Educational Attainment in the Monroe Township, Licking County, Ohio (Township)

Educational Attainment#1

Highest level of education among people aged 25 years and older.
Scope: population of Licking County and the Monroe Township
Monroe Township
Licking County
0%10%20%30%40%50%CountHigher Degree1H.S. Diploma2No H.S. Diploma230.059708%32.224377%30.059708%30.1%1,46059.419395%58.166229%59.419395%59.4%2,88610.520898%9.609394%10.520898%10.5%511

Relative Educational Attainment#2

Highest level of education among people aged 25 years and older, as percentage more or less than Licking County at large.
Scope: population of Licking County and the Monroe Township
-5%0%+5%%ref.Higher Degree1H.S. Diploma2No H.S. Diploma2-6.717491%-6.717491%-6.7%30.060%30.1%32.224%32.2%2.154455%2.154455%+2.2%59.419%59.4%58.166%58.2%9.485553%9.485553%+9.5%10.521%10.5%9.609%9.61%

Detailed Educational Attainment#3

Highest level of education among people aged 25 years and older.
Scope: population of Licking County and the Monroe Township
Monroe Township
Licking County
0%10%20%30%CountDoctorate1Professional1Master's1Bachelor's1Associate's1Some CollegeHigh School2Some H.S.3Less than H.S.3None1.585341%0.997797%1.585341%1.6%770.452954%1.285640%0.452954%0.5%224.529545%5.882353%4.529545%4.5%22016.326951%15.163535%16.326951%16.3%7937.164917%8.895051%7.164917%7.2%34821.268273%21.792700%21.268273%21.3%1,03338.151122%36.373529%38.151122%38.2%1,8537.041384%7.656800%7.041384%7.0%3423.026560%1.374275%3.026560%3.0%1470.452954%0.578319%0.452954%0.5%22

Detailed Relative Educational Attainment#4

Highest level of education among people aged 25 years and older, as percentage more or less than Licking County at large.
Scope: population of Licking County and the Monroe Township
-100%0%+100%%ref.Doctorate1Professional1Master's1Bachelor's1Associate's1Some CollegeHigh School2Some H.S.3Less than H.S.3None58.884049%58.884049%+58.9%1.585%1.59%0.998%1.00%-64.768179%-64.768179%-64.8%0.453%0.45%1.286%1.29%-22.997735%-22.997735%-23.0%4.530%4.53%5.882%5.88%7.672456%7.672456%+7.7%16.327%16.3%15.164%15.2%-19.450531%-19.450531%-19.5%7.165%7.16%8.895%8.90%-2.406438%-2.406438%-2.4%21.268%21.3%21.793%21.8%4.887052%4.887052%+4.9%38.151%38.2%36.374%36.4%-8.037513%-8.037513%-8.0%7.041%7.04%7.657%7.66%120.229562%120.229562%+120.2%3.027%3.03%1.374%1.37%-21.677363%-21.677363%-21.7%0.453%0.45%0.578%0.58%

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 Licking County and the Monroe Township
More Females More Males
Licking County
Monroe Township
10%5%0%5%FMHigher Degree1H.S. Diploma2No H.S. Diploma2-12.874458%-13.344256%-12.874458%13%31.878%31.9%28.242%28.2%7.880640%6.432624%7.880640%8%57.166%57.2%61.671%61.7%-8.616145%-8.616145%9%4.156224%10.956%11.0%10.086%10.1%

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 Licking County and the Monroe Township
More Females More Males
Licking County
Monroe Township
1k%0k%1k%FMDoctorate1Professional1Master's1Bachelor's1Associate's1Some CollegeHigh School2Some H.S.3Less than H.S.3None-85.261456%-85.261456%0k%56.523255%2.059%2.06%1.112%1.11%1,000.000000%40.004418%1,000.000000%> 1000%0.000%0%0.906%0.91%-50.061779%-42.095507%-50.061779%0k%5.437%5.44%3.623%3.62%-3.203721%14.277258%14.277258%0k%15.239%15.2%17.415%17.4%-76.263042%-31.183272%-76.263042%0k%9.143%9.14%5.187%5.19%-1.303647%25.002982%25.002982%0k%18.904%18.9%23.631%23.6%-0.582535%-0.582535%0k%11.339741%38.262%38.3%38.040%38.0%-0.806906%2.324720%2.324720%0k%6.960%6.96%7.122%7.12%-7.086340%-7.086340%0k%16.938662%3.130%3.13%2.923%2.92%-1,000.000000%-1,000.000000%> 1000%51.238054%0.865%0.86%0.041%0.04%

Bachelor's Degrees By Age#7

Percentage of age cohort whose highest degree is a Bachelor's.
Scope: population of Licking County and the Monroe Township
Monroe Township
Licking County
0%5%10%15%20%B.X.Total65+45-6435-4425-3416.600791%10.532290%16.600791%16.6%1681,0129.213615%14.929148%9.213615%9.2%1571,70423.393316%19.130682%23.393316%23.4%2731,16720.020534%17.519786%20.020534%20.0%195974

Relative Bachelor's Degrees By Age#8

Percentage of population whose highest degree is a Bachelor's, as a percentage more or less than Licking County at large.
Scope: population of Licking County and the Monroe Township
20%0%20%40%%ref.65+45-6435-4425-3457.618059%57.618059%57.6%16.601%16.6%10.532%10.5%-38.284387%-38.284387%38.3%9.214%9.21%14.929%14.9%22.281663%22.281663%22.3%23.393%23.4%19.131%19.1%14.273848%14.273848%14.3%20.021%20.0%17.520%17.5%

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 Licking County and the Monroe Township
More Females More Males
Licking County
Monroe Township
0%100%200%FM65+45-6435-4425-34257.142857%24.271483%257.142857%257.1%7.636%7.64%27.273%27.3%80.875311%0.089472%80.875311%80.9%6.590%6.59%11.919%11.9%-40.922615%-9.892798%-40.922615%40.9%27.636%27.6%19.611%19.6%-72.811754%-34.658880%-72.811754%72.8%25.702%25.7%14.873%14.9%

Median Earnings by Educational Attainment#10

Among population 25 years old and over with earnings.
Scope: population of Licking County and the Monroe Township
Monroe Township
Licking County
$0k$20k$40k$60kCount%Graduate Degree1Bachelor's DegreeSome CollegeH.S. Diploma2No H.S. Diploma2Total$62,216.000000$61,005.000000$62,216.000000$62.2k3196.568%6.57%$68,707.000000$55,590.000000$68,707.000000$68.7k79316.327%16.3%$39,321.000000$34,844.000000$39,321.000000$39.3k1,38128.433%28.4%$35,843.000000$29,653.000000$35,843.000000$35.8k1,85338.151%38.2%$26,875.000000$20,516.000000$26,875.000000$26.9k51110.521%10.5%$41,153.000000$36,291.000000$41,153.000000$41.2k4,857100.000%100%

Median Earnings by Educational Attainment#11

By sex among population 25 years old and over with earnings.
Scope: population of Licking County and the Monroe Township
Female Male
Licking County
Monroe Township
Shaded bar tips show excess over facing bar.
$50k$0k$50kFMGraduate Degree1Bachelor's DegreeSome CollegeH.S. Diploma2No H.S. Diploma2Total$-51,920.000000$-54,841.000000$-51,920.000000$51.9k$51,920.000000$18,318.000000$54,841.000000$15,217.000000$70,238.000000$70.2k182137$-67,604.000000$-45,300.000000$-67,604.000000$67.6k$67,604.000000$1,881.000000$45,300.000000$19,560.000000$69,485.000000$69.5k370423$-28,325.000000$-27,491.000000$-28,325.000000$28.3k$28,325.000000$17,587.000000$27,491.000000$14,475.000000$45,912.000000$45.9k681700$-30,657.000000$-23,009.000000$-30,657.000000$30.7k$30,657.000000$10,312.000000$23,009.000000$12,690.000000$40,969.000000$41.0k929924$-22,043.000000$-18,674.000000$-22,043.000000$22.0k$22,043.000000$16,707.000000$18,674.000000$3,777.000000$38,750.000000$38.8k266245$-32,491.000000$-30,272.000000$-32,491.000000$32.5k$32,491.000000$13,787.000000$30,272.000000$12,182.000000$46,278.000000$46.3k2,4282,429

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 Licking County and the Monroe Township
Monroe Township
Licking County
0%20%40%60%80%CountBachelor's Degree1Some College2H.S. Diploma3No H.S. Diploma386.756453%87.256324%86.756453%86.8%77377.352472%77.611085%77.352472%77.4%97077.330350%70.151759%77.330350%77.3%1,03767.409471%52.515586%67.409471%67.4%242

Lacking High School Diploma By Race#13

Percent of racial or ethnic group lacking a high school diploma (or equivalent).
Scope: population of Licking County and the Monroe Township
Female Male
Licking County
Monroe Township
Shaded bar tips show excess over facing bar.
10%5%0%5%10%15%MFWhite1AsianOther1-10.199833%-1.138615%-9.499199%-11.338448%11.3%10.199833%9.499199%0.139403%10.199833%10.2%245266-0.000000%-7.538803%-1.141753%0.000000%0.0%0.000000%0.000000%7.538803%0.000000%0.0%00-0.000000%-8.035714%0.000000%0.0%0.000000%0.000000%8.035714%10.126211%0.000000%0.0%00

College Graduates By Race#14

Percent of racial or ethnic group with a bachelor's degree or higher.
Scope: population of Licking County and the Monroe Township
Female Male
Licking County
Monroe Township
Shaded bar tips show excess over facing bar.
100%50%0%50%100%MFWhite1AsianOther1-22.731057%-0.201594%-22.161348%-1.470498%-22.932651%22.9%22.731057%22.161348%22.731057%22.7%546538-100.000000%-37.673611%-100.000000%100.0%100.000000%0.000000%37.673611%14.432819%100.000000%100.0%1414-0.000000%-19.912473%-4.704874%0.000000%0.0%0.000000%0.000000%19.912473%0.000000%0.0%00

Map of Educational Attainment by Tract in the Monroe Township

Coarse: Post-Secondary Degree Educational Attainment by Tract#15

Percentage of the population 25 years and older with given highest level of educational attainment
29.2%30.2%31.1%32.1%33.0%34.0%

Coarse: High School Diploma Educational Attainment by Tract#16

Percentage of the population 25 years and older with given highest level of educational attainment
60.35%60.44%60.53%60.62%60.71%60.80%

Coarse: No High School Diploma Educational Attainment by Tract#17

Percentage of the population 25 years and older with given highest level of educational attainment
5.2%6.3%7.3%8.4%9.4%10.5%

Detailed: Doctorate Degree Educational Attainment by Tract#18

Percentage of the population 25 years and older with given highest level of educational attainment
1.57226%1.57255%1.57283%1.57311%1.57339%1.57368%

Detailed: Professional Degree Educational Attainment by Tract#19

Percentage of the population 25 years and older with given highest level of educational attainment
0.44%0.53%0.61%0.69%0.77%0.85%

Detailed: Master's Degree Educational Attainment by Tract#20

Percentage of the population 25 years and older with given highest level of educational attainment
4.49%4.59%4.68%4.77%4.87%4.96%

Detailed: Bachelor's Degree Educational Attainment by Tract#21

Percentage of the population 25 years and older with given highest level of educational attainment
15.5%16.6%17.6%18.6%19.6%20.7%

Detailed: Associate's Degree Educational Attainment by Tract#22

Percentage of the population 25 years and older with given highest level of educational attainment
5.94%6.18%6.41%6.65%6.88%7.12%

Detailed: Some College Educational Attainment by Tract#23

Percentage of the population 25 years and older with given highest level of educational attainment
21.1%21.9%22.6%23.4%24.1%24.9%

Detailed: High School Diploma or Equivalent Educational Attainment by Tract#24

Percentage of the population 25 years and older with given highest level of educational attainment
35.9%36.6%37.3%37.9%38.6%39.3%

Detailed: Some High School Educational Attainment by Tract#25

Percentage of the population 25 years and older with given highest level of educational attainment
4.77%5.22%5.66%6.10%6.55%6.99%

Detailed: Less than High School Educational Attainment by Tract#26

Percentage of the population 25 years and older with given highest level of educational attainment
0.0%0.6%1.2%1.8%2.4%3.1%

Detailed: None Educational Attainment by Tract#27

Percentage of the population 25 years and older with given highest level of educational attainment
0.4434%0.4447%0.4459%0.4472%0.4484%0.4497%
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Educational Attainment by County Subdivision in the Columbus Area

There are 181 county subdivisions in the Columbus Area. This section compares the Monroe Township to the 50 most populous county subdivisions in the Columbus Area and to those entities that contain or substantially overlap with the Monroe Township. The least populous of the compared county subdivisions has a population of 6,814.

No H.S. Diploma by County Subdivision#28

Percent of population 25 years of age and older without a high school diploma (or equivalent).
Scope: population of the Monroe Township, selected other county subdivisions in the Columbus Area, and entities that contain the Monroe Township
0%5%10%15%20%Count#Franklin TownshipFranklinPike TownshipScioto TownshipSciotoWhitehallHamilton TownshipHamiltonCirclevilleLondonUnion TownshipUnionPrairie TownshipPrairieUnited States of AmericaUnited StatesPleasant TownshipPleasantNewarkFalls TownshipFallsLancaster City TownshipLancaster CityWalnut TownshipWalnutJefferson TownshipJeffersonColumbusEast North CentralHeathMonroe TownshipMonroeOhioHarrison TownshipHarrisonMidwestParis TownshipParisLicking CountyLickingColumbus Metro AreaColumbus AreaBlendon TownshipBlendonMadison TownshipMadisonPataskalaEtna TownshipTruro TownshipTruroColumbusJackson TownshipJacksonDelaware City TownshipDelaware CityLiberty TownshipLibertyMifflin TownshipMifflinHarrison TownshipHarrisonViolet TownshipVioletBloom TownshipBloomWestervilleNorwich TownshipNorwichJefferson TownshipJeffersonBerlin TownshipBerlinConcord TownshipConcordPlain TownshipPlainWesterville City TownshipWesterville CityBexleyJerome TownshipJeromeSharon TownshipSharonDublinLiberty TownshipLibertyOrange TownshipOrangeGranville TownshipGranvilleGenoa TownshipGenoaUpper ArlingtonGrandview HeightsGrandview Hts24.885541%24.885541%24.9%1,685119.520852%19.520852%19.5%880219.407227%19.407227%19.4%1,434319.347697%19.347697%19.3%2,272415.953777%15.953777%16.0%925515.617892%15.617892%15.6%1,442613.879574%13.879574%13.9%952713.757596%13.757596%13.8%815813.417155%13.417155%13.4%1,558913.020590%13.020590%13.0%27,818,38027.8M13.017397%13.017397%13.0%6511012.943290%12.943290%12.9%4,1061112.793800%12.793800%12.8%1,0071212.375999%12.375999%12.4%3,3311311.694215%11.694215%11.7%5661411.543839%11.543839%11.5%5781511.376979%11.376979%11.4%60,83160.8k1610.719464%10.719464%10.7%3,363,7843.36M10.699701%10.699701%10.7%7861710.520898%10.520898%10.5%5111810.514146%10.514146%10.5%825,155825k10.252270%10.252270%10.3%5081910.244520%10.244520%10.2%4,641,8354.64M10.236565%10.236565%10.2%1,640209.609394%9.609394%9.6%10,95011.0k9.314501%9.314501%9.3%123,226123k8.397699%8.397699%8.4%511218.155569%8.155569%8.2%1,384227.536491%7.536491%7.5%759237.242608%7.242608%7.2%752246.948891%6.948891%6.9%1,259256.732802%6.732802%6.7%414266.480864%6.480864%6.5%1,944276.430658%6.430658%6.4%1,475286.338438%6.338438%6.3%327295.595517%5.595517%5.6%1,408305.490989%5.490989%5.5%326313.979966%3.979966%4.0%1,041323.712336%3.712336%3.7%223333.672345%3.672345%3.7%733343.371215%3.371215%3.4%795352.958028%2.958028%3.0%222362.710914%2.710914%2.7%116372.662407%2.662407%2.7%175382.451334%2.451334%2.5%170392.242444%2.242444%2.2%138402.234276%2.234276%2.2%173412.157989%2.157989%2.2%109421.943537%1.943537%1.9%232431.754602%1.754602%1.8%428441.730449%1.730449%1.7%312451.713710%1.713710%1.7%306461.642439%1.642439%1.6%87471.387785%1.387785%1.4%227481.346130%1.346130%1.3%324490.707108%0.707108%0.7%3850

Bachelor's Degrees by County Subdivision#29

Percent of population 25 years of age and older with a bachelor's degree or higher..
Scope: population of the Monroe Township, selected other county subdivisions in the Columbus Area, and entities that contain the Monroe Township
0%20%40%60%Count#DublinBexleyUpper ArlingtonPlain TownshipPlainGrandview HeightsGrandview HtsLiberty TownshipLibertySharon TownshipSharonGenoa TownshipGenoaOrange TownshipOrangeConcord TownshipConcordGranville TownshipGranvilleJerome TownshipJeromeWesterville City TownshipWesterville CityBerlin TownshipBerlinJefferson TownshipJeffersonNorwich TownshipNorwichWestervilleMifflin TownshipMifflinViolet TownshipVioletBlendon TownshipBlendonBloom TownshipBloomColumbus Metro AreaColumbus AreaColumbusDelaware City TownshipDelaware CityEtna TownshipHarrison TownshipHarrisonUnited States of AmericaUnited StatesColumbusJackson TownshipJacksonMidwestEast North CentralTruro TownshipTruroParis TownshipParisPataskalaOhioLicking CountyLickingUnion TownshipUnionMonroe TownshipMonroeMadison TownshipMadisonPleasant TownshipPleasantLiberty TownshipLibertyPrairie TownshipPrairieHarrison TownshipHarrisonNewarkHeathWalnut TownshipWalnutLancaster City TownshipLancaster CityFalls TownshipFallsCirclevilleLondonJefferson TownshipJeffersonWhitehallScioto TownshipSciotoPike TownshipHamilton TownshipHamiltonFranklin TownshipFranklin75.246997%75.246997%75.2%18,35518.4k174.092729%74.092729%74.1%5,737274.003905%74.003905%74.0%17,81217.8k371.521269%71.521269%71.5%4,960471.027168%71.027168%71.0%3,817566.605657%66.605657%66.6%12,00912.0k666.390215%66.390215%66.4%7,925765.470441%65.470441%65.5%10,70910.7k862.964830%62.964830%63.0%11,24311.2k962.954511%62.954511%63.0%4,1381062.828016%62.828016%62.8%3,3281157.038210%57.038210%57.0%2,8811256.824829%56.824829%56.8%3,4971356.415050%56.415050%56.4%2,4141455.429714%55.429714%55.4%4,1601553.460266%53.460266%53.5%12,60712.6k1651.127255%51.127255%51.1%10,20510.2k1743.925605%43.925605%43.9%11,05311.1k1843.657287%43.657287%43.7%11,41911.4k1936.203780%36.203780%36.2%2,2032035.924754%35.924754%35.9%2,1582134.785494%34.785494%34.8%460,194460k34.685843%34.685843%34.7%185,460185k2234.119545%34.119545%34.1%7,8262332.129442%32.129442%32.1%3,3362430.907866%30.907866%30.9%1,8352530.315023%30.315023%30.3%64,767,78764.8M29.663360%29.663360%29.7%1,8242628.997200%28.997200%29.0%8,6982728.952816%28.952816%29.0%13,118,64213.1M28.462853%28.462853%28.5%8,931,6868.93M27.878353%27.878353%27.9%5,0512827.476437%27.476437%27.5%4,4022926.968523%26.968523%27.0%2,7163026.667466%26.667466%26.7%2,092,8752.09M23.329326%23.329326%23.3%26,58426.6k23.109386%23.109386%23.1%1,3693122.894791%22.894791%22.9%1,1123221.373011%21.373011%21.4%3,6273321.075785%21.075785%21.1%1,0543420.469083%20.469083%20.5%1,0563518.790906%18.790906%18.8%2,1823618.668012%18.668012%18.7%9253718.053148%18.053148%18.1%5,7273817.438062%17.438062%17.4%1,2813916.880165%16.880165%16.9%8174016.462939%16.462939%16.5%4,4314116.198704%16.198704%16.2%1,2754215.715369%15.715369%15.7%1,4514313.952471%13.952471%14.0%9574413.620931%13.620931%13.6%6824512.671379%12.671379%12.7%1,4884611.056977%11.056977%11.1%8174710.048802%10.048802%10.0%453489.796482%9.796482%9.8%568499.038547%9.038547%9.0%61250

Very Advanced Degrees by County Subdivision#30

Percent of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).
Scope: population of the Monroe Township, selected other county subdivisions in the Columbus Area, and entities that contain the Monroe Township
0%5%10%15%Count#Upper ArlingtonBexleyPlain TownshipPlainGrandview HeightsGrandview HtsGranville TownshipGranvilleSharon TownshipSharonDublinLiberty TownshipLibertyJerome TownshipJeromeJefferson TownshipJeffersonConcord TownshipConcordOrange TownshipOrangeNorwich TownshipNorwichGenoa TownshipGenoaWestervilleWesterville City TownshipWesterville CityEtna TownshipBlendon TownshipBlendonColumbus Metro AreaColumbus AreaMifflin TownshipMifflinColumbusUnited States of AmericaUnited StatesBerlin TownshipBerlinDelaware City TownshipDelaware CityViolet TownshipVioletMidwestEast North CentralOhioBloom TownshipBloomUnion TownshipUnionLicking CountyLickingHarrison TownshipHarrisonParis TownshipParisTruro TownshipTruroJackson TownshipJacksonMadison TownshipMadisonMonroe TownshipMonroePataskalaWalnut TownshipWalnutColumbusLiberty TownshipLibertyNewarkHarrison TownshipHarrisonLancaster City TownshipLancaster CityHeathFalls TownshipFallsCirclevillePleasant TownshipPleasantPrairie TownshipPrairieLondonFranklin TownshipFranklinScioto TownshipSciotoPike TownshipJefferson TownshipJeffersonWhitehallHamilton TownshipHamilton16.893099%16.893099%16.9%4,066114.748805%14.748805%14.7%1,142214.534968%14.534968%14.5%1,008313.658355%13.658355%13.7%734413.196149%13.196149%13.2%699510.404624%10.404624%10.4%1,242610.031566%10.031566%10.0%2,44778.879645%8.879645%8.9%1,60188.156801%8.156801%8.2%41297.834777%7.834777%7.8%588107.333029%7.333029%7.3%482117.073253%7.073253%7.1%1,263126.632177%6.632177%6.6%1,564135.422755%5.422755%5.4%887145.145291%5.145291%5.1%1,027154.956126%4.956126%5.0%305164.256958%4.256958%4.3%442173.944125%3.944125%3.9%240183.620928%3.620928%3.6%47,90347.9k3.389898%3.389898%3.4%853193.357865%3.357865%3.4%17,95418.0k203.336158%3.336158%3.3%7,127,6737.13M3.108203%3.108203%3.1%133212.982081%2.982081%3.0%684222.940052%2.940052%2.9%769232.893416%2.893416%2.9%1,311,0191.31M2.855432%2.855432%2.9%896,039896k2.683241%2.683241%2.7%210,582211k2.596970%2.596970%2.6%156242.329507%2.329507%2.3%138252.283438%2.283438%2.3%2,6022.280525%2.280525%2.3%113262.159665%2.159665%2.2%346272.102881%2.102881%2.1%381282.063608%2.063608%2.1%619292.044785%2.044785%2.0%347302.038295%2.038295%2.0%99311.737663%1.737663%1.7%175321.611570%1.611570%1.6%78331.317287%1.317287%1.3%81341.221167%1.221167%1.2%63351.182108%1.182108%1.2%375361.162203%1.162203%1.2%69371.159205%1.159205%1.2%312381.157092%1.157092%1.2%85391.105323%1.105323%1.1%87401.093902%1.093902%1.1%101410.939812%0.939812%0.9%47420.878402%0.878402%0.9%102430.845604%0.845604%0.8%58440.827057%0.827057%0.8%56450.825551%0.825551%0.8%61460.621118%0.621118%0.6%28470.599161%0.599161%0.6%30480.425786%0.425786%0.4%50490.120731%0.120731%0.1%750

Under-Education Sex Ratio by County Subdivision#31

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 the Monroe Township, selected other county subdivisions in the Columbus Area, and entities that contain the Monroe Township
Female
Male
6x4x2x0x2xFM#BerlinPlainSciotoGrandview HtsJeffersonHarrisonPike TownshipConcordJeffersonFallsLibertyJeromeEtna TownshipFranklinUnionWhitehallDelaware CityHeathLondonPrairieLancaster CityMidwestEast North CentralMadisonHamiltonCirclevilleUnited StatesOhioColumbus AreaPataskalaColumbusLickingNewarkJacksonMifflinNorwichPleasantGenoaLibertyBexleyMonroeWestervilleBlendonUpper ArlingtonHarrisonBloomOrangeDublinTruroColumbusSharonWalnutVioletParisWesterville CityGranville-1.000000x-1.000000x3.534140x3.534140x3.53x1.220%1.22%4.310%4.31%1-1.000000x-1.000000x2.629883x2.629883x2.63x1.352%1.35%3.556%3.56%2-1.000000x-1.000000x2.609615x2.609615x2.61x9.040%9.04%23.590%23.6%3-1.000000x-1.000000x2.304788x2.304788x2.30x0.433%0.43%0.998%1.00%4-1.000000x-1.000000x2.116996x2.116996x2.12x1.925%1.92%4.074%4.07%5-1.000000x-1.000000x1.786905x1.786905x1.79x7.497%7.50%13.397%13.4%6-1.000000x-1.000000x1.742201x1.742201x1.74x14.389%14.4%25.069%25.1%7-1.000000x-1.000000x1.714595x1.714595x1.71x1.965%1.96%3.369%3.37%8-1.000000x-1.000000x1.507670x1.507670x1.51x9.251%9.25%13.947%13.9%9-1.000000x-1.000000x1.390745x1.390745x1.39x10.820%10.8%15.048%15.0%10-1.000000x-1.000000x1.376228x1.376228x1.38x5.385%5.38%7.410%7.41%11-1.000000x-1.000000x1.340740x1.340740x1.34x1.846%1.85%2.475%2.48%12-1.000000x-1.000000x1.335507x1.335507x1.34x6.236%6.24%8.328%8.33%13-1.000000x-1.000000x1.325542x1.325542x1.33x21.302%21.3%28.237%28.2%14-1.000000x-1.000000x1.310877x1.310877x1.31x11.876%11.9%15.568%15.6%15-1.000000x-1.000000x1.273148x1.273148x1.27x17.097%17.1%21.767%21.8%16-1.000000x-1.000000x1.236558x1.236558x1.24x5.780%5.78%7.147%7.15%17-1.000000x-1.000000x1.215459x1.215459x1.22x9.732%9.73%11.829%11.8%18-1.000000x-1.000000x1.184141x1.184141x1.18x12.791%12.8%15.147%15.1%19-1.000000x-1.000000x1.155189x1.155189x1.16x12.502%12.5%14.442%14.4%20-1.000000x-1.000000x1.144160x1.144160x1.14x11.593%11.6%13.265%13.3%21-1.000000x-1.000000x1.127915x1.127915x1.13x9.647%9.65%10.881%10.9%-1.000000x-1.000000x1.125371x1.125371x1.13x10.108%10.1%11.375%11.4%-1.000000x-1.000000x1.121607x1.121607x1.12x7.715%7.72%8.654%8.65%22-1.000000x-1.000000x1.118404x1.118404x1.12x15.081%15.1%16.867%16.9%23-1.000000x-1.000000x1.114300x1.114300x1.11x14.797%14.8%16.488%16.5%24-1.000000x-1.000000x1.109070x1.109070x1.11x12.369%12.4%13.719%13.7%-1.000000x-1.000000x1.105363x1.105363x1.11x10.008%10.0%11.063%11.1%-1.000000x-1.000000x1.104385x1.104385x1.10x8.867%8.87%9.793%9.79%-1.000000x-1.000000x1.079320x1.079320x1.08x7.269%7.27%7.845%7.85%25-1.000000x-1.000000x1.052237x1.052237x1.05x11.098%11.1%11.678%11.7%26-1.000000x-1.000000x1.041562x1.041562x1.04x9.421%9.42%9.813%9.81%-1.000000x-1.000000x1.036562x1.036562x1.04x12.733%12.7%13.198%13.2%27-1.000000x-1.000000x1.025236x1.025236x1.03x6.405%6.41%6.567%6.57%28-1.053306x-1.053306x1.05x1.000000x1.000000x5.733%5.73%5.442%5.44%29-1.057578x-1.057578x1.06x1.000000x1.000000x3.463%3.46%3.274%3.27%30-1.063491x-1.063491x1.06x1.000000x1.000000x13.412%13.4%12.612%12.6%31-1.064171x-1.064171x1.06x1.000000x1.000000x1.430%1.43%1.344%1.34%32-1.069669x-1.069669x1.07x1.000000x1.000000x1.786%1.79%1.670%1.67%33-1.073251x-1.073251x1.07x1.000000x1.000000x2.308%2.31%2.151%2.15%34-1.086161x-1.086161x1.09x1.000000x1.000000x10.956%11.0%10.086%10.1%35-1.099069x-1.099069x1.10x1.000000x1.000000x3.830%3.83%3.485%3.48%36-1.159243x-1.159243x1.16x1.000000x1.000000x8.950%8.95%7.720%7.72%37-1.283067x-1.283067x1.28x1.000000x1.000000x1.500%1.50%1.169%1.17%38-1.294968x-1.294968x1.29x1.000000x1.000000x6.211%6.21%4.797%4.80%39-1.306893x-1.306893x1.31x1.000000x1.000000x4.213%4.21%3.224%3.22%40-1.310439x-1.310439x1.31x1.000000x1.000000x1.935%1.93%1.476%1.48%41-1.385029x-1.385029x1.39x1.000000x1.000000x2.028%2.03%1.464%1.46%42-1.414047x-1.414047x1.41x1.000000x1.000000x8.025%8.03%5.675%5.68%43-1.455501x-1.455501x1.46x1.000000x1.000000x7.866%7.87%5.404%5.40%44-1.481750x-1.481750x1.48x1.000000x1.000000x2.283%2.28%1.540%1.54%45-1.494722x-1.494722x1.49x1.000000x1.000000x13.851%13.9%9.267%9.27%46-1.798212x-1.798212x1.80x1.000000x1.000000x5.036%5.04%2.800%2.80%47-2.016419x-2.016419x2.02x1.000000x1.000000x12.927%12.9%6.411%6.41%48-2.172632x-2.172632x2.17x1.000000x1.000000x3.024%3.02%1.392%1.39%49-7.570273x-7.570273x7.57x1.000000x1.000000x2.883%2.88%0.381%0.38%50

Over-Education Sex Ratio by County Subdivision#32

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 the Monroe Township, selected other county subdivisions in the Columbus Area, and entities that contain the Monroe Township
Female
Male
0x5x10xFM#FallsLondonHamiltonJeffersonPike TownshipPleasantLibertyCirclevilleColumbusDelaware CityLancaster CityWestervilleBloomSharonHarrisonHeathWalnutHarrisonLibertyMifflinNewarkJeromeConcordGranvillePlainDublinFranklinUpper ArlingtonNorwichTruroOhioBexleyJeffersonEast North CentralMidwestMadisonColumbus AreaUnited StatesLickingEtna TownshipBlendonBerlinColumbusOrangeJacksonGrandview HtsVioletGenoaPrairieMonroeParisWesterville CityPataskalaUnionWhitehallScioto-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%2.367%2.37%1-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%1.830%1.83%2-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%0.247%0.25%3-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%1.227%1.23%4-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%1.293%1.29%5-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%1.906%1.91%6-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.220%0.22%2.347%2.35%7-1.000000x-1.000000x4.574814x4.574814x4.57x0.400%0.40%1.830%1.83%8-1.000000x-1.000000x3.824499x3.824499x3.82x0.573%0.57%2.190%2.19%9-1.000000x-1.000000x2.782910x2.782910x2.78x1.613%1.61%4.490%4.49%10-1.000000x-1.000000x2.442537x2.442537x2.44x0.692%0.69%1.690%1.69%11-1.000000x-1.000000x2.420464x2.420464x2.42x3.120%3.12%7.551%7.55%12-1.000000x-1.000000x2.407434x2.407434x2.41x1.517%1.52%3.651%3.65%13-1.000000x-1.000000x2.352477x2.352477x2.35x6.431%6.43%15.129%15.1%14-1.000000x-1.000000x2.344320x2.344320x2.34x1.401%1.40%3.284%3.28%15-1.000000x-1.000000x2.253443x2.253443x2.25x0.733%0.73%1.652%1.65%16-1.000000x-1.000000x2.251208x2.251208x2.25x1.014%1.01%2.284%2.28%17-1.000000x-1.000000x2.203299x2.203299x2.20x0.721%0.72%1.588%1.59%18-1.000000x-1.000000x2.163540x2.163540x2.16x5.691%5.69%12.313%12.3%19-1.000000x-1.000000x2.069018x2.069018x2.07x2.252%2.25%4.660%4.66%20-1.000000x-1.000000x1.967904x1.967904x1.97x0.822%0.82%1.618%1.62%21-1.000000x-1.000000x1.911908x1.911908x1.91x5.617%5.62%10.739%10.7%22-1.000000x-1.000000x1.876463x1.876463x1.88x5.109%5.11%9.587%9.59%23-1.000000x-1.000000x1.849712x1.849712x1.85x9.285%9.28%17.174%17.2%24-1.000000x-1.000000x1.848477x1.848477x1.85x10.213%10.2%18.878%18.9%25-1.000000x-1.000000x1.832511x1.832511x1.83x7.149%7.15%13.100%13.1%26-1.000000x-1.000000x1.821032x1.821032x1.82x0.581%0.58%1.057%1.06%27-1.000000x-1.000000x1.802942x1.802942x1.80x12.297%12.3%22.171%22.2%28-1.000000x-1.000000x1.734085x1.734085x1.73x4.889%4.89%8.478%8.48%29-1.000000x-1.000000x1.688068x1.688068x1.69x1.599%1.60%2.699%2.70%30-1.000000x-1.000000x1.669500x1.669500x1.67x2.031%2.03%3.391%3.39%-1.000000x-1.000000x1.622554x1.622554x1.62x11.419%11.4%18.528%18.5%31-1.000000x-1.000000x1.599641x1.599641x1.60x6.082%6.08%9.728%9.73%32-1.000000x-1.000000x1.597848x1.597848x1.60x2.216%2.22%3.541%3.54%-1.000000x-1.000000x1.589934x1.589934x1.59x2.251%2.25%3.579%3.58%-1.000000x-1.000000x1.576121x1.576121x1.58x1.610%1.61%2.537%2.54%33-1.000000x-1.000000x1.567060x1.567060x1.57x2.842%2.84%4.454%4.45%-1.000000x-1.000000x1.526215x1.526215x1.53x2.660%2.66%4.060%4.06%-1.000000x-1.000000x1.469621x1.469621x1.47x1.863%1.86%2.738%2.74%-1.000000x-1.000000x1.457364x1.457364x1.46x3.489%3.49%5.085%5.09%34-1.000000x-1.000000x1.449489x1.449489x1.45x3.282%3.28%4.757%4.76%35-1.000000x-1.000000x1.429540x1.429540x1.43x2.575%2.57%3.680%3.68%36-1.000000x-1.000000x1.413654x1.413654x1.41x2.801%2.80%3.959%3.96%37-1.000000x-1.000000x1.412405x1.412405x1.41x5.901%5.90%8.334%8.33%38-1.000000x-1.000000x1.297270x1.297270x1.30x1.812%1.81%2.351%2.35%39-1.000000x-1.000000x1.232696x1.232696x1.23x12.274%12.3%15.131%15.1%40-1.000000x-1.000000x1.149458x1.149458x1.15x2.746%2.75%3.157%3.16%41-1.000000x-1.000000x1.125108x1.125108x1.13x5.111%5.11%5.751%5.75%42-1.004340x-1.004340x1.00x1.000000x1.000000x0.880%0.88%0.876%0.88%43-1.020828x-1.020828x1.02x1.000000x1.000000x2.059%2.06%2.017%2.02%44-1.182723x-1.182723x1.18x1.000000x1.000000x2.307%2.31%1.950%1.95%45-1.269877x-1.269877x1.27x1.000000x1.000000x5.517%5.52%4.345%4.34%46-1.270588x-1.270588x1.27x1.000000x1.000000x1.928%1.93%1.518%1.52%47-1.311831x-1.311831x1.31x1.000000x1.000000x2.651%2.65%2.021%2.02%48-1.806191x-1.806191x1.81x1.000000x1.000000x0.542%0.54%0.300%0.30%49-2.735243x-2.735243x2.74x1.000000x1.000000x1.507%1.51%0.551%0.55%50

Educational Attainment by County Subdivision in Ohio

There are 1,606 county subdivisions in Ohio. This section compares the Monroe Township to the 50 most populous county subdivisions in Ohio and to those entities that contain or substantially overlap with the Monroe Township. The least populous of the compared county subdivisions has a population of 36,945.

No H.S. Diploma by County Subdivision#33

Percent of population 25 years of age and older without a high school diploma (or equivalent).
Scope: population of the Monroe Township, selected other county subdivisions in Ohio, and entities that contain the Monroe Township
0%5%10%15%20%Count#ClevelandMiddletownLorainYoungstownSpringfieldDaytonMansfieldLimaMarion TownshipMarionCantonHamiltonWarrenToledoCincinnatiAkronElyriaUnited States of AmericaUnited StatesNewarkBath TownshipLancaster City TownshipLancaster CityColumbusColerain TownshipColerainEast North CentralEuclidMonroe TownshipMonroeOhioMidwestParmaLicking CountyLickingColumbus Metro AreaColumbus AreaFindlayFairfieldMiami TownshipMiamiUnion TownshipUnionHuber HeightsJackson TownshipJacksonCleveland HeightsCleveland HtsCuyahoga FallsPlain TownshipPlainLakewoodKetteringGreen TownshipGrnBoardman TownshipBoardmanWest Chester TownshipW ChesterMiami TownshipMiamiMifflin TownshipMifflinMentorLiberty TownshipLibertySylvania TownshipSylvaniaStrongsvilleViolet TownshipVioletJackson TownshipJacksonWashington TownshipWashingtonAnderson TownshipAndersonDeerfield TownshipDeerfieldBeavercreek TownshipBeavercreekDublin21.582420%21.582420%21.6%54,98155.0k118.211726%18.211726%18.2%5,591217.551080%17.551080%17.6%7,207316.999061%16.999061%17.0%7,424416.947843%16.947843%16.9%6,580516.928359%16.928359%16.9%14,88914.9k616.499446%16.499446%16.5%5,361716.278163%16.278163%16.3%3,757815.742056%15.742056%15.7%4,875915.631958%15.631958%15.6%7,3021015.293656%15.293656%15.3%6,2341115.055107%15.055107%15.1%4,0981214.332972%14.332972%14.3%26,34326.3k1313.761583%13.761583%13.8%26,28626.3k1413.591726%13.591726%13.6%17,95118.0k1513.343328%13.343328%13.3%4,8061613.020590%13.020590%13.0%27,818,38027.8M12.943290%12.943290%12.9%4,1061712.411362%12.411362%12.4%3,0631812.375999%12.375999%12.4%3,3311911.376979%11.376979%11.4%60,83160.8k2010.847918%10.847918%10.8%4,3142110.719464%10.719464%10.7%3,363,7843.36M10.656581%10.656581%10.7%3,5222210.520898%10.520898%10.5%51110.514146%10.514146%10.5%825,155825k10.244520%10.244520%10.2%4,641,8354.64M9.939137%9.939137%9.9%5,683239.609394%9.609394%9.6%10,95011.0k9.314501%9.314501%9.3%123,226123k9.003845%9.003845%9.0%2,482248.712972%8.712972%8.7%2,559258.614662%8.614662%8.6%3,080268.597523%8.597523%8.6%2,777277.261193%7.261193%7.3%1,797286.480864%6.480864%6.5%1,944296.307136%6.307136%6.3%1,918306.197364%6.197364%6.2%2,215316.171554%6.171554%6.2%2,311326.109570%6.109570%6.1%2,246335.953744%5.953744%6.0%2,340345.804316%5.804316%5.8%2,402355.764815%5.764815%5.8%1,682365.727981%5.727981%5.7%2,390375.628396%5.628396%5.6%1,554385.595517%5.595517%5.6%1,408395.268752%5.268752%5.3%1,834405.136204%5.136204%5.1%1,169414.322119%4.322119%4.3%1,462424.066023%4.066023%4.1%1,313433.979966%3.979966%4.0%1,041443.830735%3.830735%3.8%1,118453.637690%3.637690%3.6%1,496463.351036%3.351036%3.4%978473.293195%3.293195%3.3%815483.105178%3.105178%3.1%1,170491.754602%1.754602%1.8%42850

Bachelor's Degrees by County Subdivision#34

Percent of population 25 years of age and older with a bachelor's degree or higher..
Scope: population of the Monroe Township, selected other county subdivisions in Ohio, and entities that contain the Monroe Township
0%20%40%60%Count#DublinDeerfield TownshipDeerfieldAnderson TownshipAndersonWashington TownshipWashingtonBeavercreek TownshipBeavercreekCleveland HeightsCleveland HtsLiberty TownshipLibertyWest Chester TownshipW ChesterSylvania TownshipSylvaniaStrongsvilleMifflin TownshipMifflinViolet TownshipVioletLakewoodMiami TownshipMiamiJackson TownshipJacksonColumbus Metro AreaColumbus AreaColumbusCincinnatiKetteringPlain TownshipPlainGreen TownshipGrnCuyahoga FallsMentorBoardman TownshipBoardmanUnited States of AmericaUnited StatesUnion TownshipUnionJackson TownshipJacksonMidwestEast North CentralFairfieldBath TownshipFindlayMiami TownshipMiamiOhioLicking CountyLickingMonroe TownshipMonroeHuber HeightsColerain TownshipColerainEuclidAkronParmaNewarkToledoDaytonMiddletownLancaster City TownshipLancaster CityClevelandElyriaHamiltonSpringfieldCantonMansfieldWarrenYoungstownLorainLimaMarion TownshipMarion75.246997%75.246997%75.2%18,35518.4k157.851139%57.851139%57.9%14,31714.3k256.039061%56.039061%56.0%16,35516.4k352.483891%52.483891%52.5%21,58421.6k451.261976%51.261976%51.3%19,31519.3k550.973364%50.973364%51.0%15,50115.5k650.549209%50.549209%50.5%11,50511.5k747.424805%47.424805%47.4%19,78819.8k846.115414%46.115414%46.1%15,59915.6k944.614765%44.614765%44.6%14,40714.4k1043.925605%43.925605%43.9%11,05311.1k1143.657287%43.657287%43.7%11,41911.4k1243.651053%43.651053%43.7%16,04716.0k1342.654835%42.654835%42.7%11,77711.8k1441.432243%41.432243%41.4%12,09212.1k1534.785494%34.785494%34.8%460,194460k34.685843%34.685843%34.7%185,460185k1633.783048%33.783048%33.8%64,52964.5k1733.391853%33.391853%33.4%13,12413.1k1833.138386%33.138386%33.1%12,40912.4k1932.914482%32.914482%32.9%13,62113.6k2032.380180%32.380180%32.4%11,57311.6k2132.238789%32.238789%32.2%11,22211.2k2231.219796%31.219796%31.2%9,1092330.315023%30.315023%30.3%64,767,78764.8M29.613003%29.613003%29.6%9,5652428.997200%28.997200%29.0%8,6982528.952816%28.952816%29.0%13,118,64213.1M28.462853%28.462853%28.5%8,931,6868.93M28.219271%28.219271%28.2%8,2882626.954091%26.954091%27.0%6,6522726.775738%26.775738%26.8%7,3812826.713842%26.713842%26.7%9,5512926.667466%26.667466%26.7%2,092,8752.09M23.329326%23.329326%23.3%26,58426.6k22.894791%22.894791%22.9%1,11222.834168%22.834168%22.8%5,6513021.665661%21.665661%21.7%8,6163120.614221%20.614221%20.6%6,8133220.213821%20.213821%20.2%26,69726.7k3319.988457%19.988457%20.0%11,42911.4k3418.053148%18.053148%18.1%5,7273518.048021%18.048021%18.0%33,17133.2k3617.635555%17.635555%17.6%15,51115.5k3716.631922%16.631922%16.6%5,1063816.462939%16.462939%16.5%4,4313916.073076%16.073076%16.1%40,94640.9k4015.411739%15.411739%15.4%5,5514115.075315%15.075315%15.1%6,1454214.851256%14.851256%14.9%5,7664314.608666%14.608666%14.6%6,8244413.812631%13.812631%13.8%4,4884512.832476%12.832476%12.8%3,4934612.044055%12.044055%12.0%5,2604711.718579%11.718579%11.7%4,8124811.460139%11.460139%11.5%2,6454910.478559%10.478559%10.5%3,24550

Very Advanced Degrees by County Subdivision#35

Percent of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).
Scope: population of the Monroe Township, selected other county subdivisions in Ohio, and entities that contain the Monroe Township
0%2%4%6%8%10%Count#Cleveland HeightsCleveland HtsDublinAnderson TownshipAndersonSylvania TownshipSylvaniaWashington TownshipWashingtonBeavercreek TownshipBeavercreekJackson TownshipJacksonLakewoodCincinnatiStrongsvilleDeerfield TownshipDeerfieldWest Chester TownshipW ChesterKetteringColumbus Metro AreaColumbus AreaLiberty TownshipLibertyMifflin TownshipMifflinColumbusUnited States of AmericaUnited StatesPlain TownshipPlainBoardman TownshipBoardmanViolet TownshipVioletMiami TownshipMiamiMidwestEast North CentralOhioCuyahoga FallsGreen TownshipGrnBath TownshipLicking CountyLickingAkronJackson TownshipJacksonMonroe TownshipMonroeClevelandMentorColerain TownshipColerainMiami TownshipMiamiFindlayToledoSpringfieldFairfieldEuclidHuber HeightsLimaDaytonCantonHamiltonUnion TownshipUnionParmaNewarkLancaster City TownshipLancaster CityMansfieldMiddletownLorainElyriaYoungstownWarrenMarion TownshipMarion10.753042%10.753042%10.8%3,270110.031566%10.031566%10.0%2,44727.476443%7.476443%7.5%2,18237.470585%7.470585%7.5%2,52746.820669%6.820669%6.8%2,80556.685422%6.685422%6.7%2,51965.297242%5.297242%5.3%1,54675.051412%5.051412%5.1%1,85784.729595%4.729595%4.7%9,03494.555308%4.555308%4.6%1,471104.149830%4.149830%4.1%1,027114.100659%4.100659%4.1%1,711123.778338%3.778338%3.8%1,485133.620928%3.620928%3.6%47,90347.9k3.514938%3.514938%3.5%800143.389898%3.389898%3.4%853153.357865%3.357865%3.4%17,95418.0k163.336158%3.336158%3.3%7,127,6737.13M3.036372%3.036372%3.0%1,137172.957809%2.957809%3.0%863182.940052%2.940052%2.9%769192.911988%2.911988%2.9%804202.893416%2.893416%2.9%1,311,0191.31M2.855432%2.855432%2.9%896,039896k2.683241%2.683241%2.7%210,582211k2.481744%2.481744%2.5%887212.476862%2.476862%2.5%1,025222.451477%2.451477%2.5%605232.283438%2.283438%2.3%2,6022.163955%2.163955%2.2%2,858242.063608%2.063608%2.1%619252.038295%2.038295%2.0%991.927780%1.927780%1.9%4,911261.815622%1.815622%1.8%632271.815530%1.815530%1.8%722281.762090%1.762090%1.8%630291.675978%1.675978%1.7%462301.642065%1.642065%1.6%3,018311.545396%1.545396%1.5%600321.477698%1.477698%1.5%434331.388805%1.388805%1.4%459341.349604%1.349604%1.3%334351.304159%1.304159%1.3%301361.257490%1.257490%1.3%1,106371.245933%1.245933%1.2%582381.241352%1.241352%1.2%506391.238390%1.238390%1.2%400401.236490%1.236490%1.2%707411.182108%1.182108%1.2%375421.159205%1.159205%1.2%312431.104887%1.104887%1.1%359440.996743%0.996743%1.0%306450.964372%0.964372%1.0%396460.952302%0.952302%1.0%343470.794541%0.794541%0.8%347480.742101%0.742101%0.7%202490.720098%0.720098%0.7%22350

Under-Education Sex Ratio by County Subdivision#36

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 the Monroe Township, selected other county subdivisions in Ohio, and entities that contain the Monroe Township
Female
Male
1x0x1xFM#AndersonMansfieldCleveland HtsBeavercreekUnionToledoFindlayLorainMarionYoungstownColerainGrnFairfieldElyriaMiddletownLancaster CityMidwestEast North CentralSpringfieldWarrenDaytonCantonUnited StatesOhioColumbus AreaLimaParmaColumbusClevelandDeerfieldLickingMentorNewarkW ChesterPlainLibertyJacksonHuber HeightsHamiltonJacksonCincinnatiAkronMifflinSylvaniaMiamiEuclidMonroeMiamiCuyahoga FallsStrongsvilleLakewoodBath TownshipDublinKetteringWashingtonBoardmanViolet-1.000000x-1.000000x1.766803x1.766803x1.77x2.468%2.47%4.360%4.36%1-1.000000x-1.000000x1.592708x1.592708x1.59x12.530%12.5%19.956%20.0%2-1.000000x-1.000000x1.485471x1.485471x1.49x5.146%5.15%7.645%7.64%3-1.000000x-1.000000x1.332397x1.332397x1.33x2.666%2.67%3.552%3.55%4-1.000000x-1.000000x1.242595x1.242595x1.24x7.704%7.70%9.573%9.57%5-1.000000x-1.000000x1.227011x1.227011x1.23x12.945%12.9%15.884%15.9%6-1.000000x-1.000000x1.222843x1.222843x1.22x8.133%8.13%9.946%9.95%7-1.000000x-1.000000x1.207850x1.207850x1.21x16.045%16.0%19.380%19.4%8-1.000000x-1.000000x1.204406x1.204406x1.20x14.131%14.1%17.020%17.0%9-1.000000x-1.000000x1.194114x1.194114x1.19x15.554%15.6%18.574%18.6%10-1.000000x-1.000000x1.175447x1.175447x1.18x10.032%10.0%11.792%11.8%11-1.000000x-1.000000x1.173903x1.173903x1.17x5.370%5.37%6.304%6.30%12-1.000000x-1.000000x1.173628x1.173628x1.17x8.033%8.03%9.428%9.43%13-1.000000x-1.000000x1.166450x1.166450x1.17x12.379%12.4%14.439%14.4%14-1.000000x-1.000000x1.147049x1.147049x1.15x17.010%17.0%19.512%19.5%15-1.000000x-1.000000x1.144160x1.144160x1.14x11.593%11.6%13.265%13.3%16-1.000000x-1.000000x1.127915x1.127915x1.13x9.647%9.65%10.881%10.9%-1.000000x-1.000000x1.125371x1.125371x1.13x10.108%10.1%11.375%11.4%-1.000000x-1.000000x1.124452x1.124452x1.12x16.027%16.0%18.022%18.0%17-1.000000x-1.000000x1.124390x1.124390x1.12x14.230%14.2%16.000%16.0%18-1.000000x-1.000000x1.114342x1.114342x1.11x16.070%16.1%17.907%17.9%19-1.000000x-1.000000x1.109752x1.109752x1.11x14.885%14.9%16.518%16.5%20-1.000000x-1.000000x1.109070x1.109070x1.11x12.369%12.4%13.719%13.7%-1.000000x-1.000000x1.105363x1.105363x1.11x10.008%10.0%11.063%11.1%-1.000000x-1.000000x1.104385x1.104385x1.10x8.867%8.87%9.793%9.79%-1.000000x-1.000000x1.087544x1.087544x1.09x15.592%15.6%16.957%17.0%21-1.000000x-1.000000x1.081824x1.081824x1.08x9.568%9.57%10.350%10.4%22-1.000000x-1.000000x1.052237x1.052237x1.05x11.098%11.1%11.678%11.7%23-1.000000x-1.000000x1.046686x1.046686x1.05x21.119%21.1%22.105%22.1%24-1.000000x-1.000000x1.045216x1.045216x1.05x3.224%3.22%3.370%3.37%25-1.000000x-1.000000x1.041562x1.041562x1.04x9.421%9.42%9.813%9.81%-1.000000x-1.000000x1.038813x1.038813x1.04x5.175%5.17%5.376%5.38%26-1.000000x-1.000000x1.036562x1.036562x1.04x12.733%12.7%13.198%13.2%27-1.000000x-1.000000x1.031821x1.031821x1.03x5.641%5.64%5.821%5.82%28-1.000000x-1.000000x1.027725x1.027725x1.03x6.093%6.09%6.262%6.26%29-1.000000x-1.000000x1.026192x1.026192x1.03x5.072%5.07%5.205%5.20%30-1.000000x-1.000000x1.025236x1.025236x1.03x6.405%6.41%6.567%6.57%31-1.000000x-1.000000x1.021443x1.021443x1.02x7.189%7.19%7.344%7.34%32-1.000000x-1.000000x1.015682x1.015682x1.02x15.182%15.2%15.420%15.4%33-1.000000x-1.000000x1.006889x1.006889x1.01x3.818%3.82%3.844%3.84%34-1.000000x-1.000000x1.001229x1.001229x1.00x13.754%13.8%13.771%13.8%35-1.001506x-1.001506x1.00x1.000000x1.000000x13.601%13.6%13.581%13.6%36-1.053306x-1.053306x1.05x1.000000x1.000000x5.733%5.73%5.442%5.44%37-1.068860x-1.068860x1.07x1.000000x1.000000x4.454%4.45%4.167%4.17%38-1.075183x-1.075183x1.08x1.000000x1.000000x5.828%5.83%5.420%5.42%39-1.084060x-1.084060x1.08x1.000000x1.000000x11.029%11.0%10.174%10.2%40-1.086161x-1.086161x1.09x1.000000x1.000000x10.956%11.0%10.086%10.1%-1.123601x-1.123601x1.12x1.000000x1.000000x9.091%9.09%8.091%8.09%41-1.132510x-1.132510x1.13x1.000000x1.000000x6.567%6.57%5.799%5.80%42-1.209810x-1.209810x1.21x1.000000x1.000000x4.433%4.43%3.664%3.66%43-1.275391x-1.275391x1.28x1.000000x1.000000x6.820%6.82%5.347%5.35%44-1.295653x-1.295653x1.30x1.000000x1.000000x13.964%14.0%10.778%10.8%45-1.385029x-1.385029x1.39x1.000000x1.000000x2.028%2.03%1.464%1.46%46-1.505212x-1.505212x1.51x1.000000x1.000000x7.040%7.04%4.677%4.68%47-1.641786x-1.641786x1.64x1.000000x1.000000x4.457%4.46%2.715%2.71%48-1.660386x-1.660386x1.66x1.000000x1.000000x7.066%7.07%4.256%4.26%49-1.798212x-1.798212x1.80x1.000000x1.000000x5.036%5.04%2.800%2.80%50

Over-Education Sex Ratio by County Subdivision#37

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 the Monroe Township, selected other county subdivisions in Ohio, and entities that contain the Monroe Township
Female
Male
1x0x1x2x3xFM#ElyriaSpringfieldWashingtonYoungstownBoardmanLorainMiddletownLancaster CityFindlayAndersonJacksonKetteringMifflinPlainBeavercreekDeerfieldDaytonNewarkEuclidMiamiAkronDublinSylvaniaStrongsvilleBath TownshipOhioFairfieldMansfieldW ChesterHuber HeightsLakewoodEast North CentralMidwestColumbus AreaWarrenUnited StatesLibertyLickingParmaCleveland HtsColumbusUnionMentorGrnJacksonClevelandCincinnatiMiamiMarionVioletColerainToledoHamiltonMonroeCantonCuyahoga FallsLima-1.000000x-1.000000x3.557903x3.557903x3.56x0.433%0.43%1.542%1.54%1-1.000000x-1.000000x3.025650x3.025650x3.03x0.799%0.80%2.417%2.42%2-1.000000x-1.000000x2.977263x2.977263x2.98x3.534%3.53%10.523%10.5%3-1.000000x-1.000000x2.809581x2.809581x2.81x0.426%0.43%1.196%1.20%4-1.000000x-1.000000x2.780060x2.780060x2.78x1.621%1.62%4.507%4.51%5-1.000000x-1.000000x2.695011x2.695011x2.70x0.546%0.55%1.472%1.47%6-1.000000x-1.000000x2.596948x2.596948x2.60x0.564%0.56%1.465%1.46%7-1.000000x-1.000000x2.442537x2.442537x2.44x0.692%0.69%1.690%1.69%8-1.000000x-1.000000x2.437656x2.437656x2.44x0.991%0.99%2.417%2.42%9-1.000000x-1.000000x2.428350x2.428350x2.43x4.486%4.49%10.893%10.9%10-1.000000x-1.000000x2.183841x2.183841x2.18x3.386%3.39%7.394%7.39%11-1.000000x-1.000000x2.155653x2.155653x2.16x2.468%2.47%5.319%5.32%12-1.000000x-1.000000x2.069018x2.069018x2.07x2.252%2.25%4.660%4.66%13-1.000000x-1.000000x2.024516x2.024516x2.02x2.059%2.06%4.169%4.17%14-1.000000x-1.000000x2.007898x2.007898x2.01x4.457%4.46%8.948%8.95%15-1.000000x-1.000000x1.991550x1.991550x1.99x2.826%2.83%5.628%5.63%16-1.000000x-1.000000x1.989047x1.989047x1.99x0.860%0.86%1.711%1.71%17-1.000000x-1.000000x1.967904x1.967904x1.97x0.822%0.82%1.618%1.62%18-1.000000x-1.000000x1.903271x1.903271x1.90x0.997%1.00%1.897%1.90%19-1.000000x-1.000000x1.851159x1.851159x1.85x2.056%2.06%3.806%3.81%20-1.000000x-1.000000x1.846298x1.846298x1.85x1.550%1.55%2.862%2.86%21-1.000000x-1.000000x1.832511x1.832511x1.83x7.149%7.15%13.100%13.1%22-1.000000x-1.000000x1.805502x1.805502x1.81x5.447%5.45%9.835%9.84%23-1.000000x-1.000000x1.769961x1.769961x1.77x3.331%3.33%5.895%5.90%24-1.000000x-1.000000x1.691857x1.691857x1.69x1.833%1.83%3.102%3.10%25-1.000000x-1.000000x1.669500x1.669500x1.67x2.031%2.03%3.391%3.39%-1.000000x-1.000000x1.650680x1.650680x1.65x1.122%1.12%1.852%1.85%26-1.000000x-1.000000x1.650301x1.650301x1.65x0.820%0.82%1.353%1.35%27-1.000000x-1.000000x1.648570x1.648570x1.65x3.124%3.12%5.150%5.15%28-1.000000x-1.000000x1.627164x1.627164x1.63x1.044%1.04%1.699%1.70%29-1.000000x-1.000000x1.624128x1.624128x1.62x3.883%3.88%6.306%6.31%30-1.000000x-1.000000x1.597848x1.597848x1.60x2.216%2.22%3.541%3.54%-1.000000x-1.000000x1.589934x1.589934x1.59x2.251%2.25%3.579%3.58%-1.000000x-1.000000x1.567060x1.567060x1.57x2.842%2.84%4.454%4.45%-1.000000x-1.000000x1.543502x1.543502x1.54x0.592%0.59%0.914%0.91%31-1.000000x-1.000000x1.526215x1.526215x1.53x2.660%2.66%4.060%4.06%-1.000000x-1.000000x1.525512x1.525512x1.53x2.801%2.80%4.272%4.27%32-1.000000x-1.000000x1.469621x1.469621x1.47x1.863%1.86%2.738%2.74%-1.000000x-1.000000x1.433883x1.433883x1.43x1.025%1.03%1.470%1.47%33-1.000000x-1.000000x1.416609x1.416609x1.42x9.009%9.01%12.763%12.8%34-1.000000x-1.000000x1.413654x1.413654x1.41x2.801%2.80%3.959%3.96%35-1.000000x-1.000000x1.348352x1.348352x1.35x1.062%1.06%1.431%1.43%36-1.000000x-1.000000x1.325696x1.325696x1.33x1.576%1.58%2.089%2.09%37-1.000000x-1.000000x1.319751x1.319751x1.32x2.156%2.16%2.845%2.85%38-1.000000x-1.000000x1.297270x1.297270x1.30x1.812%1.81%2.351%2.35%39-1.000000x-1.000000x1.286599x1.286599x1.29x1.699%1.70%2.186%2.19%40-1.000000x-1.000000x1.280610x1.280610x1.28x4.179%4.18%5.351%5.35%41-1.000000x-1.000000x1.246667x1.246667x1.25x1.577%1.58%1.966%1.97%42-1.000000x-1.000000x1.217109x1.217109x1.22x0.642%0.64%0.782%0.78%43-1.000000x-1.000000x1.149458x1.149458x1.15x2.746%2.75%3.157%3.16%44-1.000000x-1.000000x1.145376x1.145376x1.15x1.701%1.70%1.948%1.95%45-1.000000x-1.000000x1.141406x1.141406x1.14x1.539%1.54%1.757%1.76%46-1.000000x-1.000000x1.036455x1.036455x1.04x1.220%1.22%1.265%1.26%47-1.020828x-1.020828x1.02x1.000000x1.000000x2.059%2.06%2.017%2.02%-1.103703x-1.103703x1.10x1.000000x1.000000x1.302%1.30%1.180%1.18%48-1.188945x-1.188945x1.19x1.000000x1.000000x2.687%2.69%2.260%2.26%49-1.404867x-1.404867x1.40x1.000000x1.000000x1.525%1.53%1.086%1.09%50

Educational Attainment by County Subdivision in the Midwest

There are 19,478 county subdivisions in the Midwest. This section compares the Monroe Township to the 50 most populous county subdivisions in the Midwest and to those entities that contain or substantially overlap with the Monroe Township. The least populous of the compared county subdivisions has a population of 112,821.

No H.S. Diploma by County Subdivision#38

Percent of population 25 years of age and older without a high school diploma (or equivalent).
Scope: population of the Monroe Township, selected other county subdivisions in the Midwest, and entities that contain the Monroe Township
0%10%20%30%Count#Aurora TownshipAuroraCenter TownshipCtrKansas CityClevelandWayne TownshipWayneDetroitMilwaukeeNorth TownshipNDaytonChicagoProviso TownshipProvisoRockford TownshipRockfordSt. LouisWarrenGrand RapidsToledoBlue TownshipCincinnatiAkronSt. PaulSterling HeightsSterling HtsUnited States of AmericaUnited StatesThornton TownshipThorntonWichitaKaw TownshipOmahaBloomingdale TownshipBloomingdaleColumbusMaine TownshipMaineTopekaMinneapolisSpringfield TownshipSpringfieldEast North CentralWorth TownshipWorthMonroe TownshipMonroeOhioMidwestLawrence TownshipLawrenceSioux FallsLicking CountyLickingColumbus Metro AreaColumbus AreaCapital TownshipCapitalWheeling TownshipWheelingPalatine TownshipPalatineSchaumburg TownshipSchaumburgLincolnWashington TownshipWashingtonOlatheFargoCedar RapidsYork TownshipMilton TownshipMiltonMadisonDowners Grove TownshipDowners GrvLisle TownshipLisleOverland ParkAnn Arbor33.464284%33.464284%33.5%29,81429.8k123.165532%23.165532%23.2%22,92622.9k222.659362%22.659362%22.7%21,21821.2k321.582420%21.582420%21.6%54,98155.0k421.037720%21.037720%21.0%18,48918.5k521.003600%21.003600%21.0%90,67890.7k617.485105%17.485105%17.5%63,80063.8k717.062713%17.062713%17.1%17,39117.4k816.928359%16.928359%16.9%14,88914.9k916.905373%16.905373%16.9%309,770310k1015.636222%15.636222%15.6%16,11016.1k1115.608074%15.608074%15.6%18,24118.2k1215.466266%15.466266%15.5%33,80433.8k1315.286174%15.286174%15.3%14,05914.1k1414.563179%14.563179%14.6%17,64317.6k1514.332972%14.332972%14.3%26,34326.3k1614.241047%14.241047%14.2%15,25815.3k1713.761583%13.761583%13.8%26,28626.3k1813.591726%13.591726%13.6%17,95118.0k1913.278342%13.278342%13.3%24,61324.6k2013.132171%13.132171%13.1%12,21212.2k2113.020590%13.020590%13.0%27,818,38027.8M12.974232%12.974232%13.0%14,37014.4k2212.568464%12.568464%12.6%31,23131.2k2312.455744%12.455744%12.5%15,16315.2k2412.198899%12.198899%12.2%35,05035.1k2512.171847%12.171847%12.2%9,3752611.376979%11.376979%11.4%60,83160.8k2711.132206%11.132206%11.1%10,96511.0k2811.032803%11.032803%11.0%9,3772910.958428%10.958428%11.0%29,34729.3k3010.767091%10.767091%10.8%11,14911.1k3110.719464%10.719464%10.7%3,363,7843.36M10.678962%10.678962%10.7%11,17511.2k3210.520898%10.520898%10.5%51110.514146%10.514146%10.5%825,155825k10.244520%10.244520%10.2%4,641,8354.64M10.179618%10.179618%10.2%8,161339.702326%9.702326%9.7%9,123349.609394%9.609394%9.6%10,95011.0k9.314501%9.314501%9.3%123,226123k8.623103%8.623103%8.6%6,837358.424707%8.424707%8.4%9,343368.392669%8.392669%8.4%6,695377.739434%7.739434%7.7%7,226387.092309%7.092309%7.1%11,88611.9k396.804680%6.804680%6.8%6,403406.424130%6.424130%6.4%5,331416.055621%6.055621%6.1%4,270425.981653%5.981653%6.0%5,099435.461095%5.461095%5.5%4,715445.266517%5.266517%5.3%4,126454.836248%4.836248%4.8%7,351464.020265%4.020265%4.0%4,166473.522812%3.522812%3.5%2,870483.377424%3.377424%3.4%4,282493.157717%3.157717%3.2%2,05750

Bachelor's Degrees by County Subdivision#39

Percent of population 25 years of age and older with a bachelor's degree or higher..
Scope: population of the Monroe Township, selected other county subdivisions in the Midwest, and entities that contain the Monroe Township
0%20%40%60%Count#Ann ArborOverland ParkMilton TownshipMiltonLisle TownshipLisleMadisonDowners Grove TownshipDowners GrvWashington TownshipWashingtonPalatine TownshipPalatineYork TownshipMinneapolisOlatheWheeling TownshipWheelingSchaumburg TownshipSchaumburgKaw TownshipSt. PaulMaine TownshipMaineFargoLincolnLawrence TownshipLawrenceChicagoCapital TownshipCapitalColumbus Metro AreaColumbus AreaColumbusOmahaCincinnatiSt. LouisGrand RapidsBloomingdale TownshipBloomingdaleCedar RapidsUnited States of AmericaUnited StatesSioux FallsMidwestWichitaEast North CentralSterling HeightsSterling HtsTopekaSpringfield TownshipSpringfieldOhioProviso TownshipProvisoWorth TownshipWorthMilwaukeeLicking CountyLickingMonroe TownshipMonroeRockford TownshipRockfordAkronCenter TownshipCtrNorth TownshipNThornton TownshipThorntonToledoDaytonWarrenWayne TownshipWayneKansas CityClevelandAurora TownshipAuroraBlue TownshipDetroit72.810169%72.810169%72.8%47,43047.4k158.823344%58.823344%58.8%74,57874.6k257.681507%57.681507%57.7%45,19045.2k356.900171%56.900171%56.9%46,35646.4k456.337583%56.337583%56.3%85,63285.6k553.762123%53.762123%53.8%55,71155.7k650.610540%50.610540%50.6%47,62347.6k749.860853%49.860853%49.9%39,77539.8k849.728972%49.728972%49.7%42,93542.9k947.670489%47.670489%47.7%127,663128k1046.512581%46.512581%46.5%38,59838.6k1146.409378%46.409378%46.4%51,46851.5k1241.792515%41.792515%41.8%39,02039.0k1341.581304%41.581304%41.6%50,61950.6k1439.969357%39.969357%40.0%74,08874.1k1539.511462%39.511462%39.5%38,91838.9k1638.241175%38.241175%38.2%26,96527.0k1737.146608%37.146608%37.1%62,25462.3k1836.577273%36.577273%36.6%29,32429.3k1936.546320%36.546320%36.5%669,666670k2036.298510%36.298510%36.3%28,78028.8k2134.785494%34.785494%34.8%460,194460k34.685843%34.685843%34.7%185,460185k2234.651487%34.651487%34.7%99,56199.6k2333.783048%33.783048%33.8%64,52964.5k2433.007421%33.007421%33.0%72,14372.1k2532.904381%32.904381%32.9%39,86339.9k2632.623147%32.623147%32.6%25,12725.1k2731.793440%31.793440%31.8%27,10227.1k2830.315023%30.315023%30.3%64,767,78764.8M30.259813%30.259813%30.3%28,45328.5k2928.952816%28.952816%29.0%13,118,64213.1M28.877567%28.877567%28.9%71,75771.8k3028.462853%28.462853%28.5%8,931,6868.93M27.532180%27.532180%27.5%25,60325.6k3127.007248%27.007248%27.0%22,95423.0k3226.964567%26.964567%27.0%27,92127.9k3326.667466%26.667466%26.7%2,092,8752.09M26.237989%26.237989%26.2%27,03327.0k3425.217641%25.217641%25.2%26,38926.4k3523.517740%23.517740%23.5%85,81285.8k3623.329326%23.329326%23.3%26,58426.6k22.894791%22.894791%22.9%1,11221.592552%21.592552%21.6%25,23525.2k3720.213821%20.213821%20.2%26,69726.7k3820.139240%20.139240%20.1%19,93119.9k3919.650916%19.650916%19.7%20,02920.0k4018.971090%18.971090%19.0%21,01221.0k4118.048021%18.048021%18.0%33,17133.2k4217.635555%17.635555%17.6%15,51115.5k4317.280259%17.280259%17.3%15,89315.9k4416.826535%16.826535%16.8%14,78814.8k4516.167409%16.167409%16.2%15,13915.1k4616.073076%16.073076%16.1%40,94640.9k4715.929601%15.929601%15.9%14,19214.2k4815.821208%15.821208%15.8%16,95117.0k4913.833543%13.833543%13.8%59,72359.7k50

Very Advanced Degrees by County Subdivision#40

Percent of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).
Scope: population of the Monroe Township, selected other county subdivisions in the Midwest, and entities that contain the Monroe Township
0%5%10%15%Count#Ann ArborMadisonDowners Grove TownshipDowners GrvWashington TownshipWashingtonMinneapolisYork TownshipOverland ParkLisle TownshipLisleSt. PaulKaw TownshipMilton TownshipMiltonSt. LouisCincinnatiLincolnChicagoFargoCapital TownshipCapitalOmahaMaine TownshipMaineColumbus Metro AreaColumbus AreaPalatine TownshipPalatineWheeling TownshipWheelingColumbusUnited States of AmericaUnited StatesTopekaGrand RapidsLawrence TownshipLawrenceSpringfield TownshipSpringfieldCedar RapidsMidwestEast North CentralSioux FallsOlatheOhioCenter TownshipCtrSchaumburg TownshipSchaumburgWichitaLicking CountyLickingProviso TownshipProvisoAkronBloomingdale TownshipBloomingdaleRockford TownshipRockfordMilwaukeeMonroe TownshipMonroeWorth TownshipWorthClevelandToledoNorth TownshipNSterling HeightsSterling HtsKansas CityDetroitDaytonWayne TownshipWayneWarrenBlue TownshipAurora TownshipAuroraThornton TownshipThornton17.877867%17.877867%17.9%11,64611.6k19.171173%9.171173%9.2%13,94013.9k27.658384%7.658384%7.7%7,93637.306290%7.306290%7.3%6,87546.241155%6.241155%6.2%16,71416.7k56.197734%6.197734%6.2%5,35165.940071%5.940071%5.9%7,53175.933545%5.933545%5.9%4,83485.920847%5.920847%5.9%10,97511.0k95.896414%5.896414%5.9%7,178105.800061%5.800061%5.8%4,544114.880448%4.880448%4.9%10,66710.7k124.729595%4.729595%4.7%9,034134.568292%4.568292%4.6%7,656144.485379%4.485379%4.5%82,18982.2k154.336789%4.336789%4.3%3,058164.233985%4.233985%4.2%3,357174.059919%4.059919%4.1%11,66511.7k184.030539%4.030539%4.0%3,970193.620928%3.620928%3.6%47,90347.9k3.487439%3.487439%3.5%2,782203.407574%3.407574%3.4%3,779213.357865%3.357865%3.4%17,95418.0k223.336158%3.336158%3.3%7,127,6737.13M3.233245%3.233245%3.2%2,748233.174629%3.174629%3.2%3,846243.083448%3.083448%3.1%2,472252.911721%2.911721%2.9%3,015262.905776%2.905776%2.9%2,477272.893416%2.893416%2.9%1,311,0191.31M2.855432%2.855432%2.9%896,039896k2.841677%2.841677%2.8%2,672282.830666%2.830666%2.8%2,349292.683241%2.683241%2.7%210,582211k2.602914%2.602914%2.6%2,576302.551250%2.551250%2.6%2,382312.519246%2.519246%2.5%6,260322.283438%2.283438%2.3%2,6022.213918%2.213918%2.2%2,281332.163955%2.163955%2.2%2,858342.113682%2.113682%2.1%1,628352.067272%2.067272%2.1%2,416362.043126%2.043126%2.0%7,455372.038295%2.038295%2.0%991.958049%1.958049%2.0%2,049381.927780%1.927780%1.9%4,911391.642065%1.642065%1.6%3,018401.575684%1.575684%1.6%1,606411.439893%1.439893%1.4%1,339421.388310%1.388310%1.4%1,300431.318660%1.318660%1.3%5,693441.257490%1.257490%1.3%1,106451.183365%1.183365%1.2%1,040461.047058%1.047058%1.0%963470.997751%0.997751%1.0%1,069480.936111%0.936111%0.9%834490.876686%0.876686%0.9%97150

Under-Education Sex Ratio by County Subdivision#41

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 the Monroe Township, selected other county subdivisions in the Midwest, and entities that contain the Monroe Township
Female
Male
1x0x1xFM#Cedar RapidsLincolnDetroitOmahaToledoThorntonKansas CityMadisonLawrenceFargoProvisoRockfordBlue TownshipWayneMidwestTopekaEast North CentralMilwaukeeKaw TownshipDaytonSioux FallsUnited StatesOlatheOhioColumbus AreaWorthNOverland ParkAuroraWheelingGrand RapidsSchaumburgChicagoWichitaColumbusClevelandLickingPalatineCapitalWarrenSpringfieldYork TownshipSt. LouisWashingtonBloomingdaleCtrCincinnatiAkronAnn ArborSt. PaulLisleMonroeMinneapolisSterling HtsDowners GrvMiltonMaine-1.000000x-1.000000x1.243824x1.243824x1.24x5.354%5.35%6.660%6.66%1-1.000000x-1.000000x1.238529x1.238529x1.24x6.342%6.34%7.854%7.85%2-1.000000x-1.000000x1.237056x1.237056x1.24x18.951%19.0%23.443%23.4%3-1.000000x-1.000000x1.230289x1.230289x1.23x10.968%11.0%13.494%13.5%4-1.000000x-1.000000x1.227011x1.227011x1.23x12.945%12.9%15.884%15.9%5-1.000000x-1.000000x1.203250x1.203250x1.20x11.909%11.9%14.330%14.3%6-1.000000x-1.000000x1.189752x1.189752x1.19x20.748%20.7%24.685%24.7%7-1.000000x-1.000000x1.189278x1.189278x1.19x4.425%4.43%5.263%5.26%8-1.000000x-1.000000x1.181964x1.181964x1.18x9.406%9.41%11.117%11.1%9-1.000000x-1.000000x1.176963x1.176963x1.18x5.565%5.56%6.550%6.55%10-1.000000x-1.000000x1.174964x1.174964x1.17x14.460%14.5%16.990%17.0%11-1.000000x-1.000000x1.168755x1.168755x1.17x14.456%14.5%16.896%16.9%12-1.000000x-1.000000x1.161774x1.161774x1.16x13.244%13.2%15.387%15.4%13-1.000000x-1.000000x1.132245x1.132245x1.13x19.779%19.8%22.395%22.4%14-1.000000x-1.000000x1.127915x1.127915x1.13x9.647%9.65%10.881%10.9%-1.000000x-1.000000x1.125507x1.125507x1.13x10.423%10.4%11.732%11.7%15-1.000000x-1.000000x1.125371x1.125371x1.13x10.108%10.1%11.375%11.4%-1.000000x-1.000000x1.123984x1.123984x1.12x16.526%16.5%18.574%18.6%16-1.000000x-1.000000x1.115695x1.115695x1.12x11.779%11.8%13.142%13.1%17-1.000000x-1.000000x1.114342x1.114342x1.11x16.070%16.1%17.907%17.9%18-1.000000x-1.000000x1.110589x1.110589x1.11x9.201%9.20%10.219%10.2%19-1.000000x-1.000000x1.109070x1.109070x1.11x12.369%12.4%13.719%13.7%-1.000000x-1.000000x1.107847x1.107847x1.11x6.105%6.11%6.764%6.76%20-1.000000x-1.000000x1.105363x1.105363x1.11x10.008%10.0%11.063%11.1%-1.000000x-1.000000x1.104385x1.104385x1.10x8.867%8.87%9.793%9.79%-1.000000x-1.000000x1.099747x1.099747x1.10x10.199%10.2%11.216%11.2%21-1.000000x-1.000000x1.096598x1.096598x1.10x16.317%16.3%17.894%17.9%22-1.000000x-1.000000x1.095440x1.095440x1.10x3.232%3.23%3.540%3.54%23-1.000000x-1.000000x1.086583x1.086583x1.09x32.102%32.1%34.882%34.9%24-1.000000x-1.000000x1.079846x1.079846x1.08x8.111%8.11%8.758%8.76%25-1.000000x-1.000000x1.078480x1.078480x1.08x14.031%14.0%15.132%15.1%26-1.000000x-1.000000x1.077209x1.077209x1.08x7.467%7.47%8.043%8.04%27-1.000000x-1.000000x1.068021x1.068021x1.07x16.372%16.4%17.486%17.5%28-1.000000x-1.000000x1.059528x1.059528x1.06x12.215%12.2%12.942%12.9%29-1.000000x-1.000000x1.052237x1.052237x1.05x11.098%11.1%11.678%11.7%30-1.000000x-1.000000x1.046686x1.046686x1.05x21.119%21.1%22.105%22.1%31-1.000000x-1.000000x1.041562x1.041562x1.04x9.421%9.42%9.813%9.81%-1.000000x-1.000000x1.039581x1.039581x1.04x8.233%8.23%8.559%8.56%32-1.000000x-1.000000x1.039194x1.039194x1.04x8.470%8.47%8.802%8.80%33-1.000000x-1.000000x1.037373x1.037373x1.04x15.022%15.0%15.584%15.6%34-1.000000x-1.000000x1.028857x1.028857x1.03x10.622%10.6%10.928%10.9%35-1.000000x-1.000000x1.027464x1.027464x1.03x5.391%5.39%5.539%5.54%36-1.000000x-1.000000x1.018183x1.018183x1.02x15.334%15.3%15.613%15.6%37-1.000000x-1.000000x1.013146x1.013146x1.01x6.764%6.76%6.853%6.85%38-1.000000x-1.000000x1.007207x1.007207x1.01x12.130%12.1%12.217%12.2%39-1.000000x-1.000000x1.006204x1.006204x1.01x23.095%23.1%23.239%23.2%40-1.000000x-1.000000x1.001229x1.001229x1.00x13.754%13.8%13.771%13.8%41-1.001506x-1.001506x1.00x1.000000x1.000000x13.601%13.6%13.581%13.6%42-1.031649x-1.031649x1.03x1.000000x1.000000x3.205%3.21%3.107%3.11%43-1.060004x-1.060004x1.06x1.000000x1.000000x13.651%13.7%12.879%12.9%44-1.073696x-1.073696x1.07x1.000000x1.000000x3.642%3.64%3.392%3.39%45-1.086161x-1.086161x1.09x1.000000x1.000000x10.956%11.0%10.086%10.1%-1.092939x-1.092939x1.09x1.000000x1.000000x11.450%11.4%10.476%10.5%46-1.131063x-1.131063x1.13x1.000000x1.000000x13.912%13.9%12.300%12.3%47-1.140051x-1.140051x1.14x1.000000x1.000000x4.269%4.27%3.744%3.74%48-1.194783x-1.194783x1.19x1.000000x1.000000x5.710%5.71%4.779%4.78%49-1.208375x-1.208375x1.21x1.000000x1.000000x12.117%12.1%10.027%10.0%50

Over-Education Sex Ratio by County Subdivision#42

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 the Monroe Township, selected other county subdivisions in the Midwest, and entities that contain the Monroe Township
Female
Male
1x0x1x2xFM#RockfordNDaytonSioux FallsCapitalLawrenceDowners GrvAkronLisleWichitaYork TownshipMaineWarrenWheelingBlue TownshipSpringfieldOverland ParkMiltonGrand RapidsOlatheOhioOmahaFargoWashingtonEast North CentralLincolnMidwestBloomingdaleKansas CityColumbus AreaAuroraUnited StatesAnn ArborTopekaSterling HtsLickingPalatineSchaumburgColumbusMadisonKaw TownshipMilwaukeeCedar RapidsClevelandCincinnatiSt. PaulSt. LouisChicagoWayneCtrToledoMinneapolisWorthDetroitProvisoMonroeThornton-1.000000x-1.000000x2.117268x2.117268x2.12x1.353%1.35%2.866%2.87%1-1.000000x-1.000000x2.111054x2.111054x2.11x1.033%1.03%2.181%2.18%2-1.000000x-1.000000x1.989047x1.989047x1.99x0.860%0.86%1.711%1.71%3-1.000000x-1.000000x1.962539x1.962539x1.96x1.928%1.93%3.783%3.78%4-1.000000x-1.000000x1.901348x1.901348x1.90x2.990%2.99%5.686%5.69%5-1.000000x-1.000000x1.879271x1.879271x1.88x2.206%2.21%4.146%4.15%6-1.000000x-1.000000x1.852471x1.852471x1.85x5.456%5.46%10.107%10.1%7-1.000000x-1.000000x1.846298x1.846298x1.85x1.550%1.55%2.862%2.86%8-1.000000x-1.000000x1.815266x1.815266x1.82x4.271%4.27%7.754%7.75%9-1.000000x-1.000000x1.792728x1.792728x1.79x1.819%1.82%3.261%3.26%10-1.000000x-1.000000x1.792314x1.792314x1.79x4.498%4.50%8.062%8.06%11-1.000000x-1.000000x1.788417x1.788417x1.79x2.939%2.94%5.256%5.26%12-1.000000x-1.000000x1.768853x1.768853x1.77x0.769%0.77%1.361%1.36%13-1.000000x-1.000000x1.766097x1.766097x1.77x2.485%2.48%4.389%4.39%14-1.000000x-1.000000x1.761699x1.761699x1.76x0.737%0.74%1.298%1.30%15-1.000000x-1.000000x1.751445x1.751445x1.75x2.146%2.15%3.759%3.76%16-1.000000x-1.000000x1.732234x1.732234x1.73x4.415%4.41%7.647%7.65%17-1.000000x-1.000000x1.695067x1.695067x1.70x4.357%4.36%7.385%7.38%18-1.000000x-1.000000x1.689013x1.689013x1.69x2.382%2.38%4.023%4.02%19-1.000000x-1.000000x1.678153x1.678153x1.68x2.131%2.13%3.576%3.58%20-1.000000x-1.000000x1.669500x1.669500x1.67x2.031%2.03%3.391%3.39%-1.000000x-1.000000x1.669388x1.669388x1.67x3.061%3.06%5.110%5.11%21-1.000000x-1.000000x1.627456x1.627456x1.63x3.304%3.30%5.377%5.38%22-1.000000x-1.000000x1.610803x1.610803x1.61x5.701%5.70%9.183%9.18%23-1.000000x-1.000000x1.597848x1.597848x1.60x2.216%2.22%3.541%3.54%-1.000000x-1.000000x1.596978x1.596978x1.60x3.524%3.52%5.628%5.63%24-1.000000x-1.000000x1.589934x1.589934x1.59x2.251%2.25%3.579%3.58%-1.000000x-1.000000x1.586045x1.586045x1.59x1.649%1.65%2.616%2.62%25-1.000000x-1.000000x1.570028x1.570028x1.57x1.087%1.09%1.707%1.71%26-1.000000x-1.000000x1.567060x1.567060x1.57x2.842%2.84%4.454%4.45%-1.000000x-1.000000x1.550495x1.550495x1.55x0.737%0.74%1.143%1.14%27-1.000000x-1.000000x1.526215x1.526215x1.53x2.660%2.66%4.060%4.06%-1.000000x-1.000000x1.522839x1.522839x1.52x14.269%14.3%21.730%21.7%28-1.000000x-1.000000x1.481288x1.481288x1.48x2.641%2.64%3.912%3.91%29-1.000000x-1.000000x1.476996x1.476996x1.48x1.170%1.17%1.728%1.73%30-1.000000x-1.000000x1.469621x1.469621x1.47x1.863%1.86%2.738%2.74%-1.000000x-1.000000x1.457167x1.457167x1.46x2.851%2.85%4.154%4.15%31-1.000000x-1.000000x1.436165x1.436165x1.44x2.115%2.11%3.037%3.04%32-1.000000x-1.000000x1.413654x1.413654x1.41x2.801%2.80%3.959%3.96%33-1.000000x-1.000000x1.387878x1.387878x1.39x7.705%7.70%10.693%10.7%34-1.000000x-1.000000x1.373250x1.373250x1.37x4.975%4.97%6.832%6.83%35-1.000000x-1.000000x1.368590x1.368590x1.37x1.742%1.74%2.385%2.38%36-1.000000x-1.000000x1.346658x1.346658x1.35x2.491%2.49%3.354%3.35%37-1.000000x-1.000000x1.286599x1.286599x1.29x1.699%1.70%2.186%2.19%38-1.000000x-1.000000x1.280610x1.280610x1.28x4.179%4.18%5.351%5.35%39-1.000000x-1.000000x1.274509x1.274509x1.27x5.228%5.23%6.663%6.66%40-1.000000x-1.000000x1.273345x1.273345x1.27x4.319%4.32%5.500%5.50%41-1.000000x-1.000000x1.238186x1.238186x1.24x4.026%4.03%4.985%4.99%42-1.000000x-1.000000x1.223931x1.223931x1.22x1.068%1.07%1.307%1.31%43-1.000000x-1.000000x1.213574x1.213574x1.21x2.357%2.36%2.860%2.86%44-1.000000x-1.000000x1.141406x1.141406x1.14x1.539%1.54%1.757%1.76%45-1.000000x-1.000000x1.124528x1.124528x1.12x5.872%5.87%6.603%6.60%46-1.000000x-1.000000x1.084697x1.084697x1.08x1.883%1.88%2.042%2.04%47-1.000000x-1.000000x1.046557x1.046557x1.05x1.291%1.29%1.351%1.35%48-1.000000x-1.000000x1.042857x1.042857x1.04x2.171%2.17%2.264%2.26%49-1.020828x-1.020828x1.02x1.000000x1.000000x2.059%2.06%2.017%2.02%-1.706858x-1.706858x1.71x1.000000x1.000000x1.072%1.07%0.628%0.63%50

Educational Attainment by County Subdivision in the United States

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

No H.S. Diploma by County Subdivision#43

Percent of population 25 years of age and older without a high school diploma (or equivalent).
Scope: population of the Monroe Township, selected other county subdivisions in the United States, and entities that contain the Monroe Township
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 VegasPhoenixBostonSacramentoOrlandoAustinDenverUnited States of AmericaUnited StatesManhattanSan DiegoTampaSan JoseSan FranciscoTucsonAlbuquerqueTownship 1:Charlotte1, CharlotteColumbusTulsaEast North CentralMonroe TownshipMonroeOhioSalt Lake CitySalt Lk CityTown of HempsteadHempsteadMidwestNorthwest HarrisNW HarrisWashingtonLicking CountyLickingAtlantaColumbus Metro AreaColumbus AreaSeattleNortheast TarrantNE TarrantPlanoSeattle 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%63,64263.6k2713.900512%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%84,02484.0k3612.262851%12.262851%12.3%70,40970.4k3712.089143%12.089143%12.1%52,21752.2k3811.553484%11.553484%11.6%61,37861.4k3911.376979%11.376979%11.4%60,83160.8k4011.299086%11.299086%11.3%43,65343.7k4110.719464%10.719464%10.7%3,363,7843.36M10.520898%10.520898%10.5%51110.514146%10.514146%10.5%825,155825k10.435356%10.435356%10.4%64,29464.3k4210.384134%10.384134%10.4%54,23054.2k4310.244520%10.244520%10.2%4,641,8354.64M10.135583%10.135583%10.1%47,67947.7k4410.045421%10.045421%10.0%46,51046.5k459.609394%9.609394%9.6%10,95011.0k9.538552%9.538552%9.5%37,37337.4k469.314501%9.314501%9.3%123,226123k8.833573%8.833573%8.8%66,22066.2k478.418271%8.418271%8.4%31,44331.4k485.714681%5.714681%5.7%20,64420.6k494.913852%4.913852%4.9%20,32620.3k50

Bachelor's Degrees by County Subdivision#44

Percent of population 25 years of age and older with a bachelor's degree or higher..
Scope: population of the Monroe Township, selected other county subdivisions in the United States, and entities that contain the Monroe Township
0%20%40%60%Count#ManhattanSeattle EastWashingtonSan FranciscoPlanoSan JoseAtlantaSeattleBostonDenverAustinTownship 1:Charlotte1, CharlotteTown of HempsteadHempsteadSan DiegoNortheast TarrantNE TarrantNorthwest HarrisNW HarrisChicagoColumbus Metro AreaColumbus AreaColumbusLos AngelesBrooklynSan Fernando ValleySan Fernando VlyNortheast DallasNE DallasSalt Lake CitySalt Lk CityAlbuquerqueTampaTucsonOceanside-EscondidoOceanside-Escond…TulsaQueensUnited States of AmericaUnited StatesHoustonBaltimoreLong Beach-LakewoodLong Bch-LakewoodMidwestPhoenixOrlandoEast North CentralAnaheim-Santa Ana-Garden GroveAnaheim-Santa An…SacramentoEast San Gabriel ValleyE San Gabriel VlyOntarioOhioPhiladelphiaMiamiFort WorthSouthwest DallasSW DallasMilwaukeeLicking CountyLickingMonroe TownshipMonroeFresnoLas VegasEl PasoBronxSan 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%669,666670k1734.785494%34.785494%34.8%460,194460k34.685843%34.685843%34.7%185,460185k1834.593243%34.593243%34.6%604,693605k1934.081468%34.081468%34.1%597,685598k2033.231104%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%140,967141k2432.512191%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%125,423125k3129.113198%29.113198%29.1%109,693110k3228.952816%28.952816%29.0%13,118,64213.1M28.760152%28.760152%28.8%593,529594k3328.535877%28.535877%28.5%112,142112k3428.462853%28.462853%28.5%8,931,6868.93M28.412939%28.412939%28.4%312,038312k3528.231204%28.231204%28.2%209,283209k3627.276345%27.276345%27.3%170,682171k3726.758411%26.758411%26.8%111,532112k3826.667466%26.667466%26.7%2,092,8752.09M26.349720%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%85,81285.8k4323.329326%23.329326%23.3%26,58426.6k22.894791%22.894791%22.9%1,11222.486319%22.486319%22.5%94,05694.1k4421.702666%21.702666%21.7%271,037271k4521.071885%21.071885%21.1%72,12072.1k4619.131504%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

Very Advanced Degrees by County Subdivision#45

Percent of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).
Scope: population of the Monroe Township, selected other county subdivisions in the United States, and entities that contain the Monroe Township
0%5%10%Count#WashingtonManhattanSan FranciscoBostonAtlantaSeattleSan JoseSeattle EastDenverSan DiegoAustinBaltimoreLos AngelesAlbuquerquePlanoChicagoTucsonTown of HempsteadHempsteadTampaMiamiNortheast DallasNE DallasSalt Lake CitySalt Lk CityHoustonPhiladelphiaColumbus Metro AreaColumbus AreaSan Fernando ValleySan Fernando VlyTownship 1:Charlotte1, CharlotteOceanside-EscondidoOceanside-Escond…BrooklynSacramentoColumbusUnited States of AmericaUnited StatesTulsaPhoenixLong Beach-LakewoodLong Bch-LakewoodMidwestOrlandoEast North CentralFresnoAnaheim-Santa Ana-Garden GroveAnaheim-Santa An…QueensOhioNorthwest HarrisNW HarrisNortheast TarrantNE TarrantEast San Gabriel ValleyE San Gabriel VlyOntarioLicking CountyLickingFort WorthLas VegasMilwaukeeMonroe TownshipMonroeSan BernardinoSan Antonio CentralSan Antonio CntrlEl PasoSouthwest DallasSW DallasBronxDetroit12.461852%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%19,24719.2k194.025531%4.025531%4.0%27,61827.6k203.827408%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%38,51538.5k243.620928%3.620928%3.6%47,90347.9k3.601468%3.601468%3.6%45,61045.6k253.490252%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%7,127,6737.13M3.140490%3.140490%3.1%12,13312.1k313.010825%3.010825%3.0%62,13562.1k323.009440%3.009440%3.0%11,33911.3k332.893416%2.893416%2.9%1,311,0191.31M2.893233%2.893233%2.9%11,37011.4k342.855432%2.855432%2.9%896,039896k2.828959%2.828959%2.8%11,83311.8k352.763004%2.763004%2.8%30,34430.3k362.756960%2.756960%2.8%44,96545.0k372.683241%2.683241%2.7%210,582211k2.682967%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%9,688412.283438%2.283438%2.3%2,6022.173239%2.173239%2.2%11,57311.6k422.155077%2.155077%2.2%26,91426.9k432.043126%2.043126%2.0%7,455442.038295%2.038295%2.0%991.807306%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%15,06415.1k491.318660%1.318660%1.3%5,69350

Under-Education Sex Ratio by County Subdivision#46

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 the Monroe Township, selected other county subdivisions in the United States, and entities that contain the Monroe Township
Female
Male
1x0x1xFM#1, CharlotteDetroitBaltimoreTulsaSW DallasMidwestFresnoEast North CentralMilwaukeeUnited StatesOhioColumbus AreaNE DallasHoustonHempsteadOrlandoPhiladelphiaOntarioSan BernardinoAustinAtlantaFort WorthPhoenixChicagoAlbuquerqueWashingtonSacramentoColumbusSalt Lk CityDenverLickingNE TarrantTampaOceanside-EscondidoOceanside-Escond…NW HarrisBronxPlanoBrooklynSan Antonio CntrlSan Fernando VlyTucsonAnaheim-Santa Ana-Gdn GrvAnaheim-Santa An…Los AngelesLas VegasBostonE San Gabriel VlyQueensMiamiManhattanSeattleLong Bch-LakewoodSeattle EastMonroeSan JoseSan DiegoSan FranciscoEl Paso-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-1.000000x1.127915x1.127915x1.13x9.647%9.65%10.881%10.9%-1.000000x-1.000000x1.127206x1.127206x1.13x20.830%20.8%23.479%23.5%6-1.000000x-1.000000x1.125371x1.125371x1.13x10.108%10.1%11.375%11.4%-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-1.000000x1.105363x1.105363x1.11x10.008%10.0%11.063%11.1%-1.000000x-1.000000x1.104385x1.104385x1.10x8.867%8.87%9.793%9.79%-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-1.000000x1.092101x1.092101x1.09x9.951%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-1.000000x1.073220x1.073220x1.07x9.215%9.21%9.889%9.89%16-1.000000x-1.000000x1.071348x1.071348x1.07x19.379%19.4%20.762%20.8%17-1.000000x-1.000000x1.069008x1.069008x1.07x14.467%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-1.000000x1.053268x1.053268x1.05x13.558%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-1.000000x1.041562x1.041562x1.04x9.421%9.42%9.813%9.81%-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-1.000000x1.003929x1.003929x1.00x28.944%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%46-1.086161x-1.086161x1.09x1.000000x1.000000x10.956%11.0%10.086%10.1%-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

Over-Education Sex Ratio by County Subdivision#47

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 the Monroe Township, selected other county subdivisions in the United States, and entities that contain the Monroe Township
Female
Male
1x0x1x2xFM#El PasoSalt Lk CityPlanoTulsaAlbuquerqueNE DallasFort WorthOhioOrlandoPhoenixTucson1, CharlotteEast North CentralMidwestNW HarrisLas VegasColumbus AreaSeattle EastSan Antonio CntrlSan DiegoUnited StatesSan JoseHempsteadFresnoNE TarrantTampaLickingSan Fernando VlyE San Gabriel VlyHoustonSan BernardinoColumbusMiamiAtlantaMilwaukeeAnaheim-Santa Ana-Gdn GrvAnaheim-Santa An…SacramentoPhiladelphiaOceanside-EscondidoOceanside-Escond…Los AngelesAustinBaltimoreWashingtonQueensSW DallasBrooklynManhattanChicagoSeattleBostonBronxOntarioLong Bch-LakewoodDenverSan FranciscoDetroitMonroe-1.000000x-1.000000x2.132933x2.132933x2.13x1.146%1.15%2.445%2.44%1-1.000000x-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-1.000000x1.669500x1.669500x1.67x2.031%2.03%3.391%3.39%-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-1.000000x1.621815x1.621815x1.62x3.429%3.43%5.561%5.56%10-1.000000x-1.000000x1.611479x1.611479x1.61x2.711%2.71%4.369%4.37%11-1.000000x-1.000000x1.597848x1.597848x1.60x2.216%2.22%3.541%3.54%-1.000000x-1.000000x1.589934x1.589934x1.59x2.251%2.25%3.579%3.58%-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-1.000000x1.567060x1.567060x1.57x2.842%2.84%4.454%4.45%-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-1.000000x1.488724x1.488724x1.49x3.608%3.61%5.371%5.37%18-1.000000x-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-1.000000x1.469621x1.469621x1.47x1.863%1.86%2.738%2.74%-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%50-1.020828x-1.020828x1.02x1.000000x1.000000x2.059%2.06%2.017%2.02%

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.

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