Educational Attainment in Columbus, Columbia County, Wisconsin (City)

Educational Attainment#1

Highest level of education among people aged 25 years and older.
Scope: population of Columbia County and Columbus
Columbus
Columbia County
0%10%20%30%40%50%CountHigher Degree1H.S. Diploma2No H.S. Diploma245.599768%35.099388%45.599768%45.6%1,57049.520767%57.674932%49.520767%49.5%1,7054.879466%7.225680%4.879466%4.9%168
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 Columbia County at large.
Scope: population of Columbia County and Columbus
-20%0%+20%%ref.Higher Degree1H.S. Diploma2No H.S. Diploma229.916135%29.916135%+29.9%45.600%45.6%35.099%35.1%-14.138145%-14.138145%-14.1%49.521%49.5%57.675%57.7%-32.470501%-32.470501%-32.5%4.879%4.88%7.226%7.23%
% percentage with given level in Columbus
ref. percentage with given level in Columbia 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 Columbia County and Columbus
Columbus
Columbia County
0%10%20%30%CountDoctorate1Professional1Master's1Bachelor's1Associate's1Some CollegeHigh School2Some H.S.3Less than H.S.3None1.394133%0.614898%1.394133%1.4%481.800755%1.129405%1.800755%1.8%625.169910%4.670716%5.169910%5.2%17825.123439%16.260918%25.123439%25.1%86512.111531%12.423451%12.111531%12.1%41721.231484%22.630760%21.231484%21.2%73128.289283%35.044172%28.289283%28.3%9742.846355%5.017067%2.846355%2.8%982.033111%1.551049%2.033111%2.0%700.000000%0.000000%0.0%0.657565%0
Count number of people in category
1Degree 2Diploma or equivialent 3H.S. = High School

Detailed Relative Educational Attainment#4

Highest level of education among people aged 25 years and older, as percentage more or less than Columbia County at large.
Scope: population of Columbia County and Columbus
-100%0%+100%%ref.Doctorate1Professional1Master's1Bachelor's1Associate's1Some CollegeHigh School2Some H.S.3Less than H.S.3None126.725862%126.725862%+126.7%1.394%1.39%0.615%0.61%59.442863%59.442863%+59.4%1.801%1.80%1.129%1.13%10.687745%10.687745%+10.7%5.170%5.17%4.671%4.67%54.501975%54.501975%+54.5%25.123%25.1%16.261%16.3%-2.510742%-2.510742%-2.5%12.112%12.1%12.423%12.4%-6.183070%-6.183070%-6.2%21.231%21.2%22.631%22.6%-19.275358%-19.275358%-19.3%28.289%28.3%35.044%35.0%-43.266550%-43.266550%-43.3%2.846%2.85%5.017%5.02%31.079711%31.079711%+31.1%2.033%2.03%1.551%1.55%-100.000000%-100.000000%-100.0%0.000%0%0.658%0.66%
% percentage with given level in Columbus
ref. percentage with given level in Columbia 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 Columbia County and Columbus
More Females More Males
Columbia County
Columbus
10%0%10%20%30%FMHigher Degree1H.S. Diploma2No H.S. Diploma2-18.065586%11.175622%11.175622%11%43.252%43.3%48.086%48.1%-12.491019%-12.491019%12%6.953670%52.343%52.3%46.531%46.5%22.216599%31.205943%22.216599%22%4.404%4.40%5.383%5.38%
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 Columbia County and Columbus
More Females More Males
Columbia County
Columbus
0%500%1,000%FMDoctorate1Professional1Master's1Bachelor's1Associate's1Some CollegeHigh School2Some H.S.3Less than H.S.393.150155%59.501745%93.150155%93%0.960%0.96%1.854%1.85%1,000.000000%65.376868%1,000.000000%> 1000%0.000%0%3.708%3.71%-116.793191%-55.227654%-116.793191%117%7.002%7.00%3.230%3.23%-14.491402%6.658322%6.658322%7%24.337%24.3%25.957%26.0%-21.668545%21.754612%21.754612%22%10.954%11.0%13.337%13.3%-7.384403%-4.698237%-7.384403%7%21.965%22.0%20.455%20.5%-16.496666%-16.496666%16%15.091175%30.378%30.4%26.077%26.1%340.408587%54.454273%340.408587%340%1.073%1.07%4.725%4.72%-406.380576%-23.695491%-406.380576%406%3.331%3.33%0.658%0.66%
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 Columbia County and Columbus
Columbus
Columbia County
0%5%10%15%20%25%30%B.X.Total65+45-6435-4425-343.366059%9.928073%3.366059%3.4%2471326.949807%15.995029%26.949807%26.9%3491,29533.537519%22.042481%33.537519%33.5%21965334.910486%19.489489%34.910486%34.9%273782
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 Columbia County at large.
Scope: population of Columbia County and Columbus
50%0%50%%ref.65+45-6435-4425-34-66.095547%-66.095547%66.1%3.366%3.37%9.928%9.93%68.488638%68.488638%68.5%26.950%26.9%15.995%16.0%52.149473%52.149473%52.1%33.538%33.5%22.042%22.0%79.124681%79.124681%79.1%34.910%34.9%19.489%19.5%
% percentage in Columbus with a Bachelor's degree
ref percentage in Columbia 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 Columbia County and Columbus
More Females More Males
Columbia County
Columbus
1,000%500%0%FM65+45-6435-4425-34-1,000.000000%-1,000.000000%> 1000%36.796553%6.030%6.03%0.000%0%-17.530604%25.160123%25.160123%25.2%24.187%24.2%30.272%30.3%-28.294861%20.105690%20.105690%20.1%30.564%30.6%36.709%36.7%-30.805471%-46.844659%-30.805471%30.8%40.426%40.4%30.905%30.9%
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 Columbia County and Columbus
Columbus
Columbia County
$0k$20k$40kCount%Graduate Degree1Bachelor's DegreeSome CollegeH.S. Diploma2Total$52,422.000000$55,660.000000$52,422.000000$52.4k2888.365%8.36%$48,786.000000$48,853.000000$48,786.000000$48.8k86525.123%25.1%$41,354.000000$39,230.000000$41,354.000000$41.4k1,14833.343%33.3%$27,485.000000$33,646.000000$27,485.000000$27.5k97428.289%28.3%$42,411.000000$39,087.000000$42,411.000000$42.4k3,443100.000%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 Columbia County and Columbus
Female Male
Columbia County
Columbus
Shaded bar tips show excess over facing bar.
$50k$0k$50kFMGraduate Degree1Bachelor's DegreeSome CollegeH.S. Diploma2Total$-52,344.000000$-7,734.000000$-52,280.000000$-60,078.000000$60.1k$52,344.000000$52,280.000000$7,819.000000$52,344.000000$52.3k141147$-46,293.000000$-42,255.000000$-46,293.000000$46.3k$46,293.000000$14,749.000000$42,255.000000$17,941.000000$61,042.000000$61.0k431434$-30,110.000000$-31,134.000000$-30,110.000000$30.1k$30,110.000000$19,867.000000$31,134.000000$17,310.000000$49,977.000000$50.0k583565$-22,458.000000$-26,348.000000$-22,458.000000$22.5k$22,458.000000$17,943.000000$26,348.000000$13,968.000000$40,401.000000$40.4k538436$-31,528.000000$-31,460.000000$-31,528.000000$31.5k$31,528.000000$18,774.000000$31,460.000000$14,196.000000$50,302.000000$50.3k1,7711,672
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 Columbia County and Columbus
Columbus
Columbia County
0%20%40%60%80%100%CountBachelor's Degree1Some College2H.S. Diploma3No H.S. Diploma3100.000000%56.756757%100.000000%100.0%280.000000%0.000000%0.0%35.135135%00.000000%0.000000%0.0%8.108108%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 Columbia County and Columbus
Columbus
Columbia County
0%20%40%60%80%100%CountBachelor's Degree1Some College2H.S. Diploma3No H.S. Diploma388.909774%86.709453%88.909774%88.9%94682.153846%81.170900%82.153846%82.2%80185.846154%75.950143%85.846154%85.8%558100.000000%62.486002%100.000000%100.0%41
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 Columbia County and Columbus
Female Male
Columbia County
Columbus
Shaded bar tips show excess over facing bar.
30%20%10%0%10%20%MFWhite1BlackOther1-4.537522%-5.631796%-4.537522%4.5%4.537522%1.028341%5.631796%1.336219%5.565863%5.6%9078-0.000000%-22.222222%-8.010336%0.000000%0.0%0.000000%0.000000%22.222222%0.000000%0.0%00-0.000000%-11.073826%0.000000%0.0%0.000000%0.000000%11.073826%18.187538%0.000000%0.0%00
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 Columbia County and Columbus
Female Male
Columbia County
Columbus
Shaded bar tips show excess over facing bar.
30%20%10%0%10%20%30%MFWhite1BlackOther1-33.275160%-21.977267%-2.745630%-33.275160%33.3%33.275160%2.655576%21.977267%35.930736%35.9%581572-0.000000%-0.000000%0.000000%0.0%0.000000%0.000000%0.000000%0.472813%0.000000%0.0%00-0.000000%-7.386364%-5.365314%0.000000%0.0%0.000000%0.000000%7.386364%0.000000%0.0%00
M number of males in category
F number of females in category
1non-Hispanic 2excluding black and Asian Hispanics

Map of Educational Attainment by Tract in Columbus

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

Percentage of the population 25 years and older with given highest level of educational attainment
36.4%38.1%39.8%41.5%43.1%44.9%

Coarse: High School Diploma Educational Attainment by Tract#17

Percentage of the population 25 years and older with given highest level of educational attainment
49.9%51.2%52.4%53.6%54.8%56.1%

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

Percentage of the population 25 years and older with given highest level of educational attainment
5.21%5.67%6.13%6.59%7.05%7.52%

Detailed: Doctorate Degree Educational Attainment by Tract#19

Percentage of the population 25 years and older with given highest level of educational attainment
0.50%0.67%0.84%1.00%1.17%1.34%

Detailed: Professional Degree Educational Attainment by Tract#20

Percentage of the population 25 years and older with given highest level of educational attainment
0.83%1.03%1.22%1.41%1.60%1.79%

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

Percentage of the population 25 years and older with given highest level of educational attainment
5.12%5.28%5.43%5.58%5.73%5.88%

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

Percentage of the population 25 years and older with given highest level of educational attainment
17.4%18.9%20.3%21.8%23.3%24.8%

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

Percentage of the population 25 years and older with given highest level of educational attainment
11.8204%11.8241%11.8278%11.8315%11.8351%11.8388%

Detailed: Some College Educational Attainment by Tract#24

Percentage of the population 25 years and older with given highest level of educational attainment
20.48%20.58%20.68%20.77%20.87%20.97%

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

Percentage of the population 25 years and older with given highest level of educational attainment
29.0%30.3%31.6%32.9%34.2%35.6%

Detailed: Some High School Educational Attainment by Tract#26

Percentage of the population 25 years and older with given highest level of educational attainment
3.1%3.7%4.2%4.8%5.3%5.9%

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

Percentage of the population 25 years and older with given highest level of educational attainment
1.04%1.26%1.47%1.67%1.88%2.10%

Detailed: None Educational Attainment by Tract#28

Percentage of the population 25 years and older with given highest level of educational attainment
0.00%0.13%0.25%0.38%0.50%0.63%
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Educational Attainment by County Subdivision in the Madison Area

There are 149 county subdivisions in the Madison Area. This section compares Columbus to the 50 most populous county subdivisions in the Madison Area and to those entities that contain or substantially overlap with Columbus. The least populous of the compared county subdivisions has a population of 1,919.

No H.S. Diploma by County Subdivision#29

Percent of population 25 years of age and older without a high school diploma (or equivalent).
Scope: population of Columbus, selected other county subdivisions in the Madison Area, and entities that contain Columbus
0%5%10%15%20%Count#Town of MadisonMadisonUnited States of AmericaUnited StatesWisconsin DellsMarshallTown of Sun PrairieSun PrairieBrodheadEast North CentralMidwestMonroePortageFitchburgWisconsinCottage GroveStoughtonNew GlarusColumbia CountyColumbiaLodiTown of PacificPacificZIP Code 53925ZIP 53925DodgevilleMineral PointTown of LodiTown of BurkeColumbus School DistrictColumbusPardeevilleMadison Metro AreaMadison AreaTown of SpringfieldSpringfieldWindsorCross PlainsPoynetteColumbusColumbusMadisonTown of AlbionAlbionTown of DunkirkDunkirkSun PrairieTown of Pleasant SpringsPleasant SpgsTown of SpringdaleSpringdaleTown of BristolBristolTown of ExeterExeterMononaTown of RutlandRutlandTown of DekorraDekorraDeForestDeerfieldTown of West PointW PtTown of MiddletonMiddletonMount HorebMiddletonTown of Cottage GroveCottage GrvBellevilleMcFarlandVeronaTown of WestportWestportTown of DunnOregonTown of OregonOregonWaunakeeShorewood HillsShorewood Hls20.556309%20.556309%20.6%909113.020590%13.020590%13.0%27,818,38027.8M12.838227%12.838227%12.8%223212.413230%12.413230%12.4%304311.393939%11.393939%11.4%188411.343561%11.343561%11.3%244510.719464%10.719464%10.7%3,363,7843.36M10.244520%10.244520%10.2%4,641,8354.64M9.425071%9.425071%9.4%70069.011461%9.011461%9.0%62978.662728%8.662728%8.7%1,61388.637220%8.637220%8.6%336,096336k8.020883%8.020883%8.0%33897.267179%7.267179%7.3%643107.262946%7.262946%7.3%108117.225680%7.225680%7.2%2,8796.294780%6.294780%6.3%123126.119545%6.119545%6.1%129135.650531%5.650531%5.7%3145.627837%5.627837%5.6%186145.455537%5.455537%5.5%100155.433480%5.433480%5.4%136165.311502%5.311502%5.3%133175.284625%5.284625%5.3%2985.263158%5.263158%5.3%79185.241862%5.241862%5.2%21,97222.0k5.083909%5.083909%5.1%103195.076690%5.076690%5.1%235204.962406%4.962406%5.0%132214.961607%4.961607%5.0%84224.879466%4.879466%4.9%1684.879466%4.879466%4.9%168234.836248%4.836248%4.8%7,351244.741684%4.741684%4.7%67254.350417%4.350417%4.4%73263.955766%3.955766%4.0%812273.873094%3.873094%3.9%94283.871829%3.871829%3.9%58293.553099%3.553099%3.6%90303.418231%3.418231%3.4%51313.407952%3.407952%3.4%204323.379310%3.379310%3.4%49333.335218%3.335218%3.3%59343.207877%3.207877%3.2%202352.925046%2.925046%2.9%48362.822581%2.822581%2.8%42372.821242%2.821242%2.8%119382.778341%2.778341%2.8%137392.731305%2.731305%2.7%351402.503526%2.503526%2.5%71412.431373%2.431373%2.4%31422.149419%2.149419%2.1%124431.932367%1.932367%1.9%152441.882210%1.882210%1.9%62451.875617%1.875617%1.9%76461.639866%1.639866%1.6%103471.308017%1.308017%1.3%31481.194743%1.194743%1.2%100490.813609%0.813609%0.8%1150
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#30

Percent of population 25 years of age and older with a bachelor's degree or higher..
Scope: population of Columbus, selected other county subdivisions in the Madison Area, and entities that contain Columbus
0%20%40%60%80%Count#Shorewood HillsShorewood HlsTown of MiddletonMiddletonVeronaMiddletonMadisonWaunakeeMononaTown of BristolBristolFitchburgTown of WestportWestportMcFarlandTown of OregonOregonTown of SpringdaleSpringdaleWindsorMount HorebOregonMadison Metro AreaMadison AreaCottage GroveSun PrairieTown of SpringfieldSpringfieldTown of Pleasant SpringsPleasant SpgsCross PlainsTown of BurkeTown of DunnTown of RutlandRutlandTown of LodiTown of West PointW PtDeForestStoughtonDeerfieldColumbusColumbusLodiTown of ExeterExeterTown of Cottage GroveCottage GrvUnited States of AmericaUnited StatesColumbus School DistrictColumbusZIP Code 53925ZIP 53925MidwestNew GlarusTown of MadisonMadisonEast North CentralWisconsinMineral PointTown of DunkirkDunkirkBellevilleTown of Sun PrairieSun PrairieTown of DekorraDekorraTown of PacificPacificColumbia CountyColumbiaPoynetteTown of AlbionAlbionMonroeDodgevilleWisconsin DellsPardeevillePortageBrodheadMarshall84.467456%84.467456%84.5%1,142165.670934%65.670934%65.7%2,770259.661836%59.661836%59.7%4,693358.898140%58.898140%58.9%7,569456.337583%56.337583%56.3%85,63285.6k550.561529%50.561529%50.6%4,232648.847310%48.847310%48.8%2,924746.821950%46.821950%46.8%1,186846.358754%46.358754%46.4%8,632946.114147%46.114147%46.1%1,5191045.969839%45.969839%46.0%2,6521145.907173%45.907173%45.9%1,0881244.459279%44.459279%44.5%6661344.286023%44.286023%44.3%2,0501444.128980%44.128980%44.1%2,1761543.942047%43.942047%43.9%2,7601643.867317%43.867317%43.9%183,876184k42.240152%42.240152%42.2%1,7801741.077605%41.077605%41.1%8,4321839.486673%39.486673%39.5%8001938.895756%38.895756%38.9%9442038.233083%38.233083%38.2%1,0172137.300319%37.300319%37.3%9342237.290227%37.290227%37.3%1,5112337.034483%37.034483%37.0%5372435.597283%35.597283%35.6%8912535.483871%35.483871%35.5%5282634.937272%34.937272%34.9%2,2002734.900542%34.900542%34.9%3,0882833.759902%33.759902%33.8%5542933.488237%33.488237%33.5%1,15333.488237%33.488237%33.5%1,1533033.009212%33.009212%33.0%6453132.908847%32.908847%32.9%4913232.263752%32.263752%32.3%9153330.315023%30.315023%30.3%64,767,78764.8M29.792516%29.792516%29.8%1,68028.972467%28.972467%29.0%1,61028.952816%28.952816%29.0%13,118,64213.1M28.917283%28.917283%28.9%4303428.742650%28.742650%28.7%1,2713528.462853%28.462853%28.5%8,931,6868.93M28.373439%28.373439%28.4%1,104,0821.10M28.314239%28.314239%28.3%5193626.877235%26.877235%26.9%4513725.725490%25.725490%25.7%3283825.393939%25.393939%25.4%4193924.477106%24.477106%24.5%4334024.193548%24.193548%24.2%5104122.675936%22.675936%22.7%9,03522.209096%22.209096%22.2%3764221.939137%21.939137%21.9%3104321.489161%21.489161%21.5%1,5964421.422088%21.422088%21.4%7084518.364997%18.364997%18.4%3194616.588941%16.588941%16.6%2494715.587393%15.587393%15.6%1,0884812.691771%12.691771%12.7%2734912.576562%12.576562%12.6%30850
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#31

Percent of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).
Scope: population of Columbus, selected other county subdivisions in the Madison Area, and entities that contain Columbus
0%10%20%30%40%Count#Shorewood HillsShorewood HlsTown of MiddletonMiddletonMiddletonMadisonTown of WestportWestportVeronaFitchburgTown of OregonOregonMadison Metro AreaMadison AreaTown of SpringfieldSpringfieldTown of SpringdaleSpringdaleWaunakeeMononaCottage GroveTown of RutlandRutlandOregonWindsorTown of LodiTown of DunnTown of BristolBristolTown of West PointW PtUnited States of AmericaUnited StatesSun PrairieColumbusColumbusColumbus School DistrictColumbusZIP Code 53925ZIP 53925Town of MadisonMadisonTown of BurkeMidwestMineral PointEast North CentralWisconsinMcFarlandTown of Pleasant SpringsPleasant SpgsTown of Sun PrairieSun PrairieWisconsin DellsBellevilleTown of ExeterExeterMonroeTown of DekorraDekorraTown of DunkirkDunkirkMount HorebDeForestColumbia CountyColumbiaTown of PacificPacificTown of AlbionAlbionStoughtonLodiCross PlainsNew GlarusPardeevilleTown of Cottage GroveCottage GrvDodgevillePortageDeerfieldBrodheadPoynetteMarshall43.713018%43.713018%43.7%591115.576102%15.576102%15.6%657210.022566%10.022566%10.0%1,28839.171173%9.171173%9.2%13,94013.9k47.802064%7.802064%7.8%25757.653191%7.653191%7.7%60267.196563%7.196563%7.2%1,34075.991561%5.991561%6.0%14285.974750%5.974750%6.0%25,04425.0k5.923001%5.923001%5.9%12095.674232%5.674232%5.7%85105.651135%5.651135%5.7%473115.646509%5.646509%5.6%338125.220693%5.220693%5.2%220135.034483%5.034483%5.0%73145.015125%5.015125%5.0%315154.903867%4.903867%4.9%227164.394726%4.394726%4.4%110174.244817%4.244817%4.2%172183.829451%3.829451%3.8%97193.629032%3.629032%3.6%54203.336158%3.336158%3.3%7,127,6737.13M3.288352%3.288352%3.3%675213.194888%3.194888%3.2%1103.194888%3.194888%3.2%110223.103387%3.103387%3.1%1753.041209%3.041209%3.0%1692.985075%2.985075%3.0%132232.915335%2.915335%2.9%73242.893416%2.893416%2.9%1,311,0191.31M2.891435%2.891435%2.9%53252.855432%2.855432%2.9%896,039896k2.703886%2.703886%2.7%105,215105k2.565436%2.565436%2.6%148262.472188%2.472188%2.5%60272.363636%2.363636%2.4%39282.360391%2.360391%2.4%41292.352941%2.352941%2.4%30302.345845%2.345845%2.3%35312.262017%2.262017%2.3%168322.035048%2.035048%2.0%36331.966627%1.966627%2.0%33341.845467%1.845467%1.8%91351.778625%1.778625%1.8%112361.744303%1.744303%1.7%6951.707780%1.707780%1.7%36371.698514%1.698514%1.7%24381.627486%1.627486%1.6%144391.586489%1.586489%1.6%31401.503759%1.503759%1.5%40411.412239%1.412239%1.4%21421.399067%1.399067%1.4%21431.198872%1.198872%1.2%34441.180030%1.180030%1.2%39451.117479%1.117479%1.1%78460.853138%0.853138%0.9%14470.697350%0.697350%0.7%15480.649734%0.649734%0.6%11490.571662%0.571662%0.6%1450
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#32

Percentage more likely men are than women to not have a high school diploma (or equivalent) among people aged 25 years and older.
Scope: population of Columbus, selected other county subdivisions in the Madison Area, and entities that contain Columbus
Female
Male
0x5x10xFM#Town of DunnBristolCottage GrvTown of BurkeSpringdaleExeterDeForestBellevilleW PtRutlandOregonTown of LodiDodgevilleMarshallPortageColumbusSun PrairieZIP 53925DunkirkDeerfieldCottage GroveMonroeAlbionColumbiaWisconsin DellsMount HorebMadison AreaColumbusColumbusWisconsinMiddletonMadisonSpringfieldMidwestMononaEast North CentralUnited StatesWindsorOregonPacificMiddletonFitchburgSun PrairieMadisonShorewood HlsBrodheadStoughtonMineral PointCross PlainsNew GlarusPoynetteVeronaPardeevilleDekorraMcFarlandPleasant SpgsWaunakeeWestportLodi-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%3.628%3.63%1-1.000000x-1.000000x6.273080x6.273080x6.27x0.965%0.96%6.051%6.05%2-1.000000x-1.000000x5.779362x5.779362x5.78x0.754%0.75%4.357%4.36%3-1.000000x-1.000000x5.126702x5.126702x5.13x1.743%1.74%8.937%8.94%4-1.000000x-1.000000x3.762346x3.762346x3.76x1.617%1.62%6.085%6.08%5-1.000000x-1.000000x3.742564x3.742564x3.74x1.404%1.40%5.256%5.26%6-1.000000x-1.000000x3.734169x3.734169x3.73x1.394%1.39%5.205%5.21%7-1.000000x-1.000000x3.203980x3.203980x3.20x1.190%1.19%3.814%3.81%8-1.000000x-1.000000x2.388305x2.388305x2.39x1.651%1.65%3.942%3.94%9-1.000000x-1.000000x2.139053x2.139053x2.14x2.131%2.13%4.558%4.56%10-1.000000x-1.000000x2.128547x2.128547x2.13x0.838%0.84%1.784%1.78%11-1.000000x-1.000000x1.957041x1.957041x1.96x3.656%3.66%7.154%7.15%12-1.000000x-1.000000x1.952903x1.952903x1.95x3.886%3.89%7.588%7.59%13-1.000000x-1.000000x1.738772x1.738772x1.74x9.134%9.13%15.882%15.9%14-1.000000x-1.000000x1.691613x1.691613x1.69x6.604%6.60%11.172%11.2%15-1.000000x-1.000000x1.544268x1.544268x1.54x4.153%4.15%6.414%6.41%-1.000000x-1.000000x1.536810x1.536810x1.54x8.981%8.98%13.801%13.8%16-1.000000x-1.000000x1.532304x1.532304x1.53x4.457%4.46%6.829%6.83%-1.000000x-1.000000x1.517754x1.517754x1.52x3.436%3.44%5.214%5.21%17-1.000000x-1.000000x1.476903x1.476903x1.48x2.354%2.35%3.477%3.48%18-1.000000x-1.000000x1.469266x1.469266x1.47x6.528%6.53%9.591%9.59%19-1.000000x-1.000000x1.446456x1.446456x1.45x7.842%7.84%11.343%11.3%20-1.000000x-1.000000x1.347347x1.347347x1.35x4.012%4.01%5.405%5.41%21-1.000000x-1.000000x1.312059x1.312059x1.31x6.240%6.24%8.187%8.19%-1.000000x-1.000000x1.297273x1.297273x1.30x11.163%11.2%14.481%14.5%22-1.000000x-1.000000x1.259621x1.259621x1.26x2.461%2.46%3.100%3.10%23-1.000000x-1.000000x1.231258x1.231258x1.23x4.707%4.71%5.796%5.80%-1.000000x-1.000000x1.222166x1.222166x1.22x4.404%4.40%5.383%5.38%-1.000000x-1.000000x1.222166x1.222166x1.22x4.404%4.40%5.383%5.38%24-1.000000x-1.000000x1.219291x1.219291x1.22x7.799%7.80%9.509%9.51%-1.000000x-1.000000x1.211415x1.211415x1.21x2.544%2.54%3.082%3.08%25-1.000000x-1.000000x1.189278x1.189278x1.19x4.425%4.43%5.263%5.26%26-1.000000x-1.000000x1.186266x1.186266x1.19x4.634%4.63%5.498%5.50%27-1.000000x-1.000000x1.127915x1.127915x1.13x9.647%9.65%10.881%10.9%-1.000000x-1.000000x1.127054x1.127054x1.13x3.218%3.22%3.627%3.63%28-1.000000x-1.000000x1.125371x1.125371x1.13x10.108%10.1%11.375%11.4%-1.000000x-1.000000x1.109070x1.109070x1.11x12.369%12.4%13.719%13.7%-1.000000x-1.000000x1.081981x1.081981x1.08x4.877%4.88%5.277%5.28%29-1.000000x-1.000000x1.043916x1.043916x1.04x1.608%1.61%1.678%1.68%30-1.000000x-1.000000x1.030500x1.030500x1.03x6.030%6.03%6.214%6.21%31-1.000000x-1.000000x1.022109x1.022109x1.02x2.704%2.70%2.764%2.76%32-1.016031x-1.016031x1.02x1.000000x1.000000x8.734%8.73%8.596%8.60%33-1.022158x-1.022158x1.02x1.000000x1.000000x3.997%4.00%3.910%3.91%34-1.035246x-1.035246x1.04x1.000000x1.000000x20.945%20.9%20.232%20.2%35-1.047091x-1.047091x1.05x1.000000x1.000000x0.831%0.83%0.794%0.79%36-1.170222x-1.170222x1.17x1.000000x1.000000x12.206%12.2%10.431%10.4%37-1.208941x-1.208941x1.21x1.000000x1.000000x7.876%7.88%6.515%6.52%38-1.219979x-1.219979x1.22x1.000000x1.000000x5.948%5.95%4.875%4.88%39-1.288288x-1.288288x1.29x1.000000x1.000000x5.548%5.55%4.306%4.31%40-1.380712x-1.380712x1.38x1.000000x1.000000x8.313%8.31%6.021%6.02%41-1.455067x-1.455067x1.46x1.000000x1.000000x5.849%5.85%4.019%4.02%42-1.531489x-1.531489x1.53x1.000000x1.000000x2.297%2.30%1.500%1.50%43-1.538249x-1.538249x1.54x1.000000x1.000000x6.339%6.34%4.121%4.12%44-1.634942x-1.634942x1.63x1.000000x1.000000x4.197%4.20%2.567%2.57%45-1.748323x-1.748323x1.75x1.000000x1.000000x2.720%2.72%1.556%1.56%46-2.297687x-2.297687x2.30x1.000000x1.000000x5.370%5.37%2.337%2.34%47-2.740398x-2.740398x2.74x1.000000x1.000000x1.694%1.69%0.618%0.62%48-3.660958x-3.660958x3.66x1.000000x1.000000x2.932%2.93%0.801%0.80%49-4.809368x-4.809368x4.81x1.000000x1.000000x9.804%9.80%2.039%2.04%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#33

Percentage more likely men are than women to have a professional or doctorate degree (e.g., MBA, PhD, or MD) among people aged 25 years and older.
Scope: population of Columbus, selected other county subdivisions in the Madison Area, and entities that contain Columbus
Female
Male
10x5x0x5x10xFM#PortageBellevillePleasant SpgsColumbusColumbusSpringdaleW PtZIP 53925ColumbusWaunakeeExeterWindsorStoughtonMineral PointCottage GrvShorewood HlsDeForestRutlandFitchburgSun PrairieMcFarlandColumbiaEast North CentralMidwestWisconsinUnited StatesAlbionCottage GroveMount HorebLodiMonroeMiddletonMiddletonSpringfieldMadison AreaMadisonCross PlainsNew GlarusTown of DunnWestportMononaTown of LodiSun PrairieOregonPoynetteOregonDodgevilleWisconsin DellsTown of BurkeBristolVeronaDunkirkMadisonDekorraPacificMarshallBrodheadDeerfieldPardeeville-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%2.120%2.12%1-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%4.975%4.98%2-1.000000x-1.000000x6.668197x6.668197x6.67x0.651%0.65%4.341%4.34%3-1.000000x-1.000000x5.794505x5.794505x5.79x0.960%0.96%5.562%5.56%-1.000000x-1.000000x5.794505x5.794505x5.79x0.960%0.96%5.562%5.56%4-1.000000x-1.000000x3.653292x3.653292x3.65x2.426%2.43%8.862%8.86%5-1.000000x-1.000000x3.343627x3.343627x3.34x1.651%1.65%5.519%5.52%6-1.000000x-1.000000x2.803328x2.803328x2.80x1.594%1.59%4.469%4.47%-1.000000x-1.000000x2.566873x2.566873x2.57x1.739%1.74%4.465%4.46%-1.000000x-1.000000x2.325820x2.325820x2.33x3.499%3.50%8.138%8.14%7-1.000000x-1.000000x2.282051x2.282051x2.28x1.404%1.40%3.205%3.21%8-1.000000x-1.000000x2.114151x2.114151x2.11x3.151%3.15%6.661%6.66%9-1.000000x-1.000000x2.057239x2.057239x2.06x1.105%1.10%2.273%2.27%10-1.000000x-1.000000x1.946254x1.946254x1.95x2.016%2.02%3.924%3.92%11-1.000000x-1.000000x1.942508x1.942508x1.94x0.822%0.82%1.598%1.60%12-1.000000x-1.000000x1.864212x1.864212x1.86x31.163%31.2%58.095%58.1%13-1.000000x-1.000000x1.835169x1.835169x1.84x1.273%1.27%2.336%2.34%14-1.000000x-1.000000x1.811903x1.811903x1.81x3.551%3.55%6.434%6.43%15-1.000000x-1.000000x1.808864x1.808864x1.81x5.081%5.08%9.190%9.19%16-1.000000x-1.000000x1.806537x1.806537x1.81x2.381%2.38%4.302%4.30%17-1.000000x-1.000000x1.708502x1.708502x1.71x1.904%1.90%3.253%3.25%18-1.000000x-1.000000x1.632754x1.632754x1.63x1.321%1.32%2.157%2.16%-1.000000x-1.000000x1.597848x1.597848x1.60x2.216%2.22%3.541%3.54%-1.000000x-1.000000x1.589934x1.589934x1.59x2.251%2.25%3.579%3.58%-1.000000x-1.000000x1.576114x1.576114x1.58x2.109%2.11%3.323%3.32%-1.000000x-1.000000x1.526215x1.526215x1.53x2.660%2.66%4.060%4.06%-1.000000x-1.000000x1.515766x1.515766x1.52x1.337%1.34%2.027%2.03%19-1.000000x-1.000000x1.490739x1.490739x1.49x4.213%4.21%6.280%6.28%20-1.000000x-1.000000x1.475530x1.475530x1.48x1.493%1.49%2.202%2.20%21-1.000000x-1.000000x1.472820x1.472820x1.47x1.307%1.31%1.925%1.93%22-1.000000x-1.000000x1.466038x1.466038x1.47x1.868%1.87%2.739%2.74%23-1.000000x-1.000000x1.463350x1.463350x1.46x12.573%12.6%18.399%18.4%24-1.000000x-1.000000x1.452651x1.452651x1.45x8.299%8.30%12.055%12.1%25-1.000000x-1.000000x1.429525x1.429525x1.43x4.840%4.84%6.919%6.92%26-1.000000x-1.000000x1.400349x1.400349x1.40x4.993%4.99%6.992%6.99%-1.000000x-1.000000x1.387878x1.387878x1.39x7.705%7.70%10.693%10.7%27-1.000000x-1.000000x1.370370x1.370370x1.37x1.280%1.28%1.754%1.75%28-1.000000x-1.000000x1.301909x1.301909x1.30x1.241%1.24%1.615%1.62%29-1.000000x-1.000000x1.297401x1.297401x1.30x3.679%3.68%4.773%4.77%30-1.000000x-1.000000x1.193961x1.193961x1.19x7.121%7.12%8.503%8.50%31-1.000000x-1.000000x1.163055x1.163055x1.16x5.248%5.25%6.104%6.10%32-1.000000x-1.000000x1.079433x1.079433x1.08x4.224%4.22%4.560%4.56%33-1.000000x-1.000000x1.050083x1.050083x1.05x2.306%2.31%2.421%2.42%34-1.043782x-1.043782x1.04x1.000000x1.000000x6.119%6.12%5.862%5.86%35-1.129817x-1.129817x1.13x1.000000x1.000000x0.688%0.69%0.609%0.61%36-1.205414x-1.205414x1.21x1.000000x1.000000x5.437%5.44%4.510%4.51%37-1.277321x-1.277321x1.28x1.000000x1.000000x1.314%1.31%1.029%1.03%38-1.303036x-1.303036x1.30x1.000000x1.000000x2.674%2.67%2.052%2.05%39-1.333367x-1.333367x1.33x1.000000x1.000000x3.328%3.33%2.496%2.50%40-1.415262x-1.415262x1.42x1.000000x1.000000x4.502%4.50%3.181%3.18%41-1.734884x-1.734884x1.73x1.000000x1.000000x9.494%9.49%5.472%5.47%42-1.853067x-1.853067x1.85x1.000000x1.000000x2.577%2.58%1.390%1.39%43-2.320000x-2.320000x2.32x1.000000x1.000000x4.328%4.33%1.866%1.87%44-3.363309x-3.363309x3.36x1.000000x1.000000x3.237%3.24%0.963%0.96%45-4.777365x-4.777365x4.78x1.000000x1.000000x2.783%2.78%0.583%0.58%46-10.000000x-10.000000x> 10.0x1.000000x1.000000x1.112%1.11%0.000%0%47-10.000000x-10.000000x> 10.0x1.000000x1.000000x1.356%1.36%0.000%0%48-10.000000x-10.000000x> 10.0x1.000000x1.000000x1.735%1.73%0.000%0%49-10.000000x-10.000000x> 10.0x1.000000x1.000000x2.717%2.72%0.000%0%50
F percentage of females in category
M percentage of males in category
# rank of county subdivision out of 50 by male-to-female sex ratio

Educational Attainment by County Subdivision in Wisconsin

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

No H.S. Diploma by County Subdivision#34

Percent of population 25 years of age and older without a high school diploma (or equivalent).
Scope: population of Columbus, selected other county subdivisions in Wisconsin, and entities that contain Columbus
0%5%10%15%Count#BeloitRacineMilwaukeeUnited States of AmericaUnited StatesGreen BaySheboyganKenoshaManitowocCudahyWausauEast North CentralMidwestWest AllisOshkoshBeaver DamSouth MilwaukeeS MilwaukeeMarshfieldFond du LacFitchburgWisconsinJanesvilleMenomonieGreenfieldPleasant PrairieAppletonFranklinColumbia CountyColumbiaWaukeshaTown of Grand ChuteGrand ChuteLa CrosseWisconsin RapidsCaledoniaWest BendSuperiorTown of MenashaMenashaAshwaubenonEau ClaireStevens PointHowardMount PleasantMt PleasantNeenahOak CreekZIP Code 53925ZIP 53925Columbus School DistrictColumbusMadison Metro AreaMadison AreaGermantownOnalaskaColumbusColumbusMadisonMenomonee FallsNew BerlinOconomowocSun PrairieDe PereMuskegoWauwatosaBrookfieldMiddletonMequon18.491431%18.491431%18.5%4,197117.907441%17.907441%17.9%8,710217.485105%17.485105%17.5%63,80063.8k313.020590%13.020590%13.0%27,818,38027.8M12.535944%12.535944%12.5%8,414411.643417%11.643417%11.6%3,806511.549265%11.549265%11.5%7,360611.206563%11.206563%11.2%2,609711.082337%11.082337%11.1%1,455810.776184%10.776184%10.8%2,885910.719464%10.719464%10.7%3,363,7843.36M10.244520%10.244520%10.2%4,641,8354.64M10.028497%10.028497%10.0%4,399109.995428%9.995428%10.0%4,154119.950027%9.950027%10.0%1,115129.190270%9.190270%9.2%1,379138.829004%8.829004%8.8%1,091148.713948%8.713948%8.7%2,547158.662728%8.662728%8.7%1,613168.637220%8.637220%8.6%336,096336k8.522583%8.522583%8.5%3,704178.211921%8.211921%8.2%620188.204982%8.204982%8.2%2,296197.709924%7.709924%7.7%1,111207.618904%7.618904%7.6%3,034217.392323%7.392323%7.4%1,924227.225680%7.225680%7.2%2,8797.158983%7.158983%7.2%3,393237.144208%7.144208%7.1%1,133247.116644%7.116644%7.1%2,075257.048284%7.048284%7.0%889266.746719%6.746719%6.7%1,208276.565400%6.565400%6.6%1,422286.289585%6.289585%6.3%1,142296.244351%6.244351%6.2%829306.168099%6.168099%6.2%739316.128290%6.128290%6.1%2,398326.111996%6.111996%6.1%883336.065319%6.065319%6.1%780346.042598%6.042598%6.0%1,149355.863324%5.863324%5.9%1,015365.765641%5.765641%5.8%1,421375.650531%5.650531%5.7%3145.284625%5.284625%5.3%2985.241862%5.241862%5.2%21,97222.0k5.227570%5.227570%5.2%719384.888290%4.888290%4.9%617394.879466%4.879466%4.9%1684.879466%4.879466%4.9%1684.836248%4.836248%4.8%7,351404.484909%4.484909%4.5%1,165414.236891%4.236891%4.2%1,267423.988090%3.988090%4.0%442433.955766%3.955766%4.0%812443.911088%3.911088%3.9%600453.554446%3.554446%3.6%598463.390471%3.390471%3.4%1,167472.806979%2.806979%2.8%761482.731305%2.731305%2.7%351492.107701%2.107701%2.1%35550
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older without a high school diploma (or equivalent).

Bachelor's Degrees by County Subdivision#35

Percent of population 25 years of age and older with a bachelor's degree or higher..
Scope: population of Columbus, selected other county subdivisions in Wisconsin, and entities that contain Columbus
0%20%40%60%Count#MequonMiddletonWauwatosaBrookfieldMadisonFitchburgOconomowocMadison Metro AreaMadison AreaMenomonee FallsSun PrairieNew BerlinGermantownFranklinStevens PointDe PereWaukeshaOnalaskaMenomonieMuskegoColumbusColumbusPleasant PrairieLa CrosseMount PleasantMt PleasantNeenahEau ClaireAppletonTown of Grand ChuteGrand ChuteOak CreekUnited States of AmericaUnited StatesColumbus School DistrictColumbusZIP Code 53925ZIP 53925MidwestGreenfieldCaledoniaTown of MenashaMenashaHowardEast North CentralWisconsinMarshfieldWest BendAshwaubenonWausauOshkoshGreen BayWest AllisFond du LacMilwaukeeKenoshaColumbia CountyColumbiaSuperiorJanesvilleCudahyManitowocSouth MilwaukeeS MilwaukeeSheboyganBeaver DamRacineBeloitWisconsin Rapids63.254765%63.254765%63.3%10,65410.7k158.898140%58.898140%58.9%7,569258.155142%58.155142%58.2%20,01720.0k358.053926%58.053926%58.1%15,73915.7k456.337583%56.337583%56.3%85,63285.6k546.358754%46.358754%46.4%8,632644.229902%44.229902%44.2%4,902743.867317%43.867317%43.9%183,876184k41.080228%41.080228%41.1%10,67110.7k841.077605%41.077605%41.1%8,432940.780498%40.780498%40.8%12,19512.2k1039.610295%39.610295%39.6%5,4481137.841472%37.841472%37.8%9,8491236.471240%36.471240%36.5%5,2691336.151489%36.151489%36.2%5,5461435.550164%35.550164%35.6%16,84916.8k1535.152908%35.152908%35.2%4,4371635.139073%35.139073%35.1%2,6531733.499762%33.499762%33.5%5,6361833.488237%33.488237%33.5%1,15333.488237%33.488237%33.5%1,15333.074254%33.074254%33.1%4,7661932.942347%32.942347%32.9%9,6052032.747831%32.747831%32.7%6,2272132.464907%32.464907%32.5%5,6202232.432916%32.432916%32.4%12,69112.7k2332.296218%32.296218%32.3%12,86112.9k2432.202535%32.202535%32.2%5,1072531.640023%31.640023%31.6%7,7982630.315023%30.315023%30.3%64,767,78764.8M29.792516%29.792516%29.8%1,68028.972467%28.972467%29.0%1,61028.952816%28.952816%29.0%13,118,64213.1M28.921131%28.921131%28.9%8,0932728.919296%28.919296%28.9%5,1782828.909310%28.909310%28.9%3,8382928.794712%28.794712%28.8%3,7033028.462853%28.462853%28.5%8,931,6868.93M28.373439%28.373439%28.4%1,104,0821.10M28.348305%28.348305%28.3%3,5033127.212706%27.212706%27.2%5,8943226.525332%26.525332%26.5%3,1783325.519199%25.519199%25.5%6,8323424.478452%24.478452%24.5%10,17310.2k3524.139215%24.139215%24.1%16,20216.2k3623.980394%23.980394%24.0%10,51910.5k3723.606692%23.606692%23.6%6,9003823.517740%23.517740%23.5%85,81285.8k3922.927488%22.927488%22.9%14,61114.6k4022.675936%22.675936%22.7%9,03522.415597%22.415597%22.4%4,0704122.035848%22.035848%22.0%9,5774221.471552%21.471552%21.5%2,8194321.017138%21.017138%21.0%4,8934420.519827%20.519827%20.5%3,0794519.530103%19.530103%19.5%6,3844618.623951%18.623951%18.6%2,0874717.525031%17.525031%17.5%8,5244816.605719%16.605719%16.6%3,7694915.880441%15.880441%15.9%2,00350
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older with a bachelor's degree or higher..

Very Advanced Degrees by County Subdivision#36

Percent of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).
Scope: population of Columbus, selected other county subdivisions in Wisconsin, and entities that contain Columbus
0%5%10%Count#MequonMiddletonBrookfieldMadisonWauwatosaFitchburgMadison Metro AreaMadison AreaMarshfieldMenomonieLa CrosseStevens PointOnalaskaOconomowocNew BerlinUnited States of AmericaUnited StatesMenomonee FallsSun PrairieColumbusColumbusNeenahColumbus School DistrictColumbusFranklinDe PereZIP Code 53925ZIP 53925GermantownMidwestEau ClaireEast North CentralAppletonWisconsinMuskegoPleasant PrairieBeaver DamWausauTown of Grand ChuteGrand ChuteCaledoniaMount PleasantMt PleasantTown of MenashaMenashaWaukeshaMilwaukeeGreenfieldOak CreekBeloitGreen BayKenoshaColumbia CountyColumbiaWisconsin RapidsJanesvilleOshkoshSuperiorFond du LacHowardCudahyWest BendWest AllisRacineManitowocSouth MilwaukeeS MilwaukeeSheboyganAshwaubenon11.084724%11.084724%11.1%1,867110.022566%10.022566%10.0%1,28829.217661%9.217661%9.2%2,49939.171173%9.171173%9.2%13,94013.9k48.094131%8.094131%8.1%2,78657.196563%7.196563%7.2%1,34065.974750%5.974750%6.0%25,04425.0k5.867120%5.867120%5.9%72574.993377%4.993377%5.0%37784.777583%4.777583%4.8%1,39394.679172%4.679172%4.7%676104.547615%4.547615%4.5%574114.222683%4.222683%4.2%468123.762039%3.762039%3.8%1,125133.336158%3.336158%3.3%7,127,6737.13M3.295350%3.295350%3.3%856143.288352%3.288352%3.3%675153.194888%3.194888%3.2%1103.194888%3.194888%3.2%1103.188724%3.188724%3.2%552163.103387%3.103387%3.1%1753.100626%3.100626%3.1%807173.083241%3.083241%3.1%473183.041209%3.041209%3.0%1692.995492%2.995492%3.0%412192.893416%2.893416%2.9%1,311,0191.31M2.869921%2.869921%2.9%1,123202.855432%2.855432%2.9%896,039896k2.794937%2.794937%2.8%1,113212.703886%2.703886%2.7%105,215105k2.674750%2.674750%2.7%450222.637058%2.637058%2.6%380232.552204%2.552204%2.6%286242.416704%2.416704%2.4%647252.396116%2.396116%2.4%380262.356884%2.356884%2.4%422272.303445%2.303445%2.3%438282.244652%2.244652%2.2%298292.192214%2.192214%2.2%1,039302.043126%2.043126%2.0%7,455311.868992%1.868992%1.9%523321.809624%1.809624%1.8%446331.784377%1.784377%1.8%405341.777440%1.777440%1.8%1,193351.762204%1.762204%1.8%1,123361.744303%1.744303%1.7%6951.688734%1.688734%1.7%213371.555418%1.555418%1.6%676381.549604%1.549604%1.5%644391.525582%1.525582%1.5%277401.454035%1.454035%1.5%425411.384137%1.384137%1.4%178421.302460%1.302460%1.3%171431.292765%1.292765%1.3%280441.251567%1.251567%1.3%549451.155451%1.155451%1.2%562461.133972%1.133972%1.1%264470.893036%0.893036%0.9%134480.868820%0.868820%0.9%284490.784576%0.784576%0.8%9450
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).

Under-Education Sex Ratio by County Subdivision#37

Percentage more likely men are than women to not have a high school diploma (or equivalent) among people aged 25 years and older.
Scope: population of Columbus, selected other county subdivisions in Wisconsin, and entities that contain Columbus
Female
Male
1x0x1x2xFM#De PereMenashaOshkoshFranklinColumbusCaledoniaZIP 53925ManitowocGreen BayPleasant PrairieColumbiaWauwatosaWaukeshaJanesvilleMt PleasantSuperiorMadison AreaStevens PointColumbusColumbusAppletonWisconsinRacineGrand ChuteGermantownMadisonMuskegoKenoshaMequonMidwestEast North CentralMilwaukeeWest BendOnalaskaUnited StatesEau ClaireWisconsin RapidsMenomonee FallsBeloitBeaver DamLa CrosseHowardOak CreekGreenfieldMiddletonFond du LacMarshfieldNew BerlinSheboyganNeenahFitchburgSun PrairieWest AllisS MilwaukeeCudahyWausauBrookfieldAshwaubenonMenomonieOconomowoc-1.000000x-1.000000x2.147134x2.147134x2.15x2.553%2.55%5.481%5.48%1-1.000000x-1.000000x1.888774x1.888774x1.89x4.337%4.34%8.192%8.19%2-1.000000x-1.000000x1.812682x1.812682x1.81x7.022%7.02%12.729%12.7%3-1.000000x-1.000000x1.578941x1.578941x1.58x5.723%5.72%9.036%9.04%4-1.000000x-1.000000x1.544268x1.544268x1.54x4.153%4.15%6.414%6.41%-1.000000x-1.000000x1.534399x1.534399x1.53x5.333%5.33%8.182%8.18%5-1.000000x-1.000000x1.532304x1.532304x1.53x4.457%4.46%6.829%6.83%-1.000000x-1.000000x1.432549x1.432549x1.43x9.294%9.29%13.313%13.3%6-1.000000x-1.000000x1.408197x1.408197x1.41x10.435%10.4%14.694%14.7%7-1.000000x-1.000000x1.380848x1.380848x1.38x6.493%6.49%8.965%8.97%8-1.000000x-1.000000x1.312059x1.312059x1.31x6.240%6.24%8.187%8.19%-1.000000x-1.000000x1.306431x1.306431x1.31x2.969%2.97%3.879%3.88%9-1.000000x-1.000000x1.304061x1.304061x1.30x6.240%6.24%8.137%8.14%10-1.000000x-1.000000x1.294088x1.294088x1.29x7.468%7.47%9.664%9.66%11-1.000000x-1.000000x1.293422x1.293422x1.29x5.323%5.32%6.885%6.89%12-1.000000x-1.000000x1.278895x1.278895x1.28x5.545%5.54%7.091%7.09%13-1.000000x-1.000000x1.231258x1.231258x1.23x4.707%4.71%5.796%5.80%-1.000000x-1.000000x1.229327x1.229327x1.23x5.499%5.50%6.760%6.76%14-1.000000x-1.000000x1.222166x1.222166x1.22x4.404%4.40%5.383%5.38%-1.000000x-1.000000x1.222166x1.222166x1.22x4.404%4.40%5.383%5.38%-1.000000x-1.000000x1.219351x1.219351x1.22x6.887%6.89%8.397%8.40%15-1.000000x-1.000000x1.219291x1.219291x1.22x7.799%7.80%9.509%9.51%-1.000000x-1.000000x1.214505x1.214505x1.21x16.245%16.2%19.730%19.7%16-1.000000x-1.000000x1.207489x1.207489x1.21x6.484%6.48%7.830%7.83%17-1.000000x-1.000000x1.203474x1.203474x1.20x4.768%4.77%5.738%5.74%18-1.000000x-1.000000x1.189278x1.189278x1.19x4.425%4.43%5.263%5.26%19-1.000000x-1.000000x1.159324x1.159324x1.16x3.296%3.30%3.822%3.82%20-1.000000x-1.000000x1.152187x1.152187x1.15x10.767%10.8%12.406%12.4%21-1.000000x-1.000000x1.145574x1.145574x1.15x1.970%1.97%2.257%2.26%22-1.000000x-1.000000x1.127915x1.127915x1.13x9.647%9.65%10.881%10.9%-1.000000x-1.000000x1.125371x1.125371x1.13x10.108%10.1%11.375%11.4%-1.000000x-1.000000x1.123984x1.123984x1.12x16.526%16.5%18.574%18.6%23-1.000000x-1.000000x1.118245x1.118245x1.12x6.211%6.21%6.945%6.95%24-1.000000x-1.000000x1.113721x1.113721x1.11x4.646%4.65%5.175%5.17%25-1.000000x-1.000000x1.109070x1.109070x1.11x12.369%12.4%13.719%13.7%-1.000000x-1.000000x1.104897x1.104897x1.10x5.834%5.83%6.446%6.45%26-1.000000x-1.000000x1.104741x1.104741x1.10x6.724%6.72%7.428%7.43%27-1.000000x-1.000000x1.077248x1.077248x1.08x4.329%4.33%4.663%4.66%28-1.000000x-1.000000x1.069954x1.069954x1.07x17.920%17.9%19.173%19.2%29-1.000000x-1.000000x1.063348x1.063348x1.06x9.653%9.65%10.265%10.3%30-1.000000x-1.000000x1.059381x1.059381x1.06x6.918%6.92%7.329%7.33%31-1.000000x-1.000000x1.056613x1.056613x1.06x5.903%5.90%6.237%6.24%32-1.000000x-1.000000x1.048827x1.048827x1.05x5.631%5.63%5.906%5.91%33-1.000000x-1.000000x1.046668x1.046668x1.05x8.030%8.03%8.405%8.40%34-1.000000x-1.000000x1.022109x1.022109x1.02x2.704%2.70%2.764%2.76%35-1.000000x-1.000000x1.018058x1.018058x1.02x8.641%8.64%8.797%8.80%36-1.000000x-1.000000x1.015610x1.015610x1.02x8.765%8.76%8.902%8.90%37-1.000000x-1.000000x1.012610x1.012610x1.01x4.211%4.21%4.265%4.26%38-1.000000x-1.000000x1.004509x1.004509x1.00x11.618%11.6%11.670%11.7%39-1.001253x-1.001253x1.00x1.000000x1.000000x5.867%5.87%5.859%5.86%40-1.016031x-1.016031x1.02x1.000000x1.000000x8.734%8.73%8.596%8.60%41-1.022158x-1.022158x1.02x1.000000x1.000000x3.997%4.00%3.910%3.91%42-1.024115x-1.024115x1.02x1.000000x1.000000x10.145%10.1%9.906%9.91%43-1.068390x-1.068390x1.07x1.000000x1.000000x9.477%9.48%8.871%8.87%44-1.082508x-1.082508x1.08x1.000000x1.000000x11.515%11.5%10.638%10.6%45-1.083232x-1.083232x1.08x1.000000x1.000000x11.187%11.2%10.327%10.3%46-1.121159x-1.121159x1.12x1.000000x1.000000x2.957%2.96%2.637%2.64%47-1.237978x-1.237978x1.24x1.000000x1.000000x6.794%6.79%5.488%5.49%48-1.368790x-1.368790x1.37x1.000000x1.000000x9.414%9.41%6.877%6.88%49-1.427909x-1.427909x1.43x1.000000x1.000000x4.664%4.66%3.266%3.27%50
F percentage of females in category
M percentage of males in category
# rank of county subdivision out of 50 by male-to-female sex ratio

Over-Education Sex Ratio by County Subdivision#38

Percentage more likely men are than women to have a professional or doctorate degree (e.g., MBA, PhD, or MD) among people aged 25 years and older.
Scope: population of Columbus, selected other county subdivisions in Wisconsin, and entities that contain Columbus
Female
Male
0x2x4xFM#ColumbusColumbusNeenahPleasant PrairieZIP 53925CudahyMenomonieOnalaskaColumbusMuskegoHowardMarshfieldMequonJanesvilleSheboyganRacineBeaver DamBrookfieldGreen BayBeloitStevens PointWausauFitchburgSun PrairieEau ClaireOshkoshAppletonFond du LacNew BerlinWest AllisWauwatosaColumbiaWest BendEast North CentralMidwestWisconsinMt PleasantCaledoniaUnited StatesSuperiorManitowocFranklinLa CrosseS MilwaukeeMiddletonMadison AreaMenomonee FallsMadisonMilwaukeeDe PereGrand ChuteKenoshaGermantownWaukeshaOconomowocWisconsin RapidsMenashaGreenfieldOak CreekAshwaubenon-1.000000x-1.000000x5.794505x5.794505x5.79x0.960%0.96%5.562%5.56%-1.000000x-1.000000x5.794505x5.794505x5.79x0.960%0.96%5.562%5.56%-1.000000x-1.000000x3.129204x3.129204x3.13x1.585%1.59%4.960%4.96%1-1.000000x-1.000000x2.927208x2.927208x2.93x1.353%1.35%3.961%3.96%2-1.000000x-1.000000x2.803328x2.803328x2.80x1.594%1.59%4.469%4.47%-1.000000x-1.000000x2.631735x2.631735x2.63x0.722%0.72%1.899%1.90%3-1.000000x-1.000000x2.628013x2.628013x2.63x2.819%2.82%7.408%7.41%4-1.000000x-1.000000x2.571855x2.571855x2.57x2.645%2.64%6.802%6.80%5-1.000000x-1.000000x2.566873x2.566873x2.57x1.739%1.74%4.465%4.46%-1.000000x-1.000000x2.519338x2.519338x2.52x1.531%1.53%3.858%3.86%6-1.000000x-1.000000x2.492011x2.492011x2.49x0.802%0.80%1.999%2.00%7-1.000000x-1.000000x2.351130x2.351130x2.35x3.588%3.59%8.437%8.44%8-1.000000x-1.000000x2.345235x2.345235x2.35x6.743%6.74%15.813%15.8%9-1.000000x-1.000000x2.320788x2.320788x2.32x0.952%0.95%2.209%2.21%10-1.000000x-1.000000x2.236989x2.236989x2.24x0.541%0.54%1.209%1.21%11-1.000000x-1.000000x2.147202x2.147202x2.15x0.747%0.75%1.604%1.60%12-1.000000x-1.000000x2.134058x2.134058x2.13x1.646%1.65%3.514%3.51%13-1.000000x-1.000000x2.050517x2.050517x2.05x6.177%6.18%12.666%12.7%14-1.000000x-1.000000x2.006236x2.006236x2.01x1.188%1.19%2.383%2.38%15-1.000000x-1.000000x2.005610x2.005610x2.01x1.223%1.22%2.453%2.45%16-1.000000x-1.000000x1.994529x1.994529x1.99x3.154%3.15%6.290%6.29%17-1.000000x-1.000000x1.957848x1.957848x1.96x1.658%1.66%3.247%3.25%18-1.000000x-1.000000x1.808864x1.808864x1.81x5.081%5.08%9.190%9.19%19-1.000000x-1.000000x1.806537x1.806537x1.81x2.381%2.38%4.302%4.30%20-1.000000x-1.000000x1.786228x1.786228x1.79x2.083%2.08%3.720%3.72%21-1.000000x-1.000000x1.747870x1.747870x1.75x1.115%1.12%1.949%1.95%22-1.000000x-1.000000x1.733790x1.733790x1.73x2.062%2.06%3.574%3.57%23-1.000000x-1.000000x1.728996x1.728996x1.73x1.083%1.08%1.873%1.87%24-1.000000x-1.000000x1.706236x1.706236x1.71x2.810%2.81%4.794%4.79%25-1.000000x-1.000000x1.693783x1.693783x1.69x0.936%0.94%1.585%1.59%26-1.000000x-1.000000x1.663311x1.663311x1.66x6.193%6.19%10.301%10.3%27-1.000000x-1.000000x1.632754x1.632754x1.63x1.321%1.32%2.157%2.16%-1.000000x-1.000000x1.632200x1.632200x1.63x0.991%0.99%1.617%1.62%28-1.000000x-1.000000x1.597848x1.597848x1.60x2.216%2.22%3.541%3.54%-1.000000x-1.000000x1.589934x1.589934x1.59x2.251%2.25%3.579%3.58%-1.000000x-1.000000x1.576114x1.576114x1.58x2.109%2.11%3.323%3.32%-1.000000x-1.000000x1.557391x1.557391x1.56x1.833%1.83%2.855%2.85%29-1.000000x-1.000000x1.550147x1.550147x1.55x1.851%1.85%2.870%2.87%30-1.000000x-1.000000x1.526215x1.526215x1.53x2.660%2.66%4.060%4.06%-1.000000x-1.000000x1.516809x1.516809x1.52x1.222%1.22%1.853%1.85%31-1.000000x-1.000000x1.494707x1.494707x1.49x0.918%0.92%1.372%1.37%32-1.000000x-1.000000x1.475485x1.475485x1.48x2.501%2.50%3.691%3.69%33-1.000000x-1.000000x1.473120x1.473120x1.47x3.888%3.89%5.727%5.73%34-1.000000x-1.000000x1.458132x1.458132x1.46x0.734%0.73%1.070%1.07%35-1.000000x-1.000000x1.452651x1.452651x1.45x8.299%8.30%12.055%12.1%36-1.000000x-1.000000x1.400349x1.400349x1.40x4.993%4.99%6.992%6.99%-1.000000x-1.000000x1.388151x1.388151x1.39x2.789%2.79%3.872%3.87%37-1.000000x-1.000000x1.387878x1.387878x1.39x7.705%7.70%10.693%10.7%38-1.000000x-1.000000x1.368590x1.368590x1.37x1.742%1.74%2.385%2.38%39-1.000000x-1.000000x1.363936x1.363936x1.36x2.638%2.64%3.598%3.60%40-1.000000x-1.000000x1.256412x1.256412x1.26x2.128%2.13%2.674%2.67%41-1.000000x-1.000000x1.229981x1.229981x1.23x1.588%1.59%1.953%1.95%42-1.000000x-1.000000x1.211592x1.211592x1.21x2.722%2.72%3.299%3.30%43-1.000000x-1.000000x1.195990x1.195990x1.20x2.002%2.00%2.394%2.39%44-1.000000x-1.000000x1.068496x1.068496x1.07x4.087%4.09%4.367%4.37%45-1.000000x-1.000000x1.014900x1.014900x1.01x1.677%1.68%1.702%1.70%46-1.000000x-1.000000x1.008002x1.008002x1.01x2.236%2.24%2.254%2.25%47-1.098352x-1.098352x1.10x1.000000x1.000000x1.951%1.95%1.776%1.78%48-1.142247x-1.142247x1.14x1.000000x1.000000x1.927%1.93%1.687%1.69%49-1.623043x-1.623043x1.62x1.000000x1.000000x0.961%0.96%0.592%0.59%50
F percentage of females in category
M percentage of males in category
# rank of county subdivision out of 50 by male-to-female sex ratio

Educational Attainment by County Subdivision in the Midwest

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

No H.S. Diploma by County Subdivision#39

Percent of population 25 years of age and older without a high school diploma (or equivalent).
Scope: population of Columbus, selected other county subdivisions in the Midwest, and entities that contain Columbus
0%10%20%30%Count#Aurora TownshipAuroraCenter TownshipCtrKansas CityClevelandWayne TownshipWayneDetroitMilwaukeeNorth TownshipNDaytonChicagoProviso TownshipProvisoRockford TownshipRockfordSt. LouisWarrenGrand RapidsToledoBlue TownshipCincinnatiAkronSt. PaulSterling HeightsSterling HtsUnited States of AmericaUnited StatesThornton TownshipThorntonWichitaKaw TownshipOmahaBloomingdale TownshipBloomingdaleColumbusMaine TownshipMaineTopekaMinneapolisSpringfield TownshipSpringfieldEast North CentralWorth TownshipWorthMidwestLawrence TownshipLawrenceSioux FallsWisconsinCapital TownshipCapitalWheeling TownshipWheelingPalatine TownshipPalatineSchaumburg TownshipSchaumburgColumbia CountyColumbiaLincolnWashington TownshipWashingtonOlatheFargoCedar RapidsZIP Code 53925ZIP 53925York TownshipColumbus School DistrictColumbusMilton TownshipMiltonMadison Metro AreaMadison AreaColumbusColumbusMadisonDowners Grove TownshipDowners GrvLisle TownshipLisleOverland ParkAnn Arbor33.464284%33.464284%33.5%29,81429.8k123.165532%23.165532%23.2%22,92622.9k222.659362%22.659362%22.7%21,21821.2k321.582420%21.582420%21.6%54,98155.0k421.037720%21.037720%21.0%18,48918.5k521.003600%21.003600%21.0%90,67890.7k617.485105%17.485105%17.5%63,80063.8k717.062713%17.062713%17.1%17,39117.4k816.928359%16.928359%16.9%14,88914.9k916.905373%16.905373%16.9%309,770310k1015.636222%15.636222%15.6%16,11016.1k1115.608074%15.608074%15.6%18,24118.2k1215.466266%15.466266%15.5%33,80433.8k1315.286174%15.286174%15.3%14,05914.1k1414.563179%14.563179%14.6%17,64317.6k1514.332972%14.332972%14.3%26,34326.3k1614.241047%14.241047%14.2%15,25815.3k1713.761583%13.761583%13.8%26,28626.3k1813.591726%13.591726%13.6%17,95118.0k1913.278342%13.278342%13.3%24,61324.6k2013.132171%13.132171%13.1%12,21212.2k2113.020590%13.020590%13.0%27,818,38027.8M12.974232%12.974232%13.0%14,37014.4k2212.568464%12.568464%12.6%31,23131.2k2312.455744%12.455744%12.5%15,16315.2k2412.198899%12.198899%12.2%35,05035.1k2512.171847%12.171847%12.2%9,3752611.376979%11.376979%11.4%60,83160.8k2711.132206%11.132206%11.1%10,96511.0k2811.032803%11.032803%11.0%9,3772910.958428%10.958428%11.0%29,34729.3k3010.767091%10.767091%10.8%11,14911.1k3110.719464%10.719464%10.7%3,363,7843.36M10.678962%10.678962%10.7%11,17511.2k3210.244520%10.244520%10.2%4,641,8354.64M10.179618%10.179618%10.2%8,161339.702326%9.702326%9.7%9,123348.637220%8.637220%8.6%336,096336k8.623103%8.623103%8.6%6,837358.424707%8.424707%8.4%9,343368.392669%8.392669%8.4%6,695377.739434%7.739434%7.7%7,226387.225680%7.225680%7.2%2,8797.092309%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%5,099435.650531%5.650531%5.7%3145.461095%5.461095%5.5%4,715445.284625%5.284625%5.3%2985.266517%5.266517%5.3%4,126455.241862%5.241862%5.2%21,97222.0k4.879466%4.879466%4.9%1684.879466%4.879466%4.9%1684.836248%4.836248%4.8%7,351464.020265%4.020265%4.0%4,166473.522812%3.522812%3.5%2,870483.377424%3.377424%3.4%4,282493.157717%3.157717%3.2%2,05750
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older without a high school diploma (or equivalent).

Bachelor's Degrees by County Subdivision#40

Percent of population 25 years of age and older with a bachelor's degree or higher..
Scope: population of Columbus, selected other county subdivisions in the Midwest, and entities that contain Columbus
0%20%40%60%Count#Ann ArborOverland ParkMilton TownshipMiltonLisle TownshipLisleMadisonDowners Grove TownshipDowners GrvWashington TownshipWashingtonPalatine TownshipPalatineYork TownshipMinneapolisOlatheWheeling TownshipWheelingMadison Metro AreaMadison AreaSchaumburg TownshipSchaumburgKaw TownshipSt. PaulMaine TownshipMaineFargoLincolnLawrence TownshipLawrenceChicagoCapital TownshipCapitalColumbusOmahaCincinnatiColumbusColumbusSt. LouisGrand RapidsBloomingdale TownshipBloomingdaleCedar RapidsUnited States of AmericaUnited StatesSioux FallsColumbus School DistrictColumbusZIP Code 53925ZIP 53925MidwestWichitaEast North CentralWisconsinSterling HeightsSterling HtsTopekaSpringfield TownshipSpringfieldProviso TownshipProvisoWorth TownshipWorthMilwaukeeColumbia CountyColumbiaRockford TownshipRockfordAkronCenter TownshipCtrNorth TownshipNThornton TownshipThorntonToledoDaytonWarrenWayne TownshipWayneKansas CityClevelandAurora TownshipAuroraBlue TownshipDetroit72.810169%72.810169%72.8%47,43047.4k158.823344%58.823344%58.8%74,57874.6k257.681507%57.681507%57.7%45,19045.2k356.900171%56.900171%56.9%46,35646.4k456.337583%56.337583%56.3%85,63285.6k553.762123%53.762123%53.8%55,71155.7k650.610540%50.610540%50.6%47,62347.6k749.860853%49.860853%49.9%39,77539.8k849.728972%49.728972%49.7%42,93542.9k947.670489%47.670489%47.7%127,663128k1046.512581%46.512581%46.5%38,59838.6k1146.409378%46.409378%46.4%51,46851.5k1243.867317%43.867317%43.9%183,876184k41.792515%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%64,52964.5k2433.488237%33.488237%33.5%1,15333.488237%33.488237%33.5%1,15333.007421%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%28,45328.5k2929.792516%29.792516%29.8%1,68028.972467%28.972467%29.0%1,61028.952816%28.952816%29.0%13,118,64213.1M28.877567%28.877567%28.9%71,75771.8k3028.462853%28.462853%28.5%8,931,6868.93M28.373439%28.373439%28.4%1,104,0821.10M27.532180%27.532180%27.5%25,60325.6k3127.007248%27.007248%27.0%22,95423.0k3226.964567%26.964567%27.0%27,92127.9k3326.237989%26.237989%26.2%27,03327.0k3425.217641%25.217641%25.2%26,38926.4k3523.517740%23.517740%23.5%85,81285.8k3622.675936%22.675936%22.7%9,03521.592552%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%16,95117.0k4913.833543%13.833543%13.8%59,72359.7k50
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older with a bachelor's degree or higher..

Very Advanced Degrees by County Subdivision#41

Percent of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).
Scope: population of Columbus, selected other county subdivisions in the Midwest, and entities that contain Columbus
0%5%10%15%Count#Ann ArborMadisonDowners Grove TownshipDowners GrvWashington TownshipWashingtonMinneapolisYork TownshipMadison Metro AreaMadison AreaOverland ParkLisle TownshipLisleSt. PaulKaw TownshipMilton TownshipMiltonSt. LouisCincinnatiLincolnChicagoFargoCapital TownshipCapitalOmahaMaine TownshipMainePalatine TownshipPalatineWheeling TownshipWheelingColumbusUnited States of AmericaUnited StatesTopekaColumbusColumbusGrand RapidsColumbus School DistrictColumbusLawrence TownshipLawrenceZIP Code 53925ZIP 53925Springfield TownshipSpringfieldCedar RapidsMidwestEast North CentralSioux FallsOlatheWisconsinCenter TownshipCtrSchaumburg TownshipSchaumburgWichitaProviso TownshipProvisoAkronBloomingdale TownshipBloomingdaleRockford TownshipRockfordMilwaukeeWorth TownshipWorthClevelandColumbia CountyColumbiaToledoNorth TownshipNSterling HeightsSterling HtsKansas CityDetroitDaytonWayne TownshipWayneWarrenBlue TownshipAurora TownshipAuroraThornton TownshipThornton17.877867%17.877867%17.9%11,64611.6k19.171173%9.171173%9.2%13,94013.9k27.658384%7.658384%7.7%7,93637.306290%7.306290%7.3%6,87546.241155%6.241155%6.2%16,71416.7k56.197734%6.197734%6.2%5,35165.974750%5.974750%6.0%25,04425.0k5.940071%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%2,748233.194888%3.194888%3.2%1103.194888%3.194888%3.2%1103.174629%3.174629%3.2%3,846243.103387%3.103387%3.1%1753.083448%3.083448%3.1%2,472253.041209%3.041209%3.0%1692.911721%2.911721%2.9%3,015262.905776%2.905776%2.9%2,477272.893416%2.893416%2.9%1,311,0191.31M2.855432%2.855432%2.9%896,039896k2.841677%2.841677%2.8%2,672282.830666%2.830666%2.8%2,349292.703886%2.703886%2.7%105,215105k2.602914%2.602914%2.6%2,576302.551250%2.551250%2.6%2,382312.519246%2.519246%2.5%6,260322.213918%2.213918%2.2%2,281332.163955%2.163955%2.2%2,858342.113682%2.113682%2.1%1,628352.067272%2.067272%2.1%2,416362.043126%2.043126%2.0%7,455371.958049%1.958049%2.0%2,049381.927780%1.927780%1.9%4,911391.744303%1.744303%1.7%6951.642065%1.642065%1.6%3,018401.575684%1.575684%1.6%1,606411.439893%1.439893%1.4%1,339421.388310%1.388310%1.4%1,300431.318660%1.318660%1.3%5,693441.257490%1.257490%1.3%1,106451.183365%1.183365%1.2%1,040461.047058%1.047058%1.0%963470.997751%0.997751%1.0%1,069480.936111%0.936111%0.9%834490.876686%0.876686%0.9%97150
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).

Under-Education Sex Ratio by County Subdivision#42

Percentage more likely men are than women to not have a high school diploma (or equivalent) among people aged 25 years and older.
Scope: population of Columbus, selected other county subdivisions in the Midwest, and entities that contain Columbus
Female
Male
1x0x1xFM#ColumbusZIP 53925ColumbiaCedar RapidsLincolnDetroitMadison AreaOmahaToledoColumbusColumbusWisconsinThorntonKansas CityMadisonLawrenceFargoProvisoRockfordBlue TownshipWayneMidwestTopekaEast North CentralMilwaukeeKaw TownshipDaytonSioux FallsUnited StatesOlatheWorthNOverland ParkAuroraWheelingGrand RapidsSchaumburgChicagoWichitaColumbusClevelandPalatineCapitalWarrenSpringfieldYork TownshipSt. LouisWashingtonBloomingdaleCtrCincinnatiAkronAnn ArborSt. PaulLisleMinneapolisSterling HtsDowners GrvMiltonMaine-1.000000x-1.000000x1.544268x1.544268x1.54x4.153%4.15%6.414%6.41%-1.000000x-1.000000x1.532304x1.532304x1.53x4.457%4.46%6.829%6.83%-1.000000x-1.000000x1.312059x1.312059x1.31x6.240%6.24%8.187%8.19%-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-1.000000x1.231258x1.231258x1.23x4.707%4.71%5.796%5.80%-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-1.000000x1.222166x1.222166x1.22x4.404%4.40%5.383%5.38%-1.000000x-1.000000x1.222166x1.222166x1.22x4.404%4.40%5.383%5.38%-1.000000x-1.000000x1.219291x1.219291x1.22x7.799%7.80%9.509%9.51%-1.000000x-1.000000x1.203250x1.203250x1.20x11.909%11.9%14.330%14.3%6-1.000000x-1.000000x1.189752x1.189752x1.19x20.748%20.7%24.685%24.7%7-1.000000x-1.000000x1.189278x1.189278x1.19x4.425%4.43%5.263%5.26%8-1.000000x-1.000000x1.181964x1.181964x1.18x9.406%9.41%11.117%11.1%9-1.000000x-1.000000x1.176963x1.176963x1.18x5.565%5.56%6.550%6.55%10-1.000000x-1.000000x1.174964x1.174964x1.17x14.460%14.5%16.990%17.0%11-1.000000x-1.000000x1.168755x1.168755x1.17x14.456%14.5%16.896%16.9%12-1.000000x-1.000000x1.161774x1.161774x1.16x13.244%13.2%15.387%15.4%13-1.000000x-1.000000x1.132245x1.132245x1.13x19.779%19.8%22.395%22.4%14-1.000000x-1.000000x1.127915x1.127915x1.13x9.647%9.65%10.881%10.9%-1.000000x-1.000000x1.125507x1.125507x1.13x10.423%10.4%11.732%11.7%15-1.000000x-1.000000x1.125371x1.125371x1.13x10.108%10.1%11.375%11.4%-1.000000x-1.000000x1.123984x1.123984x1.12x16.526%16.5%18.574%18.6%16-1.000000x-1.000000x1.115695x1.115695x1.12x11.779%11.8%13.142%13.1%17-1.000000x-1.000000x1.114342x1.114342x1.11x16.070%16.1%17.907%17.9%18-1.000000x-1.000000x1.110589x1.110589x1.11x9.201%9.20%10.219%10.2%19-1.000000x-1.000000x1.109070x1.109070x1.11x12.369%12.4%13.719%13.7%-1.000000x-1.000000x1.107847x1.107847x1.11x6.105%6.11%6.764%6.76%20-1.000000x-1.000000x1.099747x1.099747x1.10x10.199%10.2%11.216%11.2%21-1.000000x-1.000000x1.096598x1.096598x1.10x16.317%16.3%17.894%17.9%22-1.000000x-1.000000x1.095440x1.095440x1.10x3.232%3.23%3.540%3.54%23-1.000000x-1.000000x1.086583x1.086583x1.09x32.102%32.1%34.882%34.9%24-1.000000x-1.000000x1.079846x1.079846x1.08x8.111%8.11%8.758%8.76%25-1.000000x-1.000000x1.078480x1.078480x1.08x14.031%14.0%15.132%15.1%26-1.000000x-1.000000x1.077209x1.077209x1.08x7.467%7.47%8.043%8.04%27-1.000000x-1.000000x1.068021x1.068021x1.07x16.372%16.4%17.486%17.5%28-1.000000x-1.000000x1.059528x1.059528x1.06x12.215%12.2%12.942%12.9%29-1.000000x-1.000000x1.052237x1.052237x1.05x11.098%11.1%11.678%11.7%30-1.000000x-1.000000x1.046686x1.046686x1.05x21.119%21.1%22.105%22.1%31-1.000000x-1.000000x1.039581x1.039581x1.04x8.233%8.23%8.559%8.56%32-1.000000x-1.000000x1.039194x1.039194x1.04x8.470%8.47%8.802%8.80%33-1.000000x-1.000000x1.037373x1.037373x1.04x15.022%15.0%15.584%15.6%34-1.000000x-1.000000x1.028857x1.028857x1.03x10.622%10.6%10.928%10.9%35-1.000000x-1.000000x1.027464x1.027464x1.03x5.391%5.39%5.539%5.54%36-1.000000x-1.000000x1.018183x1.018183x1.02x15.334%15.3%15.613%15.6%37-1.000000x-1.000000x1.013146x1.013146x1.01x6.764%6.76%6.853%6.85%38-1.000000x-1.000000x1.007207x1.007207x1.01x12.130%12.1%12.217%12.2%39-1.000000x-1.000000x1.006204x1.006204x1.01x23.095%23.1%23.239%23.2%40-1.000000x-1.000000x1.001229x1.001229x1.00x13.754%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#43

Percentage more likely men are than women to have a professional or doctorate degree (e.g., MBA, PhD, or MD) among people aged 25 years and older.
Scope: population of Columbus, selected other county subdivisions in the Midwest, and entities that contain Columbus
Female
Male
0x2x4xFM#ColumbusColumbusZIP 53925ColumbusRockfordNDaytonSioux FallsCapitalLawrenceDowners GrvAkronLisleWichitaYork TownshipMaineWarrenWheelingBlue TownshipSpringfieldOverland ParkMiltonGrand RapidsOlatheOmahaColumbiaFargoWashingtonEast North CentralLincolnMidwestBloomingdaleWisconsinKansas CityAuroraUnited StatesAnn ArborTopekaSterling HtsPalatineSchaumburgColumbusMadison AreaMadisonKaw TownshipMilwaukeeCedar RapidsClevelandCincinnatiSt. PaulSt. LouisChicagoWayneCtrToledoMinneapolisWorthDetroitProvisoThornton-1.000000x-1.000000x5.794505x5.794505x5.79x0.960%0.96%5.562%5.56%-1.000000x-1.000000x5.794505x5.794505x5.79x0.960%0.96%5.562%5.56%-1.000000x-1.000000x2.803328x2.803328x2.80x1.594%1.59%4.469%4.47%-1.000000x-1.000000x2.566873x2.566873x2.57x1.739%1.74%4.465%4.46%-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-1.000000x1.669388x1.669388x1.67x3.061%3.06%5.110%5.11%21-1.000000x-1.000000x1.632754x1.632754x1.63x1.321%1.32%2.157%2.16%-1.000000x-1.000000x1.627456x1.627456x1.63x3.304%3.30%5.377%5.38%22-1.000000x-1.000000x1.610803x1.610803x1.61x5.701%5.70%9.183%9.18%23-1.000000x-1.000000x1.597848x1.597848x1.60x2.216%2.22%3.541%3.54%-1.000000x-1.000000x1.596978x1.596978x1.60x3.524%3.52%5.628%5.63%24-1.000000x-1.000000x1.589934x1.589934x1.59x2.251%2.25%3.579%3.58%-1.000000x-1.000000x1.586045x1.586045x1.59x1.649%1.65%2.616%2.62%25-1.000000x-1.000000x1.576114x1.576114x1.58x2.109%2.11%3.323%3.32%-1.000000x-1.000000x1.570028x1.570028x1.57x1.087%1.09%1.707%1.71%26-1.000000x-1.000000x1.550495x1.550495x1.55x0.737%0.74%1.143%1.14%27-1.000000x-1.000000x1.526215x1.526215x1.53x2.660%2.66%4.060%4.06%-1.000000x-1.000000x1.522839x1.522839x1.52x14.269%14.3%21.730%21.7%28-1.000000x-1.000000x1.481288x1.481288x1.48x2.641%2.64%3.912%3.91%29-1.000000x-1.000000x1.476996x1.476996x1.48x1.170%1.17%1.728%1.73%30-1.000000x-1.000000x1.457167x1.457167x1.46x2.851%2.85%4.154%4.15%31-1.000000x-1.000000x1.436165x1.436165x1.44x2.115%2.11%3.037%3.04%32-1.000000x-1.000000x1.413654x1.413654x1.41x2.801%2.80%3.959%3.96%33-1.000000x-1.000000x1.400349x1.400349x1.40x4.993%4.99%6.992%6.99%-1.000000x-1.000000x1.387878x1.387878x1.39x7.705%7.70%10.693%10.7%34-1.000000x-1.000000x1.373250x1.373250x1.37x4.975%4.97%6.832%6.83%35-1.000000x-1.000000x1.368590x1.368590x1.37x1.742%1.74%2.385%2.38%36-1.000000x-1.000000x1.346658x1.346658x1.35x2.491%2.49%3.354%3.35%37-1.000000x-1.000000x1.286599x1.286599x1.29x1.699%1.70%2.186%2.19%38-1.000000x-1.000000x1.280610x1.280610x1.28x4.179%4.18%5.351%5.35%39-1.000000x-1.000000x1.274509x1.274509x1.27x5.228%5.23%6.663%6.66%40-1.000000x-1.000000x1.273345x1.273345x1.27x4.319%4.32%5.500%5.50%41-1.000000x-1.000000x1.238186x1.238186x1.24x4.026%4.03%4.985%4.99%42-1.000000x-1.000000x1.223931x1.223931x1.22x1.068%1.07%1.307%1.31%43-1.000000x-1.000000x1.213574x1.213574x1.21x2.357%2.36%2.860%2.86%44-1.000000x-1.000000x1.141406x1.141406x1.14x1.539%1.54%1.757%1.76%45-1.000000x-1.000000x1.124528x1.124528x1.12x5.872%5.87%6.603%6.60%46-1.000000x-1.000000x1.084697x1.084697x1.08x1.883%1.88%2.042%2.04%47-1.000000x-1.000000x1.046557x1.046557x1.05x1.291%1.29%1.351%1.35%48-1.000000x-1.000000x1.042857x1.042857x1.04x2.171%2.17%2.264%2.26%49-1.706858x-1.706858x1.71x1.000000x1.000000x1.072%1.07%0.628%0.63%50
F percentage of females in category
M percentage of males in category
# rank of county subdivision out of 50 by male-to-female sex ratio

Educational Attainment by County Subdivision in the United States

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

No H.S. Diploma by County Subdivision#44

Percent of population 25 years of age and older without a high school diploma (or equivalent).
Scope: population of Columbus, selected other county subdivisions in the United States, and entities that contain Columbus
0%10%20%Count#San Antonio CentralSan Antonio CntrlBronxSan BernardinoLos AngelesSouthwest DallasSW DallasEl PasoAnaheim-Santa Ana-Garden GroveAnaheim-Santa An…FresnoHoustonMiamiDetroitNortheast DallasNE DallasEast San Gabriel ValleyE San Gabriel VlyFort WorthBrooklynLong Beach-LakewoodLong Bch-LakewoodQueensSan Fernando ValleySan Fernando VlyMilwaukeePhiladelphiaOntarioChicagoBaltimoreOceanside-EscondidoOceanside-Escond…Las VegasPhoenixBostonSacramentoOrlandoAustinDenverUnited States of AmericaUnited StatesManhattanSan DiegoTampaSan JoseSan FranciscoTucsonAlbuquerqueTownship 1:Charlotte1, CharlotteColumbusTulsaEast North CentralSalt Lake CitySalt Lk CityTown of HempsteadHempsteadMidwestNorthwest HarrisNW HarrisWashingtonAtlantaSeattleWisconsinNortheast TarrantNE TarrantColumbia CountyColumbiaPlanoZIP Code 53925ZIP 53925Columbus School DistrictColumbusMadison Metro AreaMadison AreaSeattle EastColumbusColumbus28.998944%28.998944%29.0%126,922127k128.837398%28.837398%28.8%261,022261k227.582802%27.582802%27.6%135,754136k324.837401%24.837401%24.8%434,160434k423.987048%23.987048%24.0%141,940142k523.756417%23.756417%23.8%81,30881.3k622.645542%22.645542%22.6%248,699249k722.107626%22.107626%22.1%92,47292.5k821.922900%21.922900%21.9%457,347457k921.818150%21.818150%21.8%149,688150k1021.003600%21.003600%21.0%90,67890.7k1120.783651%20.783651%20.8%207,494207k1220.461493%20.461493%20.5%128,038128k1320.041576%20.041576%20.0%106,726107k1420.017506%20.017506%20.0%351,046351k1519.402518%19.402518%19.4%73,10573.1k1619.344706%19.344706%19.3%315,505316k1719.344408%19.344408%19.3%244,983245k1817.485105%17.485105%17.5%63,80063.8k1917.390838%17.390838%17.4%180,039180k2017.129346%17.129346%17.1%71,39771.4k2116.905373%16.905373%16.9%309,770310k2216.548703%16.548703%16.5%69,83969.8k2315.999398%15.999398%16.0%70,21470.2k2415.906523%15.906523%15.9%198,651199k2514.952077%14.952077%15.0%308,569309k2614.325556%14.325556%14.3%63,64263.6k2713.900512%13.900512%13.9%103,047103k2813.679368%13.679368%13.7%53,75853.8k2913.668915%13.668915%13.7%78,23878.2k3013.638703%13.638703%13.6%63,86563.9k3113.020590%13.020590%13.0%27,818,38027.8M12.996284%12.996284%13.0%160,845161k3212.985760%12.985760%13.0%206,792207k3312.979618%12.979618%13.0%57,75857.8k3412.789590%12.789590%12.8%153,604154k3512.559735%12.559735%12.6%84,02484.0k3612.262851%12.262851%12.3%70,40970.4k3712.089143%12.089143%12.1%52,21752.2k3811.553484%11.553484%11.6%61,37861.4k3911.376979%11.376979%11.4%60,83160.8k4011.299086%11.299086%11.3%43,65343.7k4110.719464%10.719464%10.7%3,363,7843.36M10.435356%10.435356%10.4%64,29464.3k4210.384134%10.384134%10.4%54,23054.2k4310.244520%10.244520%10.2%4,641,8354.64M10.135583%10.135583%10.1%47,67947.7k4410.045421%10.045421%10.0%46,51046.5k459.538552%9.538552%9.5%37,37337.4k468.833573%8.833573%8.8%66,22066.2k478.637220%8.637220%8.6%336,096336k8.418271%8.418271%8.4%31,44331.4k487.225680%7.225680%7.2%2,8795.714681%5.714681%5.7%20,64420.6k495.650531%5.650531%5.7%3145.284625%5.284625%5.3%2985.241862%5.241862%5.2%21,97222.0k4.913852%4.913852%4.9%20,32620.3k504.879466%4.879466%4.9%1684.879466%4.879466%4.9%168
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older without a high school diploma (or equivalent).

Bachelor's Degrees by County Subdivision#45

Percent of population 25 years of age and older with a bachelor's degree or higher..
Scope: population of Columbus, selected other county subdivisions in the United States, and entities that contain Columbus
0%20%40%60%Count#ManhattanSeattle EastWashingtonSan FranciscoPlanoSan JoseAtlantaSeattleBostonDenverAustinMadison Metro AreaMadison AreaTownship 1:Charlotte1, CharlotteTown of HempsteadHempsteadSan DiegoNortheast TarrantNE TarrantNorthwest HarrisNW HarrisChicagoColumbusLos AngelesBrooklynColumbusColumbusSan Fernando ValleySan Fernando VlyNortheast DallasNE DallasSalt Lake CitySalt Lk CityAlbuquerqueTampaTucsonOceanside-EscondidoOceanside-Escond…TulsaQueensUnited States of AmericaUnited StatesHoustonColumbus School DistrictColumbusBaltimoreLong Beach-LakewoodLong Bch-LakewoodZIP Code 53925ZIP 53925MidwestPhoenixOrlandoEast North CentralAnaheim-Santa Ana-Garden GroveAnaheim-Santa An…WisconsinSacramentoEast San Gabriel ValleyE San Gabriel VlyOntarioPhiladelphiaMiamiFort WorthSouthwest DallasSW DallasMilwaukeeColumbia CountyColumbiaFresnoLas VegasEl PasoBronxSan BernardinoSan Antonio CentralSan Antonio CntrlDetroit60.434640%60.434640%60.4%747,953748k157.691220%57.691220%57.7%238,638239k255.360186%55.360186%55.4%256,316256k354.793235%54.793235%54.8%366,564367k454.142756%54.142756%54.1%195,588196k549.985845%49.985845%50.0%600,334600k649.803731%49.803731%49.8%195,136195k749.626221%49.626221%49.6%372,018372k846.377869%46.377869%46.4%206,036206k945.718966%45.718966%45.7%214,085214k1044.843364%44.843364%44.8%256,674257k1143.867317%43.867317%43.9%183,876184k41.989192%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%597,685598k2033.488237%33.488237%33.5%1,15333.488237%33.488237%33.5%1,15333.231104%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%627,520628k3029.792516%29.792516%29.8%1,68029.719611%29.719611%29.7%125,423125k3129.113198%29.113198%29.1%109,693110k3228.972467%28.972467%29.0%1,61028.952816%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%312,038312k3528.373439%28.373439%28.4%1,104,0821.10M28.231204%28.231204%28.2%209,283209k3627.276345%27.276345%27.3%170,682171k3726.758411%26.758411%26.8%111,532112k3826.349720%26.349720%26.3%272,786273k3926.011156%26.011156%26.0%178,455178k4024.665414%24.665414%24.7%131,349131k4123.764821%23.764821%23.8%140,625141k4223.517740%23.517740%23.5%85,81285.8k4322.675936%22.675936%22.7%9,03522.486319%22.486319%22.5%94,05694.1k4421.702666%21.702666%21.7%271,037271k4521.071885%21.071885%21.1%72,12072.1k4619.131504%19.131504%19.1%173,169173k4716.375473%16.375473%16.4%80,59580.6k4814.929012%14.929012%14.9%65,34165.3k4913.833543%13.833543%13.8%59,72359.7k50
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older with a bachelor's degree or higher..

Very Advanced Degrees by County Subdivision#46

Percent of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).
Scope: population of Columbus, selected other county subdivisions in the United States, and entities that contain Columbus
0%5%10%Count#WashingtonManhattanSan FranciscoBostonAtlantaSeattleSan JoseSeattle EastMadison Metro AreaMadison AreaDenverSan DiegoAustinBaltimoreLos AngelesAlbuquerquePlanoChicagoTucsonTown of HempsteadHempsteadTampaMiamiNortheast DallasNE DallasSalt Lake CitySalt Lk CityHoustonPhiladelphiaSan Fernando ValleySan Fernando VlyTownship 1:Charlotte1, CharlotteOceanside-EscondidoOceanside-Escond…BrooklynSacramentoColumbusUnited States of AmericaUnited StatesColumbusColumbusTulsaColumbus School DistrictColumbusZIP Code 53925ZIP 53925PhoenixLong Beach-LakewoodLong Bch-LakewoodMidwestOrlandoEast North CentralFresnoAnaheim-Santa Ana-Garden GroveAnaheim-Santa An…QueensWisconsinNorthwest HarrisNW HarrisNortheast TarrantNE TarrantEast San Gabriel ValleyE San Gabriel VlyOntarioFort WorthLas VegasMilwaukeeSan BernardinoSan Antonio CentralSan Antonio CntrlEl PasoColumbia CountyColumbiaSouthwest DallasSW DallasBronxDetroit12.461852%12.461852%12.5%57,69857.7k110.788423%10.788423%10.8%133,520134k27.558053%7.558053%7.6%50,56350.6k37.340604%7.340604%7.3%32,61132.6k46.889819%6.889819%6.9%26,99527.0k56.641855%6.641855%6.6%49,79049.8k66.255912%6.255912%6.3%75,13475.1k76.036065%6.036065%6.0%24,96825.0k85.974750%5.974750%6.0%25,04425.0k5.725842%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%7,127,6737.13M3.194888%3.194888%3.2%1103.194888%3.194888%3.2%1103.140490%3.140490%3.1%12,13312.1k313.103387%3.103387%3.1%1753.041209%3.041209%3.0%1693.010825%3.010825%3.0%62,13562.1k323.009440%3.009440%3.0%11,33911.3k332.893416%2.893416%2.9%1,311,0191.31M2.893233%2.893233%2.9%11,37011.4k342.855432%2.855432%2.9%896,039896k2.828959%2.828959%2.8%11,83311.8k352.763004%2.763004%2.8%30,34430.3k362.756960%2.756960%2.8%44,96545.0k372.703886%2.703886%2.7%105,215105k2.682967%2.682967%2.7%12,62112.6k382.630994%2.630994%2.6%9,827392.484535%2.484535%2.5%15,54715.5k402.324315%2.324315%2.3%9,688412.173239%2.173239%2.2%11,57311.6k422.155077%2.155077%2.2%26,91426.9k432.043126%2.043126%2.0%7,455441.807306%1.807306%1.8%8,895451.792414%1.792414%1.8%7,845461.745764%1.745764%1.7%5,975471.744303%1.744303%1.7%6951.704476%1.704476%1.7%10,08610.1k481.664253%1.664253%1.7%15,06415.1k491.318660%1.318660%1.3%5,69350
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).

Under-Education Sex Ratio by County Subdivision#47

Percentage more likely men are than women to not have a high school diploma (or equivalent) among people aged 25 years and older.
Scope: population of Columbus, selected other county subdivisions in the United States, and entities that contain Columbus
Female
Male
1x0x1xFM#ColumbusZIP 53925Columbia1, CharlotteDetroitMadison AreaColumbusColumbusWisconsinBaltimoreTulsaSW DallasMidwestFresnoEast North CentralMilwaukeeUnited StatesNE DallasHoustonHempsteadOrlandoPhiladelphiaOntarioSan BernardinoAustinAtlantaFort WorthPhoenixChicagoAlbuquerqueWashingtonSacramentoColumbusSalt Lk CityDenverNE TarrantTampaOceanside-EscondidoOceanside-Escond…NW HarrisBronxPlanoBrooklynSan Antonio CntrlSan Fernando VlyTucsonAnaheim-Santa Ana-Gdn GrvAnaheim-Santa An…Los AngelesLas VegasBostonE San Gabriel VlyQueensMiamiManhattanSeattleLong Bch-LakewoodSeattle EastSan JoseSan DiegoSan FranciscoEl Paso-1.000000x-1.000000x1.544268x1.544268x1.54x4.153%4.15%6.414%6.41%-1.000000x-1.000000x1.532304x1.532304x1.53x4.457%4.46%6.829%6.83%-1.000000x-1.000000x1.312059x1.312059x1.31x6.240%6.24%8.187%8.19%-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-1.000000x1.231258x1.231258x1.23x4.707%4.71%5.796%5.80%-1.000000x-1.000000x1.222166x1.222166x1.22x4.404%4.40%5.383%5.38%-1.000000x-1.000000x1.222166x1.222166x1.22x4.404%4.40%5.383%5.38%-1.000000x-1.000000x1.219291x1.219291x1.22x7.799%7.80%9.509%9.51%-1.000000x-1.000000x1.179669x1.179669x1.18x15.289%15.3%18.036%18.0%3-1.000000x-1.000000x1.177766x1.177766x1.18x10.417%10.4%12.268%12.3%4-1.000000x-1.000000x1.160109x1.160109x1.16x22.304%22.3%25.875%25.9%5-1.000000x-1.000000x1.127915x1.127915x1.13x9.647%9.65%10.881%10.9%-1.000000x-1.000000x1.127206x1.127206x1.13x20.830%20.8%23.479%23.5%6-1.000000x-1.000000x1.125371x1.125371x1.13x10.108%10.1%11.375%11.4%-1.000000x-1.000000x1.123984x1.123984x1.12x16.526%16.5%18.574%18.6%7-1.000000x-1.000000x1.109070x1.109070x1.11x12.369%12.4%13.719%13.7%-1.000000x-1.000000x1.099797x1.099797x1.10x19.814%19.8%21.791%21.8%8-1.000000x-1.000000x1.099188x1.099188x1.10x20.902%20.9%22.975%23.0%9-1.000000x-1.000000x1.092101x1.092101x1.09x9.951%9.95%10.868%10.9%10-1.000000x-1.000000x1.090284x1.090284x1.09x13.111%13.1%14.294%14.3%11-1.000000x-1.000000x1.090163x1.090163x1.09x16.700%16.7%18.206%18.2%12-1.000000x-1.000000x1.088515x1.088515x1.09x16.417%16.4%17.871%17.9%13-1.000000x-1.000000x1.081887x1.081887x1.08x26.536%26.5%28.709%28.7%14-1.000000x-1.000000x1.078150x1.078150x1.08x13.148%13.1%14.176%14.2%15-1.000000x-1.000000x1.073220x1.073220x1.07x9.215%9.21%9.889%9.89%16-1.000000x-1.000000x1.071348x1.071348x1.07x19.379%19.4%20.762%20.8%17-1.000000x-1.000000x1.069008x1.069008x1.07x14.467%14.5%15.465%15.5%18-1.000000x-1.000000x1.068021x1.068021x1.07x16.372%16.4%17.486%17.5%19-1.000000x-1.000000x1.066879x1.066879x1.07x11.714%11.7%12.497%12.5%20-1.000000x-1.000000x1.064309x1.064309x1.06x9.751%9.75%10.378%10.4%21-1.000000x-1.000000x1.053268x1.053268x1.05x13.558%13.6%14.280%14.3%22-1.000000x-1.000000x1.052237x1.052237x1.05x11.098%11.1%11.678%11.7%23-1.000000x-1.000000x1.051272x1.051272x1.05x10.176%10.2%10.697%10.7%24-1.000000x-1.000000x1.049933x1.049933x1.05x13.307%13.3%13.971%14.0%25-1.000000x-1.000000x1.040742x1.040742x1.04x8.257%8.26%8.594%8.59%26-1.000000x-1.000000x1.040003x1.040003x1.04x12.734%12.7%13.244%13.2%27-1.000000x-1.000000x1.039910x1.039910x1.04x15.694%15.7%16.321%16.3%28-1.000000x-1.000000x1.038394x1.038394x1.04x9.953%9.95%10.335%10.3%29-1.000000x-1.000000x1.030539x1.030539x1.03x28.448%28.4%29.316%29.3%30-1.000000x-1.000000x1.023151x1.023151x1.02x5.652%5.65%5.783%5.78%31-1.000000x-1.000000x1.018960x1.018960x1.02x19.845%19.8%20.221%20.2%32-1.000000x-1.000000x1.003929x1.003929x1.00x28.944%28.9%29.058%29.1%33-1.000000x-1.000000x1.003840x1.003840x1.00x19.308%19.3%19.383%19.4%34-1.006471x-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#48

Percentage more likely men are than women to have a professional or doctorate degree (e.g., MBA, PhD, or MD) among people aged 25 years and older.
Scope: population of Columbus, selected other county subdivisions in the United States, and entities that contain Columbus
Female
Male
0x2x4xFM#ColumbusColumbusZIP 53925ColumbusEl PasoSalt Lk CityPlanoTulsaAlbuquerqueNE DallasFort WorthOrlandoPhoenixColumbiaTucson1, CharlotteEast North CentralMidwestNW HarrisLas VegasWisconsinSeattle EastSan Antonio CntrlSan DiegoUnited StatesSan JoseHempsteadFresnoNE TarrantTampaSan Fernando VlyE San Gabriel VlyHoustonSan BernardinoColumbusMadison AreaMiamiAtlantaMilwaukeeAnaheim-Santa Ana-Gdn GrvAnaheim-Santa An…SacramentoPhiladelphiaOceanside-EscondidoOceanside-Escond…Los AngelesAustinBaltimoreWashingtonQueensSW DallasBrooklynManhattanChicagoSeattleBostonBronxOntarioLong Bch-LakewoodDenverSan FranciscoDetroit-1.000000x-1.000000x5.794505x5.794505x5.79x0.960%0.96%5.562%5.56%-1.000000x-1.000000x5.794505x5.794505x5.79x0.960%0.96%5.562%5.56%-1.000000x-1.000000x2.803328x2.803328x2.80x1.594%1.59%4.469%4.47%-1.000000x-1.000000x2.566873x2.566873x2.57x1.739%1.74%4.465%4.46%-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-1.000000x1.660799x1.660799x1.66x2.196%2.20%3.647%3.65%8-1.000000x-1.000000x1.659024x1.659024x1.66x2.280%2.28%3.783%3.78%9-1.000000x-1.000000x1.632754x1.632754x1.63x1.321%1.32%2.157%2.16%-1.000000x-1.000000x1.621815x1.621815x1.62x3.429%3.43%5.561%5.56%10-1.000000x-1.000000x1.611479x1.611479x1.61x2.711%2.71%4.369%4.37%11-1.000000x-1.000000x1.597848x1.597848x1.60x2.216%2.22%3.541%3.54%-1.000000x-1.000000x1.589934x1.589934x1.59x2.251%2.25%3.579%3.58%-1.000000x-1.000000x1.579303x1.579303x1.58x2.100%2.10%3.317%3.32%12-1.000000x-1.000000x1.576623x1.576623x1.58x1.677%1.68%2.643%2.64%13-1.000000x-1.000000x1.576114x1.576114x1.58x2.109%2.11%3.323%3.32%-1.000000x-1.000000x1.557664x1.557664x1.56x4.733%4.73%7.372%7.37%14-1.000000x-1.000000x1.540473x1.540473x1.54x1.423%1.42%2.192%2.19%15-1.000000x-1.000000x1.529565x1.529565x1.53x4.164%4.16%6.370%6.37%16-1.000000x-1.000000x1.526215x1.526215x1.53x2.660%2.66%4.060%4.06%-1.000000x-1.000000x1.514156x1.514156x1.51x4.979%4.98%7.539%7.54%17-1.000000x-1.000000x1.488724x1.488724x1.49x3.608%3.61%5.371%5.37%18-1.000000x-1.000000x1.484269x1.484269x1.48x2.293%2.29%3.404%3.40%19-1.000000x-1.000000x1.481801x1.481801x1.48x2.138%2.14%3.168%3.17%20-1.000000x-1.000000x1.476874x1.476874x1.48x3.518%3.52%5.196%5.20%21-1.000000x-1.000000x1.460302x1.460302x1.46x2.944%2.94%4.299%4.30%22-1.000000x-1.000000x1.451775x1.451775x1.45x2.041%2.04%2.963%2.96%23-1.000000x-1.000000x1.424636x1.424636x1.42x3.092%3.09%4.404%4.40%24-1.000000x-1.000000x1.423621x1.423621x1.42x1.501%1.50%2.137%2.14%25-1.000000x-1.000000x1.413654x1.413654x1.41x2.801%2.80%3.959%3.96%26-1.000000x-1.000000x1.400349x1.400349x1.40x4.993%4.99%6.992%6.99%-1.000000x-1.000000x1.395174x1.395174x1.40x3.384%3.38%4.722%4.72%27-1.000000x-1.000000x1.391590x1.391590x1.39x5.799%5.80%8.070%8.07%28-1.000000x-1.000000x1.368590x1.368590x1.37x1.742%1.74%2.385%2.38%29-1.000000x-1.000000x1.362600x1.362600x1.36x2.347%2.35%3.199%3.20%30-1.000000x-1.000000x1.359928x1.359928x1.36x2.888%2.89%3.927%3.93%31-1.000000x-1.000000x1.341930x1.341930x1.34x3.216%3.22%4.316%4.32%32-1.000000x-1.000000x1.310218x1.310218x1.31x3.011%3.01%3.945%3.95%33-1.000000x-1.000000x1.308108x1.308108x1.31x4.045%4.05%5.292%5.29%34-1.000000x-1.000000x1.303834x1.303834x1.30x4.384%4.38%5.716%5.72%35-1.000000x-1.000000x1.303196x1.303196x1.30x4.332%4.33%5.645%5.65%36-1.000000x-1.000000x1.300117x1.300117x1.30x10.922%10.9%14.199%14.2%37-1.000000x-1.000000x1.285200x1.285200x1.29x2.428%2.43%3.121%3.12%38-1.000000x-1.000000x1.265486x1.265486x1.27x1.515%1.51%1.917%1.92%39-1.000000x-1.000000x1.262281x1.262281x1.26x3.021%3.02%3.814%3.81%40-1.000000x-1.000000x1.245683x1.245683x1.25x9.673%9.67%12.050%12.1%41-1.000000x-1.000000x1.238186x1.238186x1.24x4.026%4.03%4.985%4.99%42-1.000000x-1.000000x1.228890x1.228890x1.23x5.961%5.96%7.326%7.33%43-1.000000x-1.000000x1.221037x1.221037x1.22x6.643%6.64%8.112%8.11%44-1.000000x-1.000000x1.202385x1.202385x1.20x1.526%1.53%1.834%1.83%45-1.000000x-1.000000x1.198236x1.198236x1.20x2.119%2.12%2.539%2.54%46-1.000000x-1.000000x1.181998x1.181998x1.18x2.766%2.77%3.269%3.27%47-1.000000x-1.000000x1.129665x1.129665x1.13x5.378%5.38%6.075%6.08%48-1.000000x-1.000000x1.098720x1.098720x1.10x7.194%7.19%7.905%7.90%49-1.000000x-1.000000x1.046557x1.046557x1.05x1.291%1.29%1.351%1.35%50
F percentage of females in category
M percentage of males in category
# rank of county subdivision out of 50 by male-to-female sex ratio

Definitions

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

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

The coarse levels of educational attainment are as follows:

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

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

More Topics to Explore

Demographics

Income

Education

More Maps to Explore

State:
Wisconsin
County:
Columbia
Metro Area:
Madison Area
City:
Columbus
ZIP Code:
53925
Unified School District:
Columbus
Congressional District:
WI-6
State Senate Districts:
WI-13, WI-14
Assembly Districts:
WI-37, WI-42
Neighboring Towns:
Columbus, Elba
Nearby Towns:
Bristol, Calamus, Fountain Prairie, Hampden, Otsego, Portland, York