Educational Attainment in Wooster, Wayne County, Ohio (City)

Educational Attainment#1

Highest level of education among people aged 25 years and older.
Scope: population of Wayne County and Wooster
Wooster
Wayne County
0%10%20%30%40%50%CountHigher Degree1H.S. Diploma2No H.S. Diploma235.872979%28.690929%35.872979%35.9%6,16854.239851%56.735649%54.239851%54.2%9,3269.887170%14.573422%9.887170%9.9%1,700
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 Wayne County at large.
Scope: population of Wayne County and Wooster
-20%0%+20%%ref.Higher Degree1H.S. Diploma2No H.S. Diploma225.032475%25.032475%+25.0%35.873%35.9%28.691%28.7%-4.398993%-4.398993%-4.4%54.240%54.2%56.736%56.7%-32.156155%-32.156155%-32.2%9.887%9.89%14.573%14.6%
% percentage with given level in Wooster
ref. percentage with given level in Wayne 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 Wayne County and Wooster
Wooster
Wayne County
0%10%20%30%40%CountDoctorate1Professional1Master's1Bachelor's1Associate's1Some CollegeHigh School2Some H.S.3Less than H.S.3None2.378737%1.050587%2.378737%2.4%4091.971618%1.176129%1.971618%2.0%3398.485518%5.950682%8.485518%8.5%1,45915.912528%13.290253%15.912528%15.9%2,7367.124578%7.223279%7.124578%7.1%1,22519.349773%16.204144%19.349773%19.3%3,32734.890078%40.531504%34.890078%34.9%5,9997.967896%7.803415%7.967896%8.0%1,3701.442364%5.948039%1.442364%1.4%2480.476911%0.821968%0.476911%0.5%82
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 Wayne County at large.
Scope: population of Wayne County and Wooster
-100%0%+100%%ref.Doctorate1Professional1Master's1Bachelor's1Associate's1Some CollegeHigh School2Some H.S.3Less than H.S.3None126.419835%126.419835%+126.4%2.379%2.38%1.051%1.05%67.636267%67.636267%+67.6%1.972%1.97%1.176%1.18%42.597409%42.597409%+42.6%8.486%8.49%5.951%5.95%19.730813%19.730813%+19.7%15.913%15.9%13.290%13.3%-1.366430%-1.366430%-1.4%7.125%7.12%7.223%7.22%19.412497%19.412497%+19.4%19.350%19.3%16.204%16.2%-13.918621%-13.918621%-13.9%34.890%34.9%40.532%40.5%2.107809%2.107809%+2.1%7.968%7.97%7.803%7.80%-75.750602%-75.750602%-75.8%1.442%1.44%5.948%5.95%-41.979461%-41.979461%-42.0%0.477%0.48%0.822%0.82%
% percentage with given level in Wooster
ref. percentage with given level in Wayne 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 Wayne County and Wooster
More Females More Males
Wayne County
Wooster
10%0%10%FMHigher Degree1H.S. Diploma2No H.S. Diploma2-3.873989%-11.475025%-3.873989%4%36.502%36.5%35.141%35.1%3.418560%1.874005%3.418560%3%53.396%53.4%55.221%55.2%-4.814671%-4.814671%5%15.137945%10.102%10.1%9.638%9.64%
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 Wayne County and Wooster
More Females More Males
Wayne County
Wooster
0%100%FMDoctorate1Professional1Master's1Bachelor's1Associate's1Some CollegeHigh School2Some H.S.3Less than H.S.3None114.081635%73.030403%114.081635%114%1.557%1.56%3.334%3.33%174.126874%59.737864%174.126874%174%1.092%1.09%2.994%2.99%-16.700611%0.434047%0.434047%0%8.469%8.47%8.505%8.51%-8.410946%-11.028613%-8.410946%8%16.504%16.5%15.224%15.2%-74.689081%-30.748344%-74.689081%75%8.880%8.88%5.083%5.08%21.990119%0.340357%21.990119%22%17.564%17.6%21.427%21.4%-6.027714%-6.027714%6%2.493542%35.832%35.8%33.795%33.8%-8.695116%-8.695116%9%12.850557%8.274%8.27%7.612%7.61%5.592892%11.751161%5.592892%6%1.406%1.41%1.485%1.48%28.262553%74.552288%28.262553%28%0.422%0.42%0.541%0.54%
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 Wayne County and Wooster
Wooster
Wayne County
0%5%10%15%B.X.Total65+45-6435-4425-3411.369722%9.442475%11.369722%11.4%5524,85517.249757%12.804181%17.249757%17.2%1,0656,17419.828594%16.532808%19.828594%19.8%5092,56716.953863%16.592402%16.953863%17.0%6103,598
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 Wayne County at large.
Scope: population of Wayne County and Wooster
0%10%20%30%%ref.65+45-6435-4425-3420.410400%20.410400%20.4%11.370%11.4%9.442%9.44%34.719722%34.719722%34.7%17.250%17.2%12.804%12.8%19.934821%19.934821%19.9%19.829%19.8%16.533%16.5%2.178472%2.178472%2.2%16.954%17.0%16.592%16.6%
% percentage in Wooster with a Bachelor's degree
ref percentage in Wayne 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 Wayne County and Wooster
More Females More Males
Wayne County
Wooster
30%20%10%0%10%FM65+45-6435-4425-34-9.434698%-9.434698%9.4%18.919144%11.789%11.8%10.773%10.8%-11.374781%0.969462%0.969462%1.0%17.173%17.2%17.339%17.3%-30.546003%-38.371695%-30.546003%30.5%22.494%22.5%17.231%17.2%-20.343681%-20.928419%-20.343681%20.3%18.514%18.5%15.385%15.4%
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 Wayne County and Wooster
Wooster
Wayne County
$0k$20k$40kCount%Graduate Degree1Bachelor's DegreeSome CollegeH.S. Diploma2No H.S. Diploma2Total$48,750.000000$56,783.000000$48,750.000000$48.8k2,20712.836%12.8%$40,154.000000$42,343.000000$40,154.000000$40.2k2,73615.913%15.9%$30,131.000000$31,606.000000$30,131.000000$30.1k4,55226.474%26.5%$25,368.000000$30,746.000000$25,368.000000$25.4k5,99934.890%34.9%$11,880.000000$25,562.000000$11,880.000000$11.9k1,7009.887%9.89%$31,395.000000$33,187.000000$31,395.000000$31.4k17,19417.2k100.000%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 Wayne County and Wooster
Female Male
Wayne County
Wooster
Shaded bar tips show excess over facing bar.
$0k$50kFMGraduate Degree1Bachelor's DegreeSome CollegeH.S. Diploma2No H.S. Diploma2Total$-38,750.000000$-49,479.000000$-38,750.000000$38.8k$38,750.000000$19,946.000000$49,479.000000$15,139.000000$58,696.000000$58.7k1,0281,179$-30,532.000000$-31,704.000000$-30,532.000000$30.5k$30,532.000000$16,890.000000$31,704.000000$22,192.000000$47,422.000000$47.4k1,5261,210$-21,250.000000$-25,292.000000$-21,250.000000$21.3k$21,250.000000$16,152.000000$25,292.000000$15,808.000000$37,402.000000$37.4k2,4452,107$-19,152.000000$-20,631.000000$-19,152.000000$19.2k$19,152.000000$14,911.000000$20,631.000000$18,012.000000$34,063.000000$34.1k3,3132,686$-9,007.000000$-17,564.000000$-9,007.000000$9.0k$9,007.000000$3,902.000000$17,564.000000$13,714.000000$12,909.000000$12.9k934766$-22,098.000000$-24,415.000000$-22,098.000000$22.1k$22,098.000000$17,955.000000$24,415.000000$16,810.000000$40,053.000000$40.1k9,2467,948
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

Composition of the Armed Forces by Educational Attainment#12

Percentage of the armed forces aged 25 to 64 years old with various highest levels of educational attainment.
Scope: population of Wayne County and Wooster
Wooster
Wayne County
0%20%40%60%80%100%CountBachelor's Degree1Some College2H.S. Diploma3No H.S. Diploma30.000000%0.000000%0.0%36.842105%0100.000000%63.157895%100.000000%100.0%120.000000%0.000000%0.000000%0.0%00.000000%0.000000%0.000000%0.0%0
Count members of the armed forces with the given level of educational attainment
1or higher 2two or four year institution 3H.S. = High School

Employment by Educational Attainment#13

Percentage of population that is employed by highest level of educational attainment among the population aged 25 to 64 years old.
Scope: population of Wayne County and Wooster
Wooster
Wayne County
0%20%40%60%80%CountBachelor's Degree1Some College2H.S. Diploma3No H.S. Diploma386.100079%86.724717%86.100079%86.1%3,25275.036754%78.040233%75.036754%75.0%2,55265.659543%73.426542%65.659543%65.7%2,67341.651376%56.347116%41.651376%41.7%454
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#14

Percent of racial or ethnic group lacking a high school diploma (or equivalent).
Scope: population of Wayne County and Wooster
Female Male
Wayne County
Wooster
Shaded bar tips show excess over facing bar.
30%20%10%0%10%20%MFWhite1BlackAsianHispanic2Other1-9.052394%-1.286807%-13.161422%-10.339200%10.3%9.052394%13.161422%2.377469%9.052394%9.1%641887-3.112840%-12.711864%-3.112840%3.1%3.112840%3.206862%12.711864%0.277459%6.319703%6.3%178-10.300429%-20.679012%-10.215297%-10.300429%10.3%10.300429%8.958830%20.679012%19.259259%19.3%5224-11.194030%-27.504244%-6.552155%-11.194030%11.2%11.194030%6.324218%27.504244%17.518248%17.5%2415-0.000000%-11.559889%-12.332212%0.000000%0.0%0.000000%13.733906%11.559889%13.733906%13.7%320
M number of males in category
F number of females in category
1non-Hispanic 2excluding black and Asian Hispanics

College Graduates By Race#15

Percent of racial or ethnic group with a bachelor's degree or higher.
Scope: population of Wayne County and Wooster
Female Male
Wayne County
Wooster
Shaded bar tips show excess over facing bar.
50%0%50%MFWhite1BlackAsianHispanic2Other1-26.937872%-20.162055%-1.764713%-26.937872%26.9%26.937872%1.165504%20.162055%28.103375%28.1%1,9902,311-7.003891%-13.983051%-7.003891%7.0%7.003891%5.263767%13.983051%3.098800%12.267658%12.3%3318-63.090129%-43.360434%-63.090129%63.1%63.090129%5.798760%43.360434%24.849443%68.888889%68.9%186147-36.567164%-16.919740%-36.567164%36.6%36.567164%20.367142%16.919740%10.754284%56.934307%56.9%7849-61.802575%-11.274348%-26.204239%-73.076923%73.1%61.802575%26.204239%7.918324%61.802575%61.8%14438
M number of males in category
F number of females in category
1non-Hispanic 2excluding black and Asian Hispanics

Map of Educational Attainment by Tract in Wooster

Coarse: Post-Secondary Degree Educational Attainment by Tract#16

Percentage of the population 25 years and older with given highest level of educational attainment
22%30%37%44%51%58%

Coarse: High School Diploma Educational Attainment by Tract#17

Percentage of the population 25 years and older with given highest level of educational attainment
39%45%50%55%60%66%

Coarse: No High School Diploma Educational Attainment by Tract#18

Percentage of the population 25 years and older with given highest level of educational attainment
2.6%5.2%7.7%10.2%12.7%15.2%

Detailed: Doctorate Degree Educational Attainment by Tract#19

Percentage of the population 25 years and older with given highest level of educational attainment
0.0%0.9%1.8%2.8%3.7%4.7%

Detailed: Professional Degree Educational Attainment by Tract#20

Percentage of the population 25 years and older with given highest level of educational attainment
0.0%0.7%1.5%2.2%2.9%3.7%

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

Percentage of the population 25 years and older with given highest level of educational attainment
3.9%6.9%9.9%13.0%16.0%19.0%

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

Percentage of the population 25 years and older with given highest level of educational attainment
6.5%10.5%14.5%18.5%22.5%26.5%

Detailed: Associate's Degree Educational Attainment by Tract#23

Percentage of the population 25 years and older with given highest level of educational attainment
4.8%5.8%6.7%7.6%8.5%9.5%

Detailed: Some College Educational Attainment by Tract#24

Percentage of the population 25 years and older with given highest level of educational attainment
7.4%10.1%12.7%15.2%17.8%20.5%

Detailed: High School Diploma or Equivalent Educational Attainment by Tract#25

Percentage of the population 25 years and older with given highest level of educational attainment
25%32%38%45%51%58%

Detailed: Some High School Educational Attainment by Tract#26

Percentage of the population 25 years and older with given highest level of educational attainment
1.6%3.4%5.1%6.8%8.6%10.4%

Detailed: Less than High School Educational Attainment by Tract#27

Percentage of the population 25 years and older with given highest level of educational attainment
0.0%0.7%1.5%2.2%3.0%3.7%

Detailed: None Educational Attainment by Tract#28

Percentage of the population 25 years and older with given highest level of educational attainment
0.00%0.43%0.87%1.30%1.73%2.17%
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Educational Attainment by County Subdivision in the Wooster Area

There are 19 county subdivisions in the Wooster Area. This section compares Wooster to all of the county subdivisions in the Wooster Area and to those entities that contain or substantially overlap with Wooster.

No H.S. Diploma by County Subdivision#29

Percent of population 25 years of age and older without a high school diploma (or equivalent).
Scope: population of Wooster, selected other county subdivisions in the Wooster Area, and entities that contain Wooster
0%20%40%60%Count#Paint TownshipPaintSalt Creek TownshipSalt CrkFranklin TownshipFranklinEast Union TownshipE UnionSugar Creek TownshipSugar CrkWooster Metro AreaWooster AreaWayne CountyWayneUnited States of AmericaUnited StatesMilton TownshipMiltonRittmanCongress TownshipCongressBaughman TownshipBaughmanEast North CentralChester TownshipChesterOhioMidwestZIP Code 44691ZIP 44691Chippewa TownshipChippewaWoosterWoosterWooster TownshipWoosterWayne TownshipWayneGreen TownshipGrnCanaan TownshipCanaanClinton TownshipClintonPlain TownshipPlain64.091197%64.091197%64.1%1,012154.963325%54.963325%55.0%1,124230.699328%30.699328%30.7%777328.670788%28.670788%28.7%1,113419.014085%19.014085%19.0%783514.573422%14.573422%14.6%11,02811.0k14.573422%14.573422%14.6%11,02811.0k13.020590%13.020590%13.0%27,818,38027.8M13.019802%13.019802%13.0%263612.864814%12.864814%12.9%551712.076341%12.076341%12.1%367811.045943%11.045943%11.0%339910.719464%10.719464%10.7%3,363,7843.36M10.621635%10.621635%10.6%2171010.514146%10.514146%10.5%825,155825k10.244520%10.244520%10.2%4,641,8354.64M10.188151%10.188151%10.2%3,0549.987703%9.987703%10.0%731119.887170%9.887170%9.9%1,7009.887170%9.887170%9.9%1,700129.876881%9.876881%9.9%361139.476565%9.476565%9.5%277149.278351%9.278351%9.3%783158.835726%8.835726%8.8%277168.456562%8.456562%8.5%183177.609669%7.609669%7.6%17018
Count number of people in category
# rank of county subdivision out of 18 by percentage of population 25 years of age and older without a high school diploma (or equivalent).

Bachelor's Degrees by County Subdivision#30

Percent of population 25 years of age and older with a bachelor's degree or higher..
Scope: population of Wooster, selected other county subdivisions in the Wooster Area, and entities that contain Wooster
0%10%20%30%Count#United States of AmericaUnited StatesWayne TownshipWayneMidwestWoosterWoosterEast North CentralOhioZIP Code 44691ZIP 44691Green TownshipGrnChippewa TownshipChippewaChester TownshipChesterPlain TownshipPlainWooster Metro AreaWooster AreaWayne CountyWayneWooster TownshipWoosterSugar Creek TownshipSugar CrkBaughman TownshipBaughmanFranklin TownshipFranklinRittmanMilton TownshipMiltonEast Union TownshipE UnionCongress TownshipCongressClinton TownshipClintonCanaan TownshipCanaanSalt Creek TownshipSalt CrkPaint TownshipPaint30.315023%30.315023%30.3%64,767,78764.8M29.729730%29.729730%29.7%869128.952816%28.952816%29.0%13,118,64213.1M28.748401%28.748401%28.7%4,94328.748401%28.748401%28.7%4,943228.462853%28.462853%28.5%8,931,6868.93M26.667466%26.667466%26.7%2,092,8752.09M26.577929%26.577929%26.6%7,96725.370305%25.370305%25.4%2,141323.705424%23.705424%23.7%1,735422.662751%22.662751%22.7%463522.023277%22.023277%22.0%492621.467650%21.467650%21.5%16,24516.2k21.467650%21.467650%21.5%16,24516.2k20.191518%20.191518%20.2%738719.694026%19.694026%19.7%811818.116650%18.116650%18.1%556917.542473%17.542473%17.5%4441016.180247%16.180247%16.2%6931115.049505%15.049505%15.0%3041214.786193%14.786193%14.8%5741314.346825%14.346825%14.3%4361414.325323%14.325323%14.3%3101513.429027%13.429027%13.4%4211611.246944%11.246944%11.2%230175.383154%5.383154%5.4%8518
Count number of people in category
# rank of county subdivision out of 18 by percentage of population 25 years of age and older with a bachelor's degree or higher..

Very Advanced Degrees by County Subdivision#31

Percent of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).
Scope: population of Wooster, selected other county subdivisions in the Wooster Area, and entities that contain Wooster
0%1%2%3%4%Count#WoosterWoosterZIP Code 44691ZIP 44691United States of AmericaUnited StatesChester TownshipChesterMidwestEast North CentralPlain TownshipPlainOhioWayne TownshipWayneWooster Metro AreaWooster AreaWayne CountyWayneWooster TownshipWoosterChippewa TownshipChippewaFranklin TownshipFranklinPaint TownshipPaintGreen TownshipGrnCongress TownshipCongressEast Union TownshipE UnionMilton TownshipMiltonSugar Creek TownshipSugar CrkBaughman TownshipBaughmanSalt Creek TownshipSalt CrkCanaan TownshipCanaanRittmanClinton TownshipClinton4.350355%4.350355%4.4%7484.350355%4.350355%4.4%74813.649586%3.649586%3.6%1,0943.336158%3.336158%3.3%7,127,6737.13M3.328439%3.328439%3.3%6822.893416%2.893416%2.9%1,311,0191.31M2.855432%2.855432%2.9%896,039896k2.820054%2.820054%2.8%6332.683241%2.683241%2.7%210,582211k2.565857%2.565857%2.6%7542.226715%2.226715%2.2%1,6852.226715%2.226715%2.2%1,6852.134063%2.134063%2.1%7851.926493%1.926493%1.9%14161.896484%1.896484%1.9%4871.836605%1.836605%1.8%2981.765612%1.765612%1.8%14991.447845%1.447845%1.4%44101.442555%1.442555%1.4%56111.386139%1.386139%1.4%28121.165614%1.165614%1.2%48131.010101%1.010101%1.0%31140.929095%0.929095%0.9%19150.893142%0.893142%0.9%28160.583703%0.583703%0.6%25170.323475%0.323475%0.3%718
Count number of people in category
# rank of county subdivision out of 18 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#32

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 Wooster, selected other county subdivisions in the Wooster Area, and entities that contain Wooster
Female
Male
1x0x1x2xFM#WoosterChesterMiltonWayneCanaanCongressFranklinZIP 44691E UnionSugar CrkWooster AreaWayneMidwestEast North CentralUnited StatesOhioRittmanGrnWoosterWoosterSalt CrkPaintBaughmanChippewaPlainClinton-1.000000x-1.000000x2.911209x2.911209x2.91x5.135%5.13%14.949%14.9%1-1.000000x-1.000000x2.640141x2.640141x2.64x5.726%5.73%15.117%15.1%2-1.000000x-1.000000x2.389853x2.389853x2.39x7.722%7.72%18.455%18.5%3-1.000000x-1.000000x2.289639x2.289639x2.29x5.989%5.99%13.712%13.7%4-1.000000x-1.000000x1.442687x1.442687x1.44x7.279%7.28%10.502%10.5%5-1.000000x-1.000000x1.366759x1.366759x1.37x10.072%10.1%13.766%13.8%6-1.000000x-1.000000x1.317931x1.317931x1.32x26.325%26.3%34.694%34.7%7-1.000000x-1.000000x1.287259x1.287259x1.29x8.969%8.97%11.546%11.5%-1.000000x-1.000000x1.261586x1.261586x1.26x25.290%25.3%31.905%31.9%8-1.000000x-1.000000x1.181763x1.181763x1.18x17.475%17.5%20.652%20.7%9-1.000000x-1.000000x1.151379x1.151379x1.15x13.576%13.6%15.631%15.6%-1.000000x-1.000000x1.151379x1.151379x1.15x13.576%13.6%15.631%15.6%-1.000000x-1.000000x1.127915x1.127915x1.13x9.647%9.65%10.881%10.9%-1.000000x-1.000000x1.125371x1.125371x1.13x10.108%10.1%11.375%11.4%-1.000000x-1.000000x1.109070x1.109070x1.11x12.369%12.4%13.719%13.7%-1.000000x-1.000000x1.105363x1.105363x1.11x10.008%10.0%11.063%11.1%-1.000000x-1.000000x1.008050x1.008050x1.01x12.816%12.8%12.919%12.9%10-1.043025x-1.043025x1.04x1.000000x1.000000x9.460%9.46%9.070%9.07%11-1.048147x-1.048147x1.05x1.000000x1.000000x10.102%10.1%9.638%9.64%-1.048147x-1.048147x1.05x1.000000x1.000000x10.102%10.1%9.638%9.64%12-1.087881x-1.087881x1.09x1.000000x1.000000x57.344%57.3%52.712%52.7%13-1.088156x-1.088156x1.09x1.000000x1.000000x66.838%66.8%61.423%61.4%14-1.114551x-1.114551x1.11x1.000000x1.000000x11.666%11.7%10.467%10.5%15-1.223219x-1.223219x1.22x1.000000x1.000000x10.979%11.0%8.975%8.98%16-1.394674x-1.394674x1.39x1.000000x1.000000x8.829%8.83%6.330%6.33%17-1.517398x-1.517398x1.52x1.000000x1.000000x10.154%10.2%6.692%6.69%18
F percentage of females in category
M percentage of males in category
# rank of county subdivision out of 18 by male-to-female sex ratio

Over-Education Sex Ratio by County Subdivision#33

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 Wooster, selected other county subdivisions in the Wooster Area, and entities that contain Wooster
Female
Male
0x5x10xFM#CanaanWoosterPlainMiltonBaughmanPaintWoosterWoosterZIP 44691WayneOhioWooster AreaWayneEast North CentralMidwestUnited StatesFranklinSugar CrkGrnClintonChesterChippewaE UnionRittmanCongressSalt Crk-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%1.849%1.85%1-1.000000x-1.000000x8.200642x8.200642x8.20x0.476%0.48%3.907%3.91%2-1.000000x-1.000000x6.297248x6.297248x6.30x0.787%0.79%4.954%4.95%3-1.000000x-1.000000x6.156469x6.156469x6.16x0.391%0.39%2.407%2.41%4-1.000000x-1.000000x3.896070x3.896070x3.90x0.405%0.40%1.576%1.58%5-1.000000x-1.000000x2.549625x2.549625x2.55x1.028%1.03%2.622%2.62%6-1.000000x-1.000000x2.388350x2.388350x2.39x2.650%2.65%6.329%6.33%-1.000000x-1.000000x2.388350x2.388350x2.39x2.650%2.65%6.329%6.33%7-1.000000x-1.000000x2.368602x2.368602x2.37x2.215%2.22%5.248%5.25%-1.000000x-1.000000x2.038447x2.038447x2.04x1.747%1.75%3.561%3.56%8-1.000000x-1.000000x1.669500x1.669500x1.67x2.031%2.03%3.391%3.39%-1.000000x-1.000000x1.658480x1.658480x1.66x1.687%1.69%2.798%2.80%-1.000000x-1.000000x1.658480x1.658480x1.66x1.687%1.69%2.798%2.80%-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-1.000000x1.526215x1.526215x1.53x2.660%2.66%4.060%4.06%-1.000000x-1.000000x1.278307x1.278307x1.28x1.656%1.66%2.116%2.12%9-1.000000x-1.000000x1.257644x1.257644x1.26x1.036%1.04%1.303%1.30%10-1.099227x-1.099227x1.10x1.000000x1.000000x1.843%1.84%1.677%1.68%11-1.282563x-1.282563x1.28x1.000000x1.000000x0.363%0.36%0.283%0.28%12-1.299723x-1.299723x1.30x1.000000x1.000000x3.783%3.78%2.911%2.91%13-1.675901x-1.675901x1.68x1.000000x1.000000x2.407%2.41%1.436%1.44%14-1.742185x-1.742185x1.74x1.000000x1.000000x1.844%1.84%1.058%1.06%15-1.911086x-1.911086x1.91x1.000000x1.000000x0.754%0.75%0.394%0.39%16-2.076079x-2.076079x2.08x1.000000x1.000000x2.014%2.01%0.970%0.97%17-2.290912x-2.290912x2.29x1.000000x1.000000x1.308%1.31%0.571%0.57%18
F percentage of females in category
M percentage of males in category
# rank of county subdivision out of 18 by male-to-female sex ratio

Educational Attainment by County Subdivision in Ohio

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

No H.S. Diploma by County Subdivision#34

Percent of population 25 years of age and older without a high school diploma (or equivalent).
Scope: population of Wooster, selected other county subdivisions in Ohio, and entities that contain Wooster
0%5%10%15%20%Count#ClevelandMiddletownLorainYoungstownSpringfieldDaytonMansfieldLimaMarion TownshipMarionCantonHamiltonWarrenWooster Metro AreaWooster AreaWayne CountyWayneToledoCincinnatiAkronElyriaUnited States of AmericaUnited StatesNewarkBath TownshipLancaster City TownshipLancaster CityColumbusColerain TownshipColerainEast North CentralEuclidOhioMidwestZIP Code 44691ZIP 44691ParmaWoosterWoosterFindlayFairfieldMiami TownshipMiamiUnion TownshipUnionHuber HeightsJackson TownshipJacksonCleveland HeightsCleveland HtsCuyahoga FallsPlain TownshipPlainLakewoodKetteringGreen TownshipGrnBoardman TownshipBoardmanWest Chester TownshipW ChesterMiami TownshipMiamiMifflin TownshipMifflinMentorLiberty TownshipLibertySylvania TownshipSylvaniaStrongsvilleViolet TownshipVioletJackson TownshipJacksonWashington TownshipWashingtonAnderson TownshipAndersonDeerfield TownshipDeerfieldBeavercreek TownshipBeavercreekDublin21.582420%21.582420%21.6%54,98155.0k118.211726%18.211726%18.2%5,591217.551080%17.551080%17.6%7,207316.999061%16.999061%17.0%7,424416.947843%16.947843%16.9%6,580516.928359%16.928359%16.9%14,88914.9k616.499446%16.499446%16.5%5,361716.278163%16.278163%16.3%3,757815.742056%15.742056%15.7%4,875915.631958%15.631958%15.6%7,3021015.293656%15.293656%15.3%6,2341115.055107%15.055107%15.1%4,0981214.573422%14.573422%14.6%11,02811.0k14.573422%14.573422%14.6%11,02811.0k14.332972%14.332972%14.3%26,34326.3k1313.761583%13.761583%13.8%26,28626.3k1413.591726%13.591726%13.6%17,95118.0k1513.343328%13.343328%13.3%4,8061613.020590%13.020590%13.0%27,818,38027.8M12.943290%12.943290%12.9%4,1061712.411362%12.411362%12.4%3,0631812.375999%12.375999%12.4%3,3311911.376979%11.376979%11.4%60,83160.8k2010.847918%10.847918%10.8%4,3142110.719464%10.719464%10.7%3,363,7843.36M10.656581%10.656581%10.7%3,5222210.514146%10.514146%10.5%825,155825k10.244520%10.244520%10.2%4,641,8354.64M10.188151%10.188151%10.2%3,0549.939137%9.939137%9.9%5,683239.887170%9.887170%9.9%1,7009.887170%9.887170%9.9%1,7009.003845%9.003845%9.0%2,482248.712972%8.712972%8.7%2,559258.614662%8.614662%8.6%3,080268.597523%8.597523%8.6%2,777277.261193%7.261193%7.3%1,797286.480864%6.480864%6.5%1,944296.307136%6.307136%6.3%1,918306.197364%6.197364%6.2%2,215316.171554%6.171554%6.2%2,311326.109570%6.109570%6.1%2,246335.953744%5.953744%6.0%2,340345.804316%5.804316%5.8%2,402355.764815%5.764815%5.8%1,682365.727981%5.727981%5.7%2,390375.628396%5.628396%5.6%1,554385.595517%5.595517%5.6%1,408395.268752%5.268752%5.3%1,834405.136204%5.136204%5.1%1,169414.322119%4.322119%4.3%1,462424.066023%4.066023%4.1%1,313433.979966%3.979966%4.0%1,041443.830735%3.830735%3.8%1,118453.637690%3.637690%3.6%1,496463.351036%3.351036%3.4%978473.293195%3.293195%3.3%815483.105178%3.105178%3.1%1,170491.754602%1.754602%1.8%42850
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older without a high school diploma (or equivalent).

Bachelor's Degrees by County Subdivision#35

Percent of population 25 years of age and older with a bachelor's degree or higher..
Scope: population of Wooster, selected other county subdivisions in Ohio, and entities that contain Wooster
0%20%40%60%Count#DublinDeerfield TownshipDeerfieldAnderson TownshipAndersonWashington TownshipWashingtonBeavercreek TownshipBeavercreekCleveland HeightsCleveland HtsLiberty TownshipLibertyWest Chester TownshipW ChesterSylvania TownshipSylvaniaStrongsvilleMifflin TownshipMifflinViolet TownshipVioletLakewoodMiami TownshipMiamiJackson TownshipJacksonColumbusCincinnatiKetteringPlain TownshipPlainGreen TownshipGrnCuyahoga FallsMentorBoardman TownshipBoardmanUnited States of AmericaUnited StatesUnion TownshipUnionJackson TownshipJacksonMidwestWoosterWoosterEast North CentralFairfieldBath TownshipFindlayMiami TownshipMiamiOhioZIP Code 44691ZIP 44691Huber HeightsColerain TownshipColerainWooster Metro AreaWooster AreaWayne CountyWayneEuclidAkronParmaNewarkToledoDaytonMiddletownLancaster City TownshipLancaster CityClevelandElyriaHamiltonSpringfieldCantonMansfieldWarrenYoungstownLorainLimaMarion TownshipMarion75.246997%75.246997%75.2%18,35518.4k157.851139%57.851139%57.9%14,31714.3k256.039061%56.039061%56.0%16,35516.4k352.483891%52.483891%52.5%21,58421.6k451.261976%51.261976%51.3%19,31519.3k550.973364%50.973364%51.0%15,50115.5k650.549209%50.549209%50.5%11,50511.5k747.424805%47.424805%47.4%19,78819.8k846.115414%46.115414%46.1%15,59915.6k944.614765%44.614765%44.6%14,40714.4k1043.925605%43.925605%43.9%11,05311.1k1143.657287%43.657287%43.7%11,41911.4k1243.651053%43.651053%43.7%16,04716.0k1342.654835%42.654835%42.7%11,77711.8k1441.432243%41.432243%41.4%12,09212.1k1534.685843%34.685843%34.7%185,460185k1633.783048%33.783048%33.8%64,52964.5k1733.391853%33.391853%33.4%13,12413.1k1833.138386%33.138386%33.1%12,40912.4k1932.914482%32.914482%32.9%13,62113.6k2032.380180%32.380180%32.4%11,57311.6k2132.238789%32.238789%32.2%11,22211.2k2231.219796%31.219796%31.2%9,1092330.315023%30.315023%30.3%64,767,78764.8M29.613003%29.613003%29.6%9,5652428.997200%28.997200%29.0%8,6982528.952816%28.952816%29.0%13,118,64213.1M28.748401%28.748401%28.7%4,94328.748401%28.748401%28.7%4,94328.462853%28.462853%28.5%8,931,6868.93M28.219271%28.219271%28.2%8,2882626.954091%26.954091%27.0%6,6522726.775738%26.775738%26.8%7,3812826.713842%26.713842%26.7%9,5512926.667466%26.667466%26.7%2,092,8752.09M26.577929%26.577929%26.6%7,96722.834168%22.834168%22.8%5,6513021.665661%21.665661%21.7%8,6163121.467650%21.467650%21.5%16,24516.2k21.467650%21.467650%21.5%16,24516.2k20.614221%20.614221%20.6%6,8133220.213821%20.213821%20.2%26,69726.7k3319.988457%19.988457%20.0%11,42911.4k3418.053148%18.053148%18.1%5,7273518.048021%18.048021%18.0%33,17133.2k3617.635555%17.635555%17.6%15,51115.5k3716.631922%16.631922%16.6%5,1063816.462939%16.462939%16.5%4,4313916.073076%16.073076%16.1%40,94640.9k4015.411739%15.411739%15.4%5,5514115.075315%15.075315%15.1%6,1454214.851256%14.851256%14.9%5,7664314.608666%14.608666%14.6%6,8244413.812631%13.812631%13.8%4,4884512.832476%12.832476%12.8%3,4934612.044055%12.044055%12.0%5,2604711.718579%11.718579%11.7%4,8124811.460139%11.460139%11.5%2,6454910.478559%10.478559%10.5%3,24550
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older with a bachelor's degree or higher..

Very Advanced Degrees by County Subdivision#36

Percent of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).
Scope: population of Wooster, selected other county subdivisions in Ohio, and entities that contain Wooster
0%2%4%6%8%10%Count#Cleveland HeightsCleveland HtsDublinAnderson TownshipAndersonSylvania TownshipSylvaniaWashington TownshipWashingtonBeavercreek TownshipBeavercreekJackson TownshipJacksonLakewoodCincinnatiStrongsvilleWoosterWoosterDeerfield TownshipDeerfieldWest Chester TownshipW ChesterKetteringZIP Code 44691ZIP 44691Liberty TownshipLibertyMifflin TownshipMifflinColumbusUnited States of AmericaUnited StatesPlain TownshipPlainBoardman TownshipBoardmanViolet TownshipVioletMiami TownshipMiamiMidwestEast North CentralOhioCuyahoga FallsGreen TownshipGrnBath TownshipWooster Metro AreaWooster AreaWayne CountyWayneAkronJackson TownshipJacksonClevelandMentorColerain TownshipColerainMiami TownshipMiamiFindlayToledoSpringfieldFairfieldEuclidHuber HeightsLimaDaytonCantonHamiltonUnion TownshipUnionParmaNewarkLancaster City TownshipLancaster CityMansfieldMiddletownLorainElyriaYoungstownWarrenMarion TownshipMarion10.753042%10.753042%10.8%3,270110.031566%10.031566%10.0%2,44727.476443%7.476443%7.5%2,18237.470585%7.470585%7.5%2,52746.820669%6.820669%6.8%2,80556.685422%6.685422%6.7%2,51965.297242%5.297242%5.3%1,54675.051412%5.051412%5.1%1,85784.729595%4.729595%4.7%9,03494.555308%4.555308%4.6%1,471104.350355%4.350355%4.4%7484.350355%4.350355%4.4%7484.149830%4.149830%4.1%1,027114.100659%4.100659%4.1%1,711123.778338%3.778338%3.8%1,485133.649586%3.649586%3.6%1,0943.514938%3.514938%3.5%800143.389898%3.389898%3.4%853153.357865%3.357865%3.4%17,95418.0k163.336158%3.336158%3.3%7,127,6737.13M3.036372%3.036372%3.0%1,137172.957809%2.957809%3.0%863182.940052%2.940052%2.9%769192.911988%2.911988%2.9%804202.893416%2.893416%2.9%1,311,0191.31M2.855432%2.855432%2.9%896,039896k2.683241%2.683241%2.7%210,582211k2.481744%2.481744%2.5%887212.476862%2.476862%2.5%1,025222.451477%2.451477%2.5%605232.226715%2.226715%2.2%1,6852.226715%2.226715%2.2%1,6852.163955%2.163955%2.2%2,858242.063608%2.063608%2.1%619251.927780%1.927780%1.9%4,911261.815622%1.815622%1.8%632271.815530%1.815530%1.8%722281.762090%1.762090%1.8%630291.675978%1.675978%1.7%462301.642065%1.642065%1.6%3,018311.545396%1.545396%1.5%600321.477698%1.477698%1.5%434331.388805%1.388805%1.4%459341.349604%1.349604%1.3%334351.304159%1.304159%1.3%301361.257490%1.257490%1.3%1,106371.245933%1.245933%1.2%582381.241352%1.241352%1.2%506391.238390%1.238390%1.2%400401.236490%1.236490%1.2%707411.182108%1.182108%1.2%375421.159205%1.159205%1.2%312431.104887%1.104887%1.1%359440.996743%0.996743%1.0%306450.964372%0.964372%1.0%396460.952302%0.952302%1.0%343470.794541%0.794541%0.8%347480.742101%0.742101%0.7%202490.720098%0.720098%0.7%22350
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).

Under-Education Sex Ratio by County Subdivision#37

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 Wooster, selected other county subdivisions in Ohio, and entities that contain Wooster
Female
Male
1x0x1xFM#AndersonMansfieldCleveland HtsBeavercreekZIP 44691UnionToledoFindlayLorainMarionYoungstownColerainGrnFairfieldElyriaWooster AreaWayneMiddletownLancaster CityMidwestEast North CentralSpringfieldWarrenDaytonCantonUnited StatesOhioLimaParmaColumbusClevelandDeerfieldMentorNewarkW ChesterPlainLibertyJacksonHuber HeightsHamiltonJacksonCincinnatiAkronWoosterWoosterMifflinSylvaniaMiamiEuclidMiamiCuyahoga FallsStrongsvilleLakewoodBath TownshipDublinKetteringWashingtonBoardmanViolet-1.000000x-1.000000x1.766803x1.766803x1.77x2.468%2.47%4.360%4.36%1-1.000000x-1.000000x1.592708x1.592708x1.59x12.530%12.5%19.956%20.0%2-1.000000x-1.000000x1.485471x1.485471x1.49x5.146%5.15%7.645%7.64%3-1.000000x-1.000000x1.332397x1.332397x1.33x2.666%2.67%3.552%3.55%4-1.000000x-1.000000x1.287259x1.287259x1.29x8.969%8.97%11.546%11.5%-1.000000x-1.000000x1.242595x1.242595x1.24x7.704%7.70%9.573%9.57%5-1.000000x-1.000000x1.227011x1.227011x1.23x12.945%12.9%15.884%15.9%6-1.000000x-1.000000x1.222843x1.222843x1.22x8.133%8.13%9.946%9.95%7-1.000000x-1.000000x1.207850x1.207850x1.21x16.045%16.0%19.380%19.4%8-1.000000x-1.000000x1.204406x1.204406x1.20x14.131%14.1%17.020%17.0%9-1.000000x-1.000000x1.194114x1.194114x1.19x15.554%15.6%18.574%18.6%10-1.000000x-1.000000x1.175447x1.175447x1.18x10.032%10.0%11.792%11.8%11-1.000000x-1.000000x1.173903x1.173903x1.17x5.370%5.37%6.304%6.30%12-1.000000x-1.000000x1.173628x1.173628x1.17x8.033%8.03%9.428%9.43%13-1.000000x-1.000000x1.166450x1.166450x1.17x12.379%12.4%14.439%14.4%14-1.000000x-1.000000x1.151379x1.151379x1.15x13.576%13.6%15.631%15.6%-1.000000x-1.000000x1.151379x1.151379x1.15x13.576%13.6%15.631%15.6%-1.000000x-1.000000x1.147049x1.147049x1.15x17.010%17.0%19.512%19.5%15-1.000000x-1.000000x1.144160x1.144160x1.14x11.593%11.6%13.265%13.3%16-1.000000x-1.000000x1.127915x1.127915x1.13x9.647%9.65%10.881%10.9%-1.000000x-1.000000x1.125371x1.125371x1.13x10.108%10.1%11.375%11.4%-1.000000x-1.000000x1.124452x1.124452x1.12x16.027%16.0%18.022%18.0%17-1.000000x-1.000000x1.124390x1.124390x1.12x14.230%14.2%16.000%16.0%18-1.000000x-1.000000x1.114342x1.114342x1.11x16.070%16.1%17.907%17.9%19-1.000000x-1.000000x1.109752x1.109752x1.11x14.885%14.9%16.518%16.5%20-1.000000x-1.000000x1.109070x1.109070x1.11x12.369%12.4%13.719%13.7%-1.000000x-1.000000x1.105363x1.105363x1.11x10.008%10.0%11.063%11.1%-1.000000x-1.000000x1.087544x1.087544x1.09x15.592%15.6%16.957%17.0%21-1.000000x-1.000000x1.081824x1.081824x1.08x9.568%9.57%10.350%10.4%22-1.000000x-1.000000x1.052237x1.052237x1.05x11.098%11.1%11.678%11.7%23-1.000000x-1.000000x1.046686x1.046686x1.05x21.119%21.1%22.105%22.1%24-1.000000x-1.000000x1.045216x1.045216x1.05x3.224%3.22%3.370%3.37%25-1.000000x-1.000000x1.038813x1.038813x1.04x5.175%5.17%5.376%5.38%26-1.000000x-1.000000x1.036562x1.036562x1.04x12.733%12.7%13.198%13.2%27-1.000000x-1.000000x1.031821x1.031821x1.03x5.641%5.64%5.821%5.82%28-1.000000x-1.000000x1.027725x1.027725x1.03x6.093%6.09%6.262%6.26%29-1.000000x-1.000000x1.026192x1.026192x1.03x5.072%5.07%5.205%5.20%30-1.000000x-1.000000x1.025236x1.025236x1.03x6.405%6.41%6.567%6.57%31-1.000000x-1.000000x1.021443x1.021443x1.02x7.189%7.19%7.344%7.34%32-1.000000x-1.000000x1.015682x1.015682x1.02x15.182%15.2%15.420%15.4%33-1.000000x-1.000000x1.006889x1.006889x1.01x3.818%3.82%3.844%3.84%34-1.000000x-1.000000x1.001229x1.001229x1.00x13.754%13.8%13.771%13.8%35-1.001506x-1.001506x1.00x1.000000x1.000000x13.601%13.6%13.581%13.6%36-1.048147x-1.048147x1.05x1.000000x1.000000x10.102%10.1%9.638%9.64%-1.048147x-1.048147x1.05x1.000000x1.000000x10.102%10.1%9.638%9.64%-1.053306x-1.053306x1.05x1.000000x1.000000x5.733%5.73%5.442%5.44%37-1.068860x-1.068860x1.07x1.000000x1.000000x4.454%4.45%4.167%4.17%38-1.075183x-1.075183x1.08x1.000000x1.000000x5.828%5.83%5.420%5.42%39-1.084060x-1.084060x1.08x1.000000x1.000000x11.029%11.0%10.174%10.2%40-1.123601x-1.123601x1.12x1.000000x1.000000x9.091%9.09%8.091%8.09%41-1.132510x-1.132510x1.13x1.000000x1.000000x6.567%6.57%5.799%5.80%42-1.209810x-1.209810x1.21x1.000000x1.000000x4.433%4.43%3.664%3.66%43-1.275391x-1.275391x1.28x1.000000x1.000000x6.820%6.82%5.347%5.35%44-1.295653x-1.295653x1.30x1.000000x1.000000x13.964%14.0%10.778%10.8%45-1.385029x-1.385029x1.39x1.000000x1.000000x2.028%2.03%1.464%1.46%46-1.505212x-1.505212x1.51x1.000000x1.000000x7.040%7.04%4.677%4.68%47-1.641786x-1.641786x1.64x1.000000x1.000000x4.457%4.46%2.715%2.71%48-1.660386x-1.660386x1.66x1.000000x1.000000x7.066%7.07%4.256%4.26%49-1.798212x-1.798212x1.80x1.000000x1.000000x5.036%5.04%2.800%2.80%50
F percentage of females in category
M percentage of males in category
# rank of county subdivision out of 50 by male-to-female sex ratio

Over-Education Sex Ratio by County Subdivision#38

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 Wooster, selected other county subdivisions in Ohio, and entities that contain Wooster
Female
Male
1x0x1x2x3xFM#ElyriaSpringfieldWashingtonYoungstownBoardmanLorainMiddletownLancaster CityFindlayAndersonWoosterWoosterZIP 44691JacksonKetteringMifflinPlainBeavercreekDeerfieldDaytonNewarkEuclidMiamiAkronDublinSylvaniaStrongsvilleBath TownshipOhioWooster AreaWayneFairfieldMansfieldW ChesterHuber HeightsLakewoodEast North CentralMidwestWarrenUnited StatesLibertyParmaCleveland HtsColumbusUnionMentorGrnJacksonClevelandCincinnatiMiamiMarionVioletColerainToledoHamiltonCantonCuyahoga FallsLima-1.000000x-1.000000x3.557903x3.557903x3.56x0.433%0.43%1.542%1.54%1-1.000000x-1.000000x3.025650x3.025650x3.03x0.799%0.80%2.417%2.42%2-1.000000x-1.000000x2.977263x2.977263x2.98x3.534%3.53%10.523%10.5%3-1.000000x-1.000000x2.809581x2.809581x2.81x0.426%0.43%1.196%1.20%4-1.000000x-1.000000x2.780060x2.780060x2.78x1.621%1.62%4.507%4.51%5-1.000000x-1.000000x2.695011x2.695011x2.70x0.546%0.55%1.472%1.47%6-1.000000x-1.000000x2.596948x2.596948x2.60x0.564%0.56%1.465%1.46%7-1.000000x-1.000000x2.442537x2.442537x2.44x0.692%0.69%1.690%1.69%8-1.000000x-1.000000x2.437656x2.437656x2.44x0.991%0.99%2.417%2.42%9-1.000000x-1.000000x2.428350x2.428350x2.43x4.486%4.49%10.893%10.9%10-1.000000x-1.000000x2.388350x2.388350x2.39x2.650%2.65%6.329%6.33%-1.000000x-1.000000x2.388350x2.388350x2.39x2.650%2.65%6.329%6.33%-1.000000x-1.000000x2.368602x2.368602x2.37x2.215%2.22%5.248%5.25%-1.000000x-1.000000x2.183841x2.183841x2.18x3.386%3.39%7.394%7.39%11-1.000000x-1.000000x2.155653x2.155653x2.16x2.468%2.47%5.319%5.32%12-1.000000x-1.000000x2.069018x2.069018x2.07x2.252%2.25%4.660%4.66%13-1.000000x-1.000000x2.024516x2.024516x2.02x2.059%2.06%4.169%4.17%14-1.000000x-1.000000x2.007898x2.007898x2.01x4.457%4.46%8.948%8.95%15-1.000000x-1.000000x1.991550x1.991550x1.99x2.826%2.83%5.628%5.63%16-1.000000x-1.000000x1.989047x1.989047x1.99x0.860%0.86%1.711%1.71%17-1.000000x-1.000000x1.967904x1.967904x1.97x0.822%0.82%1.618%1.62%18-1.000000x-1.000000x1.903271x1.903271x1.90x0.997%1.00%1.897%1.90%19-1.000000x-1.000000x1.851159x1.851159x1.85x2.056%2.06%3.806%3.81%20-1.000000x-1.000000x1.846298x1.846298x1.85x1.550%1.55%2.862%2.86%21-1.000000x-1.000000x1.832511x1.832511x1.83x7.149%7.15%13.100%13.1%22-1.000000x-1.000000x1.805502x1.805502x1.81x5.447%5.45%9.835%9.84%23-1.000000x-1.000000x1.769961x1.769961x1.77x3.331%3.33%5.895%5.90%24-1.000000x-1.000000x1.691857x1.691857x1.69x1.833%1.83%3.102%3.10%25-1.000000x-1.000000x1.669500x1.669500x1.67x2.031%2.03%3.391%3.39%-1.000000x-1.000000x1.658480x1.658480x1.66x1.687%1.69%2.798%2.80%-1.000000x-1.000000x1.658480x1.658480x1.66x1.687%1.69%2.798%2.80%-1.000000x-1.000000x1.650680x1.650680x1.65x1.122%1.12%1.852%1.85%26-1.000000x-1.000000x1.650301x1.650301x1.65x0.820%0.82%1.353%1.35%27-1.000000x-1.000000x1.648570x1.648570x1.65x3.124%3.12%5.150%5.15%28-1.000000x-1.000000x1.627164x1.627164x1.63x1.044%1.04%1.699%1.70%29-1.000000x-1.000000x1.624128x1.624128x1.62x3.883%3.88%6.306%6.31%30-1.000000x-1.000000x1.597848x1.597848x1.60x2.216%2.22%3.541%3.54%-1.000000x-1.000000x1.589934x1.589934x1.59x2.251%2.25%3.579%3.58%-1.000000x-1.000000x1.543502x1.543502x1.54x0.592%0.59%0.914%0.91%31-1.000000x-1.000000x1.526215x1.526215x1.53x2.660%2.66%4.060%4.06%-1.000000x-1.000000x1.525512x1.525512x1.53x2.801%2.80%4.272%4.27%32-1.000000x-1.000000x1.433883x1.433883x1.43x1.025%1.03%1.470%1.47%33-1.000000x-1.000000x1.416609x1.416609x1.42x9.009%9.01%12.763%12.8%34-1.000000x-1.000000x1.413654x1.413654x1.41x2.801%2.80%3.959%3.96%35-1.000000x-1.000000x1.348352x1.348352x1.35x1.062%1.06%1.431%1.43%36-1.000000x-1.000000x1.325696x1.325696x1.33x1.576%1.58%2.089%2.09%37-1.000000x-1.000000x1.319751x1.319751x1.32x2.156%2.16%2.845%2.85%38-1.000000x-1.000000x1.297270x1.297270x1.30x1.812%1.81%2.351%2.35%39-1.000000x-1.000000x1.286599x1.286599x1.29x1.699%1.70%2.186%2.19%40-1.000000x-1.000000x1.280610x1.280610x1.28x4.179%4.18%5.351%5.35%41-1.000000x-1.000000x1.246667x1.246667x1.25x1.577%1.58%1.966%1.97%42-1.000000x-1.000000x1.217109x1.217109x1.22x0.642%0.64%0.782%0.78%43-1.000000x-1.000000x1.149458x1.149458x1.15x2.746%2.75%3.157%3.16%44-1.000000x-1.000000x1.145376x1.145376x1.15x1.701%1.70%1.948%1.95%45-1.000000x-1.000000x1.141406x1.141406x1.14x1.539%1.54%1.757%1.76%46-1.000000x-1.000000x1.036455x1.036455x1.04x1.220%1.22%1.265%1.26%47-1.103703x-1.103703x1.10x1.000000x1.000000x1.302%1.30%1.180%1.18%48-1.188945x-1.188945x1.19x1.000000x1.000000x2.687%2.69%2.260%2.26%49-1.404867x-1.404867x1.40x1.000000x1.000000x1.525%1.53%1.086%1.09%50
F percentage of females in category
M percentage of males in category
# rank of county subdivision out of 50 by male-to-female sex ratio

Educational Attainment by County Subdivision in the Midwest

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

No H.S. Diploma by County Subdivision#39

Percent of population 25 years of age and older without a high school diploma (or equivalent).
Scope: population of Wooster, selected other county subdivisions in the Midwest, and entities that contain Wooster
0%10%20%30%Count#Aurora TownshipAuroraCenter TownshipCtrKansas CityClevelandWayne TownshipWayneDetroitMilwaukeeNorth TownshipNDaytonChicagoProviso TownshipProvisoRockford TownshipRockfordSt. LouisWarrenWooster Metro AreaWooster AreaWayne CountyWayneGrand RapidsToledoBlue TownshipCincinnatiAkronSt. PaulSterling HeightsSterling HtsUnited States of AmericaUnited StatesThornton TownshipThorntonWichitaKaw TownshipOmahaBloomingdale TownshipBloomingdaleColumbusMaine TownshipMaineTopekaMinneapolisSpringfield TownshipSpringfieldEast North CentralWorth TownshipWorthOhioMidwestZIP Code 44691ZIP 44691Lawrence TownshipLawrenceWoosterWoosterSioux FallsCapital TownshipCapitalWheeling TownshipWheelingPalatine TownshipPalatineSchaumburg TownshipSchaumburgLincolnWashington TownshipWashingtonOlatheFargoCedar RapidsYork TownshipMilton TownshipMiltonMadisonDowners Grove TownshipDowners GrvLisle TownshipLisleOverland ParkAnn Arbor33.464284%33.464284%33.5%29,81429.8k123.165532%23.165532%23.2%22,92622.9k222.659362%22.659362%22.7%21,21821.2k321.582420%21.582420%21.6%54,98155.0k421.037720%21.037720%21.0%18,48918.5k521.003600%21.003600%21.0%90,67890.7k617.485105%17.485105%17.5%63,80063.8k717.062713%17.062713%17.1%17,39117.4k816.928359%16.928359%16.9%14,88914.9k916.905373%16.905373%16.9%309,770310k1015.636222%15.636222%15.6%16,11016.1k1115.608074%15.608074%15.6%18,24118.2k1215.466266%15.466266%15.5%33,80433.8k1315.286174%15.286174%15.3%14,05914.1k1414.573422%14.573422%14.6%11,02811.0k14.573422%14.573422%14.6%11,02811.0k14.563179%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%11,14911.1k3110.719464%10.719464%10.7%3,363,7843.36M10.678962%10.678962%10.7%11,17511.2k3210.514146%10.514146%10.5%825,155825k10.244520%10.244520%10.2%4,641,8354.64M10.188151%10.188151%10.2%3,05410.179618%10.179618%10.2%8,161339.887170%9.887170%9.9%1,7009.887170%9.887170%9.9%1,7009.702326%9.702326%9.7%9,123348.623103%8.623103%8.6%6,837358.424707%8.424707%8.4%9,343368.392669%8.392669%8.4%6,695377.739434%7.739434%7.7%7,226387.092309%7.092309%7.1%11,88611.9k396.804680%6.804680%6.8%6,403406.424130%6.424130%6.4%5,331416.055621%6.055621%6.1%4,270425.981653%5.981653%6.0%5,099435.461095%5.461095%5.5%4,715445.266517%5.266517%5.3%4,126454.836248%4.836248%4.8%7,351464.020265%4.020265%4.0%4,166473.522812%3.522812%3.5%2,870483.377424%3.377424%3.4%4,282493.157717%3.157717%3.2%2,05750
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older without a high school diploma (or equivalent).

Bachelor's Degrees by County Subdivision#40

Percent of population 25 years of age and older with a bachelor's degree or higher..
Scope: population of Wooster, selected other county subdivisions in the Midwest, and entities that contain Wooster
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 FallsMidwestWichitaWoosterWoosterEast North CentralSterling HeightsSterling HtsTopekaSpringfield TownshipSpringfieldOhioZIP Code 44691ZIP 44691Proviso TownshipProvisoWorth TownshipWorthMilwaukeeRockford TownshipRockfordWooster Metro AreaWooster AreaWayne CountyWayneAkronCenter TownshipCtrNorth 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%71,75771.8k3028.748401%28.748401%28.7%4,94328.748401%28.748401%28.7%4,94328.462853%28.462853%28.5%8,931,6868.93M27.532180%27.532180%27.5%25,60325.6k3127.007248%27.007248%27.0%22,95423.0k3226.964567%26.964567%27.0%27,92127.9k3326.667466%26.667466%26.7%2,092,8752.09M26.577929%26.577929%26.6%7,96726.237989%26.237989%26.2%27,03327.0k3425.217641%25.217641%25.2%26,38926.4k3523.517740%23.517740%23.5%85,81285.8k3621.592552%21.592552%21.6%25,23525.2k3721.467650%21.467650%21.5%16,24516.2k21.467650%21.467650%21.5%16,24516.2k20.213821%20.213821%20.2%26,69726.7k3820.139240%20.139240%20.1%19,93119.9k3919.650916%19.650916%19.7%20,02920.0k4018.971090%18.971090%19.0%21,01221.0k4118.048021%18.048021%18.0%33,17133.2k4217.635555%17.635555%17.6%15,51115.5k4317.280259%17.280259%17.3%15,89315.9k4416.826535%16.826535%16.8%14,78814.8k4516.167409%16.167409%16.2%15,13915.1k4616.073076%16.073076%16.1%40,94640.9k4715.929601%15.929601%15.9%14,19214.2k4815.821208%15.821208%15.8%16,95117.0k4913.833543%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#41

Percent of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).
Scope: population of Wooster, selected other county subdivisions in the Midwest, and entities that contain Wooster
0%5%10%15%Count#Ann ArborMadisonDowners Grove TownshipDowners GrvWashington TownshipWashingtonMinneapolisYork TownshipOverland ParkLisle TownshipLisleSt. PaulKaw TownshipMilton TownshipMiltonSt. LouisCincinnatiLincolnChicagoWoosterWoosterFargoCapital TownshipCapitalOmahaMaine TownshipMaineZIP Code 44691ZIP 44691Palatine TownshipPalatineWheeling TownshipWheelingColumbusUnited States of AmericaUnited StatesTopekaGrand RapidsLawrence TownshipLawrenceSpringfield TownshipSpringfieldCedar RapidsMidwestEast North CentralSioux FallsOlatheOhioCenter TownshipCtrSchaumburg TownshipSchaumburgWichitaWooster Metro AreaWooster AreaWayne CountyWayneProviso TownshipProvisoAkronBloomingdale TownshipBloomingdaleRockford TownshipRockfordMilwaukeeWorth TownshipWorthClevelandToledoNorth TownshipNSterling HeightsSterling HtsKansas CityDetroitDaytonWayne TownshipWayneWarrenBlue TownshipAurora TownshipAuroraThornton TownshipThornton17.877867%17.877867%17.9%11,64611.6k19.171173%9.171173%9.2%13,94013.9k27.658384%7.658384%7.7%7,93637.306290%7.306290%7.3%6,87546.241155%6.241155%6.2%16,71416.7k56.197734%6.197734%6.2%5,35165.940071%5.940071%5.9%7,53175.933545%5.933545%5.9%4,83485.920847%5.920847%5.9%10,97511.0k95.896414%5.896414%5.9%7,178105.800061%5.800061%5.8%4,544114.880448%4.880448%4.9%10,66710.7k124.729595%4.729595%4.7%9,034134.568292%4.568292%4.6%7,656144.485379%4.485379%4.5%82,18982.2k154.350355%4.350355%4.4%7484.350355%4.350355%4.4%7484.336789%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%3,970193.649586%3.649586%3.6%1,0943.487439%3.487439%3.5%2,782203.407574%3.407574%3.4%3,779213.357865%3.357865%3.4%17,95418.0k223.336158%3.336158%3.3%7,127,6737.13M3.233245%3.233245%3.2%2,748233.174629%3.174629%3.2%3,846243.083448%3.083448%3.1%2,472252.911721%2.911721%2.9%3,015262.905776%2.905776%2.9%2,477272.893416%2.893416%2.9%1,311,0191.31M2.855432%2.855432%2.9%896,039896k2.841677%2.841677%2.8%2,672282.830666%2.830666%2.8%2,349292.683241%2.683241%2.7%210,582211k2.602914%2.602914%2.6%2,576302.551250%2.551250%2.6%2,382312.519246%2.519246%2.5%6,260322.226715%2.226715%2.2%1,6852.226715%2.226715%2.2%1,6852.213918%2.213918%2.2%2,281332.163955%2.163955%2.2%2,858342.113682%2.113682%2.1%1,628352.067272%2.067272%2.1%2,416362.043126%2.043126%2.0%7,455371.958049%1.958049%2.0%2,049381.927780%1.927780%1.9%4,911391.642065%1.642065%1.6%3,018401.575684%1.575684%1.6%1,606411.439893%1.439893%1.4%1,339421.388310%1.388310%1.4%1,300431.318660%1.318660%1.3%5,693441.257490%1.257490%1.3%1,106451.183365%1.183365%1.2%1,040461.047058%1.047058%1.0%963470.997751%0.997751%1.0%1,069480.936111%0.936111%0.9%834490.876686%0.876686%0.9%97150
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).

Under-Education Sex Ratio by County Subdivision#42

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 Wooster, selected other county subdivisions in the Midwest, and entities that contain Wooster
Female
Male
1x0x1xFM#ZIP 44691Cedar RapidsLincolnDetroitOmahaToledoThorntonKansas CityMadisonLawrenceFargoProvisoRockfordBlue TownshipWooster AreaWayneWayneMidwestTopekaEast North CentralMilwaukeeKaw TownshipDaytonSioux FallsUnited StatesOlatheOhioWorthNOverland ParkAuroraWheelingGrand RapidsSchaumburgChicagoWichitaColumbusClevelandPalatineCapitalWarrenSpringfieldYork TownshipSt. LouisWashingtonBloomingdaleCtrCincinnatiAkronAnn ArborWoosterWoosterSt. PaulLisleMinneapolisSterling HtsDowners GrvMiltonMaine-1.000000x-1.000000x1.287259x1.287259x1.29x8.969%8.97%11.546%11.5%-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-1.000000x1.151379x1.151379x1.15x13.576%13.6%15.631%15.6%-1.000000x-1.000000x1.151379x1.151379x1.15x13.576%13.6%15.631%15.6%-1.000000x-1.000000x1.132245x1.132245x1.13x19.779%19.8%22.395%22.4%14-1.000000x-1.000000x1.127915x1.127915x1.13x9.647%9.65%10.881%10.9%-1.000000x-1.000000x1.125507x1.125507x1.13x10.423%10.4%11.732%11.7%15-1.000000x-1.000000x1.125371x1.125371x1.13x10.108%10.1%11.375%11.4%-1.000000x-1.000000x1.123984x1.123984x1.12x16.526%16.5%18.574%18.6%16-1.000000x-1.000000x1.115695x1.115695x1.12x11.779%11.8%13.142%13.1%17-1.000000x-1.000000x1.114342x1.114342x1.11x16.070%16.1%17.907%17.9%18-1.000000x-1.000000x1.110589x1.110589x1.11x9.201%9.20%10.219%10.2%19-1.000000x-1.000000x1.109070x1.109070x1.11x12.369%12.4%13.719%13.7%-1.000000x-1.000000x1.107847x1.107847x1.11x6.105%6.11%6.764%6.76%20-1.000000x-1.000000x1.105363x1.105363x1.11x10.008%10.0%11.063%11.1%-1.000000x-1.000000x1.099747x1.099747x1.10x10.199%10.2%11.216%11.2%21-1.000000x-1.000000x1.096598x1.096598x1.10x16.317%16.3%17.894%17.9%22-1.000000x-1.000000x1.095440x1.095440x1.10x3.232%3.23%3.540%3.54%23-1.000000x-1.000000x1.086583x1.086583x1.09x32.102%32.1%34.882%34.9%24-1.000000x-1.000000x1.079846x1.079846x1.08x8.111%8.11%8.758%8.76%25-1.000000x-1.000000x1.078480x1.078480x1.08x14.031%14.0%15.132%15.1%26-1.000000x-1.000000x1.077209x1.077209x1.08x7.467%7.47%8.043%8.04%27-1.000000x-1.000000x1.068021x1.068021x1.07x16.372%16.4%17.486%17.5%28-1.000000x-1.000000x1.059528x1.059528x1.06x12.215%12.2%12.942%12.9%29-1.000000x-1.000000x1.052237x1.052237x1.05x11.098%11.1%11.678%11.7%30-1.000000x-1.000000x1.046686x1.046686x1.05x21.119%21.1%22.105%22.1%31-1.000000x-1.000000x1.039581x1.039581x1.04x8.233%8.23%8.559%8.56%32-1.000000x-1.000000x1.039194x1.039194x1.04x8.470%8.47%8.802%8.80%33-1.000000x-1.000000x1.037373x1.037373x1.04x15.022%15.0%15.584%15.6%34-1.000000x-1.000000x1.028857x1.028857x1.03x10.622%10.6%10.928%10.9%35-1.000000x-1.000000x1.027464x1.027464x1.03x5.391%5.39%5.539%5.54%36-1.000000x-1.000000x1.018183x1.018183x1.02x15.334%15.3%15.613%15.6%37-1.000000x-1.000000x1.013146x1.013146x1.01x6.764%6.76%6.853%6.85%38-1.000000x-1.000000x1.007207x1.007207x1.01x12.130%12.1%12.217%12.2%39-1.000000x-1.000000x1.006204x1.006204x1.01x23.095%23.1%23.239%23.2%40-1.000000x-1.000000x1.001229x1.001229x1.00x13.754%13.8%13.771%13.8%41-1.001506x-1.001506x1.00x1.000000x1.000000x13.601%13.6%13.581%13.6%42-1.031649x-1.031649x1.03x1.000000x1.000000x3.205%3.21%3.107%3.11%43-1.048147x-1.048147x1.05x1.000000x1.000000x10.102%10.1%9.638%9.64%-1.048147x-1.048147x1.05x1.000000x1.000000x10.102%10.1%9.638%9.64%-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#43

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 Wooster, selected other county subdivisions in the Midwest, and entities that contain Wooster
Female
Male
1x0x1x2xFM#WoosterWoosterZIP 44691RockfordNDaytonSioux FallsCapitalLawrenceDowners GrvAkronLisleWichitaYork TownshipMaineWarrenWheelingBlue TownshipSpringfieldOverland ParkMiltonGrand RapidsOlatheOhioOmahaWooster AreaWayneFargoWashingtonEast North CentralLincolnMidwestBloomingdaleKansas CityAuroraUnited StatesAnn ArborTopekaSterling HtsPalatineSchaumburgColumbusMadisonKaw TownshipMilwaukeeCedar RapidsClevelandCincinnatiSt. PaulSt. LouisChicagoWayneCtrToledoMinneapolisWorthDetroitProvisoThornton-1.000000x-1.000000x2.388350x2.388350x2.39x2.650%2.65%6.329%6.33%-1.000000x-1.000000x2.388350x2.388350x2.39x2.650%2.65%6.329%6.33%-1.000000x-1.000000x2.368602x2.368602x2.37x2.215%2.22%5.248%5.25%-1.000000x-1.000000x2.117268x2.117268x2.12x1.353%1.35%2.866%2.87%1-1.000000x-1.000000x2.111054x2.111054x2.11x1.033%1.03%2.181%2.18%2-1.000000x-1.000000x1.989047x1.989047x1.99x0.860%0.86%1.711%1.71%3-1.000000x-1.000000x1.962539x1.962539x1.96x1.928%1.93%3.783%3.78%4-1.000000x-1.000000x1.901348x1.901348x1.90x2.990%2.99%5.686%5.69%5-1.000000x-1.000000x1.879271x1.879271x1.88x2.206%2.21%4.146%4.15%6-1.000000x-1.000000x1.852471x1.852471x1.85x5.456%5.46%10.107%10.1%7-1.000000x-1.000000x1.846298x1.846298x1.85x1.550%1.55%2.862%2.86%8-1.000000x-1.000000x1.815266x1.815266x1.82x4.271%4.27%7.754%7.75%9-1.000000x-1.000000x1.792728x1.792728x1.79x1.819%1.82%3.261%3.26%10-1.000000x-1.000000x1.792314x1.792314x1.79x4.498%4.50%8.062%8.06%11-1.000000x-1.000000x1.788417x1.788417x1.79x2.939%2.94%5.256%5.26%12-1.000000x-1.000000x1.768853x1.768853x1.77x0.769%0.77%1.361%1.36%13-1.000000x-1.000000x1.766097x1.766097x1.77x2.485%2.48%4.389%4.39%14-1.000000x-1.000000x1.761699x1.761699x1.76x0.737%0.74%1.298%1.30%15-1.000000x-1.000000x1.751445x1.751445x1.75x2.146%2.15%3.759%3.76%16-1.000000x-1.000000x1.732234x1.732234x1.73x4.415%4.41%7.647%7.65%17-1.000000x-1.000000x1.695067x1.695067x1.70x4.357%4.36%7.385%7.38%18-1.000000x-1.000000x1.689013x1.689013x1.69x2.382%2.38%4.023%4.02%19-1.000000x-1.000000x1.678153x1.678153x1.68x2.131%2.13%3.576%3.58%20-1.000000x-1.000000x1.669500x1.669500x1.67x2.031%2.03%3.391%3.39%-1.000000x-1.000000x1.669388x1.669388x1.67x3.061%3.06%5.110%5.11%21-1.000000x-1.000000x1.658480x1.658480x1.66x1.687%1.69%2.798%2.80%-1.000000x-1.000000x1.658480x1.658480x1.66x1.687%1.69%2.798%2.80%-1.000000x-1.000000x1.627456x1.627456x1.63x3.304%3.30%5.377%5.38%22-1.000000x-1.000000x1.610803x1.610803x1.61x5.701%5.70%9.183%9.18%23-1.000000x-1.000000x1.597848x1.597848x1.60x2.216%2.22%3.541%3.54%-1.000000x-1.000000x1.596978x1.596978x1.60x3.524%3.52%5.628%5.63%24-1.000000x-1.000000x1.589934x1.589934x1.59x2.251%2.25%3.579%3.58%-1.000000x-1.000000x1.586045x1.586045x1.59x1.649%1.65%2.616%2.62%25-1.000000x-1.000000x1.570028x1.570028x1.57x1.087%1.09%1.707%1.71%26-1.000000x-1.000000x1.550495x1.550495x1.55x0.737%0.74%1.143%1.14%27-1.000000x-1.000000x1.526215x1.526215x1.53x2.660%2.66%4.060%4.06%-1.000000x-1.000000x1.522839x1.522839x1.52x14.269%14.3%21.730%21.7%28-1.000000x-1.000000x1.481288x1.481288x1.48x2.641%2.64%3.912%3.91%29-1.000000x-1.000000x1.476996x1.476996x1.48x1.170%1.17%1.728%1.73%30-1.000000x-1.000000x1.457167x1.457167x1.46x2.851%2.85%4.154%4.15%31-1.000000x-1.000000x1.436165x1.436165x1.44x2.115%2.11%3.037%3.04%32-1.000000x-1.000000x1.413654x1.413654x1.41x2.801%2.80%3.959%3.96%33-1.000000x-1.000000x1.387878x1.387878x1.39x7.705%7.70%10.693%10.7%34-1.000000x-1.000000x1.373250x1.373250x1.37x4.975%4.97%6.832%6.83%35-1.000000x-1.000000x1.368590x1.368590x1.37x1.742%1.74%2.385%2.38%36-1.000000x-1.000000x1.346658x1.346658x1.35x2.491%2.49%3.354%3.35%37-1.000000x-1.000000x1.286599x1.286599x1.29x1.699%1.70%2.186%2.19%38-1.000000x-1.000000x1.280610x1.280610x1.28x4.179%4.18%5.351%5.35%39-1.000000x-1.000000x1.274509x1.274509x1.27x5.228%5.23%6.663%6.66%40-1.000000x-1.000000x1.273345x1.273345x1.27x4.319%4.32%5.500%5.50%41-1.000000x-1.000000x1.238186x1.238186x1.24x4.026%4.03%4.985%4.99%42-1.000000x-1.000000x1.223931x1.223931x1.22x1.068%1.07%1.307%1.31%43-1.000000x-1.000000x1.213574x1.213574x1.21x2.357%2.36%2.860%2.86%44-1.000000x-1.000000x1.141406x1.141406x1.14x1.539%1.54%1.757%1.76%45-1.000000x-1.000000x1.124528x1.124528x1.12x5.872%5.87%6.603%6.60%46-1.000000x-1.000000x1.084697x1.084697x1.08x1.883%1.88%2.042%2.04%47-1.000000x-1.000000x1.046557x1.046557x1.05x1.291%1.29%1.351%1.35%48-1.000000x-1.000000x1.042857x1.042857x1.04x2.171%2.17%2.264%2.26%49-1.706858x-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 Wooster to the 50 most populous county subdivisions in the United States and to those entities that contain or substantially overlap with Wooster. The least populous of the compared county subdivisions has a population of 547,300.

No H.S. Diploma by County Subdivision#44

Percent of population 25 years of age and older without a high school diploma (or equivalent).
Scope: population of Wooster, selected other county subdivisions in the United States, and entities that contain Wooster
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 VegasPhoenixWooster Metro AreaWooster AreaWayne CountyWayneBostonSacramentoOrlandoAustinDenverUnited States of AmericaUnited StatesManhattanSan DiegoTampaSan JoseSan FranciscoTucsonAlbuquerqueTownship 1:Charlotte1, CharlotteColumbusTulsaEast North CentralOhioSalt Lake CitySalt Lk CityTown of HempsteadHempsteadMidwestZIP Code 44691ZIP 44691Northwest HarrisNW HarrisWashingtonWoosterWoosterAtlantaSeattleNortheast 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%308,569309k2614.573422%14.573422%14.6%11,02811.0k14.573422%14.573422%14.6%11,02811.0k14.325556%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%43,65343.7k4110.719464%10.719464%10.7%3,363,7843.36M10.514146%10.514146%10.5%825,155825k10.435356%10.435356%10.4%64,29464.3k4210.384134%10.384134%10.4%54,23054.2k4310.244520%10.244520%10.2%4,641,8354.64M10.188151%10.188151%10.2%3,05410.135583%10.135583%10.1%47,67947.7k4410.045421%10.045421%10.0%46,51046.5k459.887170%9.887170%9.9%1,7009.887170%9.887170%9.9%1,7009.538552%9.538552%9.5%37,37337.4k468.833573%8.833573%8.8%66,22066.2k478.418271%8.418271%8.4%31,44331.4k485.714681%5.714681%5.7%20,64420.6k494.913852%4.913852%4.9%20,32620.3k50
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older without a high school diploma (or equivalent).

Bachelor's Degrees by County Subdivision#45

Percent of population 25 years of age and older with a bachelor's degree or higher..
Scope: population of Wooster, selected other county subdivisions in the United States, and entities that contain Wooster
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-LakewoodMidwestPhoenixWoosterWoosterOrlandoEast North CentralAnaheim-Santa Ana-Garden GroveAnaheim-Santa An…SacramentoEast San Gabriel ValleyE San Gabriel VlyOntarioOhioZIP Code 44691ZIP 44691PhiladelphiaMiamiFort WorthSouthwest DallasSW DallasMilwaukeeFresnoLas VegasWooster Metro AreaWooster AreaWayne CountyWayneEl PasoBronxSan 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%593,529594k3328.748401%28.748401%28.7%4,94328.748401%28.748401%28.7%4,94328.535877%28.535877%28.5%112,142112k3428.462853%28.462853%28.5%8,931,6868.93M28.412939%28.412939%28.4%312,038312k3528.231204%28.231204%28.2%209,283209k3627.276345%27.276345%27.3%170,682171k3726.758411%26.758411%26.8%111,532112k3826.667466%26.667466%26.7%2,092,8752.09M26.577929%26.577929%26.6%7,96726.349720%26.349720%26.3%272,786273k3926.011156%26.011156%26.0%178,455178k4024.665414%24.665414%24.7%131,349131k4123.764821%23.764821%23.8%140,625141k4223.517740%23.517740%23.5%85,81285.8k4322.486319%22.486319%22.5%94,05694.1k4421.702666%21.702666%21.7%271,037271k4521.467650%21.467650%21.5%16,24516.2k21.467650%21.467650%21.5%16,24516.2k21.071885%21.071885%21.1%72,12072.1k4619.131504%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#46

Percent of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).
Scope: population of Wooster, selected other county subdivisions in the United States, and entities that contain Wooster
0%5%10%Count#WashingtonManhattanSan FranciscoBostonAtlantaSeattleSan JoseSeattle EastDenverSan DiegoAustinBaltimoreLos AngelesAlbuquerquePlanoChicagoTucsonTown of HempsteadHempsteadWoosterWoosterTampaMiamiNortheast DallasNE DallasSalt Lake CitySalt Lk CityHoustonPhiladelphiaZIP Code 44691ZIP 44691San Fernando ValleySan Fernando VlyTownship 1:Charlotte1, CharlotteOceanside-EscondidoOceanside-Escond…BrooklynSacramentoColumbusUnited States of AmericaUnited StatesTulsaPhoenixLong Beach-LakewoodLong Bch-LakewoodMidwestOrlandoEast North CentralFresnoAnaheim-Santa Ana-Garden GroveAnaheim-Santa An…QueensOhioNorthwest HarrisNW HarrisNortheast TarrantNE TarrantEast San Gabriel ValleyE San Gabriel VlyOntarioWooster Metro AreaWooster AreaWayne CountyWayneFort WorthLas VegasMilwaukeeSan BernardinoSan Antonio CentralSan Antonio CntrlEl PasoSouthwest DallasSW DallasBronxDetroit12.461852%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%23,19423.2k184.350355%4.350355%4.4%7484.350355%4.350355%4.4%7484.325266%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%38,51538.5k243.649586%3.649586%3.6%1,0943.601468%3.601468%3.6%45,61045.6k253.490252%3.490252%3.5%18,54218.5k263.466073%3.466073%3.5%15,21115.2k273.384967%3.384967%3.4%59,36259.4k283.380196%3.380196%3.4%25,05825.1k293.357865%3.357865%3.4%17,95418.0k303.336158%3.336158%3.3%7,127,6737.13M3.140490%3.140490%3.1%12,13312.1k313.010825%3.010825%3.0%62,13562.1k323.009440%3.009440%3.0%11,33911.3k332.893416%2.893416%2.9%1,311,0191.31M2.893233%2.893233%2.9%11,37011.4k342.855432%2.855432%2.9%896,039896k2.828959%2.828959%2.8%11,83311.8k352.763004%2.763004%2.8%30,34430.3k362.756960%2.756960%2.8%44,96545.0k372.683241%2.683241%2.7%210,582211k2.682967%2.682967%2.7%12,62112.6k382.630994%2.630994%2.6%9,827392.484535%2.484535%2.5%15,54715.5k402.324315%2.324315%2.3%9,688412.226715%2.226715%2.2%1,6852.226715%2.226715%2.2%1,6852.173239%2.173239%2.2%11,57311.6k422.155077%2.155077%2.2%26,91426.9k432.043126%2.043126%2.0%7,455441.807306%1.807306%1.8%8,895451.792414%1.792414%1.8%7,845461.745764%1.745764%1.7%5,975471.704476%1.704476%1.7%10,08610.1k481.664253%1.664253%1.7%15,06415.1k491.318660%1.318660%1.3%5,69350
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).

Under-Education Sex Ratio by County Subdivision#47

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 Wooster, selected other county subdivisions in the United States, and entities that contain Wooster
Female
Male
1x0x1xFM#ZIP 446911, CharlotteDetroitBaltimoreTulsaSW DallasWooster AreaWayneMidwestFresnoEast North CentralMilwaukeeUnited StatesOhioNE DallasHoustonHempsteadOrlandoPhiladelphiaOntarioSan BernardinoAustinAtlantaFort WorthPhoenixChicagoAlbuquerqueWashingtonSacramentoColumbusSalt Lk CityDenverNE TarrantTampaOceanside-EscondidoOceanside-Escond…NW HarrisBronxPlanoBrooklynSan Antonio CntrlSan Fernando VlyTucsonAnaheim-Santa Ana-Gdn GrvAnaheim-Santa An…Los AngelesLas VegasBostonE San Gabriel VlyQueensMiamiManhattanWoosterWoosterSeattleLong Bch-LakewoodSeattle EastSan JoseSan DiegoSan FranciscoEl Paso-1.000000x-1.000000x1.287259x1.287259x1.29x8.969%8.97%11.546%11.5%-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-1.000000x1.151379x1.151379x1.15x13.576%13.6%15.631%15.6%-1.000000x-1.000000x1.151379x1.151379x1.15x13.576%13.6%15.631%15.6%-1.000000x-1.000000x1.127915x1.127915x1.13x9.647%9.65%10.881%10.9%-1.000000x-1.000000x1.127206x1.127206x1.13x20.830%20.8%23.479%23.5%6-1.000000x-1.000000x1.125371x1.125371x1.13x10.108%10.1%11.375%11.4%-1.000000x-1.000000x1.123984x1.123984x1.12x16.526%16.5%18.574%18.6%7-1.000000x-1.000000x1.109070x1.109070x1.11x12.369%12.4%13.719%13.7%-1.000000x-1.000000x1.105363x1.105363x1.11x10.008%10.0%11.063%11.1%-1.000000x-1.000000x1.099797x1.099797x1.10x19.814%19.8%21.791%21.8%8-1.000000x-1.000000x1.099188x1.099188x1.10x20.902%20.9%22.975%23.0%9-1.000000x-1.000000x1.092101x1.092101x1.09x9.951%9.95%10.868%10.9%10-1.000000x-1.000000x1.090284x1.090284x1.09x13.111%13.1%14.294%14.3%11-1.000000x-1.000000x1.090163x1.090163x1.09x16.700%16.7%18.206%18.2%12-1.000000x-1.000000x1.088515x1.088515x1.09x16.417%16.4%17.871%17.9%13-1.000000x-1.000000x1.081887x1.081887x1.08x26.536%26.5%28.709%28.7%14-1.000000x-1.000000x1.078150x1.078150x1.08x13.148%13.1%14.176%14.2%15-1.000000x-1.000000x1.073220x1.073220x1.07x9.215%9.21%9.889%9.89%16-1.000000x-1.000000x1.071348x1.071348x1.07x19.379%19.4%20.762%20.8%17-1.000000x-1.000000x1.069008x1.069008x1.07x14.467%14.5%15.465%15.5%18-1.000000x-1.000000x1.068021x1.068021x1.07x16.372%16.4%17.486%17.5%19-1.000000x-1.000000x1.066879x1.066879x1.07x11.714%11.7%12.497%12.5%20-1.000000x-1.000000x1.064309x1.064309x1.06x9.751%9.75%10.378%10.4%21-1.000000x-1.000000x1.053268x1.053268x1.05x13.558%13.6%14.280%14.3%22-1.000000x-1.000000x1.052237x1.052237x1.05x11.098%11.1%11.678%11.7%23-1.000000x-1.000000x1.051272x1.051272x1.05x10.176%10.2%10.697%10.7%24-1.000000x-1.000000x1.049933x1.049933x1.05x13.307%13.3%13.971%14.0%25-1.000000x-1.000000x1.040742x1.040742x1.04x8.257%8.26%8.594%8.59%26-1.000000x-1.000000x1.040003x1.040003x1.04x12.734%12.7%13.244%13.2%27-1.000000x-1.000000x1.039910x1.039910x1.04x15.694%15.7%16.321%16.3%28-1.000000x-1.000000x1.038394x1.038394x1.04x9.953%9.95%10.335%10.3%29-1.000000x-1.000000x1.030539x1.030539x1.03x28.448%28.4%29.316%29.3%30-1.000000x-1.000000x1.023151x1.023151x1.02x5.652%5.65%5.783%5.78%31-1.000000x-1.000000x1.018960x1.018960x1.02x19.845%19.8%20.221%20.2%32-1.000000x-1.000000x1.003929x1.003929x1.00x28.944%28.9%29.058%29.1%33-1.000000x-1.000000x1.003840x1.003840x1.00x19.308%19.3%19.383%19.4%34-1.006471x-1.006471x1.01x1.000000x1.000000x12.301%12.3%12.222%12.2%35-1.008020x-1.008020x1.01x1.000000x1.000000x22.734%22.7%22.553%22.6%36-1.013004x-1.013004x1.01x1.000000x1.000000x24.995%25.0%24.674%24.7%37-1.016645x-1.016645x1.02x1.000000x1.000000x16.036%16.0%15.774%15.8%38-1.022333x-1.022333x1.02x1.000000x1.000000x14.476%14.5%14.159%14.2%39-1.026902x-1.026902x1.03x1.000000x1.000000x20.723%20.7%20.180%20.2%40-1.027762x-1.027762x1.03x1.000000x1.000000x19.596%19.6%19.067%19.1%41-1.030897x-1.030897x1.03x1.000000x1.000000x22.136%22.1%21.473%21.5%42-1.044246x-1.044246x1.04x1.000000x1.000000x13.260%13.3%12.698%12.7%43-1.048147x-1.048147x1.05x1.000000x1.000000x10.102%10.1%9.638%9.64%-1.048147x-1.048147x1.05x1.000000x1.000000x10.102%10.1%9.638%9.64%-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#48

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 Wooster, selected other county subdivisions in the United States, and entities that contain Wooster
Female
Male
1x0x1x2xFM#WoosterWoosterZIP 44691El PasoSalt Lk CityPlanoTulsaAlbuquerqueNE DallasFort WorthOhioOrlandoPhoenixWooster AreaWayneTucson1, CharlotteEast North CentralMidwestNW HarrisLas VegasSeattle EastSan Antonio CntrlSan DiegoUnited StatesSan JoseHempsteadFresnoNE TarrantTampaSan Fernando VlyE San Gabriel VlyHoustonSan BernardinoColumbusMiamiAtlantaMilwaukeeAnaheim-Santa Ana-Gdn GrvAnaheim-Santa An…SacramentoPhiladelphiaOceanside-EscondidoOceanside-Escond…Los AngelesAustinBaltimoreWashingtonQueensSW DallasBrooklynManhattanChicagoSeattleBostonBronxOntarioLong Bch-LakewoodDenverSan FranciscoDetroit-1.000000x-1.000000x2.388350x2.388350x2.39x2.650%2.65%6.329%6.33%-1.000000x-1.000000x2.388350x2.388350x2.39x2.650%2.65%6.329%6.33%-1.000000x-1.000000x2.368602x2.368602x2.37x2.215%2.22%5.248%5.25%-1.000000x-1.000000x2.132933x2.132933x2.13x1.146%1.15%2.445%2.44%1-1.000000x-1.000000x2.053360x2.053360x2.05x2.488%2.49%5.109%5.11%2-1.000000x-1.000000x1.782054x1.782054x1.78x3.355%3.35%5.978%5.98%3-1.000000x-1.000000x1.720683x1.720683x1.72x2.338%2.34%4.022%4.02%4-1.000000x-1.000000x1.707718x1.707718x1.71x3.458%3.46%5.905%5.91%5-1.000000x-1.000000x1.692229x1.692229x1.69x2.857%2.86%4.836%4.84%6-1.000000x-1.000000x1.684272x1.684272x1.68x1.637%1.64%2.757%2.76%7-1.000000x-1.000000x1.669500x1.669500x1.67x2.031%2.03%3.391%3.39%-1.000000x-1.000000x1.660799x1.660799x1.66x2.196%2.20%3.647%3.65%8-1.000000x-1.000000x1.659024x1.659024x1.66x2.280%2.28%3.783%3.78%9-1.000000x-1.000000x1.658480x1.658480x1.66x1.687%1.69%2.798%2.80%-1.000000x-1.000000x1.658480x1.658480x1.66x1.687%1.69%2.798%2.80%-1.000000x-1.000000x1.621815x1.621815x1.62x3.429%3.43%5.561%5.56%10-1.000000x-1.000000x1.611479x1.611479x1.61x2.711%2.71%4.369%4.37%11-1.000000x-1.000000x1.597848x1.597848x1.60x2.216%2.22%3.541%3.54%-1.000000x-1.000000x1.589934x1.589934x1.59x2.251%2.25%3.579%3.58%-1.000000x-1.000000x1.579303x1.579303x1.58x2.100%2.10%3.317%3.32%12-1.000000x-1.000000x1.576623x1.576623x1.58x1.677%1.68%2.643%2.64%13-1.000000x-1.000000x1.557664x1.557664x1.56x4.733%4.73%7.372%7.37%14-1.000000x-1.000000x1.540473x1.540473x1.54x1.423%1.42%2.192%2.19%15-1.000000x-1.000000x1.529565x1.529565x1.53x4.164%4.16%6.370%6.37%16-1.000000x-1.000000x1.526215x1.526215x1.53x2.660%2.66%4.060%4.06%-1.000000x-1.000000x1.514156x1.514156x1.51x4.979%4.98%7.539%7.54%17-1.000000x-1.000000x1.488724x1.488724x1.49x3.608%3.61%5.371%5.37%18-1.000000x-1.000000x1.484269x1.484269x1.48x2.293%2.29%3.404%3.40%19-1.000000x-1.000000x1.481801x1.481801x1.48x2.138%2.14%3.168%3.17%20-1.000000x-1.000000x1.476874x1.476874x1.48x3.518%3.52%5.196%5.20%21-1.000000x-1.000000x1.460302x1.460302x1.46x2.944%2.94%4.299%4.30%22-1.000000x-1.000000x1.451775x1.451775x1.45x2.041%2.04%2.963%2.96%23-1.000000x-1.000000x1.424636x1.424636x1.42x3.092%3.09%4.404%4.40%24-1.000000x-1.000000x1.423621x1.423621x1.42x1.501%1.50%2.137%2.14%25-1.000000x-1.000000x1.413654x1.413654x1.41x2.801%2.80%3.959%3.96%26-1.000000x-1.000000x1.395174x1.395174x1.40x3.384%3.38%4.722%4.72%27-1.000000x-1.000000x1.391590x1.391590x1.39x5.799%5.80%8.070%8.07%28-1.000000x-1.000000x1.368590x1.368590x1.37x1.742%1.74%2.385%2.38%29-1.000000x-1.000000x1.362600x1.362600x1.36x2.347%2.35%3.199%3.20%30-1.000000x-1.000000x1.359928x1.359928x1.36x2.888%2.89%3.927%3.93%31-1.000000x-1.000000x1.341930x1.341930x1.34x3.216%3.22%4.316%4.32%32-1.000000x-1.000000x1.310218x1.310218x1.31x3.011%3.01%3.945%3.95%33-1.000000x-1.000000x1.308108x1.308108x1.31x4.045%4.05%5.292%5.29%34-1.000000x-1.000000x1.303834x1.303834x1.30x4.384%4.38%5.716%5.72%35-1.000000x-1.000000x1.303196x1.303196x1.30x4.332%4.33%5.645%5.65%36-1.000000x-1.000000x1.300117x1.300117x1.30x10.922%10.9%14.199%14.2%37-1.000000x-1.000000x1.285200x1.285200x1.29x2.428%2.43%3.121%3.12%38-1.000000x-1.000000x1.265486x1.265486x1.27x1.515%1.51%1.917%1.92%39-1.000000x-1.000000x1.262281x1.262281x1.26x3.021%3.02%3.814%3.81%40-1.000000x-1.000000x1.245683x1.245683x1.25x9.673%9.67%12.050%12.1%41-1.000000x-1.000000x1.238186x1.238186x1.24x4.026%4.03%4.985%4.99%42-1.000000x-1.000000x1.228890x1.228890x1.23x5.961%5.96%7.326%7.33%43-1.000000x-1.000000x1.221037x1.221037x1.22x6.643%6.64%8.112%8.11%44-1.000000x-1.000000x1.202385x1.202385x1.20x1.526%1.53%1.834%1.83%45-1.000000x-1.000000x1.198236x1.198236x1.20x2.119%2.12%2.539%2.54%46-1.000000x-1.000000x1.181998x1.181998x1.18x2.766%2.77%3.269%3.27%47-1.000000x-1.000000x1.129665x1.129665x1.13x5.378%5.38%6.075%6.08%48-1.000000x-1.000000x1.098720x1.098720x1.10x7.194%7.19%7.905%7.90%49-1.000000x-1.000000x1.046557x1.046557x1.05x1.291%1.29%1.351%1.35%50
F percentage of females in category
M percentage of males in category
# rank of county subdivision out of 50 by male-to-female sex ratio

Definitions

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

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

The coarse levels of educational attainment are as follows:

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

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

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State:
Ohio
County:
Wayne
Metro Area:
Wooster Area
City:
Wooster
ZIP Code:
44691
Unified School Districts:
Green, Triway, Wooster
Congressional District:
OH-16
State Senate District:
OH-27
State House District:
OH-1
Neighboring Townships:
Franklin, Wayne, Wooster
Nearby Townships:
Canaan, Chester, Clinton, Congress, East Union, Green, Milton, Plain, Salt Creek, Sugar Creek