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

Educational Attainment#1

Highest level of education among people aged 25 years and older.
Scope: population of Clermont County and the Monroe Township
Monroe Township
Clermont County
0%10%20%30%40%50%60%CountHigher Degree1H.S. Diploma2No H.S. Diploma225.249723%37.141807%25.249723%25.2%1,36562.079171%52.450667%62.079171%62.1%3,35612.671106%10.407526%12.671106%12.7%685
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 Clermont County at large.
Scope: population of Clermont County and the Monroe Township
-20%0%+20%%ref.Higher Degree1H.S. Diploma2No H.S. Diploma2-32.018056%-32.018056%-32.0%25.250%25.2%37.142%37.1%18.357258%18.357258%+18.4%62.079%62.1%52.451%52.5%21.749457%21.749457%+21.7%12.671%12.7%10.408%10.4%
% percentage with given level in the Monroe Township
ref. percentage with given level in Clermont 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 Clermont County and the Monroe Township
Monroe Township
Clermont County
0%10%20%30%40%CountDoctorate1Professional1Master's1Bachelor's1Associate's1Some CollegeHigh School2Some H.S.3Less than H.S.3None0.000000%0.000000%0.0%0.643810%00.850906%1.188403%0.850906%0.9%465.049945%7.396465%5.049945%5.0%2739.766926%18.389740%9.766926%9.8%5289.581946%9.523390%9.581946%9.6%51816.481687%18.949032%16.481687%16.5%89145.597484%33.501635%45.597484%45.6%2,4659.193489%7.491273%9.193489%9.2%4972.108768%1.911586%2.108768%2.1%1141.368849%1.004667%1.368849%1.4%74
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 Clermont County at large.
Scope: population of Clermont 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%0.644%0.64%-28.399147%-28.399147%-28.4%0.851%0.85%1.188%1.19%-31.724891%-31.724891%-31.7%5.050%5.05%7.396%7.40%-46.889268%-46.889268%-46.9%9.767%9.77%18.390%18.4%0.614870%0.614870%+0.6%9.582%9.58%9.523%9.52%-13.020954%-13.020954%-13.0%16.482%16.5%18.949%18.9%36.105250%36.105250%+36.1%45.597%45.6%33.502%33.5%22.722657%22.722657%+22.7%9.193%9.19%7.491%7.49%10.315080%10.315080%+10.3%2.109%2.11%1.912%1.91%36.249084%36.249084%+36.2%1.369%1.37%1.005%1.00%
% percentage with given level in the Monroe Township
ref. percentage with given level in Clermont 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 Clermont County and the Monroe Township
More Females More Males
Clermont County
Monroe Township
60%40%20%0%20%FMHigher Degree1H.S. Diploma2No H.S. Diploma2-73.121208%-2.761768%-73.121208%73%31.918%31.9%18.437%18.4%-2.022592%22.228401%22.228401%22%55.930%55.9%68.362%68.4%8.631534%21.905938%8.631534%9%12.152%12.2%13.201%13.2%
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 Clermont County and the Monroe Township
More Females More Males
Clermont County
Monroe Township
50%0%50%FMProfessional1Master's1Bachelor's1Associate's1Some CollegeHigh School2Some H.S.3Less than H.S.3None32.819746%64.368135%32.819746%33%0.732%0.73%0.972%0.97%-69.327233%-11.735352%-69.327233%69%6.332%6.33%3.740%3.74%-75.557182%-75.557182%76%9.201460%12.408%12.4%7.068%7.07%-86.956093%-35.635201%-86.956093%87%12.445%12.4%6.657%6.66%-1.312028%1.939957%1.939957%2%16.325%16.3%16.642%16.6%-2.426794%30.591290%30.591290%31%39.605%39.6%51.720%51.7%6.793971%17.579744%6.793971%7%8.895%8.89%9.499%9.50%35.530353%38.503410%35.530353%36%1.794%1.79%2.431%2.43%-15.149427%-15.149427%15%25.397977%1.464%1.46%1.272%1.27%
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 Clermont County and the Monroe Township
Monroe Township
Clermont County
0%5%10%15%20%B.X.Total65+45-6435-4425-346.270627%11.229394%6.270627%6.3%5790910.158847%18.469026%10.158847%10.2%2752,70713.505155%22.595745%13.505155%13.5%1319707.926829%22.049871%7.926829%7.9%65820
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 Clermont County at large.
Scope: population of Clermont County and the Monroe Township
60%50%40%30%20%10%0%%ref.65+45-6435-4425-34-44.158813%-44.158813%44.2%6.271%6.27%11.229%11.2%-44.995219%-44.995219%45.0%10.159%10.2%18.469%18.5%-40.231425%-40.231425%40.2%13.505%13.5%22.596%22.6%-64.050450%-64.050450%64.1%7.927%7.93%22.050%22.0%
% percentage in the Monroe Township with a Bachelor's degree
ref percentage in Clermont 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 Clermont County and the Monroe Township
More Females More Males
Clermont County
Monroe Township
600%400%200%0%FM65+45-6435-4425-34-55.256065%-55.256065%55.3%70.828981%7.547%7.55%4.861%4.86%-50.012057%-50.012057%50.0%8.601539%12.228%12.2%8.151%8.15%-56.742394%-56.742394%56.7%2.117149%16.430%16.4%10.482%10.5%-796.231546%-18.173794%-796.231546%796.2%13.753%13.8%1.535%1.53%
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 Clermont County and the Monroe Township
Monroe Township
Clermont County
$0k$20k$40k$60kCount%Graduate Degree1Bachelor's DegreeSome CollegeH.S. Diploma2No H.S. Diploma2Total$73,289.000000$66,304.000000$73,289.000000$73.3k3195.901%5.90%$75,972.000000$54,342.000000$75,972.000000$76.0k5289.767%9.77%$29,535.000000$37,257.000000$29,535.000000$29.5k1,40926.064%26.1%$30,678.000000$30,979.000000$30,678.000000$30.7k2,46545.597%45.6%$17,868.000000$21,845.000000$17,868.000000$17.9k68512.671%12.7%$33,005.000000$39,290.000000$33,005.000000$33.0k5,406100.000%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 Clermont County and the Monroe Township
Female Male
Clermont County
Monroe Township
Shaded bar tips show excess over facing bar.
$50k$0k$50kFMGraduate Degree1Bachelor's DegreeSome CollegeH.S. Diploma2Total$-71,250.000000$-3,654.000000$-57,255.000000$-74,904.000000$74.9k$71,250.000000$57,255.000000$21,729.000000$71,250.000000$71.3k193126$-52,969.000000$-43,322.000000$-52,969.000000$53.0k$52,969.000000$32,187.000000$43,322.000000$28,143.000000$85,156.000000$85.2k339189$-23,163.000000$-30,204.000000$-23,163.000000$23.2k$23,163.000000$30,098.000000$30,204.000000$15,313.000000$53,261.000000$53.3k786623$-22,907.000000$-26,200.000000$-22,907.000000$22.9k$22,907.000000$13,999.000000$26,200.000000$10,282.000000$36,906.000000$36.9k1,0821,383$-25,341.000000$-31,708.000000$-25,341.000000$25.3k$25,341.000000$16,340.000000$31,708.000000$14,917.000000$41,681.000000$41.7k2,7322,674
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 Clermont County and the Monroe Township
Monroe Township
Clermont County
0%20%40%60%80%CountBachelor's Degree1Some College2H.S. Diploma3No H.S. Diploma378.083990%84.844457%78.083990%78.1%59566.693614%76.693616%66.693614%66.7%82567.814371%69.353830%67.814371%67.8%1,35940.890688%47.147350%40.890688%40.9%202
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 Clermont County and the Monroe Township
Female Male
Clermont County
Monroe Township
Shaded bar tips show excess over facing bar.
10%5%0%5%10%15%20%MFWhite1BlackOther1-12.476513%-9.259590%-12.476513%12.5%12.476513%0.890014%9.259590%1.899687%13.366526%13.4%349332-0.000000%-8.974359%0.000000%0.0%0.000000%0.000000%8.974359%6.523379%0.000000%0.0%00-0.000000%-13.967136%-0.508002%0.000000%0.0%0.000000%23.529412%13.967136%23.529412%23.5%40
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 Clermont County and the Monroe Township
Female Male
Clermont County
Monroe Township
Shaded bar tips show excess over facing bar.
30%20%10%0%10%20%MFWhite1BlackOther1-12.064343%-7.665082%-26.409844%-19.729425%19.7%12.064343%26.409844%2.117871%12.064343%12.1%315525-0.000000%-23.642534%-8.266298%0.000000%0.0%0.000000%0.000000%23.642534%0.000000%0.0%00-0.000000%-36.842105%-15.492958%-8.484943%-36.842105%36.8%0.000000%15.492958%0.000000%0.0%07
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 Cincinnati Area

There are 153 county subdivisions in the Cincinnati Area. This section compares the Monroe Township to the 50 most populous county subdivisions in the Cincinnati Area and to those entities that contain or substantially overlap with the Monroe Township. The least populous of the compared county subdivisions has a population of 9,645.

No H.S. Diploma by County Subdivision#15

Percent of population 25 years of age and older without a high school diploma (or equivalent).
Scope: population of the Monroe Township, selected other county subdivisions in the Cincinnati Area, and entities that contain the Monroe Township
0%5%10%15%Count#Williamstown-Dry RidgeWilliamstown-Dry …MiddletownTurtlecreek TownshipTurtlecreekNorwoodHamiltonGoshen TownshipGoshenFranklin TownshipFranklinCincinnatiSpringdaleUnited States of AmericaUnited StatesMonroe TownshipMonroeReadingBatavia TownshipBataviaForest ParkColerain TownshipColerainNewport-Fort ThomasNewport-Fort Thom…East North CentralIndependenceOhioLawrenceburg TownshipLawrenceburgCovingtonClermont CountyClermontMidwestTrentonCincinnati Metro AreaCincinnatiLemon TownshipLemonFlorenceFairfieldUnion TownshipUnionOxford TownshipOxfordSharonvilleDelhi TownshipDelhiSpringfield TownshipSpringfieldBurlingtonHarrison TownshipHarrisonLebanonMiami TownshipMiamiAlexandriaWaltonSycamore TownshipSycamoreMiller TownshipMillerPierce TownshipPierceGreen TownshipGrnWest Chester TownshipW ChesterLovelandMiami TownshipMiamiLiberty TownshipLibertyHamilton TownshipHamiltonFairfield TownshipFairfieldBlue AshHebronAnderson TownshipAndersonDeerfield TownshipDeerfieldClear Creek TownshipClear CrkMasonSymmes TownshipSymmesMontgomery19.584570%19.584570%19.6%1,914118.211726%18.211726%18.2%5,591216.037736%16.037736%16.0%1,836316.030240%16.030240%16.0%2,078415.293656%15.293656%15.3%6,234515.251718%15.251718%15.3%1,642614.325856%14.325856%14.3%3,008713.761583%13.761583%13.8%26,28626.3k813.402200%13.402200%13.4%999913.020590%13.020590%13.0%27,818,38027.8M12.671106%12.671106%12.7%68512.480718%12.480718%12.5%8901011.524425%11.524425%11.5%1,8001110.900938%10.900938%10.9%1,3371210.847918%10.847918%10.8%4,3141310.750959%10.750959%10.8%5,0151410.719464%10.719464%10.7%3,363,7843.36M10.657293%10.657293%10.7%3,0321510.514146%10.514146%10.5%825,155825k10.500723%10.500723%10.5%7991610.452332%10.452332%10.5%7,9861710.407526%10.407526%10.4%14,16114.2k10.244520%10.244520%10.2%4,641,8354.64M10.022156%10.022156%10.0%769189.940523%9.940523%9.9%141,727142k9.225966%9.225966%9.2%857198.943345%8.943345%8.9%3,989208.712972%8.712972%8.7%2,559218.597523%8.597523%8.6%2,777228.275675%8.275675%8.3%610237.943026%7.943026%7.9%619247.596086%7.596086%7.6%1,506257.516812%7.516812%7.5%1,822267.483438%7.483438%7.5%915277.287530%7.287530%7.3%734286.881451%6.881451%6.9%880296.874486%6.874486%6.9%752306.852638%6.852638%6.9%678316.823028%6.823028%6.8%896326.662846%6.662846%6.7%930336.253006%6.253006%6.3%390345.888155%5.888155%5.9%597355.804316%5.804316%5.8%2,402365.727981%5.727981%5.7%2,390375.681479%5.681479%5.7%381385.628396%5.628396%5.6%1,554395.136204%5.136204%5.1%1,169404.830743%4.830743%4.8%802414.741951%4.741951%4.7%679424.283979%4.283979%4.3%388433.526057%3.526057%3.5%408443.351036%3.351036%3.4%978453.293195%3.293195%3.3%815463.167093%3.167093%3.2%656472.512136%2.512136%2.5%533482.504472%2.504472%2.5%252492.279594%2.279594%2.3%16650
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older without a high school diploma (or equivalent).

Bachelor's Degrees by County Subdivision#16

Percent of population 25 years of age and older with a bachelor's degree or higher..
Scope: population of the Monroe Township, selected other county subdivisions in the Cincinnati Area, and entities that contain the Monroe Township
0%20%40%60%Count#MontgomerySymmes TownshipSymmesMasonDeerfield TownshipDeerfieldAnderson TownshipAndersonBlue AshOxford TownshipOxfordHamilton TownshipHamiltonLiberty TownshipLibertyClear Creek TownshipClear CrkWest Chester TownshipW ChesterSycamore TownshipSycamoreMiami TownshipMiamiSharonvilleLovelandHebronWaltonPierce TownshipPierceCincinnatiMiami TownshipMiamiGreen TownshipGrnSpringdaleNewport-Fort ThomasNewport-Fort Thom…Cincinnati Metro AreaCincinnatiCovingtonUnited States of AmericaUnited StatesAlexandriaFairfield TownshipFairfieldSpringfield TownshipSpringfieldUnion TownshipUnionLebanonMidwestEast North CentralNorwoodFairfieldFlorenceLemon TownshipLemonDelhi TownshipDelhiClermont CountyClermontForest ParkMiller TownshipMillerIndependenceBurlingtonOhioBatavia TownshipBataviaTurtlecreek TownshipTurtlecreekHarrison TownshipHarrisonColerain TownshipColerainReadingLawrenceburg TownshipLawrenceburgMiddletownGoshen TownshipGoshenMonroe TownshipMonroeHamiltonTrentonFranklin TownshipFranklinWilliamstown-Dry RidgeWilliamstown-Dry …69.101895%69.101895%69.1%5,032165.056649%65.056649%65.1%6,546259.329783%59.329783%59.3%12,58812.6k357.851139%57.851139%57.9%14,31714.3k456.039061%56.039061%56.0%16,35516.4k555.415701%55.415701%55.4%5,019655.026455%55.026455%55.0%4,056751.282978%51.282978%51.3%8,514850.549209%50.549209%50.5%11,50511.5k949.152706%49.152706%49.2%10,18110.2k1047.424805%47.424805%47.4%19,78819.8k1147.406505%47.406505%47.4%6,6171242.654835%42.654835%42.7%11,77711.8k1339.830617%39.830617%39.8%3,1041439.114226%39.114226%39.1%2,6231538.976752%38.976752%39.0%4,5101637.823637%37.823637%37.8%4,9671737.114114%37.114114%37.1%3,7631833.783048%33.783048%33.8%64,52964.5k1933.348569%33.348569%33.3%3,6482032.914482%32.914482%32.9%13,62113.6k2132.130400%32.130400%32.1%2,3952231.967758%31.967758%32.0%14,91214.9k2331.723093%31.723093%31.7%452,292452k30.669860%30.669860%30.7%23,43323.4k2430.315023%30.315023%30.3%64,767,78764.8M30.220336%30.220336%30.2%2,9902529.701795%29.701795%29.7%4,2532629.700070%29.700070%29.7%7,1992729.613003%29.613003%29.6%9,5652829.222709%29.222709%29.2%3,7372928.952816%28.952816%29.0%13,118,64213.1M28.462853%28.462853%28.5%8,931,6868.93M28.257348%28.257348%28.3%3,6633028.219271%28.219271%28.2%8,2883128.152815%28.152815%28.2%12,55712.6k3228.097750%28.097750%28.1%2,6103328.018763%28.018763%28.0%5,5553427.618418%27.618418%27.6%37,57937.6k27.215654%27.215654%27.2%3,3383527.112394%27.112394%27.1%1,6913627.089631%27.089631%27.1%7,7073726.915842%26.915842%26.9%3,2913826.667466%26.667466%26.7%2,092,8752.09M25.059223%25.059223%25.1%3,9143924.406010%24.406010%24.4%2,7944022.656871%22.656871%22.7%2,2824121.665661%21.665661%21.7%8,6164220.333754%20.333754%20.3%1,4504318.202129%18.202129%18.2%1,3854416.631922%16.631922%16.6%5,1064516.384915%16.384915%16.4%1,7644615.667777%15.667777%15.7%84715.075315%15.075315%15.1%6,1454714.779096%14.779096%14.8%1,1344814.178216%14.178216%14.2%2,9774912.872199%12.872199%12.9%1,25850
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older with a bachelor's degree or higher..

Very Advanced Degrees by County Subdivision#17

Percent of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).
Scope: population of the Monroe Township, selected other county subdivisions in the Cincinnati Area, and entities that contain the Monroe Township
0%5%10%15%Count#Oxford TownshipOxfordMontgomerySymmes TownshipSymmesBlue AshAnderson TownshipAndersonMasonClear Creek TownshipClear CrkSycamore TownshipSycamoreCincinnatiHamilton TownshipHamiltonDeerfield TownshipDeerfieldSharonvilleWest Chester TownshipW ChesterWaltonNewport-Fort ThomasNewport-Fort Thom…Liberty TownshipLibertyUnited States of AmericaUnited StatesPierce TownshipPierceHebronCincinnati Metro AreaCincinnatiCovingtonMiami TownshipMiamiMidwestEast North CentralOhioMiami TownshipMiamiFairfield TownshipFairfieldGreen TownshipGrnSpringfield TownshipSpringfieldIndependenceFlorenceNorwoodAlexandriaMiller TownshipMillerClermont CountyClermontBatavia TownshipBataviaColerain TownshipColerainDelhi TownshipDelhiBurlingtonFairfieldLovelandSpringdaleWilliamstown-Dry RidgeWilliamstown-Dry …Forest ParkLebanonLemon TownshipLemonLawrenceburg TownshipLawrenceburgHamiltonUnion TownshipUnionMiddletownTurtlecreek TownshipTurtlecreekMonroe TownshipMonroeTrentonFranklin TownshipFranklinReadingGoshen TownshipGoshenHarrison TownshipHarrison15.533849%15.533849%15.5%1,145110.395496%10.395496%10.4%75729.809183%9.809183%9.8%98739.031688%9.031688%9.0%81847.476443%7.476443%7.5%2,18257.098082%7.098082%7.1%1,50665.817602%5.817602%5.8%1,20575.702823%5.702823%5.7%79684.729595%4.729595%4.7%9,03494.324780%4.324780%4.3%718104.149830%4.149830%4.1%1,027114.131913%4.131913%4.1%322124.100659%4.100659%4.1%1,711134.051173%4.051173%4.1%532143.803031%3.803031%3.8%1,774153.514938%3.514938%3.5%800163.336158%3.336158%3.3%7,127,6737.13M3.274485%3.274485%3.3%332173.154438%3.154438%3.2%365183.129371%3.129371%3.1%44,61744.6k3.026020%3.026020%3.0%2,312192.911988%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%210,582211k2.641923%2.641923%2.6%289212.479223%2.479223%2.5%355222.476862%2.476862%2.5%1,025232.396964%2.396964%2.4%581242.161687%2.161687%2.2%615252.138870%2.138870%2.1%954262.082851%2.082851%2.1%270272.071963%2.071963%2.1%205281.956069%1.956069%2.0%122291.832213%1.832213%1.8%2,4931.824701%1.824701%1.8%285301.815530%1.815530%1.8%722311.704832%1.704832%1.7%338321.627546%1.627546%1.6%199331.477698%1.477698%1.5%434341.461378%1.461378%1.5%98351.435471%1.435471%1.4%107361.381357%1.381357%1.4%135371.377905%1.377905%1.4%169381.360651%1.360651%1.4%174391.345678%1.345678%1.3%125401.314233%1.314233%1.3%100411.241352%1.241352%1.2%506421.238390%1.238390%1.2%400430.996743%0.996743%1.0%306440.899720%0.899720%0.9%103450.850906%0.850906%0.9%460.821061%0.821061%0.8%63460.561985%0.561985%0.6%118470.434722%0.434722%0.4%31480.408694%0.408694%0.4%44490.228356%0.228356%0.2%2350
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).

Under-Education Sex Ratio by County Subdivision#18

Percentage more likely men are than women to not have a high school diploma (or equivalent) among people aged 25 years and older.
Scope: population of the Monroe Township, selected other county subdivisions in the Cincinnati Area, and entities that contain the Monroe Township
Female
Male
2x0x2x4xFM#TurtlecreekLebanonAndersonSymmesMillerWilliamstown-Dry RdgWilliamstown-Dry …GoshenIndependenceWaltonForest ParkLovelandUnionAlexandriaClermontBurlingtonSharonvilleCovingtonColerainGrnFairfieldMiddletownMidwestMasonEast North CentralCincinnatiNewport-Fort ThomasNewport-Fort Thom…LawrenceburgUnited StatesOhioHebronSpringdaleMonroeHamiltonFranklinPierceTrentonDeerfieldW ChesterFlorenceLibertyHamiltonCincinnatiClear CrkDelhiBataviaMiamiHarrisonSycamoreSpringfieldOxfordMiamiReadingNorwoodMontgomeryFairfieldBlue AshLemon-1.000000x-1.000000x4.656298x4.656298x4.66x4.700%4.70%21.882%21.9%1-1.000000x-1.000000x2.046987x2.046987x2.05x4.586%4.59%9.387%9.39%2-1.000000x-1.000000x1.766803x1.766803x1.77x2.468%2.47%4.360%4.36%3-1.000000x-1.000000x1.546207x1.546207x1.55x1.971%1.97%3.047%3.05%4-1.000000x-1.000000x1.539153x1.539153x1.54x4.933%4.93%7.593%7.59%5-1.000000x-1.000000x1.536446x1.536446x1.54x15.458%15.5%23.751%23.8%6-1.000000x-1.000000x1.419705x1.419705x1.42x12.616%12.6%17.910%17.9%7-1.000000x-1.000000x1.376987x1.376987x1.38x8.996%9.00%12.388%12.4%8-1.000000x-1.000000x1.354184x1.354184x1.35x5.799%5.80%7.853%7.85%9-1.000000x-1.000000x1.264074x1.264074x1.26x9.719%9.72%12.285%12.3%10-1.000000x-1.000000x1.259785x1.259785x1.26x5.045%5.04%6.356%6.36%11-1.000000x-1.000000x1.242595x1.242595x1.24x7.704%7.70%9.573%9.57%12-1.000000x-1.000000x1.232380x1.232380x1.23x6.180%6.18%7.616%7.62%13-1.000000x-1.000000x1.219059x1.219059x1.22x9.410%9.41%11.471%11.5%-1.000000x-1.000000x1.202049x1.202049x1.20x6.789%6.79%8.161%8.16%14-1.000000x-1.000000x1.195320x1.195320x1.20x7.243%7.24%8.657%8.66%15-1.000000x-1.000000x1.190394x1.190394x1.19x9.571%9.57%11.394%11.4%16-1.000000x-1.000000x1.175447x1.175447x1.18x10.032%10.0%11.792%11.8%17-1.000000x-1.000000x1.173903x1.173903x1.17x5.370%5.37%6.304%6.30%18-1.000000x-1.000000x1.173628x1.173628x1.17x8.033%8.03%9.428%9.43%19-1.000000x-1.000000x1.147049x1.147049x1.15x17.010%17.0%19.512%19.5%20-1.000000x-1.000000x1.127915x1.127915x1.13x9.647%9.65%10.881%10.9%-1.000000x-1.000000x1.125850x1.125850x1.13x2.371%2.37%2.669%2.67%21-1.000000x-1.000000x1.125371x1.125371x1.13x10.108%10.1%11.375%11.4%-1.000000x-1.000000x1.120901x1.120901x1.12x9.396%9.40%10.532%10.5%-1.000000x-1.000000x1.120330x1.120330x1.12x10.166%10.2%11.389%11.4%22-1.000000x-1.000000x1.112326x1.112326x1.11x9.959%9.96%11.078%11.1%23-1.000000x-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-1.000000x1.093703x1.093703x1.09x3.370%3.37%3.686%3.69%24-1.000000x-1.000000x1.087946x1.087946x1.09x12.855%12.9%13.985%14.0%25-1.000000x-1.000000x1.086315x1.086315x1.09x12.152%12.2%13.201%13.2%-1.000000x-1.000000x1.073344x1.073344x1.07x4.661%4.66%5.003%5.00%26-1.000000x-1.000000x1.070157x1.070157x1.07x13.859%13.9%14.832%14.8%27-1.000000x-1.000000x1.060151x1.060151x1.06x5.721%5.72%6.066%6.07%28-1.000000x-1.000000x1.054139x1.054139x1.05x9.775%9.78%10.304%10.3%29-1.000000x-1.000000x1.045216x1.045216x1.05x3.224%3.22%3.370%3.37%30-1.000000x-1.000000x1.031821x1.031821x1.03x5.641%5.64%5.821%5.82%31-1.000000x-1.000000x1.026336x1.026336x1.03x8.833%8.83%9.066%9.07%32-1.000000x-1.000000x1.026192x1.026192x1.03x5.072%5.07%5.205%5.20%33-1.000000x-1.000000x1.015682x1.015682x1.02x15.182%15.2%15.420%15.4%34-1.000000x-1.000000x1.001229x1.001229x1.00x13.754%13.8%13.771%13.8%35-1.027411x-1.027411x1.03x1.000000x1.000000x3.208%3.21%3.122%3.12%36-1.035513x-1.035513x1.04x1.000000x1.000000x7.718%7.72%7.454%7.45%37-1.042513x-1.042513x1.04x1.000000x1.000000x11.748%11.7%11.269%11.3%38-1.075183x-1.075183x1.08x1.000000x1.000000x5.828%5.83%5.420%5.42%39-1.076898x-1.076898x1.08x1.000000x1.000000x7.533%7.53%6.995%7.00%40-1.102881x-1.102881x1.10x1.000000x1.000000x6.964%6.96%6.315%6.31%41-1.145574x-1.145574x1.15x1.000000x1.000000x7.957%7.96%6.946%6.95%42-1.192103x-1.192103x1.19x1.000000x1.000000x9.013%9.01%7.561%7.56%43-1.202620x-1.202620x1.20x1.000000x1.000000x7.519%7.52%6.252%6.25%44-1.217030x-1.217030x1.22x1.000000x1.000000x13.540%13.5%11.125%11.1%45-1.344711x-1.344711x1.34x1.000000x1.000000x18.373%18.4%13.663%13.7%46-1.565337x-1.565337x1.57x1.000000x1.000000x2.745%2.75%1.754%1.75%47-1.600997x-1.600997x1.60x1.000000x1.000000x5.728%5.73%3.578%3.58%48-1.852773x-1.852773x1.85x1.000000x1.000000x5.536%5.54%2.988%2.99%49-2.002309x-2.002309x2.00x1.000000x1.000000x12.031%12.0%6.009%6.01%50
F percentage of females in category
M percentage of males in category
# rank of county subdivision out of 50 by male-to-female sex ratio

Over-Education Sex Ratio by County Subdivision#19

Percentage more likely men are than women to have a professional or doctorate degree (e.g., MBA, PhD, or MD) among people aged 25 years and older.
Scope: population of the Monroe Township, selected other county subdivisions in the Cincinnati Area, and entities that contain the Monroe Township
Female
Male
2x0x2xFM#FairfieldLebanonMontgomerySymmesPierceMiddletownOxfordAndersonBurlingtonMillerDeerfieldDelhiNewport-Fort ThomasNewport-Fort Thom…MiamiHarrisonWaltonHebronBlue AshClermontBataviaOhioFairfieldW ChesterSpringfieldClear CrkEast North CentralMidwestCincinnatiLemonUnited StatesLibertyFlorenceCovingtonHamiltonSpringdaleUnionAlexandriaMonroeGrnCincinnatiSycamoreForest ParkMasonFranklinColerainHamiltonGoshenIndependenceMiamiLovelandNorwoodLawrenceburgSharonvilleTurtlecreekWilliamstown-Dry RdgWilliamstown-Dry …ReadingTrenton-1.000000x-1.000000x3.276704x3.276704x3.28x1.213%1.21%3.974%3.97%1-1.000000x-1.000000x3.224151x3.224151x3.22x0.659%0.66%2.126%2.13%2-1.000000x-1.000000x3.080069x3.080069x3.08x5.258%5.26%16.194%16.2%3-1.000000x-1.000000x2.687619x2.687619x2.69x5.341%5.34%14.354%14.4%4-1.000000x-1.000000x2.614950x2.614950x2.61x1.837%1.84%4.804%4.80%5-1.000000x-1.000000x2.596948x2.596948x2.60x0.564%0.56%1.465%1.46%6-1.000000x-1.000000x2.488110x2.488110x2.49x8.848%8.85%22.014%22.0%7-1.000000x-1.000000x2.428350x2.428350x2.43x4.486%4.49%10.893%10.9%8-1.000000x-1.000000x2.106750x2.106750x2.11x1.043%1.04%2.198%2.20%9-1.000000x-1.000000x2.005611x2.005611x2.01x1.305%1.30%2.617%2.62%10-1.000000x-1.000000x1.991550x1.991550x1.99x2.826%2.83%5.628%5.63%11-1.000000x-1.000000x1.914242x1.914242x1.91x1.199%1.20%2.295%2.30%12-1.000000x-1.000000x1.898515x1.898515x1.90x2.660%2.66%5.049%5.05%13-1.000000x-1.000000x1.851159x1.851159x1.85x2.056%2.06%3.806%3.81%14-1.000000x-1.000000x1.848215x1.848215x1.85x0.165%0.16%0.304%0.30%15-1.000000x-1.000000x1.826461x1.826461x1.83x2.869%2.87%5.241%5.24%16-1.000000x-1.000000x1.824013x1.824013x1.82x2.241%2.24%4.087%4.09%17-1.000000x-1.000000x1.805733x1.805733x1.81x6.470%6.47%11.683%11.7%18-1.000000x-1.000000x1.797099x1.797099x1.80x1.322%1.32%2.376%2.38%-1.000000x-1.000000x1.708065x1.708065x1.71x1.371%1.37%2.342%2.34%19-1.000000x-1.000000x1.669500x1.669500x1.67x2.031%2.03%3.391%3.39%-1.000000x-1.000000x1.650680x1.650680x1.65x1.122%1.12%1.852%1.85%20-1.000000x-1.000000x1.648570x1.648570x1.65x3.124%3.12%5.150%5.15%21-1.000000x-1.000000x1.646433x1.646433x1.65x1.871%1.87%3.080%3.08%22-1.000000x-1.000000x1.609013x1.609013x1.61x4.513%4.51%7.261%7.26%23-1.000000x-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-1.000000x1.582232x1.582232x1.58x2.447%2.45%3.871%3.87%-1.000000x-1.000000x1.557853x1.557853x1.56x1.068%1.07%1.664%1.66%24-1.000000x-1.000000x1.526215x1.526215x1.53x2.660%2.66%4.060%4.06%-1.000000x-1.000000x1.525512x1.525512x1.53x2.801%2.80%4.272%4.27%25-1.000000x-1.000000x1.516293x1.516293x1.52x1.719%1.72%2.607%2.61%26-1.000000x-1.000000x1.394111x1.394111x1.39x2.542%2.54%3.543%3.54%27-1.000000x-1.000000x1.367987x1.367987x1.37x3.657%3.66%5.003%5.00%28-1.000000x-1.000000x1.358615x1.358615x1.36x1.223%1.22%1.662%1.66%29-1.000000x-1.000000x1.348352x1.348352x1.35x1.062%1.06%1.431%1.43%30-1.000000x-1.000000x1.339826x1.339826x1.34x1.787%1.79%2.395%2.39%31-1.000000x-1.000000x1.328197x1.328197x1.33x0.732%0.73%0.972%0.97%-1.000000x-1.000000x1.319751x1.319751x1.32x2.156%2.16%2.845%2.85%32-1.000000x-1.000000x1.280610x1.280610x1.28x4.179%4.18%5.351%5.35%33-1.000000x-1.000000x1.277233x1.277233x1.28x5.053%5.05%6.454%6.45%34-1.000000x-1.000000x1.272394x1.272394x1.27x1.224%1.22%1.558%1.56%35-1.000000x-1.000000x1.186547x1.186547x1.19x6.522%6.52%7.739%7.74%36-1.000000x-1.000000x1.160587x1.160587x1.16x0.522%0.52%0.606%0.61%37-1.000000x-1.000000x1.145376x1.145376x1.15x1.701%1.70%1.948%1.95%38-1.000000x-1.000000x1.036455x1.036455x1.04x1.220%1.22%1.265%1.26%39-1.000000x-1.000000x1.008582x1.008582x1.01x0.407%0.41%0.410%0.41%40-1.027634x-1.027634x1.03x1.000000x1.000000x2.191%2.19%2.132%2.13%41-1.043114x-1.043114x1.04x1.000000x1.000000x2.699%2.70%2.587%2.59%42-1.067505x-1.067505x1.07x1.000000x1.000000x1.508%1.51%1.412%1.41%43-1.081783x-1.081783x1.08x1.000000x1.000000x2.164%2.16%2.001%2.00%44-1.193952x-1.193952x1.19x1.000000x1.000000x1.426%1.43%1.195%1.19%45-1.242801x-1.242801x1.24x1.000000x1.000000x4.574%4.57%3.681%3.68%46-1.282842x-1.282842x1.28x1.000000x1.000000x1.053%1.05%0.821%0.82%47-2.270737x-2.270737x2.27x1.000000x1.000000x1.914%1.91%0.843%0.84%48-2.679134x-2.679134x2.68x1.000000x1.000000x0.600%0.60%0.224%0.22%49-2.800391x-2.800391x2.80x1.000000x1.000000x1.173%1.17%0.419%0.42%50
F percentage of females in category
M percentage of males in category
# rank of county subdivision out of 50 by male-to-female sex ratio

Educational Attainment by County Subdivision in Ohio

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

No H.S. Diploma by County Subdivision#20

Percent of population 25 years of age and older without a high school diploma (or equivalent).
Scope: population of the Monroe Township, selected other county subdivisions in Ohio, and entities that contain the Monroe Township
0%5%10%15%20%Count#ClevelandMiddletownLorainYoungstownSpringfieldDaytonMansfieldLimaMarion TownshipMarionCantonHamiltonWarrenToledoCincinnatiAkronElyriaUnited States of AmericaUnited StatesNewarkMonroe TownshipMonroeBath TownshipLancaster City TownshipLancaster CityColumbusColerain TownshipColerainEast North CentralEuclidOhioClermont CountyClermontMidwestCincinnati Metro AreaCincinnatiParmaFindlayFairfieldMiami TownshipMiamiUnion TownshipUnionHuber HeightsJackson TownshipJacksonCleveland HeightsCleveland HtsCuyahoga FallsPlain TownshipPlainLakewoodKetteringGreen TownshipGrnBoardman TownshipBoardmanWest Chester TownshipW ChesterMiami TownshipMiamiMifflin TownshipMifflinMentorLiberty TownshipLibertySylvania TownshipSylvaniaStrongsvilleViolet TownshipVioletJackson TownshipJacksonWashington TownshipWashingtonAnderson TownshipAndersonDeerfield TownshipDeerfieldBeavercreek TownshipBeavercreekDublin21.582420%21.582420%21.6%54,98155.0k118.211726%18.211726%18.2%5,591217.551080%17.551080%17.6%7,207316.999061%16.999061%17.0%7,424416.947843%16.947843%16.9%6,580516.928359%16.928359%16.9%14,88914.9k616.499446%16.499446%16.5%5,361716.278163%16.278163%16.3%3,757815.742056%15.742056%15.7%4,875915.631958%15.631958%15.6%7,3021015.293656%15.293656%15.3%6,2341115.055107%15.055107%15.1%4,0981214.332972%14.332972%14.3%26,34326.3k1313.761583%13.761583%13.8%26,28626.3k1413.591726%13.591726%13.6%17,95118.0k1513.343328%13.343328%13.3%4,8061613.020590%13.020590%13.0%27,818,38027.8M12.943290%12.943290%12.9%4,1061712.671106%12.671106%12.7%68512.411362%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%825,155825k10.407526%10.407526%10.4%14,16114.2k10.244520%10.244520%10.2%4,641,8354.64M9.940523%9.940523%9.9%141,727142k9.939137%9.939137%9.9%5,683239.003845%9.003845%9.0%2,482248.712972%8.712972%8.7%2,559258.614662%8.614662%8.6%3,080268.597523%8.597523%8.6%2,777277.261193%7.261193%7.3%1,797286.480864%6.480864%6.5%1,944296.307136%6.307136%6.3%1,918306.197364%6.197364%6.2%2,215316.171554%6.171554%6.2%2,311326.109570%6.109570%6.1%2,246335.953744%5.953744%6.0%2,340345.804316%5.804316%5.8%2,402355.764815%5.764815%5.8%1,682365.727981%5.727981%5.7%2,390375.628396%5.628396%5.6%1,554385.595517%5.595517%5.6%1,408395.268752%5.268752%5.3%1,834405.136204%5.136204%5.1%1,169414.322119%4.322119%4.3%1,462424.066023%4.066023%4.1%1,313433.979966%3.979966%4.0%1,041443.830735%3.830735%3.8%1,118453.637690%3.637690%3.6%1,496463.351036%3.351036%3.4%978473.293195%3.293195%3.3%815483.105178%3.105178%3.1%1,170491.754602%1.754602%1.8%42850
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older without a high school diploma (or equivalent).

Bachelor's Degrees by County Subdivision#21

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 FallsMentorCincinnati Metro AreaCincinnatiBoardman TownshipBoardmanUnited States of AmericaUnited StatesUnion TownshipUnionJackson TownshipJacksonMidwestEast North CentralFairfieldClermont CountyClermontBath TownshipFindlayMiami TownshipMiamiOhioHuber HeightsColerain TownshipColerainEuclidAkronParmaNewarkToledoDaytonMiddletownLancaster City TownshipLancaster CityClevelandMonroe TownshipMonroeElyriaHamiltonSpringfieldCantonMansfieldWarrenYoungstownLorainLimaMarion TownshipMarion75.246997%75.246997%75.2%18,35518.4k157.851139%57.851139%57.9%14,31714.3k256.039061%56.039061%56.0%16,35516.4k352.483891%52.483891%52.5%21,58421.6k451.261976%51.261976%51.3%19,31519.3k550.973364%50.973364%51.0%15,50115.5k650.549209%50.549209%50.5%11,50511.5k747.424805%47.424805%47.4%19,78819.8k846.115414%46.115414%46.1%15,59915.6k944.614765%44.614765%44.6%14,40714.4k1043.925605%43.925605%43.9%11,05311.1k1143.657287%43.657287%43.7%11,41911.4k1243.651053%43.651053%43.7%16,04716.0k1342.654835%42.654835%42.7%11,77711.8k1441.432243%41.432243%41.4%12,09212.1k1534.685843%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%11,22211.2k2231.723093%31.723093%31.7%452,292452k31.219796%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%8,2882627.618418%27.618418%27.6%37,57937.6k26.954091%26.954091%27.0%6,6522726.775738%26.775738%26.8%7,3812826.713842%26.713842%26.7%9,5512926.667466%26.667466%26.7%2,092,8752.09M22.834168%22.834168%22.8%5,6513021.665661%21.665661%21.7%8,6163120.614221%20.614221%20.6%6,8133220.213821%20.213821%20.2%26,69726.7k3319.988457%19.988457%20.0%11,42911.4k3418.053148%18.053148%18.1%5,7273518.048021%18.048021%18.0%33,17133.2k3617.635555%17.635555%17.6%15,51115.5k3716.631922%16.631922%16.6%5,1063816.462939%16.462939%16.5%4,4313916.073076%16.073076%16.1%40,94640.9k4015.667777%15.667777%15.7%84715.411739%15.411739%15.4%5,5514115.075315%15.075315%15.1%6,1454214.851256%14.851256%14.9%5,7664314.608666%14.608666%14.6%6,8244413.812631%13.812631%13.8%4,4884512.832476%12.832476%12.8%3,4934612.044055%12.044055%12.0%5,2604711.718579%11.718579%11.7%4,8124811.460139%11.460139%11.5%2,6454910.478559%10.478559%10.5%3,24550
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older with a bachelor's degree or higher..

Very Advanced Degrees by County Subdivision#22

Percent of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).
Scope: population of 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 StatesCincinnati Metro AreaCincinnatiPlain TownshipPlainBoardman TownshipBoardmanViolet TownshipVioletMiami TownshipMiamiMidwestEast North CentralOhioCuyahoga FallsGreen TownshipGrnBath TownshipAkronJackson TownshipJacksonClevelandClermont CountyClermontMentorColerain TownshipColerainMiami TownshipMiamiFindlayToledoSpringfieldFairfieldEuclidHuber HeightsLimaDaytonCantonHamiltonUnion TownshipUnionParmaNewarkLancaster City TownshipLancaster CityMansfieldMiddletownLorainElyriaMonroe TownshipMonroeYoungstownWarrenMarion TownshipMarion10.753042%10.753042%10.8%3,270110.031566%10.031566%10.0%2,44727.476443%7.476443%7.5%2,18237.470585%7.470585%7.5%2,52746.820669%6.820669%6.8%2,80556.685422%6.685422%6.7%2,51965.297242%5.297242%5.3%1,54675.051412%5.051412%5.1%1,85784.729595%4.729595%4.7%9,03494.555308%4.555308%4.6%1,471104.149830%4.149830%4.1%1,027114.100659%4.100659%4.1%1,711123.778338%3.778338%3.8%1,485133.514938%3.514938%3.5%800143.389898%3.389898%3.4%853153.357865%3.357865%3.4%17,95418.0k163.336158%3.336158%3.3%7,127,6737.13M3.129371%3.129371%3.1%44,61744.6k3.036372%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%4,911261.832213%1.832213%1.8%2,4931.815622%1.815622%1.8%632271.815530%1.815530%1.8%722281.762090%1.762090%1.8%630291.675978%1.675978%1.7%462301.642065%1.642065%1.6%3,018311.545396%1.545396%1.5%600321.477698%1.477698%1.5%434331.388805%1.388805%1.4%459341.349604%1.349604%1.3%334351.304159%1.304159%1.3%301361.257490%1.257490%1.3%1,106371.245933%1.245933%1.2%582381.241352%1.241352%1.2%506391.238390%1.238390%1.2%400401.236490%1.236490%1.2%707411.182108%1.182108%1.2%375421.159205%1.159205%1.2%312431.104887%1.104887%1.1%359440.996743%0.996743%1.0%306450.964372%0.964372%1.0%396460.952302%0.952302%1.0%343470.850906%0.850906%0.9%460.794541%0.794541%0.8%347480.742101%0.742101%0.7%202490.720098%0.720098%0.7%22350
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).

Under-Education Sex Ratio by County Subdivision#23

Percentage more likely men are than women to not have a high school diploma (or equivalent) among people aged 25 years and older.
Scope: population of the Monroe Township, selected other county subdivisions in Ohio, and entities that contain the Monroe Township
Female
Male
1x0x1xFM#AndersonMansfieldCleveland HtsBeavercreekUnionToledoFindlayClermontLorainMarionYoungstownColerainGrnFairfieldElyriaMiddletownLancaster CityMidwestEast North CentralSpringfieldWarrenCincinnatiDaytonCantonUnited StatesOhioLimaMonroeParmaColumbusClevelandDeerfieldMentorNewarkW ChesterPlainLibertyJacksonHuber HeightsHamiltonJacksonCincinnatiAkronMifflinSylvaniaMiamiEuclidMiamiCuyahoga FallsStrongsvilleLakewoodBath TownshipDublinKetteringWashingtonBoardmanViolet-1.000000x-1.000000x1.766803x1.766803x1.77x2.468%2.47%4.360%4.36%1-1.000000x-1.000000x1.592708x1.592708x1.59x12.530%12.5%19.956%20.0%2-1.000000x-1.000000x1.485471x1.485471x1.49x5.146%5.15%7.645%7.64%3-1.000000x-1.000000x1.332397x1.332397x1.33x2.666%2.67%3.552%3.55%4-1.000000x-1.000000x1.242595x1.242595x1.24x7.704%7.70%9.573%9.57%5-1.000000x-1.000000x1.227011x1.227011x1.23x12.945%12.9%15.884%15.9%6-1.000000x-1.000000x1.222843x1.222843x1.22x8.133%8.13%9.946%9.95%7-1.000000x-1.000000x1.219059x1.219059x1.22x9.410%9.41%11.471%11.5%-1.000000x-1.000000x1.207850x1.207850x1.21x16.045%16.0%19.380%19.4%8-1.000000x-1.000000x1.204406x1.204406x1.20x14.131%14.1%17.020%17.0%9-1.000000x-1.000000x1.194114x1.194114x1.19x15.554%15.6%18.574%18.6%10-1.000000x-1.000000x1.175447x1.175447x1.18x10.032%10.0%11.792%11.8%11-1.000000x-1.000000x1.173903x1.173903x1.17x5.370%5.37%6.304%6.30%12-1.000000x-1.000000x1.173628x1.173628x1.17x8.033%8.03%9.428%9.43%13-1.000000x-1.000000x1.166450x1.166450x1.17x12.379%12.4%14.439%14.4%14-1.000000x-1.000000x1.147049x1.147049x1.15x17.010%17.0%19.512%19.5%15-1.000000x-1.000000x1.144160x1.144160x1.14x11.593%11.6%13.265%13.3%16-1.000000x-1.000000x1.127915x1.127915x1.13x9.647%9.65%10.881%10.9%-1.000000x-1.000000x1.125371x1.125371x1.13x10.108%10.1%11.375%11.4%-1.000000x-1.000000x1.124452x1.124452x1.12x16.027%16.0%18.022%18.0%17-1.000000x-1.000000x1.124390x1.124390x1.12x14.230%14.2%16.000%16.0%18-1.000000x-1.000000x1.120901x1.120901x1.12x9.396%9.40%10.532%10.5%-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-1.000000x1.086315x1.086315x1.09x12.152%12.2%13.201%13.2%-1.000000x-1.000000x1.081824x1.081824x1.08x9.568%9.57%10.350%10.4%22-1.000000x-1.000000x1.052237x1.052237x1.05x11.098%11.1%11.678%11.7%23-1.000000x-1.000000x1.046686x1.046686x1.05x21.119%21.1%22.105%22.1%24-1.000000x-1.000000x1.045216x1.045216x1.05x3.224%3.22%3.370%3.37%25-1.000000x-1.000000x1.038813x1.038813x1.04x5.175%5.17%5.376%5.38%26-1.000000x-1.000000x1.036562x1.036562x1.04x12.733%12.7%13.198%13.2%27-1.000000x-1.000000x1.031821x1.031821x1.03x5.641%5.64%5.821%5.82%28-1.000000x-1.000000x1.027725x1.027725x1.03x6.093%6.09%6.262%6.26%29-1.000000x-1.000000x1.026192x1.026192x1.03x5.072%5.07%5.205%5.20%30-1.000000x-1.000000x1.025236x1.025236x1.03x6.405%6.41%6.567%6.57%31-1.000000x-1.000000x1.021443x1.021443x1.02x7.189%7.19%7.344%7.34%32-1.000000x-1.000000x1.015682x1.015682x1.02x15.182%15.2%15.420%15.4%33-1.000000x-1.000000x1.006889x1.006889x1.01x3.818%3.82%3.844%3.84%34-1.000000x-1.000000x1.001229x1.001229x1.00x13.754%13.8%13.771%13.8%35-1.001506x-1.001506x1.00x1.000000x1.000000x13.601%13.6%13.581%13.6%36-1.053306x-1.053306x1.05x1.000000x1.000000x5.733%5.73%5.442%5.44%37-1.068860x-1.068860x1.07x1.000000x1.000000x4.454%4.45%4.167%4.17%38-1.075183x-1.075183x1.08x1.000000x1.000000x5.828%5.83%5.420%5.42%39-1.084060x-1.084060x1.08x1.000000x1.000000x11.029%11.0%10.174%10.2%40-1.123601x-1.123601x1.12x1.000000x1.000000x9.091%9.09%8.091%8.09%41-1.132510x-1.132510x1.13x1.000000x1.000000x6.567%6.57%5.799%5.80%42-1.209810x-1.209810x1.21x1.000000x1.000000x4.433%4.43%3.664%3.66%43-1.275391x-1.275391x1.28x1.000000x1.000000x6.820%6.82%5.347%5.35%44-1.295653x-1.295653x1.30x1.000000x1.000000x13.964%14.0%10.778%10.8%45-1.385029x-1.385029x1.39x1.000000x1.000000x2.028%2.03%1.464%1.46%46-1.505212x-1.505212x1.51x1.000000x1.000000x7.040%7.04%4.677%4.68%47-1.641786x-1.641786x1.64x1.000000x1.000000x4.457%4.46%2.715%2.71%48-1.660386x-1.660386x1.66x1.000000x1.000000x7.066%7.07%4.256%4.26%49-1.798212x-1.798212x1.80x1.000000x1.000000x5.036%5.04%2.800%2.80%50
F percentage of females in category
M percentage of males in category
# rank of county subdivision out of 50 by male-to-female sex ratio

Over-Education Sex Ratio by County Subdivision#24

Percentage more likely men are than women to have a professional or doctorate degree (e.g., MBA, PhD, or MD) among people aged 25 years and older.
Scope: population of the Monroe Township, selected other county subdivisions in Ohio, and entities that contain the Monroe Township
Female
Male
1x0x1x2x3xFM#ElyriaSpringfieldWashingtonYoungstownBoardmanLorainMiddletownLancaster CityFindlayAndersonJacksonKetteringMifflinPlainBeavercreekDeerfieldDaytonNewarkEuclidMiamiAkronDublinSylvaniaClermontStrongsvilleBath TownshipOhioFairfieldMansfieldW ChesterHuber HeightsLakewoodEast North CentralMidwestCincinnatiWarrenUnited StatesLibertyParmaCleveland HtsColumbusUnionMonroeMentorGrnJacksonClevelandCincinnatiMiamiMarionVioletColerainToledoHamiltonCantonCuyahoga FallsLima-1.000000x-1.000000x3.557903x3.557903x3.56x0.433%0.43%1.542%1.54%1-1.000000x-1.000000x3.025650x3.025650x3.03x0.799%0.80%2.417%2.42%2-1.000000x-1.000000x2.977263x2.977263x2.98x3.534%3.53%10.523%10.5%3-1.000000x-1.000000x2.809581x2.809581x2.81x0.426%0.43%1.196%1.20%4-1.000000x-1.000000x2.780060x2.780060x2.78x1.621%1.62%4.507%4.51%5-1.000000x-1.000000x2.695011x2.695011x2.70x0.546%0.55%1.472%1.47%6-1.000000x-1.000000x2.596948x2.596948x2.60x0.564%0.56%1.465%1.46%7-1.000000x-1.000000x2.442537x2.442537x2.44x0.692%0.69%1.690%1.69%8-1.000000x-1.000000x2.437656x2.437656x2.44x0.991%0.99%2.417%2.42%9-1.000000x-1.000000x2.428350x2.428350x2.43x4.486%4.49%10.893%10.9%10-1.000000x-1.000000x2.183841x2.183841x2.18x3.386%3.39%7.394%7.39%11-1.000000x-1.000000x2.155653x2.155653x2.16x2.468%2.47%5.319%5.32%12-1.000000x-1.000000x2.069018x2.069018x2.07x2.252%2.25%4.660%4.66%13-1.000000x-1.000000x2.024516x2.024516x2.02x2.059%2.06%4.169%4.17%14-1.000000x-1.000000x2.007898x2.007898x2.01x4.457%4.46%8.948%8.95%15-1.000000x-1.000000x1.991550x1.991550x1.99x2.826%2.83%5.628%5.63%16-1.000000x-1.000000x1.989047x1.989047x1.99x0.860%0.86%1.711%1.71%17-1.000000x-1.000000x1.967904x1.967904x1.97x0.822%0.82%1.618%1.62%18-1.000000x-1.000000x1.903271x1.903271x1.90x0.997%1.00%1.897%1.90%19-1.000000x-1.000000x1.851159x1.851159x1.85x2.056%2.06%3.806%3.81%20-1.000000x-1.000000x1.846298x1.846298x1.85x1.550%1.55%2.862%2.86%21-1.000000x-1.000000x1.832511x1.832511x1.83x7.149%7.15%13.100%13.1%22-1.000000x-1.000000x1.805502x1.805502x1.81x5.447%5.45%9.835%9.84%23-1.000000x-1.000000x1.797099x1.797099x1.80x1.322%1.32%2.376%2.38%-1.000000x-1.000000x1.769961x1.769961x1.77x3.331%3.33%5.895%5.90%24-1.000000x-1.000000x1.691857x1.691857x1.69x1.833%1.83%3.102%3.10%25-1.000000x-1.000000x1.669500x1.669500x1.67x2.031%2.03%3.391%3.39%-1.000000x-1.000000x1.650680x1.650680x1.65x1.122%1.12%1.852%1.85%26-1.000000x-1.000000x1.650301x1.650301x1.65x0.820%0.82%1.353%1.35%27-1.000000x-1.000000x1.648570x1.648570x1.65x3.124%3.12%5.150%5.15%28-1.000000x-1.000000x1.627164x1.627164x1.63x1.044%1.04%1.699%1.70%29-1.000000x-1.000000x1.624128x1.624128x1.62x3.883%3.88%6.306%6.31%30-1.000000x-1.000000x1.597848x1.597848x1.60x2.216%2.22%3.541%3.54%-1.000000x-1.000000x1.589934x1.589934x1.59x2.251%2.25%3.579%3.58%-1.000000x-1.000000x1.582232x1.582232x1.58x2.447%2.45%3.871%3.87%-1.000000x-1.000000x1.543502x1.543502x1.54x0.592%0.59%0.914%0.91%31-1.000000x-1.000000x1.526215x1.526215x1.53x2.660%2.66%4.060%4.06%-1.000000x-1.000000x1.525512x1.525512x1.53x2.801%2.80%4.272%4.27%32-1.000000x-1.000000x1.433883x1.433883x1.43x1.025%1.03%1.470%1.47%33-1.000000x-1.000000x1.416609x1.416609x1.42x9.009%9.01%12.763%12.8%34-1.000000x-1.000000x1.413654x1.413654x1.41x2.801%2.80%3.959%3.96%35-1.000000x-1.000000x1.348352x1.348352x1.35x1.062%1.06%1.431%1.43%36-1.000000x-1.000000x1.328197x1.328197x1.33x0.732%0.73%0.972%0.97%-1.000000x-1.000000x1.325696x1.325696x1.33x1.576%1.58%2.089%2.09%37-1.000000x-1.000000x1.319751x1.319751x1.32x2.156%2.16%2.845%2.85%38-1.000000x-1.000000x1.297270x1.297270x1.30x1.812%1.81%2.351%2.35%39-1.000000x-1.000000x1.286599x1.286599x1.29x1.699%1.70%2.186%2.19%40-1.000000x-1.000000x1.280610x1.280610x1.28x4.179%4.18%5.351%5.35%41-1.000000x-1.000000x1.246667x1.246667x1.25x1.577%1.58%1.966%1.97%42-1.000000x-1.000000x1.217109x1.217109x1.22x0.642%0.64%0.782%0.78%43-1.000000x-1.000000x1.149458x1.149458x1.15x2.746%2.75%3.157%3.16%44-1.000000x-1.000000x1.145376x1.145376x1.15x1.701%1.70%1.948%1.95%45-1.000000x-1.000000x1.141406x1.141406x1.14x1.539%1.54%1.757%1.76%46-1.000000x-1.000000x1.036455x1.036455x1.04x1.220%1.22%1.265%1.26%47-1.103703x-1.103703x1.10x1.000000x1.000000x1.302%1.30%1.180%1.18%48-1.188945x-1.188945x1.19x1.000000x1.000000x2.687%2.69%2.260%2.26%49-1.404867x-1.404867x1.40x1.000000x1.000000x1.525%1.53%1.086%1.09%50
F percentage of females in category
M percentage of males in category
# rank of county subdivision out of 50 by male-to-female sex ratio

Educational Attainment by County Subdivision in the Midwest

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

No H.S. Diploma by County Subdivision#25

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 TownshipThorntonMonroe TownshipMonroeWichitaKaw TownshipOmahaBloomingdale TownshipBloomingdaleColumbusMaine TownshipMaineTopekaMinneapolisSpringfield TownshipSpringfieldEast North CentralWorth TownshipWorthOhioClermont CountyClermontMidwestLawrence TownshipLawrenceCincinnati Metro AreaCincinnatiSioux FallsCapital TownshipCapitalWheeling TownshipWheelingPalatine TownshipPalatineSchaumburg TownshipSchaumburgLincolnWashington TownshipWashingtonOlatheFargoCedar RapidsYork TownshipMilton TownshipMiltonMadisonDowners Grove TownshipDowners GrvLisle TownshipLisleOverland ParkAnn Arbor33.464284%33.464284%33.5%29,81429.8k123.165532%23.165532%23.2%22,92622.9k222.659362%22.659362%22.7%21,21821.2k321.582420%21.582420%21.6%54,98155.0k421.037720%21.037720%21.0%18,48918.5k521.003600%21.003600%21.0%90,67890.7k617.485105%17.485105%17.5%63,80063.8k717.062713%17.062713%17.1%17,39117.4k816.928359%16.928359%16.9%14,88914.9k916.905373%16.905373%16.9%309,770310k1015.636222%15.636222%15.6%16,11016.1k1115.608074%15.608074%15.6%18,24118.2k1215.466266%15.466266%15.5%33,80433.8k1315.286174%15.286174%15.3%14,05914.1k1414.563179%14.563179%14.6%17,64317.6k1514.332972%14.332972%14.3%26,34326.3k1614.241047%14.241047%14.2%15,25815.3k1713.761583%13.761583%13.8%26,28626.3k1813.591726%13.591726%13.6%17,95118.0k1913.278342%13.278342%13.3%24,61324.6k2013.132171%13.132171%13.1%12,21212.2k2113.020590%13.020590%13.0%27,818,38027.8M12.974232%12.974232%13.0%14,37014.4k2212.671106%12.671106%12.7%68512.568464%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%825,155825k10.407526%10.407526%10.4%14,16114.2k10.244520%10.244520%10.2%4,641,8354.64M10.179618%10.179618%10.2%8,161339.940523%9.940523%9.9%141,727142k9.702326%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%7,226387.092309%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#26

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 RapidsCincinnati Metro AreaCincinnatiUnited States of AmericaUnited StatesSioux FallsMidwestWichitaEast North CentralClermont CountyClermontSterling HeightsSterling HtsTopekaSpringfield TownshipSpringfieldOhioProviso TownshipProvisoWorth TownshipWorthMilwaukeeRockford TownshipRockfordAkronCenter TownshipCtrNorth TownshipNThornton TownshipThorntonToledoDaytonWarrenWayne TownshipWayneKansas CityClevelandAurora TownshipAuroraBlue TownshipMonroe TownshipMonroeDetroit72.810169%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%27,10227.1k2831.723093%31.723093%31.7%452,292452k30.315023%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%8,931,6868.93M27.618418%27.618418%27.6%37,57937.6k27.532180%27.532180%27.5%25,60325.6k3127.007248%27.007248%27.0%22,95423.0k3226.964567%26.964567%27.0%27,92127.9k3326.667466%26.667466%26.7%2,092,8752.09M26.237989%26.237989%26.2%27,03327.0k3425.217641%25.217641%25.2%26,38926.4k3523.517740%23.517740%23.5%85,81285.8k3621.592552%21.592552%21.6%25,23525.2k3720.213821%20.213821%20.2%26,69726.7k3820.139240%20.139240%20.1%19,93119.9k3919.650916%19.650916%19.7%20,02920.0k4018.971090%18.971090%19.0%21,01221.0k4118.048021%18.048021%18.0%33,17133.2k4217.635555%17.635555%17.6%15,51115.5k4317.280259%17.280259%17.3%15,89315.9k4416.826535%16.826535%16.8%14,78814.8k4516.167409%16.167409%16.2%15,13915.1k4616.073076%16.073076%16.1%40,94640.9k4715.929601%15.929601%15.9%14,19214.2k4815.821208%15.821208%15.8%16,95117.0k4915.667777%15.667777%15.7%84713.833543%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#27

Percent of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).
Scope: population of 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 RapidsCincinnati Metro AreaCincinnatiLawrence TownshipLawrenceSpringfield TownshipSpringfieldCedar RapidsMidwestEast North CentralSioux FallsOlatheOhioCenter TownshipCtrSchaumburg TownshipSchaumburgWichitaProviso TownshipProvisoAkronBloomingdale TownshipBloomingdaleRockford TownshipRockfordMilwaukeeWorth TownshipWorthClevelandClermont CountyClermontToledoNorth TownshipNSterling HeightsSterling HtsKansas CityDetroitDaytonWayne TownshipWayneWarrenBlue TownshipAurora 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%3,846243.129371%3.129371%3.1%44,61744.6k3.083448%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%4,911391.832213%1.832213%1.8%2,4931.642065%1.642065%1.6%3,018401.575684%1.575684%1.6%1,606411.439893%1.439893%1.4%1,339421.388310%1.388310%1.4%1,300431.318660%1.318660%1.3%5,693441.257490%1.257490%1.3%1,106451.183365%1.183365%1.2%1,040461.047058%1.047058%1.0%963470.997751%0.997751%1.0%1,069480.936111%0.936111%0.9%834490.876686%0.876686%0.9%971500.850906%0.850906%0.9%46
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).

Under-Education Sex Ratio by County Subdivision#28

Percentage more likely men are than women to not have a high school diploma (or equivalent) among people aged 25 years and older.
Scope: population of the Monroe Township, selected other county subdivisions in the Midwest, and entities that contain the Monroe Township
Female
Male
1x0x1xFM#Cedar RapidsLincolnDetroitOmahaToledoClermontThorntonKansas CityMadisonLawrenceFargoProvisoRockfordBlue TownshipWayneMidwestTopekaEast North CentralMilwaukeeCincinnatiKaw TownshipDaytonSioux FallsUnited StatesOlatheOhioWorthNOverland ParkAuroraMonroeWheelingGrand RapidsSchaumburgChicagoWichitaColumbusClevelandPalatineCapitalWarrenSpringfieldYork TownshipSt. LouisWashingtonBloomingdaleCtrCincinnatiAkronAnn ArborSt. PaulLisleMinneapolisSterling HtsDowners GrvMiltonMaine-1.000000x-1.000000x1.243824x1.243824x1.24x5.354%5.35%6.660%6.66%1-1.000000x-1.000000x1.238529x1.238529x1.24x6.342%6.34%7.854%7.85%2-1.000000x-1.000000x1.237056x1.237056x1.24x18.951%19.0%23.443%23.4%3-1.000000x-1.000000x1.230289x1.230289x1.23x10.968%11.0%13.494%13.5%4-1.000000x-1.000000x1.227011x1.227011x1.23x12.945%12.9%15.884%15.9%5-1.000000x-1.000000x1.219059x1.219059x1.22x9.410%9.41%11.471%11.5%-1.000000x-1.000000x1.203250x1.203250x1.20x11.909%11.9%14.330%14.3%6-1.000000x-1.000000x1.189752x1.189752x1.19x20.748%20.7%24.685%24.7%7-1.000000x-1.000000x1.189278x1.189278x1.19x4.425%4.43%5.263%5.26%8-1.000000x-1.000000x1.181964x1.181964x1.18x9.406%9.41%11.117%11.1%9-1.000000x-1.000000x1.176963x1.176963x1.18x5.565%5.56%6.550%6.55%10-1.000000x-1.000000x1.174964x1.174964x1.17x14.460%14.5%16.990%17.0%11-1.000000x-1.000000x1.168755x1.168755x1.17x14.456%14.5%16.896%16.9%12-1.000000x-1.000000x1.161774x1.161774x1.16x13.244%13.2%15.387%15.4%13-1.000000x-1.000000x1.132245x1.132245x1.13x19.779%19.8%22.395%22.4%14-1.000000x-1.000000x1.127915x1.127915x1.13x9.647%9.65%10.881%10.9%-1.000000x-1.000000x1.125507x1.125507x1.13x10.423%10.4%11.732%11.7%15-1.000000x-1.000000x1.125371x1.125371x1.13x10.108%10.1%11.375%11.4%-1.000000x-1.000000x1.123984x1.123984x1.12x16.526%16.5%18.574%18.6%16-1.000000x-1.000000x1.120901x1.120901x1.12x9.396%9.40%10.532%10.5%-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-1.000000x1.086315x1.086315x1.09x12.152%12.2%13.201%13.2%-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#29

Percentage more likely men are than women to have a professional or doctorate degree (e.g., MBA, PhD, or MD) among people aged 25 years and older.
Scope: population of the Monroe Township, selected other county subdivisions in the Midwest, and entities that contain the Monroe Township
Female
Male
1x0x1x2xFM#RockfordNDaytonSioux FallsCapitalLawrenceDowners GrvAkronLisleClermontWichitaYork TownshipMaineWarrenWheelingBlue TownshipSpringfieldOverland ParkMiltonGrand RapidsOlatheOhioOmahaFargoWashingtonEast North CentralLincolnMidwestBloomingdaleCincinnatiKansas CityAuroraUnited StatesAnn ArborTopekaSterling HtsPalatineSchaumburgColumbusMadisonKaw TownshipMilwaukeeCedar RapidsMonroeClevelandCincinnatiSt. PaulSt. LouisChicagoWayneCtrToledoMinneapolisWorthDetroitProvisoThornton-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-1.000000x1.797099x1.797099x1.80x1.322%1.32%2.376%2.38%-1.000000x-1.000000x1.792728x1.792728x1.79x1.819%1.82%3.261%3.26%10-1.000000x-1.000000x1.792314x1.792314x1.79x4.498%4.50%8.062%8.06%11-1.000000x-1.000000x1.788417x1.788417x1.79x2.939%2.94%5.256%5.26%12-1.000000x-1.000000x1.768853x1.768853x1.77x0.769%0.77%1.361%1.36%13-1.000000x-1.000000x1.766097x1.766097x1.77x2.485%2.48%4.389%4.39%14-1.000000x-1.000000x1.761699x1.761699x1.76x0.737%0.74%1.298%1.30%15-1.000000x-1.000000x1.751445x1.751445x1.75x2.146%2.15%3.759%3.76%16-1.000000x-1.000000x1.732234x1.732234x1.73x4.415%4.41%7.647%7.65%17-1.000000x-1.000000x1.695067x1.695067x1.70x4.357%4.36%7.385%7.38%18-1.000000x-1.000000x1.689013x1.689013x1.69x2.382%2.38%4.023%4.02%19-1.000000x-1.000000x1.678153x1.678153x1.68x2.131%2.13%3.576%3.58%20-1.000000x-1.000000x1.669500x1.669500x1.67x2.031%2.03%3.391%3.39%-1.000000x-1.000000x1.669388x1.669388x1.67x3.061%3.06%5.110%5.11%21-1.000000x-1.000000x1.627456x1.627456x1.63x3.304%3.30%5.377%5.38%22-1.000000x-1.000000x1.610803x1.610803x1.61x5.701%5.70%9.183%9.18%23-1.000000x-1.000000x1.597848x1.597848x1.60x2.216%2.22%3.541%3.54%-1.000000x-1.000000x1.596978x1.596978x1.60x3.524%3.52%5.628%5.63%24-1.000000x-1.000000x1.589934x1.589934x1.59x2.251%2.25%3.579%3.58%-1.000000x-1.000000x1.586045x1.586045x1.59x1.649%1.65%2.616%2.62%25-1.000000x-1.000000x1.582232x1.582232x1.58x2.447%2.45%3.871%3.87%-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-1.000000x1.328197x1.328197x1.33x0.732%0.73%0.972%0.97%-1.000000x-1.000000x1.286599x1.286599x1.29x1.699%1.70%2.186%2.19%38-1.000000x-1.000000x1.280610x1.280610x1.28x4.179%4.18%5.351%5.35%39-1.000000x-1.000000x1.274509x1.274509x1.27x5.228%5.23%6.663%6.66%40-1.000000x-1.000000x1.273345x1.273345x1.27x4.319%4.32%5.500%5.50%41-1.000000x-1.000000x1.238186x1.238186x1.24x4.026%4.03%4.985%4.99%42-1.000000x-1.000000x1.223931x1.223931x1.22x1.068%1.07%1.307%1.31%43-1.000000x-1.000000x1.213574x1.213574x1.21x2.357%2.36%2.860%2.86%44-1.000000x-1.000000x1.141406x1.141406x1.14x1.539%1.54%1.757%1.76%45-1.000000x-1.000000x1.124528x1.124528x1.12x5.872%5.87%6.603%6.60%46-1.000000x-1.000000x1.084697x1.084697x1.08x1.883%1.88%2.042%2.04%47-1.000000x-1.000000x1.046557x1.046557x1.05x1.291%1.29%1.351%1.35%48-1.000000x-1.000000x1.042857x1.042857x1.04x2.171%2.17%2.264%2.26%49-1.706858x-1.706858x1.71x1.000000x1.000000x1.072%1.07%0.628%0.63%50
F percentage of females in category
M percentage of males in category
# rank of county subdivision out of 50 by male-to-female sex ratio

Educational Attainment by County Subdivision in the United States

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

No H.S. Diploma by County Subdivision#30

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 JoseMonroe TownshipMonroeSan FranciscoTucsonAlbuquerqueTownship 1:Charlotte1, CharlotteColumbusTulsaEast North CentralOhioSalt Lake CitySalt Lk CityClermont CountyClermontTown of HempsteadHempsteadMidwestNorthwest HarrisNW HarrisWashingtonCincinnati Metro AreaCincinnatiAtlantaSeattleNortheast TarrantNE TarrantPlanoSeattle East28.998944%28.998944%29.0%126,922127k128.837398%28.837398%28.8%261,022261k227.582802%27.582802%27.6%135,754136k324.837401%24.837401%24.8%434,160434k423.987048%23.987048%24.0%141,940142k523.756417%23.756417%23.8%81,30881.3k622.645542%22.645542%22.6%248,699249k722.107626%22.107626%22.1%92,47292.5k821.922900%21.922900%21.9%457,347457k921.818150%21.818150%21.8%149,688150k1021.003600%21.003600%21.0%90,67890.7k1120.783651%20.783651%20.8%207,494207k1220.461493%20.461493%20.5%128,038128k1320.041576%20.041576%20.0%106,726107k1420.017506%20.017506%20.0%351,046351k1519.402518%19.402518%19.4%73,10573.1k1619.344706%19.344706%19.3%315,505316k1719.344408%19.344408%19.3%244,983245k1817.485105%17.485105%17.5%63,80063.8k1917.390838%17.390838%17.4%180,039180k2017.129346%17.129346%17.1%71,39771.4k2116.905373%16.905373%16.9%309,770310k2216.548703%16.548703%16.5%69,83969.8k2315.999398%15.999398%16.0%70,21470.2k2415.906523%15.906523%15.9%198,651199k2514.952077%14.952077%15.0%308,569309k2614.325556%14.325556%14.3%63,64263.6k2713.900512%13.900512%13.9%103,047103k2813.679368%13.679368%13.7%53,75853.8k2913.668915%13.668915%13.7%78,23878.2k3013.638703%13.638703%13.6%63,86563.9k3113.020590%13.020590%13.0%27,818,38027.8M12.996284%12.996284%13.0%160,845161k3212.985760%12.985760%13.0%206,792207k3312.979618%12.979618%13.0%57,75857.8k3412.789590%12.789590%12.8%153,604154k3512.671106%12.671106%12.7%68512.559735%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%64,29464.3k4210.407526%10.407526%10.4%14,16114.2k10.384134%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%46,51046.5k459.940523%9.940523%9.9%141,727142k9.538552%9.538552%9.5%37,37337.4k468.833573%8.833573%8.8%66,22066.2k478.418271%8.418271%8.4%31,44331.4k485.714681%5.714681%5.7%20,64420.6k494.913852%4.913852%4.9%20,32620.3k50
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older without a high school diploma (or equivalent).

Bachelor's Degrees by County Subdivision#31

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 CityAlbuquerqueTampaTucsonCincinnati Metro AreaCincinnatiOceanside-EscondidoOceanside-Escond…TulsaQueensUnited States of AmericaUnited StatesHoustonBaltimoreLong Beach-LakewoodLong Bch-LakewoodMidwestPhoenixOrlandoEast North CentralAnaheim-Santa Ana-Garden GroveAnaheim-Santa An…SacramentoClermont CountyClermontEast San Gabriel ValleyE San Gabriel VlyOntarioOhioPhiladelphiaMiamiFort WorthSouthwest DallasSW DallasMilwaukeeFresnoLas VegasEl PasoBronxSan BernardinoMonroe TownshipMonroeSan 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%184,237184k2631.723093%31.723093%31.7%452,292452k31.198303%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%209,283209k3627.618418%27.618418%27.6%37,57937.6k27.276345%27.276345%27.3%170,682171k3726.758411%26.758411%26.8%111,532112k3826.667466%26.667466%26.7%2,092,8752.09M26.349720%26.349720%26.3%272,786273k3926.011156%26.011156%26.0%178,455178k4024.665414%24.665414%24.7%131,349131k4123.764821%23.764821%23.8%140,625141k4223.517740%23.517740%23.5%85,81285.8k4322.486319%22.486319%22.5%94,05694.1k4421.702666%21.702666%21.7%271,037271k4521.071885%21.071885%21.1%72,12072.1k4619.131504%19.131504%19.1%173,169173k4716.375473%16.375473%16.4%80,59580.6k4815.667777%15.667777%15.7%84714.929012%14.929012%14.9%65,34165.3k4913.833543%13.833543%13.8%59,72359.7k50
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older with a bachelor's degree or higher..

Very Advanced Degrees by County Subdivision#32

Percent of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).
Scope: population of 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 StatesTulsaCincinnati Metro AreaCincinnatiPhoenixLong Beach-LakewoodLong Bch-LakewoodMidwestOrlandoEast North CentralFresnoAnaheim-Santa Ana-Garden GroveAnaheim-Santa An…QueensOhioNorthwest HarrisNW HarrisNortheast TarrantNE TarrantEast San Gabriel ValleyE San Gabriel VlyOntarioFort WorthLas VegasMilwaukeeClermont CountyClermontSan BernardinoSan Antonio CentralSan Antonio CntrlEl PasoSouthwest DallasSW DallasBronxDetroitMonroe 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%12,13312.1k313.129371%3.129371%3.1%44,61744.6k3.010825%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%7,455441.832213%1.832213%1.8%2,4931.807306%1.807306%1.8%8,895451.792414%1.792414%1.8%7,845461.745764%1.745764%1.7%5,975471.704476%1.704476%1.7%10,08610.1k481.664253%1.664253%1.7%15,06415.1k491.318660%1.318660%1.3%5,693500.850906%0.850906%0.9%46
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).

Under-Education Sex Ratio by County Subdivision#33

Percentage more likely men are than women to not have a high school diploma (or equivalent) among people aged 25 years and older.
Scope: population of the Monroe Township, selected other county subdivisions in the United States, and entities that contain the Monroe Township
Female
Male
1x0x1xFM#1, CharlotteDetroitClermontBaltimoreTulsaSW DallasMidwestFresnoEast North CentralMilwaukeeCincinnatiUnited StatesOhioNE DallasHoustonHempsteadOrlandoPhiladelphiaOntarioMonroeSan BernardinoAustinAtlantaFort WorthPhoenixChicagoAlbuquerqueWashingtonSacramentoColumbusSalt Lk CityDenverNE TarrantTampaOceanside-EscondidoOceanside-Escond…NW HarrisBronxPlanoBrooklynSan Antonio CntrlSan Fernando VlyTucsonAnaheim-Santa Ana-Gdn GrvAnaheim-Santa An…Los AngelesLas VegasBostonE San Gabriel VlyQueensMiamiManhattanSeattleLong Bch-LakewoodSeattle EastSan JoseSan DiegoSan FranciscoEl Paso-1.000000x-1.000000x1.285784x1.285784x1.29x10.185%10.2%13.096%13.1%1-1.000000x-1.000000x1.237056x1.237056x1.24x18.951%19.0%23.443%23.4%2-1.000000x-1.000000x1.219059x1.219059x1.22x9.410%9.41%11.471%11.5%-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-1.000000x1.120901x1.120901x1.12x9.396%9.40%10.532%10.5%-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-1.000000x1.086315x1.086315x1.09x12.152%12.2%13.201%13.2%-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#34

Percentage more likely men are than women to have a professional or doctorate degree (e.g., MBA, PhD, or MD) among people aged 25 years and older.
Scope: population of the Monroe Township, selected other county subdivisions in the United States, and entities that contain the Monroe Township
Female
Male
1x0x1x2xFM#El PasoSalt Lk CityClermontPlanoTulsaAlbuquerqueNE DallasFort WorthOhioOrlandoPhoenixTucson1, CharlotteEast North CentralMidwestCincinnatiNW HarrisLas VegasSeattle EastSan Antonio CntrlSan DiegoUnited StatesSan JoseHempsteadFresnoNE TarrantTampaSan Fernando VlyE San Gabriel VlyHoustonSan BernardinoColumbusMiamiAtlantaMilwaukeeAnaheim-Santa Ana-Gdn GrvAnaheim-Santa An…SacramentoPhiladelphiaMonroeOceanside-EscondidoOceanside-Escond…Los AngelesAustinBaltimoreWashingtonQueensSW DallasBrooklynManhattanChicagoSeattleBostonBronxOntarioLong Bch-LakewoodDenverSan FranciscoDetroit-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-1.000000x1.797099x1.797099x1.80x1.322%1.32%2.376%2.38%-1.000000x-1.000000x1.782054x1.782054x1.78x3.355%3.35%5.978%5.98%3-1.000000x-1.000000x1.720683x1.720683x1.72x2.338%2.34%4.022%4.02%4-1.000000x-1.000000x1.707718x1.707718x1.71x3.458%3.46%5.905%5.91%5-1.000000x-1.000000x1.692229x1.692229x1.69x2.857%2.86%4.836%4.84%6-1.000000x-1.000000x1.684272x1.684272x1.68x1.637%1.64%2.757%2.76%7-1.000000x-1.000000x1.669500x1.669500x1.67x2.031%2.03%3.391%3.39%-1.000000x-1.000000x1.660799x1.660799x1.66x2.196%2.20%3.647%3.65%8-1.000000x-1.000000x1.659024x1.659024x1.66x2.280%2.28%3.783%3.78%9-1.000000x-1.000000x1.621815x1.621815x1.62x3.429%3.43%5.561%5.56%10-1.000000x-1.000000x1.611479x1.611479x1.61x2.711%2.71%4.369%4.37%11-1.000000x-1.000000x1.597848x1.597848x1.60x2.216%2.22%3.541%3.54%-1.000000x-1.000000x1.589934x1.589934x1.59x2.251%2.25%3.579%3.58%-1.000000x-1.000000x1.582232x1.582232x1.58x2.447%2.45%3.871%3.87%-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-1.000000x1.328197x1.328197x1.33x0.732%0.73%0.972%0.97%-1.000000x-1.000000x1.310218x1.310218x1.31x3.011%3.01%3.945%3.95%33-1.000000x-1.000000x1.308108x1.308108x1.31x4.045%4.05%5.292%5.29%34-1.000000x-1.000000x1.303834x1.303834x1.30x4.384%4.38%5.716%5.72%35-1.000000x-1.000000x1.303196x1.303196x1.30x4.332%4.33%5.645%5.65%36-1.000000x-1.000000x1.300117x1.300117x1.30x10.922%10.9%14.199%14.2%37-1.000000x-1.000000x1.285200x1.285200x1.29x2.428%2.43%3.121%3.12%38-1.000000x-1.000000x1.265486x1.265486x1.27x1.515%1.51%1.917%1.92%39-1.000000x-1.000000x1.262281x1.262281x1.26x3.021%3.02%3.814%3.81%40-1.000000x-1.000000x1.245683x1.245683x1.25x9.673%9.67%12.050%12.1%41-1.000000x-1.000000x1.238186x1.238186x1.24x4.026%4.03%4.985%4.99%42-1.000000x-1.000000x1.228890x1.228890x1.23x5.961%5.96%7.326%7.33%43-1.000000x-1.000000x1.221037x1.221037x1.22x6.643%6.64%8.112%8.11%44-1.000000x-1.000000x1.202385x1.202385x1.20x1.526%1.53%1.834%1.83%45-1.000000x-1.000000x1.198236x1.198236x1.20x2.119%2.12%2.539%2.54%46-1.000000x-1.000000x1.181998x1.181998x1.18x2.766%2.77%3.269%3.27%47-1.000000x-1.000000x1.129665x1.129665x1.13x5.378%5.38%6.075%6.08%48-1.000000x-1.000000x1.098720x1.098720x1.10x7.194%7.19%7.905%7.90%49-1.000000x-1.000000x1.046557x1.046557x1.05x1.291%1.29%1.351%1.35%50
F percentage of females in category
M percentage of males in category
# rank of county subdivision out of 50 by male-to-female sex ratio

Definitions

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

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

The coarse levels of educational attainment are as follows:

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

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

More Topics to Explore

Demographics

Income

Education

More Maps to Explore

State:
Ohio
County:
Clermont
Metro Area:
Cincinnati Area
ZIP Codes:
45102, 45106, 45153, 45157
Unified School Districts:
Bethel-Tate, Felicity-Franklin, New Richmond, West Clermont
Congressional District:
OH-2
State Senate District:
OH-14
State House District:
OH-66
Neighboring Townships:
Batavia, Ohio, Pierce, Tate, Washington
Nearby Townships:
Anderson, Clark, Franklin, Lewis, Pike, Scott, Union, Williamsburg