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

Educational Attainment#1

Highest level of education among people aged 25 years and older.
Scope: population of Muskingum County and the Monroe Township
Monroe Township
Muskingum County
0%10%20%30%40%50%60%CountHigher Degree1H.S. Diploma2No H.S. Diploma220.000000%24.350655%20.000000%20.0%5364.528302%62.151230%64.528302%64.5%17115.471698%13.498115%15.471698%15.5%41
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 Muskingum County at large.
Scope: population of Muskingum County and the Monroe Township
-10%0%+10%%ref.Higher Degree1H.S. Diploma2No H.S. Diploma2-17.866686%-17.866686%-17.9%20.000%20.0%24.351%24.4%3.824658%3.824658%+3.8%64.528%64.5%62.151%62.2%14.621174%14.621174%+14.6%15.472%15.5%13.498%13.5%
% percentage with given level in the Monroe Township
ref. percentage with given level in Muskingum 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 Muskingum County and the Monroe Township
Monroe Township
Muskingum County
0%10%20%30%40%CountDoctorate1Professional1Master's1Bachelor's1Associate's1Some CollegeHigh School2Some H.S.3Less than H.S.3None0.000000%0.000000%0.0%0.244419%00.000000%0.000000%0.0%0.740141%05.283019%4.292821%5.283019%5.3%140.000000%0.000000%0.0%9.788801%014.716981%9.284473%14.716981%14.7%3925.660377%20.737732%25.660377%25.7%6838.867925%41.413498%38.867925%38.9%1037.924528%10.823278%7.924528%7.9%217.547170%1.917483%7.547170%7.5%200.000000%0.000000%0.0%0.757354%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 Muskingum County at large.
Scope: population of Muskingum County and the Monroe Township
-200%0%+200%%ref.Doctorate1Professional1Master's1Bachelor's1Associate's1Some CollegeHigh School2Some H.S.3Less than H.S.3None-100.000000%-100.000000%-100.0%0.000%0%0.244%0.24%-100.000000%-100.000000%-100.0%0.000%0%0.740%0.74%23.066378%23.066378%+23.1%5.283%5.28%4.293%4.29%-100.000000%-100.000000%-100.0%0.000%0%9.789%9.79%58.511764%58.511764%+58.5%14.717%14.7%9.284%9.28%23.737628%23.737628%+23.7%25.660%25.7%20.738%20.7%-6.146724%-6.146724%-6.1%38.868%38.9%41.413%41.4%-26.782551%-26.782551%-26.8%7.925%7.92%10.823%10.8%293.597778%293.597778%+293.6%7.547%7.55%1.917%1.92%-100.000000%-100.000000%-100.0%0.000%0%0.757%0.76%
% percentage with given level in the Monroe Township
ref. percentage with given level in Muskingum 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 Muskingum County and the Monroe Township
More Females More Males
Muskingum County
Monroe Township
0%200%FMHigher Degree1H.S. Diploma2No H.S. Diploma2-26.336455%29.300813%29.300813%29%17.606%17.6%22.764%22.8%-52.283053%-52.283053%52%5.406773%76.761%76.8%50.407%50.4%376.219512%19.004529%376.219512%376%5.634%5.63%26.829%26.8%
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 Muskingum County and the Monroe Township
More Females More Males
Muskingum County
Monroe Township
1k%0k%1k%FMMaster's1Associate's1Some CollegeHigh School2Some H.S.3Less than H.S.3-1,000.000000%-70.690933%-1,000.000000%> 1000%9.859%9.86%0.000%0%-83.440243%193.865484%193.865484%0k%7.746%7.75%22.764%22.8%-16.266883%8.850174%8.850174%0k%24.648%24.6%26.829%26.8%-121.029626%-121.029626%0k%16.624218%52.113%52.1%23.577%23.6%87.601626%12.492749%87.601626%0k%5.634%5.63%10.569%10.6%1,000.000000%68.568877%1,000.000000%> 1000%0.000%0%16.260%16.3%
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 Muskingum County and the Monroe Township
Monroe Township
Muskingum County
0%2%4%6%8%10%B.X.Total65+45-6425-340.000000%0.000000%0.0%8.174120%0480.000000%0.000000%0.0%8.037905%01960.000000%0.000000%0.0%10.029557%021
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 Muskingum County at large.
Scope: population of Muskingum County and the Monroe Township
100%80%60%40%20%0%%ref.65+45-6425-34-100.000000%-100.000000%100.0%0.000%0%8.174%8.17%-100.000000%-100.000000%100.0%0.000%0%8.038%8.04%-100.000000%-100.000000%100.0%0.000%0%10.030%10.0%
% percentage in the Monroe Township with a Bachelor's degree
ref percentage in Muskingum County with a Bachelor's degree

Median Earnings by Educational Attainment#9

Among population 25 years old and over with earnings.
Scope: population of Muskingum County and the Monroe Township
Monroe Township
Muskingum County
$0k$10k$20k$30kCount%H.S. Diploma2Total$37,857.000000$29,007.000000$37,857.000000$37.9k10338.868%38.9%$38,889.000000$30,956.000000$38,889.000000$38.9k265100.000%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#10

By sex among population 25 years old and over with earnings.
Scope: population of Muskingum County and the Monroe Township
Female Male
Muskingum County
Monroe Township
Shaded bar tips show excess over facing bar.
$20k$0k$20k$40k$60kFMSome CollegeH.S. Diploma2Total$-6,364.000000$-25,523.000000$-6,364.000000$6.4k$6,364.000000$66,374.000000$25,523.000000$14,271.000000$72,738.000000$72.7k4661$-31,875.000000$-20,264.000000$-31,875.000000$31.9k$31,875.000000$14,375.000000$20,264.000000$16,617.000000$46,250.000000$46.3k7429$-30,125.000000$-25,542.000000$-30,125.000000$30.1k$30,125.000000$16,125.000000$25,542.000000$13,894.000000$46,250.000000$46.3k142123
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#11

Percentage of population that is employed by highest level of educational attainment among the population aged 25 to 64 years old.
Scope: population of Muskingum County and the Monroe Township
Monroe Township
Muskingum County
0%20%40%60%80%100%CountBachelor's Degree1Some College2H.S. Diploma3No H.S. Diploma3100.000000%85.505358%100.000000%100.0%1462.365591%76.112556%62.365591%62.4%5890.721649%67.839602%90.721649%90.7%8846.153846%36.339948%46.153846%46.2%6
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#12

Percent of racial or ethnic group lacking a high school diploma (or equivalent).
Scope: population of Muskingum County and the Monroe Township
Female Male
Muskingum County
Monroe Township
Shaded bar tips show excess over facing bar.
10%5%0%5%10%15%20%25%MFWhite1-5.633803%-11.584031%-5.633803%5.6%5.633803%21.195465%11.584031%2.633352%26.829268%26.8%338
M number of males in category
F number of females in category
1non-Hispanic 2excluding black and Asian Hispanics

College Graduates By Race#13

Percent of racial or ethnic group with a bachelor's degree or higher.
Scope: population of Muskingum County and the Monroe Township
Female Male
Muskingum County
Monroe Township
Shaded bar tips show excess over facing bar.
15%10%5%0%5%10%15%MFWhite1-0.000000%-9.859155%-15.302353%-0.152288%-9.859155%9.9%0.000000%15.302353%0.000000%0.0%014
M number of males in category
F number of females in category
1non-Hispanic 2excluding black and Asian Hispanics

Educational Attainment by County Subdivision in the Zanesville Area

There are 26 county subdivisions in the Zanesville Area. This section compares the Monroe Township to all of the county subdivisions in the Zanesville Area and to those entities that contain or substantially overlap with the Monroe Township.

No H.S. Diploma by County Subdivision#14

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 Zanesville Area, and entities that contain the Monroe Township
0%5%10%15%20%Count#Brush Creek TownshipBrush CrkNewton TownshipNewtonAdams TownshipAdamsZanesvilleClay TownshipMonroe TownshipMonroeBlue Rock TownshipBlue RockHarrison TownshipHarrisonSpringfield TownshipSpringfieldZanesville Metro AreaZanesvilleMuskingum CountyMuskingumMuskingum TownshipMuskingumUnited States of AmericaUnited StatesPerry TownshipPerryHopewell TownshipHopewellSalt Creek TownshipSalt CrkCass TownshipJackson TownshipJacksonEast North CentralOhioMidwest911000Tract 911000Wayne TownshipWayneHighland TownshipHighlandEast Muskingum Local School DistrictE MuskingumRich Hill TownshipRich HlFalls TownshipFallsJefferson TownshipJeffersonLicking TownshipLickingMeigs TownshipMeigsUnion TownshipUnionSalem TownshipSalemWashington TownshipWashingtonMadison TownshipMadison24.862486%24.862486%24.9%226120.532003%20.532003%20.5%741220.171674%20.171674%20.2%94319.199100%19.199100%19.2%3,241418.398876%18.398876%18.4%131515.471698%15.471698%15.5%41614.789916%14.789916%14.8%88714.469453%14.469453%14.5%135814.236958%14.236958%14.2%584913.498115%13.498115%13.5%7,84213.498115%13.498115%13.5%7,84213.108495%13.108495%13.1%4121013.020590%13.020590%13.0%27,818,38027.8M12.486428%12.486428%12.5%2301112.170889%12.170889%12.2%2451211.318242%11.318242%11.3%851311.111111%11.111111%11.1%1291411.095700%11.095700%11.1%1601510.719464%10.719464%10.7%3,363,7843.36M10.514146%10.514146%10.5%825,155825k10.244520%10.244520%10.2%4,641,8354.64M9.352291%9.352291%9.4%2969.180227%9.180227%9.2%299169.052334%9.052334%9.1%64178.619824%8.619824%8.6%6878.178439%8.178439%8.2%22187.264472%7.264472%7.3%448196.735751%6.735751%6.7%78206.571243%6.571243%6.6%101215.392157%5.392157%5.4%11225.255682%5.255682%5.3%111234.560261%4.560261%4.6%28244.473503%4.473503%4.5%130252.339181%2.339181%2.3%826
Count number of people in category
# rank of county subdivision out of 26 by percentage of population 25 years of age and older without a high school diploma (or equivalent).

Bachelor's Degrees by County Subdivision#15

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 Zanesville Area, and entities that contain the Monroe Township
0%10%20%30%Count#United States of AmericaUnited StatesMidwestEast North CentralCass TownshipLicking TownshipLickingOhioUnion TownshipUnionPerry TownshipPerryFalls TownshipFallsHopewell TownshipHopewellMuskingum TownshipMuskingumEast Muskingum Local School DistrictE MuskingumRich Hill TownshipRich HlMeigs TownshipMeigsZanesville Metro AreaZanesvilleMuskingum CountyMuskingumWashington TownshipWashingtonHighland TownshipHighlandJefferson TownshipJeffersonZanesville911000Tract 911000Wayne TownshipWayneAdams TownshipAdamsSalem TownshipSalemSpringfield TownshipSpringfieldHarrison TownshipHarrisonMadison TownshipMadisonClay TownshipNewton TownshipNewtonJackson TownshipJacksonBrush Creek TownshipBrush CrkBlue Rock TownshipBlue RockMonroe TownshipMonroeSalt Creek TownshipSalt Crk30.315023%30.315023%30.3%64,767,78764.8M28.952816%28.952816%29.0%13,118,64213.1M28.462853%28.462853%28.5%8,931,6868.93M28.423773%28.423773%28.4%330128.366949%28.366949%28.4%436226.667466%26.667466%26.7%2,092,8752.09M26.136364%26.136364%26.1%552324.104235%24.104235%24.1%444424.095995%24.095995%24.1%1,486524.043716%24.043716%24.0%484623.448934%23.448934%23.4%737720.602258%20.602258%20.6%1,64218.959108%18.959108%19.0%51817.647059%17.647059%17.6%36915.066182%15.066182%15.1%8,75315.066182%15.066182%15.1%8,75314.487268%14.487268%14.5%4211012.871287%12.871287%12.9%911112.607945%12.607945%12.6%1461212.102364%12.102364%12.1%2,0431311.690363%11.690363%11.7%37010.868898%10.868898%10.9%3541410.515021%10.515021%10.5%49159.283388%9.283388%9.3%57169.019990%9.019990%9.0%370178.145766%8.145766%8.1%76187.894737%7.894737%7.9%27197.303371%7.303371%7.3%52207.204212%7.204212%7.2%260216.934813%6.934813%6.9%100226.820682%6.820682%6.8%62236.554622%6.554622%6.6%39245.283019%5.283019%5.3%14254.793609%4.793609%4.8%3626
Count number of people in category
# rank of county subdivision out of 26 by percentage of population 25 years of age and older with a bachelor's degree or higher..

Very Advanced Degrees by County Subdivision#16

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 Zanesville Area, and entities that contain the Monroe Township
0%1%2%3%Count#Highland TownshipHighlandMadison TownshipMadisonUnited States of AmericaUnited StatesHopewell TownshipHopewellMidwestEast North CentralOhioUnion TownshipUnionFalls TownshipFallsEast Muskingum Local School DistrictE MuskingumJefferson TownshipJeffersonAdams TownshipAdamsZanesville911000Tract 911000Zanesville Metro AreaZanesvilleMuskingum CountyMuskingumNewton TownshipNewtonWashington TownshipWashingtonSpringfield TownshipSpringfieldPerry TownshipPerryClay TownshipJackson TownshipJacksonWayne TownshipWayneMuskingum TownshipMuskingumLicking TownshipLickingCass TownshipHarrison TownshipHarrisonBrush Creek TownshipBrush CrkSalt Creek TownshipSalt CrkSalem TownshipSalemBlue Rock TownshipBlue RockRich Hill TownshipRich HlMonroe TownshipMonroeMeigs TownshipMeigs3.677511%3.677511%3.7%2613.508772%3.508772%3.5%1223.336158%3.336158%3.3%7,127,6737.13M2.930949%2.930949%2.9%5932.893416%2.893416%2.9%1,311,0191.31M2.855432%2.855432%2.9%896,039896k2.683241%2.683241%2.7%210,582211k2.320076%2.320076%2.3%4941.880979%1.880979%1.9%11651.480552%1.480552%1.5%1181.381693%1.381693%1.4%1661.287554%1.287554%1.3%671.249926%1.249926%1.2%21181.169036%1.169036%1.2%370.984560%0.984560%1.0%5720.984560%0.984560%1.0%5720.914381%0.914381%0.9%3390.481762%0.481762%0.5%14100.438810%0.438810%0.4%18110.434311%0.434311%0.4%8120.280899%0.280899%0.3%2130.138696%0.138696%0.1%2140.000000%0.000000%0.0%0150.000000%0.000000%0.0%0160.000000%0.000000%0.0%0170.000000%0.000000%0.0%0180.000000%0.000000%0.0%0190.000000%0.000000%0.0%0200.000000%0.000000%0.0%0210.000000%0.000000%0.0%0220.000000%0.000000%0.0%0230.000000%0.000000%0.0%0240.000000%0.000000%0.0%0250.000000%0.000000%0.0%026
Count number of people in category
# rank of county subdivision out of 26 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#17

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 Zanesville Area, and entities that contain the Monroe Township
Female
Male
10x5x0x5x10xFM#MeigsMonroeWayneWashingtonAdamsSalemUnionE MuskingumBrush CrkCass TownshipPerryTract 911000LickingZanesvilleZanesvilleMuskingumFallsHarrisonNewtonMidwestEast North CentralUnited StatesOhioClay TownshipSpringfieldJacksonMuskingumHighlandHopewellRich HlBlue RockSalt CrkJeffersonMadison-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%11.340%11.3%1-1.000000x-1.000000x4.762195x4.762195x4.76x5.634%5.63%26.829%26.8%2-1.000000x-1.000000x4.316967x4.316967x4.32x3.636%3.64%15.698%15.7%3-1.000000x-1.000000x2.812713x2.812713x2.81x2.322%2.32%6.532%6.53%4-1.000000x-1.000000x2.397959x2.397959x2.40x11.915%11.9%28.571%28.6%5-1.000000x-1.000000x2.054896x2.054896x2.05x2.888%2.89%5.935%5.93%6-1.000000x-1.000000x1.744997x1.744997x1.74x3.942%3.94%6.878%6.88%7-1.000000x-1.000000x1.695486x1.695486x1.70x6.484%6.48%10.993%11.0%-1.000000x-1.000000x1.540063x1.540063x1.54x19.654%19.7%30.269%30.3%8-1.000000x-1.000000x1.524283x1.524283x1.52x8.711%8.71%13.279%13.3%9-1.000000x-1.000000x1.443599x1.443599x1.44x10.168%10.2%14.678%14.7%10-1.000000x-1.000000x1.391541x1.391541x1.39x7.832%7.83%10.899%10.9%-1.000000x-1.000000x1.368283x1.368283x1.37x5.556%5.56%7.602%7.60%11-1.000000x-1.000000x1.319553x1.319553x1.32x16.852%16.9%22.237%22.2%12-1.000000x-1.000000x1.190045x1.190045x1.19x12.386%12.4%14.740%14.7%-1.000000x-1.000000x1.190045x1.190045x1.19x12.386%12.4%14.740%14.7%-1.000000x-1.000000x1.173614x1.173614x1.17x6.718%6.72%7.884%7.88%13-1.000000x-1.000000x1.173394x1.173394x1.17x13.424%13.4%15.752%15.8%14-1.000000x-1.000000x1.144382x1.144382x1.14x19.172%19.2%21.940%21.9%15-1.000000x-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-1.000000x1.105363x1.105363x1.11x10.008%10.0%11.063%11.1%-1.000000x-1.000000x1.016137x1.016137x1.02x18.256%18.3%18.551%18.6%16-1.022000x-1.022000x1.02x1.000000x1.000000x14.387%14.4%14.077%14.1%17-1.074835x-1.074835x1.07x1.000000x1.000000x11.506%11.5%10.705%10.7%18-1.409584x-1.409584x1.41x1.000000x1.000000x15.298%15.3%10.853%10.9%19-1.473684x-1.473684x1.47x1.000000x1.000000x10.526%10.5%7.143%7.14%20-1.675545x-1.675545x1.68x1.000000x1.000000x15.393%15.4%9.187%9.19%21-1.934300x-1.934300x1.93x1.000000x1.000000x11.304%11.3%5.844%5.84%22-2.027656x-2.027656x2.03x1.000000x1.000000x19.799%19.8%9.764%9.76%23-2.275282x-2.275282x2.28x1.000000x1.000000x15.733%15.7%6.915%6.91%24-4.460784x-4.460784x4.46x1.000000x1.000000x10.621%10.6%2.381%2.38%25-10.000000x-10.000000x> 10.0x1.000000x1.000000x4.762%4.76%0.000%0%26
F percentage of females in category
M percentage of males in category
# rank of county subdivision out of 26 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#18

Percent of population 25 years of age and older without a high school diploma (or equivalent).
Scope: population of the Monroe Township, selected other county subdivisions in Ohio, and entities that contain the Monroe Township
0%5%10%15%20%Count#ClevelandMiddletownLorainYoungstownSpringfieldDaytonMansfieldLimaMarion TownshipMarionCantonMonroe TownshipMonroeHamiltonWarrenToledoCincinnatiAkronZanesville Metro AreaZanesvilleMuskingum CountyMuskingumElyriaUnited States of AmericaUnited StatesNewarkBath TownshipLancaster City TownshipLancaster CityColumbusColerain TownshipColerainEast North CentralEuclidOhioMidwestParma911000Tract 911000FindlayFairfieldEast Muskingum Local School DistrictE MuskingumMiami TownshipMiamiUnion TownshipUnionHuber HeightsJackson TownshipJacksonCleveland HeightsCleveland HtsCuyahoga FallsPlain TownshipPlainLakewoodKetteringGreen TownshipGrnBoardman TownshipBoardmanWest Chester TownshipW ChesterMiami TownshipMiamiMifflin TownshipMifflinMentorLiberty TownshipLibertySylvania TownshipSylvaniaStrongsvilleViolet TownshipVioletJackson TownshipJacksonWashington TownshipWashingtonAnderson TownshipAndersonDeerfield TownshipDeerfieldBeavercreek TownshipBeavercreekDublin21.582420%21.582420%21.6%54,98155.0k118.211726%18.211726%18.2%5,591217.551080%17.551080%17.6%7,207316.999061%16.999061%17.0%7,424416.947843%16.947843%16.9%6,580516.928359%16.928359%16.9%14,88914.9k616.499446%16.499446%16.5%5,361716.278163%16.278163%16.3%3,757815.742056%15.742056%15.7%4,875915.631958%15.631958%15.6%7,3021015.471698%15.471698%15.5%4115.293656%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%17,95118.0k1513.498115%13.498115%13.5%7,84213.498115%13.498115%13.5%7,84213.343328%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%5,683239.352291%9.352291%9.4%2969.003845%9.003845%9.0%2,482248.712972%8.712972%8.7%2,559258.619824%8.619824%8.6%6878.614662%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#19

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 TownshipJacksonColumbusCincinnatiKetteringPlain TownshipPlainGreen TownshipGrnCuyahoga FallsMentorBoardman TownshipBoardmanUnited States of AmericaUnited StatesUnion TownshipUnionJackson TownshipJacksonMidwestEast North CentralFairfieldBath TownshipFindlayMiami TownshipMiamiOhioHuber HeightsColerain TownshipColerainEuclidEast Muskingum Local School DistrictE MuskingumAkronParmaNewarkToledoDaytonMiddletownLancaster City TownshipLancaster CityClevelandElyriaHamiltonZanesville Metro AreaZanesvilleMuskingum CountyMuskingumSpringfieldCantonMansfieldWarrenYoungstownLorain911000Tract 911000LimaMarion TownshipMarionMonroe TownshipMonroe75.246997%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%12,09212.1k1534.685843%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%6,8133220.602258%20.602258%20.6%1,64220.213821%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%6,1454215.066182%15.066182%15.1%8,75315.066182%15.066182%15.1%8,75314.851256%14.851256%14.9%5,7664314.608666%14.608666%14.6%6,8244413.812631%13.812631%13.8%4,4884512.832476%12.832476%12.8%3,4934612.044055%12.044055%12.0%5,2604711.718579%11.718579%11.7%4,8124811.690363%11.690363%11.7%37011.460139%11.460139%11.5%2,6454910.478559%10.478559%10.5%3,245505.283019%5.283019%5.3%14
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#20

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 ChesterKetteringLiberty TownshipLibertyMifflin TownshipMifflinColumbusUnited States of AmericaUnited StatesPlain TownshipPlainBoardman TownshipBoardmanViolet TownshipVioletMiami TownshipMiamiMidwestEast North CentralOhioCuyahoga FallsGreen TownshipGrnBath TownshipAkronJackson TownshipJacksonClevelandMentorColerain TownshipColerainMiami TownshipMiamiFindlayToledoSpringfieldEast Muskingum Local School DistrictE MuskingumFairfieldEuclidHuber HeightsLimaDaytonCantonHamiltonUnion TownshipUnionParmaNewark911000Tract 911000Lancaster City TownshipLancaster CityMansfieldMiddletownZanesville Metro AreaZanesvilleMuskingum CountyMuskingumLorainElyriaYoungstownWarrenMarion TownshipMarionMonroe 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%1,485133.514938%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%600321.480552%1.480552%1.5%1181.477698%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%375421.169036%1.169036%1.2%371.159205%1.159205%1.2%312431.104887%1.104887%1.1%359440.996743%0.996743%1.0%306450.984560%0.984560%1.0%5720.984560%0.984560%1.0%5720.964372%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%223500.000000%0.000000%0.0%0
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#21

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
0x2x4xFM#MonroeAndersonE MuskingumMansfieldCleveland HtsTract 911000BeavercreekUnionToledoFindlayLorainMarionYoungstownZanesvilleMuskingumColerainGrnFairfieldElyriaMiddletownLancaster CityMidwestEast North CentralSpringfieldWarrenDaytonCantonUnited StatesOhioLimaParmaColumbusClevelandDeerfieldMentorNewarkW ChesterPlainLibertyJacksonHuber HeightsHamiltonJacksonCincinnatiAkronMifflinSylvaniaMiamiEuclidMiamiCuyahoga FallsStrongsvilleLakewoodBath TownshipDublinKetteringWashingtonBoardmanViolet-1.000000x-1.000000x4.762195x4.762195x4.76x5.634%5.63%26.829%26.8%-1.000000x-1.000000x1.766803x1.766803x1.77x2.468%2.47%4.360%4.36%1-1.000000x-1.000000x1.695486x1.695486x1.70x6.484%6.48%10.993%11.0%-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-1.000000x1.391541x1.391541x1.39x7.832%7.83%10.899%10.9%-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-1.000000x1.190045x1.190045x1.19x12.386%12.4%14.740%14.7%-1.000000x-1.000000x1.190045x1.190045x1.19x12.386%12.4%14.740%14.7%-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-1.000000x1.087544x1.087544x1.09x15.592%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

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#22

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 TownshipRockfordMonroe TownshipMonroeSt. LouisWarrenGrand RapidsToledoBlue TownshipCincinnatiAkronZanesville Metro AreaZanesvilleMuskingum CountyMuskingumSt. PaulSterling HeightsSterling HtsUnited States of AmericaUnited StatesThornton TownshipThorntonWichitaKaw TownshipOmahaBloomingdale TownshipBloomingdaleColumbusMaine TownshipMaineTopekaMinneapolisSpringfield TownshipSpringfieldEast North CentralWorth TownshipWorthOhioMidwestLawrence TownshipLawrenceSioux Falls911000Tract 911000Capital TownshipCapitalEast Muskingum Local School DistrictE MuskingumWheeling TownshipWheelingPalatine TownshipPalatineSchaumburg TownshipSchaumburgLincolnWashington TownshipWashingtonOlatheFargoCedar RapidsYork TownshipMilton TownshipMiltonMadisonDowners Grove TownshipDowners GrvLisle TownshipLisleOverland ParkAnn Arbor33.464284%33.464284%33.5%29,81429.8k123.165532%23.165532%23.2%22,92622.9k222.659362%22.659362%22.7%21,21821.2k321.582420%21.582420%21.6%54,98155.0k421.037720%21.037720%21.0%18,48918.5k521.003600%21.003600%21.0%90,67890.7k617.485105%17.485105%17.5%63,80063.8k717.062713%17.062713%17.1%17,39117.4k816.928359%16.928359%16.9%14,88914.9k916.905373%16.905373%16.9%309,770310k1015.636222%15.636222%15.6%16,11016.1k1115.608074%15.608074%15.6%18,24118.2k1215.471698%15.471698%15.5%4115.466266%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%17,95118.0k1913.498115%13.498115%13.5%7,84213.498115%13.498115%13.5%7,84213.278342%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%9,123349.352291%9.352291%9.4%2968.623103%8.623103%8.6%6,837358.619824%8.619824%8.6%6878.424707%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#23

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 CentralSterling HeightsSterling HtsTopekaSpringfield TownshipSpringfieldOhioProviso TownshipProvisoWorth TownshipWorthMilwaukeeRockford TownshipRockfordEast Muskingum Local School DistrictE MuskingumAkronCenter TownshipCtrNorth TownshipNThornton TownshipThorntonToledoDaytonWarrenWayne TownshipWayneKansas CityClevelandAurora TownshipAuroraBlue TownshipZanesville Metro AreaZanesvilleMuskingum CountyMuskingumDetroit911000Tract 911000Monroe TownshipMonroe72.810169%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%8,931,6868.93M27.532180%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%25,23525.2k3720.602258%20.602258%20.6%1,64220.213821%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%16,95117.0k4915.066182%15.066182%15.1%8,75315.066182%15.066182%15.1%8,75313.833543%13.833543%13.8%59,72359.7k5011.690363%11.690363%11.7%3705.283019%5.283019%5.3%14
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#24

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 FallsOlatheOhioCenter TownshipCtrSchaumburg TownshipSchaumburgWichitaProviso TownshipProvisoAkronBloomingdale TownshipBloomingdaleRockford TownshipRockfordMilwaukeeWorth TownshipWorthClevelandToledoNorth TownshipNEast Muskingum Local School DistrictE MuskingumSterling HeightsSterling HtsKansas CityDetroitDaytonWayne TownshipWayne911000Tract 911000WarrenBlue TownshipZanesville Metro AreaZanesvilleMuskingum CountyMuskingumAurora TownshipAuroraThornton TownshipThorntonMonroe 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%3,970193.487439%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%1,606411.480552%1.480552%1.5%1181.439893%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%1,040461.169036%1.169036%1.2%371.047058%1.047058%1.0%963470.997751%0.997751%1.0%1,069480.984560%0.984560%1.0%5720.984560%0.984560%1.0%5720.936111%0.936111%0.9%834490.876686%0.876686%0.9%971500.000000%0.000000%0.0%0
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#25

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
1x0x1x2x3x4xFM#MonroeE MuskingumTract 911000Cedar RapidsLincolnDetroitOmahaToledoThorntonZanesvilleMuskingumKansas CityMadisonLawrenceFargoProvisoRockfordBlue TownshipWayneMidwestTopekaEast North CentralMilwaukeeKaw TownshipDaytonSioux FallsUnited StatesOlatheOhioWorthNOverland ParkAuroraWheelingGrand RapidsSchaumburgChicagoWichitaColumbusClevelandPalatineCapitalWarrenSpringfieldYork TownshipSt. LouisWashingtonBloomingdaleCtrCincinnatiAkronAnn ArborSt. PaulLisleMinneapolisSterling HtsDowners GrvMiltonMaine-1.000000x-1.000000x4.762195x4.762195x4.76x5.634%5.63%26.829%26.8%-1.000000x-1.000000x1.695486x1.695486x1.70x6.484%6.48%10.993%11.0%-1.000000x-1.000000x1.391541x1.391541x1.39x7.832%7.83%10.899%10.9%-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-1.000000x1.190045x1.190045x1.19x12.386%12.4%14.740%14.7%-1.000000x-1.000000x1.190045x1.190045x1.19x12.386%12.4%14.740%14.7%-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-1.000000x1.099747x1.099747x1.10x10.199%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

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#26

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 VegasMonroe TownshipMonroePhoenixBostonSacramentoOrlandoAustinDenverZanesville Metro AreaZanesvilleMuskingum CountyMuskingumUnited States of AmericaUnited StatesManhattanSan DiegoTampaSan JoseSan FranciscoTucsonAlbuquerqueTownship 1:Charlotte1, CharlotteColumbusTulsaEast North CentralOhioSalt Lake CitySalt Lk CityTown of HempsteadHempsteadMidwestNorthwest HarrisNW HarrisWashingtonAtlanta911000Tract 911000SeattleEast Muskingum Local School DistrictE MuskingumNortheast TarrantNE TarrantPlanoSeattle East28.998944%28.998944%29.0%126,922127k128.837398%28.837398%28.8%261,022261k227.582802%27.582802%27.6%135,754136k324.837401%24.837401%24.8%434,160434k423.987048%23.987048%24.0%141,940142k523.756417%23.756417%23.8%81,30881.3k622.645542%22.645542%22.6%248,699249k722.107626%22.107626%22.1%92,47292.5k821.922900%21.922900%21.9%457,347457k921.818150%21.818150%21.8%149,688150k1021.003600%21.003600%21.0%90,67890.7k1120.783651%20.783651%20.8%207,494207k1220.461493%20.461493%20.5%128,038128k1320.041576%20.041576%20.0%106,726107k1420.017506%20.017506%20.0%351,046351k1519.402518%19.402518%19.4%73,10573.1k1619.344706%19.344706%19.3%315,505316k1719.344408%19.344408%19.3%244,983245k1817.485105%17.485105%17.5%63,80063.8k1917.390838%17.390838%17.4%180,039180k2017.129346%17.129346%17.1%71,39771.4k2116.905373%16.905373%16.9%309,770310k2216.548703%16.548703%16.5%69,83969.8k2315.999398%15.999398%16.0%70,21470.2k2415.906523%15.906523%15.9%198,651199k2515.471698%15.471698%15.5%4114.952077%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%63,86563.9k3113.498115%13.498115%13.5%7,84213.498115%13.498115%13.5%7,84213.020590%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%37,37337.4k469.352291%9.352291%9.4%2968.833573%8.833573%8.8%66,22066.2k478.619824%8.619824%8.6%6878.418271%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#27

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 CentralAnaheim-Santa Ana-Garden GroveAnaheim-Santa An…SacramentoEast San Gabriel ValleyE San Gabriel VlyOntarioOhioPhiladelphiaMiamiFort WorthSouthwest DallasSW DallasMilwaukeeFresnoLas VegasEl PasoEast Muskingum Local School DistrictE MuskingumBronxSan BernardinoZanesville Metro AreaZanesvilleMuskingum CountyMuskingumSan Antonio CentralSan Antonio CntrlDetroit911000Tract 911000Monroe TownshipMonroe60.434640%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%8,931,6868.93M28.412939%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%72,12072.1k4620.602258%20.602258%20.6%1,64219.131504%19.131504%19.1%173,169173k4716.375473%16.375473%16.4%80,59580.6k4815.066182%15.066182%15.1%8,75315.066182%15.066182%15.1%8,75314.929012%14.929012%14.9%65,34165.3k4913.833543%13.833543%13.8%59,72359.7k5011.690363%11.690363%11.7%3705.283019%5.283019%5.3%14
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#28

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…QueensOhioNorthwest HarrisNW HarrisNortheast TarrantNE TarrantEast San Gabriel ValleyE San Gabriel VlyOntarioFort WorthLas VegasMilwaukeeSan BernardinoSan Antonio CentralSan Antonio CntrlEl PasoSouthwest DallasSW DallasBronxEast Muskingum Local School DistrictE MuskingumDetroit911000Tract 911000Zanesville Metro AreaZanesvilleMuskingum CountyMuskingumMonroe 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%38,51538.5k243.601468%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%15,06415.1k491.480552%1.480552%1.5%1181.318660%1.318660%1.3%5,693501.169036%1.169036%1.2%370.984560%0.984560%1.0%5720.984560%0.984560%1.0%5720.000000%0.000000%0.0%0
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#29

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#MonroeE MuskingumTract 9110001, CharlotteDetroitZanesvilleMuskingumBaltimoreTulsaSW DallasMidwestFresnoEast North CentralMilwaukeeUnited StatesOhioNE 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-1.000000x4.762195x4.762195x4.76x5.634%5.63%26.829%26.8%-1.000000x-1.000000x1.695486x1.695486x1.70x6.484%6.48%10.993%11.0%-1.000000x-1.000000x1.391541x1.391541x1.39x7.832%7.83%10.899%10.9%-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-1.000000x1.190045x1.190045x1.19x12.386%12.4%14.740%14.7%-1.000000x-1.000000x1.190045x1.190045x1.19x12.386%12.4%14.740%14.7%-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-1.000000x1.105363x1.105363x1.11x10.008%10.0%11.063%11.1%-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

Definitions

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

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

The coarse levels of educational attainment are as follows:

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

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

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State:
Ohio
County:
Muskingum
Metro Area:
Zanesville Area
ZIP Codes:
43762, 43767, 43802, 43812
Unified School District:
East Muskingum
Congressional District:
OH-6
State Senate District:
OH-20
State House District:
OH-97
Neighboring Townships:
Adams, Adams, Highland, Knox, Linton, Salem
Nearby Townships:
Cambridge, Franklin, Lafayette, Liberty, Madison, Oxford, Union, Virginia, Wheeling