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

Educational Attainment#1

Highest level of education among people aged 25 years and older.
Scope: population of Perry County and the Monroe Township
Monroe Township
Perry County
0%10%20%30%40%50%60%CountHigher Degree1H.S. Diploma2No H.S. Diploma218.475751%21.889868%18.475751%18.5%16064.549654%62.020603%64.549654%64.5%55916.974596%16.089529%16.974596%17.0%147
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 Perry County at large.
Scope: population of Perry County and the Monroe Township
-10%0%+10%%ref.Higher Degree1H.S. Diploma2No H.S. Diploma2-15.596793%-15.596793%-15.6%18.476%18.5%21.890%21.9%4.077758%4.077758%+4.1%64.550%64.5%62.021%62.0%5.500889%5.500889%+5.5%16.975%17.0%16.090%16.1%
% percentage with given level in the Monroe Township
ref. percentage with given level in Perry 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 Perry County and the Monroe Township
Monroe Township
Perry County
0%10%20%30%40%CountDoctorate1Professional1Master's1Bachelor's1Associate's1Some CollegeHigh School2Some H.S.3Less than H.S.3None0.000000%0.000000%0.0%0.215134%00.115473%0.450954%0.115473%0.1%12.886836%3.111166%2.886836%2.9%259.006928%8.183360%9.006928%9.0%786.466513%9.929254%6.466513%6.5%5618.937644%17.744404%18.937644%18.9%16445.612009%44.276199%45.612009%45.6%39511.893764%12.792189%11.893764%11.9%1034.503464%2.432667%4.503464%4.5%390.577367%0.864673%0.577367%0.6%5
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 Perry County at large.
Scope: population of Perry County and the Monroe Township
-100%0%+100%%ref.Doctorate1Professional1Master's1Bachelor's1Associate's1Some CollegeHigh School2Some H.S.3Less than H.S.3None-100.000000%-100.000000%-100.0%0.000%0%0.215%0.22%-74.393500%-74.393500%-74.4%0.115%0.12%0.451%0.45%-7.210487%-7.210487%-7.2%2.887%2.89%3.111%3.11%10.063937%10.063937%+10.1%9.007%9.01%8.183%8.18%-34.874134%-34.874134%-34.9%6.467%6.47%9.929%9.93%6.724598%6.724598%+6.7%18.938%18.9%17.744%17.7%3.016995%3.016995%+3.0%45.612%45.6%44.276%44.3%-7.023228%-7.023228%-7.0%11.894%11.9%12.792%12.8%85.124546%85.124546%+85.1%4.503%4.50%2.433%2.43%-33.227068%-33.227068%-33.2%0.577%0.58%0.865%0.86%
% percentage with given level in the Monroe Township
ref. percentage with given level in Perry 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 Perry County and the Monroe Township
More Females More Males
Perry County
Monroe Township
100%50%0%50%FMHigher Degree1H.S. Diploma2No H.S. Diploma2-133.434008%-49.077680%-133.434008%133%24.947%24.9%10.687%10.7%6.938140%5.395120%6.938140%7%62.579%62.6%66.921%66.9%79.514383%39.778105%79.514383%80%12.474%12.5%22.392%22.4%
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 Perry County and the Monroe Township
More Females More Males
Perry County
Monroe Township
0%500%1,000%FMProfessional1Master's1Bachelor's1Associate's1Some CollegeHigh School2Some H.S.3Less than H.S.3None1,000.000000%593.845106%1,000.000000%> 1000%0.000%0%0.254%0.25%-34.937434%30.385920%30.385920%30%2.537%2.54%3.308%3.31%-356.976744%-23.788721%-356.976744%357%13.953%14.0%3.053%3.05%-107.716702%-107.424791%-107.716702%108%8.457%8.46%4.071%4.07%35.986914%0.595548%35.986914%36%16.279%16.3%22.137%22.1%-3.386268%-3.386268%3%7.382989%46.300%46.3%44.784%44.8%5.038168%28.018372%5.038168%5%11.628%11.6%12.214%12.2%1,000.000000%101.403204%1,000.000000%> 1000%0.423%0.42%9.415%9.41%80.534351%94.560660%80.534351%81%0.423%0.42%0.763%0.76%
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 Perry County and the Monroe Township
Monroe Township
Perry County
0%2%4%6%8%10%12%B.X.Total65+45-6435-4425-347.203390%6.934172%7.203390%7.2%1723613.823529%9.103367%13.823529%13.8%473406.730769%8.346492%6.730769%6.7%71043.763441%7.365095%3.763441%3.8%7186
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 Perry County at large.
Scope: population of Perry County and the Monroe Township
40%20%0%20%40%%ref.65+45-6435-4425-343.882486%3.882486%3.9%7.203%7.20%6.934%6.93%51.850727%51.850727%51.9%13.824%13.8%9.103%9.10%-19.358108%-19.358108%19.4%6.731%6.73%8.346%8.35%-48.901664%-48.901664%48.9%3.763%3.76%7.365%7.37%
% percentage in the Monroe Township with a Bachelor's degree
ref percentage in Perry 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 Perry County and the Monroe Township
More Females More Males
Perry County
Monroe Township
1,000%500%0%FM65+45-6435-4425-34-1,000.000000%-1,000.000000%> 1000%130.754317%13.386%13.4%0.000%0%-289.484127%-30.022029%-289.484127%289.5%20.635%20.6%5.298%5.30%-1,000.000000%-90.219644%-1,000.000000%> 1000%15.909%15.9%0.000%0%-157.530726%106.392694%106.392694%106.4%2.655%2.65%5.479%5.48%
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 Perry County and the Monroe Township
Monroe Township
Perry County
$0k$20k$40kCount%Bachelor's DegreeSome CollegeH.S. Diploma2No H.S. Diploma2Total$57,931.000000$47,321.000000$57,931.000000$57.9k789.007%9.01%$33,421.000000$32,978.000000$33,421.000000$33.4k22025.404%25.4%$28,750.000000$27,143.000000$28,750.000000$28.8k39545.612%45.6%$21,146.000000$19,129.000000$21,146.000000$21.1k14716.975%17.0%$32,067.000000$30,966.000000$32,067.000000$32.1k866100.000%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 Perry County and the Monroe Township
Female Male
Perry County
Monroe Township
Shaded bar tips show excess over facing bar.
$20k$0k$20k$40kFMSome CollegeH.S. Diploma2Total$-30,114.000000$-26,021.000000$-30,114.000000$30.1k$30,114.000000$22,230.000000$26,021.000000$19,684.000000$52,344.000000$52.3k117103$-17,452.000000$-20,233.000000$-17,452.000000$17.5k$17,452.000000$19,707.000000$20,233.000000$15,927.000000$37,159.000000$37.2k219176$-24,722.000000$-23,925.000000$-24,722.000000$24.7k$24,722.000000$10,846.000000$23,925.000000$14,868.000000$35,568.000000$35.6k473393
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 Perry County and the Monroe Township
Monroe Township
Perry County
0%20%40%60%80%CountBachelor's Degree1Some College2H.S. Diploma3No H.S. Diploma388.235294%80.835796%88.235294%88.2%7550.980392%73.887446%50.980392%51.0%10464.197531%63.222990%64.197531%64.2%15633.673469%40.008432%33.673469%33.7%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 Perry County and the Monroe Township
Female Male
Perry County
Monroe Township
Shaded bar tips show excess over facing bar.
20%10%0%10%20%MFWhite1Other1-12.715517%-13.078017%-12.715517%12.7%12.715517%11.004159%13.078017%5.765044%23.719677%23.7%8859-0.000000%-18.354430%-9.793718%0.000000%0.0%0.000000%0.000000%18.354430%0.000000%0.0%00
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 Perry County and the Monroe Township
Female Male
Perry County
Monroe Township
Shaded bar tips show excess over facing bar.
10%0%10%20%30%MFWhite1Other1-7.008086%-9.802259%-10.756461%-2.162680%-16.810345%16.8%7.008086%10.756461%7.008086%7.0%2678-0.000000%-0.000000%0.000000%0.0%0.000000%0.000000%0.000000%32.911392%0.000000%0.0%00
M number of males in category
F number of females in category
1non-Hispanic 2excluding black and Asian Hispanics

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
17.36%17.68%17.99%18.30%18.62%18.93%

Coarse: High School Diploma Educational Attainment by Tract#16

Percentage of the population 25 years and older with given highest level of educational attainment
59.4%60.8%62.1%63.4%64.7%66.0%

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
15.1%16.7%18.3%19.9%21.5%23.2%

Detailed: Doctorate Degree Educational Attainment by Tract#18

Percentage of the population 25 years and older with given highest level of educational attainment
0.000%0.024%0.049%0.073%0.097%0.122%

Detailed: Professional Degree Educational Attainment by Tract#19

Percentage of the population 25 years and older with given highest level of educational attainment
0.038%0.045%0.052%0.059%0.066%0.074%

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

Percentage of the population 25 years and older with given highest level of educational attainment
1.37%1.52%1.65%1.79%1.93%2.08%

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

Percentage of the population 25 years and older with given highest level of educational attainment
5.79%6.15%6.51%6.86%7.22%7.58%

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

Percentage of the population 25 years and older with given highest level of educational attainment
9.30%9.43%9.56%9.69%9.81%9.95%

Detailed: Some College Educational Attainment by Tract#23

Percentage of the population 25 years and older with given highest level of educational attainment
13.6%14.9%16.1%17.3%18.5%19.8%

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
39.7%42.3%44.8%47.3%49.8%52.3%

Detailed: Some High School Educational Attainment by Tract#25

Percentage of the population 25 years and older with given highest level of educational attainment
11.6%13.2%14.8%16.3%17.9%19.5%

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
1.85%2.02%2.20%2.37%2.54%2.72%

Detailed: None Educational Attainment by Tract#27

Percentage of the population 25 years and older with given highest level of educational attainment
0.76%0.98%1.19%1.40%1.61%1.83%
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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 TownshipSciotoWhitehallMonroe TownshipMonroePerry CountyPerryHamilton TownshipHamiltonCirclevilleLondonUnion TownshipUnionPrairie TownshipPrairieUnited States of AmericaUnited StatesPleasant TownshipPleasantNewarkFalls TownshipFallsLancaster City TownshipLancaster CityWalnut TownshipWalnutJefferson TownshipJeffersonColumbusEast North CentralHeathMonroe TownshipMonroeOhioHarrison TownshipHarrisonMidwestParis TownshipParisColumbus 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%2,272416.974596%16.974596%17.0%14716.089529%16.089529%16.1%3,88915.953777%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%1,640209.314501%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
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#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 TownshipParisPataskalaOhioUnion TownshipUnionMonroe TownshipMonroeMadison TownshipMadisonPleasant TownshipPleasantLiberty TownshipLibertyPrairie TownshipPrairieHarrison TownshipHarrisonNewarkHeathWalnut TownshipWalnutLancaster City TownshipLancaster CityFalls TownshipFallsCirclevilleLondonJefferson TownshipJeffersonWhitehallMonroe TownshipMonroePerry CountyPerryScioto 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%2,092,8752.09M23.109386%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%1,4884612.009238%12.009238%12.0%10411.960614%11.960614%12.0%2,89111.056977%11.056977%11.1%8174710.048802%10.048802%10.0%453489.796482%9.796482%9.8%568499.038547%9.038547%9.0%61250
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#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 TownshipUnionHarrison TownshipHarrisonParis TownshipParisTruro TownshipTruroJackson TownshipJacksonMadison TownshipMadisonMonroe TownshipMonroePataskalaWalnut TownshipWalnutColumbusLiberty TownshipLibertyNewarkHarrison TownshipHarrisonLancaster City TownshipLancaster CityHeathFalls TownshipFallsCirclevillePleasant TownshipPleasantPrairie TownshipPrairieLondonFranklin TownshipFranklinScioto TownshipSciotoPerry CountyPerryPike TownshipJefferson TownshipJeffersonWhitehallHamilton TownshipHamiltonMonroe TownshipMonroe16.893099%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%138252.280525%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%61460.666087%0.666087%0.7%1610.621118%0.621118%0.6%28470.599161%0.599161%0.6%30480.425786%0.425786%0.4%50490.120731%0.120731%0.1%7500.115473%0.115473%0.1%1
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#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 HtsJeffersonMonroeHarrisonPike TownshipConcordJeffersonPerryFallsLibertyJeromeEtna TownshipFranklinUnionWhitehallDelaware CityHeathLondonPrairieLancaster CityMidwestEast North CentralMadisonHamiltonCirclevilleUnited StatesOhioColumbus AreaPataskalaColumbusNewarkJacksonMifflinNorwichPleasantGenoaLibertyBexleyMonroeWestervilleBlendonUpper 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-1.000000x1.795144x1.795144x1.80x12.474%12.5%22.392%22.4%-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-1.000000x1.397781x1.397781x1.40x13.445%13.4%18.793%18.8%-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-1.000000x1.036562x1.036562x1.04x12.733%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
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#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#MonroeFallsLondonHamiltonJeffersonPike TownshipPleasantLibertyPerryCirclevilleColumbusDelaware CityLancaster CityWestervilleBloomSharonHarrisonHeathWalnutHarrisonLibertyMifflinNewarkJeromeConcordGranvillePlainDublinFranklinUpper ArlingtonNorwichTruroOhioBexleyJeffersonEast North CentralMidwestMadisonColumbus AreaUnited StatesEtna TownshipBlendonBerlinColumbusOrangeJacksonGrandview HtsVioletGenoaPrairieMonroeParisWesterville CityPataskalaUnionWhitehallScioto-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%0.254%0.25%-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-1.000000x6.135051x6.135051x6.14x0.188%0.19%1.155%1.15%-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-1.000000x1.457364x1.457364x1.46x3.489%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
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 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#ClevelandMiddletownLorainYoungstownMonroe TownshipMonroeSpringfieldDaytonMansfieldLimaPerry CountyPerryMarion TownshipMarionCantonHamiltonWarrenToledoCincinnatiAkronElyriaUnited States of AmericaUnited StatesNewarkBath TownshipLancaster City TownshipLancaster CityColumbusColerain TownshipColerainEast North CentralEuclidOhioMidwestParmaColumbus 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%7,424416.974596%16.974596%17.0%14716.947843%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%3,757816.089529%16.089529%16.1%3,88915.742056%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%3,5222210.514146%10.514146%10.5%825,155825k10.244520%10.244520%10.2%4,641,8354.64M9.939137%9.939137%9.9%5,683239.314501%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
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#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 TownshipMiamiOhioHuber HeightsColerain TownshipColerainEuclidAkronParmaNewarkToledoDaytonMiddletownLancaster City TownshipLancaster CityClevelandElyriaHamiltonSpringfieldCantonMansfieldWarrenYoungstownMonroe TownshipMonroePerry CountyPerryLorainLimaMarion 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%2,092,8752.09M22.834168%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%5,2604712.009238%12.009238%12.0%10411.960614%11.960614%12.0%2,89111.718579%11.718579%11.7%4,8124811.460139%11.460139%11.5%2,6454910.478559%10.478559%10.5%3,24550
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#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 TownshipAkronJackson TownshipJacksonClevelandMentorColerain TownshipColerainMiami TownshipMiamiFindlayToledoSpringfieldFairfieldEuclidHuber HeightsLimaDaytonCantonHamiltonUnion TownshipUnionParmaNewarkLancaster City TownshipLancaster CityMansfieldMiddletownLorainElyriaYoungstownWarrenMarion TownshipMarionPerry CountyPerryMonroe TownshipMonroe10.753042%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%605232.163955%2.163955%2.2%2,858242.063608%2.063608%2.1%619251.927780%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%223500.666087%0.666087%0.7%1610.115473%0.115473%0.1%1
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#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#MonroeAndersonMansfieldCleveland HtsPerryBeavercreekUnionToledoFindlayLorainMarionYoungstownColerainGrnFairfieldElyriaMiddletownLancaster CityMidwestEast North CentralSpringfieldWarrenDaytonCantonUnited StatesOhioColumbus AreaLimaParmaColumbusClevelandDeerfieldMentorNewarkW ChesterPlainLibertyJacksonHuber HeightsHamiltonJacksonCincinnatiAkronMifflinSylvaniaMiamiEuclidMiamiCuyahoga FallsStrongsvilleLakewoodBath TownshipDublinKetteringWashingtonBoardmanViolet-1.000000x-1.000000x1.795144x1.795144x1.80x12.474%12.5%22.392%22.4%-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-1.000000x1.397781x1.397781x1.40x13.445%13.4%18.793%18.8%-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-1.000000x1.038813x1.038813x1.04x5.175%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%40-1.123601x-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
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#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
0x5x10xFM#MonroePerryElyriaSpringfieldWashingtonYoungstownBoardmanLorainMiddletownLancaster CityFindlayAndersonJacksonKetteringMifflinPlainBeavercreekDeerfieldDaytonNewarkEuclidMiamiAkronDublinSylvaniaStrongsvilleBath TownshipOhioFairfieldMansfieldW ChesterHuber HeightsLakewoodEast North CentralMidwestColumbus AreaWarrenUnited StatesLibertyParmaCleveland HtsColumbusUnionMentorGrnJacksonClevelandCincinnatiMiamiMarionVioletColerainToledoHamiltonCantonCuyahoga FallsLima-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%0.254%0.25%-1.000000x-1.000000x6.135051x6.135051x6.14x0.188%0.19%1.155%1.15%-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-1.000000x1.433883x1.433883x1.43x1.025%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%47-1.103703x-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
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 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 TownshipNMonroe TownshipMonroeDaytonChicagoPerry CountyPerryProviso TownshipProvisoRockford TownshipRockfordSt. LouisWarrenGrand RapidsToledoBlue TownshipCincinnatiAkronSt. PaulSterling HeightsSterling HtsUnited States of AmericaUnited StatesThornton TownshipThorntonWichitaKaw TownshipOmahaBloomingdale TownshipBloomingdaleColumbusMaine TownshipMaineTopekaMinneapolisSpringfield TownshipSpringfieldEast North CentralWorth TownshipWorthOhioMidwestLawrence TownshipLawrenceSioux FallsColumbus 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%17,39117.4k816.974596%16.974596%17.0%14716.928359%16.928359%16.9%14,88914.9k916.905373%16.905373%16.9%309,770310k1016.089529%16.089529%16.1%3,88915.636222%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%11,17511.2k3210.514146%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%9,123349.314501%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
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#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 TownshipWorthMilwaukeeRockford TownshipRockfordAkronCenter TownshipCtrNorth TownshipNThornton TownshipThorntonToledoDaytonWarrenWayne TownshipWayneKansas CityClevelandAurora TownshipAuroraBlue TownshipDetroitMonroe TownshipMonroePerry CountyPerry72.810169%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%85,81285.8k3621.592552%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%59,72359.7k5012.009238%12.009238%12.0%10411.960614%11.960614%12.0%2,891
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#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 TownshipSchaumburgWichitaProviso TownshipProvisoAkronBloomingdale TownshipBloomingdaleRockford TownshipRockfordMilwaukeeWorth TownshipWorthClevelandToledoNorth TownshipNSterling HeightsSterling HtsKansas CityDetroitDaytonWayne TownshipWayneWarrenBlue TownshipAurora TownshipAuroraThornton TownshipThorntonPerry CountyPerryMonroe TownshipMonroe17.877867%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%6,260322.213918%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%7,455371.958049%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%971500.666087%0.666087%0.7%1610.115473%0.115473%0.1%1
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#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#MonroePerryCedar RapidsLincolnDetroitOmahaToledoThorntonKansas CityMadisonLawrenceFargoProvisoRockfordBlue TownshipWayneMidwestTopekaEast North CentralMilwaukeeKaw TownshipDaytonSioux FallsUnited StatesOlatheOhioColumbus AreaWorthNOverland ParkAuroraWheelingGrand RapidsSchaumburgChicagoWichitaColumbusClevelandPalatineCapitalWarrenSpringfieldYork TownshipSt. LouisWashingtonBloomingdaleCtrCincinnatiAkronAnn ArborSt. PaulLisleMinneapolisSterling HtsDowners GrvMiltonMaine-1.000000x-1.000000x1.795144x1.795144x1.80x12.474%12.5%22.392%22.4%-1.000000x-1.000000x1.397781x1.397781x1.40x13.445%13.4%18.793%18.8%-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-1.000000x1.039581x1.039581x1.04x8.233%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%45-1.092939x-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
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#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
0x5x10xFM#MonroePerryRockfordNDaytonSioux FallsCapitalLawrenceDowners GrvAkronLisleWichitaYork TownshipMaineWarrenWheelingBlue TownshipSpringfieldOverland ParkMiltonGrand RapidsOlatheOhioOmahaFargoWashingtonEast North CentralLincolnMidwestBloomingdaleKansas CityColumbus AreaAuroraUnited StatesAnn ArborTopekaSterling HtsPalatineSchaumburgColumbusMadisonKaw TownshipMilwaukeeCedar RapidsClevelandCincinnatiSt. PaulSt. LouisChicagoWayneCtrToledoMinneapolisWorthDetroitProvisoThornton-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%0.254%0.25%-1.000000x-1.000000x6.135051x6.135051x6.14x0.188%0.19%1.155%1.15%-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-1.000000x1.457167x1.457167x1.46x2.851%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%49-1.706858x-1.706858x1.71x1.000000x1.000000x1.072%1.07%0.628%0.63%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 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 VlyMilwaukeePhiladelphiaOntarioMonroe TownshipMonroeChicagoBaltimorePerry CountyPerryOceanside-EscondidoOceanside-Escond…Las VegasPhoenixBostonSacramentoOrlandoAustinDenverUnited States of AmericaUnited StatesManhattanSan DiegoTampaSan JoseSan FranciscoTucsonAlbuquerqueTownship 1:Charlotte1, CharlotteColumbusTulsaEast North CentralOhioSalt Lake CitySalt Lk CityTown of HempsteadHempsteadMidwestNorthwest HarrisNW HarrisWashingtonAtlantaColumbus 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%71,39771.4k2116.974596%16.974596%17.0%14716.905373%16.905373%16.9%309,770310k2216.548703%16.548703%16.5%69,83969.8k2316.089529%16.089529%16.1%3,88915.999398%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%3,363,7843.36M10.514146%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%46,51046.5k459.538552%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
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#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 DallasMilwaukeeFresnoLas VegasEl PasoBronxSan BernardinoSan Antonio CentralSan Antonio CntrlDetroitMonroe TownshipMonroePerry CountyPerry60.434640%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%85,81285.8k4322.486319%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%59,72359.7k5012.009238%12.009238%12.0%10411.960614%11.960614%12.0%2,891
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#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 VlyOntarioFort WorthLas VegasMilwaukeeSan BernardinoSan Antonio CentralSan Antonio CntrlEl PasoSouthwest DallasSW DallasBronxDetroitPerry CountyPerryMonroe TownshipMonroe12.461852%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%9,688412.173239%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%15,06415.1k491.318660%1.318660%1.3%5,693500.666087%0.666087%0.7%1610.115473%0.115473%0.1%1
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#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#MonroePerry1, CharlotteDetroitBaltimoreTulsaSW DallasMidwestFresnoEast North CentralMilwaukeeUnited StatesOhioColumbus AreaNE DallasHoustonHempsteadOrlandoPhiladelphiaOntarioSan BernardinoAustinAtlantaFort WorthPhoenixChicagoAlbuquerqueWashingtonSacramentoColumbusSalt Lk CityDenverNE TarrantTampaOceanside-EscondidoOceanside-Escond…NW HarrisBronxPlanoBrooklynSan 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-1.000000x1.795144x1.795144x1.80x12.474%12.5%22.392%22.4%-1.000000x-1.000000x1.397781x1.397781x1.40x13.445%13.4%18.793%18.8%-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-1.000000x1.040742x1.040742x1.04x8.257%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%46-1.127548x-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#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
0x5x10xFM#MonroePerryEl PasoSalt Lk CityPlanoTulsaAlbuquerqueNE DallasFort WorthOhioOrlandoPhoenixTucson1, CharlotteEast North CentralMidwestNW HarrisLas VegasColumbus AreaSeattle EastSan Antonio CntrlSan DiegoUnited StatesSan JoseHempsteadFresnoNE 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%0.254%0.25%-1.000000x-1.000000x6.135051x6.135051x6.14x0.188%0.19%1.155%1.15%-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-1.000000x1.460302x1.460302x1.46x2.944%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:
Ohio
County:
Perry
Metro Area:
Columbus Area
Villages:
Corning, Rendville
ZIP Codes:
43730, 45732
Unified School Districts:
Crooksville, Southern
Congressional District:
OH-15
State Senate District:
OH-31
State House District:
OH-72
Neighboring Townships:
Bearfield, Coal, Deerfield, Homer, Pleasant, Salt Lick, Trimble, Union
Nearby Townships:
Dover, Harrison, Malta, Marion, Monday Creek, Penn, Pike, Ward, York, York