Educational Attainment in the Monroe Township, Howard County, Indiana (Township)

Educational Attainment#1

Highest level of education among people aged 25 years and older.
Scope: population of Howard County and the Monroe Township
Monroe Township
Howard County
0%10%20%30%40%50%60%CountHigher Degree1H.S. Diploma2No H.S. Diploma239.270833%27.899906%39.270833%39.3%37753.437500%60.591340%53.437500%53.4%5137.291667%11.508755%7.291667%7.3%70
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 Howard County at large.
Scope: population of Howard County and the Monroe Township
-40%-20%-0%+20%+40%%ref.Higher Degree1H.S. Diploma2No H.S. Diploma240.756151%40.756151%+40.8%39.271%39.3%27.900%27.9%-11.806703%-11.806703%-11.8%53.438%53.4%60.591%60.6%-36.642436%-36.642436%-36.6%7.292%7.29%11.509%11.5%
% percentage with given level in the Monroe Township
ref. percentage with given level in Howard 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 Howard County and the Monroe Township
Monroe Township
Howard County
0%10%20%30%CountDoctorate1Professional1Master's1Bachelor's1Associate's1Some CollegeHigh School2Some H.S.3Less than H.S.3None0.000000%0.000000%0.0%0.333764%01.458333%1.111383%1.458333%1.5%1414.791667%5.490511%14.791667%14.8%14212.187500%12.613148%12.187500%12.2%11710.833333%8.351099%10.833333%10.8%10420.937500%24.111418%20.937500%20.9%20132.500000%36.479922%32.500000%32.5%3125.104167%8.172858%5.104167%5.1%492.187500%2.173837%2.187500%2.2%210.000000%0.000000%0.0%1.162059%0
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 Howard County at large.
Scope: population of Howard 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%0.334%0.33%31.217898%31.217898%+31.2%1.458%1.46%1.111%1.11%169.404175%169.404175%+169.4%14.792%14.8%5.491%5.49%-3.374636%-3.374636%-3.4%12.188%12.2%12.613%12.6%29.723443%29.723443%+29.7%10.833%10.8%8.351%8.35%-13.163547%-13.163547%-13.2%20.938%20.9%24.111%24.1%-10.909897%-10.909897%-10.9%32.500%32.5%36.480%36.5%-37.547351%-37.547351%-37.5%5.104%5.10%8.173%8.17%0.628517%0.628517%+0.6%2.188%2.19%2.174%2.17%-100.000000%-100.000000%-100.0%0.000%0%1.162%1.16%
% percentage with given level in the Monroe Township
ref. percentage with given level in Howard 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 Howard County and the Monroe Township
More Females More Males
Howard County
Monroe Township
0%100%200%300%FMHigher Degree1H.S. Diploma2No H.S. Diploma2-13.754278%-0.043510%-13.754278%14%41.921%41.9%36.853%36.9%-8.332487%-3.837235%-8.332487%8%55.677%55.7%51.394%51.4%389.351684%21.954339%389.351684%389%2.402%2.40%11.753%11.8%
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 Howard County and the Monroe Township
More Females More Males
Howard County
Monroe Township
0%500%1,000%FMProfessional1Master's1Bachelor's1Associate's1Some CollegeHigh School2Some H.S.3Less than H.S.3-9.606987%-9.606987%10%112.517393%1.528%1.53%1.394%1.39%-235.084217%-10.657293%-235.084217%235%23.362%23.4%6.972%6.97%142.343127%3.218780%142.343127%142%6.987%6.99%16.932%16.9%-14.073139%15.035510%15.035510%15%10.044%10.0%11.554%11.6%-2.229594%-2.229594%2%2.839438%21.179%21.2%20.717%20.7%-12.453922%-8.462082%-12.453922%12%34.498%34.5%30.677%30.7%1,000.000000%2.870959%1,000.000000%> 1000%0.000%0%9.761%9.76%-20.567686%-20.567686%21%85.103213%2.402%2.40%1.992%1.99%
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 Howard County and the Monroe Township
Monroe Township
Howard County
0%5%10%15%B.X.Total65+45-6435-4425-347.920792%7.811130%7.920792%7.9%1620215.384615%13.880415%15.384615%15.4%6441610.727969%14.121511%10.727969%10.7%2826111.111111%15.436103%11.111111%11.1%981
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 Howard County at large.
Scope: population of Howard County and the Monroe Township
20%10%0%10%%ref.65+45-6435-4425-341.403923%1.403923%1.4%7.921%7.92%7.811%7.81%10.836855%10.836855%10.8%15.385%15.4%13.880%13.9%-24.031008%-24.031008%24.0%10.728%10.7%14.122%14.1%-28.018679%-28.018679%28.0%11.111%11.1%15.436%15.4%
% percentage in the Monroe Township with a Bachelor's degree
ref percentage in Howard 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 Howard County and the Monroe Township
More Females More Males
Howard County
Monroe Township
0%500%1,000%FM65+45-6435-4425-34-40.476190%-40.476190%40.5%71.384031%9.524%9.52%6.780%6.78%333.130699%3.205492%333.130699%333.1%6.140%6.14%26.596%26.6%-16.068886%57.985612%57.985612%58.0%8.197%8.20%12.950%12.9%-34.123646%1,000.000000%1,000.000000%> 1000%0.000%0%15.789%15.8%
F female degree holders as a percentage of all females
M male degree holders as a percentage of all males

Median Earnings by Educational Attainment#10

Among population 25 years old and over with earnings.
Scope: population of Howard County and the Monroe Township
Monroe Township
Howard County
$0k$20k$40k$60kCount%Graduate Degree1Some CollegeH.S. Diploma2Total$60,139.000000$56,553.000000$60,139.000000$60.1k15616.250%16.3%$41,111.000000$33,360.000000$41,111.000000$41.1k30531.771%31.8%$40,508.000000$27,724.000000$40,508.000000$40.5k31232.500%32.5%$42,531.000000$33,103.000000$42,531.000000$42.5k960100.000%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 Howard County and the Monroe Township
Female Male
Howard County
Monroe Township
Shaded bar tips show excess over facing bar.
$50k$0k$50kFMGraduate Degree1Some CollegeTotal$-44,432.000000$-54,205.000000$-44,432.000000$44.4k$44,432.000000$38,693.000000$54,205.000000$7,959.000000$83,125.000000$83.1k11442$-27,273.000000$-27,690.000000$-27,273.000000$27.3k$27,273.000000$21,298.000000$27,690.000000$15,538.000000$48,571.000000$48.6k143162$-36,118.000000$-27,817.000000$-36,118.000000$36.1k$36,118.000000$17,493.000000$27,817.000000$13,419.000000$53,611.000000$53.6k458502
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 Howard County and the Monroe Township
Monroe Township
Howard County
0%20%40%60%80%CountBachelor's Degree1Some College2H.S. Diploma3No H.S. Diploma390.041494%85.061150%90.041494%90.0%21789.015152%73.189824%89.015152%89.0%23564.676617%63.662668%64.676617%64.7%13040.384615%44.243738%40.384615%40.4%21
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 Howard County and the Monroe Township
Female Male
Howard County
Monroe Township
Shaded bar tips show excess over facing bar.
20%10%0%10%20%30%MFWhite1Hispanic2-2.455357%-10.215672%-2.455357%2.5%2.455357%9.487963%10.215672%1.458392%11.943320%11.9%5911-0.000000%-20.827586%0.000000%0.0%0.000000%0.000000%20.827586%18.699973%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 Howard County and the Monroe Township
Female Male
Howard County
Monroe Township
Shaded bar tips show excess over facing bar.
30%20%10%0%10%20%MFWhite1Hispanic2-25.708502%-6.880784%-19.525595%-32.589286%32.6%25.708502%19.525595%1.272496%25.708502%25.7%127146-0.000000%-13.931034%0.000000%0.0%0.000000%0.000000%13.931034%3.549280%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
39.96%40.24%40.52%40.80%41.08%41.36%

Coarse: High School Diploma Educational Attainment by Tract#16

Percentage of the population 25 years and older with given highest level of educational attainment
54.02%54.36%54.69%55.02%55.35%55.69%

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
4.35%4.41%4.46%4.51%4.56%4.62%

Detailed: Doctorate Degree Educational Attainment by Tract#18

Percentage of the population 25 years and older with given highest level of educational attainment
0.00%0.08%0.16%0.23%0.31%0.40%

Detailed: Professional Degree Educational Attainment by Tract#19

Percentage of the population 25 years and older with given highest level of educational attainment
1.11%1.38%1.64%1.90%2.16%2.42%

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

Percentage of the population 25 years and older with given highest level of educational attainment
8.1%8.9%9.6%10.4%11.1%11.9%

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

Percentage of the population 25 years and older with given highest level of educational attainment
17.1%18.1%19.0%19.9%20.9%21.8%

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

Percentage of the population 25 years and older with given highest level of educational attainment
7.6%8.3%8.9%9.5%10.2%10.8%

Detailed: Some College Educational Attainment by Tract#23

Percentage of the population 25 years and older with given highest level of educational attainment
24.1%24.9%25.6%26.4%27.1%27.9%

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

Percentage of the population 25 years and older with given highest level of educational attainment
27.84%28.25%28.66%29.07%29.48%29.90%

Detailed: Some High School Educational Attainment by Tract#25

Percentage of the population 25 years and older with given highest level of educational attainment
3.485%3.498%3.512%3.525%3.538%3.552%

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

Percentage of the population 25 years and older with given highest level of educational attainment
0.47%0.55%0.63%0.71%0.79%0.88%

Detailed: None Educational Attainment by Tract#27

Percentage of the population 25 years and older with given highest level of educational attainment
0.00%0.12%0.23%0.35%0.47%0.59%
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Educational Attainment by County Subdivision in the Kokomo Area

There are 11 county subdivisions in the Kokomo Area. This section compares the Monroe Township to all of the county subdivisions in the Kokomo Area and to those entities that contain or substantially overlap with the Monroe Township.

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 Kokomo Area, and entities that contain the Monroe Township
0%5%10%15%Count#Howard TownshipHowardUnion TownshipUnionCenter TownshipCtrUnited States of AmericaUnited StatesIndianaTaylor TownshipTaylorKokomo Metro AreaKokomo AreaHoward CountyHowardEast North CentralMidwestLiberty TownshipLibertyJackson TownshipJacksonMonroe TownshipMonroeHarrison TownshipHarrisonHoney Creek TownshipHoney CrkClay TownshipErvin TownshipErvin15.639269%15.639269%15.6%274115.294118%15.294118%15.3%117214.176197%14.176197%14.2%4,475313.020590%13.020590%13.0%27,818,38027.8M11.923855%11.923855%11.9%517,458517k11.796502%11.796502%11.8%742411.508755%11.508755%11.5%6,58611.508755%11.508755%11.5%6,58610.719464%10.719464%10.7%3,363,7843.36M10.244520%10.244520%10.2%4,641,8354.64M7.744875%7.744875%7.7%27257.692308%7.692308%7.7%1967.291667%7.291667%7.3%7076.041924%6.041924%6.0%39285.659121%5.659121%5.7%8593.827019%3.827019%3.8%100102.614379%2.614379%2.6%4011
Count number of people in category
# rank of county subdivision out of 11 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 Kokomo Area, and entities that contain the Monroe Township
0%10%20%30%Count#Clay TownshipErvin TownshipErvinHarrison TownshipHarrisonUnited States of AmericaUnited StatesMidwestEast North CentralMonroe TownshipMonroeHoney Creek TownshipHoney CrkIndianaHoward TownshipHowardTaylor TownshipTaylorKokomo Metro AreaKokomo AreaHoward CountyHowardLiberty TownshipLibertyUnion TownshipUnionCenter TownshipCtrJackson TownshipJackson33.027172%33.027172%33.0%863132.222222%32.222222%32.2%493231.365598%31.365598%31.4%2,035330.315023%30.315023%30.3%64,767,78764.8M28.952816%28.952816%29.0%13,118,64213.1M28.462853%28.462853%28.5%8,931,6868.93M28.437500%28.437500%28.4%273428.162450%28.162450%28.2%423524.611498%24.611498%24.6%1,068,0621.07M23.573059%23.573059%23.6%413621.875994%21.875994%21.9%1,376719.548806%19.548806%19.5%11,18711.2k19.548806%19.548806%19.5%11,18711.2k18.109339%18.109339%18.1%636817.777778%17.777778%17.8%136914.280736%14.280736%14.3%4,5081012.550607%12.550607%12.6%3111
Count number of people in category
# rank of county subdivision out of 11 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 Kokomo Area, and entities that contain the Monroe Township
0%1%2%3%Count#Harrison TownshipHarrisonUnited States of AmericaUnited StatesMidwestClay TownshipEast North CentralIndianaErvin TownshipErvinHoney Creek TownshipHoney CrkMonroe TownshipMonroeKokomo Metro AreaKokomo AreaHoward CountyHowardTaylor TownshipTaylorHoward TownshipHowardLiberty TownshipLibertyCenter TownshipCtrUnion TownshipUnionJackson TownshipJackson3.868681%3.868681%3.9%25113.336158%3.336158%3.3%7,127,6737.13M2.893416%2.893416%2.9%1,311,0191.31M2.870264%2.870264%2.9%7522.855432%2.855432%2.9%896,039896k2.359248%2.359248%2.4%102,384102k1.699346%1.699346%1.7%2631.531292%1.531292%1.5%2341.458333%1.458333%1.5%1451.445147%1.445147%1.4%8271.445147%1.445147%1.4%8271.271860%1.271860%1.3%8061.255708%1.255708%1.3%2270.996583%0.996583%1.0%3580.953527%0.953527%1.0%30190.000000%0.000000%0.0%0100.000000%0.000000%0.0%011
Count number of people in category
# rank of county subdivision out of 11 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 Kokomo Area, and entities that contain the Monroe Township
Female
Male
0x5x10xFM#JacksonMonroeErvinClay TownshipHarrisonLibertyCtrKokomo AreaHowardMidwestEast North CentralUnited StatesHowardIndianaUnionTaylorHoney Crk-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%17.925%17.9%1-1.000000x-1.000000x4.893517x4.893517x4.89x2.402%2.40%11.753%11.8%2-1.000000x-1.000000x2.393108x2.393108x2.39x1.511%1.51%3.616%3.62%3-1.000000x-1.000000x2.084948x2.084948x2.08x2.533%2.53%5.280%5.28%4-1.000000x-1.000000x1.504216x1.504216x1.50x4.828%4.83%7.262%7.26%5-1.000000x-1.000000x1.413063x1.413063x1.41x6.430%6.43%9.086%9.09%6-1.000000x-1.000000x1.268582x1.268582x1.27x12.634%12.6%16.027%16.0%7-1.000000x-1.000000x1.219543x1.219543x1.22x10.434%10.4%12.725%12.7%-1.000000x-1.000000x1.219543x1.219543x1.22x10.434%10.4%12.725%12.7%-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-1.000000x1.109070x1.109070x1.11x12.369%12.4%13.719%13.7%-1.000000x-1.000000x1.102684x1.102684x1.10x14.975%15.0%16.513%16.5%8-1.000000x-1.000000x1.101821x1.101821x1.10x11.365%11.4%12.522%12.5%-1.000000x-1.000000x1.044408x1.044408x1.04x14.961%15.0%15.625%15.6%9-1.066164x-1.066164x1.07x1.000000x1.000000x12.155%12.2%11.401%11.4%10-2.368254x-2.368254x2.37x1.000000x1.000000x7.937%7.94%3.351%3.35%11
F percentage of females in category
M percentage of males in category
# rank of county subdivision out of 11 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 Kokomo Area, and entities that contain the Monroe Township
Female
Male
10x5x0x5xFM#Clay TownshipCtrHarrisonKokomo AreaHowardIndianaEast North CentralMidwestLibertyUnited StatesMonroeHoney CrkTaylorErvinHoward-1.000000x-1.000000x8.232873x8.232873x8.23x0.651%0.65%5.361%5.36%1-1.000000x-1.000000x4.920548x4.920548x4.92x0.343%0.34%1.686%1.69%2-1.000000x-1.000000x2.704483x2.704483x2.70x2.091%2.09%5.655%5.66%3-1.000000x-1.000000x2.426957x2.426957x2.43x0.866%0.87%2.101%2.10%-1.000000x-1.000000x2.426957x2.426957x2.43x0.866%0.87%2.101%2.10%-1.000000x-1.000000x1.691858x1.691858x1.69x1.769%1.77%2.992%2.99%-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-1.000000x1.529327x1.529327x1.53x0.790%0.79%1.208%1.21%4-1.000000x-1.000000x1.526215x1.526215x1.53x2.660%2.66%4.060%4.06%-1.096070x-1.096070x1.10x1.000000x1.000000x1.528%1.53%1.394%1.39%5-1.534979x-1.534979x1.53x1.000000x1.000000x1.852%1.85%1.206%1.21%6-1.683757x-1.683757x1.68x1.000000x1.000000x1.576%1.58%0.936%0.94%7-2.478709x-2.478709x2.48x1.000000x1.000000x2.473%2.47%0.998%1.00%8-10.000000x-10.000000x> 10.0x1.000000x1.000000x2.211%2.21%0.000%0%9
F percentage of females in category
M percentage of males in category
# rank of county subdivision out of 9 by male-to-female sex ratio

Educational Attainment by County Subdivision in Indiana

There are 1,012 county subdivisions in Indiana. This section compares the Monroe Township to the 50 most populous county subdivisions in Indiana 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 32,697.

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 Indiana, and entities that contain the Monroe Township
0%5%10%15%20%Count#Center TownshipCtrConcord TownshipConcordWayne TownshipWayneElkhart TownshipElkhartPortage TownshipPortageWayne TownshipWayneWayne TownshipWayneNorth TownshipNHarrison TownshipHarrisonWarren TownshipWarrenAdams TownshipAdamsHobart TownshipHobartAnderson TownshipAndersonCalumet TownshipCalumetPerry TownshipPerryCenter TownshipCtrDecatur TownshipDecaturNew Albany TownshipNew AlbanyCenter TownshipCtrUnited States of AmericaUnited StatesJeffersonville TownshipJeffersonvilleFairfield TownshipFairfieldIndianaWashington TownshipWashingtonPenn TownshipWea TownshipKokomo Metro AreaKokomo AreaHoward CountyHowardPortage TownshipPortageEast North CentralKnight TownshipKnightMidwestLawrence TownshipLawrencePike TownshipRoss TownshipClay TownshipColumbus TownshipColumbusPleasant TownshipPleasantBloomington TownshipBloomingtonCenter TownshipCtrMonroe TownshipMonroeFranklin TownshipFranklinSt. Joseph TownshipSt. JosephWashington TownshipWashingtonWabash TownshipWabashNoblesville TownshipNoblesvilleSt. John TownshipSt. JohnPerry TownshipPerryWashington TownshipWashingtonOhio TownshipWhite River TownshipWhite RivCenter TownshipCtrWashington TownshipWashingtonFall Creek TownshipFall CrkDelaware TownshipDelawareAboite TownshipAboiteClay Township23.165532%23.165532%23.2%22,92622.9k121.816299%21.816299%21.8%7,584221.037720%21.037720%21.0%18,48918.5k321.001088%21.001088%21.0%5,018419.418924%19.418924%19.4%10,54710.5k518.195035%18.195035%18.2%5,006617.532152%17.532152%17.5%11,56011.6k717.062713%17.062713%17.1%17,39117.4k815.973269%15.973269%16.0%4,876915.481486%15.481486%15.5%10,30210.3k1015.213692%15.213692%15.2%3,1291115.089946%15.089946%15.1%4,0181214.786671%14.786671%14.8%5,5071314.467691%14.467691%14.5%9,5291414.326632%14.326632%14.3%10,55410.6k1514.176197%14.176197%14.2%4,4751613.599622%13.599622%13.6%2,8771713.529737%13.529737%13.5%4,6431813.471419%13.471419%13.5%5,0341913.020590%13.020590%13.0%27,818,38027.8M13.003477%13.003477%13.0%5,4982012.444341%12.444341%12.4%4,2762111.923855%11.923855%11.9%517,458517k11.655058%11.655058%11.7%2,9452211.623484%11.623484%11.6%5,1952311.557160%11.557160%11.6%2,4012411.508755%11.508755%11.5%6,58611.508755%11.508755%11.5%6,58611.495287%11.495287%11.5%3,7072510.719464%10.719464%10.7%3,363,7843.36M10.287806%10.287806%10.3%4,7222610.244520%10.244520%10.2%4,641,8354.64M10.179618%10.179618%10.2%8,161279.909467%9.909467%9.9%5,035289.596081%9.596081%9.6%3,193299.305117%9.305117%9.3%2,093309.026455%9.026455%9.0%2,890318.654557%8.654557%8.7%3,159328.319071%8.319071%8.3%1,361337.616061%7.616061%7.6%2,113347.291667%7.291667%7.3%707.113476%7.113476%7.1%2,473357.107130%7.107130%7.1%3,467366.804680%6.804680%6.8%6,403376.335308%6.335308%6.3%1,476386.187687%6.187687%6.2%2,197395.972798%5.972798%6.0%2,793405.962782%5.962782%6.0%1,945415.826158%5.826158%5.8%1,793425.604955%5.604955%5.6%1,475435.183872%5.183872%5.2%1,521445.023085%5.023085%5.0%1,447454.507433%4.507433%4.5%1,040463.059982%3.059982%3.1%1,081472.923599%2.923599%2.9%680482.546689%2.546689%2.5%630492.265751%2.265751%2.3%1,37350
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 Indiana, and entities that contain the Monroe Township
0%20%40%60%Count#Clay TownshipFall Creek TownshipFall CrkWabash TownshipWabashDelaware TownshipDelawarePerry TownshipPerryWashington TownshipWashingtonBloomington TownshipBloomingtonWashington TownshipWashingtonAboite TownshipAboiteWhite River TownshipWhite RivNoblesville TownshipNoblesvilleClay TownshipCenter TownshipCtrWashington TownshipWashingtonPike TownshipLawrence TownshipLawrenceColumbus TownshipColumbusOhio TownshipFranklin TownshipFranklinSt. Joseph TownshipSt. JosephSt. John TownshipSt. JohnCenter TownshipCtrUnited States of AmericaUnited StatesMidwestEast North CentralMonroe TownshipMonroeFairfield TownshipFairfieldPleasant TownshipPleasantWea TownshipWashington TownshipWashingtonIndianaPerry TownshipPerryPenn TownshipKnight TownshipKnightRoss TownshipNew Albany TownshipNew AlbanyElkhart TownshipElkhartPortage TownshipPortageCenter TownshipCtrCenter TownshipCtrNorth TownshipNKokomo Metro AreaKokomo AreaHoward CountyHowardHarrison TownshipHarrisonWarren TownshipWarrenJeffersonville TownshipJeffersonvilleWayne TownshipWayneWayne TownshipWayneWayne TownshipWaynePortage TownshipPortageHobart TownshipHobartDecatur TownshipDecaturAnderson TownshipAndersonAdams TownshipAdamsCenter TownshipCtrConcord TownshipConcordCalumet TownshipCalumet68.328988%68.328988%68.3%41,40641.4k165.318312%65.318312%65.3%23,07523.1k261.284230%61.284230%61.3%14,27814.3k356.851111%56.851111%56.9%13,22313.2k455.639351%55.639351%55.6%18,14918.1k553.478091%53.478091%53.5%12,33912.3k653.202934%53.202934%53.2%8,704750.610540%50.610540%50.6%47,62347.6k850.044466%50.044466%50.0%12,38012.4k942.452541%42.452541%42.5%12,45612.5k1042.333690%42.333690%42.3%15,03115.0k1139.376695%39.376695%39.4%8,8571239.368903%39.368903%39.4%11,34111.3k1338.953696%38.953696%39.0%11,98812.0k1437.193466%37.193466%37.2%18,89818.9k1536.577273%36.577273%36.6%29,32429.3k1635.515507%35.515507%35.5%11,37111.4k1734.397325%34.397325%34.4%9,0521834.336258%34.336258%34.3%11,93711.9k1931.579271%31.579271%31.6%15,40515.4k2031.570506%31.570506%31.6%14,76314.8k2130.875144%30.875144%30.9%8,5662230.315023%30.315023%30.3%64,767,78764.8M28.952816%28.952816%29.0%13,118,64213.1M28.462853%28.462853%28.5%8,931,6868.93M28.437500%28.437500%28.4%27326.099357%26.099357%26.1%8,9682325.634914%25.634914%25.6%9,3572424.837545%24.837545%24.8%5,1602524.738800%24.738800%24.7%6,2512624.611498%24.611498%24.6%1,068,0621.07M24.563237%24.563237%24.6%18,09518.1k2724.367924%24.367924%24.4%10,89110.9k2823.643217%23.643217%23.6%10,85210.9k2923.381619%23.381619%23.4%7,7803023.320803%23.320803%23.3%8,0033122.511928%22.511928%22.5%5,3793221.836393%21.836393%21.8%11,86011.9k3321.823485%21.823485%21.8%8,1553420.139240%20.139240%20.1%19,93119.9k3519.650916%19.650916%19.7%20,02920.0k3619.548806%19.548806%19.5%11,18711.2k19.548806%19.548806%19.5%11,18711.2k19.262268%19.262268%19.3%5,8803719.034023%19.034023%19.0%12,66612.7k3818.228046%18.228046%18.2%7,7073917.915858%17.915858%17.9%11,81311.8k4016.897467%16.897467%16.9%4,6494116.826535%16.826535%16.8%14,78814.8k4215.836641%15.836641%15.8%5,1074315.364104%15.364104%15.4%4,0914415.140629%15.140629%15.1%3,2034514.996107%14.996107%15.0%5,5854614.654544%14.654544%14.7%3,0144714.280736%14.280736%14.3%4,5084813.804908%13.804908%13.8%4,7994913.054172%13.054172%13.1%8,59850
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 Indiana, and entities that contain the Monroe Township
0%5%10%Count#Wabash TownshipWabashClay TownshipPerry TownshipPerryFall Creek TownshipFall CrkBloomington TownshipBloomingtonWashington TownshipWashingtonClay TownshipAboite TownshipAboiteWashington TownshipWashingtonCenter TownshipCtrDelaware TownshipDelawarePike TownshipOhio TownshipNoblesville TownshipNoblesvilleUnited States of AmericaUnited StatesWhite River TownshipWhite RivPortage TownshipPortageLawrence TownshipLawrenceMidwestEast North CentralSt. Joseph TownshipSt. JosephCenter TownshipCtrCenter TownshipCtrSt. John TownshipSt. JohnFairfield TownshipFairfieldCenter TownshipCtrColumbus TownshipColumbusFranklin TownshipFranklinIndianaPerry TownshipPerryKnight TownshipKnightElkhart TownshipElkhartHarrison TownshipHarrisonWashington TownshipWashingtonWayne TownshipWayneWashington TownshipWashingtonNew Albany TownshipNew AlbanyNorth TownshipNPenn TownshipJeffersonville TownshipJeffersonvilleMonroe TownshipMonroeWea TownshipKokomo Metro AreaKokomo AreaHoward CountyHowardRoss TownshipPortage TownshipPortageWayne TownshipWayneAnderson TownshipAndersonWayne TownshipWaynePleasant TownshipPleasantCenter TownshipCtrConcord TownshipConcordAdams TownshipAdamsWarren TownshipWarrenCalumet TownshipCalumetHobart TownshipHobartDecatur TownshipDecatur14.996995%14.996995%15.0%3,494110.452490%10.452490%10.5%6,334210.377387%10.377387%10.4%3,38538.741189%8.741189%8.7%3,08848.068460%8.068460%8.1%1,32057.306290%7.306290%7.3%6,87566.704308%6.704308%6.7%1,50876.269707%6.269707%6.3%1,55185.209552%5.209552%5.2%1,20295.016142%5.016142%5.0%1,445104.965820%4.965820%5.0%1,155114.833694%4.833694%4.8%2,456123.921569%3.921569%3.9%1,032133.393793%3.393793%3.4%1,205143.336158%3.336158%3.3%7,127,6737.13M3.220749%3.220749%3.2%945153.122641%3.122641%3.1%1,696163.083448%3.083448%3.1%2,472172.893416%2.893416%2.9%1,311,0191.31M2.855432%2.855432%2.9%896,039896k2.830962%2.830962%2.8%1,381182.676086%2.676086%2.7%1,000192.602914%2.602914%2.6%2,576202.564048%2.564048%2.6%1,199212.482466%2.482466%2.5%853222.454585%2.454585%2.5%681232.401849%2.401849%2.4%769242.384582%2.384582%2.4%829252.359248%2.359248%2.4%102,384102k2.212660%2.212660%2.2%1,630262.146016%2.146016%2.1%985272.105131%2.105131%2.1%503282.083470%2.083470%2.1%636292.043867%2.043867%2.0%629301.879112%1.879112%1.9%517311.800697%1.800697%1.8%455321.690124%1.690124%1.7%580331.575684%1.575684%1.6%1,606341.557256%1.557256%1.6%696351.506587%1.506587%1.5%637361.458333%1.458333%1.5%141.448857%1.448857%1.4%301371.445147%1.445147%1.4%8271.445147%1.445147%1.4%8271.412514%1.412514%1.4%470381.305507%1.305507%1.3%421391.183365%1.183365%1.2%1,040401.146524%1.146524%1.1%427411.143533%1.143533%1.1%754421.021890%1.021890%1.0%373430.953527%0.953527%1.0%301440.917642%0.917642%0.9%319450.875188%0.875188%0.9%180460.840046%0.840046%0.8%559470.816835%0.816835%0.8%538480.811207%0.811207%0.8%216490.581423%0.581423%0.6%12350
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 Indiana, and entities that contain the Monroe Township
Female
Male
0x2x4xFM#MonroeNoblesvilleWabashCtrWea TownshipAdamsWarrenFranklinElkhartSt. JosephKokomo AreaHowardWashingtonWayneClay TownshipPerryLawrenceCalumetPenn TownshipJeffersonvilleOhio TownshipPike TownshipWayneMidwestPerryEast North CentralUnited StatesRoss TownshipIndianaNBloomingtonWashingtonKnightPortageAndersonHobartDecaturWashingtonCtrCtrWaynePortageWashingtonConcordNew AlbanyCtrFairfieldAboiteColumbusPleasantSt. JohnDelawareHarrisonCtrWhite RivClay TownshipFall Crk-1.000000x-1.000000x4.893517x4.893517x4.89x2.402%2.40%11.753%11.8%-1.000000x-1.000000x1.368916x1.368916x1.37x5.278%5.28%7.225%7.22%1-1.000000x-1.000000x1.315975x1.315975x1.32x5.455%5.46%7.179%7.18%2-1.000000x-1.000000x1.268582x1.268582x1.27x12.634%12.6%16.027%16.0%3-1.000000x-1.000000x1.261563x1.261563x1.26x10.300%10.3%12.994%13.0%4-1.000000x-1.000000x1.243110x1.243110x1.24x13.682%13.7%17.008%17.0%5-1.000000x-1.000000x1.242727x1.242727x1.24x13.919%13.9%17.298%17.3%6-1.000000x-1.000000x1.229379x1.229379x1.23x6.415%6.42%7.887%7.89%7-1.000000x-1.000000x1.228271x1.228271x1.23x18.842%18.8%23.143%23.1%8-1.000000x-1.000000x1.222685x1.222685x1.22x6.437%6.44%7.871%7.87%9-1.000000x-1.000000x1.219543x1.219543x1.22x10.434%10.4%12.725%12.7%-1.000000x-1.000000x1.219543x1.219543x1.22x10.434%10.4%12.725%12.7%-1.000000x-1.000000x1.218680x1.218680x1.22x4.077%4.08%4.969%4.97%10-1.000000x-1.000000x1.199569x1.199569x1.20x15.997%16.0%19.190%19.2%11-1.000000x-1.000000x1.195034x1.195034x1.20x2.075%2.07%2.479%2.48%12-1.000000x-1.000000x1.184825x1.184825x1.18x13.166%13.2%15.600%15.6%13-1.000000x-1.000000x1.181964x1.181964x1.18x9.406%9.41%11.117%11.1%14-1.000000x-1.000000x1.168789x1.168789x1.17x13.469%13.5%15.743%15.7%15-1.000000x-1.000000x1.164733x1.164733x1.16x10.782%10.8%12.558%12.6%16-1.000000x-1.000000x1.161888x1.161888x1.16x12.085%12.1%14.041%14.0%17-1.000000x-1.000000x1.151492x1.151492x1.15x5.223%5.22%6.014%6.01%18-1.000000x-1.000000x1.134102x1.134102x1.13x9.351%9.35%10.605%10.6%19-1.000000x-1.000000x1.132245x1.132245x1.13x19.779%19.8%22.395%22.4%20-1.000000x-1.000000x1.127915x1.127915x1.13x9.647%9.65%10.881%10.9%-1.000000x-1.000000x1.126339x1.126339x1.13x5.616%5.62%6.326%6.33%21-1.000000x-1.000000x1.125371x1.125371x1.13x10.108%10.1%11.375%11.4%-1.000000x-1.000000x1.109070x1.109070x1.11x12.369%12.4%13.719%13.7%-1.000000x-1.000000x1.106906x1.106906x1.11x9.131%9.13%10.107%10.1%22-1.000000x-1.000000x1.101821x1.101821x1.10x11.365%11.4%12.522%12.5%-1.000000x-1.000000x1.096598x1.096598x1.10x16.317%16.3%17.894%17.9%23-1.000000x-1.000000x1.083251x1.083251x1.08x7.983%7.98%8.648%8.65%24-1.000000x-1.000000x1.081415x1.081415x1.08x11.208%11.2%12.121%12.1%25-1.000000x-1.000000x1.068180x1.068180x1.07x9.969%9.97%10.648%10.6%26-1.000000x-1.000000x1.056311x1.056311x1.06x18.916%18.9%19.981%20.0%27-1.000000x-1.000000x1.055380x1.055380x1.06x14.413%14.4%15.211%15.2%28-1.000000x-1.000000x1.049767x1.049767x1.05x14.731%14.7%15.464%15.5%29-1.000000x-1.000000x1.032740x1.032740x1.03x13.380%13.4%13.818%13.8%30-1.000000x-1.000000x1.013146x1.013146x1.01x6.764%6.76%6.853%6.85%31-1.000000x-1.000000x1.010381x1.010381x1.01x13.405%13.4%13.544%13.5%32-1.000000x-1.000000x1.006204x1.006204x1.01x23.095%23.1%23.239%23.2%33-1.011355x-1.011355x1.01x1.000000x1.000000x18.290%18.3%18.085%18.1%34-1.015833x-1.015833x1.02x1.000000x1.000000x11.580%11.6%11.399%11.4%35-1.022668x-1.022668x1.02x1.000000x1.000000x5.889%5.89%5.758%5.76%36-1.025563x-1.025563x1.03x1.000000x1.000000x22.081%22.1%21.530%21.5%37-1.038459x-1.038459x1.04x1.000000x1.000000x13.769%13.8%13.259%13.3%38-1.071041x-1.071041x1.07x1.000000x1.000000x5.189%5.19%4.845%4.84%39-1.089549x-1.089549x1.09x1.000000x1.000000x12.962%13.0%11.897%11.9%40-1.093153x-1.093153x1.09x1.000000x1.000000x2.650%2.65%2.424%2.42%41-1.099707x-1.099707x1.10x1.000000x1.000000x9.439%9.44%8.583%8.58%42-1.102703x-1.102703x1.10x1.000000x1.000000x9.045%9.05%8.203%8.20%43-1.112325x-1.112325x1.11x1.000000x1.000000x6.278%6.28%5.644%5.64%44-1.142082x-1.142082x1.14x1.000000x1.000000x3.107%3.11%2.720%2.72%45-1.170944x-1.170944x1.17x1.000000x1.000000x17.156%17.2%14.651%14.7%46-1.194691x-1.194691x1.19x1.000000x1.000000x8.269%8.27%6.921%6.92%47-1.236588x-1.236588x1.24x1.000000x1.000000x5.712%5.71%4.619%4.62%48-1.340641x-1.340641x1.34x1.000000x1.000000x10.604%10.6%7.910%7.91%49-1.421606x-1.421606x1.42x1.000000x1.000000x3.566%3.57%2.508%2.51%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 Indiana, and entities that contain the Monroe Township
Female
Male
0x2x4xFM#AdamsCtrConcordClay TownshipOhio TownshipAboiteAndersonKokomo AreaHowardCtrNWhite RivSt. JosephClay TownshipCtrWabashColumbusWashingtonLawrenceSt. JohnWayneFranklinDecaturPenn TownshipIndianaNew AlbanyPerryWashingtonKnightEast North CentralMidwestRoss TownshipUnited StatesPike TownshipPerryWayneFairfieldPortageNoblesvilleDelawareFall CrkWarrenWayneCtrBloomingtonPleasantElkhartJeffersonvilleHarrisonHobartWea TownshipPortageCalumetMonroeCtrWashingtonWashington-1.000000x-1.000000x5.217819x5.217819x5.22x0.297%0.30%1.552%1.55%1-1.000000x-1.000000x4.920548x4.920548x4.92x0.343%0.34%1.686%1.69%2-1.000000x-1.000000x4.308574x4.308574x4.31x0.354%0.35%1.527%1.53%3-1.000000x-1.000000x3.730733x3.730733x3.73x2.894%2.89%10.796%10.8%4-1.000000x-1.000000x2.941854x2.941854x2.94x2.023%2.02%5.951%5.95%5-1.000000x-1.000000x2.935012x2.935012x2.94x3.322%3.32%9.751%9.75%6-1.000000x-1.000000x2.902465x2.902465x2.90x0.606%0.61%1.760%1.76%7-1.000000x-1.000000x2.426957x2.426957x2.43x0.866%0.87%2.101%2.10%-1.000000x-1.000000x2.426957x2.426957x2.43x0.866%0.87%2.101%2.10%-1.000000x-1.000000x2.143087x2.143087x2.14x1.728%1.73%3.704%3.70%8-1.000000x-1.000000x2.111054x2.111054x2.11x1.033%1.03%2.181%2.18%9-1.000000x-1.000000x2.098144x2.098144x2.10x2.104%2.10%4.415%4.41%10-1.000000x-1.000000x1.977884x1.977884x1.98x1.943%1.94%3.843%3.84%11-1.000000x-1.000000x1.973355x1.973355x1.97x7.159%7.16%14.128%14.1%12-1.000000x-1.000000x1.956253x1.956253x1.96x3.435%3.43%6.719%6.72%13-1.000000x-1.000000x1.928515x1.928515x1.93x10.174%10.2%19.620%19.6%14-1.000000x-1.000000x1.918490x1.918490x1.92x1.665%1.66%3.194%3.19%15-1.000000x-1.000000x1.906040x1.906040x1.91x3.625%3.63%6.910%6.91%16-1.000000x-1.000000x1.879271x1.879271x1.88x2.206%2.21%4.146%4.15%17-1.000000x-1.000000x1.837195x1.837195x1.84x1.827%1.83%3.357%3.36%18-1.000000x-1.000000x1.820086x1.820086x1.82x1.362%1.36%2.478%2.48%19-1.000000x-1.000000x1.797904x1.797904x1.80x1.730%1.73%3.110%3.11%20-1.000000x-1.000000x1.787156x1.787156x1.79x0.417%0.42%0.745%0.75%21-1.000000x-1.000000x1.709561x1.709561x1.71x1.165%1.17%1.992%1.99%22-1.000000x-1.000000x1.691858x1.691858x1.69x1.769%1.77%2.992%2.99%-1.000000x-1.000000x1.657824x1.657824x1.66x1.291%1.29%2.141%2.14%23-1.000000x-1.000000x1.654297x1.654297x1.65x7.864%7.86%13.009%13.0%24-1.000000x-1.000000x1.610803x1.610803x1.61x5.701%5.70%9.183%9.18%25-1.000000x-1.000000x1.605585x1.605585x1.61x1.671%1.67%2.683%2.68%26-1.000000x-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-1.000000x1.536785x1.536785x1.54x1.125%1.12%1.729%1.73%27-1.000000x-1.000000x1.526215x1.526215x1.53x2.660%2.66%4.060%4.06%-1.000000x-1.000000x1.518639x1.518639x1.52x3.926%3.93%5.963%5.96%28-1.000000x-1.000000x1.514015x1.514015x1.51x1.777%1.78%2.691%2.69%29-1.000000x-1.000000x1.497053x1.497053x1.50x0.923%0.92%1.382%1.38%30-1.000000x-1.000000x1.446563x1.446563x1.45x2.040%2.04%2.950%2.95%31-1.000000x-1.000000x1.417405x1.417405x1.42x2.609%2.61%3.697%3.70%32-1.000000x-1.000000x1.361506x1.361506x1.36x2.903%2.90%3.953%3.95%33-1.000000x-1.000000x1.354365x1.354365x1.35x4.251%4.25%5.758%5.76%34-1.000000x-1.000000x1.329765x1.329765x1.33x7.550%7.55%10.040%10.0%35-1.000000x-1.000000x1.317700x1.317700x1.32x0.732%0.73%0.965%0.97%36-1.000000x-1.000000x1.223931x1.223931x1.22x1.068%1.07%1.307%1.31%37-1.000000x-1.000000x1.213574x1.213574x1.21x2.357%2.36%2.860%2.86%38-1.000000x-1.000000x1.199873x1.199873x1.20x7.328%7.33%8.793%8.79%39-1.000000x-1.000000x1.199817x1.199817x1.20x0.935%0.94%1.122%1.12%40-1.000000x-1.000000x1.149524x1.149524x1.15x1.958%1.96%2.251%2.25%41-1.000000x-1.000000x1.147252x1.147252x1.15x1.409%1.41%1.617%1.62%42-1.000000x-1.000000x1.131803x1.131803x1.13x1.961%1.96%2.220%2.22%43-1.000000x-1.000000x1.103144x1.103144x1.10x0.772%0.77%0.852%0.85%44-1.000000x-1.000000x1.090487x1.090487x1.09x1.390%1.39%1.516%1.52%45-1.000000x-1.000000x1.050088x1.050088x1.05x1.276%1.28%1.340%1.34%46-1.064408x-1.064408x1.06x1.000000x1.000000x0.839%0.84%0.788%0.79%47-1.096070x-1.096070x1.10x1.000000x1.000000x1.528%1.53%1.394%1.39%-1.164720x-1.164720x1.16x1.000000x1.000000x2.635%2.64%2.262%2.26%48-1.189996x-1.189996x1.19x1.000000x1.000000x1.953%1.95%1.641%1.64%49-1.308468x-1.308468x1.31x1.000000x1.000000x2.305%2.31%1.762%1.76%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 TownshipNDaytonChicagoProviso TownshipProvisoRockford TownshipRockfordSt. LouisWarrenGrand RapidsToledoBlue TownshipCincinnatiAkronSt. PaulSterling HeightsSterling HtsUnited States of AmericaUnited StatesThornton TownshipThorntonWichitaKaw TownshipOmahaBloomingdale TownshipBloomingdaleIndianaKokomo Metro AreaKokomo AreaHoward CountyHowardColumbusMaine TownshipMaineTopekaMinneapolisSpringfield TownshipSpringfieldEast North CentralWorth TownshipWorthMidwestLawrence TownshipLawrenceSioux FallsCapital TownshipCapitalWheeling TownshipWheelingPalatine TownshipPalatineSchaumburg TownshipSchaumburgMonroe TownshipMonroeLincolnWashington TownshipWashingtonOlatheFargoCedar RapidsYork TownshipMilton TownshipMiltonMadisonDowners Grove TownshipDowners GrvLisle TownshipLisleOverland ParkAnn Arbor33.464284%33.464284%33.5%29,81429.8k123.165532%23.165532%23.2%22,92622.9k222.659362%22.659362%22.7%21,21821.2k321.582420%21.582420%21.6%54,98155.0k421.037720%21.037720%21.0%18,48918.5k521.003600%21.003600%21.0%90,67890.7k617.485105%17.485105%17.5%63,80063.8k717.062713%17.062713%17.1%17,39117.4k816.928359%16.928359%16.9%14,88914.9k916.905373%16.905373%16.9%309,770310k1015.636222%15.636222%15.6%16,11016.1k1115.608074%15.608074%15.6%18,24118.2k1215.466266%15.466266%15.5%33,80433.8k1315.286174%15.286174%15.3%14,05914.1k1414.563179%14.563179%14.6%17,64317.6k1514.332972%14.332972%14.3%26,34326.3k1614.241047%14.241047%14.2%15,25815.3k1713.761583%13.761583%13.8%26,28626.3k1813.591726%13.591726%13.6%17,95118.0k1913.278342%13.278342%13.3%24,61324.6k2013.132171%13.132171%13.1%12,21212.2k2113.020590%13.020590%13.0%27,818,38027.8M12.974232%12.974232%13.0%14,37014.4k2212.568464%12.568464%12.6%31,23131.2k2312.455744%12.455744%12.5%15,16315.2k2412.198899%12.198899%12.2%35,05035.1k2512.171847%12.171847%12.2%9,3752611.923855%11.923855%11.9%517,458517k11.508755%11.508755%11.5%6,58611.508755%11.508755%11.5%6,58611.376979%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%11,17511.2k3210.244520%10.244520%10.2%4,641,8354.64M10.179618%10.179618%10.2%8,161339.702326%9.702326%9.7%9,123348.623103%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%7,226387.291667%7.291667%7.3%707.092309%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 TownshipCapitalColumbusOmahaCincinnatiSt. LouisGrand RapidsBloomingdale TownshipBloomingdaleCedar RapidsUnited States of AmericaUnited StatesSioux FallsMidwestWichitaEast North CentralMonroe TownshipMonroeSterling HeightsSterling HtsTopekaSpringfield TownshipSpringfieldProviso TownshipProvisoWorth TownshipWorthIndianaMilwaukeeRockford TownshipRockfordAkronCenter TownshipCtrNorth TownshipNKokomo Metro AreaKokomo AreaHoward CountyHowardThornton TownshipThorntonToledoDaytonWarrenWayne TownshipWayneKansas CityClevelandAurora TownshipAuroraBlue TownshipDetroit72.810169%72.810169%72.8%47,43047.4k158.823344%58.823344%58.8%74,57874.6k257.681507%57.681507%57.7%45,19045.2k356.900171%56.900171%56.9%46,35646.4k456.337583%56.337583%56.3%85,63285.6k553.762123%53.762123%53.8%55,71155.7k650.610540%50.610540%50.6%47,62347.6k749.860853%49.860853%49.9%39,77539.8k849.728972%49.728972%49.7%42,93542.9k947.670489%47.670489%47.7%127,663128k1046.512581%46.512581%46.5%38,59838.6k1146.409378%46.409378%46.4%51,46851.5k1241.792515%41.792515%41.8%39,02039.0k1341.581304%41.581304%41.6%50,61950.6k1439.969357%39.969357%40.0%74,08874.1k1539.511462%39.511462%39.5%38,91838.9k1638.241175%38.241175%38.2%26,96527.0k1737.146608%37.146608%37.1%62,25462.3k1836.577273%36.577273%36.6%29,32429.3k1936.546320%36.546320%36.5%669,666670k2036.298510%36.298510%36.3%28,78028.8k2134.685843%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%8,931,6868.93M28.437500%28.437500%28.4%27327.532180%27.532180%27.5%25,60325.6k3127.007248%27.007248%27.0%22,95423.0k3226.964567%26.964567%27.0%27,92127.9k3326.237989%26.237989%26.2%27,03327.0k3425.217641%25.217641%25.2%26,38926.4k3524.611498%24.611498%24.6%1,068,0621.07M23.517740%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%20,02920.0k4019.548806%19.548806%19.5%11,18711.2k19.548806%19.548806%19.5%11,18711.2k18.971090%18.971090%19.0%21,01221.0k4118.048021%18.048021%18.0%33,17133.2k4217.635555%17.635555%17.6%15,51115.5k4317.280259%17.280259%17.3%15,89315.9k4416.826535%16.826535%16.8%14,78814.8k4516.167409%16.167409%16.2%15,13915.1k4616.073076%16.073076%16.1%40,94640.9k4715.929601%15.929601%15.9%14,19214.2k4815.821208%15.821208%15.8%16,95117.0k4913.833543%13.833543%13.8%59,72359.7k50
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 TownshipMainePalatine TownshipPalatineWheeling TownshipWheelingColumbusUnited States of AmericaUnited StatesTopekaGrand RapidsLawrence TownshipLawrenceSpringfield TownshipSpringfieldCedar RapidsMidwestEast North CentralSioux FallsOlatheCenter TownshipCtrSchaumburg TownshipSchaumburgWichitaIndianaProviso TownshipProvisoAkronBloomingdale TownshipBloomingdaleRockford TownshipRockfordMilwaukeeWorth TownshipWorthClevelandToledoNorth TownshipNMonroe TownshipMonroeKokomo Metro AreaKokomo AreaHoward CountyHowardSterling HeightsSterling HtsKansas CityDetroitDaytonWayne TownshipWayneWarrenBlue TownshipAurora TownshipAuroraThornton TownshipThornton17.877867%17.877867%17.9%11,64611.6k19.171173%9.171173%9.2%13,94013.9k27.658384%7.658384%7.7%7,93637.306290%7.306290%7.3%6,87546.241155%6.241155%6.2%16,71416.7k56.197734%6.197734%6.2%5,35165.940071%5.940071%5.9%7,53175.933545%5.933545%5.9%4,83485.920847%5.920847%5.9%10,97511.0k95.896414%5.896414%5.9%7,178105.800061%5.800061%5.8%4,544114.880448%4.880448%4.9%10,66710.7k124.729595%4.729595%4.7%9,034134.568292%4.568292%4.6%7,656144.485379%4.485379%4.5%82,18982.2k154.336789%4.336789%4.3%3,058164.233985%4.233985%4.2%3,357174.059919%4.059919%4.1%11,66511.7k184.030539%4.030539%4.0%3,970193.487439%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%2,349292.602914%2.602914%2.6%2,576302.551250%2.551250%2.6%2,382312.519246%2.519246%2.5%6,260322.359248%2.359248%2.4%102,384102k2.213918%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%1,606411.458333%1.458333%1.5%141.445147%1.445147%1.4%8271.445147%1.445147%1.4%8271.439893%1.439893%1.4%1,339421.388310%1.388310%1.4%1,300431.318660%1.318660%1.3%5,693441.257490%1.257490%1.3%1,106451.183365%1.183365%1.2%1,040461.047058%1.047058%1.0%963470.997751%0.997751%1.0%1,069480.936111%0.936111%0.9%834490.876686%0.876686%0.9%97150
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
0x2x4xFM#MonroeCedar RapidsLincolnDetroitOmahaToledoKokomo AreaHowardThorntonKansas CityMadisonLawrenceFargoProvisoRockfordBlue TownshipWayneMidwestTopekaEast North CentralMilwaukeeKaw TownshipDaytonSioux FallsUnited StatesOlatheIndianaWorthNOverland ParkAuroraWheelingGrand RapidsSchaumburgChicagoWichitaColumbusClevelandPalatineCapitalWarrenSpringfieldYork TownshipSt. LouisWashingtonBloomingdaleCtrCincinnatiAkronAnn ArborSt. PaulLisleMinneapolisSterling HtsDowners GrvMiltonMaine-1.000000x-1.000000x4.893517x4.893517x4.89x2.402%2.40%11.753%11.8%-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-1.000000x1.219543x1.219543x1.22x10.434%10.4%12.725%12.7%-1.000000x-1.000000x1.219543x1.219543x1.22x10.434%10.4%12.725%12.7%-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-1.000000x1.101821x1.101821x1.10x11.365%11.4%12.522%12.5%-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
1x0x1x2xFM#Kokomo AreaHowardRockfordNDaytonSioux FallsCapitalLawrenceDowners GrvAkronLisleWichitaYork TownshipMaineWarrenWheelingBlue TownshipSpringfieldOverland ParkMiltonIndianaGrand RapidsOlatheOmahaFargoWashingtonEast North CentralLincolnMidwestBloomingdaleKansas CityAuroraUnited StatesAnn ArborTopekaSterling HtsPalatineSchaumburgColumbusMadisonKaw TownshipMilwaukeeCedar RapidsClevelandCincinnatiSt. PaulSt. LouisChicagoWayneCtrToledoMinneapolisWorthDetroitProvisoMonroeThornton-1.000000x-1.000000x2.426957x2.426957x2.43x0.866%0.87%2.101%2.10%-1.000000x-1.000000x2.426957x2.426957x2.43x0.866%0.87%2.101%2.10%-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-1.000000x1.691858x1.691858x1.69x1.769%1.77%2.992%2.99%-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-1.000000x1.669388x1.669388x1.67x3.061%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-1.000000x1.550495x1.550495x1.55x0.737%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%49-1.096070x-1.096070x1.10x1.000000x1.000000x1.528%1.53%1.394%1.39%-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 VlyMilwaukeePhiladelphiaOntarioChicagoBaltimoreOceanside-EscondidoOceanside-Escond…Las VegasPhoenixBostonSacramentoOrlandoAustinDenverUnited States of AmericaUnited StatesManhattanSan DiegoTampaSan JoseSan FranciscoTucsonAlbuquerqueIndianaTownship 1:Charlotte1, CharlotteKokomo Metro AreaKokomo AreaHoward CountyHowardColumbusTulsaEast North CentralSalt Lake CitySalt Lk CityTown of HempsteadHempsteadMidwestNorthwest HarrisNW HarrisWashingtonAtlantaSeattleNortheast TarrantNE TarrantMonroe TownshipMonroePlanoSeattle East28.998944%28.998944%29.0%126,922127k128.837398%28.837398%28.8%261,022261k227.582802%27.582802%27.6%135,754136k324.837401%24.837401%24.8%434,160434k423.987048%23.987048%24.0%141,940142k523.756417%23.756417%23.8%81,30881.3k622.645542%22.645542%22.6%248,699249k722.107626%22.107626%22.1%92,47292.5k821.922900%21.922900%21.9%457,347457k921.818150%21.818150%21.8%149,688150k1021.003600%21.003600%21.0%90,67890.7k1120.783651%20.783651%20.8%207,494207k1220.461493%20.461493%20.5%128,038128k1320.041576%20.041576%20.0%106,726107k1420.017506%20.017506%20.0%351,046351k1519.402518%19.402518%19.4%73,10573.1k1619.344706%19.344706%19.3%315,505316k1719.344408%19.344408%19.3%244,983245k1817.485105%17.485105%17.5%63,80063.8k1917.390838%17.390838%17.4%180,039180k2017.129346%17.129346%17.1%71,39771.4k2116.905373%16.905373%16.9%309,770310k2216.548703%16.548703%16.5%69,83969.8k2315.999398%15.999398%16.0%70,21470.2k2415.906523%15.906523%15.9%198,651199k2514.952077%14.952077%15.0%308,569309k2614.325556%14.325556%14.3%63,64263.6k2713.900512%13.900512%13.9%103,047103k2813.679368%13.679368%13.7%53,75853.8k2913.668915%13.668915%13.7%78,23878.2k3013.638703%13.638703%13.6%63,86563.9k3113.020590%13.020590%13.0%27,818,38027.8M12.996284%12.996284%13.0%160,845161k3212.985760%12.985760%13.0%206,792207k3312.979618%12.979618%13.0%57,75857.8k3412.789590%12.789590%12.8%153,604154k3512.559735%12.559735%12.6%84,02484.0k3612.262851%12.262851%12.3%70,40970.4k3712.089143%12.089143%12.1%52,21752.2k3811.923855%11.923855%11.9%517,458517k11.553484%11.553484%11.6%61,37861.4k3911.508755%11.508755%11.5%6,58611.508755%11.508755%11.5%6,58611.376979%11.376979%11.4%60,83160.8k4011.299086%11.299086%11.3%43,65343.7k4110.719464%10.719464%10.7%3,363,7843.36M10.435356%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%37,37337.4k468.833573%8.833573%8.8%66,22066.2k478.418271%8.418271%8.4%31,44331.4k487.291667%7.291667%7.3%705.714681%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 HarrisChicagoColumbusLos AngelesBrooklynSan Fernando ValleySan Fernando VlyNortheast DallasNE DallasSalt Lake CitySalt Lk CityAlbuquerqueTampaTucsonOceanside-EscondidoOceanside-Escond…TulsaQueensUnited States of AmericaUnited StatesHoustonBaltimoreLong Beach-LakewoodLong Bch-LakewoodMidwestPhoenixOrlandoEast North CentralMonroe TownshipMonroeAnaheim-Santa Ana-Garden GroveAnaheim-Santa An…SacramentoEast San Gabriel ValleyE San Gabriel VlyOntarioPhiladelphiaMiamiFort WorthIndianaSouthwest DallasSW DallasMilwaukeeFresnoLas VegasEl PasoKokomo Metro AreaKokomo AreaHoward CountyHowardBronxSan BernardinoSan Antonio CentralSan Antonio CntrlDetroit60.434640%60.434640%60.4%747,953748k157.691220%57.691220%57.7%238,638239k255.360186%55.360186%55.4%256,316256k354.793235%54.793235%54.8%366,564367k454.142756%54.142756%54.1%195,588196k549.985845%49.985845%50.0%600,334600k649.803731%49.803731%49.8%195,136195k749.626221%49.626221%49.6%372,018372k846.377869%46.377869%46.4%206,036206k945.718966%45.718966%45.7%214,085214k1044.843364%44.843364%44.8%256,674257k1141.989192%41.989192%42.0%223,068223k1238.767308%38.767308%38.8%202,458202k1338.701072%38.701072%38.7%616,296616k1438.547398%38.547398%38.5%143,978144k1536.877886%36.877886%36.9%173,478173k1636.546320%36.546320%36.5%669,666670k1734.685843%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%8,931,6868.93M28.437500%28.437500%28.4%27328.412939%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%111,532112k3826.349720%26.349720%26.3%272,786273k3926.011156%26.011156%26.0%178,455178k4024.665414%24.665414%24.7%131,349131k4124.611498%24.611498%24.6%1,068,0621.07M23.764821%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%72,12072.1k4619.548806%19.548806%19.5%11,18711.2k19.548806%19.548806%19.5%11,18711.2k19.131504%19.131504%19.1%173,169173k4716.375473%16.375473%16.4%80,59580.6k4814.929012%14.929012%14.9%65,34165.3k4913.833543%13.833543%13.8%59,72359.7k50
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older with a bachelor's degree or higher..

Very Advanced Degrees by County Subdivision#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 CityHoustonPhiladelphiaSan 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…QueensNorthwest HarrisNW HarrisNortheast TarrantNE TarrantEast San Gabriel ValleyE San Gabriel VlyIndianaOntarioFort WorthLas VegasMilwaukeeSan BernardinoSan Antonio CentralSan Antonio CntrlEl PasoSouthwest DallasSW DallasBronxMonroe TownshipMonroeKokomo Metro AreaKokomo AreaHoward CountyHowardDetroit12.461852%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%38,51538.5k243.601468%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%44,96545.0k372.682967%2.682967%2.7%12,62112.6k382.630994%2.630994%2.6%9,827392.484535%2.484535%2.5%15,54715.5k402.359248%2.359248%2.4%102,384102k2.324315%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%15,06415.1k491.458333%1.458333%1.5%141.445147%1.445147%1.4%8271.445147%1.445147%1.4%8271.318660%1.318660%1.3%5,69350
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
0x2x4xFM#Monroe1, CharlotteDetroitKokomo AreaHowardBaltimoreTulsaSW DallasMidwestFresnoEast North CentralMilwaukeeUnited StatesIndianaNE 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-1.000000x4.893517x4.893517x4.89x2.402%2.40%11.753%11.8%-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-1.000000x1.219543x1.219543x1.22x10.434%10.4%12.725%12.7%-1.000000x-1.000000x1.219543x1.219543x1.22x10.434%10.4%12.725%12.7%-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-1.000000x1.101821x1.101821x1.10x11.365%11.4%12.522%12.5%-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
1x0x1x2xFM#Kokomo AreaHowardEl PasoSalt Lk CityPlanoTulsaAlbuquerqueNE DallasIndianaFort WorthOrlandoPhoenixTucson1, CharlotteEast North CentralMidwestNW HarrisLas VegasSeattle 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 FranciscoDetroitMonroe-1.000000x-1.000000x2.426957x2.426957x2.43x0.866%0.87%2.101%2.10%-1.000000x-1.000000x2.426957x2.426957x2.43x0.866%0.87%2.101%2.10%-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-1.000000x1.691858x1.691858x1.69x1.769%1.77%2.992%2.99%-1.000000x-1.000000x1.684272x1.684272x1.68x1.637%1.64%2.757%2.76%7-1.000000x-1.000000x1.660799x1.660799x1.66x2.196%2.20%3.647%3.65%8-1.000000x-1.000000x1.659024x1.659024x1.66x2.280%2.28%3.783%3.78%9-1.000000x-1.000000x1.621815x1.621815x1.62x3.429%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-1.000000x1.557664x1.557664x1.56x4.733%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%50-1.096070x-1.096070x1.10x1.000000x1.000000x1.528%1.53%1.394%1.39%
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:
Indiana
County:
Howard
Metro Area:
Kokomo Area
ZIP Codes:
46901, 46979
Unified School Districts:
Northwestern, Western
Congressional District:
IN-4
State Senate District:
IN-21
State House District:
IN-38
Neighboring Townships:
Burlington, Clay, Ervin, Forest, Harrison, Honey Creek, Warren
Nearby Townships:
Carrollton, Center, Deer Creek, Democrat, Jackson, Johnson, Michigan, Monroe, Owen, Prairie