Educational Attainment in the Ohio Township, Franklin County, Kansas (Township)

Educational Attainment#1

Highest level of education among people aged 25 years and older.
Scope: population of Franklin County and the Ohio Township
Ohio Township
Franklin County
0%20%40%60%CountHigher Degree1H.S. Diploma2No H.S. Diploma227.852998%30.060735%27.852998%27.9%14465.570600%61.813786%65.570600%65.6%3396.576402%8.125479%6.576402%6.6%34
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 Franklin County at large.
Scope: population of Franklin County and the Ohio Township
-10%0%+10%%ref.Higher Degree1H.S. Diploma2No H.S. Diploma2-7.344254%-7.344254%-7.3%27.853%27.9%30.061%30.1%6.077630%6.077630%+6.1%65.571%65.6%61.814%61.8%-19.064436%-19.064436%-19.1%6.576%6.58%8.125%8.13%
% percentage with given level in the Ohio Township
ref. percentage with given level in Franklin 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 Franklin County and the Ohio Township
Ohio Township
Franklin County
0%10%20%30%CountDoctorate1Professional1Master's1Bachelor's1Associate's1Some CollegeHigh School2Some H.S.3Less than H.S.3None0.193424%0.719382%0.193424%0.2%10.967118%0.813727%0.967118%1.0%55.802708%5.194882%5.802708%5.8%3011.218569%13.190636%11.218569%11.2%589.671180%10.142107%9.671180%9.7%5030.947776%25.756236%30.947776%30.9%16034.622824%36.057551%34.622824%34.6%1795.609284%5.796332%5.609284%5.6%290.967118%1.798455%0.967118%1.0%50.000000%0.000000%0.0%0.530692%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 Franklin County at large.
Scope: population of Franklin County and the Ohio Township
-100%0%+100%%ref.Doctorate1Professional1Master's1Bachelor's1Associate's1Some CollegeHigh School2Some H.S.3Less than H.S.3None-73.112534%-73.112534%-73.1%0.193%0.19%0.719%0.72%18.850391%18.850391%+18.9%0.967%0.97%0.814%0.81%11.700481%11.700481%+11.7%5.803%5.80%5.195%5.19%-14.950511%-14.950511%-15.0%11.219%11.2%13.191%13.2%-4.643291%-4.643291%-4.6%9.671%9.67%10.142%10.1%20.156439%20.156439%+20.2%30.948%30.9%25.756%25.8%-3.978991%-3.978991%-4.0%34.623%34.6%36.058%36.1%-3.227006%-3.227006%-3.2%5.609%5.61%5.796%5.80%-46.225069%-46.225069%-46.2%0.967%0.97%1.798%1.80%-100.000000%-100.000000%-100.0%0.000%0%0.531%0.53%
% percentage with given level in the Ohio Township
ref. percentage with given level in Franklin 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 Franklin County and the Ohio Township
More Females More Males
Franklin County
Ohio Township
30%20%10%0%10%FMHigher Degree1H.S. Diploma2No H.S. Diploma2-36.639676%-25.682554%-36.639676%37%32.389%32.4%23.704%23.7%13.897474%11.085586%13.897474%14%61.134%61.1%69.630%69.6%2.916667%3.829946%2.916667%3%6.478%6.48%6.667%6.67%
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 Franklin County and the Ohio Township
More Females More Males
Franklin County
Ohio Township
1k%0k%1k%FMDoctorate1Professional1Master's1Bachelor's1Associate's1Some CollegeHigh School2Some H.S.3Less than H.S.3-1,000.000000%-1,000.000000%> 1000%61.102011%0.405%0.40%0.000%0%-1,000.000000%-1,000.000000%> 1000%218.231643%2.024%2.02%0.000%0%-23.055776%151.574074%151.574074%0k%3.239%3.24%8.148%8.15%-278.386795%-32.625098%-278.386795%0k%18.219%18.2%4.815%4.81%-38.712972%26.331570%26.331570%0k%8.502%8.50%10.741%10.7%-3.979461%-9.794177%-3.979461%0k%31.579%31.6%30.370%30.4%32.836124%28.026444%32.836124%0k%29.555%29.6%39.259%39.3%-34.537527%-34.537527%0k%9.242661%6.478%6.48%4.815%4.81%-6.151242%1,000.000000%1,000.000000%> 1000%0.000%0%1.852%1.85%
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 Franklin County and the Ohio Township
Ohio Township
Franklin County
0%5%10%15%20%25%B.X.Total65+45-6435-4425-340.000000%0.000000%0.0%12.301193%0843.255814%11.339625%3.255814%3.3%721517.582418%17.692308%17.582418%17.6%169127.559055%14.482527%27.559055%27.6%35127
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 Franklin County at large.
Scope: population of Franklin County and the Ohio Township
100%50%0%50%%ref.65+45-6435-4425-34-100.000000%-100.000000%100.0%0.000%0%12.301%12.3%-71.288170%-71.288170%71.3%3.256%3.26%11.340%11.3%-0.621118%-0.621118%0.6%17.582%17.6%17.692%17.7%90.291759%90.291759%90.3%27.559%27.6%14.483%14.5%
% percentage in the Ohio Township with a Bachelor's degree
ref percentage in Franklin 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 Franklin County and the Ohio Township
More Females More Males
Franklin County
Ohio Township
1,000%500%0%FM45-6435-4425-34-313.580247%-4.144594%-313.580247%313.6%6.173%6.17%1.493%1.49%-1,000.000000%-220.215649%-1,000.000000%> 1000%32.000%32.0%0.000%0%-41.676505%-115.183355%-41.676505%41.7%31.169%31.2%22.000%22.0%
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 Franklin County and the Ohio Township
Ohio Township
Franklin County
$0k$20k$40k$60kCount%Graduate Degree1Bachelor's DegreeSome CollegeH.S. Diploma2No H.S. Diploma2Total$65,000.000000$58,025.000000$65,000.000000$65.0k366.963%6.96%$34,167.000000$39,418.000000$34,167.000000$34.2k5811.219%11.2%$40,000.000000$34,514.000000$40,000.000000$40.0k21040.619%40.6%$30,859.000000$31,250.000000$30,859.000000$30.9k17934.623%34.6%$21,458.000000$17,374.000000$21,458.000000$21.5k346.576%6.58%$35,000.000000$35,245.000000$35,000.000000$35.0k517100.000%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 Franklin County and the Ohio Township
Female Male
Franklin County
Ohio Township
Shaded bar tips show excess over facing bar.
$50k$0k$50kFMGraduate Degree1Some CollegeNo H.S. Diploma2Total$-56,750.000000$-16,500.000000$-49,443.000000$-73,250.000000$73.3k$56,750.000000$49,443.000000$14,353.000000$56,750.000000$56.8k1422$-32,031.000000$-28,438.000000$-32,031.000000$32.0k$32,031.000000$8,819.000000$28,438.000000$13,854.000000$40,850.000000$40.9k99111$-2,499.000000$-16,279.000000$-2,499.000000$2.5k$2,499.000000$27,918.000000$16,279.000000$9,346.000000$30,417.000000$30.4k1618$-27,708.000000$-28,625.000000$-27,708.000000$27.7k$27,708.000000$12,642.000000$28,625.000000$12,279.000000$40,350.000000$40.4k247270
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 Franklin County and the Ohio Township
Ohio Township
Franklin County
0%20%40%60%80%CountBachelor's Degree1Some College2H.S. Diploma3No H.S. Diploma384.810127%85.964912%84.810127%84.8%6781.914894%77.688634%81.914894%81.9%15482.733813%77.108716%82.733813%82.7%11574.074074%49.480969%74.074074%74.1%20
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 Franklin County and the Ohio Township
Female Male
Franklin County
Ohio Township
Shaded bar tips show excess over facing bar.
6%4%2%0%2%4%6%MFWhite1-5.303030%-1.201035%-7.170643%-0.675134%-6.504065%6.5%5.303030%7.170643%5.303030%5.3%1416
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 Franklin County and the Ohio Township
Female Male
Franklin County
Ohio Township
Shaded bar tips show excess over facing bar.
20%10%0%10%MFWhite1-13.257576%-10.726164%-18.866701%-3.299761%-23.983740%24.0%13.257576%18.866701%13.257576%13.3%3559
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 Ottawa Area

There are 17 county subdivisions in the Ottawa Area. This section compares the Ohio Township to all of the county subdivisions in the Ottawa Area and to those entities that contain or substantially overlap with the Ohio Township.

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 Ohio Township, selected other county subdivisions in the Ottawa Area, and entities that contain the Ohio Township
0%5%10%15%20%Count#Appanoose TownshipAppanooseUnited States of AmericaUnited StatesPeoria TownshipPeoriaOttawa TownshipOttawaPomona TownshipPomonaMidwestOttawaKansasWest North CentralWilliamsburg TownshipWilliamsburgOttawa Metro AreaOttawa AreaFranklin CountyFranklinHomewood TownshipHomewoodRichmond TownshipRichmond954500Tract 954500Ohio TownshipCutler TownshipCutlerHarrison TownshipHarrisonPottawatomie TownshipPottawatomieFranklin TownshipFranklinGreenwood TownshipGreenwoodCentropolis TownshipCentropolisLincoln TownshipLincolnHayes TownshipHayes20.833333%20.833333%20.8%30113.020590%13.020590%13.0%27,818,38027.8M12.530120%12.530120%12.5%52211.610487%11.610487%11.6%62310.459184%10.459184%10.5%82410.244520%10.244520%10.2%4,641,8354.64M10.071134%10.071134%10.1%80759.691216%9.691216%9.7%182,049182k9.174633%9.174633%9.2%1,278,0511.28M8.388521%8.388521%8.4%3868.125479%8.125479%8.1%1,3788.125479%8.125479%8.1%1,3786.940063%6.940063%6.9%2276.866197%6.866197%6.9%3986.724351%6.724351%6.7%2726.576402%6.576402%6.6%3495.136986%5.136986%5.1%30105.078125%5.078125%5.1%13115.052265%5.052265%5.1%29124.767184%4.767184%4.8%86134.638219%4.638219%4.6%25144.160689%4.160689%4.2%29150.000000%0.000000%0.0%0160.000000%0.000000%0.0%017
Count number of people in category
# rank of county subdivision out of 17 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 Ohio Township, selected other county subdivisions in the Ottawa Area, and entities that contain the Ohio Township
0%10%20%30%40%Count#Lincoln TownshipLincolnHarrison TownshipHarrisonHayes TownshipHayesWilliamsburg TownshipWilliamsburgKansasUnited States of AmericaUnited StatesWest North CentralMidwest954500Tract 954500Ottawa TownshipOttawaCutler TownshipCutlerFranklin TownshipFranklinOttawaOttawa Metro AreaOttawa AreaFranklin CountyFranklinPottawatomie TownshipPottawatomieOhio TownshipPeoria TownshipPeoriaRichmond TownshipRichmondHomewood TownshipHomewoodCentropolis TownshipCentropolisAppanoose TownshipAppanooseGreenwood TownshipGreenwoodPomona TownshipPomona43.902439%43.902439%43.9%234138.671875%38.671875%38.7%99232.599119%32.599119%32.6%74332.450331%32.450331%32.5%147431.610465%31.610465%31.6%593,801594k30.315023%30.315023%30.3%64,767,78764.8M30.056536%30.056536%30.1%4,186,9564.19M28.952816%28.952816%29.0%13,118,64213.1M22.744129%22.744129%22.7%92022.284644%22.284644%22.3%119522.089041%22.089041%22.1%129621.119734%21.119734%21.1%381720.566579%20.566579%20.6%1,648819.918627%19.918627%19.9%3,37819.918627%19.918627%19.9%3,37819.860627%19.860627%19.9%114918.181818%18.181818%18.2%941016.867470%16.867470%16.9%701113.908451%13.908451%13.9%791210.094637%10.094637%10.1%32139.612626%9.612626%9.6%67147.638889%7.638889%7.6%11156.864564%6.864564%6.9%37165.484694%5.484694%5.5%4317
Count number of people in category
# rank of county subdivision out of 17 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 Ohio Township, selected other county subdivisions in the Ottawa Area, and entities that contain the Ohio Township
0%5%10%Count#Harrison TownshipHarrisonLincoln TownshipLincolnPottawatomie TownshipPottawatomieHayes TownshipHayesUnited States of AmericaUnited StatesKansasWest North CentralMidwest954500Tract 954500OttawaOttawa Metro AreaOttawa AreaFranklin CountyFranklinOhio TownshipCutler TownshipCutlerFranklin TownshipFranklinPomona TownshipPomonaCentropolis TownshipCentropolisRichmond TownshipRichmondWilliamsburg TownshipWilliamsburgGreenwood TownshipGreenwoodPeoria TownshipPeoriaOttawa TownshipOttawaHomewood TownshipHomewoodAppanoose TownshipAppanoose11.328125%11.328125%11.3%2917.879925%7.879925%7.9%4226.271777%6.271777%6.3%3635.286344%5.286344%5.3%1243.336158%3.336158%3.3%7,127,6737.13M3.019438%3.019438%3.0%56,72056.7k2.978981%2.978981%3.0%414,980415k2.893416%2.893416%2.9%1,311,0191.31M1.804697%1.804697%1.8%731.584924%1.584924%1.6%12751.533109%1.533109%1.5%2601.533109%1.533109%1.5%2601.160542%1.160542%1.2%660.342466%0.342466%0.3%270.332594%0.332594%0.3%680.000000%0.000000%0.0%090.000000%0.000000%0.0%0100.000000%0.000000%0.0%0110.000000%0.000000%0.0%0120.000000%0.000000%0.0%0130.000000%0.000000%0.0%0140.000000%0.000000%0.0%0150.000000%0.000000%0.0%0160.000000%0.000000%0.0%017
Count number of people in category
# rank of county subdivision out of 17 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 Ohio Township, selected other county subdivisions in the Ottawa Area, and entities that contain the Ohio Township
Female
Male
10x5x0x5x10xFM#GreenwoodHomewoodHarrisonCutlerOttawaFranklinWilliamsburgWest North CentralKansasMidwestUnited StatesOttawaOttawa AreaFranklinOhio TownshipTract 954500RichmondAppanoosePomonaPottawatomieCentropolisPeoria-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%8.591%8.59%1-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%11.702%11.7%2-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%8.553%8.55%3-1.000000x-1.000000x3.047834x3.047834x3.05x2.606%2.61%7.942%7.94%4-1.000000x-1.000000x2.863799x2.863799x2.86x5.882%5.88%16.846%16.8%5-1.000000x-1.000000x2.132010x2.132010x2.13x3.060%3.06%6.524%6.52%6-1.000000x-1.000000x1.678946x1.678946x1.68x5.978%5.98%10.037%10.0%7-1.000000x-1.000000x1.137506x1.137506x1.14x8.598%8.60%9.780%9.78%-1.000000x-1.000000x1.136078x1.136078x1.14x9.088%9.09%10.324%10.3%-1.000000x-1.000000x1.127915x1.127915x1.13x9.647%9.65%10.881%10.9%-1.000000x-1.000000x1.109070x1.109070x1.11x12.369%12.4%13.719%13.7%-1.000000x-1.000000x1.080037x1.080037x1.08x9.713%9.71%10.491%10.5%8-1.000000x-1.000000x1.038299x1.038299x1.04x7.979%7.98%8.284%8.28%-1.000000x-1.000000x1.038299x1.038299x1.04x7.979%7.98%8.284%8.28%-1.000000x-1.000000x1.029167x1.029167x1.03x6.478%6.48%6.667%6.67%9-1.219194x-1.219194x1.22x1.000000x1.000000x7.391%7.39%6.062%6.06%-1.518148x-1.518148x1.52x1.000000x1.000000x8.143%8.14%5.364%5.36%10-1.630435x-1.630435x1.63x1.000000x1.000000x26.087%26.1%16.000%16.0%11-2.450070x-2.450070x2.45x1.000000x1.000000x14.713%14.7%6.005%6.01%12-2.459627x-2.459627x2.46x1.000000x1.000000x6.832%6.83%2.778%2.78%13-10.000000x-10.000000x> 10.0x1.000000x1.000000x7.436%7.44%0.000%0%14-10.000000x-10.000000x> 10.0x1.000000x1.000000x23.853%23.9%0.000%0%15
F percentage of females in category
M percentage of males in category
# rank of county subdivision out of 15 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 Ohio Township, selected other county subdivisions in the Ottawa Area, and entities that contain the Ohio Township
Female
Male
10x5x0x5x10xFM#LincolnHarrisonHayesOttawa AreaFranklinTract 954500MidwestOttawaWest North CentralKansasUnited StatesPottawatomieFranklinOhio TownshipCutler-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%16.471%16.5%1-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%19.079%19.1%2-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%10.526%10.5%3-1.000000x-1.000000x2.265727x2.265727x2.27x0.953%0.95%2.160%2.16%-1.000000x-1.000000x2.265727x2.265727x2.27x0.953%0.95%2.160%2.16%-1.000000x-1.000000x1.796110x1.796110x1.80x1.290%1.29%2.316%2.32%-1.000000x-1.000000x1.589934x1.589934x1.59x2.251%2.25%3.579%3.58%-1.000000x-1.000000x1.584551x1.584551x1.58x1.249%1.25%1.979%1.98%4-1.000000x-1.000000x1.572017x1.572017x1.57x2.329%2.33%3.662%3.66%-1.000000x-1.000000x1.571500x1.571500x1.57x2.361%2.36%3.710%3.71%-1.000000x-1.000000x1.526215x1.526215x1.53x2.660%2.66%4.060%4.06%-1.000000x-1.000000x1.277778x1.277778x1.28x5.590%5.59%7.143%7.14%5-1.943169x-1.943169x1.94x1.000000x1.000000x0.437%0.44%0.225%0.22%6-10.000000x-10.000000x> 10.0x1.000000x1.000000x2.429%2.43%0.000%0%7-10.000000x-10.000000x> 10.0x1.000000x1.000000x0.651%0.65%0.000%0%8
F percentage of females in category
M percentage of males in category
# rank of county subdivision out of 8 by male-to-female sex ratio

Educational Attainment by County Subdivision in Kansas

There are 1,531 county subdivisions in Kansas. This section compares the Ohio Township to the 50 most populous county subdivisions in Kansas and to those entities that contain or substantially overlap with the Ohio Township. The least populous of the compared county subdivisions has a population of 7,732.

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 Ohio Township, selected other county subdivisions in Kansas, and entities that contain the Ohio Township
0%10%20%30%Count#LiberalDodge CityGarden CityKansas CityGreat BendCoffeyvilleArkansas CityParsonsHutchinsonEmporiaUnited States of AmericaUnited StatesWichitaChanutePittsburgSalinaTopekaNewtonFort ScottLansingRiverside TownshipRiversideIndependenceMidwestJunction CityAugustaOttawaWinfieldKansasWellingtonWest North CentralLeavenworthSalem TownshipSalemKechi TownshipKechiEl DoradoOttawa Metro AreaOttawa AreaFranklin CountyFranklinAtchison954500Tract 954500Ohio TownshipOlatheMerriamHaysShawneeGardnerFairmount TownshipFairmountMcPhersonLawrenceTecumseh TownshipTecumsehLenexaManhattanBruno TownshipBrunoMissionRockford TownshipRockfordOverland ParkMission TownshipMissionMadison TownshipMadisonSoldier TownshipSoldierPrairie VillagePrairie VlgLeawood34.641303%34.641303%34.6%4,061132.097762%32.097762%32.1%5,135228.082803%28.082803%28.1%4,409322.659362%22.659362%22.7%21,21821.2k415.641026%15.641026%15.6%1,586515.171442%15.171442%15.2%969614.949801%14.949801%14.9%1,087714.551455%14.551455%14.6%970813.823602%13.823602%13.8%3,923913.704420%13.704420%13.7%1,9131013.020590%13.020590%13.0%27,818,38027.8M12.568464%12.568464%12.6%31,23131.2k1111.381977%11.381977%11.4%6771211.295872%11.295872%11.3%1,1821311.048593%11.048593%11.0%3,4561411.032803%11.032803%11.0%9,3771510.761381%10.761381%10.8%1,3711610.586383%10.586383%10.6%5381710.514597%10.514597%10.5%8501810.505186%10.505186%10.5%9421910.428082%10.428082%10.4%6092010.244520%10.244520%10.2%4,641,8354.64M10.182349%10.182349%10.2%1,3962110.146444%10.146444%10.1%5822210.071134%10.071134%10.1%807239.929435%9.929435%9.9%788249.691216%9.691216%9.7%182,049182k9.444135%9.444135%9.4%508259.174633%9.174633%9.2%1,278,0511.28M8.617355%8.617355%8.6%2,005268.603845%8.603845%8.6%546278.502773%8.502773%8.5%506288.221457%8.221457%8.2%692298.125479%8.125479%8.1%1,3788.125479%8.125479%8.1%1,3787.664294%7.664294%7.7%463306.724351%6.724351%6.7%2726.576402%6.576402%6.6%346.424130%6.424130%6.4%5,331316.386839%6.386839%6.4%528326.015657%6.015657%6.0%730335.113489%5.113489%5.1%2,174345.078221%5.078221%5.1%620354.979317%4.979317%5.0%325364.929499%4.929499%4.9%444374.814682%4.814682%4.8%2,411384.468530%4.468530%4.5%235394.370740%4.370740%4.4%1,526404.012073%4.012073%4.0%1,090413.841537%3.841537%3.8%352423.518712%3.518712%3.5%236433.398651%3.398651%3.4%529443.377424%3.377424%3.4%4,282452.942916%2.942916%2.9%199462.354874%2.354874%2.4%86472.351807%2.351807%2.4%244481.096310%1.096310%1.1%172490.675882%0.675882%0.7%15550
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 Ohio Township, selected other county subdivisions in Kansas, and entities that contain the Ohio Township
0%20%40%60%Count#LeawoodPrairie VillagePrairie VlgOverland ParkLenexaLawrenceMissionManhattanMission TownshipMissionOlatheShawneeBruno TownshipBrunoRockford TownshipRockfordFairmount TownshipFairmountHaysMerriamGardnerPittsburgSoldier TownshipSoldierKansasLeavenworthUnited States of AmericaUnited StatesWest North CentralTecumseh TownshipTecumsehMcPhersonMidwestWichitaLansingEmporiaKechi TownshipKechiTopekaNewtonAtchisonSalinaAugusta954500Tract 954500El DoradoWinfieldFort ScottJunction CityIndependenceOttawaOttawa Metro AreaOttawa AreaFranklin CountyFranklinRiverside TownshipRiversideParsonsGarden CityWellingtonOhio TownshipHutchinsonGreat BendMadison TownshipMadisonDodge CityArkansas CityKansas CityChanuteCoffeyvilleSalem TownshipSalemLiberal74.085379%74.085379%74.1%16,99017.0k170.080948%70.080948%70.1%10,99511.0k258.823344%58.823344%58.8%74,57874.6k355.353153%55.353153%55.4%19,32619.3k453.552600%53.552600%53.6%26,81726.8k552.273744%52.273744%52.3%3,506652.149588%52.149588%52.1%14,16814.2k749.556344%49.556344%49.6%3,351846.512581%46.512581%46.5%38,59838.6k946.174291%46.174291%46.2%19,63119.6k1043.599258%43.599258%43.6%3,9951141.336332%41.336332%41.3%6,4341237.521066%37.521066%37.5%2,4491337.354759%37.354759%37.4%4,5331434.135720%34.135720%34.1%2,8221533.729216%33.729216%33.7%4,1181633.581804%33.581804%33.6%3,5141732.771084%32.771084%32.8%3,4001831.610465%31.610465%31.6%593,801594k31.370611%31.370611%31.4%7,2991930.315023%30.315023%30.3%64,767,78764.8M30.056536%30.056536%30.1%4,186,9564.19M29.549344%29.549344%29.5%1,5542029.121794%29.121794%29.1%2,6232128.952816%28.952816%29.0%13,118,64213.1M28.877567%28.877567%28.9%71,75771.8k2228.871846%28.871846%28.9%2,3342327.380185%27.380185%27.4%3,8222427.188708%27.188708%27.2%1,6182527.007248%27.007248%27.0%22,95423.0k2624.513344%24.513344%24.5%3,1232723.671578%23.671578%23.7%1,4302823.516624%23.516624%23.5%7,3562922.960251%22.960251%23.0%1,3173022.744129%22.744129%22.7%92021.527860%21.527860%21.5%1,8123121.509577%21.509577%21.5%1,7073221.507281%21.507281%21.5%1,0933321.356674%21.356674%21.4%2,9283420.856164%20.856164%20.9%1,2183520.566579%20.566579%20.6%1,6483619.918627%19.918627%19.9%3,37819.918627%19.918627%19.9%3,37819.348723%19.348723%19.3%1,7353718.871887%18.871887%18.9%1,2583818.611465%18.611465%18.6%2,9223918.293363%18.293363%18.3%9844018.181818%18.181818%18.2%9418.171888%18.171888%18.2%5,1574116.982249%16.982249%17.0%1,7224216.730559%16.730559%16.7%6114316.327041%16.327041%16.3%2,6124416.187595%16.187595%16.2%1,1774516.167409%16.167409%16.2%15,13915.1k4616.055817%16.055817%16.1%9554714.044152%14.044152%14.0%8974813.063347%13.063347%13.1%8294911.362279%11.362279%11.4%1,33250
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 Ohio Township, selected other county subdivisions in Kansas, and entities that contain the Ohio Township
0%5%10%Count#LeawoodManhattanPrairie VillagePrairie VlgLawrenceMission TownshipMissionOverland ParkLenexaShawneeHaysMissionPittsburgBruno TownshipBrunoUnited States of AmericaUnited StatesTopekaParsonsKansasAtchisonWest North CentralMidwestFairmount TownshipFairmountOlatheSalinaFort ScottWichitaEmporiaMerriamWellingtonKechi TownshipKechiSoldier TownshipSoldierMcPhersonLansingWinfield954500Tract 954500Tecumseh TownshipTecumsehGreat BendNewtonRockford TownshipRockfordJunction CityOttawaIndependenceOttawa Metro AreaOttawa AreaFranklin CountyFranklinLeavenworthChanuteKansas CityGarden CityDodge CityOhio TownshipHutchinsonMadison TownshipMadisonRiverside TownshipRiversideGardnerEl DoradoLiberalArkansas CitySalem TownshipSalemCoffeyvilleAugusta14.267649%14.267649%14.3%3,272110.228946%10.228946%10.2%2,779210.198228%10.198228%10.2%1,60039.509545%9.509545%9.5%4,76247.068915%7.068915%7.1%47855.940071%5.940071%5.9%7,53165.358882%5.358882%5.4%1,87173.958603%3.958603%4.0%1,68383.765966%3.765966%3.8%45793.503802%3.503802%3.5%235103.373471%3.373471%3.4%353113.350431%3.350431%3.4%307123.336158%3.336158%3.3%7,127,6737.13M3.233245%3.233245%3.2%2,748133.090309%3.090309%3.1%206143.019438%3.019438%3.0%56,72056.7k3.012746%3.012746%3.0%182152.978981%2.978981%3.0%414,980415k2.893416%2.893416%2.9%1,311,0191.31M2.849701%2.849701%2.8%186162.830666%2.830666%2.8%2,349172.608696%2.608696%2.6%816182.597403%2.597403%2.6%132192.519246%2.519246%2.5%6,260202.399885%2.399885%2.4%335212.237813%2.237813%2.2%185222.212307%2.212307%2.2%119232.150899%2.150899%2.2%128242.053012%2.053012%2.1%213251.942933%1.942933%1.9%175261.830777%1.830777%1.8%148271.814516%1.814516%1.8%144281.804697%1.804697%1.8%731.768397%1.768397%1.8%93291.715976%1.715976%1.7%174301.711146%1.711146%1.7%218311.612592%1.612592%1.6%251321.611962%1.611962%1.6%221331.584924%1.584924%1.6%127341.575342%1.575342%1.6%92351.533109%1.533109%1.5%2601.533109%1.533109%1.5%2601.439807%1.439807%1.4%335361.429052%1.429052%1.4%85371.388310%1.388310%1.4%1,300381.375796%1.375796%1.4%216391.343918%1.343918%1.3%215401.160542%1.160542%1.2%61.018359%1.018359%1.0%289410.985761%0.985761%1.0%36420.970224%0.970224%1.0%87430.933737%0.933737%0.9%114440.796008%0.796008%0.8%67450.639768%0.639768%0.6%75460.577637%0.577637%0.6%42470.378191%0.378191%0.4%24480.266166%0.266166%0.3%17490.261506%0.261506%0.3%1550
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 Ohio Township, selected other county subdivisions in Kansas, and entities that contain the Ohio Township
Female
Male
2x0x2x4x6xFM#SoldierPrairie VlgLansingKechiSalemEl DoradoWinfieldCoffeyvillePittsburgHutchinsonGreat BendLawrenceGardnerIndependenceNewtonKansas CityChanuteFairmountWest North CentralKansasMidwestMissionTopekaDodge CityArkansas CityUnited StatesOlatheFort ScottOverland ParkOttawaLiberalEmporiaWichitaHaysOttawa AreaFranklinOhio TownshipLeavenworthParsonsBrunoGarden CityLenexaSalinaRiversideShawneeMerriamTract 954500TecumsehRockfordWellingtonAugustaManhattanJunction CityMadisonMcPhersonMissionAtchisonLeawood-1.000000x-1.000000x6.409381x6.409381x6.41x0.652%0.65%4.177%4.18%1-1.000000x-1.000000x2.955512x2.955512x2.96x0.582%0.58%1.720%1.72%2-1.000000x-1.000000x2.364703x2.364703x2.36x5.753%5.75%13.604%13.6%3-1.000000x-1.000000x1.701345x1.701345x1.70x6.355%6.36%10.813%10.8%4-1.000000x-1.000000x1.576560x1.576560x1.58x6.708%6.71%10.575%10.6%5-1.000000x-1.000000x1.411259x1.411259x1.41x6.927%6.93%9.775%9.78%6-1.000000x-1.000000x1.312419x1.312419x1.31x8.574%8.57%11.252%11.3%7-1.000000x-1.000000x1.305222x1.305222x1.31x13.337%13.3%17.408%17.4%8-1.000000x-1.000000x1.290383x1.290383x1.29x9.952%9.95%12.842%12.8%9-1.000000x-1.000000x1.285110x1.285110x1.29x12.110%12.1%15.563%15.6%10-1.000000x-1.000000x1.276094x1.276094x1.28x13.844%13.8%17.667%17.7%11-1.000000x-1.000000x1.232644x1.232644x1.23x4.323%4.32%5.329%5.33%12-1.000000x-1.000000x1.223779x1.223779x1.22x4.572%4.57%5.595%5.60%13-1.000000x-1.000000x1.221651x1.221651x1.22x9.421%9.42%11.510%11.5%14-1.000000x-1.000000x1.212719x1.212719x1.21x9.765%9.76%11.842%11.8%15-1.000000x-1.000000x1.189752x1.189752x1.19x20.748%20.7%24.685%24.7%16-1.000000x-1.000000x1.181812x1.181812x1.18x10.500%10.5%12.409%12.4%17-1.000000x-1.000000x1.141862x1.141862x1.14x4.642%4.64%5.301%5.30%18-1.000000x-1.000000x1.137506x1.137506x1.14x8.598%8.60%9.780%9.78%-1.000000x-1.000000x1.136078x1.136078x1.14x9.088%9.09%10.324%10.3%-1.000000x-1.000000x1.127915x1.127915x1.13x9.647%9.65%10.881%10.9%-1.000000x-1.000000x1.127040x1.127040x1.13x2.776%2.78%3.129%3.13%19-1.000000x-1.000000x1.125507x1.125507x1.13x10.423%10.4%11.732%11.7%20-1.000000x-1.000000x1.117097x1.117097x1.12x30.255%30.3%33.798%33.8%21-1.000000x-1.000000x1.113954x1.113954x1.11x14.168%14.2%15.782%15.8%22-1.000000x-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%23-1.000000x-1.000000x1.106385x1.106385x1.11x10.110%10.1%11.185%11.2%24-1.000000x-1.000000x1.095440x1.095440x1.10x3.232%3.23%3.540%3.54%25-1.000000x-1.000000x1.080037x1.080037x1.08x9.713%9.71%10.491%10.5%26-1.000000x-1.000000x1.076705x1.076705x1.08x33.351%33.4%35.909%35.9%27-1.000000x-1.000000x1.064594x1.064594x1.06x13.284%13.3%14.142%14.1%28-1.000000x-1.000000x1.059528x1.059528x1.06x12.215%12.2%12.942%12.9%29-1.000000x-1.000000x1.056897x1.056897x1.06x5.851%5.85%6.184%6.18%30-1.000000x-1.000000x1.038299x1.038299x1.04x7.979%7.98%8.284%8.28%-1.000000x-1.000000x1.038299x1.038299x1.04x7.979%7.98%8.284%8.28%-1.000000x-1.000000x1.029167x1.029167x1.03x6.478%6.48%6.667%6.67%-1.000000x-1.000000x1.023913x1.023913x1.02x8.507%8.51%8.710%8.71%31-1.000000x-1.000000x1.002176x1.002176x1.00x14.537%14.5%14.568%14.6%32-1.021682x-1.021682x1.02x1.000000x1.000000x3.880%3.88%3.798%3.80%33-1.028302x-1.028302x1.03x1.000000x1.000000x28.471%28.5%27.687%27.7%34-1.036696x-1.036696x1.04x1.000000x1.000000x4.445%4.45%4.288%4.29%35-1.067382x-1.067382x1.07x1.000000x1.000000x11.394%11.4%10.675%10.7%36-1.114198x-1.114198x1.11x1.000000x1.000000x11.058%11.1%9.925%9.92%37-1.120654x-1.120654x1.12x1.000000x1.000000x5.393%5.39%4.812%4.81%38-1.159410x-1.159410x1.16x1.000000x1.000000x6.844%6.84%5.903%5.90%39-1.219194x-1.219194x1.22x1.000000x1.000000x7.391%7.39%6.062%6.06%-1.248115x-1.248115x1.25x1.000000x1.000000x4.950%4.95%3.966%3.97%40-1.345784x-1.345784x1.35x1.000000x1.000000x3.874%3.87%2.879%2.88%41-1.374204x-1.374204x1.37x1.000000x1.000000x10.926%10.9%7.951%7.95%42-1.534357x-1.534357x1.53x1.000000x1.000000x12.019%12.0%7.833%7.83%43-1.571770x-1.571770x1.57x1.000000x1.000000x4.938%4.94%3.142%3.14%44-1.599843x-1.599843x1.60x1.000000x1.000000x12.475%12.5%7.798%7.80%45-1.716758x-1.716758x1.72x1.000000x1.000000x3.140%3.14%1.829%1.83%46-1.760420x-1.760420x1.76x1.000000x1.000000x6.213%6.21%3.529%3.53%47-1.814184x-1.814184x1.81x1.000000x1.000000x4.429%4.43%2.441%2.44%48-2.476800x-2.476800x2.48x1.000000x1.000000x10.476%10.5%4.229%4.23%49-2.686567x-2.686567x2.69x1.000000x1.000000x0.970%0.97%0.361%0.36%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 Ohio Township, selected other county subdivisions in Kansas, and entities that contain the Ohio Township
Female
Male
10x5x0x5x10xFM#AugustaChanuteWinfieldRockfordSoldierEmporiaArkansas CityHutchinsonMerriamMissionKechiGardnerEl DoradoFort ScottOttawa AreaFranklinLeawoodGarden CityMadisonParsonsPittsburgTract 954500WichitaSalinaJunction CityOverland ParkOlatheRiversideMcPhersonPrairie VlgMidwestOttawaWest North CentralKansasKansas CityLenexaUnited StatesTopekaLeavenworthIndependenceManhattanDodge CityShawneeWellingtonLawrenceAtchisonBrunoHaysCoffeyvilleNewtonLiberalGreat BendMissionTecumsehLansingFairmountOhio TownshipSalem-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%0.585%0.58%1-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.063%0.06%3.020%3.02%2-1.000000x-1.000000x7.288333x7.288333x7.29x0.434%0.43%3.162%3.16%3-1.000000x-1.000000x4.747377x4.747377x4.75x0.578%0.58%2.744%2.74%4-1.000000x-1.000000x4.007141x4.007141x4.01x0.838%0.84%3.357%3.36%5-1.000000x-1.000000x3.312765x3.312765x3.31x1.125%1.12%3.725%3.73%6-1.000000x-1.000000x2.998168x2.998168x3.00x0.293%0.29%0.880%0.88%7-1.000000x-1.000000x2.794101x2.794101x2.79x0.539%0.54%1.505%1.51%8-1.000000x-1.000000x2.782546x2.782546x2.78x1.199%1.20%3.337%3.34%9-1.000000x-1.000000x2.537230x2.537230x2.54x4.094%4.09%10.388%10.4%10-1.000000x-1.000000x2.366516x2.366516x2.37x1.297%1.30%3.069%3.07%11-1.000000x-1.000000x2.304595x2.304595x2.30x0.567%0.57%1.308%1.31%12-1.000000x-1.000000x2.295552x2.295552x2.30x0.501%0.50%1.150%1.15%13-1.000000x-1.000000x2.270873x2.270873x2.27x1.661%1.66%3.773%3.77%14-1.000000x-1.000000x2.265727x2.265727x2.27x0.953%0.95%2.160%2.16%-1.000000x-1.000000x2.265727x2.265727x2.27x0.953%0.95%2.160%2.16%-1.000000x-1.000000x2.087205x2.087205x2.09x9.355%9.35%19.525%19.5%15-1.000000x-1.000000x2.084839x2.084839x2.08x0.895%0.90%1.866%1.87%16-1.000000x-1.000000x2.009602x2.009602x2.01x0.614%0.61%1.235%1.23%17-1.000000x-1.000000x1.908318x1.908318x1.91x2.176%2.18%4.153%4.15%18-1.000000x-1.000000x1.879461x1.879461x1.88x2.394%2.39%4.500%4.50%19-1.000000x-1.000000x1.796110x1.796110x1.80x1.290%1.29%2.316%2.32%-1.000000x-1.000000x1.792728x1.792728x1.79x1.819%1.82%3.261%3.26%20-1.000000x-1.000000x1.784144x1.784144x1.78x1.895%1.89%3.381%3.38%21-1.000000x-1.000000x1.763230x1.763230x1.76x1.173%1.17%2.068%2.07%22-1.000000x-1.000000x1.732234x1.732234x1.73x4.415%4.41%7.647%7.65%23-1.000000x-1.000000x1.678153x1.678153x1.68x2.131%2.13%3.576%3.58%24-1.000000x-1.000000x1.637602x1.637602x1.64x0.740%0.74%1.212%1.21%25-1.000000x-1.000000x1.636870x1.636870x1.64x1.489%1.49%2.438%2.44%26-1.000000x-1.000000x1.609745x1.609745x1.61x7.994%7.99%12.868%12.9%27-1.000000x-1.000000x1.589934x1.589934x1.59x2.251%2.25%3.579%3.58%-1.000000x-1.000000x1.584551x1.584551x1.58x1.249%1.25%1.979%1.98%28-1.000000x-1.000000x1.572017x1.572017x1.57x2.329%2.33%3.662%3.66%-1.000000x-1.000000x1.571500x1.571500x1.57x2.361%2.36%3.710%3.71%-1.000000x-1.000000x1.570028x1.570028x1.57x1.087%1.09%1.707%1.71%29-1.000000x-1.000000x1.562944x1.562944x1.56x4.233%4.23%6.617%6.62%30-1.000000x-1.000000x1.526215x1.526215x1.53x2.660%2.66%4.060%4.06%-1.000000x-1.000000x1.481288x1.481288x1.48x2.641%2.64%3.912%3.91%31-1.000000x-1.000000x1.473714x1.473714x1.47x1.146%1.15%1.688%1.69%32-1.000000x-1.000000x1.336698x1.336698x1.34x1.355%1.36%1.812%1.81%33-1.000000x-1.000000x1.323486x1.323486x1.32x8.767%8.77%11.603%11.6%34-1.000000x-1.000000x1.281717x1.281717x1.28x1.172%1.17%1.502%1.50%35-1.000000x-1.000000x1.271087x1.271087x1.27x3.502%3.50%4.451%4.45%36-1.000000x-1.000000x1.255044x1.255044x1.26x1.963%1.96%2.464%2.46%37-1.000000x-1.000000x1.209380x1.209380x1.21x8.627%8.63%10.433%10.4%38-1.000000x-1.000000x1.195212x1.195212x1.20x2.769%2.77%3.310%3.31%39-1.000000x-1.000000x1.187864x1.187864x1.19x3.079%3.08%3.658%3.66%40-1.000000x-1.000000x1.095717x1.095717x1.10x3.595%3.60%3.939%3.94%41-1.000000x-1.000000x1.083777x1.083777x1.08x0.256%0.26%0.278%0.28%42-1.000000x-1.000000x1.083742x1.083742x1.08x1.645%1.65%1.783%1.78%43-1.000000x-1.000000x1.063736x1.063736x1.06x0.620%0.62%0.659%0.66%44-1.000000x-1.000000x1.052399x1.052399x1.05x1.675%1.67%1.762%1.76%45-1.121244x-1.121244x1.12x1.000000x1.000000x3.686%3.69%3.288%3.29%46-1.268292x-1.268292x1.27x1.000000x1.000000x1.972%1.97%1.555%1.56%47-1.421235x-1.421235x1.42x1.000000x1.000000x2.232%2.23%1.570%1.57%48-2.772437x-2.772437x2.77x1.000000x1.000000x4.235%4.23%1.527%1.53%49-10.000000x-10.000000x> 10.0x1.000000x1.000000x2.429%2.43%0.000%0%-10.000000x-10.000000x> 10.0x1.000000x1.000000x0.742%0.74%0.000%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 Midwest

There are 19,478 county subdivisions in the Midwest. This section compares the Ohio Township to the 50 most populous county subdivisions in the Midwest and to those entities that contain or substantially overlap with the Ohio 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 Ohio Township, selected other county subdivisions in the Midwest, and entities that contain the Ohio Township
0%10%20%30%Count#Aurora TownshipAuroraCenter TownshipCtrKansas CityClevelandWayne TownshipWayneDetroitMilwaukeeNorth TownshipNDaytonChicagoProviso TownshipProvisoRockford TownshipRockfordSt. LouisWarrenGrand RapidsToledoBlue TownshipCincinnatiAkronSt. PaulSterling HeightsSterling HtsUnited States of AmericaUnited StatesThornton TownshipThorntonWichitaKaw TownshipOmahaBloomingdale TownshipBloomingdaleColumbusMaine TownshipMaineTopekaMinneapolisSpringfield TownshipSpringfieldWorth TownshipWorthMidwestLawrence TownshipLawrenceSioux FallsKansasWest North CentralCapital TownshipCapitalWheeling TownshipWheelingPalatine TownshipPalatineOttawa Metro AreaOttawa AreaFranklin CountyFranklinSchaumburg TownshipSchaumburgLincolnWashington TownshipWashington954500Tract 954500Ohio TownshipOlatheFargoCedar RapidsYork TownshipMilton TownshipMiltonMadisonDowners Grove TownshipDowners GrvLisle TownshipLisleOverland ParkAnn Arbor33.464284%33.464284%33.5%29,81429.8k123.165532%23.165532%23.2%22,92622.9k222.659362%22.659362%22.7%21,21821.2k321.582420%21.582420%21.6%54,98155.0k421.037720%21.037720%21.0%18,48918.5k521.003600%21.003600%21.0%90,67890.7k617.485105%17.485105%17.5%63,80063.8k717.062713%17.062713%17.1%17,39117.4k816.928359%16.928359%16.9%14,88914.9k916.905373%16.905373%16.9%309,770310k1015.636222%15.636222%15.6%16,11016.1k1115.608074%15.608074%15.6%18,24118.2k1215.466266%15.466266%15.5%33,80433.8k1315.286174%15.286174%15.3%14,05914.1k1414.563179%14.563179%14.6%17,64317.6k1514.332972%14.332972%14.3%26,34326.3k1614.241047%14.241047%14.2%15,25815.3k1713.761583%13.761583%13.8%26,28626.3k1813.591726%13.591726%13.6%17,95118.0k1913.278342%13.278342%13.3%24,61324.6k2013.132171%13.132171%13.1%12,21212.2k2113.020590%13.020590%13.0%27,818,38027.8M12.974232%12.974232%13.0%14,37014.4k2212.568464%12.568464%12.6%31,23131.2k2312.455744%12.455744%12.5%15,16315.2k2412.198899%12.198899%12.2%35,05035.1k2512.171847%12.171847%12.2%9,3752611.376979%11.376979%11.4%60,83160.8k2711.132206%11.132206%11.1%10,96511.0k2811.032803%11.032803%11.0%9,3772910.958428%10.958428%11.0%29,34729.3k3010.767091%10.767091%10.8%11,14911.1k3110.678962%10.678962%10.7%11,17511.2k3210.244520%10.244520%10.2%4,641,8354.64M10.179618%10.179618%10.2%8,161339.702326%9.702326%9.7%9,123349.691216%9.691216%9.7%182,049182k9.174633%9.174633%9.2%1,278,0511.28M8.623103%8.623103%8.6%6,837358.424707%8.424707%8.4%9,343368.392669%8.392669%8.4%6,695378.125479%8.125479%8.1%1,3788.125479%8.125479%8.1%1,3787.739434%7.739434%7.7%7,226387.092309%7.092309%7.1%11,88611.9k396.804680%6.804680%6.8%6,403406.724351%6.724351%6.7%2726.576402%6.576402%6.6%346.424130%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 Ohio Township, selected other county subdivisions in the Midwest, and entities that contain the Ohio 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 RapidsKansasUnited States of AmericaUnited StatesSioux FallsWest North CentralMidwestWichitaSterling HeightsSterling HtsTopekaSpringfield TownshipSpringfieldProviso TownshipProvisoWorth TownshipWorthMilwaukee954500Tract 954500Rockford TownshipRockfordAkronCenter TownshipCtrOttawa Metro AreaOttawa AreaFranklin CountyFranklinNorth TownshipNThornton TownshipThorntonOhio TownshipToledoDaytonWarrenWayne TownshipWayneKansas CityClevelandAurora TownshipAuroraBlue TownshipDetroit72.810169%72.810169%72.8%47,43047.4k158.823344%58.823344%58.8%74,57874.6k257.681507%57.681507%57.7%45,19045.2k356.900171%56.900171%56.9%46,35646.4k456.337583%56.337583%56.3%85,63285.6k553.762123%53.762123%53.8%55,71155.7k650.610540%50.610540%50.6%47,62347.6k749.860853%49.860853%49.9%39,77539.8k849.728972%49.728972%49.7%42,93542.9k947.670489%47.670489%47.7%127,663128k1046.512581%46.512581%46.5%38,59838.6k1146.409378%46.409378%46.4%51,46851.5k1241.792515%41.792515%41.8%39,02039.0k1341.581304%41.581304%41.6%50,61950.6k1439.969357%39.969357%40.0%74,08874.1k1539.511462%39.511462%39.5%38,91838.9k1638.241175%38.241175%38.2%26,96527.0k1737.146608%37.146608%37.1%62,25462.3k1836.577273%36.577273%36.6%29,32429.3k1936.546320%36.546320%36.5%669,666670k2036.298510%36.298510%36.3%28,78028.8k2134.685843%34.685843%34.7%185,460185k2234.651487%34.651487%34.7%99,56199.6k2333.783048%33.783048%33.8%64,52964.5k2433.007421%33.007421%33.0%72,14372.1k2532.904381%32.904381%32.9%39,86339.9k2632.623147%32.623147%32.6%25,12725.1k2731.793440%31.793440%31.8%27,10227.1k2831.610465%31.610465%31.6%593,801594k30.315023%30.315023%30.3%64,767,78764.8M30.259813%30.259813%30.3%28,45328.5k2930.056536%30.056536%30.1%4,186,9564.19M28.952816%28.952816%29.0%13,118,64213.1M28.877567%28.877567%28.9%71,75771.8k3027.532180%27.532180%27.5%25,60325.6k3127.007248%27.007248%27.0%22,95423.0k3226.964567%26.964567%27.0%27,92127.9k3326.237989%26.237989%26.2%27,03327.0k3425.217641%25.217641%25.2%26,38926.4k3523.517740%23.517740%23.5%85,81285.8k3622.744129%22.744129%22.7%92021.592552%21.592552%21.6%25,23525.2k3720.213821%20.213821%20.2%26,69726.7k3820.139240%20.139240%20.1%19,93119.9k3919.918627%19.918627%19.9%3,37819.918627%19.918627%19.9%3,37819.650916%19.650916%19.7%20,02920.0k4018.971090%18.971090%19.0%21,01221.0k4118.181818%18.181818%18.2%9418.048021%18.048021%18.0%33,17133.2k4217.635555%17.635555%17.6%15,51115.5k4317.280259%17.280259%17.3%15,89315.9k4416.826535%16.826535%16.8%14,78814.8k4516.167409%16.167409%16.2%15,13915.1k4616.073076%16.073076%16.1%40,94640.9k4715.929601%15.929601%15.9%14,19214.2k4815.821208%15.821208%15.8%16,95117.0k4913.833543%13.833543%13.8%59,72359.7k50
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older with a bachelor's degree or higher..

Very Advanced Degrees by County Subdivision#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 Ohio Township, selected other county subdivisions in the Midwest, and entities that contain the Ohio 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 TownshipLawrenceKansasWest North CentralSpringfield TownshipSpringfieldCedar RapidsMidwestSioux FallsOlatheCenter TownshipCtrSchaumburg TownshipSchaumburgWichitaProviso TownshipProvisoAkronBloomingdale TownshipBloomingdaleRockford TownshipRockfordMilwaukeeWorth TownshipWorthCleveland954500Tract 954500ToledoNorth TownshipNOttawa Metro AreaOttawa AreaFranklin CountyFranklinSterling HeightsSterling HtsKansas CityDetroitDaytonWayne TownshipWayneOhio TownshipWarrenBlue TownshipAurora TownshipAuroraThornton TownshipThornton17.877867%17.877867%17.9%11,64611.6k19.171173%9.171173%9.2%13,94013.9k27.658384%7.658384%7.7%7,93637.306290%7.306290%7.3%6,87546.241155%6.241155%6.2%16,71416.7k56.197734%6.197734%6.2%5,35165.940071%5.940071%5.9%7,53175.933545%5.933545%5.9%4,83485.920847%5.920847%5.9%10,97511.0k95.896414%5.896414%5.9%7,178105.800061%5.800061%5.8%4,544114.880448%4.880448%4.9%10,66710.7k124.729595%4.729595%4.7%9,034134.568292%4.568292%4.6%7,656144.485379%4.485379%4.5%82,18982.2k154.336789%4.336789%4.3%3,058164.233985%4.233985%4.2%3,357174.059919%4.059919%4.1%11,66511.7k184.030539%4.030539%4.0%3,970193.487439%3.487439%3.5%2,782203.407574%3.407574%3.4%3,779213.357865%3.357865%3.4%17,95418.0k223.336158%3.336158%3.3%7,127,6737.13M3.233245%3.233245%3.2%2,748233.174629%3.174629%3.2%3,846243.083448%3.083448%3.1%2,472253.019438%3.019438%3.0%56,72056.7k2.978981%2.978981%3.0%414,980415k2.911721%2.911721%2.9%3,015262.905776%2.905776%2.9%2,477272.893416%2.893416%2.9%1,311,0191.31M2.841677%2.841677%2.8%2,672282.830666%2.830666%2.8%2,349292.602914%2.602914%2.6%2,576302.551250%2.551250%2.6%2,382312.519246%2.519246%2.5%6,260322.213918%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%4,911391.804697%1.804697%1.8%731.642065%1.642065%1.6%3,018401.575684%1.575684%1.6%1,606411.533109%1.533109%1.5%2601.533109%1.533109%1.5%2601.439893%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%1,040461.160542%1.160542%1.2%61.047058%1.047058%1.0%963470.997751%0.997751%1.0%1,069480.936111%0.936111%0.9%834490.876686%0.876686%0.9%97150
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).

Under-Education Sex Ratio by County Subdivision#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 Ohio Township, selected other county subdivisions in the Midwest, and entities that contain the Ohio Township
Female
Male
1x0x1xFM#Cedar RapidsLincolnDetroitOmahaToledoThorntonKansas CityMadisonLawrenceFargoProvisoRockfordBlue TownshipWest North CentralKansasWayneMidwestTopekaMilwaukeeKaw TownshipDaytonSioux FallsUnited StatesOlatheWorthNOverland ParkAuroraWheelingGrand RapidsSchaumburgChicagoWichitaColumbusClevelandPalatineCapitalOttawa AreaFranklinWarrenOhio TownshipSpringfieldYork TownshipSt. LouisWashingtonBloomingdaleCtrCincinnatiAkronAnn ArborSt. PaulLisleMinneapolisSterling HtsDowners GrvMiltonMaineTract 954500-1.000000x-1.000000x1.243824x1.243824x1.24x5.354%5.35%6.660%6.66%1-1.000000x-1.000000x1.238529x1.238529x1.24x6.342%6.34%7.854%7.85%2-1.000000x-1.000000x1.237056x1.237056x1.24x18.951%19.0%23.443%23.4%3-1.000000x-1.000000x1.230289x1.230289x1.23x10.968%11.0%13.494%13.5%4-1.000000x-1.000000x1.227011x1.227011x1.23x12.945%12.9%15.884%15.9%5-1.000000x-1.000000x1.203250x1.203250x1.20x11.909%11.9%14.330%14.3%6-1.000000x-1.000000x1.189752x1.189752x1.19x20.748%20.7%24.685%24.7%7-1.000000x-1.000000x1.189278x1.189278x1.19x4.425%4.43%5.263%5.26%8-1.000000x-1.000000x1.181964x1.181964x1.18x9.406%9.41%11.117%11.1%9-1.000000x-1.000000x1.176963x1.176963x1.18x5.565%5.56%6.550%6.55%10-1.000000x-1.000000x1.174964x1.174964x1.17x14.460%14.5%16.990%17.0%11-1.000000x-1.000000x1.168755x1.168755x1.17x14.456%14.5%16.896%16.9%12-1.000000x-1.000000x1.161774x1.161774x1.16x13.244%13.2%15.387%15.4%13-1.000000x-1.000000x1.137506x1.137506x1.14x8.598%8.60%9.780%9.78%-1.000000x-1.000000x1.136078x1.136078x1.14x9.088%9.09%10.324%10.3%-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-1.000000x1.123984x1.123984x1.12x16.526%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-1.000000x1.099747x1.099747x1.10x10.199%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-1.000000x1.038299x1.038299x1.04x7.979%7.98%8.284%8.28%-1.000000x-1.000000x1.038299x1.038299x1.04x7.979%7.98%8.284%8.28%-1.000000x-1.000000x1.037373x1.037373x1.04x15.022%15.0%15.584%15.6%34-1.000000x-1.000000x1.029167x1.029167x1.03x6.478%6.48%6.667%6.67%-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%50-1.219194x-1.219194x1.22x1.000000x1.000000x7.391%7.39%6.062%6.06%
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 Ohio Township, selected other county subdivisions in the Midwest, and entities that contain the Ohio Township
Female
Male
10x5x0xFM#Ottawa AreaFranklinRockfordNDaytonSioux FallsCapitalLawrenceDowners GrvAkronLisleTract 954500WichitaYork TownshipMaineWarrenWheelingBlue TownshipSpringfieldOverland ParkMiltonGrand RapidsOlatheOmahaFargoWashingtonLincolnMidwestBloomingdaleWest North CentralKansasKansas CityAuroraUnited StatesAnn ArborTopekaSterling HtsPalatineSchaumburgColumbusMadisonKaw TownshipMilwaukeeCedar RapidsClevelandCincinnatiSt. PaulSt. LouisChicagoWayneCtrToledoMinneapolisWorthDetroitProvisoThorntonOhio Township-1.000000x-1.000000x2.265727x2.265727x2.27x0.953%0.95%2.160%2.16%-1.000000x-1.000000x2.265727x2.265727x2.27x0.953%0.95%2.160%2.16%-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-1.000000x1.796110x1.796110x1.80x1.290%1.29%2.316%2.32%-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-1.000000x1.669388x1.669388x1.67x3.061%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-1.000000x1.596978x1.596978x1.60x3.524%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-1.000000x1.572017x1.572017x1.57x2.329%2.33%3.662%3.66%-1.000000x-1.000000x1.571500x1.571500x1.57x2.361%2.36%3.710%3.71%-1.000000x-1.000000x1.570028x1.570028x1.57x1.087%1.09%1.707%1.71%26-1.000000x-1.000000x1.550495x1.550495x1.55x0.737%0.74%1.143%1.14%27-1.000000x-1.000000x1.526215x1.526215x1.53x2.660%2.66%4.060%4.06%-1.000000x-1.000000x1.522839x1.522839x1.52x14.269%14.3%21.730%21.7%28-1.000000x-1.000000x1.481288x1.481288x1.48x2.641%2.64%3.912%3.91%29-1.000000x-1.000000x1.476996x1.476996x1.48x1.170%1.17%1.728%1.73%30-1.000000x-1.000000x1.457167x1.457167x1.46x2.851%2.85%4.154%4.15%31-1.000000x-1.000000x1.436165x1.436165x1.44x2.115%2.11%3.037%3.04%32-1.000000x-1.000000x1.413654x1.413654x1.41x2.801%2.80%3.959%3.96%33-1.000000x-1.000000x1.387878x1.387878x1.39x7.705%7.70%10.693%10.7%34-1.000000x-1.000000x1.373250x1.373250x1.37x4.975%4.97%6.832%6.83%35-1.000000x-1.000000x1.368590x1.368590x1.37x1.742%1.74%2.385%2.38%36-1.000000x-1.000000x1.346658x1.346658x1.35x2.491%2.49%3.354%3.35%37-1.000000x-1.000000x1.286599x1.286599x1.29x1.699%1.70%2.186%2.19%38-1.000000x-1.000000x1.280610x1.280610x1.28x4.179%4.18%5.351%5.35%39-1.000000x-1.000000x1.274509x1.274509x1.27x5.228%5.23%6.663%6.66%40-1.000000x-1.000000x1.273345x1.273345x1.27x4.319%4.32%5.500%5.50%41-1.000000x-1.000000x1.238186x1.238186x1.24x4.026%4.03%4.985%4.99%42-1.000000x-1.000000x1.223931x1.223931x1.22x1.068%1.07%1.307%1.31%43-1.000000x-1.000000x1.213574x1.213574x1.21x2.357%2.36%2.860%2.86%44-1.000000x-1.000000x1.141406x1.141406x1.14x1.539%1.54%1.757%1.76%45-1.000000x-1.000000x1.124528x1.124528x1.12x5.872%5.87%6.603%6.60%46-1.000000x-1.000000x1.084697x1.084697x1.08x1.883%1.88%2.042%2.04%47-1.000000x-1.000000x1.046557x1.046557x1.05x1.291%1.29%1.351%1.35%48-1.000000x-1.000000x1.042857x1.042857x1.04x2.171%2.17%2.264%2.26%49-1.706858x-1.706858x1.71x1.000000x1.000000x1.072%1.07%0.628%0.63%50-10.000000x-10.000000x> 10.0x1.000000x1.000000x2.429%2.43%0.000%0%
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 Ohio Township to the 50 most populous county subdivisions in the United States and to those entities that contain or substantially overlap with the Ohio 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 Ohio Township, selected other county subdivisions in the United States, and entities that contain the Ohio Township
0%10%20%Count#San Antonio CentralSan Antonio CntrlBronxSan BernardinoLos AngelesSouthwest DallasSW DallasEl PasoAnaheim-Santa Ana-Garden GroveAnaheim-Santa An…FresnoHoustonMiamiDetroitNortheast DallasNE DallasEast San Gabriel ValleyE San Gabriel VlyFort WorthBrooklynLong Beach-LakewoodLong Bch-LakewoodQueensSan Fernando ValleySan Fernando VlyMilwaukeePhiladelphiaOntarioChicagoBaltimoreOceanside-EscondidoOceanside-Escond…Las VegasPhoenixBostonSacramentoOrlandoAustinDenverUnited States of AmericaUnited StatesManhattanSan DiegoTampaSan JoseSan FranciscoTucsonAlbuquerqueTownship 1:Charlotte1, CharlotteColumbusTulsaSalt Lake CitySalt Lk CityTown of HempsteadHempsteadMidwestNorthwest HarrisNW HarrisWashingtonKansasAtlantaWest North CentralSeattleNortheast TarrantNE TarrantOttawa Metro AreaOttawa AreaFranklin CountyFranklin954500Tract 954500Ohio TownshipPlanoSeattle East28.998944%28.998944%29.0%126,922127k128.837398%28.837398%28.8%261,022261k227.582802%27.582802%27.6%135,754136k324.837401%24.837401%24.8%434,160434k423.987048%23.987048%24.0%141,940142k523.756417%23.756417%23.8%81,30881.3k622.645542%22.645542%22.6%248,699249k722.107626%22.107626%22.1%92,47292.5k821.922900%21.922900%21.9%457,347457k921.818150%21.818150%21.8%149,688150k1021.003600%21.003600%21.0%90,67890.7k1120.783651%20.783651%20.8%207,494207k1220.461493%20.461493%20.5%128,038128k1320.041576%20.041576%20.0%106,726107k1420.017506%20.017506%20.0%351,046351k1519.402518%19.402518%19.4%73,10573.1k1619.344706%19.344706%19.3%315,505316k1719.344408%19.344408%19.3%244,983245k1817.485105%17.485105%17.5%63,80063.8k1917.390838%17.390838%17.4%180,039180k2017.129346%17.129346%17.1%71,39771.4k2116.905373%16.905373%16.9%309,770310k2216.548703%16.548703%16.5%69,83969.8k2315.999398%15.999398%16.0%70,21470.2k2415.906523%15.906523%15.9%198,651199k2514.952077%14.952077%15.0%308,569309k2614.325556%14.325556%14.3%63,64263.6k2713.900512%13.900512%13.9%103,047103k2813.679368%13.679368%13.7%53,75853.8k2913.668915%13.668915%13.7%78,23878.2k3013.638703%13.638703%13.6%63,86563.9k3113.020590%13.020590%13.0%27,818,38027.8M12.996284%12.996284%13.0%160,845161k3212.985760%12.985760%13.0%206,792207k3312.979618%12.979618%13.0%57,75857.8k3412.789590%12.789590%12.8%153,604154k3512.559735%12.559735%12.6%84,02484.0k3612.262851%12.262851%12.3%70,40970.4k3712.089143%12.089143%12.1%52,21752.2k3811.553484%11.553484%11.6%61,37861.4k3911.376979%11.376979%11.4%60,83160.8k4011.299086%11.299086%11.3%43,65343.7k4110.435356%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%46,51046.5k459.691216%9.691216%9.7%182,049182k9.538552%9.538552%9.5%37,37337.4k469.174633%9.174633%9.2%1,278,0511.28M8.833573%8.833573%8.8%66,22066.2k478.418271%8.418271%8.4%31,44331.4k488.125479%8.125479%8.1%1,3788.125479%8.125479%8.1%1,3786.724351%6.724351%6.7%2726.576402%6.576402%6.6%345.714681%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 Ohio Township, selected other county subdivisions in the United States, and entities that contain the Ohio 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 CityAlbuquerqueTampaTucsonKansasOceanside-EscondidoOceanside-Escond…TulsaQueensUnited States of AmericaUnited StatesHoustonWest North CentralBaltimoreLong Beach-LakewoodLong Bch-LakewoodMidwestPhoenixOrlandoAnaheim-Santa Ana-Garden GroveAnaheim-Santa An…SacramentoEast San Gabriel ValleyE San Gabriel VlyOntarioPhiladelphiaMiamiFort WorthSouthwest DallasSW DallasMilwaukee954500Tract 954500FresnoLas VegasEl PasoOttawa Metro AreaOttawa AreaFranklin CountyFranklinBronxOhio TownshipSan BernardinoSan Antonio CentralSan Antonio CntrlDetroit60.434640%60.434640%60.4%747,953748k157.691220%57.691220%57.7%238,638239k255.360186%55.360186%55.4%256,316256k354.793235%54.793235%54.8%366,564367k454.142756%54.142756%54.1%195,588196k549.985845%49.985845%50.0%600,334600k649.803731%49.803731%49.8%195,136195k749.626221%49.626221%49.6%372,018372k846.377869%46.377869%46.4%206,036206k945.718966%45.718966%45.7%214,085214k1044.843364%44.843364%44.8%256,674257k1141.989192%41.989192%42.0%223,068223k1238.767308%38.767308%38.8%202,458202k1338.701072%38.701072%38.7%616,296616k1438.547398%38.547398%38.5%143,978144k1536.877886%36.877886%36.9%173,478173k1636.546320%36.546320%36.5%669,666670k1734.685843%34.685843%34.7%185,460185k1834.593243%34.593243%34.6%604,693605k1934.081468%34.081468%34.1%597,685598k2033.231104%33.231104%33.2%420,848421k2133.191099%33.191099%33.2%331,364331k2233.118385%33.118385%33.1%204,048204k2332.636312%32.636312%32.6%140,967141k2432.512191%32.512191%32.5%144,676145k2532.087814%32.087814%32.1%184,237184k2631.610465%31.610465%31.6%593,801594k31.198303%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%627,520628k3030.056536%30.056536%30.1%4,186,9564.19M29.719611%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%112,142112k3428.412939%28.412939%28.4%312,038312k3528.231204%28.231204%28.2%209,283209k3627.276345%27.276345%27.3%170,682171k3726.758411%26.758411%26.8%111,532112k3826.349720%26.349720%26.3%272,786273k3926.011156%26.011156%26.0%178,455178k4024.665414%24.665414%24.7%131,349131k4123.764821%23.764821%23.8%140,625141k4223.517740%23.517740%23.5%85,81285.8k4322.744129%22.744129%22.7%92022.486319%22.486319%22.5%94,05694.1k4421.702666%21.702666%21.7%271,037271k4521.071885%21.071885%21.1%72,12072.1k4619.918627%19.918627%19.9%3,37819.918627%19.918627%19.9%3,37819.131504%19.131504%19.1%173,169173k4718.181818%18.181818%18.2%9416.375473%16.375473%16.4%80,59580.6k4814.929012%14.929012%14.9%65,34165.3k4913.833543%13.833543%13.8%59,72359.7k50
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older with a bachelor's degree or higher..

Very Advanced Degrees by County Subdivision#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 Ohio Township, selected other county subdivisions in the United States, and entities that contain the Ohio 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 StatesTulsaKansasPhoenixLong Beach-LakewoodLong Bch-LakewoodWest North CentralMidwestOrlandoFresnoAnaheim-Santa Ana-Garden GroveAnaheim-Santa An…QueensNorthwest HarrisNW HarrisNortheast TarrantNE TarrantEast San Gabriel ValleyE San Gabriel VlyOntarioFort WorthLas VegasMilwaukeeSan Bernardino954500Tract 954500San Antonio CentralSan Antonio CntrlEl PasoSouthwest DallasSW DallasBronxOttawa Metro AreaOttawa AreaFranklin CountyFranklinDetroitOhio Township12.461852%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%12,13312.1k313.019438%3.019438%3.0%56,72056.7k3.010825%3.010825%3.0%62,13562.1k323.009440%3.009440%3.0%11,33911.3k332.978981%2.978981%3.0%414,980415k2.893416%2.893416%2.9%1,311,0191.31M2.893233%2.893233%2.9%11,37011.4k342.828959%2.828959%2.8%11,83311.8k352.763004%2.763004%2.8%30,34430.3k362.756960%2.756960%2.8%44,96545.0k372.682967%2.682967%2.7%12,62112.6k382.630994%2.630994%2.6%9,827392.484535%2.484535%2.5%15,54715.5k402.324315%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%8,895451.804697%1.804697%1.8%731.792414%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%15,06415.1k491.533109%1.533109%1.5%2601.533109%1.533109%1.5%2601.318660%1.318660%1.3%5,693501.160542%1.160542%1.2%6
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 Ohio Township, selected other county subdivisions in the United States, and entities that contain the Ohio Township
Female
Male
1x0x1xFM#1, CharlotteDetroitBaltimoreTulsaSW DallasWest North CentralKansasMidwestFresnoMilwaukeeUnited StatesNE DallasHoustonHempsteadOrlandoPhiladelphiaOntarioSan BernardinoAustinAtlantaFort WorthPhoenixChicagoAlbuquerqueWashingtonSacramentoColumbusSalt Lk CityDenverNE TarrantTampaOceanside-EscondidoOceanside-Escond…NW HarrisOttawa AreaFranklinBronxOhio TownshipPlanoBrooklynSan Antonio CntrlSan Fernando VlyTucsonAnaheim-Santa Ana-Gdn GrvAnaheim-Santa An…Los AngelesLas VegasBostonE San Gabriel VlyQueensMiamiManhattanSeattleLong Bch-LakewoodSeattle EastSan JoseSan DiegoTract 954500San FranciscoEl Paso-1.000000x-1.000000x1.285784x1.285784x1.29x10.185%10.2%13.096%13.1%1-1.000000x-1.000000x1.237056x1.237056x1.24x18.951%19.0%23.443%23.4%2-1.000000x-1.000000x1.179669x1.179669x1.18x15.289%15.3%18.036%18.0%3-1.000000x-1.000000x1.177766x1.177766x1.18x10.417%10.4%12.268%12.3%4-1.000000x-1.000000x1.160109x1.160109x1.16x22.304%22.3%25.875%25.9%5-1.000000x-1.000000x1.137506x1.137506x1.14x8.598%8.60%9.780%9.78%-1.000000x-1.000000x1.136078x1.136078x1.14x9.088%9.09%10.324%10.3%-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-1.000000x1.123984x1.123984x1.12x16.526%16.5%18.574%18.6%7-1.000000x-1.000000x1.109070x1.109070x1.11x12.369%12.4%13.719%13.7%-1.000000x-1.000000x1.099797x1.099797x1.10x19.814%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-1.000000x1.038299x1.038299x1.04x7.979%7.98%8.284%8.28%-1.000000x-1.000000x1.038299x1.038299x1.04x7.979%7.98%8.284%8.28%-1.000000x-1.000000x1.030539x1.030539x1.03x28.448%28.4%29.316%29.3%30-1.000000x-1.000000x1.029167x1.029167x1.03x6.478%6.48%6.667%6.67%-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%48-1.219194x-1.219194x1.22x1.000000x1.000000x7.391%7.39%6.062%6.06%-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 Ohio Township, selected other county subdivisions in the United States, and entities that contain the Ohio Township
Female
Male
10x5x0xFM#Ottawa AreaFranklinEl PasoSalt Lk CityTract 954500PlanoTulsaAlbuquerqueNE DallasFort WorthOrlandoPhoenixTucson1, CharlotteMidwestNW HarrisLas VegasWest North CentralKansasSeattle EastSan Antonio CntrlSan DiegoUnited StatesSan JoseHempsteadFresnoNE TarrantTampaSan Fernando VlyE San Gabriel VlyHoustonSan BernardinoColumbusMiamiAtlantaMilwaukeeAnaheim-Santa Ana-Gdn GrvAnaheim-Santa An…SacramentoPhiladelphiaOceanside-EscondidoOceanside-Escond…Los AngelesAustinBaltimoreWashingtonQueensSW DallasBrooklynManhattanChicagoSeattleBostonBronxOntarioLong Bch-LakewoodDenverSan FranciscoDetroitOhio Township-1.000000x-1.000000x2.265727x2.265727x2.27x0.953%0.95%2.160%2.16%-1.000000x-1.000000x2.265727x2.265727x2.27x0.953%0.95%2.160%2.16%-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-1.000000x1.796110x1.796110x1.80x1.290%1.29%2.316%2.32%-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-1.000000x1.660799x1.660799x1.66x2.196%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-1.000000x1.589934x1.589934x1.59x2.251%2.25%3.579%3.58%-1.000000x-1.000000x1.579303x1.579303x1.58x2.100%2.10%3.317%3.32%12-1.000000x-1.000000x1.576623x1.576623x1.58x1.677%1.68%2.643%2.64%13-1.000000x-1.000000x1.572017x1.572017x1.57x2.329%2.33%3.662%3.66%-1.000000x-1.000000x1.571500x1.571500x1.57x2.361%2.36%3.710%3.71%-1.000000x-1.000000x1.557664x1.557664x1.56x4.733%4.73%7.372%7.37%14-1.000000x-1.000000x1.540473x1.540473x1.54x1.423%1.42%2.192%2.19%15-1.000000x-1.000000x1.529565x1.529565x1.53x4.164%4.16%6.370%6.37%16-1.000000x-1.000000x1.526215x1.526215x1.53x2.660%2.66%4.060%4.06%-1.000000x-1.000000x1.514156x1.514156x1.51x4.979%4.98%7.539%7.54%17-1.000000x-1.000000x1.488724x1.488724x1.49x3.608%3.61%5.371%5.37%18-1.000000x-1.000000x1.484269x1.484269x1.48x2.293%2.29%3.404%3.40%19-1.000000x-1.000000x1.481801x1.481801x1.48x2.138%2.14%3.168%3.17%20-1.000000x-1.000000x1.476874x1.476874x1.48x3.518%3.52%5.196%5.20%21-1.000000x-1.000000x1.460302x1.460302x1.46x2.944%2.94%4.299%4.30%22-1.000000x-1.000000x1.451775x1.451775x1.45x2.041%2.04%2.963%2.96%23-1.000000x-1.000000x1.424636x1.424636x1.42x3.092%3.09%4.404%4.40%24-1.000000x-1.000000x1.423621x1.423621x1.42x1.501%1.50%2.137%2.14%25-1.000000x-1.000000x1.413654x1.413654x1.41x2.801%2.80%3.959%3.96%26-1.000000x-1.000000x1.395174x1.395174x1.40x3.384%3.38%4.722%4.72%27-1.000000x-1.000000x1.391590x1.391590x1.39x5.799%5.80%8.070%8.07%28-1.000000x-1.000000x1.368590x1.368590x1.37x1.742%1.74%2.385%2.38%29-1.000000x-1.000000x1.362600x1.362600x1.36x2.347%2.35%3.199%3.20%30-1.000000x-1.000000x1.359928x1.359928x1.36x2.888%2.89%3.927%3.93%31-1.000000x-1.000000x1.341930x1.341930x1.34x3.216%3.22%4.316%4.32%32-1.000000x-1.000000x1.310218x1.310218x1.31x3.011%3.01%3.945%3.95%33-1.000000x-1.000000x1.308108x1.308108x1.31x4.045%4.05%5.292%5.29%34-1.000000x-1.000000x1.303834x1.303834x1.30x4.384%4.38%5.716%5.72%35-1.000000x-1.000000x1.303196x1.303196x1.30x4.332%4.33%5.645%5.65%36-1.000000x-1.000000x1.300117x1.300117x1.30x10.922%10.9%14.199%14.2%37-1.000000x-1.000000x1.285200x1.285200x1.29x2.428%2.43%3.121%3.12%38-1.000000x-1.000000x1.265486x1.265486x1.27x1.515%1.51%1.917%1.92%39-1.000000x-1.000000x1.262281x1.262281x1.26x3.021%3.02%3.814%3.81%40-1.000000x-1.000000x1.245683x1.245683x1.25x9.673%9.67%12.050%12.1%41-1.000000x-1.000000x1.238186x1.238186x1.24x4.026%4.03%4.985%4.99%42-1.000000x-1.000000x1.228890x1.228890x1.23x5.961%5.96%7.326%7.33%43-1.000000x-1.000000x1.221037x1.221037x1.22x6.643%6.64%8.112%8.11%44-1.000000x-1.000000x1.202385x1.202385x1.20x1.526%1.53%1.834%1.83%45-1.000000x-1.000000x1.198236x1.198236x1.20x2.119%2.12%2.539%2.54%46-1.000000x-1.000000x1.181998x1.181998x1.18x2.766%2.77%3.269%3.27%47-1.000000x-1.000000x1.129665x1.129665x1.13x5.378%5.38%6.075%6.08%48-1.000000x-1.000000x1.098720x1.098720x1.10x7.194%7.19%7.905%7.90%49-1.000000x-1.000000x1.046557x1.046557x1.05x1.291%1.29%1.351%1.35%50-10.000000x-10.000000x> 10.0x1.000000x1.000000x2.429%2.43%0.000%0%
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:
Kansas
County:
Franklin
Metro Area:
Ottawa Area
City:
Princeton
ZIP Codes:
66067, 66078, 66080
Unified School Districts:
Central Heights 288, Ottawa 290, West Franklin 287
Congressional District:
KS-2
State Senate District:
KS-12
State House Districts:
KS-5, KS-59
Neighboring Townships:
Cutler, Harrison, Homewood, Lincoln, Pottawatomie, Richmond, Williamsburg
Nearby Townships:
Greenwood, Jackson, Monroe, Ottawa, Peoria, Putnam, Reeder, Walker