodbridgeTown of New HavenNew HvnBrooklynMiddle AtlanticPittsburgh Metro AreaPittsburghTown of RamapoRamapoTown of BrookhavenBrookhavenYonkersToms River TownshipToms RivStaten IslandQueensUnited States of AmericaUnited StatesWorcesterProvidencePennsylvaniaTown of GreeceGreeceWashington CountyWashingtonManchesterTown of IslipLakewood TownshipLakewoodSyracusePhiladelphiaTown of BabylonBabylonBuffaloRochester715700Tract 715700McDonaldLowellErieFort Cherry School DistrictFort CherryLynnMcDonaldBronxTown of BridgeportBridgeportSpringfieldBrocktonTown of HartfordHartfordNew BedfordAllentownTown of WaterburyWaterburyNewarkElizabethPaterson74.864332%74.864332%74.9%54,63054.6k161.467067%61.467067%61.5%39,73639.7k260.434640%60.434640%60.4%747,953748k354.244922%54.244922%54.2%39,74239.7k454.117365%54.117365%54.1%45,18845.2k553.266008%53.266008%53.3%85,28985.3k650.346515%50.346515%50.3%71,41271.4k748.123874%48.123874%48.1%99,85899.9k847.268483%47.268483%47.3%42,31942.3k946.377869%46.377869%46.4%206,036206k1046.287805%46.287805%46.3%37,95638.0k1144.105197%44.105197%44.1%80,75080.8k1242.147695%42.147695%42.1%29,43329.4k1340.731207%40.731207%40.7%83,07783.1k1438.767308%38.767308%38.8%202,458202k1537.277810%37.277810%37.3%22,33522.3k1635.069154%35.069154%35.1%3,77834.780899%34.780899%34.8%13,437,26113.4M34.631340%34.631340%34.6%25,46225.5k1734.235698%34.235698%34.2%27,81027.8k1834.081468%34.081468%34.1%597,685598k1933.644618%33.644618%33.6%9,577,4379.58M32.546256%32.546256%32.5%550,613551k32.475875%32.475875%32.5%23,45723.5k2032.119689%32.119689%32.1%104,821105k2132.032147%32.032147%32.0%43,80343.8k2231.493222%31.493222%31.5%20,51520.5k2331.359684%31.359684%31.4%101,712102k2430.595789%30.595789%30.6%499,006499k2530.315023%30.315023%30.3%64,767,78764.8M29.720018%29.720018%29.7%35,31635.3k2629.442164%29.442164%29.4%30,99231.0k2729.333279%29.333279%29.3%2,595,9502.60M28.513632%28.513632%28.5%20,22720.2k2828.137320%28.137320%28.1%41,82541.8k27.975544%27.975544%28.0%21,36821.4k2927.874579%27.874579%27.9%62,00762.0k3026.896161%26.896161%26.9%11,87611.9k3126.804231%26.804231%26.8%23,23923.2k3226.349720%26.349720%26.3%272,786273k3325.418993%25.418993%25.4%37,38637.4k3425.263101%25.263101%25.3%41,84141.8k3523.661076%23.661076%23.7%31,24831.2k3622.559475%22.559475%22.6%27522.559475%22.559475%22.6%27522.302702%22.302702%22.3%15,64215.6k3721.735984%21.735984%21.7%14,11614.1k3820.159583%20.159583%20.2%1,23819.566137%19.566137%19.6%11,56311.6k3919.271814%19.271814%19.3%30719.131504%19.131504%19.1%173,169173k4017.869695%17.869695%17.9%16,72816.7k4117.800761%17.800761%17.8%16,60916.6k4217.271084%17.271084%17.3%10,60610.6k4316.703567%16.703567%16.7%12,37312.4k4415.806950%15.806950%15.8%10,23510.2k4515.372023%15.372023%15.4%11,26811.3k4615.070917%15.070917%15.1%10,47710.5k4713.654578%13.654578%13.7%24,29624.3k4811.763247%11.763247%11.8%9,4864910.403055%10.403055%10.4%9,50650
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older with a bachelor's degree or higher..

Very Advanced Degrees by County Subdivision#27

Percent of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).
Scope: population of McDonald, selected other county subdivisions in the Northeast, and entities that contain McDonald
0%5%10%15%Count#CambridgeTown of GreenburghGreenburghManhattanTown of North HempsteadN HempsteadTown of AmherstAmherstTown of New HavenNew HvnTown of HuntingtonHuntingtonPittsburghBostonTown of Oyster BayOyster BayTown of StamfordStamfordProvidenceTown of SmithtownSmithtownAlbanyEdison TownshipEdisonTown of HempsteadHempsteadJersey CitySyracuseNortheastTown of RamapoRamapoTown of BrookhavenBrookhavenMiddle AtlanticPhiladelphiaQuincyPittsburgh Metro AreaPittsburghWorcesterYonkersBrooklynUnited States of AmericaUnited StatesPennsylvaniaBuffaloStaten IslandQueensToms River TownshipToms RivRochesterTown of IslipWashington CountyWashingtonTown of HartfordHartfordTown of GreeceGreeceWoodbridge TownshipWoodbridgeLakewood TownshipLakewoodLowellManchesterTown of BridgeportBridgeportBronxAllentownTown of BabylonBabylonErieZIP Code 15057ZIP 15057SpringfieldLynnTown of WaterburyWaterburyNew BedfordNewarkElizabethBrockton715700Tract 715700McDonaldPatersonMcDonaldFort Cherry School DistrictFort Cherry19.696596%19.696596%19.7%14,37314.4k111.932680%11.932680%11.9%7,714210.788423%10.788423%10.8%133,520134k310.319825%10.319825%10.3%16,52416.5k49.511377%9.511377%9.5%7,94258.607551%8.607551%8.6%6,99267.591599%7.591599%7.6%10,76810.8k77.432194%7.432194%7.4%15,15915.2k87.340604%7.340604%7.3%32,61132.6k96.073676%6.073676%6.1%12,60312.6k105.972366%5.972366%6.0%5,347115.846253%5.846253%5.8%6,154125.571951%5.571951%5.6%4,569135.285822%5.285822%5.3%3,167145.170343%5.170343%5.2%3,788154.441262%4.441262%4.4%23,19423.2k164.296365%4.296365%4.3%7,866174.250337%4.250337%4.3%3,685184.085016%4.085016%4.1%1,578,2061.58M4.063465%4.063465%4.1%2,935193.952259%3.952259%4.0%12,89812.9k203.884861%3.884861%3.9%1,105,8831.11M3.720350%3.720350%3.7%38,51538.5k213.698824%3.698824%3.7%2,583223.600869%3.600869%3.6%60,91960.9k3.571519%3.571519%3.6%4,244233.426766%3.426766%3.4%4,686243.384967%3.384967%3.4%59,36259.4k253.336158%3.336158%3.3%7,127,6737.13M3.299391%3.299391%3.3%291,991292k3.202492%3.202492%3.2%5,304263.037245%3.037245%3.0%9,851272.756960%2.756960%2.8%44,96545.0k282.735604%2.735604%2.7%1,782292.719873%2.719873%2.7%3,592302.384356%2.384356%2.4%5,304312.279241%2.279241%2.3%3,3882.259902%2.259902%2.3%1,674322.249852%2.249852%2.2%1,596332.147627%2.147627%2.1%1,579342.040539%2.040539%2.0%901351.961931%1.961931%2.0%1,376361.813278%1.813278%1.8%1,385371.680358%1.680358%1.7%1,573381.664253%1.664253%1.7%15,06415.1k391.607050%1.607050%1.6%1,178401.603220%1.603220%1.6%2,358411.599864%1.599864%1.6%1,039421.596584%1.596584%1.6%1721.501527%1.501527%1.5%1,401431.189570%1.189570%1.2%703441.165166%1.165166%1.2%810451.153668%1.153668%1.2%747461.070628%1.070628%1.1%1,905471.051574%1.051574%1.1%848481.035679%1.035679%1.0%636490.574241%0.574241%0.6%70.574241%0.574241%0.6%70.572354%0.572354%0.6%523500.439422%0.439422%0.4%70.407100%0.407100%0.4%25
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).

Under-Education Sex Ratio by County Subdivision#28

Percentage more likely men are than women to not have a high school diploma (or equivalent) among people aged 25 years and older.
Scope: population of McDonald, selected other county subdivisions in the Northeast, and entities that contain McDonald
Female
Male
1x0x1xFM#Tract 715700McDonaldMcDonaldFort CherryStamfordGreenburghSpringfieldNewarkGreeceRamapoBrookhavenBridgeportNew BedfordWorcesterUnited StatesTown of IslipManchesterPennsylvaniaRochesterHempsteadPhiladelphiaHuntingtonNew HvnYonkersSyracuseElizabethNortheastZIP 15057WashingtonMiddle AtlanticProvidenceBabylonN HempsteadToms RivWaterburyAllentownLynnHartfordErieBronxLakewoodBrooklynPatersonPittsburghStaten IslandAlbanyBrocktonBostonQueensManhattanBuffaloPittsburghOyster BayLowellWoodbridgeJersey CityQuincySmithtownAmherstCambridgeEdison-1.000000x-1.000000x1.331183x1.331183x1.33x10.016%10.0%13.333%13.3%-1.000000x-1.000000x1.331183x1.331183x1.33x10.016%10.0%13.333%13.3%-1.000000x-1.000000x1.314658x1.314658x1.31x12.088%12.1%15.891%15.9%-1.000000x-1.000000x1.290542x1.290542x1.29x8.846%8.85%11.416%11.4%-1.000000x-1.000000x1.289374x1.289374x1.29x9.609%9.61%12.390%12.4%1-1.000000x-1.000000x1.269590x1.269590x1.27x6.408%6.41%8.136%8.14%2-1.000000x-1.000000x1.257718x1.257718x1.26x20.468%20.5%25.743%25.7%3-1.000000x-1.000000x1.160031x1.160031x1.16x24.796%24.8%28.764%28.8%4-1.000000x-1.000000x1.148263x1.148263x1.15x6.949%6.95%7.980%7.98%5-1.000000x-1.000000x1.130956x1.130956x1.13x16.378%16.4%18.523%18.5%6-1.000000x-1.000000x1.130425x1.130425x1.13x8.092%8.09%9.147%9.15%7-1.000000x-1.000000x1.126520x1.126520x1.13x22.316%22.3%25.139%25.1%8-1.000000x-1.000000x1.111286x1.111286x1.11x26.024%26.0%28.920%28.9%9-1.000000x-1.000000x1.110069x1.110069x1.11x14.771%14.8%16.397%16.4%10-1.000000x-1.000000x1.109070x1.109070x1.11x12.369%12.4%13.719%13.7%-1.000000x-1.000000x1.102369x1.102369x1.10x13.961%14.0%15.390%15.4%11-1.000000x-1.000000x1.097386x1.097386x1.10x12.006%12.0%13.176%13.2%12-1.000000x-1.000000x1.094514x1.094514x1.09x10.006%10.0%10.952%11.0%-1.000000x-1.000000x1.092586x1.092586x1.09x18.427%18.4%20.133%20.1%13-1.000000x-1.000000x1.092101x1.092101x1.09x9.951%9.95%10.868%10.9%14-1.000000x-1.000000x1.090163x1.090163x1.09x16.700%16.7%18.206%18.2%15-1.000000x-1.000000x1.086755x1.086755x1.09x7.076%7.08%7.690%7.69%16-1.000000x-1.000000x1.085150x1.085150x1.09x15.699%15.7%17.035%17.0%17-1.000000x-1.000000x1.083417x1.083417x1.08x16.184%16.2%17.534%17.5%18-1.000000x-1.000000x1.079690x1.079690x1.08x18.321%18.3%19.780%19.8%19-1.000000x-1.000000x1.077654x1.077654x1.08x25.951%26.0%27.966%28.0%20-1.000000x-1.000000x1.074442x1.074442x1.07x11.216%11.2%12.051%12.1%-1.000000x-1.000000x1.073596x1.073596x1.07x6.866%6.87%7.372%7.37%-1.000000x-1.000000x1.071245x1.071245x1.07x7.973%7.97%8.541%8.54%-1.000000x-1.000000x1.059800x1.059800x1.06x11.972%12.0%12.688%12.7%-1.000000x-1.000000x1.056204x1.056204x1.06x23.167%23.2%24.469%24.5%21-1.000000x-1.000000x1.052862x1.052862x1.05x12.028%12.0%12.664%12.7%22-1.000000x-1.000000x1.049383x1.049383x1.05x8.711%8.71%9.141%9.14%23-1.000000x-1.000000x1.047109x1.047109x1.05x7.436%7.44%7.786%7.79%24-1.000000x-1.000000x1.047067x1.047067x1.05x20.442%20.4%21.404%21.4%25-1.000000x-1.000000x1.046856x1.046856x1.05x21.252%21.3%22.248%22.2%26-1.000000x-1.000000x1.040899x1.040899x1.04x20.290%20.3%21.120%21.1%27-1.000000x-1.000000x1.039426x1.039426x1.04x27.388%27.4%28.468%28.5%28-1.000000x-1.000000x1.033360x1.033360x1.03x12.706%12.7%13.130%13.1%29-1.000000x-1.000000x1.030539x1.030539x1.03x28.448%28.4%29.316%29.3%30-1.000000x-1.000000x1.022095x1.022095x1.02x16.005%16.0%16.358%16.4%31-1.000000x-1.000000x1.018960x1.018960x1.02x19.845%19.8%20.221%20.2%32-1.000000x-1.000000x1.016806x1.016806x1.02x28.378%28.4%28.855%28.9%33-1.000000x-1.000000x1.015146x1.015146x1.02x7.080%7.08%7.187%7.19%-1.000000x-1.000000x1.004211x1.004211x1.00x11.097%11.1%11.144%11.1%34-1.015553x-1.015553x1.02x1.000000x1.000000x10.330%10.3%10.172%10.2%35-1.016098x-1.016098x1.02x1.000000x1.000000x18.712%18.7%18.416%18.4%36-1.022333x-1.022333x1.02x1.000000x1.000000x14.476%14.5%14.159%14.2%37-1.027762x-1.027762x1.03x1.000000x1.000000x19.596%19.6%19.067%19.1%38-1.044246x-1.044246x1.04x1.000000x1.000000x13.260%13.3%12.698%12.7%39-1.048932x-1.048932x1.05x1.000000x1.000000x17.120%17.1%16.322%16.3%40-1.054084x-1.054084x1.05x1.000000x1.000000x8.249%8.25%7.826%7.83%41-1.065498x-1.065498x1.07x1.000000x1.000000x5.933%5.93%5.568%5.57%42-1.082021x-1.082021x1.08x1.000000x1.000000x21.048%21.0%19.452%19.5%43-1.092845x-1.092845x1.09x1.000000x1.000000x9.423%9.42%8.623%8.62%44-1.106483x-1.106483x1.11x1.000000x1.000000x14.808%14.8%13.383%13.4%45-1.113634x-1.113634x1.11x1.000000x1.000000x11.579%11.6%10.397%10.4%46-1.188832x-1.188832x1.19x1.000000x1.000000x4.943%4.94%4.158%4.16%47-1.191205x-1.191205x1.19x1.000000x1.000000x4.962%4.96%4.165%4.17%48-1.302480x-1.302480x1.30x1.000000x1.000000x6.597%6.60%5.065%5.06%49-1.377298x-1.377298x1.38x1.000000x1.000000x9.172%9.17%6.659%6.66%50
F percentage of females in category
M percentage of males in category
# rank of county subdivision out of 50 by male-to-female sex ratio

Over-Education Sex Ratio by County Subdivision#29

Percentage more likely men are than women to have a professional or doctorate degree (e.g., MBA, PhD, or MD) among people aged 25 years and older.
Scope: population of McDonald, selected other county subdivisions in the Northeast, and entities that contain McDonald
Female
Male
0x5x10xFM#McDonaldTract 715700McDonaldZIP 15057LakewoodFort CherryAllentownToms RivWoodbridgeSmithtownHuntingtonBrookhavenAmherstStamfordOyster BayGreenburghManchesterWashingtonPittsburghPennsylvaniaElizabethBuffaloNew BedfordN HempsteadSyracuseEdisonUnited StatesMiddle AtlanticHempsteadNortheastRamapoAlbanyGreeceHartfordQuincyRochesterPittsburghPhiladelphiaProvidenceBridgeportQueensCambridgeLowellBrooklynManhattanPatersonStaten IslandBostonSpringfieldWaterburyErieLynnBronxTown of IslipJersey CityBabylonNew HvnYonkersNewarkWorcesterBrockton-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%0.904%0.90%-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%1.167%1.17%-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%1.167%1.17%-1.000000x-1.000000x3.760285x3.760285x3.76x0.670%0.67%2.519%2.52%-1.000000x-1.000000x2.794240x2.794240x2.79x1.082%1.08%3.024%3.02%1-1.000000x-1.000000x2.131238x2.131238x2.13x0.260%0.26%0.554%0.55%-1.000000x-1.000000x1.966185x1.966185x1.97x1.102%1.10%2.166%2.17%2-1.000000x-1.000000x1.866111x1.866111x1.87x1.933%1.93%3.608%3.61%3-1.000000x-1.000000x1.800589x1.800589x1.80x1.521%1.52%2.738%2.74%4-1.000000x-1.000000x1.796128x1.796128x1.80x4.030%4.03%7.238%7.24%5-1.000000x-1.000000x1.783986x1.783986x1.78x5.517%5.52%9.842%9.84%6-1.000000x-1.000000x1.779979x1.779979x1.78x2.869%2.87%5.106%5.11%7-1.000000x-1.000000x1.771370x1.771370x1.77x7.007%7.01%12.411%12.4%8-1.000000x-1.000000x1.765297x1.765297x1.77x4.359%4.36%7.695%7.69%9-1.000000x-1.000000x1.747049x1.747049x1.75x4.477%4.48%7.822%7.82%10-1.000000x-1.000000x1.685185x1.685185x1.69x9.057%9.06%15.263%15.3%11-1.000000x-1.000000x1.681608x1.681608x1.68x1.353%1.35%2.276%2.28%12-1.000000x-1.000000x1.652123x1.652123x1.65x1.736%1.74%2.868%2.87%-1.000000x-1.000000x1.634496x1.634496x1.63x2.765%2.77%4.520%4.52%-1.000000x-1.000000x1.629829x1.629829x1.63x2.534%2.53%4.130%4.13%-1.000000x-1.000000x1.556739x1.556739x1.56x0.827%0.83%1.287%1.29%13-1.000000x-1.000000x1.547792x1.547792x1.55x2.553%2.55%3.952%3.95%14-1.000000x-1.000000x1.546996x1.546996x1.55x0.920%0.92%1.424%1.42%15-1.000000x-1.000000x1.545980x1.545980x1.55x8.227%8.23%12.719%12.7%16-1.000000x-1.000000x1.539638x1.539638x1.54x3.397%3.40%5.230%5.23%17-1.000000x-1.000000x1.526951x1.526951x1.53x4.127%4.13%6.301%6.30%18-1.000000x-1.000000x1.526215x1.526215x1.53x2.660%2.66%4.060%4.06%-1.000000x-1.000000x1.502828x1.502828x1.50x3.134%3.13%4.710%4.71%-1.000000x-1.000000x1.488724x1.488724x1.49x3.608%3.61%5.371%5.37%19-1.000000x-1.000000x1.486326x1.486326x1.49x3.316%3.32%4.929%4.93%-1.000000x-1.000000x1.473331x1.473331x1.47x3.302%3.30%4.864%4.86%20-1.000000x-1.000000x1.463655x1.463655x1.46x4.342%4.34%6.355%6.35%21-1.000000x-1.000000x1.440372x1.440372x1.44x1.863%1.86%2.684%2.68%22-1.000000x-1.000000x1.439109x1.439109x1.44x1.876%1.88%2.700%2.70%23-1.000000x-1.000000x1.422215x1.422215x1.42x3.082%3.08%4.384%4.38%24-1.000000x-1.000000x1.407741x1.407741x1.41x2.278%2.28%3.207%3.21%25-1.000000x-1.000000x1.398688x1.398688x1.40x6.228%6.23%8.711%8.71%26-1.000000x-1.000000x1.341930x1.341930x1.34x3.216%3.22%4.316%4.32%27-1.000000x-1.000000x1.338337x1.338337x1.34x5.022%5.02%6.721%6.72%28-1.000000x-1.000000x1.315069x1.315069x1.32x1.464%1.46%1.925%1.93%29-1.000000x-1.000000x1.285200x1.285200x1.29x2.428%2.43%3.121%3.12%30-1.000000x-1.000000x1.275829x1.275829x1.28x17.386%17.4%22.181%22.2%31-1.000000x-1.000000x1.264337x1.264337x1.26x1.739%1.74%2.199%2.20%32-1.000000x-1.000000x1.262281x1.262281x1.26x3.021%3.02%3.814%3.81%33-1.000000x-1.000000x1.245683x1.245683x1.25x9.673%9.67%12.050%12.1%34-1.000000x-1.000000x1.231387x1.231387x1.23x0.516%0.52%0.635%0.64%35-1.000000x-1.000000x1.229783x1.229783x1.23x2.740%2.74%3.370%3.37%36-1.000000x-1.000000x1.221037x1.221037x1.22x6.643%6.64%8.112%8.11%37-1.000000x-1.000000x1.213642x1.213642x1.21x1.369%1.37%1.662%1.66%38-1.000000x-1.000000x1.211475x1.211475x1.21x1.061%1.06%1.285%1.29%39-1.000000x-1.000000x1.210953x1.210953x1.21x1.452%1.45%1.759%1.76%40-1.000000x-1.000000x1.204417x1.204417x1.20x1.083%1.08%1.304%1.30%41-1.000000x-1.000000x1.202385x1.202385x1.20x1.526%1.53%1.834%1.83%42-1.000000x-1.000000x1.168032x1.168032x1.17x2.206%2.21%2.576%2.58%43-1.000000x-1.000000x1.165264x1.165264x1.17x3.973%3.97%4.630%4.63%44-1.000000x-1.000000x1.157113x1.157113x1.16x1.492%1.49%1.726%1.73%45-1.000000x-1.000000x1.135572x1.135572x1.14x8.112%8.11%9.212%9.21%46-1.000000x-1.000000x1.127265x1.127265x1.13x3.237%3.24%3.649%3.65%47-1.000000x-1.000000x1.113365x1.113365x1.11x1.015%1.01%1.130%1.13%48-1.000000x-1.000000x1.051874x1.051874x1.05x3.484%3.48%3.665%3.67%49-1.041380x-1.041380x1.04x1.000000x1.000000x1.055%1.06%1.013%1.01%50
F percentage of females in category
M percentage of males in category
# rank of county subdivision out of 50 by male-to-female sex ratio

Educational Attainment by County Subdivision in the United States

There are 35,600 county subdivisions in the United States. This section compares McDonald to the 50 most populous county subdivisions in the United States and to those entities that contain or substantially overlap with McDonald. The least populous of the compared county subdivisions has a population of 547,300.

No H.S. Diploma by County Subdivision#30

Percent of population 25 years of age and older without a high school diploma (or equivalent).
Scope: population of McDonald, selected other county subdivisions in the United States, and entities that contain McDonald
0%10%20%Count#San Antonio CentralSan Antonio CntrlBronxSan BernardinoLos AngelesSouthwest DallasSW DallasEl PasoAnaheim-Santa Ana-Garden GroveAnaheim-Santa An…FresnoHoustonMiamiDetroitNortheast DallasNE DallasEast San Gabriel ValleyE San Gabriel VlyFort WorthBrooklynLong Beach-LakewoodLong Bch-LakewoodQueensSan Fernando ValleySan Fernando VlyMilwaukeePhiladelphiaOntarioChicagoBaltimoreOceanside-EscondidoOceanside-Escond…Las VegasPhoenixBostonMcDonaldSacramentoOrlandoAustinDenverUnited States of AmericaUnited StatesManhattanSan DiegoTampaSan JoseSan FranciscoMiddle AtlanticTucsonAlbuquerque715700Tract 715700McDonaldNortheastTownship 1:Charlotte1, CharlotteColumbusTulsaPennsylvaniaSalt Lake CitySalt Lk CityTown of HempsteadHempsteadNorthwest HarrisNW HarrisFort Cherry School DistrictFort CherryWashingtonAtlantaSeattleNortheast TarrantNE TarrantWashington CountyWashingtonPittsburgh Metro AreaPittsburghZIP Code 15057ZIP 15057PlanoSeattle East28.998944%28.998944%29.0%126,922127k128.837398%28.837398%28.8%261,022261k227.582802%27.582802%27.6%135,754136k324.837401%24.837401%24.8%434,160434k423.987048%23.987048%24.0%141,940142k523.756417%23.756417%23.8%81,30881.3k622.645542%22.645542%22.6%248,699249k722.107626%22.107626%22.1%92,47292.5k821.922900%21.922900%21.9%457,347457k921.818150%21.818150%21.8%149,688150k1021.003600%21.003600%21.0%90,67890.7k1120.783651%20.783651%20.8%207,494207k1220.461493%20.461493%20.5%128,038128k1320.041576%20.041576%20.0%106,726107k1420.017506%20.017506%20.0%351,046351k1519.402518%19.402518%19.4%73,10573.1k1619.344706%19.344706%19.3%315,505316k1719.344408%19.344408%19.3%244,983245k1817.485105%17.485105%17.5%63,80063.8k1917.390838%17.390838%17.4%180,039180k2017.129346%17.129346%17.1%71,39771.4k2116.905373%16.905373%16.9%309,770310k2216.548703%16.548703%16.5%69,83969.8k2315.999398%15.999398%16.0%70,21470.2k2415.906523%15.906523%15.9%198,651199k2514.952077%14.952077%15.0%308,569309k2614.325556%14.325556%14.3%63,64263.6k2713.935970%13.935970%13.9%22213.900512%13.900512%13.9%103,047103k2813.679368%13.679368%13.7%53,75853.8k2913.668915%13.668915%13.7%78,23878.2k3013.638703%13.638703%13.6%63,86563.9k3113.020590%13.020590%13.0%27,818,38027.8M12.996284%12.996284%13.0%160,845161k3212.985760%12.985760%13.0%206,792207k3312.979618%12.979618%13.0%57,75857.8k3412.789590%12.789590%12.8%153,604154k3512.559735%12.559735%12.6%84,02484.0k3612.313400%12.313400%12.3%3,505,1913.51M12.262851%12.262851%12.3%70,40970.4k3712.089143%12.089143%12.1%52,21752.2k3811.648893%11.648893%11.6%14211.648893%11.648893%11.6%14211.614335%11.614335%11.6%4,487,0854.49M11.553484%11.553484%11.6%61,37861.4k3911.376979%11.376979%11.4%60,83160.8k4011.299086%11.299086%11.3%43,65343.7k4110.459911%10.459911%10.5%925,686926k10.435356%10.435356%10.4%64,29464.3k4210.384134%10.384134%10.4%54,23054.2k4310.135583%10.135583%10.1%47,67947.7k4410.128644%10.128644%10.1%62210.045421%10.045421%10.0%46,51046.5k459.538552%9.538552%9.5%37,37337.4k468.833573%8.833573%8.8%66,22066.2k478.418271%8.418271%8.4%31,44331.4k488.245765%8.245765%8.2%12,25712.3k7.130926%7.130926%7.1%120,640121k7.119651%7.119651%7.1%7675.714681%5.714681%5.7%20,64420.6k494.913852%4.913852%4.9%20,32620.3k50
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older without a high school diploma (or equivalent).

Bachelor's Degrees by County Subdivision#31

Percent of population 25 years of age and older with a bachelor's degree or higher..
Scope: population of McDonald, selected other county subdivisions in the United States, and entities that contain McDonald
0%20%40%60%Count#ManhattanSeattle EastWashingtonSan FranciscoPlanoSan JoseAtlantaSeattleBostonDenverAustinTownship 1:Charlotte1, CharlotteTown of HempsteadHempsteadSan DiegoNortheast TarrantNE TarrantNorthwest HarrisNW HarrisChicagoZIP Code 15057ZIP 15057NortheastColumbusLos AngelesBrooklynMiddle AtlanticSan Fernando ValleySan Fernando VlyNortheast DallasNE DallasSalt Lake CitySalt Lk CityAlbuquerquePittsburgh Metro AreaPittsburghTampaTucsonOceanside-EscondidoOceanside-Escond…TulsaQueensUnited States of AmericaUnited StatesHoustonBaltimorePennsylvaniaLong Beach-LakewoodLong Bch-LakewoodPhoenixOrlandoAnaheim-Santa Ana-Garden GroveAnaheim-Santa An…SacramentoWashington CountyWashingtonEast San Gabriel ValleyE San Gabriel VlyOntarioPhiladelphiaMiamiFort WorthSouthwest DallasSW DallasMilwaukee715700Tract 715700McDonaldFresnoLas VegasEl PasoFort Cherry School DistrictFort CherryMcDonaldBronxSan BernardinoSan Antonio CentralSan Antonio CntrlDetroit60.434640%60.434640%60.4%747,953748k157.691220%57.691220%57.7%238,638239k255.360186%55.360186%55.4%256,316256k354.793235%54.793235%54.8%366,564367k454.142756%54.142756%54.1%195,588196k549.985845%49.985845%50.0%600,334600k649.803731%49.803731%49.8%195,136195k749.626221%49.626221%49.6%372,018372k846.377869%46.377869%46.4%206,036206k945.718966%45.718966%45.7%214,085214k1044.843364%44.843364%44.8%256,674257k1141.989192%41.989192%42.0%223,068223k1238.767308%38.767308%38.8%202,458202k1338.701072%38.701072%38.7%616,296616k1438.547398%38.547398%38.5%143,978144k1536.877886%36.877886%36.9%173,478173k1636.546320%36.546320%36.5%669,666670k1735.069154%35.069154%35.1%3,77834.780899%34.780899%34.8%13,437,26113.4M34.685843%34.685843%34.7%185,460185k1834.593243%34.593243%34.6%604,693605k1934.081468%34.081468%34.1%597,685598k2033.644618%33.644618%33.6%9,577,4379.58M33.231104%33.231104%33.2%420,848421k2133.191099%33.191099%33.2%331,364331k2233.118385%33.118385%33.1%204,048204k2332.636312%32.636312%32.6%140,967141k2432.546256%32.546256%32.5%550,613551k32.512191%32.512191%32.5%144,676145k2532.087814%32.087814%32.1%184,237184k2631.198303%31.198303%31.2%136,915137k2731.110082%31.110082%31.1%120,191120k2830.595789%30.595789%30.6%499,006499k2930.315023%30.315023%30.3%64,767,78764.8M30.080133%30.080133%30.1%627,520628k3029.719611%29.719611%29.7%125,423125k3129.333279%29.333279%29.3%2,595,9502.60M29.113198%29.113198%29.1%109,693110k3228.760152%28.760152%28.8%593,529594k3328.535877%28.535877%28.5%112,142112k3428.412939%28.412939%28.4%312,038312k3528.231204%28.231204%28.2%209,283209k3628.137320%28.137320%28.1%41,82541.8k27.276345%27.276345%27.3%170,682171k3726.758411%26.758411%26.8%111,532112k3826.349720%26.349720%26.3%272,786273k3926.011156%26.011156%26.0%178,455178k4024.665414%24.665414%24.7%131,349131k4123.764821%23.764821%23.8%140,625141k4223.517740%23.517740%23.5%85,81285.8k4322.559475%22.559475%22.6%27522.559475%22.559475%22.6%27522.486319%22.486319%22.5%94,05694.1k4421.702666%21.702666%21.7%271,037271k4521.071885%21.071885%21.1%72,12072.1k4620.159583%20.159583%20.2%1,23819.271814%19.271814%19.3%30719.131504%19.131504%19.1%173,169173k4716.375473%16.375473%16.4%80,59580.6k4814.929012%14.929012%14.9%65,34165.3k4913.833543%13.833543%13.8%59,72359.7k50
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older with a bachelor's degree or higher..

Very Advanced Degrees by County Subdivision#32

Percent of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).
Scope: population of McDonald, selected other county subdivisions in the United States, and entities that contain McDonald
0%5%10%Count#WashingtonManhattanSan FranciscoBostonAtlantaSeattleSan JoseSeattle EastDenverSan DiegoAustinBaltimoreLos AngelesAlbuquerquePlanoChicagoTucsonTown of HempsteadHempsteadTampaNortheastMiamiMiddle AtlanticNortheast DallasNE DallasSalt Lake CitySalt Lk CityHoustonPhiladelphiaSan Fernando ValleySan Fernando VlyPittsburgh Metro AreaPittsburghTownship 1:Charlotte1, CharlotteOceanside-EscondidoOceanside-Escond…BrooklynSacramentoColumbusUnited States of AmericaUnited StatesPennsylvaniaTulsaPhoenixLong Beach-LakewoodLong Bch-LakewoodOrlandoFresnoAnaheim-Santa Ana-Garden GroveAnaheim-Santa An…QueensNorthwest HarrisNW HarrisNortheast TarrantNE TarrantEast San Gabriel ValleyE San Gabriel VlyOntarioWashington CountyWashingtonFort WorthLas VegasMilwaukeeSan BernardinoSan Antonio CentralSan Antonio CntrlEl PasoSouthwest DallasSW DallasBronxZIP Code 15057ZIP 15057Detroit715700Tract 715700McDonaldMcDonaldFort Cherry School DistrictFort Cherry12.461852%12.461852%12.5%57,69857.7k110.788423%10.788423%10.8%133,520134k27.558053%7.558053%7.6%50,56350.6k37.340604%7.340604%7.3%32,61132.6k46.889819%6.889819%6.9%26,99527.0k56.641855%6.641855%6.6%49,79049.8k66.255912%6.255912%6.3%75,13475.1k76.036065%6.036065%6.0%24,96825.0k85.725842%5.725842%5.7%26,81226.8k95.247128%5.247128%5.2%83,55883.6k105.058711%5.058711%5.1%28,95529.0k114.934352%4.934352%4.9%20,82420.8k124.659072%4.659072%4.7%81,44181.4k134.631274%4.631274%4.6%20,00420.0k144.617088%4.617088%4.6%16,67916.7k154.485379%4.485379%4.5%82,18982.2k164.461087%4.461087%4.5%25,61425.6k174.441262%4.441262%4.4%23,19423.2k184.325266%4.325266%4.3%19,24719.2k194.085016%4.085016%4.1%1,578,2061.58M4.025531%4.025531%4.0%27,61827.6k203.884861%3.884861%3.9%1,105,8831.11M3.827408%3.827408%3.8%38,21138.2k213.792624%3.792624%3.8%23,36723.4k223.737871%3.737871%3.7%77,97878.0k233.720350%3.720350%3.7%38,51538.5k243.601468%3.601468%3.6%45,61045.6k253.600869%3.600869%3.6%60,91960.9k3.490252%3.490252%3.5%18,54218.5k263.466073%3.466073%3.5%15,21115.2k273.384967%3.384967%3.4%59,36259.4k283.380196%3.380196%3.4%25,05825.1k293.357865%3.357865%3.4%17,95418.0k303.336158%3.336158%3.3%7,127,6737.13M3.299391%3.299391%3.3%291,991292k3.140490%3.140490%3.1%12,13312.1k313.010825%3.010825%3.0%62,13562.1k323.009440%3.009440%3.0%11,33911.3k332.893233%2.893233%2.9%11,37011.4k342.828959%2.828959%2.8%11,83311.8k352.763004%2.763004%2.8%30,34430.3k362.756960%2.756960%2.8%44,96545.0k372.682967%2.682967%2.7%12,62112.6k382.630994%2.630994%2.6%9,827392.484535%2.484535%2.5%15,54715.5k402.324315%2.324315%2.3%9,688412.279241%2.279241%2.3%3,3882.173239%2.173239%2.2%11,57311.6k422.155077%2.155077%2.2%26,91426.9k432.043126%2.043126%2.0%7,455441.807306%1.807306%1.8%8,895451.792414%1.792414%1.8%7,845461.745764%1.745764%1.7%5,975471.704476%1.704476%1.7%10,08610.1k481.664253%1.664253%1.7%15,06415.1k491.596584%1.596584%1.6%1721.318660%1.318660%1.3%5,693500.574241%0.574241%0.6%70.574241%0.574241%0.6%70.439422%0.439422%0.4%70.407100%0.407100%0.4%25
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).

Under-Education Sex Ratio by County Subdivision#33

Percentage more likely men are than women to not have a high school diploma (or equivalent) among people aged 25 years and older.
Scope: population of McDonald, selected other county subdivisions in the United States, and entities that contain McDonald
Female
Male
1x0x1xFM#Tract 715700McDonaldMcDonaldFort Cherry1, CharlotteDetroitBaltimoreTulsaSW DallasFresnoMilwaukeeUnited StatesNE DallasHoustonPennsylvaniaHempsteadOrlandoPhiladelphiaOntarioSan BernardinoAustinNortheastZIP 15057AtlantaFort WorthWashingtonPhoenixChicagoAlbuquerqueWashingtonMiddle AtlanticSacramentoColumbusSalt Lk CityDenverNE TarrantTampaOceanside-EscondidoOceanside-Escond…NW HarrisBronxPlanoBrooklynPittsburghSan Antonio CntrlSan Fernando VlyTucsonAnaheim-Santa Ana-Gdn GrvAnaheim-Santa An…Los AngelesLas VegasBostonE San Gabriel VlyQueensMiamiManhattanSeattleLong Bch-LakewoodSeattle EastSan JoseSan DiegoSan FranciscoEl Paso-1.000000x-1.000000x1.331183x1.331183x1.33x10.016%10.0%13.333%13.3%-1.000000x-1.000000x1.331183x1.331183x1.33x10.016%10.0%13.333%13.3%-1.000000x-1.000000x1.314658x1.314658x1.31x12.088%12.1%15.891%15.9%-1.000000x-1.000000x1.290542x1.290542x1.29x8.846%8.85%11.416%11.4%-1.000000x-1.000000x1.285784x1.285784x1.29x10.185%10.2%13.096%13.1%1-1.000000x-1.000000x1.237056x1.237056x1.24x18.951%19.0%23.443%23.4%2-1.000000x-1.000000x1.179669x1.179669x1.18x15.289%15.3%18.036%18.0%3-1.000000x-1.000000x1.177766x1.177766x1.18x10.417%10.4%12.268%12.3%4-1.000000x-1.000000x1.160109x1.160109x1.16x22.304%22.3%25.875%25.9%5-1.000000x-1.000000x1.127206x1.127206x1.13x20.830%20.8%23.479%23.5%6-1.000000x-1.000000x1.123984x1.123984x1.12x16.526%16.5%18.574%18.6%7-1.000000x-1.000000x1.109070x1.109070x1.11x12.369%12.4%13.719%13.7%-1.000000x-1.000000x1.099797x1.099797x1.10x19.814%19.8%21.791%21.8%8-1.000000x-1.000000x1.099188x1.099188x1.10x20.902%20.9%22.975%23.0%9-1.000000x-1.000000x1.094514x1.094514x1.09x10.006%10.0%10.952%11.0%-1.000000x-1.000000x1.092101x1.092101x1.09x9.951%9.95%10.868%10.9%10-1.000000x-1.000000x1.090284x1.090284x1.09x13.111%13.1%14.294%14.3%11-1.000000x-1.000000x1.090163x1.090163x1.09x16.700%16.7%18.206%18.2%12-1.000000x-1.000000x1.088515x1.088515x1.09x16.417%16.4%17.871%17.9%13-1.000000x-1.000000x1.081887x1.081887x1.08x26.536%26.5%28.709%28.7%14-1.000000x-1.000000x1.078150x1.078150x1.08x13.148%13.1%14.176%14.2%15-1.000000x-1.000000x1.074442x1.074442x1.07x11.216%11.2%12.051%12.1%-1.000000x-1.000000x1.073596x1.073596x1.07x6.866%6.87%7.372%7.37%-1.000000x-1.000000x1.073220x1.073220x1.07x9.215%9.21%9.889%9.89%16-1.000000x-1.000000x1.071348x1.071348x1.07x19.379%19.4%20.762%20.8%17-1.000000x-1.000000x1.071245x1.071245x1.07x7.973%7.97%8.541%8.54%-1.000000x-1.000000x1.069008x1.069008x1.07x14.467%14.5%15.465%15.5%18-1.000000x-1.000000x1.068021x1.068021x1.07x16.372%16.4%17.486%17.5%19-1.000000x-1.000000x1.066879x1.066879x1.07x11.714%11.7%12.497%12.5%20-1.000000x-1.000000x1.064309x1.064309x1.06x9.751%9.75%10.378%10.4%21-1.000000x-1.000000x1.059800x1.059800x1.06x11.972%12.0%12.688%12.7%-1.000000x-1.000000x1.053268x1.053268x1.05x13.558%13.6%14.280%14.3%22-1.000000x-1.000000x1.052237x1.052237x1.05x11.098%11.1%11.678%11.7%23-1.000000x-1.000000x1.051272x1.051272x1.05x10.176%10.2%10.697%10.7%24-1.000000x-1.000000x1.049933x1.049933x1.05x13.307%13.3%13.971%14.0%25-1.000000x-1.000000x1.040742x1.040742x1.04x8.257%8.26%8.594%8.59%26-1.000000x-1.000000x1.040003x1.040003x1.04x12.734%12.7%13.244%13.2%27-1.000000x-1.000000x1.039910x1.039910x1.04x15.694%15.7%16.321%16.3%28-1.000000x-1.000000x1.038394x1.038394x1.04x9.953%9.95%10.335%10.3%29-1.000000x-1.000000x1.030539x1.030539x1.03x28.448%28.4%29.316%29.3%30-1.000000x-1.000000x1.023151x1.023151x1.02x5.652%5.65%5.783%5.78%31-1.000000x-1.000000x1.018960x1.018960x1.02x19.845%19.8%20.221%20.2%32-1.000000x-1.000000x1.015146x1.015146x1.02x7.080%7.08%7.187%7.19%-1.000000x-1.000000x1.003929x1.003929x1.00x28.944%28.9%29.058%29.1%33-1.000000x-1.000000x1.003840x1.003840x1.00x19.308%19.3%19.383%19.4%34-1.006471x-1.006471x1.01x1.000000x1.000000x12.301%12.3%12.222%12.2%35-1.008020x-1.008020x1.01x1.000000x1.000000x22.734%22.7%22.553%22.6%36-1.013004x-1.013004x1.01x1.000000x1.000000x24.995%25.0%24.674%24.7%37-1.016645x-1.016645x1.02x1.000000x1.000000x16.036%16.0%15.774%15.8%38-1.022333x-1.022333x1.02x1.000000x1.000000x14.476%14.5%14.159%14.2%39-1.026902x-1.026902x1.03x1.000000x1.000000x20.723%20.7%20.180%20.2%40-1.027762x-1.027762x1.03x1.000000x1.000000x19.596%19.6%19.067%19.1%41-1.030897x-1.030897x1.03x1.000000x1.000000x22.136%22.1%21.473%21.5%42-1.044246x-1.044246x1.04x1.000000x1.000000x13.260%13.3%12.698%12.7%43-1.049689x-1.049689x1.05x1.000000x1.000000x9.047%9.05%8.619%8.62%44-1.056864x-1.056864x1.06x1.000000x1.000000x19.921%19.9%18.849%18.8%45-1.057675x-1.057675x1.06x1.000000x1.000000x5.050%5.05%4.774%4.77%46-1.127548x-1.127548x1.13x1.000000x1.000000x13.555%13.6%12.021%12.0%47-1.168454x-1.168454x1.17x1.000000x1.000000x13.975%14.0%11.960%12.0%48-1.228758x-1.228758x1.23x1.000000x1.000000x13.883%13.9%11.298%11.3%49-1.276282x-1.276282x1.28x1.000000x1.000000x26.394%26.4%20.680%20.7%50
F percentage of females in category
M percentage of males in category
# rank of county subdivision out of 50 by male-to-female sex ratio

Over-Education Sex Ratio by County Subdivision#34

Percentage more likely men are than women to have a professional or doctorate degree (e.g., MBA, PhD, or MD) among people aged 25 years and older.
Scope: population of McDonald, selected other county subdivisions in the United States, and entities that contain McDonald
Female
Male
0x5x10xFM#McDonaldTract 715700McDonaldZIP 15057El PasoFort CherrySalt Lk CityPlanoTulsaAlbuquerqueNE DallasFort WorthOrlandoPhoenixWashingtonPittsburghPennsylvaniaTucson1, CharlotteNW HarrisLas VegasSeattle EastSan Antonio CntrlSan DiegoUnited StatesSan JoseMiddle AtlanticHempsteadNortheastFresnoNE TarrantTampaSan Fernando VlyE San Gabriel VlyHoustonSan BernardinoColumbusMiamiAtlantaMilwaukeeAnaheim-Santa Ana-Gdn GrvAnaheim-Santa An…SacramentoPhiladelphiaOceanside-EscondidoOceanside-Escond…Los AngelesAustinBaltimoreWashingtonQueensSW DallasBrooklynManhattanChicagoSeattleBostonBronxOntarioLong Bch-LakewoodDenverSan FranciscoDetroit-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%0.904%0.90%-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%1.167%1.17%-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%1.167%1.17%-1.000000x-1.000000x3.760285x3.760285x3.76x0.670%0.67%2.519%2.52%-1.000000x-1.000000x2.132933x2.132933x2.13x1.146%1.15%2.445%2.44%1-1.000000x-1.000000x2.131238x2.131238x2.13x0.260%0.26%0.554%0.55%-1.000000x-1.000000x2.053360x2.053360x2.05x2.488%2.49%5.109%5.11%2-1.000000x-1.000000x1.782054x1.782054x1.78x3.355%3.35%5.978%5.98%3-1.000000x-1.000000x1.720683x1.720683x1.72x2.338%2.34%4.022%4.02%4-1.000000x-1.000000x1.707718x1.707718x1.71x3.458%3.46%5.905%5.91%5-1.000000x-1.000000x1.692229x1.692229x1.69x2.857%2.86%4.836%4.84%6-1.000000x-1.000000x1.684272x1.684272x1.68x1.637%1.64%2.757%2.76%7-1.000000x-1.000000x1.660799x1.660799x1.66x2.196%2.20%3.647%3.65%8-1.000000x-1.000000x1.659024x1.659024x1.66x2.280%2.28%3.783%3.78%9-1.000000x-1.000000x1.652123x1.652123x1.65x1.736%1.74%2.868%2.87%-1.000000x-1.000000x1.634496x1.634496x1.63x2.765%2.77%4.520%4.52%-1.000000x-1.000000x1.629829x1.629829x1.63x2.534%2.53%4.130%4.13%-1.000000x-1.000000x1.621815x1.621815x1.62x3.429%3.43%5.561%5.56%10-1.000000x-1.000000x1.611479x1.611479x1.61x2.711%2.71%4.369%4.37%11-1.000000x-1.000000x1.579303x1.579303x1.58x2.100%2.10%3.317%3.32%12-1.000000x-1.000000x1.576623x1.576623x1.58x1.677%1.68%2.643%2.64%13-1.000000x-1.000000x1.557664x1.557664x1.56x4.733%4.73%7.372%7.37%14-1.000000x-1.000000x1.540473x1.540473x1.54x1.423%1.42%2.192%2.19%15-1.000000x-1.000000x1.529565x1.529565x1.53x4.164%4.16%6.370%6.37%16-1.000000x-1.000000x1.526215x1.526215x1.53x2.660%2.66%4.060%4.06%-1.000000x-1.000000x1.514156x1.514156x1.51x4.979%4.98%7.539%7.54%17-1.000000x-1.000000x1.502828x1.502828x1.50x3.134%3.13%4.710%4.71%-1.000000x-1.000000x1.488724x1.488724x1.49x3.608%3.61%5.371%5.37%18-1.000000x-1.000000x1.486326x1.486326x1.49x3.316%3.32%4.929%4.93%-1.000000x-1.000000x1.484269x1.484269x1.48x2.293%2.29%3.404%3.40%19-1.000000x-1.000000x1.481801x1.481801x1.48x2.138%2.14%3.168%3.17%20-1.000000x-1.000000x1.476874x1.476874x1.48x3.518%3.52%5.196%5.20%21-1.000000x-1.000000x1.460302x1.460302x1.46x2.944%2.94%4.299%4.30%22-1.000000x-1.000000x1.451775x1.451775x1.45x2.041%2.04%2.963%2.96%23-1.000000x-1.000000x1.424636x1.424636x1.42x3.092%3.09%4.404%4.40%24-1.000000x-1.000000x1.423621x1.423621x1.42x1.501%1.50%2.137%2.14%25-1.000000x-1.000000x1.413654x1.413654x1.41x2.801%2.80%3.959%3.96%26-1.000000x-1.000000x1.395174x1.395174x1.40x3.384%3.38%4.722%4.72%27-1.000000x-1.000000x1.391590x1.391590x1.39x5.799%5.80%8.070%8.07%28-1.000000x-1.000000x1.368590x1.368590x1.37x1.742%1.74%2.385%2.38%29-1.000000x-1.000000x1.362600x1.362600x1.36x2.347%2.35%3.199%3.20%30-1.000000x-1.000000x1.359928x1.359928x1.36x2.888%2.89%3.927%3.93%31-1.000000x-1.000000x1.341930x1.341930x1.34x3.216%3.22%4.316%4.32%32-1.000000x-1.000000x1.310218x1.310218x1.31x3.011%3.01%3.945%3.95%33-1.000000x-1.000000x1.308108x1.308108x1.31x4.045%4.05%5.292%5.29%34-1.000000x-1.000000x1.303834x1.303834x1.30x4.384%4.38%5.716%5.72%35-1.000000x-1.000000x1.303196x1.303196x1.30x4.332%4.33%5.645%5.65%36-1.000000x-1.000000x1.300117x1.300117x1.30x10.922%10.9%14.199%14.2%37-1.000000x-1.000000x1.285200x1.285200x1.29x2.428%2.43%3.121%3.12%38-1.000000x-1.000000x1.265486x1.265486x1.27x1.515%1.51%1.917%1.92%39-1.000000x-1.000000x1.262281x1.262281x1.26x3.021%3.02%3.814%3.81%40-1.000000x-1.000000x1.245683x1.245683x1.25x9.673%9.67%12.050%12.1%41-1.000000x-1.000000x1.238186x1.238186x1.24x4.026%4.03%4.985%4.99%42-1.000000x-1.000000x1.228890x1.228890x1.23x5.961%5.96%7.326%7.33%43-1.000000x-1.000000x1.221037x1.221037x1.22x6.643%6.64%8.112%8.11%44-1.000000x-1.000000x1.202385x1.202385x1.20x1.526%1.53%1.834%1.83%45-1.000000x-1.000000x1.198236x1.198236x1.20x2.119%2.12%2.539%2.54%46-1.000000x-1.000000x1.181998x1.181998x1.18x2.766%2.77%3.269%3.27%47-1.000000x-1.000000x1.129665x1.129665x1.13x5.378%5.38%6.075%6.08%48-1.000000x-1.000000x1.098720x1.098720x1.10x7.194%7.19%7.905%7.90%49-1.000000x-1.000000x1.046557x1.046557x1.05x1.291%1.29%1.351%1.35%50
F percentage of females in category
M percentage of males in category
# rank of county subdivision out of 50 by male-to-female sex ratio

Definitions

Educational attainment is reported in terms of the highest level of education obtained by persons aged 25 years and older. On this page, we report on both detailed and coarse categorizations of the levels of education in the population. The detailed levels of educational attainment are as follows:

  • None: no formal education at all
  • Less than High School: some education, but stopped short of high school
  • Some High School: some high school education, but no high school diploma (or equivalent)
  • Some College: high school diploma (or equivalent), and some college, but no post-secondary degree
  • Associate's Degree: highest post-secondary degree is an associate's degree (including occupational or academic degrees)
  • Bachelor's Degree: highest post-secondary degree is a bachelor's degree (e.g., BA, BS, AB)
  • Master's Degree: highest post-secondary degree is a master's degree (e.g., MA, MS, MENG, MSW)
  • Professional Degree: highest post-secondary degree is a professional degree (e.g., MD, DDC, JD)
  • Doctorate Degree: highest post-secondary degree is a doctorate degree (e.g., PhD, EdD)

The coarse levels of educational attainment are as follows:

  • No High School Diploma: does not have a high school diploma or equivalent
  • High School Diploma: has a high school diploma or equivalent and possibly some college, but no post-secondary degrees
  • Higher Degree: has some post-secondary degree (associate's, bachelor's, master's, professional, doctorate)

For additional information about the data presented on this site, including our sources, please see the About Page.

More Topics to Explore

Demographics

Income

Education

More Maps to Explore

State:
Pennsylvania
County:
Washington
Metro Area:
Pittsburgh Area
Borough:
McDonald
ZIP Code:
15057
Unified School District:
Fort Cherry
Congressional District:
PA-18
State Senate District:
PA-46
State House District:
PA-46
Neighboring Townships:
Cecil, Robinson
Nearby Townships:
Collier, Mount Pleasant, North Fayette, Smith, South Fayette