Educational Attainment in Cleveland, Manitowoc County, Wisconsin (Village)

Educational Attainment#1

Highest level of education among people aged 25 years and older.
Scope: population of Manitowoc County and Cleveland
Cleveland
Manitowoc County
0%10%20%30%40%50%60%CountHigher Degree1H.S. Diploma2No H.S. Diploma238.679245%30.413826%38.679245%38.7%41048.301887%60.485864%48.301887%48.3%51213.018868%9.100310%13.018868%13.0%138
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 Manitowoc County at large.
Scope: population of Manitowoc County and Cleveland
0%%ref.Higher Degree1H.S. Diploma2No H.S. Diploma227.176520%27.176520%+27.2%38.679%38.7%30.414%30.4%-20.143512%-20.143512%-20.1%48.302%48.3%60.486%60.5%43.059605%43.059605%+43.1%13.019%13.0%9.100%9.10%
% percentage with given level in Cleveland
ref. percentage with given level in Manitowoc 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 Manitowoc County and Cleveland
Cleveland
Manitowoc County
0%10%20%30%40%CountDoctorate1Professional1Master's1Bachelor's1Associate's1Some CollegeHigh School2Some H.S.3Less than H.S.3None0.754717%0.254150%0.754717%0.8%80.849057%0.820290%0.849057%0.8%99.433962%4.404676%9.433962%9.4%10017.641509%14.179798%17.641509%17.6%18710.000000%10.754912%10.000000%10.0%10619.433962%19.981421%19.433962%19.4%20628.867925%40.504443%28.867925%28.9%3067.830189%6.050514%7.830189%7.8%830.471698%2.026186%0.471698%0.5%54.716981%1.023610%4.716981%4.7%50
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 Manitowoc County at large.
Scope: population of Manitowoc County and Cleveland
-200%0%+200%%ref.Doctorate1Professional1Master's1Bachelor's1Associate's1Some CollegeHigh School2Some H.S.3Less than H.S.3None196.957710%196.957710%+197.0%0.755%0.75%0.254%0.25%3.506894%3.506894%+3.5%0.849%0.85%0.820%0.82%114.180601%114.180601%+114.2%9.434%9.43%4.405%4.40%24.412984%24.412984%+24.4%17.642%17.6%14.180%14.2%-7.019231%-7.019231%-7.0%10.000%10.0%10.755%10.8%-2.739838%-2.739838%-2.7%19.434%19.4%19.981%20.0%-28.728993%-28.728993%-28.7%28.868%28.9%40.504%40.5%29.413602%29.413602%+29.4%7.830%7.83%6.051%6.05%-76.719903%-76.719903%-76.7%0.472%0.47%2.026%2.03%360.818364%360.818364%+360.8%4.717%4.72%1.024%1.02%
% percentage with given level in Cleveland
ref. percentage with given level in Manitowoc 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 Manitowoc County and Cleveland
More Females More Males
Manitowoc County
Cleveland
0%20%FMHigher Degree1H.S. Diploma2No H.S. Diploma2-0.785945%-17.561915%-0.785945%1%38.835%38.8%38.532%38.5%0.591891%3.244385%0.591891%1%48.155%48.2%48.440%48.4%0.136930%38.911874%0.136930%0%13.010%13.0%13.028%13.0%
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 Manitowoc County and Cleveland
More Females More Males
Manitowoc County
Cleveland
1k%0k%1k%FMDoctorate1Professional1Master's1Bachelor's1Associate's1Some CollegeHigh School2Some H.S.3Less than H.S.3None-1,000.000000%-1,000.000000%> 1000%20.229791%1.553%1.55%0.000%0%1,000.000000%106.548616%1,000.000000%> 1000%0.000%0%1.651%1.65%-25.595124%15.494393%15.494393%0k%8.738%8.74%10.092%10.1%-16.526672%-21.252536%-16.526672%0k%19.029%19.0%16.330%16.3%-18.362758%9.923235%9.923235%0k%9.515%9.51%10.459%10.5%-5.750115%6.185567%6.185567%0k%18.835%18.8%20.000%20.0%-3.094269%-3.094269%0k%7.814139%29.320%29.3%28.440%28.4%-25.319366%-25.319366%0k%52.834105%8.738%8.74%6.972%6.97%1,000.000000%21.133775%1,000.000000%> 1000%0.000%0%0.917%0.92%20.266889%4.698781%20.266889%0k%4.272%4.27%5.138%5.14%
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 Manitowoc County and Cleveland
Cleveland
Manitowoc County
0%5%10%15%20%B.X.Total65+45-6435-4425-3413.714286%10.483546%13.714286%13.7%2417523.310023%14.414231%23.310023%23.3%10042915.789474%15.468338%15.789474%15.8%3924711.483254%18.597812%11.483254%11.5%24209
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 Manitowoc County at large.
Scope: population of Manitowoc County and Cleveland
20%0%20%40%60%%ref.65+45-6435-4425-3430.817242%30.817242%30.8%13.714%13.7%10.484%10.5%61.715344%61.715344%61.7%23.310%23.3%14.414%14.4%2.076086%2.076086%2.1%15.789%15.8%15.468%15.5%-38.254814%-38.254814%38.3%11.483%11.5%18.598%18.6%
% percentage in Cleveland with a Bachelor's degree
ref percentage in Manitowoc 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 Manitowoc County and Cleveland
More Females More Males
Manitowoc County
Cleveland
100%50%0%FM65+45-6435-4425-34-5.226824%-5.478056%-5.226824%5.2%14.103%14.1%13.402%13.4%16.183575%0.886844%16.183575%16.2%21.622%21.6%25.121%25.1%-133.644860%-88.966045%-133.644860%133.6%23.364%23.4%10.000%10.0%-30.925926%-67.266356%-30.925926%30.9%12.963%13.0%9.901%9.90%
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 Manitowoc County and Cleveland
Cleveland
Manitowoc County
$0k$20k$40kCount%Graduate Degree1Bachelor's DegreeSome CollegeH.S. Diploma2No H.S. Diploma2Total$53,333.000000$59,970.000000$53,333.000000$53.3k11711.038%11.0%$40,625.000000$44,918.000000$40,625.000000$40.6k18717.642%17.6%$39,167.000000$35,132.000000$39,167.000000$39.2k31229.434%29.4%$38,450.000000$31,410.000000$38,450.000000$38.5k30628.868%28.9%$25,577.000000$23,100.000000$25,577.000000$25.6k13813.019%13.0%$38,387.000000$35,096.000000$38,387.000000$38.4k1,060100.000%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 Manitowoc County and Cleveland
Female Male
Manitowoc County
Cleveland
Shaded bar tips show excess over facing bar.
$50k$0k$50kFMGraduate Degree1Bachelor's DegreeSome CollegeH.S. Diploma2No H.S. Diploma2Total$-51,563.000000$-57,522.000000$-51,563.000000$51.6k$51,563.000000$9,131.000000$57,522.000000$7,582.000000$60,694.000000$60.7k5364$-20,000.000000$-38,391.000000$-20,000.000000$20.0k$20,000.000000$36,042.000000$38,391.000000$20,984.000000$56,042.000000$56.0k9889$-25,833.000000$-26,364.000000$-25,833.000000$25.8k$25,833.000000$25,917.000000$26,364.000000$19,259.000000$51,750.000000$51.8k146166$-26,875.000000$-24,267.000000$-26,875.000000$26.9k$26,875.000000$14,201.000000$24,267.000000$13,030.000000$41,076.000000$41.1k151155$-24,792.000000$-18,728.000000$-24,792.000000$24.8k$24,792.000000$977.000000$18,728.000000$7,868.000000$25,769.000000$25.8k6771$-28,333.000000$-27,307.000000$-28,333.000000$28.3k$28,333.000000$14,723.000000$27,307.000000$14,512.000000$43,056.000000$43.1k515545
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 Manitowoc County and Cleveland
Cleveland
Manitowoc County
0%20%40%60%80%CountBachelor's Degree1Some College2H.S. Diploma3No H.S. Diploma385.714286%85.805655%85.714286%85.7%22279.422383%84.308219%79.422383%79.4%22081.777778%77.063687%81.777778%81.8%18457.258065%59.324708%57.258065%57.3%71
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 Manitowoc County and Cleveland
Female Male
Manitowoc County
Cleveland
Shaded bar tips show excess over facing bar.
50%0%50%MFWhite1Hispanic2-6.765328%-6.294036%-6.765328%6.8%6.765328%0.348493%6.294036%2.674370%7.113821%7.1%3532-67.924528%-21.819061%-37.281553%-89.743590%89.7%67.924528%37.281553%3.178528%67.924528%67.9%3635
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 Manitowoc County and Cleveland
Female Male
Manitowoc County
Cleveland
Shaded bar tips show excess over facing bar.
30%20%10%0%10%20%30%MFWhite1Hispanic2-31.097561%-0.826329%-18.340694%-3.298007%-31.923890%31.9%31.097561%18.340694%31.097561%31.1%153151-0.000000%-7.983762%-2.307500%0.000000%0.0%0.000000%0.000000%7.983762%0.000000%0.0%00
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 Manitowoc Area

There are 31 county subdivisions in the Manitowoc Area. This section compares Cleveland to all of the county subdivisions in the Manitowoc Area and to those entities that contain or substantially overlap with Cleveland.

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 Cleveland, selected other county subdivisions in the Manitowoc Area, and entities that contain Cleveland
0%5%10%Count#United States of AmericaUnited StatesClevelandClevelandManitowocZIP Code 53015ZIP 53015Town of MishicotMishicotEast North CentralTown of MeemeMidwestKellnersville010600Tract 010600Town of Maple GroveMaple GrvMaribelManitowoc Metro AreaManitowocManitowoc CountyManitowocTwo RiversTown of FranklinFranklinTown of NewtonNewtonReedsvilleWisconsinTown of CentervilleCentervilleTown of RocklandRocklandWhitelawTown of GibsonGibsonMishicotTown of LibertyLibertyValdersSt. NazianzTown of CooperstownCooperstownTown of SchleswigSchleswigTown of Two CreeksTwo CreeksTown of EatonTown of CatoKielTown of ManitowocManitowocTown of Two RiversTwo RiversTown of KossuthKossuthFrancis CreekTown of Manitowoc RapidsManitowoc Rapids13.020590%13.020590%13.0%27,818,38027.8M13.018868%13.018868%13.0%13813.018868%13.018868%13.0%138111.206563%11.206563%11.2%2,609211.060948%11.060948%11.1%19611.023622%11.023622%11.0%112310.719464%10.719464%10.7%3,363,7843.36M10.678643%10.678643%10.7%107410.244520%10.244520%10.2%4,641,8354.64M10.101010%10.101010%10.1%3059.857612%9.857612%9.9%3609.448819%9.448819%9.4%4869.387755%9.387755%9.4%2379.100310%9.100310%9.1%5,1929.100310%9.100310%9.1%5,1928.970944%8.970944%9.0%74188.872902%8.872902%8.9%7498.750000%8.750000%8.8%147108.689840%8.689840%8.7%65118.637220%8.637220%8.6%336,096336k8.539326%8.539326%8.5%38128.381503%8.381503%8.4%58138.123791%8.123791%8.1%42148.016878%8.016878%8.0%76157.754280%7.754280%7.8%77167.710012%7.710012%7.7%67177.507987%7.507987%7.5%47187.334526%7.334526%7.3%41197.322404%7.322404%7.3%67206.566970%6.566970%6.6%101216.285714%6.285714%6.3%22225.730129%5.730129%5.7%31235.316456%5.316456%5.3%63245.146406%5.146406%5.1%116254.922280%4.922280%4.9%38264.867573%4.867573%4.9%68274.671632%4.671632%4.7%69283.768844%3.768844%3.8%15293.766707%3.766707%3.8%6230
Count number of people in category
# rank of county subdivision out of 30 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 Cleveland, selected other county subdivisions in the Manitowoc Area, and entities that contain Cleveland
0%10%20%30%Count#Town of Manitowoc RapidsManitowoc RapidsUnited States of AmericaUnited StatesMidwestClevelandClevelandEast North CentralWisconsinZIP Code 53015ZIP 53015Town of ManitowocManitowocTown of CentervilleCentervilleTown of NewtonNewtonTown of SchleswigSchleswig010600Tract 010600Town of LibertyLibertyManitowocTown of CooperstownCooperstownTown of CatoManitowoc Metro AreaManitowocManitowoc CountyManitowocTown of GibsonGibsonTown of EatonTown of RocklandRocklandTwo RiversTown of KossuthKossuthMishicotTown of Two RiversTwo RiversTown of Maple GroveMaple GrvTown of MeemeTown of Two CreeksTwo CreeksWhitelawReedsvilleTown of FranklinFranklinFrancis CreekKellnersvilleSt. NazianzMaribelValdersKielTown of MishicotMishicot39.125152%39.125152%39.1%644130.315023%30.315023%30.3%64,767,78764.8M28.952816%28.952816%29.0%13,118,64213.1M28.679245%28.679245%28.7%30428.679245%28.679245%28.7%304228.462853%28.462853%28.5%8,931,6868.93M28.373439%28.373439%28.4%1,104,0821.10M24.887133%24.887133%24.9%44124.870466%24.870466%24.9%192324.494382%24.494382%24.5%109423.928571%23.928571%23.9%402522.756827%22.756827%22.8%350622.727273%22.727273%22.7%83021.058688%21.058688%21.1%183721.017138%21.017138%21.0%4,893820.437158%20.437158%20.4%187920.168776%20.168776%20.2%2391019.658914%19.658914%19.7%11,21611.2k19.658914%19.658914%19.7%11,21611.2k18.459916%18.459916%18.5%1751118.299445%18.299445%18.3%991218.063584%18.063584%18.1%1251317.869249%17.869249%17.9%1,4761417.603250%17.603250%17.6%2601517.220544%17.220544%17.2%1711616.607015%16.607015%16.6%2321715.551181%15.551181%15.6%791814.770459%14.770459%14.8%1481914.571429%14.571429%14.6%512014.313346%14.313346%14.3%742114.171123%14.171123%14.2%1062214.028777%14.028777%14.0%1172312.311558%12.311558%12.3%492412.121212%12.121212%12.1%362511.985689%11.985689%12.0%672611.428571%11.428571%11.4%282711.341853%11.341853%11.3%712811.313221%11.313221%11.3%255299.251969%9.251969%9.3%9430
Count number of people in category
# rank of county subdivision out of 30 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 Cleveland, selected other county subdivisions in the Manitowoc Area, and entities that contain Cleveland
0%1%2%3%4%Count#Town of Manitowoc RapidsManitowoc RapidsUnited States of AmericaUnited StatesTown of Two RiversTwo RiversMidwestEast North CentralWisconsinTown of NewtonNewtonTown of CentervilleCentervilleZIP Code 53015ZIP 53015ClevelandClevelandTown of KossuthKossuthTown of LibertyLibertyTown of Cato010600Tract 010600Town of ManitowocManitowocManitowocTown of FranklinFranklinManitowoc Metro AreaManitowocManitowoc CountyManitowocTown of SchleswigSchleswigTown of CooperstownCooperstownTown of EatonTown of RocklandRocklandValdersMishicotTown of MeemeTown of Maple GroveMaple GrvTown of Two CreeksTwo CreeksFrancis CreekWhitelawReedsvilleKielTwo RiversTown of MishicotMishicotTown of GibsonGibsonSt. NazianzKellnersvilleMaribel4.981774%4.981774%5.0%8213.336158%3.336158%3.3%7,127,6737.13M3.078024%3.078024%3.1%4322.893416%2.893416%2.9%1,311,0191.31M2.855432%2.855432%2.9%896,039896k2.703886%2.703886%2.7%105,215105k2.500000%2.500000%2.5%4232.471910%2.471910%2.5%1141.749436%1.749436%1.7%311.603774%1.603774%1.6%171.603774%1.603774%1.6%1751.557211%1.557211%1.6%2361.495972%1.495972%1.5%1371.350211%1.350211%1.4%1681.314348%1.314348%1.3%481.295337%1.295337%1.3%1091.133972%1.133972%1.1%264101.079137%1.079137%1.1%9111.074440%1.074440%1.1%6131.074440%1.074440%1.1%6130.910273%0.910273%0.9%14120.874317%0.874317%0.9%8130.739372%0.739372%0.7%4140.722543%0.722543%0.7%5150.638978%0.638978%0.6%4160.604230%0.604230%0.6%6170.598802%0.598802%0.6%6180.590551%0.590551%0.6%3190.571429%0.571429%0.6%2200.502513%0.502513%0.5%2210.386847%0.386847%0.4%2220.267380%0.267380%0.3%2230.266193%0.266193%0.3%6240.230024%0.230024%0.2%19250.000000%0.000000%0.0%0260.000000%0.000000%0.0%0270.000000%0.000000%0.0%0280.000000%0.000000%0.0%0290.000000%0.000000%0.0%030
Count number of people in category
# rank of county subdivision out of 30 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 Cleveland, selected other county subdivisions in the Manitowoc Area, and entities that contain Cleveland
Female
Male
0x5x10xFM#Two CreeksMishicotManitowoc RapidsMishicotCooperstownKossuthReedsvilleTwo RiversRocklandSchleswigFranklinMaple GrvManitowocManitowocTown of CatoTown of EatonManitowocManitowocFrancis CreekTown of MeemeTwo RiversTract 010600ZIP 53015ValdersWisconsinWhitelawMidwestEast North CentralUnited StatesCentervilleKellnersvilleClevelandClevelandKielNewtonLibertyGibsonSt. NazianzMaribel-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%11.111%11.1%1-1.000000x-1.000000x4.263739x4.263739x4.26x4.017%4.02%17.127%17.1%2-1.000000x-1.000000x2.687642x2.687642x2.69x2.088%2.09%5.612%5.61%3-1.000000x-1.000000x2.398547x2.398547x2.40x4.642%4.64%11.134%11.1%4-1.000000x-1.000000x2.279462x2.279462x2.28x4.378%4.38%9.979%9.98%5-1.000000x-1.000000x2.133134x2.133134x2.13x2.945%2.95%6.283%6.28%6-1.000000x-1.000000x1.996767x1.996767x2.00x5.753%5.75%11.488%11.5%7-1.000000x-1.000000x1.971678x1.971678x1.97x3.245%3.24%6.398%6.40%8-1.000000x-1.000000x1.959857x1.959857x1.96x5.621%5.62%11.017%11.0%9-1.000000x-1.000000x1.846496x1.846496x1.85x4.570%4.57%8.438%8.44%10-1.000000x-1.000000x1.734114x1.734114x1.73x6.284%6.28%10.897%10.9%11-1.000000x-1.000000x1.569705x1.569705x1.57x7.234%7.23%11.355%11.4%12-1.000000x-1.000000x1.517526x1.517526x1.52x3.906%3.91%5.928%5.93%13-1.000000x-1.000000x1.432549x1.432549x1.43x9.294%9.29%13.313%13.3%14-1.000000x-1.000000x1.427954x1.427954x1.43x4.355%4.36%6.219%6.22%15-1.000000x-1.000000x1.389744x1.389744x1.39x4.797%4.80%6.667%6.67%16-1.000000x-1.000000x1.389119x1.389119x1.39x7.638%7.64%10.610%10.6%-1.000000x-1.000000x1.389119x1.389119x1.39x7.638%7.64%10.610%10.6%-1.000000x-1.000000x1.370192x1.370192x1.37x3.158%3.16%4.327%4.33%17-1.000000x-1.000000x1.328596x1.328596x1.33x9.198%9.20%12.220%12.2%18-1.000000x-1.000000x1.265267x1.265267x1.27x7.966%7.97%10.079%10.1%19-1.000000x-1.000000x1.250258x1.250258x1.25x8.739%8.74%10.927%10.9%-1.000000x-1.000000x1.231994x1.231994x1.23x9.871%9.87%12.161%12.2%-1.000000x-1.000000x1.222373x1.222373x1.22x6.752%6.75%8.254%8.25%20-1.000000x-1.000000x1.219291x1.219291x1.22x7.799%7.80%9.509%9.51%-1.000000x-1.000000x1.133452x1.133452x1.13x7.600%7.60%8.614%8.61%21-1.000000x-1.000000x1.127915x1.127915x1.13x9.647%9.65%10.881%10.9%-1.000000x-1.000000x1.125371x1.125371x1.13x10.108%10.1%11.375%11.4%-1.000000x-1.000000x1.109070x1.109070x1.11x12.369%12.4%13.719%13.7%-1.000000x-1.000000x1.045643x1.045643x1.05x8.333%8.33%8.714%8.71%22-1.000000x-1.000000x1.032967x1.032967x1.03x9.929%9.93%10.256%10.3%23-1.000000x-1.000000x1.001369x1.001369x1.00x13.010%13.0%13.028%13.0%-1.000000x-1.000000x1.001369x1.001369x1.00x13.010%13.0%13.028%13.0%24-1.035901x-1.035901x1.04x1.000000x1.000000x5.236%5.24%5.054%5.05%25-1.060038x-1.060038x1.06x1.000000x1.000000x9.022%9.02%8.511%8.51%26-1.282551x-1.282551x1.28x1.000000x1.000000x8.685%8.69%6.772%6.77%27-1.513670x-1.513670x1.51x1.000000x1.000000x9.859%9.86%6.513%6.51%28-1.583062x-1.583062x1.58x1.000000x1.000000x8.795%8.79%5.556%5.56%29-2.385965x-2.385965x2.39x1.000000x1.000000x12.782%12.8%5.357%5.36%30
F percentage of females in category
M percentage of males in category
# rank of county subdivision out of 30 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 Cleveland, selected other county subdivisions in the Manitowoc Area, and entities that contain Cleveland
Female
Male
10x5x0x5x10xFM#Two RiversKielReedsvilleTown of EatonTwo CreeksNewtonSchleswigManitowoc RapidsTwo RiversCooperstownManitowocMishicotManitowocManitowocTract 010600East North CentralMidwestWisconsinLibertyUnited StatesManitowocCentervilleClevelandClevelandTown of MeemeValdersZIP 53015FranklinKossuthTown of CatoRocklandMaple GrvWhitelawFrancis Creek-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%0.484%0.48%1-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%0.542%0.54%2-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%0.522%0.52%3-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%1.481%1.48%4-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%1.010%1.01%5-1.000000x-1.000000x8.372340x8.372340x8.37x0.508%0.51%4.255%4.26%6-1.000000x-1.000000x5.622166x5.622166x5.62x0.269%0.27%1.511%1.51%7-1.000000x-1.000000x3.645677x3.645677x3.65x2.204%2.20%8.036%8.04%8-1.000000x-1.000000x2.743204x2.743204x2.74x1.622%1.62%4.451%4.45%9-1.000000x-1.000000x2.706861x2.706861x2.71x0.461%0.46%1.247%1.25%10-1.000000x-1.000000x2.309278x2.309278x2.31x0.781%0.78%1.804%1.80%11-1.000000x-1.000000x2.172269x2.172269x2.17x0.387%0.39%0.840%0.84%12-1.000000x-1.000000x1.806143x1.806143x1.81x0.769%0.77%1.390%1.39%-1.000000x-1.000000x1.806143x1.806143x1.81x0.769%0.77%1.390%1.39%-1.000000x-1.000000x1.743439x1.743439x1.74x0.952%0.95%1.660%1.66%-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-1.000000x1.576114x1.576114x1.58x2.109%2.11%3.323%3.32%-1.000000x-1.000000x1.538600x1.538600x1.54x1.174%1.17%1.806%1.81%13-1.000000x-1.000000x1.526215x1.526215x1.53x2.660%2.66%4.060%4.06%-1.000000x-1.000000x1.494707x1.494707x1.49x0.918%0.92%1.372%1.37%14-1.000000x-1.000000x1.481328x1.481328x1.48x1.961%1.96%2.905%2.90%15-1.000000x-1.000000x1.063073x1.063073x1.06x1.553%1.55%1.651%1.65%-1.000000x-1.000000x1.063073x1.063073x1.06x1.553%1.55%1.651%1.65%16-1.000000x-1.000000x1.040733x1.040733x1.04x0.587%0.59%0.611%0.61%17-1.012862x-1.012862x1.01x1.000000x1.000000x0.643%0.64%0.635%0.63%18-1.014615x-1.014615x1.01x1.000000x1.000000x1.763%1.76%1.737%1.74%-1.598361x-1.598361x1.60x1.000000x1.000000x1.366%1.37%0.855%0.85%19-2.009116x-2.009116x2.01x1.000000x1.000000x2.104%2.10%1.047%1.05%20-7.451220x-7.451220x7.45x1.000000x1.000000x2.439%2.44%0.327%0.33%21-10.000000x-10.000000x> 10.0x1.000000x1.000000x1.479%1.48%0.000%0%22-10.000000x-10.000000x> 10.0x1.000000x1.000000x1.277%1.28%0.000%0%23-10.000000x-10.000000x> 10.0x1.000000x1.000000x0.800%0.80%0.000%0%24-10.000000x-10.000000x> 10.0x1.000000x1.000000x1.053%1.05%0.000%0%25
F percentage of females in category
M percentage of males in category
# rank of county subdivision out of 25 by male-to-female sex ratio

Educational Attainment by County Subdivision in Wisconsin

There are 1,927 county subdivisions in Wisconsin. This section compares Cleveland to the 50 most populous county subdivisions in Wisconsin and to those entities that contain or substantially overlap with Cleveland. The least populous of the compared county subdivisions has a population of 16,289.

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 Cleveland, selected other county subdivisions in Wisconsin, and entities that contain Cleveland
0%5%10%15%Count#BeloitRacineMilwaukeeUnited States of AmericaUnited StatesClevelandClevelandGreen BaySheboyganKenoshaManitowocCudahyZIP Code 53015ZIP 53015WausauEast North CentralMidwestWest AllisOshkoshBeaver Dam010600Tract 010600South MilwaukeeS MilwaukeeManitowoc Metro AreaManitowocManitowoc CountyManitowocMarshfieldFond du LacFitchburgWisconsinJanesvilleMenomonieGreenfieldPleasant PrairieAppletonFranklinWaukeshaTown of Grand ChuteGrand ChuteLa CrosseWisconsin RapidsCaledoniaWest BendSuperiorTown of MenashaMenashaAshwaubenonEau ClaireStevens PointHowardMount PleasantMt PleasantNeenahOak CreekGermantownOnalaskaMadisonMenomonee FallsNew BerlinOconomowocSun PrairieDe PereMuskegoWauwatosaBrookfieldMiddletonMequon18.491431%18.491431%18.5%4,197117.907441%17.907441%17.9%8,710217.485105%17.485105%17.5%63,80063.8k313.020590%13.020590%13.0%27,818,38027.8M13.018868%13.018868%13.0%13813.018868%13.018868%13.0%13812.535944%12.535944%12.5%8,414411.643417%11.643417%11.6%3,806511.549265%11.549265%11.5%7,360611.206563%11.206563%11.2%2,609711.082337%11.082337%11.1%1,455811.060948%11.060948%11.1%19610.776184%10.776184%10.8%2,885910.719464%10.719464%10.7%3,363,7843.36M10.244520%10.244520%10.2%4,641,8354.64M10.028497%10.028497%10.0%4,399109.995428%9.995428%10.0%4,154119.950027%9.950027%10.0%1,115129.857612%9.857612%9.9%3609.190270%9.190270%9.2%1,379139.100310%9.100310%9.1%5,1929.100310%9.100310%9.1%5,1928.829004%8.829004%8.8%1,091148.713948%8.713948%8.7%2,547158.662728%8.662728%8.7%1,613168.637220%8.637220%8.6%336,096336k8.522583%8.522583%8.5%3,704178.211921%8.211921%8.2%620188.204982%8.204982%8.2%2,296197.709924%7.709924%7.7%1,111207.618904%7.618904%7.6%3,034217.392323%7.392323%7.4%1,924227.158983%7.158983%7.2%3,393237.144208%7.144208%7.1%1,133247.116644%7.116644%7.1%2,075257.048284%7.048284%7.0%889266.746719%6.746719%6.7%1,208276.565400%6.565400%6.6%1,422286.289585%6.289585%6.3%1,142296.244351%6.244351%6.2%829306.168099%6.168099%6.2%739316.128290%6.128290%6.1%2,398326.111996%6.111996%6.1%883336.065319%6.065319%6.1%780346.042598%6.042598%6.0%1,149355.863324%5.863324%5.9%1,015365.765641%5.765641%5.8%1,421375.227570%5.227570%5.2%719384.888290%4.888290%4.9%617394.836248%4.836248%4.8%7,351404.484909%4.484909%4.5%1,165414.236891%4.236891%4.2%1,267423.988090%3.988090%4.0%442433.955766%3.955766%4.0%812443.911088%3.911088%3.9%600453.554446%3.554446%3.6%598463.390471%3.390471%3.4%1,167472.806979%2.806979%2.8%761482.731305%2.731305%2.7%351492.107701%2.107701%2.1%35550
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 Cleveland, selected other county subdivisions in Wisconsin, and entities that contain Cleveland
0%20%40%60%Count#MequonMiddletonWauwatosaBrookfieldMadisonFitchburgOconomowocMenomonee FallsSun PrairieNew BerlinGermantownFranklinStevens PointDe PereWaukeshaOnalaskaMenomonieMuskegoPleasant PrairieLa CrosseMount PleasantMt PleasantNeenahEau ClaireAppletonTown of Grand ChuteGrand ChuteOak CreekUnited States of AmericaUnited StatesMidwestGreenfieldCaledoniaTown of MenashaMenashaHowardClevelandClevelandEast North CentralWisconsinMarshfieldWest BendAshwaubenonWausauZIP Code 53015ZIP 53015OshkoshGreen BayWest AllisFond du LacMilwaukeeKenosha010600Tract 010600SuperiorJanesvilleCudahyManitowocSouth MilwaukeeS MilwaukeeManitowoc Metro AreaManitowocManitowoc CountyManitowocSheboyganBeaver DamRacineBeloitWisconsin Rapids63.254765%63.254765%63.3%10,65410.7k158.898140%58.898140%58.9%7,569258.155142%58.155142%58.2%20,01720.0k358.053926%58.053926%58.1%15,73915.7k456.337583%56.337583%56.3%85,63285.6k546.358754%46.358754%46.4%8,632644.229902%44.229902%44.2%4,902741.080228%41.080228%41.1%10,67110.7k841.077605%41.077605%41.1%8,432940.780498%40.780498%40.8%12,19512.2k1039.610295%39.610295%39.6%5,4481137.841472%37.841472%37.8%9,8491236.471240%36.471240%36.5%5,2691336.151489%36.151489%36.2%5,5461435.550164%35.550164%35.6%16,84916.8k1535.152908%35.152908%35.2%4,4371635.139073%35.139073%35.1%2,6531733.499762%33.499762%33.5%5,6361833.074254%33.074254%33.1%4,7661932.942347%32.942347%32.9%9,6052032.747831%32.747831%32.7%6,2272132.464907%32.464907%32.5%5,6202232.432916%32.432916%32.4%12,69112.7k2332.296218%32.296218%32.3%12,86112.9k2432.202535%32.202535%32.2%5,1072531.640023%31.640023%31.6%7,7982630.315023%30.315023%30.3%64,767,78764.8M28.952816%28.952816%29.0%13,118,64213.1M28.921131%28.921131%28.9%8,0932728.919296%28.919296%28.9%5,1782828.909310%28.909310%28.9%3,8382928.794712%28.794712%28.8%3,7033028.679245%28.679245%28.7%30428.679245%28.679245%28.7%30428.462853%28.462853%28.5%8,931,6868.93M28.373439%28.373439%28.4%1,104,0821.10M28.348305%28.348305%28.3%3,5033127.212706%27.212706%27.2%5,8943226.525332%26.525332%26.5%3,1783325.519199%25.519199%25.5%6,8323424.887133%24.887133%24.9%44124.478452%24.478452%24.5%10,17310.2k3524.139215%24.139215%24.1%16,20216.2k3623.980394%23.980394%24.0%10,51910.5k3723.606692%23.606692%23.6%6,9003823.517740%23.517740%23.5%85,81285.8k3922.927488%22.927488%22.9%14,61114.6k4022.727273%22.727273%22.7%83022.415597%22.415597%22.4%4,0704122.035848%22.035848%22.0%9,5774221.471552%21.471552%21.5%2,8194321.017138%21.017138%21.0%4,8934420.519827%20.519827%20.5%3,0794519.658914%19.658914%19.7%11,21611.2k19.658914%19.658914%19.7%11,21611.2k19.530103%19.530103%19.5%6,3844618.623951%18.623951%18.6%2,0874717.525031%17.525031%17.5%8,5244816.605719%16.605719%16.6%3,7694915.880441%15.880441%15.9%2,00350
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 Cleveland, selected other county subdivisions in Wisconsin, and entities that contain Cleveland
0%5%10%Count#MequonMiddletonBrookfieldMadisonWauwatosaFitchburgMarshfieldMenomonieLa CrosseStevens PointOnalaskaOconomowocNew BerlinUnited States of AmericaUnited StatesMenomonee FallsSun PrairieNeenahFranklinDe PereGermantownMidwestEau ClaireEast North CentralAppletonWisconsinMuskegoPleasant PrairieBeaver DamWausauTown of Grand ChuteGrand ChuteCaledoniaMount PleasantMt PleasantTown of MenashaMenashaWaukeshaMilwaukeeGreenfieldOak CreekBeloitGreen BayKenoshaZIP Code 53015ZIP 53015Wisconsin RapidsClevelandClevelandJanesvilleOshkoshSuperiorFond du LacHoward010600Tract 010600CudahyWest BendWest AllisRacineManitowocManitowoc Metro AreaManitowocManitowoc CountyManitowocSouth MilwaukeeS MilwaukeeSheboyganAshwaubenon11.084724%11.084724%11.1%1,867110.022566%10.022566%10.0%1,28829.217661%9.217661%9.2%2,49939.171173%9.171173%9.2%13,94013.9k48.094131%8.094131%8.1%2,78657.196563%7.196563%7.2%1,34065.867120%5.867120%5.9%72574.993377%4.993377%5.0%37784.777583%4.777583%4.8%1,39394.679172%4.679172%4.7%676104.547615%4.547615%4.5%574114.222683%4.222683%4.2%468123.762039%3.762039%3.8%1,125133.336158%3.336158%3.3%7,127,6737.13M3.295350%3.295350%3.3%856143.288352%3.288352%3.3%675153.188724%3.188724%3.2%552163.100626%3.100626%3.1%807173.083241%3.083241%3.1%473182.995492%2.995492%3.0%412192.893416%2.893416%2.9%1,311,0191.31M2.869921%2.869921%2.9%1,123202.855432%2.855432%2.9%896,039896k2.794937%2.794937%2.8%1,113212.703886%2.703886%2.7%105,215105k2.674750%2.674750%2.7%450222.637058%2.637058%2.6%380232.552204%2.552204%2.6%286242.416704%2.416704%2.4%647252.396116%2.396116%2.4%380262.356884%2.356884%2.4%422272.303445%2.303445%2.3%438282.244652%2.244652%2.2%298292.192214%2.192214%2.2%1,039302.043126%2.043126%2.0%7,455311.868992%1.868992%1.9%523321.809624%1.809624%1.8%446331.784377%1.784377%1.8%405341.777440%1.777440%1.8%1,193351.762204%1.762204%1.8%1,123361.749436%1.749436%1.7%311.688734%1.688734%1.7%213371.603774%1.603774%1.6%171.603774%1.603774%1.6%171.555418%1.555418%1.6%676381.549604%1.549604%1.5%644391.525582%1.525582%1.5%277401.454035%1.454035%1.5%425411.384137%1.384137%1.4%178421.314348%1.314348%1.3%481.302460%1.302460%1.3%171431.292765%1.292765%1.3%280441.251567%1.251567%1.3%549451.155451%1.155451%1.2%562461.133972%1.133972%1.1%264471.074440%1.074440%1.1%6131.074440%1.074440%1.1%6130.893036%0.893036%0.9%134480.868820%0.868820%0.9%284490.784576%0.784576%0.8%9450
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 Cleveland, selected other county subdivisions in Wisconsin, and entities that contain Cleveland
Female
Male
1x0x1x2xFM#De PereMenashaOshkoshFranklinCaledoniaManitowocGreen BayManitowocManitowocPleasant PrairieWauwatosaWaukeshaJanesvilleMt PleasantSuperiorTract 010600ZIP 53015Stevens PointAppletonWisconsinRacineGrand ChuteGermantownMadisonMuskegoKenoshaMequonMidwestEast North CentralMilwaukeeWest BendOnalaskaUnited StatesEau ClaireWisconsin RapidsMenomonee FallsBeloitBeaver DamLa CrosseHowardOak CreekGreenfieldMiddletonFond du LacMarshfieldNew BerlinSheboyganClevelandClevelandNeenahFitchburgSun PrairieWest AllisS MilwaukeeCudahyWausauBrookfieldAshwaubenonMenomonieOconomowoc-1.000000x-1.000000x2.147134x2.147134x2.15x2.553%2.55%5.481%5.48%1-1.000000x-1.000000x1.888774x1.888774x1.89x4.337%4.34%8.192%8.19%2-1.000000x-1.000000x1.812682x1.812682x1.81x7.022%7.02%12.729%12.7%3-1.000000x-1.000000x1.578941x1.578941x1.58x5.723%5.72%9.036%9.04%4-1.000000x-1.000000x1.534399x1.534399x1.53x5.333%5.33%8.182%8.18%5-1.000000x-1.000000x1.432549x1.432549x1.43x9.294%9.29%13.313%13.3%6-1.000000x-1.000000x1.408197x1.408197x1.41x10.435%10.4%14.694%14.7%7-1.000000x-1.000000x1.389119x1.389119x1.39x7.638%7.64%10.610%10.6%-1.000000x-1.000000x1.389119x1.389119x1.39x7.638%7.64%10.610%10.6%-1.000000x-1.000000x1.380848x1.380848x1.38x6.493%6.49%8.965%8.97%8-1.000000x-1.000000x1.306431x1.306431x1.31x2.969%2.97%3.879%3.88%9-1.000000x-1.000000x1.304061x1.304061x1.30x6.240%6.24%8.137%8.14%10-1.000000x-1.000000x1.294088x1.294088x1.29x7.468%7.47%9.664%9.66%11-1.000000x-1.000000x1.293422x1.293422x1.29x5.323%5.32%6.885%6.89%12-1.000000x-1.000000x1.278895x1.278895x1.28x5.545%5.54%7.091%7.09%13-1.000000x-1.000000x1.250258x1.250258x1.25x8.739%8.74%10.927%10.9%-1.000000x-1.000000x1.231994x1.231994x1.23x9.871%9.87%12.161%12.2%-1.000000x-1.000000x1.229327x1.229327x1.23x5.499%5.50%6.760%6.76%14-1.000000x-1.000000x1.219351x1.219351x1.22x6.887%6.89%8.397%8.40%15-1.000000x-1.000000x1.219291x1.219291x1.22x7.799%7.80%9.509%9.51%-1.000000x-1.000000x1.214505x1.214505x1.21x16.245%16.2%19.730%19.7%16-1.000000x-1.000000x1.207489x1.207489x1.21x6.484%6.48%7.830%7.83%17-1.000000x-1.000000x1.203474x1.203474x1.20x4.768%4.77%5.738%5.74%18-1.000000x-1.000000x1.189278x1.189278x1.19x4.425%4.43%5.263%5.26%19-1.000000x-1.000000x1.159324x1.159324x1.16x3.296%3.30%3.822%3.82%20-1.000000x-1.000000x1.152187x1.152187x1.15x10.767%10.8%12.406%12.4%21-1.000000x-1.000000x1.145574x1.145574x1.15x1.970%1.97%2.257%2.26%22-1.000000x-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-1.000000x1.123984x1.123984x1.12x16.526%16.5%18.574%18.6%23-1.000000x-1.000000x1.118245x1.118245x1.12x6.211%6.21%6.945%6.95%24-1.000000x-1.000000x1.113721x1.113721x1.11x4.646%4.65%5.175%5.17%25-1.000000x-1.000000x1.109070x1.109070x1.11x12.369%12.4%13.719%13.7%-1.000000x-1.000000x1.104897x1.104897x1.10x5.834%5.83%6.446%6.45%26-1.000000x-1.000000x1.104741x1.104741x1.10x6.724%6.72%7.428%7.43%27-1.000000x-1.000000x1.077248x1.077248x1.08x4.329%4.33%4.663%4.66%28-1.000000x-1.000000x1.069954x1.069954x1.07x17.920%17.9%19.173%19.2%29-1.000000x-1.000000x1.063348x1.063348x1.06x9.653%9.65%10.265%10.3%30-1.000000x-1.000000x1.059381x1.059381x1.06x6.918%6.92%7.329%7.33%31-1.000000x-1.000000x1.056613x1.056613x1.06x5.903%5.90%6.237%6.24%32-1.000000x-1.000000x1.048827x1.048827x1.05x5.631%5.63%5.906%5.91%33-1.000000x-1.000000x1.046668x1.046668x1.05x8.030%8.03%8.405%8.40%34-1.000000x-1.000000x1.022109x1.022109x1.02x2.704%2.70%2.764%2.76%35-1.000000x-1.000000x1.018058x1.018058x1.02x8.641%8.64%8.797%8.80%36-1.000000x-1.000000x1.015610x1.015610x1.02x8.765%8.76%8.902%8.90%37-1.000000x-1.000000x1.012610x1.012610x1.01x4.211%4.21%4.265%4.26%38-1.000000x-1.000000x1.004509x1.004509x1.00x11.618%11.6%11.670%11.7%39-1.000000x-1.000000x1.001369x1.001369x1.00x13.010%13.0%13.028%13.0%-1.000000x-1.000000x1.001369x1.001369x1.00x13.010%13.0%13.028%13.0%-1.001253x-1.001253x1.00x1.000000x1.000000x5.867%5.87%5.859%5.86%40-1.016031x-1.016031x1.02x1.000000x1.000000x8.734%8.73%8.596%8.60%41-1.022158x-1.022158x1.02x1.000000x1.000000x3.997%4.00%3.910%3.91%42-1.024115x-1.024115x1.02x1.000000x1.000000x10.145%10.1%9.906%9.91%43-1.068390x-1.068390x1.07x1.000000x1.000000x9.477%9.48%8.871%8.87%44-1.082508x-1.082508x1.08x1.000000x1.000000x11.515%11.5%10.638%10.6%45-1.083232x-1.083232x1.08x1.000000x1.000000x11.187%11.2%10.327%10.3%46-1.121159x-1.121159x1.12x1.000000x1.000000x2.957%2.96%2.637%2.64%47-1.237978x-1.237978x1.24x1.000000x1.000000x6.794%6.79%5.488%5.49%48-1.368790x-1.368790x1.37x1.000000x1.000000x9.414%9.41%6.877%6.88%49-1.427909x-1.427909x1.43x1.000000x1.000000x4.664%4.66%3.266%3.27%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 Cleveland, selected other county subdivisions in Wisconsin, and entities that contain Cleveland
Female
Male
1x0x1x2x3xFM#NeenahPleasant PrairieCudahyMenomonieOnalaskaMuskegoHowardMarshfieldMequonJanesvilleSheboyganRacineBeaver DamBrookfieldGreen BayBeloitStevens PointWausauFitchburgSun PrairieManitowocManitowocEau ClaireOshkoshTract 010600AppletonFond du LacNew BerlinWest AllisWauwatosaWest BendEast North CentralMidwestWisconsinMt PleasantCaledoniaUnited StatesSuperiorManitowocFranklinLa CrosseS MilwaukeeMiddletonMenomonee FallsMadisonMilwaukeeDe PereGrand ChuteKenoshaGermantownWaukeshaOconomowocClevelandClevelandWisconsin RapidsMenashaZIP 53015GreenfieldOak CreekAshwaubenon-1.000000x-1.000000x3.129204x3.129204x3.13x1.585%1.59%4.960%4.96%1-1.000000x-1.000000x2.927208x2.927208x2.93x1.353%1.35%3.961%3.96%2-1.000000x-1.000000x2.631735x2.631735x2.63x0.722%0.72%1.899%1.90%3-1.000000x-1.000000x2.628013x2.628013x2.63x2.819%2.82%7.408%7.41%4-1.000000x-1.000000x2.571855x2.571855x2.57x2.645%2.64%6.802%6.80%5-1.000000x-1.000000x2.519338x2.519338x2.52x1.531%1.53%3.858%3.86%6-1.000000x-1.000000x2.492011x2.492011x2.49x0.802%0.80%1.999%2.00%7-1.000000x-1.000000x2.351130x2.351130x2.35x3.588%3.59%8.437%8.44%8-1.000000x-1.000000x2.345235x2.345235x2.35x6.743%6.74%15.813%15.8%9-1.000000x-1.000000x2.320788x2.320788x2.32x0.952%0.95%2.209%2.21%10-1.000000x-1.000000x2.236989x2.236989x2.24x0.541%0.54%1.209%1.21%11-1.000000x-1.000000x2.147202x2.147202x2.15x0.747%0.75%1.604%1.60%12-1.000000x-1.000000x2.134058x2.134058x2.13x1.646%1.65%3.514%3.51%13-1.000000x-1.000000x2.050517x2.050517x2.05x6.177%6.18%12.666%12.7%14-1.000000x-1.000000x2.006236x2.006236x2.01x1.188%1.19%2.383%2.38%15-1.000000x-1.000000x2.005610x2.005610x2.01x1.223%1.22%2.453%2.45%16-1.000000x-1.000000x1.994529x1.994529x1.99x3.154%3.15%6.290%6.29%17-1.000000x-1.000000x1.957848x1.957848x1.96x1.658%1.66%3.247%3.25%18-1.000000x-1.000000x1.808864x1.808864x1.81x5.081%5.08%9.190%9.19%19-1.000000x-1.000000x1.806537x1.806537x1.81x2.381%2.38%4.302%4.30%20-1.000000x-1.000000x1.806143x1.806143x1.81x0.769%0.77%1.390%1.39%-1.000000x-1.000000x1.806143x1.806143x1.81x0.769%0.77%1.390%1.39%-1.000000x-1.000000x1.786228x1.786228x1.79x2.083%2.08%3.720%3.72%21-1.000000x-1.000000x1.747870x1.747870x1.75x1.115%1.12%1.949%1.95%22-1.000000x-1.000000x1.743439x1.743439x1.74x0.952%0.95%1.660%1.66%-1.000000x-1.000000x1.733790x1.733790x1.73x2.062%2.06%3.574%3.57%23-1.000000x-1.000000x1.728996x1.728996x1.73x1.083%1.08%1.873%1.87%24-1.000000x-1.000000x1.706236x1.706236x1.71x2.810%2.81%4.794%4.79%25-1.000000x-1.000000x1.693783x1.693783x1.69x0.936%0.94%1.585%1.59%26-1.000000x-1.000000x1.663311x1.663311x1.66x6.193%6.19%10.301%10.3%27-1.000000x-1.000000x1.632200x1.632200x1.63x0.991%0.99%1.617%1.62%28-1.000000x-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-1.000000x1.576114x1.576114x1.58x2.109%2.11%3.323%3.32%-1.000000x-1.000000x1.557391x1.557391x1.56x1.833%1.83%2.855%2.85%29-1.000000x-1.000000x1.550147x1.550147x1.55x1.851%1.85%2.870%2.87%30-1.000000x-1.000000x1.526215x1.526215x1.53x2.660%2.66%4.060%4.06%-1.000000x-1.000000x1.516809x1.516809x1.52x1.222%1.22%1.853%1.85%31-1.000000x-1.000000x1.494707x1.494707x1.49x0.918%0.92%1.372%1.37%32-1.000000x-1.000000x1.475485x1.475485x1.48x2.501%2.50%3.691%3.69%33-1.000000x-1.000000x1.473120x1.473120x1.47x3.888%3.89%5.727%5.73%34-1.000000x-1.000000x1.458132x1.458132x1.46x0.734%0.73%1.070%1.07%35-1.000000x-1.000000x1.452651x1.452651x1.45x8.299%8.30%12.055%12.1%36-1.000000x-1.000000x1.388151x1.388151x1.39x2.789%2.79%3.872%3.87%37-1.000000x-1.000000x1.387878x1.387878x1.39x7.705%7.70%10.693%10.7%38-1.000000x-1.000000x1.368590x1.368590x1.37x1.742%1.74%2.385%2.38%39-1.000000x-1.000000x1.363936x1.363936x1.36x2.638%2.64%3.598%3.60%40-1.000000x-1.000000x1.256412x1.256412x1.26x2.128%2.13%2.674%2.67%41-1.000000x-1.000000x1.229981x1.229981x1.23x1.588%1.59%1.953%1.95%42-1.000000x-1.000000x1.211592x1.211592x1.21x2.722%2.72%3.299%3.30%43-1.000000x-1.000000x1.195990x1.195990x1.20x2.002%2.00%2.394%2.39%44-1.000000x-1.000000x1.068496x1.068496x1.07x4.087%4.09%4.367%4.37%45-1.000000x-1.000000x1.063073x1.063073x1.06x1.553%1.55%1.651%1.65%-1.000000x-1.000000x1.063073x1.063073x1.06x1.553%1.55%1.651%1.65%-1.000000x-1.000000x1.014900x1.014900x1.01x1.677%1.68%1.702%1.70%46-1.000000x-1.000000x1.008002x1.008002x1.01x2.236%2.24%2.254%2.25%47-1.014615x-1.014615x1.01x1.000000x1.000000x1.763%1.76%1.737%1.74%-1.098352x-1.098352x1.10x1.000000x1.000000x1.951%1.95%1.776%1.78%48-1.142247x-1.142247x1.14x1.000000x1.000000x1.927%1.93%1.687%1.69%49-1.623043x-1.623043x1.62x1.000000x1.000000x0.961%0.96%0.592%0.59%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 Cleveland to the 50 most populous county subdivisions in the Midwest and to those entities that contain or substantially overlap with Cleveland. 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 Cleveland, selected other county subdivisions in the Midwest, and entities that contain Cleveland
0%10%20%30%Count#Aurora TownshipAuroraCenter TownshipCtrKansas CityClevelandWayne TownshipWayneDetroitMilwaukeeNorth TownshipNDaytonChicagoProviso TownshipProvisoRockford TownshipRockfordSt. LouisWarrenGrand RapidsToledoBlue TownshipCincinnatiAkronSt. PaulSterling HeightsSterling HtsUnited States of AmericaUnited StatesClevelandClevelandThornton TownshipThorntonWichitaKaw TownshipOmahaBloomingdale TownshipBloomingdaleColumbusMaine TownshipMaineZIP Code 53015ZIP 53015TopekaMinneapolisSpringfield TownshipSpringfieldEast North CentralWorth TownshipWorthMidwestLawrence TownshipLawrence010600Tract 010600Sioux FallsManitowoc Metro AreaManitowocManitowoc CountyManitowocWisconsinCapital 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%27,818,38027.8M13.018868%13.018868%13.0%13813.018868%13.018868%13.0%13812.974232%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%10,96511.0k2811.060948%11.060948%11.1%19611.032803%11.032803%11.0%9,3772910.958428%10.958428%11.0%29,34729.3k3010.767091%10.767091%10.8%11,14911.1k3110.719464%10.719464%10.7%3,363,7843.36M10.678962%10.678962%10.7%11,17511.2k3210.244520%10.244520%10.2%4,641,8354.64M10.179618%10.179618%10.2%8,161339.857612%9.857612%9.9%3609.702326%9.702326%9.7%9,123349.100310%9.100310%9.1%5,1929.100310%9.100310%9.1%5,1928.637220%8.637220%8.6%336,096336k8.623103%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 Cleveland, selected other county subdivisions in the Midwest, and entities that contain Cleveland
0%20%40%60%Count#Ann ArborOverland ParkMilton TownshipMiltonLisle TownshipLisleMadisonDowners Grove TownshipDowners GrvWashington TownshipWashingtonPalatine TownshipPalatineYork TownshipMinneapolisOlatheWheeling TownshipWheelingSchaumburg TownshipSchaumburgKaw TownshipSt. PaulMaine TownshipMaineFargoLincolnLawrence TownshipLawrenceChicagoCapital TownshipCapitalColumbusOmahaCincinnatiSt. LouisGrand RapidsBloomingdale TownshipBloomingdaleCedar RapidsUnited States of AmericaUnited StatesSioux FallsMidwestWichitaClevelandClevelandEast North CentralWisconsinSterling HeightsSterling HtsTopekaSpringfield TownshipSpringfieldProviso TownshipProvisoWorth TownshipWorthZIP Code 53015ZIP 53015Milwaukee010600Tract 010600Rockford TownshipRockfordAkronCenter TownshipCtrManitowoc Metro AreaManitowocManitowoc CountyManitowocNorth TownshipNThornton TownshipThorntonToledoDaytonWarrenWayne TownshipWayneKansas CityClevelandAurora TownshipAuroraBlue TownshipDetroit72.810169%72.810169%72.8%47,43047.4k158.823344%58.823344%58.8%74,57874.6k257.681507%57.681507%57.7%45,19045.2k356.900171%56.900171%56.9%46,35646.4k456.337583%56.337583%56.3%85,63285.6k553.762123%53.762123%53.8%55,71155.7k650.610540%50.610540%50.6%47,62347.6k749.860853%49.860853%49.9%39,77539.8k849.728972%49.728972%49.7%42,93542.9k947.670489%47.670489%47.7%127,663128k1046.512581%46.512581%46.5%38,59838.6k1146.409378%46.409378%46.4%51,46851.5k1241.792515%41.792515%41.8%39,02039.0k1341.581304%41.581304%41.6%50,61950.6k1439.969357%39.969357%40.0%74,08874.1k1539.511462%39.511462%39.5%38,91838.9k1638.241175%38.241175%38.2%26,96527.0k1737.146608%37.146608%37.1%62,25462.3k1836.577273%36.577273%36.6%29,32429.3k1936.546320%36.546320%36.5%669,666670k2036.298510%36.298510%36.3%28,78028.8k2134.685843%34.685843%34.7%185,460185k2234.651487%34.651487%34.7%99,56199.6k2333.783048%33.783048%33.8%64,52964.5k2433.007421%33.007421%33.0%72,14372.1k2532.904381%32.904381%32.9%39,86339.9k2632.623147%32.623147%32.6%25,12725.1k2731.793440%31.793440%31.8%27,10227.1k2830.315023%30.315023%30.3%64,767,78764.8M30.259813%30.259813%30.3%28,45328.5k2928.952816%28.952816%29.0%13,118,64213.1M28.877567%28.877567%28.9%71,75771.8k3028.679245%28.679245%28.7%30428.679245%28.679245%28.7%30428.462853%28.462853%28.5%8,931,6868.93M28.373439%28.373439%28.4%1,104,0821.10M27.532180%27.532180%27.5%25,60325.6k3127.007248%27.007248%27.0%22,95423.0k3226.964567%26.964567%27.0%27,92127.9k3326.237989%26.237989%26.2%27,03327.0k3425.217641%25.217641%25.2%26,38926.4k3524.887133%24.887133%24.9%44123.517740%23.517740%23.5%85,81285.8k3622.727273%22.727273%22.7%83021.592552%21.592552%21.6%25,23525.2k3720.213821%20.213821%20.2%26,69726.7k3820.139240%20.139240%20.1%19,93119.9k3919.658914%19.658914%19.7%11,21611.2k19.658914%19.658914%19.7%11,21611.2k19.650916%19.650916%19.7%20,02920.0k4018.971090%18.971090%19.0%21,01221.0k4118.048021%18.048021%18.0%33,17133.2k4217.635555%17.635555%17.6%15,51115.5k4317.280259%17.280259%17.3%15,89315.9k4416.826535%16.826535%16.8%14,78814.8k4516.167409%16.167409%16.2%15,13915.1k4616.073076%16.073076%16.1%40,94640.9k4715.929601%15.929601%15.9%14,19214.2k4815.821208%15.821208%15.8%16,95117.0k4913.833543%13.833543%13.8%59,72359.7k50
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 Cleveland, selected other county subdivisions in the Midwest, and entities that contain Cleveland
0%5%10%15%Count#Ann ArborMadisonDowners Grove TownshipDowners GrvWashington TownshipWashingtonMinneapolisYork TownshipOverland ParkLisle TownshipLisleSt. PaulKaw TownshipMilton TownshipMiltonSt. LouisCincinnatiLincolnChicagoFargoCapital TownshipCapitalOmahaMaine TownshipMainePalatine TownshipPalatineWheeling TownshipWheelingColumbusUnited States of AmericaUnited StatesTopekaGrand RapidsLawrence TownshipLawrenceSpringfield TownshipSpringfieldCedar RapidsMidwestEast North CentralSioux FallsOlatheWisconsinCenter TownshipCtrSchaumburg TownshipSchaumburgWichitaProviso TownshipProvisoAkronBloomingdale TownshipBloomingdaleRockford TownshipRockfordMilwaukeeWorth TownshipWorthClevelandZIP Code 53015ZIP 53015ToledoClevelandClevelandNorth TownshipNSterling HeightsSterling HtsKansas CityDetroit010600Tract 010600DaytonWayne TownshipWayneManitowoc Metro AreaManitowocManitowoc CountyManitowocWarrenBlue TownshipAurora TownshipAuroraThornton TownshipThornton17.877867%17.877867%17.9%11,64611.6k19.171173%9.171173%9.2%13,94013.9k27.658384%7.658384%7.7%7,93637.306290%7.306290%7.3%6,87546.241155%6.241155%6.2%16,71416.7k56.197734%6.197734%6.2%5,35165.940071%5.940071%5.9%7,53175.933545%5.933545%5.9%4,83485.920847%5.920847%5.9%10,97511.0k95.896414%5.896414%5.9%7,178105.800061%5.800061%5.8%4,544114.880448%4.880448%4.9%10,66710.7k124.729595%4.729595%4.7%9,034134.568292%4.568292%4.6%7,656144.485379%4.485379%4.5%82,18982.2k154.336789%4.336789%4.3%3,058164.233985%4.233985%4.2%3,357174.059919%4.059919%4.1%11,66511.7k184.030539%4.030539%4.0%3,970193.487439%3.487439%3.5%2,782203.407574%3.407574%3.4%3,779213.357865%3.357865%3.4%17,95418.0k223.336158%3.336158%3.3%7,127,6737.13M3.233245%3.233245%3.2%2,748233.174629%3.174629%3.2%3,846243.083448%3.083448%3.1%2,472252.911721%2.911721%2.9%3,015262.905776%2.905776%2.9%2,477272.893416%2.893416%2.9%1,311,0191.31M2.855432%2.855432%2.9%896,039896k2.841677%2.841677%2.8%2,672282.830666%2.830666%2.8%2,349292.703886%2.703886%2.7%105,215105k2.602914%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%4,911391.749436%1.749436%1.7%311.642065%1.642065%1.6%3,018401.603774%1.603774%1.6%171.603774%1.603774%1.6%171.575684%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%5,693441.314348%1.314348%1.3%481.257490%1.257490%1.3%1,106451.183365%1.183365%1.2%1,040461.074440%1.074440%1.1%6131.074440%1.074440%1.1%6131.047058%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 Cleveland, selected other county subdivisions in the Midwest, and entities that contain Cleveland
Female
Male
1x0x1xFM#ManitowocManitowocTract 010600Cedar RapidsLincolnDetroitZIP 53015OmahaToledoWisconsinThorntonKansas CityMadisonLawrenceFargoProvisoRockfordBlue TownshipWayneMidwestTopekaEast North CentralMilwaukeeKaw TownshipDaytonSioux FallsUnited StatesOlatheWorthNOverland ParkAuroraWheelingGrand RapidsSchaumburgChicagoWichitaColumbusClevelandPalatineCapitalWarrenSpringfieldYork TownshipSt. LouisWashingtonBloomingdaleCtrClevelandClevelandCincinnatiAkronAnn ArborSt. PaulLisleMinneapolisSterling HtsDowners GrvMiltonMaine-1.000000x-1.000000x1.389119x1.389119x1.39x7.638%7.64%10.610%10.6%-1.000000x-1.000000x1.389119x1.389119x1.39x7.638%7.64%10.610%10.6%-1.000000x-1.000000x1.250258x1.250258x1.25x8.739%8.74%10.927%10.9%-1.000000x-1.000000x1.243824x1.243824x1.24x5.354%5.35%6.660%6.66%1-1.000000x-1.000000x1.238529x1.238529x1.24x6.342%6.34%7.854%7.85%2-1.000000x-1.000000x1.237056x1.237056x1.24x18.951%19.0%23.443%23.4%3-1.000000x-1.000000x1.231994x1.231994x1.23x9.871%9.87%12.161%12.2%-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-1.000000x1.219291x1.219291x1.22x7.799%7.80%9.509%9.51%-1.000000x-1.000000x1.203250x1.203250x1.20x11.909%11.9%14.330%14.3%6-1.000000x-1.000000x1.189752x1.189752x1.19x20.748%20.7%24.685%24.7%7-1.000000x-1.000000x1.189278x1.189278x1.19x4.425%4.43%5.263%5.26%8-1.000000x-1.000000x1.181964x1.181964x1.18x9.406%9.41%11.117%11.1%9-1.000000x-1.000000x1.176963x1.176963x1.18x5.565%5.56%6.550%6.55%10-1.000000x-1.000000x1.174964x1.174964x1.17x14.460%14.5%16.990%17.0%11-1.000000x-1.000000x1.168755x1.168755x1.17x14.456%14.5%16.896%16.9%12-1.000000x-1.000000x1.161774x1.161774x1.16x13.244%13.2%15.387%15.4%13-1.000000x-1.000000x1.132245x1.132245x1.13x19.779%19.8%22.395%22.4%14-1.000000x-1.000000x1.127915x1.127915x1.13x9.647%9.65%10.881%10.9%-1.000000x-1.000000x1.125507x1.125507x1.13x10.423%10.4%11.732%11.7%15-1.000000x-1.000000x1.125371x1.125371x1.13x10.108%10.1%11.375%11.4%-1.000000x-1.000000x1.123984x1.123984x1.12x16.526%16.5%18.574%18.6%16-1.000000x-1.000000x1.115695x1.115695x1.12x11.779%11.8%13.142%13.1%17-1.000000x-1.000000x1.114342x1.114342x1.11x16.070%16.1%17.907%17.9%18-1.000000x-1.000000x1.110589x1.110589x1.11x9.201%9.20%10.219%10.2%19-1.000000x-1.000000x1.109070x1.109070x1.11x12.369%12.4%13.719%13.7%-1.000000x-1.000000x1.107847x1.107847x1.11x6.105%6.11%6.764%6.76%20-1.000000x-1.000000x1.099747x1.099747x1.10x10.199%10.2%11.216%11.2%21-1.000000x-1.000000x1.096598x1.096598x1.10x16.317%16.3%17.894%17.9%22-1.000000x-1.000000x1.095440x1.095440x1.10x3.232%3.23%3.540%3.54%23-1.000000x-1.000000x1.086583x1.086583x1.09x32.102%32.1%34.882%34.9%24-1.000000x-1.000000x1.079846x1.079846x1.08x8.111%8.11%8.758%8.76%25-1.000000x-1.000000x1.078480x1.078480x1.08x14.031%14.0%15.132%15.1%26-1.000000x-1.000000x1.077209x1.077209x1.08x7.467%7.47%8.043%8.04%27-1.000000x-1.000000x1.068021x1.068021x1.07x16.372%16.4%17.486%17.5%28-1.000000x-1.000000x1.059528x1.059528x1.06x12.215%12.2%12.942%12.9%29-1.000000x-1.000000x1.052237x1.052237x1.05x11.098%11.1%11.678%11.7%30-1.000000x-1.000000x1.046686x1.046686x1.05x21.119%21.1%22.105%22.1%31-1.000000x-1.000000x1.039581x1.039581x1.04x8.233%8.23%8.559%8.56%32-1.000000x-1.000000x1.039194x1.039194x1.04x8.470%8.47%8.802%8.80%33-1.000000x-1.000000x1.037373x1.037373x1.04x15.022%15.0%15.584%15.6%34-1.000000x-1.000000x1.028857x1.028857x1.03x10.622%10.6%10.928%10.9%35-1.000000x-1.000000x1.027464x1.027464x1.03x5.391%5.39%5.539%5.54%36-1.000000x-1.000000x1.018183x1.018183x1.02x15.334%15.3%15.613%15.6%37-1.000000x-1.000000x1.013146x1.013146x1.01x6.764%6.76%6.853%6.85%38-1.000000x-1.000000x1.007207x1.007207x1.01x12.130%12.1%12.217%12.2%39-1.000000x-1.000000x1.006204x1.006204x1.01x23.095%23.1%23.239%23.2%40-1.000000x-1.000000x1.001369x1.001369x1.00x13.010%13.0%13.028%13.0%-1.000000x-1.000000x1.001369x1.001369x1.00x13.010%13.0%13.028%13.0%-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 Cleveland, selected other county subdivisions in the Midwest, and entities that contain Cleveland
Female
Male
1x0x1x2xFM#RockfordNDaytonSioux FallsCapitalLawrenceDowners GrvAkronLisleManitowocManitowocWichitaYork TownshipMaineWarrenWheelingBlue TownshipSpringfieldTract 010600Overland ParkMiltonGrand RapidsOlatheOmahaFargoWashingtonEast North CentralLincolnMidwestBloomingdaleWisconsinKansas CityAuroraUnited StatesAnn ArborTopekaSterling HtsPalatineSchaumburgColumbusMadisonKaw TownshipMilwaukeeCedar RapidsClevelandCincinnatiSt. PaulSt. LouisChicagoWayneCtrToledoMinneapolisWorthClevelandClevelandDetroitProvisoZIP 53015Thornton-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-1.000000x1.806143x1.806143x1.81x0.769%0.77%1.390%1.39%-1.000000x-1.000000x1.806143x1.806143x1.81x0.769%0.77%1.390%1.39%-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-1.000000x1.743439x1.743439x1.74x0.952%0.95%1.660%1.66%-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-1.000000x1.597848x1.597848x1.60x2.216%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-1.000000x1.576114x1.576114x1.58x2.109%2.11%3.323%3.32%-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-1.000000x1.063073x1.063073x1.06x1.553%1.55%1.651%1.65%-1.000000x-1.000000x1.063073x1.063073x1.06x1.553%1.55%1.651%1.65%-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%49-1.014615x-1.014615x1.01x1.000000x1.000000x1.763%1.76%1.737%1.74%-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 Cleveland to the 50 most populous county subdivisions in the United States and to those entities that contain or substantially overlap with Cleveland. 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 Cleveland, selected other county subdivisions in the United States, and entities that contain Cleveland
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 StatesClevelandClevelandManhattanSan DiegoTampaSan JoseSan FranciscoTucsonAlbuquerqueTownship 1:Charlotte1, CharlotteColumbusTulsaZIP Code 53015ZIP 53015East North CentralSalt Lake CitySalt Lk CityTown of HempsteadHempsteadMidwestNorthwest HarrisNW HarrisWashington010600Tract 010600AtlantaManitowoc Metro AreaManitowocManitowoc CountyManitowocSeattleWisconsinNortheast 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%27,818,38027.8M13.018868%13.018868%13.0%13813.018868%13.018868%13.0%13812.996284%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%43,65343.7k4111.060948%11.060948%11.1%19610.719464%10.719464%10.7%3,363,7843.36M10.435356%10.435356%10.4%64,29464.3k4210.384134%10.384134%10.4%54,23054.2k4310.244520%10.244520%10.2%4,641,8354.64M10.135583%10.135583%10.1%47,67947.7k4410.045421%10.045421%10.0%46,51046.5k459.857612%9.857612%9.9%3609.538552%9.538552%9.5%37,37337.4k469.100310%9.100310%9.1%5,1929.100310%9.100310%9.1%5,1928.833573%8.833573%8.8%66,22066.2k478.637220%8.637220%8.6%336,096336k8.418271%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 Cleveland, selected other county subdivisions in the United States, and entities that contain Cleveland
0%20%40%60%Count#ManhattanSeattle EastWashingtonSan FranciscoPlanoSan JoseAtlantaSeattleBostonDenverAustinTownship 1:Charlotte1, CharlotteTown of HempsteadHempsteadSan DiegoNortheast TarrantNE TarrantNorthwest HarrisNW HarrisChicagoColumbusLos AngelesBrooklynSan Fernando ValleySan Fernando VlyNortheast DallasNE DallasSalt Lake CitySalt Lk CityAlbuquerqueTampaTucsonOceanside-EscondidoOceanside-Escond…TulsaQueensUnited States of AmericaUnited StatesHoustonBaltimoreLong Beach-LakewoodLong Bch-LakewoodMidwestPhoenixClevelandClevelandOrlandoEast North CentralAnaheim-Santa Ana-Garden GroveAnaheim-Santa An…WisconsinSacramentoEast San Gabriel ValleyE San Gabriel VlyOntarioPhiladelphiaMiamiZIP Code 53015ZIP 53015Fort WorthSouthwest DallasSW DallasMilwaukee010600Tract 010600FresnoLas VegasEl PasoManitowoc Metro AreaManitowocManitowoc CountyManitowocBronxSan BernardinoSan Antonio CentralSan Antonio CntrlDetroit60.434640%60.434640%60.4%747,953748k157.691220%57.691220%57.7%238,638239k255.360186%55.360186%55.4%256,316256k354.793235%54.793235%54.8%366,564367k454.142756%54.142756%54.1%195,588196k549.985845%49.985845%50.0%600,334600k649.803731%49.803731%49.8%195,136195k749.626221%49.626221%49.6%372,018372k846.377869%46.377869%46.4%206,036206k945.718966%45.718966%45.7%214,085214k1044.843364%44.843364%44.8%256,674257k1141.989192%41.989192%42.0%223,068223k1238.767308%38.767308%38.8%202,458202k1338.701072%38.701072%38.7%616,296616k1438.547398%38.547398%38.5%143,978144k1536.877886%36.877886%36.9%173,478173k1636.546320%36.546320%36.5%669,666670k1734.685843%34.685843%34.7%185,460185k1834.593243%34.593243%34.6%604,693605k1934.081468%34.081468%34.1%597,685598k2033.231104%33.231104%33.2%420,848421k2133.191099%33.191099%33.2%331,364331k2233.118385%33.118385%33.1%204,048204k2332.636312%32.636312%32.6%140,967141k2432.512191%32.512191%32.5%144,676145k2532.087814%32.087814%32.1%184,237184k2631.198303%31.198303%31.2%136,915137k2731.110082%31.110082%31.1%120,191120k2830.595789%30.595789%30.6%499,006499k2930.315023%30.315023%30.3%64,767,78764.8M30.080133%30.080133%30.1%627,520628k3029.719611%29.719611%29.7%125,423125k3129.113198%29.113198%29.1%109,693110k3228.952816%28.952816%29.0%13,118,64213.1M28.760152%28.760152%28.8%593,529594k3328.679245%28.679245%28.7%30428.679245%28.679245%28.7%30428.535877%28.535877%28.5%112,142112k3428.462853%28.462853%28.5%8,931,6868.93M28.412939%28.412939%28.4%312,038312k3528.373439%28.373439%28.4%1,104,0821.10M28.231204%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%178,455178k4024.887133%24.887133%24.9%44124.665414%24.665414%24.7%131,349131k4123.764821%23.764821%23.8%140,625141k4223.517740%23.517740%23.5%85,81285.8k4322.727273%22.727273%22.7%83022.486319%22.486319%22.5%94,05694.1k4421.702666%21.702666%21.7%271,037271k4521.071885%21.071885%21.1%72,12072.1k4619.658914%19.658914%19.7%11,21611.2k19.658914%19.658914%19.7%11,21611.2k19.131504%19.131504%19.1%173,169173k4716.375473%16.375473%16.4%80,59580.6k4814.929012%14.929012%14.9%65,34165.3k4913.833543%13.833543%13.8%59,72359.7k50
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older with a bachelor's degree or higher..

Very Advanced Degrees by County Subdivision#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 Cleveland, selected other county subdivisions in the United States, and entities that contain Cleveland
0%5%10%Count#WashingtonManhattanSan FranciscoBostonAtlantaSeattleSan JoseSeattle EastDenverSan DiegoAustinBaltimoreLos AngelesAlbuquerquePlanoChicagoTucsonTown of HempsteadHempsteadTampaMiamiNortheast DallasNE DallasSalt Lake CitySalt Lk CityHoustonPhiladelphiaSan Fernando ValleySan Fernando VlyTownship 1:Charlotte1, CharlotteOceanside-EscondidoOceanside-Escond…BrooklynSacramentoColumbusUnited States of AmericaUnited StatesTulsaPhoenixLong Beach-LakewoodLong Bch-LakewoodMidwestOrlandoEast North CentralFresnoAnaheim-Santa Ana-Garden GroveAnaheim-Santa An…QueensWisconsinNorthwest HarrisNW HarrisNortheast TarrantNE TarrantEast San Gabriel ValleyE San Gabriel VlyOntarioFort WorthLas VegasMilwaukeeSan BernardinoSan Antonio CentralSan Antonio CntrlZIP Code 53015ZIP 53015El PasoSouthwest DallasSW DallasBronxClevelandClevelandDetroit010600Tract 010600Manitowoc Metro AreaManitowocManitowoc CountyManitowoc12.461852%12.461852%12.5%57,69857.7k110.788423%10.788423%10.8%133,520134k27.558053%7.558053%7.6%50,56350.6k37.340604%7.340604%7.3%32,61132.6k46.889819%6.889819%6.9%26,99527.0k56.641855%6.641855%6.6%49,79049.8k66.255912%6.255912%6.3%75,13475.1k76.036065%6.036065%6.0%24,96825.0k85.725842%5.725842%5.7%26,81226.8k95.247128%5.247128%5.2%83,55883.6k105.058711%5.058711%5.1%28,95529.0k114.934352%4.934352%4.9%20,82420.8k124.659072%4.659072%4.7%81,44181.4k134.631274%4.631274%4.6%20,00420.0k144.617088%4.617088%4.6%16,67916.7k154.485379%4.485379%4.5%82,18982.2k164.461087%4.461087%4.5%25,61425.6k174.441262%4.441262%4.4%23,19423.2k184.325266%4.325266%4.3%19,24719.2k194.025531%4.025531%4.0%27,61827.6k203.827408%3.827408%3.8%38,21138.2k213.792624%3.792624%3.8%23,36723.4k223.737871%3.737871%3.7%77,97878.0k233.720350%3.720350%3.7%38,51538.5k243.601468%3.601468%3.6%45,61045.6k253.490252%3.490252%3.5%18,54218.5k263.466073%3.466073%3.5%15,21115.2k273.384967%3.384967%3.4%59,36259.4k283.380196%3.380196%3.4%25,05825.1k293.357865%3.357865%3.4%17,95418.0k303.336158%3.336158%3.3%7,127,6737.13M3.140490%3.140490%3.1%12,13312.1k313.010825%3.010825%3.0%62,13562.1k323.009440%3.009440%3.0%11,33911.3k332.893416%2.893416%2.9%1,311,0191.31M2.893233%2.893233%2.9%11,37011.4k342.855432%2.855432%2.9%896,039896k2.828959%2.828959%2.8%11,83311.8k352.763004%2.763004%2.8%30,34430.3k362.756960%2.756960%2.8%44,96545.0k372.703886%2.703886%2.7%105,215105k2.682967%2.682967%2.7%12,62112.6k382.630994%2.630994%2.6%9,827392.484535%2.484535%2.5%15,54715.5k402.324315%2.324315%2.3%9,688412.173239%2.173239%2.2%11,57311.6k422.155077%2.155077%2.2%26,91426.9k432.043126%2.043126%2.0%7,455441.807306%1.807306%1.8%8,895451.792414%1.792414%1.8%7,845461.749436%1.749436%1.7%311.745764%1.745764%1.7%5,975471.704476%1.704476%1.7%10,08610.1k481.664253%1.664253%1.7%15,06415.1k491.603774%1.603774%1.6%171.603774%1.603774%1.6%171.318660%1.318660%1.3%5,693501.314348%1.314348%1.3%481.074440%1.074440%1.1%6131.074440%1.074440%1.1%613
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 Cleveland, selected other county subdivisions in the United States, and entities that contain Cleveland
Female
Male
1x0x1xFM#ManitowocManitowoc1, CharlotteTract 010600DetroitZIP 53015WisconsinBaltimoreTulsaSW DallasMidwestFresnoEast North CentralMilwaukeeUnited StatesNE DallasHoustonHempsteadOrlandoPhiladelphiaOntarioSan BernardinoAustinAtlantaFort WorthPhoenixChicagoAlbuquerqueWashingtonSacramentoColumbusSalt Lk CityDenverNE TarrantTampaOceanside-EscondidoOceanside-Escond…NW HarrisBronxPlanoBrooklynSan Antonio CntrlSan Fernando VlyClevelandClevelandTucsonAnaheim-Santa Ana-Gdn GrvAnaheim-Santa An…Los AngelesLas VegasBostonE San Gabriel VlyQueensMiamiManhattanSeattleLong Bch-LakewoodSeattle EastSan JoseSan DiegoSan FranciscoEl Paso-1.000000x-1.000000x1.389119x1.389119x1.39x7.638%7.64%10.610%10.6%-1.000000x-1.000000x1.389119x1.389119x1.39x7.638%7.64%10.610%10.6%-1.000000x-1.000000x1.285784x1.285784x1.29x10.185%10.2%13.096%13.1%1-1.000000x-1.000000x1.250258x1.250258x1.25x8.739%8.74%10.927%10.9%-1.000000x-1.000000x1.237056x1.237056x1.24x18.951%19.0%23.443%23.4%2-1.000000x-1.000000x1.231994x1.231994x1.23x9.871%9.87%12.161%12.2%-1.000000x-1.000000x1.219291x1.219291x1.22x7.799%7.80%9.509%9.51%-1.000000x-1.000000x1.179669x1.179669x1.18x15.289%15.3%18.036%18.0%3-1.000000x-1.000000x1.177766x1.177766x1.18x10.417%10.4%12.268%12.3%4-1.000000x-1.000000x1.160109x1.160109x1.16x22.304%22.3%25.875%25.9%5-1.000000x-1.000000x1.127915x1.127915x1.13x9.647%9.65%10.881%10.9%-1.000000x-1.000000x1.127206x1.127206x1.13x20.830%20.8%23.479%23.5%6-1.000000x-1.000000x1.125371x1.125371x1.13x10.108%10.1%11.375%11.4%-1.000000x-1.000000x1.123984x1.123984x1.12x16.526%16.5%18.574%18.6%7-1.000000x-1.000000x1.109070x1.109070x1.11x12.369%12.4%13.719%13.7%-1.000000x-1.000000x1.099797x1.099797x1.10x19.814%19.8%21.791%21.8%8-1.000000x-1.000000x1.099188x1.099188x1.10x20.902%20.9%22.975%23.0%9-1.000000x-1.000000x1.092101x1.092101x1.09x9.951%9.95%10.868%10.9%10-1.000000x-1.000000x1.090284x1.090284x1.09x13.111%13.1%14.294%14.3%11-1.000000x-1.000000x1.090163x1.090163x1.09x16.700%16.7%18.206%18.2%12-1.000000x-1.000000x1.088515x1.088515x1.09x16.417%16.4%17.871%17.9%13-1.000000x-1.000000x1.081887x1.081887x1.08x26.536%26.5%28.709%28.7%14-1.000000x-1.000000x1.078150x1.078150x1.08x13.148%13.1%14.176%14.2%15-1.000000x-1.000000x1.073220x1.073220x1.07x9.215%9.21%9.889%9.89%16-1.000000x-1.000000x1.071348x1.071348x1.07x19.379%19.4%20.762%20.8%17-1.000000x-1.000000x1.069008x1.069008x1.07x14.467%14.5%15.465%15.5%18-1.000000x-1.000000x1.068021x1.068021x1.07x16.372%16.4%17.486%17.5%19-1.000000x-1.000000x1.066879x1.066879x1.07x11.714%11.7%12.497%12.5%20-1.000000x-1.000000x1.064309x1.064309x1.06x9.751%9.75%10.378%10.4%21-1.000000x-1.000000x1.053268x1.053268x1.05x13.558%13.6%14.280%14.3%22-1.000000x-1.000000x1.052237x1.052237x1.05x11.098%11.1%11.678%11.7%23-1.000000x-1.000000x1.051272x1.051272x1.05x10.176%10.2%10.697%10.7%24-1.000000x-1.000000x1.049933x1.049933x1.05x13.307%13.3%13.971%14.0%25-1.000000x-1.000000x1.040742x1.040742x1.04x8.257%8.26%8.594%8.59%26-1.000000x-1.000000x1.040003x1.040003x1.04x12.734%12.7%13.244%13.2%27-1.000000x-1.000000x1.039910x1.039910x1.04x15.694%15.7%16.321%16.3%28-1.000000x-1.000000x1.038394x1.038394x1.04x9.953%9.95%10.335%10.3%29-1.000000x-1.000000x1.030539x1.030539x1.03x28.448%28.4%29.316%29.3%30-1.000000x-1.000000x1.023151x1.023151x1.02x5.652%5.65%5.783%5.78%31-1.000000x-1.000000x1.018960x1.018960x1.02x19.845%19.8%20.221%20.2%32-1.000000x-1.000000x1.003929x1.003929x1.00x28.944%28.9%29.058%29.1%33-1.000000x-1.000000x1.003840x1.003840x1.00x19.308%19.3%19.383%19.4%34-1.000000x-1.000000x1.001369x1.001369x1.00x13.010%13.0%13.028%13.0%-1.000000x-1.000000x1.001369x1.001369x1.00x13.010%13.0%13.028%13.0%-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 Cleveland, selected other county subdivisions in the United States, and entities that contain Cleveland
Female
Male
1x0x1x2xFM#El PasoSalt Lk CityManitowocManitowocPlanoTract 010600TulsaAlbuquerqueNE DallasFort WorthOrlandoPhoenixTucson1, CharlotteEast North CentralMidwestNW HarrisLas VegasWisconsinSeattle 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 FranciscoClevelandClevelandDetroitZIP 53015-1.000000x-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-1.000000x1.806143x1.806143x1.81x0.769%0.77%1.390%1.39%-1.000000x-1.000000x1.806143x1.806143x1.81x0.769%0.77%1.390%1.39%-1.000000x-1.000000x1.782054x1.782054x1.78x3.355%3.35%5.978%5.98%3-1.000000x-1.000000x1.743439x1.743439x1.74x0.952%0.95%1.660%1.66%-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-1.000000x1.597848x1.597848x1.60x2.216%2.22%3.541%3.54%-1.000000x-1.000000x1.589934x1.589934x1.59x2.251%2.25%3.579%3.58%-1.000000x-1.000000x1.579303x1.579303x1.58x2.100%2.10%3.317%3.32%12-1.000000x-1.000000x1.576623x1.576623x1.58x1.677%1.68%2.643%2.64%13-1.000000x-1.000000x1.576114x1.576114x1.58x2.109%2.11%3.323%3.32%-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-1.000000x1.063073x1.063073x1.06x1.553%1.55%1.651%1.65%-1.000000x-1.000000x1.063073x1.063073x1.06x1.553%1.55%1.651%1.65%-1.000000x-1.000000x1.046557x1.046557x1.05x1.291%1.29%1.351%1.35%50-1.014615x-1.014615x1.01x1.000000x1.000000x1.763%1.76%1.737%1.74%
F percentage of females in category
M percentage of males in category
# rank of county subdivision out of 50 by male-to-female sex ratio

Definitions

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

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

The coarse levels of educational attainment are as follows:

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

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

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State:
Wisconsin
County:
Manitowoc
Metro Area:
Manitowoc Area
Village:
Cleveland
ZIP Code:
53015
Unified School Districts:
Manitowoc, Sheboygan
Congressional District:
WI-6
State Senate District:
WI-9
Assembly District:
WI-27
Neighboring Towns:
Centerville
Nearby Towns:
Herman, Liberty, Meeme, Mosel, Newton, Schleswig, Sheboygan, Sheboygan Falls