Educational Attainment in Canton, Stark County, Ohio (City)

Educational Attainment#1

Highest level of education among people aged 25 years and older.
Scope: population of Stark County and Canton
Canton
Stark County
0%10%20%30%40%50%60%CountHigher Degree1H.S. Diploma2No H.S. Diploma222.488868%31.054737%22.488868%22.5%10,50510.5k61.879175%59.380180%61.879175%61.9%28,90528.9k15.631958%9.565083%15.631958%15.6%7,302
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 Stark County at large.
Scope: population of Stark County and Canton
-50%0%+50%%ref.Higher Degree1H.S. Diploma2No H.S. Diploma2-27.583131%-27.583131%-27.6%22.489%22.5%31.055%31.1%4.208465%4.208465%+4.2%61.879%61.9%59.380%59.4%63.427307%63.427307%+63.4%15.632%15.6%9.565%9.57%
% percentage with given level in Canton
ref. percentage with given level in Stark 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 Stark County and Canton
Canton
Stark County
0%10%20%30%CountDoctorate1Professional1Master's1Bachelor's1Associate's1Some CollegeHigh School2Some H.S.3Less than H.S.3None0.387481%0.763568%0.387481%0.4%1810.858452%1.199838%0.858452%0.9%4013.690700%6.178488%3.690700%3.7%1,7249.672033%14.489634%9.672033%9.7%4,5187.880202%8.423208%7.880202%7.9%3,68124.905806%21.488494%24.905806%24.9%11,63411.6k36.973369%37.891686%36.973369%37.0%17,27117.3k11.206970%6.801399%11.206970%11.2%5,2353.018496%1.888440%3.018496%3.0%1,4101.406491%0.875244%1.406491%1.4%657
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 Stark County at large.
Scope: population of Stark County and Canton
-50%0%+50%%ref.Doctorate1Professional1Master's1Bachelor's1Associate's1Some CollegeHigh School2Some H.S.3Less than H.S.3None-49.253947%-49.253947%-49.3%0.387%0.39%0.764%0.76%-28.452674%-28.452674%-28.5%0.858%0.86%1.200%1.20%-40.265312%-40.265312%-40.3%3.691%3.69%6.178%6.18%-33.248606%-33.248606%-33.2%9.672%9.67%14.490%14.5%-6.446550%-6.446550%-6.4%7.880%7.88%8.423%8.42%15.902982%15.902982%+15.9%24.906%24.9%21.488%21.5%-2.423533%-2.423533%-2.4%36.973%37.0%37.892%37.9%64.774492%64.774492%+64.8%11.207%11.2%6.801%6.80%59.840714%59.840714%+59.8%3.018%3.02%1.888%1.89%60.697012%60.697012%+60.7%1.406%1.41%0.875%0.88%
% percentage with given level in Canton
ref. percentage with given level in Stark 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 Stark County and Canton
More Females More Males
Stark County
Canton
20%10%0%10%FMHigher Degree1H.S. Diploma2No H.S. Diploma2-21.001390%-5.864160%-21.001390%21%24.428%24.4%20.188%20.2%4.294407%2.509953%4.294407%4%60.687%60.7%63.293%63.3%10.975212%3.116107%10.975212%11%14.885%14.9%16.518%16.5%
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 Stark County and Canton
More Females More Males
Stark County
Canton
50%0%50%FMDoctorate1Professional1Master's1Bachelor's1Associate's1Some CollegeHigh School2Some H.S.3Less than H.S.3None17.344367%38.763564%17.344367%17%0.359%0.36%0.421%0.42%-24.343119%-24.343119%24%87.852997%0.943%0.94%0.758%0.76%-26.914192%-17.181061%-26.914192%27%4.087%4.09%3.220%3.22%-1.196815%-1.196815%1%3.187539%9.725%9.72%9.610%9.61%-50.751252%-30.954247%-50.751252%51%9.314%9.31%6.179%6.18%-9.577617%-9.577617%10%8.018738%25.943%25.9%23.675%23.7%-0.495109%14.027286%14.027286%14%34.744%34.7%39.618%39.6%12.941401%0.794253%12.941401%13%10.581%10.6%11.950%12.0%-2.570557%-2.570557%3%4.479901%3.053%3.05%2.977%2.98%27.256737%19.613167%27.256737%27%1.251%1.25%1.591%1.59%
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 Stark County and Canton
Canton
Stark County
0%5%10%15%B.X.Total65+45-6435-4425-347.612357%9.679753%7.612357%7.6%79110,39110.4k9.925282%14.194529%9.925282%9.9%1,78017,93417.9k9.193224%17.638521%9.193224%9.2%7768,44111.773577%19.446635%11.773577%11.8%1,1719,946
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 Stark County at large.
Scope: population of Stark County and Canton
40%30%20%10%0%%ref.65+45-6435-4425-34-21.357942%-21.357942%21.4%7.612%7.61%9.680%9.68%-30.076711%-30.076711%30.1%9.925%9.93%14.195%14.2%-47.879850%-47.879850%47.9%9.193%9.19%17.639%17.6%-39.456994%-39.456994%39.5%11.774%11.8%19.447%19.4%
% percentage in Canton with a Bachelor's degree
ref percentage in Stark 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 Stark County and Canton
More Females More Males
Stark County
Canton
40%20%0%20%40%FM65+45-6435-4425-3458.207192%53.882648%58.207192%58.2%6.175%6.17%9.769%9.77%-2.404162%-2.404162%2.4%5.506831%10.039%10.0%9.803%9.80%-51.019957%-18.202838%-51.019957%51.0%10.849%10.8%7.184%7.18%-12.343926%-25.817681%-12.343926%12.3%12.428%12.4%11.062%11.1%
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 Stark County and Canton
Canton
Stark County
$0k$20k$40k$60kCount%Graduate Degree1Bachelor's DegreeSome CollegeH.S. Diploma2No H.S. Diploma2Total$51,295.000000$60,203.000000$51,295.000000$51.3k2,3064.937%4.94%$39,931.000000$46,569.000000$39,931.000000$39.9k4,5189.672%9.67%$25,083.000000$31,543.000000$25,083.000000$25.1k15,31515.3k32.786%32.8%$21,877.000000$27,479.000000$21,877.000000$21.9k17,27117.3k36.973%37.0%$13,815.000000$19,043.000000$13,815.000000$13.8k7,30215.632%15.6%$25,060.000000$32,906.000000$25,060.000000$25.1k46,71246.7k100.000%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 Stark County and Canton
Female Male
Stark County
Canton
Shaded bar tips show excess over facing bar.
$50k$0k$50kFMGraduate Degree1Bachelor's DegreeSome CollegeH.S. Diploma2No H.S. Diploma2Total$-44,900.000000$-53,502.000000$-44,900.000000$44.9k$44,900.000000$16,146.000000$53,502.000000$13,696.000000$61,046.000000$61.0k1,366940$-38,567.000000$-36,940.000000$-38,567.000000$38.6k$38,567.000000$3,288.000000$36,940.000000$24,683.000000$41,855.000000$41.9k2,4652,053$-19,774.000000$-24,517.000000$-19,774.000000$19.8k$19,774.000000$13,689.000000$24,517.000000$16,536.000000$33,463.000000$33.5k8,9376,378$-15,807.000000$-21,203.000000$-15,807.000000$15.8k$15,807.000000$10,322.000000$21,203.000000$13,610.000000$26,129.000000$26.1k8,8078,464$-8,293.000000$-11,057.000000$-8,293.000000$8.3k$8,293.000000$13,112.000000$11,057.000000$15,739.000000$21,405.000000$21.4k3,7733,529$-19,856.000000$-26,033.000000$-19,856.000000$19.9k$19,856.000000$10,268.000000$26,033.000000$15,185.000000$30,124.000000$30.1k25,34825.3k21,36421.4k
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 Stark County and Canton
Canton
Stark County
0%10%20%30%40%50%CountBachelor's Degree1Some College2H.S. Diploma3No H.S. Diploma350.000000%42.391304%50.000000%50.0%1250.000000%57.608696%50.000000%50.0%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 Stark County and Canton
Canton
Stark County
0%20%40%60%80%CountBachelor's Degree1Some College2H.S. Diploma3No H.S. Diploma385.413290%84.209644%85.413290%85.4%4,74368.039404%75.666499%68.039404%68.0%9,18661.738924%69.898927%61.738924%61.7%7,81843.961772%47.988648%43.961772%44.0%2,024
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 Stark County and Canton
Female Male
Stark County
Canton
Shaded bar tips show excess over facing bar.
40%20%0%20%40%MFWhite1BlackAsianHispanic2Other1-13.872832%-8.819133%-13.872832%13.9%13.872832%2.432867%8.819133%0.300848%16.305699%16.3%2,4922,544-14.309800%-0.546831%-12.535897%-0.887679%-14.856631%14.9%14.309800%12.535897%14.309800%14.3%679829-0.000000%-22.695035%-9.058403%-3.062809%-22.695035%22.7%0.000000%9.058403%0.000000%0.0%032-42.905405%-27.337701%-42.905405%42.9%42.905405%0.741829%27.337701%5.476537%43.647235%43.6%292254-19.523269%-14.519604%-19.523269%19.5%19.523269%1.983414%14.519604%0.671495%21.506683%21.5%177172
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 Stark County and Canton
Female Male
Stark County
Canton
Shaded bar tips show excess over facing bar.
40%20%0%20%40%60%MFWhite1BlackAsianHispanic2Other1-15.860760%-1.600250%-23.019432%-17.461010%17.5%15.860760%23.019432%0.648853%15.860760%15.9%2,4243,202-8.154122%-9.501810%-2.026672%-8.154122%8.2%8.154122%0.107206%9.501810%8.261328%8.3%392455-43.971631%-57.056277%-43.971631%44.0%43.971631%4.712579%57.056277%12.550398%48.684211%48.7%3762-8.221226%-1.069315%-16.685206%-1.539928%-9.290541%9.3%8.221226%16.685206%8.221226%8.2%5555-6.469921%-14.519604%-6.469921%6.5%6.469921%3.858147%14.519604%3.429114%10.328068%10.3%8557
M number of males in category
F number of females in category
1non-Hispanic 2excluding black and Asian Hispanics

Map of Educational Attainment by Neighborhood in Canton

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

Percentage of the population 25 years and older with given highest level of educational attainment
7%13%19%24%30%36%

Coarse: High School Diploma Educational Attainment by Neighborhood#17

Percentage of the population 25 years and older with given highest level of educational attainment
53.8%57.1%60.4%63.7%66.9%70.2%

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

Percentage of the population 25 years and older with given highest level of educational attainment
8.6%12.3%15.9%19.5%23.1%26.7%

Detailed: Doctorate Degree Educational Attainment by Neighborhood#19

Percentage of the population 25 years and older with given highest level of educational attainment
0.00%0.22%0.43%0.65%0.87%1.09%

Detailed: Professional Degree Educational Attainment by Neighborhood#20

Percentage of the population 25 years and older with given highest level of educational attainment
0.0%0.6%1.1%1.7%2.2%2.8%

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

Percentage of the population 25 years and older with given highest level of educational attainment
0.4%2.3%4.1%6.0%7.8%9.7%

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

Percentage of the population 25 years and older with given highest level of educational attainment
1.5%5.4%9.2%12.9%16.7%20.6%

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

Percentage of the population 25 years and older with given highest level of educational attainment
3.5%5.1%6.7%8.2%9.7%11.3%

Detailed: Some College Educational Attainment by Neighborhood#24

Percentage of the population 25 years and older with given highest level of educational attainment
16.8%19.1%21.4%23.7%26.0%28.4%

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

Percentage of the population 25 years and older with given highest level of educational attainment
30.1%33.1%36.1%39.0%41.9%44.9%

Detailed: Some High School Educational Attainment by Neighborhood#26

Percentage of the population 25 years and older with given highest level of educational attainment
4.1%7.9%11.6%15.3%19.0%22.7%

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

Percentage of the population 25 years and older with given highest level of educational attainment
0.8%1.8%2.7%3.6%4.5%5.5%

Detailed: None Educational Attainment by Neighborhood#28

Percentage of the population 25 years and older with given highest level of educational attainment
0.07%0.57%1.07%1.57%2.07%2.57%
Road Data ©OpenStreetMap

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Map of Educational Attainment by Tract in Canton

Coarse: Post-Secondary Degree Educational Attainment by Tract#29

Percentage of the population 25 years and older with given highest level of educational attainment
7%16%25%33%42%51%

Coarse: High School Diploma Educational Attainment by Tract#30

Percentage of the population 25 years and older with given highest level of educational attainment
44%50%55%61%66%72%

Coarse: No High School Diploma Educational Attainment by Tract#31

Percentage of the population 25 years and older with given highest level of educational attainment
2%8%13%19%24%30%

Detailed: Doctorate Degree Educational Attainment by Tract#32

Percentage of the population 25 years and older with given highest level of educational attainment
0.00%0.47%0.94%1.41%1.88%2.35%

Detailed: Professional Degree Educational Attainment by Tract#33

Percentage of the population 25 years and older with given highest level of educational attainment
0.0%0.7%1.4%2.1%2.8%3.5%

Detailed: Master's Degree Educational Attainment by Tract#34

Percentage of the population 25 years and older with given highest level of educational attainment
0.0%2.4%4.9%7.3%9.8%12.3%

Detailed: Bachelor's Degree Educational Attainment by Tract#35

Percentage of the population 25 years and older with given highest level of educational attainment
1%7%12%18%23%29%

Detailed: Associate's Degree Educational Attainment by Tract#36

Percentage of the population 25 years and older with given highest level of educational attainment
3.2%5.4%7.4%9.5%11.6%13.7%

Detailed: Some College Educational Attainment by Tract#37

Percentage of the population 25 years and older with given highest level of educational attainment
15.8%20.8%25.8%30.8%35.7%40.8%

Detailed: High School Diploma or Equivalent Educational Attainment by Tract#38

Percentage of the population 25 years and older with given highest level of educational attainment
25%30%35%40%45%51%

Detailed: Some High School Educational Attainment by Tract#39

Percentage of the population 25 years and older with given highest level of educational attainment
1.9%6.1%10.2%14.4%18.5%22.8%

Detailed: Less than High School Educational Attainment by Tract#40

Percentage of the population 25 years and older with given highest level of educational attainment
0.0%1.6%3.2%4.8%6.4%8.1%

Detailed: None Educational Attainment by Tract#41

Percentage of the population 25 years and older with given highest level of educational attainment
0.0%0.8%1.6%2.3%3.1%4.0%
Road Data ©OpenStreetMap

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Educational Attainment by Neighborhood in Canton

There are 16 neighborhoods that are fully or partially contained within Canton (9 fully and 7 partially). This section compares all 16 of those to each other, Canton, and other entities that contain or substantially overlap with Canton.

No H.S. Diploma by Neighborhood#42

Percent of population 25 years of age and older without a high school diploma (or equivalent).
Scope: population of Canton, selected neighborhoods in Canton, and entities that contain Canton
0%5%10%15%20%25%Count#Whittier Park NeighborhoodWhittier ParkDowntown NeighborhoodDowntownSummit NeighborhoodSummitGibbs NeighborhoodGibbsCrystal Park NeighborhoodCrystal ParkFairmount NeighborhoodFairmountCantonCantonUnited States of AmericaUnited StatesWest Park NeighborhoodWest ParkVassar Park NeighborhoodVassar ParkEdgefield NeighborhoodEdgefieldMarket Heights NeighborhoodMarket HtsEdmeyer Park NeighborhoodEdmeyer ParkRidgewood NeighborhoodRidgewoodEast North CentralOhioColonial Heights NeighborhoodColonial HtsMidwestWestbrook NeighborhoodWestbrookCanton and Massillon Metro AreaCanton AreaStark CountyStarkMount Vernon NeighborhoodMount VernonHarter Heights NeighborhoodHarter Hts26.691210%26.691210%26.7%8283124.849417%24.849417%24.8%252253222.595520%22.595520%22.6%458459322.146985%22.146985%22.1%871419.660390%19.660390%19.7%788517.094351%17.094351%17.1%403615.631958%15.631958%15.6%7,30215.631958%15.631958%15.6%7,30213.020590%13.020590%13.0%27,818,38027.8M12.974706%12.974706%13.0%517518712.654090%12.654090%12.7%308309811.339686%11.339686%11.3%280281911.230966%11.230966%11.2%1151010.957607%10.957607%11.0%2122131110.938507%10.938507%10.9%2362371210.719464%10.719464%10.7%3,363,7843.36M10.514146%10.514146%10.5%825,155825k10.513595%10.513595%10.5%1071310.244520%10.244520%10.2%4,641,8354.64M10.233930%10.233930%10.2%298149.808753%9.808753%9.8%27,34727.3k9.565083%9.565083%9.6%24,75324.8k9.199736%9.199736%9.2%262263158.666202%8.666202%8.7%20420516
Count number of people in category
# rank of neighborhood out of 16 by percentage of population 25 years of age and older without a high school diploma (or equivalent).

Bachelor's Degrees by Neighborhood#43

Percent of population 25 years of age and older with a bachelor's degree or higher..
Scope: population of Canton, selected neighborhoods in Canton, and entities that contain Canton
0%10%20%30%Count#United States of AmericaUnited StatesMidwestEast North CentralOhioMount Vernon NeighborhoodMount VernonVassar Park NeighborhoodVassar ParkRidgewood NeighborhoodRidgewoodColonial Heights NeighborhoodColonial HtsMarket Heights NeighborhoodMarket HtsEdgefield NeighborhoodEdgefieldStark CountyStarkCanton and Massillon Metro AreaCanton AreaEdmeyer Park NeighborhoodEdmeyer ParkWest Park NeighborhoodWest ParkHarter Heights NeighborhoodHarter HtsCantonCantonWestbrook NeighborhoodWestbrookGibbs NeighborhoodGibbsFairmount NeighborhoodFairmountDowntown NeighborhoodDowntownCrystal Park NeighborhoodCrystal ParkWhittier Park NeighborhoodWhittier ParkSummit NeighborhoodSummit30.315023%30.315023%30.3%64,767,78764.8M28.952816%28.952816%29.0%13,118,64213.1M28.462853%28.462853%28.5%8,931,6868.93M26.667466%26.667466%26.7%2,092,8752.09M26.650688%26.650688%26.7%761762126.226812%26.226812%26.2%639225.572905%25.572905%25.6%553325.317221%25.317221%25.3%258259425.220480%25.220480%25.2%259525.005608%25.005608%25.0%619622.631528%22.631528%22.6%58,56758.6k21.826960%21.826960%21.8%60,85460.9k21.584280%21.584280%21.6%419717.954101%17.954101%18.0%716815.720388%15.720388%15.7%371914.608666%14.608666%14.6%6,82414.608666%14.608666%14.6%6,82412.103011%12.103011%12.1%3523531010.036118%10.036118%10.0%394395118.695461%8.695461%8.7%205125.154354%5.154354%5.2%52134.154211%4.154211%4.2%166167143.129314%3.129314%3.1%910152.042161%2.042161%2.0%4116
Count number of people in category
# rank of neighborhood out of 16 by percentage of population 25 years of age and older with a bachelor's degree or higher..

Very Advanced Degrees by Neighborhood#44

Percent of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).
Scope: population of Canton, selected neighborhoods in Canton, and entities that contain Canton
0%1%2%3%Count#United States of AmericaUnited StatesVassar Park NeighborhoodVassar ParkMidwestEast North CentralWest Park NeighborhoodWest ParkOhioMount Vernon NeighborhoodMount VernonMarket Heights NeighborhoodMarket HtsEdgefield NeighborhoodEdgefieldStark CountyStarkCanton and Massillon Metro AreaCanton AreaCantonCantonRidgewood NeighborhoodRidgewoodEdmeyer Park NeighborhoodEdmeyer ParkDowntown NeighborhoodDowntownFairmount NeighborhoodFairmountWestbrook NeighborhoodWestbrookGibbs NeighborhoodGibbsColonial Heights NeighborhoodColonial HtsHarter Heights NeighborhoodHarter HtsCrystal Park NeighborhoodCrystal ParkSummit NeighborhoodSummitWhittier Park NeighborhoodWhittier Park3.336158%3.336158%3.3%7,127,6737.13M3.256586%3.256586%3.3%7912.893416%2.893416%2.9%1,311,0191.31M2.855432%2.855432%2.9%896,039896k2.789861%2.789861%2.8%11122.683241%2.683241%2.7%210,582211k2.398283%2.398283%2.4%686932.279404%2.279404%2.3%2342.219369%2.219369%2.2%545551.963406%1.963406%2.0%5,0811.919283%1.919283%1.9%5,3511.245933%1.245933%1.2%5821.245933%1.245933%1.2%5821.206934%1.206934%1.2%2661.174573%1.174573%1.2%222370.758308%0.758308%0.8%7880.599949%0.599949%0.6%1490.567045%0.567045%0.6%1617100.459516%0.459516%0.5%18110.422961%0.422961%0.4%4120.407354%0.407354%0.4%910130.000000%0.000000%0.0%0140.000000%0.000000%0.0%0150.000000%0.000000%0.0%016
Count number of people in category
# rank of neighborhood out of 16 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 Neighborhood#45

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 Canton, selected neighborhoods in Canton, and entities that contain Canton
Female
Male
2x1x0x1xFM#Mount VernonDowntownWest ParkWhittier ParkVassar ParkEdgefieldEdmeyer ParkMidwestEast North CentralCantonCantonUnited StatesOhioCanton AreaStarkMarket HtsRidgewoodColonial HtsCrystal ParkGibbsHarter HtsFairmountWestbrookSummit-1.000000x-1.000000x1.909369x1.909369x1.91x6.523%6.52%12.455%12.5%1-1.000000x-1.000000x1.581176x1.581176x1.58x18.622%18.6%29.444%29.4%2-1.000000x-1.000000x1.424549x1.424549x1.42x10.878%10.9%15.496%15.5%3-1.000000x-1.000000x1.361173x1.361173x1.36x22.845%22.8%31.096%31.1%4-1.000000x-1.000000x1.248828x1.248828x1.25x11.169%11.2%13.948%13.9%5-1.000000x-1.000000x1.238831x1.238831x1.24x10.266%10.3%12.718%12.7%6-1.000000x-1.000000x1.158530x1.158530x1.16x10.187%10.2%11.802%11.8%7-1.000000x-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-1.000000x1.109752x1.109752x1.11x14.885%14.9%16.518%16.5%-1.000000x-1.000000x1.109752x1.109752x1.11x14.885%14.9%16.518%16.5%-1.000000x-1.000000x1.109070x1.109070x1.11x12.369%12.4%13.719%13.7%-1.000000x-1.000000x1.105363x1.105363x1.11x10.008%10.0%11.063%11.1%-1.000000x-1.000000x1.051981x1.051981x1.05x9.572%9.57%10.070%10.1%-1.000000x-1.000000x1.031161x1.031161x1.03x9.426%9.43%9.720%9.72%-1.000000x-1.000000x1.030186x1.030186x1.03x11.086%11.1%11.421%11.4%8-1.000000x-1.000000x1.027227x1.027227x1.03x10.804%10.8%11.098%11.1%9-1.000000x-1.000000x1.027018x1.027018x1.03x10.390%10.4%10.670%10.7%10-1.048609x-1.048609x1.05x1.000000x1.000000x20.106%20.1%19.174%19.2%11-1.063012x-1.063012x1.06x1.000000x1.000000x22.749%22.7%21.401%21.4%12-1.124848x-1.124848x1.12x1.000000x1.000000x9.175%9.17%8.157%8.16%13-1.246945x-1.246945x1.25x1.000000x1.000000x18.859%18.9%15.124%15.1%14-1.357868x-1.357868x1.36x1.000000x1.000000x11.670%11.7%8.595%8.59%15-2.148588x-2.148588x2.15x1.000000x1.000000x30.086%30.1%14.003%14.0%16
F percentage of females in category
M percentage of males in category
# rank of neighborhood out of 16 by male-to-female sex ratio

Over-Education Sex Ratio by Neighborhood#46

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 Canton, selected neighborhoods in Canton, and entities that contain Canton
Female
Male
10x5x0x5x10xFM#Colonial HtsEdgefieldMount VernonMarket HtsFairmountRidgewoodWest ParkOhioStarkCanton AreaEast North CentralMidwestUnited StatesEdmeyer ParkHarter HtsVassar ParkCantonCantonGibbsWestbrookDowntown-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%0.958%0.96%1-1.000000x-1.000000x6.994538x6.994538x6.99x0.612%0.61%4.282%4.28%2-1.000000x-1.000000x5.116893x5.116893x5.12x0.839%0.84%4.294%4.29%3-1.000000x-1.000000x5.018946x5.018946x5.02x0.832%0.83%4.175%4.18%4-1.000000x-1.000000x2.978074x2.978074x2.98x0.310%0.31%0.924%0.92%5-1.000000x-1.000000x2.496909x2.496909x2.50x0.717%0.72%1.791%1.79%6-1.000000x-1.000000x1.779709x1.779709x1.78x2.060%2.06%3.667%3.67%7-1.000000x-1.000000x1.669500x1.669500x1.67x2.031%2.03%3.391%3.39%-1.000000x-1.000000x1.666317x1.666317x1.67x1.492%1.49%2.486%2.49%-1.000000x-1.000000x1.636723x1.636723x1.64x1.473%1.47%2.411%2.41%-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-1.000000x1.369634x1.369634x1.37x0.998%1.00%1.368%1.37%8-1.000000x-1.000000x1.252134x1.252134x1.25x0.362%0.36%0.453%0.45%9-1.089970x-1.089970x1.09x1.000000x1.000000x3.407%3.41%3.126%3.13%10-1.103703x-1.103703x1.10x1.000000x1.000000x1.302%1.30%1.180%1.18%-1.103703x-1.103703x1.10x1.000000x1.000000x1.302%1.30%1.180%1.18%-3.724580x-3.724580x3.72x1.000000x1.000000x0.682%0.68%0.183%0.18%11-10.000000x-10.000000x> 10.0x1.000000x1.000000x1.064%1.06%0.000%0%12-10.000000x-10.000000x> 10.0x1.000000x1.000000x1.786%1.79%0.000%0%13
F percentage of females in category
M percentage of males in category
# rank of neighborhood out of 13 by male-to-female sex ratio

Educational Attainment by County Subdivision in the Canton Area

There are 35 county subdivisions in the Canton Area. This section compares Canton to all of the county subdivisions in the Canton Area and to those entities that contain or substantially overlap with Canton.

No H.S. Diploma by County Subdivision#47

Percent of population 25 years of age and older without a high school diploma (or equivalent).
Scope: population of Canton, selected other county subdivisions in the Canton Area, and entities that contain Canton
0%5%10%15%20%Count#Augusta TownshipAugustaEast TownshipLoudon TownshipLoudonUnion TownshipUnionWashington TownshipWashingtonCantonCantonAllianceLee TownshipSugar Creek TownshipSugar CrkMonroe TownshipMonroeFox TownshipUnited States of AmericaUnited StatesOsnaburg TownshipOsnaburgPerry TownshipPerryBrown TownshipBrownCanton TownshipCantonCenter TownshipCtrLexington TownshipLexingtonBethlehem TownshipBethlehemMassillonEast North CentralOhioTuscarawas TownshipTuscarawasMidwestCanton and Massillon Metro AreaCanton AreaStark CountyStarkPerry TownshipPerryPike TownshipLouisvilleParis TownshipParisSandy TownshipSandyHarrison TownshipHarrisonMarlboro TownshipMarlboroOrange TownshipOrangeNimishillen TownshipNimishillenRose TownshipLawrence TownshipLawrencePlain TownshipPlainLake TownshipWashington TownshipWashingtonJackson TownshipJackson23.234811%23.234811%23.2%283121.568627%21.568627%21.6%121217.398649%17.398649%17.4%103316.407599%16.407599%16.4%95416.270784%16.270784%16.3%137515.631958%15.631958%15.6%7,30215.631958%15.631958%15.6%7,302615.014535%15.014535%15.0%2,066714.627995%14.627995%14.6%116814.597902%14.597902%14.6%668914.016490%14.016490%14.0%2381013.636364%13.636364%13.6%811113.020590%13.020590%13.0%27,818,38027.8M12.677460%12.677460%12.7%5091212.330623%12.330623%12.3%911312.248322%12.248322%12.2%6571411.265632%11.265632%11.3%1,0451511.244240%11.244240%11.2%3661611.213186%11.213186%11.2%4151710.792667%10.792667%10.8%4181810.749201%10.749201%10.7%2,3531910.719464%10.719464%10.7%3,363,7843.36M10.514146%10.514146%10.5%825,155825k10.260405%10.260405%10.3%4612010.244520%10.244520%10.2%4,641,8354.64M9.808753%9.808753%9.8%27,34727.3k9.565083%9.565083%9.6%24,75324.8k9.496584%9.496584%9.5%1,960219.294200%9.294200%9.3%266229.027563%9.027563%9.0%583238.841843%8.841843%8.8%355248.609272%8.609272%8.6%221258.528428%8.528428%8.5%153268.206486%8.206486%8.2%248277.752699%7.752699%7.8%79287.694508%7.694508%7.7%538297.628866%7.628866%7.6%74306.789425%6.789425%6.8%660316.171554%6.171554%6.2%2,311325.389607%5.389607%5.4%1,088334.948454%4.948454%4.9%168343.830735%3.830735%3.8%1,11835
Count number of people in category
# rank of county subdivision out of 35 by percentage of population 25 years of age and older without a high school diploma (or equivalent).

Bachelor's Degrees by County Subdivision#48

Percent of population 25 years of age and older with a bachelor's degree or higher..
Scope: population of Canton, selected other county subdivisions in the Canton Area, and entities that contain Canton
0%10%20%30%40%Count#Jackson TownshipJacksonLake TownshipPlain TownshipPlainUnited States of AmericaUnited StatesMidwestEast North CentralOhioMarlboro TownshipMarlboroLawrence TownshipLawrenceStark CountyStarkCanton and Massillon Metro AreaCanton AreaLouisvilleParis TownshipParisPike TownshipWashington TownshipWashingtonMassillonNimishillen TownshipNimishillenCenter TownshipCtrRose TownshipAllianceTuscarawas TownshipTuscarawasCantonCantonBethlehem TownshipBethlehemPerry TownshipPerryOsnaburg TownshipOsnaburgEast TownshipMonroe TownshipMonroeCanton TownshipCantonLexington TownshipLexingtonBrown TownshipBrownSandy TownshipSandyPerry TownshipPerrySugar Creek TownshipSugar CrkHarrison TownshipHarrisonFox TownshipUnion TownshipUnionWashington TownshipWashingtonAugusta TownshipAugustaLoudon TownshipLoudonOrange TownshipOrangeLee Township41.432243%41.432243%41.4%12,09212.1k135.795314%35.795314%35.8%7,226233.138386%33.138386%33.1%12,40912.4k330.315023%30.315023%30.3%64,767,78764.8M28.952816%28.952816%29.0%13,118,64213.1M28.462853%28.462853%28.5%8,931,6868.93M26.667466%26.667466%26.7%2,092,8752.09M24.751820%24.751820%24.8%748422.940027%22.940027%22.9%2,230522.631528%22.631528%22.6%58,56758.6k21.826960%21.826960%21.8%60,85460.9k21.477238%21.477238%21.5%1,387617.559153%17.559153%17.6%705717.365479%17.365479%17.4%497816.907216%16.907216%16.9%574916.340795%16.340795%16.3%3,5771015.574943%15.574943%15.6%1,0891115.360983%15.360983%15.4%5001215.257732%15.257732%15.3%1481314.890988%14.890988%14.9%2,0491414.689517%14.689517%14.7%6601514.608666%14.608666%14.6%6,82414.608666%14.608666%14.6%6,8241614.097599%14.097599%14.1%5461713.939629%13.939629%13.9%2,8771813.623910%13.623910%13.6%5471913.547237%13.547237%13.5%762013.486455%13.486455%13.5%2292113.357050%13.357050%13.4%1,2392212.861389%12.861389%12.9%4762312.602535%12.602535%12.6%6762411.647838%11.647838%11.6%2992511.382114%11.382114%11.4%842611.276224%11.276224%11.3%516279.364548%9.364548%9.4%168288.754209%8.754209%8.8%52298.290155%8.290155%8.3%48308.194774%8.194774%8.2%69317.224959%7.224959%7.2%88327.094595%7.094595%7.1%42336.378803%6.378803%6.4%65345.296343%5.296343%5.3%4235
Count number of people in category
# rank of county subdivision out of 35 by percentage of population 25 years of age and older with a bachelor's degree or higher..

Very Advanced Degrees by County Subdivision#49

Percent of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).
Scope: population of Canton, selected other county subdivisions in the Canton Area, and entities that contain Canton
0%1%2%3%4%5%Count#Jackson TownshipJacksonCenter TownshipCtrUnited States of AmericaUnited StatesMarlboro TownshipMarlboroPlain TownshipPlainMidwestEast North CentralOhioMonroe TownshipMonroeLake TownshipParis TownshipParisLawrence TownshipLawrenceStark CountyStarkCanton and Massillon Metro AreaCanton AreaHarrison TownshipHarrisonBrown TownshipBrownLouisvilleOsnaburg TownshipOsnaburgBethlehem TownshipBethlehemSandy TownshipSandyCantonCantonSugar Creek TownshipSugar CrkAlliancePerry TownshipPerryWashington TownshipWashingtonMassillonTuscarawas TownshipTuscarawasLexington TownshipLexingtonNimishillen TownshipNimishillenPike TownshipCanton TownshipCantonAugusta TownshipAugustaRose TownshipOrange TownshipOrangeWashington TownshipWashingtonLee TownshipFox TownshipPerry TownshipPerryEast TownshipLoudon TownshipLoudonUnion TownshipUnion5.297242%5.297242%5.3%1,54613.655914%3.655914%3.7%11923.336158%3.336158%3.3%7,127,6737.13M3.176704%3.176704%3.2%9633.036372%3.036372%3.0%1,13742.893416%2.893416%2.9%1,311,0191.31M2.855432%2.855432%2.9%896,039896k2.683241%2.683241%2.7%210,582211k2.296820%2.296820%2.3%3952.214296%2.214296%2.2%44762.166874%2.166874%2.2%8772.016253%2.016253%2.0%19681.963406%1.963406%2.0%5,0811.919283%1.919283%1.9%5,3511.783724%1.783724%1.8%3291.491424%1.491424%1.5%80101.471044%1.471044%1.5%95111.394770%1.394770%1.4%56121.394268%1.394268%1.4%54131.246591%1.246591%1.2%32141.245933%1.245933%1.2%5821.245933%1.245933%1.2%582151.223776%1.223776%1.2%56161.039244%1.039244%1.0%143170.954504%0.954504%1.0%197180.913108%0.913108%0.9%31190.872545%0.872545%0.9%191200.756733%0.756733%0.8%34210.675493%0.675493%0.7%25220.672197%0.672197%0.7%47230.559050%0.559050%0.6%16240.140147%0.140147%0.1%13250.000000%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%0300.000000%0.000000%0.0%0310.000000%0.000000%0.0%0320.000000%0.000000%0.0%0330.000000%0.000000%0.0%0340.000000%0.000000%0.0%035
Count number of people in category
# rank of county subdivision out of 35 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#50

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 Canton, selected other county subdivisions in the Canton Area, and entities that contain Canton
Female
Male
2x1x0x1x2xFM#MonroePerryUnionLoudonWashingtonEast TownshipPike TownshipSugar CrkLake TownshipTuscarawasOsnaburgNimishillenLouisvilleMidwestBrownEast North CentralCantonCantonUnited StatesOhioLexingtonBethlehemCanton AreaHarrisonStarkPlainJacksonOrangeAugustaParisPerryFox TownshipCantonCtrSandyMassillonAllianceLee TownshipMarlboroLawrenceRose TownshipWashington-1.000000x-1.000000x2.913234x2.913234x2.91x7.209%7.21%21.002%21.0%1-1.000000x-1.000000x2.801724x2.801724x2.80x6.667%6.67%18.678%18.7%2-1.000000x-1.000000x2.200647x2.200647x2.20x10.000%10.0%22.006%22.0%3-1.000000x-1.000000x2.014857x2.014857x2.01x11.273%11.3%22.713%22.7%4-1.000000x-1.000000x1.877700x1.877700x1.88x11.663%11.7%21.900%21.9%5-1.000000x-1.000000x1.615885x1.615885x1.62x16.609%16.6%26.838%26.8%6-1.000000x-1.000000x1.613243x1.613243x1.61x7.103%7.10%11.458%11.5%7-1.000000x-1.000000x1.559800x1.559800x1.56x11.437%11.4%17.840%17.8%8-1.000000x-1.000000x1.485105x1.485105x1.49x4.365%4.37%6.483%6.48%9-1.000000x-1.000000x1.369796x1.369796x1.37x8.686%8.69%11.898%11.9%10-1.000000x-1.000000x1.223222x1.223222x1.22x11.378%11.4%13.917%13.9%11-1.000000x-1.000000x1.214211x1.214211x1.21x6.973%6.97%8.467%8.47%12-1.000000x-1.000000x1.128138x1.128138x1.13x8.519%8.52%9.611%9.61%13-1.000000x-1.000000x1.127915x1.127915x1.13x9.647%9.65%10.881%10.9%-1.000000x-1.000000x1.127575x1.127575x1.13x11.519%11.5%12.988%13.0%14-1.000000x-1.000000x1.125371x1.125371x1.13x10.108%10.1%11.375%11.4%-1.000000x-1.000000x1.109752x1.109752x1.11x14.885%14.9%16.518%16.5%-1.000000x-1.000000x1.109752x1.109752x1.11x14.885%14.9%16.518%16.5%15-1.000000x-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-1.000000x1.097597x1.097597x1.10x10.687%10.7%11.730%11.7%16-1.000000x-1.000000x1.056004x1.056004x1.06x10.516%10.5%11.105%11.1%17-1.000000x-1.000000x1.051981x1.051981x1.05x9.572%9.57%10.070%10.1%-1.000000x-1.000000x1.045752x1.045752x1.05x8.333%8.33%8.715%8.71%18-1.000000x-1.000000x1.031161x1.031161x1.03x9.426%9.43%9.720%9.72%-1.000000x-1.000000x1.027725x1.027725x1.03x6.093%6.09%6.262%6.26%19-1.000000x-1.000000x1.006889x1.006889x1.01x3.818%3.82%3.844%3.84%20-1.000199x-1.000199x1.00x1.000000x1.000000x7.753%7.75%7.752%7.75%21-1.011875x-1.011875x1.01x1.000000x1.000000x23.364%23.4%23.090%23.1%22-1.032873x-1.032873x1.03x1.000000x1.000000x8.986%8.99%8.700%8.70%23-1.033196x-1.033196x1.03x1.000000x1.000000x9.646%9.65%9.336%9.34%24-1.053291x-1.053291x1.05x1.000000x1.000000x14.022%14.0%13.313%13.3%25-1.061381x-1.061381x1.06x1.000000x1.000000x11.585%11.6%10.915%10.9%26-1.076484x-1.076484x1.08x1.000000x1.000000x11.632%11.6%10.806%10.8%27-1.091207x-1.091207x1.09x1.000000x1.000000x9.014%9.01%8.261%8.26%28-1.128210x-1.128210x1.13x1.000000x1.000000x11.360%11.4%10.069%10.1%29-1.134516x-1.134516x1.13x1.000000x1.000000x15.871%15.9%13.989%14.0%30-1.232908x-1.232908x1.23x1.000000x1.000000x16.067%16.1%13.032%13.0%31-1.278610x-1.278610x1.28x1.000000x1.000000x9.211%9.21%7.204%7.20%32-1.492219x-1.492219x1.49x1.000000x1.000000x8.081%8.08%5.415%5.42%33-1.573219x-1.573219x1.57x1.000000x1.000000x9.402%9.40%5.976%5.98%34-2.513029x-2.513029x2.51x1.000000x1.000000x7.043%7.04%2.803%2.80%35
F percentage of females in category
M percentage of males in category
# rank of county subdivision out of 35 by male-to-female sex ratio

Over-Education Sex Ratio by County Subdivision#51

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 Canton, selected other county subdivisions in the Canton Area, and entities that contain Canton
Female
Male
0x5x10xFM#CantonPike TownshipWashingtonSugar CrkHarrisonAllianceParisJacksonPlainLawrenceNimishillenOhioStarkCanton AreaEast North CentralMidwestUnited StatesOsnaburgLake TownshipMonroeCtrLouisvilleTuscarawasMassillonPerryLexingtonBrownCantonCantonBethlehemMarlboroSandy-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%0.294%0.29%1-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%1.111%1.11%2-1.000000x-1.000000x3.512395x3.512395x3.51x0.407%0.41%1.431%1.43%3-1.000000x-1.000000x3.077025x3.077025x3.08x0.604%0.60%1.859%1.86%4-1.000000x-1.000000x2.862745x2.862745x2.86x0.913%0.91%2.614%2.61%5-1.000000x-1.000000x2.784607x2.784607x2.78x0.573%0.57%1.597%1.60%6-1.000000x-1.000000x2.441997x2.441997x2.44x1.255%1.26%3.065%3.06%7-1.000000x-1.000000x2.183841x2.183841x2.18x3.386%3.39%7.394%7.39%8-1.000000x-1.000000x2.024516x2.024516x2.02x2.059%2.06%4.169%4.17%9-1.000000x-1.000000x1.873847x1.873847x1.87x1.417%1.42%2.654%2.65%10-1.000000x-1.000000x1.723669x1.723669x1.72x0.498%0.50%0.858%0.86%11-1.000000x-1.000000x1.669500x1.669500x1.67x2.031%2.03%3.391%3.39%-1.000000x-1.000000x1.666317x1.666317x1.67x1.492%1.49%2.486%2.49%-1.000000x-1.000000x1.636723x1.636723x1.64x1.473%1.47%2.411%2.41%-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-1.000000x1.474010x1.474010x1.47x1.122%1.12%1.655%1.65%12-1.000000x-1.000000x1.342453x1.342453x1.34x1.900%1.90%2.550%2.55%13-1.000000x-1.000000x1.197295x1.197295x1.20x2.093%2.09%2.506%2.51%14-1.000000x-1.000000x1.190163x1.190163x1.19x3.356%3.36%3.995%3.99%15-1.000000x-1.000000x1.172074x1.172074x1.17x1.362%1.36%1.596%1.60%16-1.000000x-1.000000x1.170470x1.170470x1.17x0.698%0.70%0.817%0.82%17-1.000000x-1.000000x1.150771x1.150771x1.15x0.814%0.81%0.937%0.94%18-1.000000x-1.000000x1.091782x1.091782x1.09x0.914%0.91%0.998%1.00%19-1.000000x-1.000000x1.064185x1.064185x1.06x0.654%0.65%0.696%0.70%20-1.000000x-1.000000x1.013514x1.013514x1.01x1.481%1.48%1.502%1.50%21-1.103703x-1.103703x1.10x1.000000x1.000000x1.302%1.30%1.180%1.18%-1.103703x-1.103703x1.10x1.000000x1.000000x1.302%1.30%1.180%1.18%22-1.106986x-1.106986x1.11x1.000000x1.000000x1.461%1.46%1.319%1.32%23-1.235825x-1.235825x1.24x1.000000x1.000000x3.512%3.51%2.842%2.84%24-2.557709x-2.557709x2.56x1.000000x1.000000x1.853%1.85%0.725%0.72%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 Ohio

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

No H.S. Diploma by County Subdivision#52

Percent of population 25 years of age and older without a high school diploma (or equivalent).
Scope: population of Canton, selected other county subdivisions in Ohio, and entities that contain Canton
0%5%10%15%20%Count#ClevelandMiddletownLorainYoungstownSpringfieldDaytonMansfieldLimaMarion TownshipMarionCantonCantonHamiltonWarrenToledoCincinnatiAkronElyriaUnited States of AmericaUnited StatesNewarkBath TownshipLancaster City TownshipLancaster CityColumbusColerain TownshipColerainEast North CentralEuclidOhioMidwestParmaCanton and Massillon Metro AreaCanton AreaStark CountyStarkFindlayFairfieldMiami 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%7,30215.631958%15.631958%15.6%7,3021015.293656%15.293656%15.3%6,2341115.055107%15.055107%15.1%4,0981214.332972%14.332972%14.3%26,34326.3k1313.761583%13.761583%13.8%26,28626.3k1413.591726%13.591726%13.6%17,95118.0k1513.343328%13.343328%13.3%4,8061613.020590%13.020590%13.0%27,818,38027.8M12.943290%12.943290%12.9%4,1061712.411362%12.411362%12.4%3,0631812.375999%12.375999%12.4%3,3311911.376979%11.376979%11.4%60,83160.8k2010.847918%10.847918%10.8%4,3142110.719464%10.719464%10.7%3,363,7843.36M10.656581%10.656581%10.7%3,5222210.514146%10.514146%10.5%825,155825k10.244520%10.244520%10.2%4,641,8354.64M9.939137%9.939137%9.9%5,683239.808753%9.808753%9.8%27,34727.3k9.565083%9.565083%9.6%24,75324.8k9.003845%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#53

Percent of population 25 years of age and older with a bachelor's degree or higher..
Scope: population of Canton, selected other county subdivisions in Ohio, and entities that contain Canton
0%20%40%60%Count#DublinDeerfield TownshipDeerfieldAnderson TownshipAndersonWashington TownshipWashingtonBeavercreek TownshipBeavercreekCleveland HeightsCleveland HtsLiberty TownshipLibertyWest Chester TownshipW ChesterSylvania TownshipSylvaniaStrongsvilleMifflin TownshipMifflinViolet TownshipVioletLakewoodMiami TownshipMiamiJackson TownshipJacksonColumbusCincinnatiKetteringPlain TownshipPlainGreen TownshipGrnCuyahoga FallsMentorBoardman TownshipBoardmanUnited States of AmericaUnited StatesUnion TownshipUnionJackson TownshipJacksonMidwestEast North CentralFairfieldBath TownshipFindlayMiami TownshipMiamiOhioHuber HeightsStark CountyStarkCanton and Massillon Metro AreaCanton AreaColerain TownshipColerainEuclidAkronParmaNewarkToledoDaytonMiddletownLancaster City TownshipLancaster CityClevelandElyriaHamiltonSpringfieldCantonCantonMansfieldWarrenYoungstownLorainLimaMarion 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%13,118,64213.1M28.462853%28.462853%28.5%8,931,6868.93M28.219271%28.219271%28.2%8,2882626.954091%26.954091%27.0%6,6522726.775738%26.775738%26.8%7,3812826.713842%26.713842%26.7%9,5512926.667466%26.667466%26.7%2,092,8752.09M22.834168%22.834168%22.8%5,6513022.631528%22.631528%22.6%58,56758.6k21.826960%21.826960%21.8%60,85460.9k21.665661%21.665661%21.7%8,6163120.614221%20.614221%20.6%6,8133220.213821%20.213821%20.2%26,69726.7k3319.988457%19.988457%20.0%11,42911.4k3418.053148%18.053148%18.1%5,7273518.048021%18.048021%18.0%33,17133.2k3617.635555%17.635555%17.6%15,51115.5k3716.631922%16.631922%16.6%5,1063816.462939%16.462939%16.5%4,4313916.073076%16.073076%16.1%40,94640.9k4015.411739%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%6,82414.608666%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#54

Percent of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).
Scope: population of Canton, selected other county subdivisions in Ohio, and entities that contain Canton
0%2%4%6%8%10%Count#Cleveland HeightsCleveland HtsDublinAnderson TownshipAndersonSylvania TownshipSylvaniaWashington TownshipWashingtonBeavercreek TownshipBeavercreekJackson TownshipJacksonLakewoodCincinnatiStrongsvilleDeerfield TownshipDeerfieldWest Chester TownshipW ChesterKetteringLiberty TownshipLibertyMifflin TownshipMifflinColumbusUnited States of AmericaUnited StatesPlain TownshipPlainBoardman TownshipBoardmanViolet TownshipVioletMiami TownshipMiamiMidwestEast North CentralOhioCuyahoga FallsGreen TownshipGrnBath TownshipAkronJackson TownshipJacksonStark CountyStarkClevelandCanton and Massillon Metro AreaCanton AreaMentorColerain TownshipColerainMiami TownshipMiamiFindlayToledoSpringfieldFairfieldEuclidHuber HeightsLimaDaytonCantonCantonHamiltonUnion 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%1,471104.149830%4.149830%4.1%1,027114.100659%4.100659%4.1%1,711123.778338%3.778338%3.8%1,485133.514938%3.514938%3.5%800143.389898%3.389898%3.4%853153.357865%3.357865%3.4%17,95418.0k163.336158%3.336158%3.3%7,127,6737.13M3.036372%3.036372%3.0%1,137172.957809%2.957809%3.0%863182.940052%2.940052%2.9%769192.911988%2.911988%2.9%804202.893416%2.893416%2.9%1,311,0191.31M2.855432%2.855432%2.9%896,039896k2.683241%2.683241%2.7%210,582211k2.481744%2.481744%2.5%887212.476862%2.476862%2.5%1,025222.451477%2.451477%2.5%605232.163955%2.163955%2.2%2,858242.063608%2.063608%2.1%619251.963406%1.963406%2.0%5,0811.927780%1.927780%1.9%4,911261.919283%1.919283%1.9%5,3511.815622%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%5821.245933%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#55

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 Canton, selected other county subdivisions in Ohio, and entities that contain Canton
Female
Male
1x0x1xFM#AndersonMansfieldCleveland HtsBeavercreekUnionToledoFindlayLorainMarionYoungstownColerainGrnFairfieldElyriaMiddletownLancaster CityMidwestEast North CentralSpringfieldWarrenDaytonCantonCantonUnited StatesOhioLimaParmaColumbusCanton AreaClevelandDeerfieldMentorNewarkW ChesterStarkPlainLibertyJacksonHuber HeightsHamiltonJacksonCincinnatiAkronMifflinSylvaniaMiamiEuclidMiamiCuyahoga FallsStrongsvilleLakewoodBath TownshipDublinKetteringWashingtonBoardmanViolet-1.000000x-1.000000x1.766803x1.766803x1.77x2.468%2.47%4.360%4.36%1-1.000000x-1.000000x1.592708x1.592708x1.59x12.530%12.5%19.956%20.0%2-1.000000x-1.000000x1.485471x1.485471x1.49x5.146%5.15%7.645%7.64%3-1.000000x-1.000000x1.332397x1.332397x1.33x2.666%2.67%3.552%3.55%4-1.000000x-1.000000x1.242595x1.242595x1.24x7.704%7.70%9.573%9.57%5-1.000000x-1.000000x1.227011x1.227011x1.23x12.945%12.9%15.884%15.9%6-1.000000x-1.000000x1.222843x1.222843x1.22x8.133%8.13%9.946%9.95%7-1.000000x-1.000000x1.207850x1.207850x1.21x16.045%16.0%19.380%19.4%8-1.000000x-1.000000x1.204406x1.204406x1.20x14.131%14.1%17.020%17.0%9-1.000000x-1.000000x1.194114x1.194114x1.19x15.554%15.6%18.574%18.6%10-1.000000x-1.000000x1.175447x1.175447x1.18x10.032%10.0%11.792%11.8%11-1.000000x-1.000000x1.173903x1.173903x1.17x5.370%5.37%6.304%6.30%12-1.000000x-1.000000x1.173628x1.173628x1.17x8.033%8.03%9.428%9.43%13-1.000000x-1.000000x1.166450x1.166450x1.17x12.379%12.4%14.439%14.4%14-1.000000x-1.000000x1.147049x1.147049x1.15x17.010%17.0%19.512%19.5%15-1.000000x-1.000000x1.144160x1.144160x1.14x11.593%11.6%13.265%13.3%16-1.000000x-1.000000x1.127915x1.127915x1.13x9.647%9.65%10.881%10.9%-1.000000x-1.000000x1.125371x1.125371x1.13x10.108%10.1%11.375%11.4%-1.000000x-1.000000x1.124452x1.124452x1.12x16.027%16.0%18.022%18.0%17-1.000000x-1.000000x1.124390x1.124390x1.12x14.230%14.2%16.000%16.0%18-1.000000x-1.000000x1.114342x1.114342x1.11x16.070%16.1%17.907%17.9%19-1.000000x-1.000000x1.109752x1.109752x1.11x14.885%14.9%16.518%16.5%-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-1.000000x1.051981x1.051981x1.05x9.572%9.57%10.070%10.1%-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-1.000000x1.031161x1.031161x1.03x9.426%9.43%9.720%9.72%-1.000000x-1.000000x1.027725x1.027725x1.03x6.093%6.09%6.262%6.26%29-1.000000x-1.000000x1.026192x1.026192x1.03x5.072%5.07%5.205%5.20%30-1.000000x-1.000000x1.025236x1.025236x1.03x6.405%6.41%6.567%6.57%31-1.000000x-1.000000x1.021443x1.021443x1.02x7.189%7.19%7.344%7.34%32-1.000000x-1.000000x1.015682x1.015682x1.02x15.182%15.2%15.420%15.4%33-1.000000x-1.000000x1.006889x1.006889x1.01x3.818%3.82%3.844%3.84%34-1.000000x-1.000000x1.001229x1.001229x1.00x13.754%13.8%13.771%13.8%35-1.001506x-1.001506x1.00x1.000000x1.000000x13.601%13.6%13.581%13.6%36-1.053306x-1.053306x1.05x1.000000x1.000000x5.733%5.73%5.442%5.44%37-1.068860x-1.068860x1.07x1.000000x1.000000x4.454%4.45%4.167%4.17%38-1.075183x-1.075183x1.08x1.000000x1.000000x5.828%5.83%5.420%5.42%39-1.084060x-1.084060x1.08x1.000000x1.000000x11.029%11.0%10.174%10.2%40-1.123601x-1.123601x1.12x1.000000x1.000000x9.091%9.09%8.091%8.09%41-1.132510x-1.132510x1.13x1.000000x1.000000x6.567%6.57%5.799%5.80%42-1.209810x-1.209810x1.21x1.000000x1.000000x4.433%4.43%3.664%3.66%43-1.275391x-1.275391x1.28x1.000000x1.000000x6.820%6.82%5.347%5.35%44-1.295653x-1.295653x1.30x1.000000x1.000000x13.964%14.0%10.778%10.8%45-1.385029x-1.385029x1.39x1.000000x1.000000x2.028%2.03%1.464%1.46%46-1.505212x-1.505212x1.51x1.000000x1.000000x7.040%7.04%4.677%4.68%47-1.641786x-1.641786x1.64x1.000000x1.000000x4.457%4.46%2.715%2.71%48-1.660386x-1.660386x1.66x1.000000x1.000000x7.066%7.07%4.256%4.26%49-1.798212x-1.798212x1.80x1.000000x1.000000x5.036%5.04%2.800%2.80%50
F percentage of females in category
M percentage of males in category
# rank of county subdivision out of 50 by male-to-female sex ratio

Over-Education Sex Ratio by County Subdivision#56

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 Canton, selected other county subdivisions in Ohio, and entities that contain Canton
Female
Male
1x0x1x2x3xFM#ElyriaSpringfieldWashingtonYoungstownBoardmanLorainMiddletownLancaster CityFindlayAndersonJacksonKetteringMifflinPlainBeavercreekDeerfieldDaytonNewarkEuclidMiamiAkronDublinSylvaniaStrongsvilleBath TownshipOhioStarkFairfieldMansfieldW ChesterCanton AreaHuber HeightsLakewoodEast North CentralMidwestWarrenUnited StatesLibertyParmaCleveland HtsColumbusUnionMentorGrnJacksonClevelandCincinnatiMiamiMarionVioletColerainToledoHamiltonCantonCantonCuyahoga FallsLima-1.000000x-1.000000x3.557903x3.557903x3.56x0.433%0.43%1.542%1.54%1-1.000000x-1.000000x3.025650x3.025650x3.03x0.799%0.80%2.417%2.42%2-1.000000x-1.000000x2.977263x2.977263x2.98x3.534%3.53%10.523%10.5%3-1.000000x-1.000000x2.809581x2.809581x2.81x0.426%0.43%1.196%1.20%4-1.000000x-1.000000x2.780060x2.780060x2.78x1.621%1.62%4.507%4.51%5-1.000000x-1.000000x2.695011x2.695011x2.70x0.546%0.55%1.472%1.47%6-1.000000x-1.000000x2.596948x2.596948x2.60x0.564%0.56%1.465%1.46%7-1.000000x-1.000000x2.442537x2.442537x2.44x0.692%0.69%1.690%1.69%8-1.000000x-1.000000x2.437656x2.437656x2.44x0.991%0.99%2.417%2.42%9-1.000000x-1.000000x2.428350x2.428350x2.43x4.486%4.49%10.893%10.9%10-1.000000x-1.000000x2.183841x2.183841x2.18x3.386%3.39%7.394%7.39%11-1.000000x-1.000000x2.155653x2.155653x2.16x2.468%2.47%5.319%5.32%12-1.000000x-1.000000x2.069018x2.069018x2.07x2.252%2.25%4.660%4.66%13-1.000000x-1.000000x2.024516x2.024516x2.02x2.059%2.06%4.169%4.17%14-1.000000x-1.000000x2.007898x2.007898x2.01x4.457%4.46%8.948%8.95%15-1.000000x-1.000000x1.991550x1.991550x1.99x2.826%2.83%5.628%5.63%16-1.000000x-1.000000x1.989047x1.989047x1.99x0.860%0.86%1.711%1.71%17-1.000000x-1.000000x1.967904x1.967904x1.97x0.822%0.82%1.618%1.62%18-1.000000x-1.000000x1.903271x1.903271x1.90x0.997%1.00%1.897%1.90%19-1.000000x-1.000000x1.851159x1.851159x1.85x2.056%2.06%3.806%3.81%20-1.000000x-1.000000x1.846298x1.846298x1.85x1.550%1.55%2.862%2.86%21-1.000000x-1.000000x1.832511x1.832511x1.83x7.149%7.15%13.100%13.1%22-1.000000x-1.000000x1.805502x1.805502x1.81x5.447%5.45%9.835%9.84%23-1.000000x-1.000000x1.769961x1.769961x1.77x3.331%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-1.000000x1.666317x1.666317x1.67x1.492%1.49%2.486%2.49%-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-1.000000x1.636723x1.636723x1.64x1.473%1.47%2.411%2.41%-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%-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 Canton to the 50 most populous county subdivisions in the Midwest and to those entities that contain or substantially overlap with Canton. The least populous of the compared county subdivisions has a population of 112,821.

No H.S. Diploma by County Subdivision#57

Percent of population 25 years of age and older without a high school diploma (or equivalent).
Scope: population of Canton, selected other county subdivisions in the Midwest, and entities that contain Canton
0%10%20%30%Count#Aurora TownshipAuroraCenter TownshipCtrKansas CityClevelandWayne TownshipWayneDetroitMilwaukeeNorth TownshipNDaytonChicagoProviso TownshipProvisoCantonCantonRockford TownshipRockfordSt. LouisWarrenGrand RapidsToledoBlue TownshipCincinnatiAkronSt. PaulSterling HeightsSterling HtsUnited States of AmericaUnited StatesThornton TownshipThorntonWichitaKaw TownshipOmahaBloomingdale TownshipBloomingdaleColumbusMaine TownshipMaineTopekaMinneapolisSpringfield TownshipSpringfieldEast North CentralWorth TownshipWorthOhioMidwestLawrence TownshipLawrenceCanton and Massillon Metro AreaCanton AreaSioux FallsStark CountyStarkCapital 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%16,11016.1k1115.631958%15.631958%15.6%7,30215.631958%15.631958%15.6%7,30215.608074%15.608074%15.6%18,24118.2k1215.466266%15.466266%15.5%33,80433.8k1315.286174%15.286174%15.3%14,05914.1k1414.563179%14.563179%14.6%17,64317.6k1514.332972%14.332972%14.3%26,34326.3k1614.241047%14.241047%14.2%15,25815.3k1713.761583%13.761583%13.8%26,28626.3k1813.591726%13.591726%13.6%17,95118.0k1913.278342%13.278342%13.3%24,61324.6k2013.132171%13.132171%13.1%12,21212.2k2113.020590%13.020590%13.0%27,818,38027.8M12.974232%12.974232%13.0%14,37014.4k2212.568464%12.568464%12.6%31,23131.2k2312.455744%12.455744%12.5%15,16315.2k2412.198899%12.198899%12.2%35,05035.1k2512.171847%12.171847%12.2%9,3752611.376979%11.376979%11.4%60,83160.8k2711.132206%11.132206%11.1%10,96511.0k2811.032803%11.032803%11.0%9,3772910.958428%10.958428%11.0%29,34729.3k3010.767091%10.767091%10.8%11,14911.1k3110.719464%10.719464%10.7%3,363,7843.36M10.678962%10.678962%10.7%11,17511.2k3210.514146%10.514146%10.5%825,155825k10.244520%10.244520%10.2%4,641,8354.64M10.179618%10.179618%10.2%8,161339.808753%9.808753%9.8%27,34727.3k9.702326%9.702326%9.7%9,123349.565083%9.565083%9.6%24,75324.8k8.623103%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#58

Percent of population 25 years of age and older with a bachelor's degree or higher..
Scope: population of Canton, selected other county subdivisions in the Midwest, and entities that contain Canton
0%20%40%60%Count#Ann ArborOverland ParkMilton TownshipMiltonLisle TownshipLisleMadisonDowners Grove TownshipDowners GrvWashington TownshipWashingtonPalatine TownshipPalatineYork TownshipMinneapolisOlatheWheeling TownshipWheelingSchaumburg TownshipSchaumburgKaw TownshipSt. PaulMaine TownshipMaineFargoLincolnLawrence TownshipLawrenceChicagoCapital TownshipCapitalColumbusOmahaCincinnatiSt. LouisGrand RapidsBloomingdale TownshipBloomingdaleCedar RapidsUnited States of AmericaUnited StatesSioux FallsMidwestWichitaEast North CentralSterling HeightsSterling HtsTopekaSpringfield TownshipSpringfieldOhioProviso TownshipProvisoWorth TownshipWorthMilwaukeeStark CountyStarkCanton and Massillon Metro AreaCanton AreaRockford TownshipRockfordAkronCenter TownshipCtrNorth TownshipNThornton TownshipThorntonToledoDaytonWarrenWayne TownshipWayneKansas CityClevelandAurora TownshipAuroraBlue TownshipCantonCantonDetroit72.810169%72.810169%72.8%47,43047.4k158.823344%58.823344%58.8%74,57874.6k257.681507%57.681507%57.7%45,19045.2k356.900171%56.900171%56.9%46,35646.4k456.337583%56.337583%56.3%85,63285.6k553.762123%53.762123%53.8%55,71155.7k650.610540%50.610540%50.6%47,62347.6k749.860853%49.860853%49.9%39,77539.8k849.728972%49.728972%49.7%42,93542.9k947.670489%47.670489%47.7%127,663128k1046.512581%46.512581%46.5%38,59838.6k1146.409378%46.409378%46.4%51,46851.5k1241.792515%41.792515%41.8%39,02039.0k1341.581304%41.581304%41.6%50,61950.6k1439.969357%39.969357%40.0%74,08874.1k1539.511462%39.511462%39.5%38,91838.9k1638.241175%38.241175%38.2%26,96527.0k1737.146608%37.146608%37.1%62,25462.3k1836.577273%36.577273%36.6%29,32429.3k1936.546320%36.546320%36.5%669,666670k2036.298510%36.298510%36.3%28,78028.8k2134.685843%34.685843%34.7%185,460185k2234.651487%34.651487%34.7%99,56199.6k2333.783048%33.783048%33.8%64,52964.5k2433.007421%33.007421%33.0%72,14372.1k2532.904381%32.904381%32.9%39,86339.9k2632.623147%32.623147%32.6%25,12725.1k2731.793440%31.793440%31.8%27,10227.1k2830.315023%30.315023%30.3%64,767,78764.8M30.259813%30.259813%30.3%28,45328.5k2928.952816%28.952816%29.0%13,118,64213.1M28.877567%28.877567%28.9%71,75771.8k3028.462853%28.462853%28.5%8,931,6868.93M27.532180%27.532180%27.5%25,60325.6k3127.007248%27.007248%27.0%22,95423.0k3226.964567%26.964567%27.0%27,92127.9k3326.667466%26.667466%26.7%2,092,8752.09M26.237989%26.237989%26.2%27,03327.0k3425.217641%25.217641%25.2%26,38926.4k3523.517740%23.517740%23.5%85,81285.8k3622.631528%22.631528%22.6%58,56758.6k21.826960%21.826960%21.8%60,85460.9k21.592552%21.592552%21.6%25,23525.2k3720.213821%20.213821%20.2%26,69726.7k3820.139240%20.139240%20.1%19,93119.9k3919.650916%19.650916%19.7%20,02920.0k4018.971090%18.971090%19.0%21,01221.0k4118.048021%18.048021%18.0%33,17133.2k4217.635555%17.635555%17.6%15,51115.5k4317.280259%17.280259%17.3%15,89315.9k4416.826535%16.826535%16.8%14,78814.8k4516.167409%16.167409%16.2%15,13915.1k4616.073076%16.073076%16.1%40,94640.9k4715.929601%15.929601%15.9%14,19214.2k4815.821208%15.821208%15.8%16,95117.0k4914.608666%14.608666%14.6%6,82414.608666%14.608666%14.6%6,82413.833543%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#59

Percent of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).
Scope: population of Canton, selected other county subdivisions in the Midwest, and entities that contain Canton
0%5%10%15%Count#Ann ArborMadisonDowners Grove TownshipDowners GrvWashington TownshipWashingtonMinneapolisYork TownshipOverland ParkLisle TownshipLisleSt. PaulKaw TownshipMilton TownshipMiltonSt. LouisCincinnatiLincolnChicagoFargoCapital TownshipCapitalOmahaMaine TownshipMainePalatine TownshipPalatineWheeling TownshipWheelingColumbusUnited States of AmericaUnited StatesTopekaGrand RapidsLawrence TownshipLawrenceSpringfield TownshipSpringfieldCedar RapidsMidwestEast North CentralSioux FallsOlatheOhioCenter TownshipCtrSchaumburg TownshipSchaumburgWichitaProviso TownshipProvisoAkronBloomingdale TownshipBloomingdaleRockford TownshipRockfordMilwaukeeStark CountyStarkWorth TownshipWorthClevelandCanton and Massillon Metro AreaCanton AreaToledoNorth TownshipNSterling HeightsSterling HtsKansas CityDetroitDaytonCantonCantonWayne 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%82,18982.2k154.336789%4.336789%4.3%3,058164.233985%4.233985%4.2%3,357174.059919%4.059919%4.1%11,66511.7k184.030539%4.030539%4.0%3,970193.487439%3.487439%3.5%2,782203.407574%3.407574%3.4%3,779213.357865%3.357865%3.4%17,95418.0k223.336158%3.336158%3.3%7,127,6737.13M3.233245%3.233245%3.2%2,748233.174629%3.174629%3.2%3,846243.083448%3.083448%3.1%2,472252.911721%2.911721%2.9%3,015262.905776%2.905776%2.9%2,477272.893416%2.893416%2.9%1,311,0191.31M2.855432%2.855432%2.9%896,039896k2.841677%2.841677%2.8%2,672282.830666%2.830666%2.8%2,349292.683241%2.683241%2.7%210,582211k2.602914%2.602914%2.6%2,576302.551250%2.551250%2.6%2,382312.519246%2.519246%2.5%6,260322.213918%2.213918%2.2%2,281332.163955%2.163955%2.2%2,858342.113682%2.113682%2.1%1,628352.067272%2.067272%2.1%2,416362.043126%2.043126%2.0%7,455371.963406%1.963406%2.0%5,0811.958049%1.958049%2.0%2,049381.927780%1.927780%1.9%4,911391.919283%1.919283%1.9%5,3511.642065%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%1,106451.245933%1.245933%1.2%5821.245933%1.245933%1.2%5821.183365%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#60

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 Canton, selected other county subdivisions in the Midwest, and entities that contain Canton
Female
Male
1x0x1xFM#Cedar RapidsLincolnDetroitOmahaToledoThorntonKansas CityMadisonLawrenceFargoProvisoRockfordBlue TownshipWayneMidwestTopekaEast North CentralMilwaukeeKaw TownshipDaytonSioux FallsCantonCantonUnited StatesOlatheOhioWorthNOverland ParkAuroraWheelingGrand RapidsSchaumburgChicagoWichitaColumbusCanton AreaClevelandPalatineCapitalWarrenStarkSpringfieldYork TownshipSt. LouisWashingtonBloomingdaleCtrCincinnatiAkronAnn ArborSt. PaulLisleMinneapolisSterling HtsDowners GrvMiltonMaine-1.000000x-1.000000x1.243824x1.243824x1.24x5.354%5.35%6.660%6.66%1-1.000000x-1.000000x1.238529x1.238529x1.24x6.342%6.34%7.854%7.85%2-1.000000x-1.000000x1.237056x1.237056x1.24x18.951%19.0%23.443%23.4%3-1.000000x-1.000000x1.230289x1.230289x1.23x10.968%11.0%13.494%13.5%4-1.000000x-1.000000x1.227011x1.227011x1.23x12.945%12.9%15.884%15.9%5-1.000000x-1.000000x1.203250x1.203250x1.20x11.909%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-1.000000x1.109752x1.109752x1.11x14.885%14.9%16.518%16.5%-1.000000x-1.000000x1.109752x1.109752x1.11x14.885%14.9%16.518%16.5%-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-1.000000x1.051981x1.051981x1.05x9.572%9.57%10.070%10.1%-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-1.000000x1.031161x1.031161x1.03x9.426%9.43%9.720%9.72%-1.000000x-1.000000x1.028857x1.028857x1.03x10.622%10.6%10.928%10.9%35-1.000000x-1.000000x1.027464x1.027464x1.03x5.391%5.39%5.539%5.54%36-1.000000x-1.000000x1.018183x1.018183x1.02x15.334%15.3%15.613%15.6%37-1.000000x-1.000000x1.013146x1.013146x1.01x6.764%6.76%6.853%6.85%38-1.000000x-1.000000x1.007207x1.007207x1.01x12.130%12.1%12.217%12.2%39-1.000000x-1.000000x1.006204x1.006204x1.01x23.095%23.1%23.239%23.2%40-1.000000x-1.000000x1.001229x1.001229x1.00x13.754%13.8%13.771%13.8%41-1.001506x-1.001506x1.00x1.000000x1.000000x13.601%13.6%13.581%13.6%42-1.031649x-1.031649x1.03x1.000000x1.000000x3.205%3.21%3.107%3.11%43-1.060004x-1.060004x1.06x1.000000x1.000000x13.651%13.7%12.879%12.9%44-1.073696x-1.073696x1.07x1.000000x1.000000x3.642%3.64%3.392%3.39%45-1.092939x-1.092939x1.09x1.000000x1.000000x11.450%11.4%10.476%10.5%46-1.131063x-1.131063x1.13x1.000000x1.000000x13.912%13.9%12.300%12.3%47-1.140051x-1.140051x1.14x1.000000x1.000000x4.269%4.27%3.744%3.74%48-1.194783x-1.194783x1.19x1.000000x1.000000x5.710%5.71%4.779%4.78%49-1.208375x-1.208375x1.21x1.000000x1.000000x12.117%12.1%10.027%10.0%50
F percentage of females in category
M percentage of males in category
# rank of county subdivision out of 50 by male-to-female sex ratio

Over-Education Sex Ratio by County Subdivision#61

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 Canton, selected other county subdivisions in the Midwest, and entities that contain Canton
Female
Male
1x0x1x2xFM#RockfordNDaytonSioux FallsCapitalLawrenceDowners GrvAkronLisleWichitaYork TownshipMaineWarrenWheelingBlue TownshipSpringfieldOverland ParkMiltonGrand RapidsOlatheOhioOmahaStarkCanton AreaFargoWashingtonEast North CentralLincolnMidwestBloomingdaleKansas CityAuroraUnited StatesAnn ArborTopekaSterling HtsPalatineSchaumburgColumbusMadisonKaw TownshipMilwaukeeCedar RapidsClevelandCincinnatiSt. PaulSt. LouisChicagoWayneCtrToledoMinneapolisWorthDetroitProvisoCantonCantonThornton-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-1.000000x1.666317x1.666317x1.67x1.492%1.49%2.486%2.49%-1.000000x-1.000000x1.636723x1.636723x1.64x1.473%1.47%2.411%2.41%-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%49-1.103703x-1.103703x1.10x1.000000x1.000000x1.302%1.30%1.180%1.18%-1.103703x-1.103703x1.10x1.000000x1.000000x1.302%1.30%1.180%1.18%-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 Canton to the 50 most populous county subdivisions in the United States and to those entities that contain or substantially overlap with Canton. The least populous of the compared county subdivisions has a population of 547,300.

No H.S. Diploma by County Subdivision#62

Percent of population 25 years of age and older without a high school diploma (or equivalent).
Scope: population of Canton, selected other county subdivisions in the United States, and entities that contain Canton
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 VegasCantonCantonPhoenixBostonSacramentoOrlandoAustinDenverUnited States of AmericaUnited StatesManhattanSan DiegoTampaSan JoseSan FranciscoTucsonAlbuquerqueTownship 1:Charlotte1, CharlotteColumbusTulsaEast North CentralOhioSalt Lake CitySalt Lk CityTown of HempsteadHempsteadMidwestNorthwest HarrisNW HarrisWashingtonCanton and Massillon Metro AreaCanton AreaStark CountyStarkAtlantaSeattleNortheast TarrantNE TarrantPlanoSeattle East28.998944%28.998944%29.0%126,922127k128.837398%28.837398%28.8%261,022261k227.582802%27.582802%27.6%135,754136k324.837401%24.837401%24.8%434,160434k423.987048%23.987048%24.0%141,940142k523.756417%23.756417%23.8%81,30881.3k622.645542%22.645542%22.6%248,699249k722.107626%22.107626%22.1%92,47292.5k821.922900%21.922900%21.9%457,347457k921.818150%21.818150%21.8%149,688150k1021.003600%21.003600%21.0%90,67890.7k1120.783651%20.783651%20.8%207,494207k1220.461493%20.461493%20.5%128,038128k1320.041576%20.041576%20.0%106,726107k1420.017506%20.017506%20.0%351,046351k1519.402518%19.402518%19.4%73,10573.1k1619.344706%19.344706%19.3%315,505316k1719.344408%19.344408%19.3%244,983245k1817.485105%17.485105%17.5%63,80063.8k1917.390838%17.390838%17.4%180,039180k2017.129346%17.129346%17.1%71,39771.4k2116.905373%16.905373%16.9%309,770310k2216.548703%16.548703%16.5%69,83969.8k2315.999398%15.999398%16.0%70,21470.2k2415.906523%15.906523%15.9%198,651199k2515.631958%15.631958%15.6%7,30215.631958%15.631958%15.6%7,30214.952077%14.952077%15.0%308,569309k2614.325556%14.325556%14.3%63,64263.6k2713.900512%13.900512%13.9%103,047103k2813.679368%13.679368%13.7%53,75853.8k2913.668915%13.668915%13.7%78,23878.2k3013.638703%13.638703%13.6%63,86563.9k3113.020590%13.020590%13.0%27,818,38027.8M12.996284%12.996284%13.0%160,845161k3212.985760%12.985760%13.0%206,792207k3312.979618%12.979618%13.0%57,75857.8k3412.789590%12.789590%12.8%153,604154k3512.559735%12.559735%12.6%84,02484.0k3612.262851%12.262851%12.3%70,40970.4k3712.089143%12.089143%12.1%52,21752.2k3811.553484%11.553484%11.6%61,37861.4k3911.376979%11.376979%11.4%60,83160.8k4011.299086%11.299086%11.3%43,65343.7k4110.719464%10.719464%10.7%3,363,7843.36M10.514146%10.514146%10.5%825,155825k10.435356%10.435356%10.4%64,29464.3k4210.384134%10.384134%10.4%54,23054.2k4310.244520%10.244520%10.2%4,641,8354.64M10.135583%10.135583%10.1%47,67947.7k4410.045421%10.045421%10.0%46,51046.5k459.808753%9.808753%9.8%27,34727.3k9.565083%9.565083%9.6%24,75324.8k9.538552%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#63

Percent of population 25 years of age and older with a bachelor's degree or higher..
Scope: population of Canton, selected other county subdivisions in the United States, and entities that contain Canton
0%20%40%60%Count#ManhattanSeattle EastWashingtonSan FranciscoPlanoSan JoseAtlantaSeattleBostonDenverAustinTownship 1:Charlotte1, CharlotteTown of HempsteadHempsteadSan DiegoNortheast TarrantNE TarrantNorthwest HarrisNW HarrisChicagoColumbusLos AngelesBrooklynSan Fernando ValleySan Fernando VlyNortheast DallasNE DallasSalt Lake CitySalt Lk CityAlbuquerqueTampaTucsonOceanside-EscondidoOceanside-Escond…TulsaQueensUnited States of AmericaUnited StatesHoustonBaltimoreLong Beach-LakewoodLong Bch-LakewoodMidwestPhoenixOrlandoEast North CentralAnaheim-Santa Ana-Garden GroveAnaheim-Santa An…SacramentoEast San Gabriel ValleyE San Gabriel VlyOntarioOhioPhiladelphiaMiamiFort WorthSouthwest DallasSW DallasMilwaukeeStark CountyStarkFresnoCanton and Massillon Metro AreaCanton AreaLas VegasEl PasoBronxSan BernardinoSan Antonio CentralSan Antonio CntrlCantonCantonDetroit60.434640%60.434640%60.4%747,953748k157.691220%57.691220%57.7%238,638239k255.360186%55.360186%55.4%256,316256k354.793235%54.793235%54.8%366,564367k454.142756%54.142756%54.1%195,588196k549.985845%49.985845%50.0%600,334600k649.803731%49.803731%49.8%195,136195k749.626221%49.626221%49.6%372,018372k846.377869%46.377869%46.4%206,036206k945.718966%45.718966%45.7%214,085214k1044.843364%44.843364%44.8%256,674257k1141.989192%41.989192%42.0%223,068223k1238.767308%38.767308%38.8%202,458202k1338.701072%38.701072%38.7%616,296616k1438.547398%38.547398%38.5%143,978144k1536.877886%36.877886%36.9%173,478173k1636.546320%36.546320%36.5%669,666670k1734.685843%34.685843%34.7%185,460185k1834.593243%34.593243%34.6%604,693605k1934.081468%34.081468%34.1%597,685598k2033.231104%33.231104%33.2%420,848421k2133.191099%33.191099%33.2%331,364331k2233.118385%33.118385%33.1%204,048204k2332.636312%32.636312%32.6%140,967141k2432.512191%32.512191%32.5%144,676145k2532.087814%32.087814%32.1%184,237184k2631.198303%31.198303%31.2%136,915137k2731.110082%31.110082%31.1%120,191120k2830.595789%30.595789%30.6%499,006499k2930.315023%30.315023%30.3%64,767,78764.8M30.080133%30.080133%30.1%627,520628k3029.719611%29.719611%29.7%125,423125k3129.113198%29.113198%29.1%109,693110k3228.952816%28.952816%29.0%13,118,64213.1M28.760152%28.760152%28.8%593,529594k3328.535877%28.535877%28.5%112,142112k3428.462853%28.462853%28.5%8,931,6868.93M28.412939%28.412939%28.4%312,038312k3528.231204%28.231204%28.2%209,283209k3627.276345%27.276345%27.3%170,682171k3726.758411%26.758411%26.8%111,532112k3826.667466%26.667466%26.7%2,092,8752.09M26.349720%26.349720%26.3%272,786273k3926.011156%26.011156%26.0%178,455178k4024.665414%24.665414%24.7%131,349131k4123.764821%23.764821%23.8%140,625141k4223.517740%23.517740%23.5%85,81285.8k4322.631528%22.631528%22.6%58,56758.6k22.486319%22.486319%22.5%94,05694.1k4421.826960%21.826960%21.8%60,85460.9k21.702666%21.702666%21.7%271,037271k4521.071885%21.071885%21.1%72,12072.1k4619.131504%19.131504%19.1%173,169173k4716.375473%16.375473%16.4%80,59580.6k4814.929012%14.929012%14.9%65,34165.3k4914.608666%14.608666%14.6%6,82414.608666%14.608666%14.6%6,82413.833543%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#64

Percent of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).
Scope: population of Canton, selected other county subdivisions in the United States, and entities that contain Canton
0%5%10%Count#WashingtonManhattanSan FranciscoBostonAtlantaSeattleSan JoseSeattle EastDenverSan DiegoAustinBaltimoreLos AngelesAlbuquerquePlanoChicagoTucsonTown of HempsteadHempsteadTampaMiamiNortheast DallasNE DallasSalt Lake CitySalt Lk CityHoustonPhiladelphiaSan Fernando ValleySan Fernando VlyTownship 1:Charlotte1, CharlotteOceanside-EscondidoOceanside-Escond…BrooklynSacramentoColumbusUnited States of AmericaUnited StatesTulsaPhoenixLong Beach-LakewoodLong Bch-LakewoodMidwestOrlandoEast North CentralFresnoAnaheim-Santa Ana-Garden GroveAnaheim-Santa An…QueensOhioNorthwest HarrisNW HarrisNortheast TarrantNE TarrantEast San Gabriel ValleyE San Gabriel VlyOntarioFort WorthLas VegasMilwaukeeStark CountyStarkCanton and Massillon Metro AreaCanton AreaSan BernardinoSan Antonio CentralSan Antonio CntrlEl PasoSouthwest DallasSW DallasBronxDetroitCantonCanton12.461852%12.461852%12.5%57,69857.7k110.788423%10.788423%10.8%133,520134k27.558053%7.558053%7.6%50,56350.6k37.340604%7.340604%7.3%32,61132.6k46.889819%6.889819%6.9%26,99527.0k56.641855%6.641855%6.6%49,79049.8k66.255912%6.255912%6.3%75,13475.1k76.036065%6.036065%6.0%24,96825.0k85.725842%5.725842%5.7%26,81226.8k95.247128%5.247128%5.2%83,55883.6k105.058711%5.058711%5.1%28,95529.0k114.934352%4.934352%4.9%20,82420.8k124.659072%4.659072%4.7%81,44181.4k134.631274%4.631274%4.6%20,00420.0k144.617088%4.617088%4.6%16,67916.7k154.485379%4.485379%4.5%82,18982.2k164.461087%4.461087%4.5%25,61425.6k174.441262%4.441262%4.4%23,19423.2k184.325266%4.325266%4.3%19,24719.2k194.025531%4.025531%4.0%27,61827.6k203.827408%3.827408%3.8%38,21138.2k213.792624%3.792624%3.8%23,36723.4k223.737871%3.737871%3.7%77,97878.0k233.720350%3.720350%3.7%38,51538.5k243.601468%3.601468%3.6%45,61045.6k253.490252%3.490252%3.5%18,54218.5k263.466073%3.466073%3.5%15,21115.2k273.384967%3.384967%3.4%59,36259.4k283.380196%3.380196%3.4%25,05825.1k293.357865%3.357865%3.4%17,95418.0k303.336158%3.336158%3.3%7,127,6737.13M3.140490%3.140490%3.1%12,13312.1k313.010825%3.010825%3.0%62,13562.1k323.009440%3.009440%3.0%11,33911.3k332.893416%2.893416%2.9%1,311,0191.31M2.893233%2.893233%2.9%11,37011.4k342.855432%2.855432%2.9%896,039896k2.828959%2.828959%2.8%11,83311.8k352.763004%2.763004%2.8%30,34430.3k362.756960%2.756960%2.8%44,96545.0k372.683241%2.683241%2.7%210,582211k2.682967%2.682967%2.7%12,62112.6k382.630994%2.630994%2.6%9,827392.484535%2.484535%2.5%15,54715.5k402.324315%2.324315%2.3%9,688412.173239%2.173239%2.2%11,57311.6k422.155077%2.155077%2.2%26,91426.9k432.043126%2.043126%2.0%7,455441.963406%1.963406%2.0%5,0811.919283%1.919283%1.9%5,3511.807306%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%5,693501.245933%1.245933%1.2%5821.245933%1.245933%1.2%582
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#65

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 Canton, selected other county subdivisions in the United States, and entities that contain Canton
Female
Male
1x0x1xFM#1, CharlotteDetroitBaltimoreTulsaSW DallasMidwestFresnoEast North CentralMilwaukeeCantonCantonUnited StatesOhioNE DallasHoustonHempsteadOrlandoPhiladelphiaOntarioSan BernardinoAustinAtlantaFort WorthPhoenixChicagoAlbuquerqueWashingtonSacramentoColumbusCanton AreaSalt Lk CityDenverNE TarrantTampaOceanside-EscondidoOceanside-Escond…NW HarrisStarkBronxPlanoBrooklynSan Antonio CntrlSan Fernando VlyTucsonAnaheim-Santa Ana-Gdn GrvAnaheim-Santa An…Los AngelesLas VegasBostonE San Gabriel VlyQueensMiamiManhattanSeattleLong Bch-LakewoodSeattle EastSan JoseSan DiegoSan FranciscoEl Paso-1.000000x-1.000000x1.285784x1.285784x1.29x10.185%10.2%13.096%13.1%1-1.000000x-1.000000x1.237056x1.237056x1.24x18.951%19.0%23.443%23.4%2-1.000000x-1.000000x1.179669x1.179669x1.18x15.289%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-1.000000x1.109752x1.109752x1.11x14.885%14.9%16.518%16.5%-1.000000x-1.000000x1.109752x1.109752x1.11x14.885%14.9%16.518%16.5%-1.000000x-1.000000x1.109070x1.109070x1.11x12.369%12.4%13.719%13.7%-1.000000x-1.000000x1.105363x1.105363x1.11x10.008%10.0%11.063%11.1%-1.000000x-1.000000x1.099797x1.099797x1.10x19.814%19.8%21.791%21.8%8-1.000000x-1.000000x1.099188x1.099188x1.10x20.902%20.9%22.975%23.0%9-1.000000x-1.000000x1.092101x1.092101x1.09x9.951%9.95%10.868%10.9%10-1.000000x-1.000000x1.090284x1.090284x1.09x13.111%13.1%14.294%14.3%11-1.000000x-1.000000x1.090163x1.090163x1.09x16.700%16.7%18.206%18.2%12-1.000000x-1.000000x1.088515x1.088515x1.09x16.417%16.4%17.871%17.9%13-1.000000x-1.000000x1.081887x1.081887x1.08x26.536%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-1.000000x1.051981x1.051981x1.05x9.572%9.57%10.070%10.1%-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-1.000000x1.031161x1.031161x1.03x9.426%9.43%9.720%9.72%-1.000000x-1.000000x1.030539x1.030539x1.03x28.448%28.4%29.316%29.3%30-1.000000x-1.000000x1.023151x1.023151x1.02x5.652%5.65%5.783%5.78%31-1.000000x-1.000000x1.018960x1.018960x1.02x19.845%19.8%20.221%20.2%32-1.000000x-1.000000x1.003929x1.003929x1.00x28.944%28.9%29.058%29.1%33-1.000000x-1.000000x1.003840x1.003840x1.00x19.308%19.3%19.383%19.4%34-1.006471x-1.006471x1.01x1.000000x1.000000x12.301%12.3%12.222%12.2%35-1.008020x-1.008020x1.01x1.000000x1.000000x22.734%22.7%22.553%22.6%36-1.013004x-1.013004x1.01x1.000000x1.000000x24.995%25.0%24.674%24.7%37-1.016645x-1.016645x1.02x1.000000x1.000000x16.036%16.0%15.774%15.8%38-1.022333x-1.022333x1.02x1.000000x1.000000x14.476%14.5%14.159%14.2%39-1.026902x-1.026902x1.03x1.000000x1.000000x20.723%20.7%20.180%20.2%40-1.027762x-1.027762x1.03x1.000000x1.000000x19.596%19.6%19.067%19.1%41-1.030897x-1.030897x1.03x1.000000x1.000000x22.136%22.1%21.473%21.5%42-1.044246x-1.044246x1.04x1.000000x1.000000x13.260%13.3%12.698%12.7%43-1.049689x-1.049689x1.05x1.000000x1.000000x9.047%9.05%8.619%8.62%44-1.056864x-1.056864x1.06x1.000000x1.000000x19.921%19.9%18.849%18.8%45-1.057675x-1.057675x1.06x1.000000x1.000000x5.050%5.05%4.774%4.77%46-1.127548x-1.127548x1.13x1.000000x1.000000x13.555%13.6%12.021%12.0%47-1.168454x-1.168454x1.17x1.000000x1.000000x13.975%14.0%11.960%12.0%48-1.228758x-1.228758x1.23x1.000000x1.000000x13.883%13.9%11.298%11.3%49-1.276282x-1.276282x1.28x1.000000x1.000000x26.394%26.4%20.680%20.7%50
F percentage of females in category
M percentage of males in category
# rank of county subdivision out of 50 by male-to-female sex ratio

Over-Education Sex Ratio by County Subdivision#66

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 Canton, selected other county subdivisions in the United States, and entities that contain Canton
Female
Male
1x0x1x2xFM#El PasoSalt Lk CityPlanoTulsaAlbuquerqueNE DallasFort WorthOhioStarkOrlandoPhoenixCanton AreaTucson1, 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 FranciscoDetroitCantonCanton-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-1.000000x1.666317x1.666317x1.67x1.492%1.49%2.486%2.49%-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-1.000000x1.636723x1.636723x1.64x1.473%1.47%2.411%2.41%-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%50-1.103703x-1.103703x1.10x1.000000x1.000000x1.302%1.30%1.180%1.18%-1.103703x-1.103703x1.10x1.000000x1.000000x1.302%1.30%1.180%1.18%
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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Demographics

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Education

More Maps to Explore

State:
Ohio
County:
Stark
Metro Area:
Canton Area
City:
Canton
ZIP Codes:
44641, 44702, 44703, 44704, 44705, 44706, 44707, 44708, 44709, 44710, 44714, 44718, 44720, 44721, 44730
Unified School Districts:
Canton, Canton, Jackson, Louisville, North Canton, Osnaburg, Perry, Plain
Neighborhoods:
Colonial Heights, Crystal Park, Downtown, Edgefield, Edmeyer Park, Fairmount, Gibbs, Harter Heights, Market Heights, Mount Vernon, Ridgewood, Summit, Vassar Park, West Park, Westbrook, Whittier Park
Congressional Districts:
OH-7, OH-16
State Senate District:
OH-29
State House Districts:
OH-48, OH-49
Neighboring Townships:
Canton, Jackson, Nimishillen, Osnaburg, Perry, Plain
Nearby Townships:
Bethlehem, Lake, Marlboro, Paris, Pike, Sandy, Tuscarawas, Washington