Educational Attainment in Dakota, Winona County, Minnesota (City)

Educational Attainment#1

Highest level of education among people aged 25 years and older.
Scope: population of Winona County and Dakota
Dakota
Winona County
0%10%20%30%40%50%CountHigher Degree1H.S. Diploma2No H.S. Diploma235.348837%40.928134%35.348837%35.3%7657.209302%51.575894%57.209302%57.2%1237.441860%7.495972%7.441860%7.4%16
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 Winona County at large.
Scope: population of Winona County and Dakota
-10%0%+10%%ref.Higher Degree1H.S. Diploma2No H.S. Diploma2-13.631936%-13.631936%-13.6%35.349%35.3%40.928%40.9%10.922560%10.922560%+10.9%57.209%57.2%51.576%51.6%-0.721870%-0.721870%-0.7%7.442%7.44%7.496%7.50%
% percentage with given level in Dakota
ref. percentage with given level in Winona 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 Winona County and Dakota
Dakota
Winona County
0%5%10%15%20%25%30%CountDoctorate1Professional1Master's1Bachelor's1Associate's1Some CollegeHigh School2Some H.S.3Less than H.S.3None0.465116%1.859491%0.465116%0.5%11.395349%1.214953%1.395349%1.4%30.465116%7.051241%0.465116%0.5%113.953488%19.152433%13.953488%14.0%3019.069767%11.650016%19.069767%19.1%4124.186047%22.404125%24.186047%24.2%5233.023256%29.171769%33.023256%33.0%715.581395%4.676120%5.581395%5.6%121.860465%2.165646%1.860465%1.9%40.000000%0.000000%0.0%0.654206%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 Winona County at large.
Scope: population of Winona County and Dakota
-100%0%+100%%ref.Doctorate1Professional1Master's1Bachelor's1Associate's1Some CollegeHigh School2Some H.S.3Less than H.S.3None-74.986901%-74.986901%-75.0%0.465%0.47%1.859%1.86%14.847943%14.847943%+14.8%1.395%1.40%1.215%1.21%-93.403767%-93.403767%-93.4%0.465%0.47%7.051%7.05%-27.145088%-27.145088%-27.1%13.953%14.0%19.152%19.2%63.688765%63.688765%+63.7%19.070%19.1%11.650%11.7%7.953542%7.953542%+8.0%24.186%24.2%22.404%22.4%13.202787%13.202787%+13.2%33.023%33.0%29.172%29.2%19.359544%19.359544%+19.4%5.581%5.58%4.676%4.68%-14.091916%-14.091916%-14.1%1.860%1.86%2.166%2.17%-100.000000%-100.000000%-100.0%0.000%0%0.654%0.65%
% percentage with given level in Dakota
ref. percentage with given level in Winona 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 Winona County and Dakota
More Females More Males
Winona County
Dakota
50%0%50%FMHigher Degree1H.S. Diploma2No H.S. Diploma2-73.069307%-13.155583%-73.069307%73%45.545%45.5%26.316%26.3%29.350877%7.302625%29.350877%29%49.505%49.5%64.035%64.0%94.912281%20.843258%94.912281%95%4.950%4.95%9.649%9.65%
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 Winona County and Dakota
More Females More Males
Winona County
Dakota
1k%0k%1k%FMDoctorate1Professional1Master's1Bachelor's1Associate's1Some CollegeHigh School2Some H.S.3Less than H.S.3-1,000.000000%-1,000.000000%> 1000%95.169503%0.990%0.99%0.000%0%1,000.000000%172.789160%1,000.000000%> 1000%0.000%0%2.632%2.63%-1,000.000000%-72.494091%-1,000.000000%> 1000%0.990%0.99%0.000%0%-12.871287%-12.146522%-12.871287%0k%14.851%14.9%13.158%13.2%-172.772277%-13.204272%-172.772277%0k%28.713%28.7%10.526%10.5%-4.510451%-4.510451%0k%6.130134%24.752%24.8%23.684%23.7%63.017544%8.212150%63.017544%0k%24.752%24.8%40.351%40.4%342.982456%7.954137%342.982456%0k%1.980%1.98%8.772%8.77%-238.613861%-238.613861%0k%66.508785%2.970%2.97%0.877%0.88%
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 Winona County and Dakota
Dakota
Winona County
0%5%10%15%20%25%B.X.Total65+45-6435-4425-3417.021277%12.322891%17.021277%17.0%84716.129032%18.278453%16.129032%16.1%15936.250000%21.119171%6.250000%6.3%23211.627907%28.150000%11.627907%11.6%543
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 Winona County at large.
Scope: population of Winona County and Dakota
60%40%20%0%20%%ref.65+45-6435-4425-3438.127300%38.127300%38.1%17.021%17.0%12.323%12.3%-11.759313%-11.759313%11.8%16.129%16.1%18.278%18.3%-70.406035%-70.406035%70.4%6.250%6.25%21.119%21.1%-58.693048%-58.693048%58.7%11.628%11.6%28.150%28.2%
% percentage in Dakota with a Bachelor's degree
ref percentage in Winona 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 Winona County and Dakota
More Females More Males
Winona County
Dakota
1,000%500%0%FM65+45-6435-4425-34187.500000%3.141990%187.500000%187.5%8.696%8.70%25.000%25.0%-32.890365%-6.791466%-32.890365%32.9%18.605%18.6%14.000%14.0%-1,000.000000%-37.003678%-1,000.000000%> 1000%11.111%11.1%0.000%0%-129.411765%-26.518069%-129.411765%129.4%17.647%17.6%7.692%7.69%
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 Winona County and Dakota
Dakota
Winona County
$0k$10k$20k$30k$40kCount%Bachelor's DegreeSome CollegeH.S. Diploma2No H.S. Diploma2Total$43,125.000000$39,614.000000$43,125.000000$43.1k3013.953%14.0%$34,250.000000$32,250.000000$34,250.000000$34.3k9343.256%43.3%$40,625.000000$30,275.000000$40,625.000000$40.6k7133.023%33.0%$46,250.000000$20,518.000000$46,250.000000$46.3k167.442%7.44%$40,625.000000$34,406.000000$40,625.000000$40.6k215100.000%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 Winona County and Dakota
Female Male
Winona County
Dakota
Shaded bar tips show excess over facing bar.
$40k$20k$0k$20k$40kFMBachelor's DegreeSome CollegeTotal$-43,125.000000$-35,739.000000$-43,125.000000$43.1k$43,125.000000$3,125.000000$35,739.000000$11,123.000000$46,250.000000$46.3k1515$-29,167.000000$-29,072.000000$-29,167.000000$29.2k$29,167.000000$12,916.000000$29,072.000000$8,632.000000$42,083.000000$42.1k5439$-30,000.000000$-30,131.000000$-30,000.000000$30.0k$30,000.000000$14,167.000000$30,131.000000$9,784.000000$44,167.000000$44.2k101114
F females with given highest level of educational attainment
M males with given highest level of educational attainment
1or professional degree 2H.S. = High School

Employment by Educational Attainment#12

Percentage of population that is employed by highest level of educational attainment among the population aged 25 to 64 years old.
Scope: population of Winona County and Dakota
Dakota
Winona County
0%20%40%60%80%100%CountBachelor's Degree1Some College2H.S. Diploma3No H.S. Diploma366.666667%90.120912%66.666667%66.7%1685.365854%83.410660%85.365854%85.4%7084.615385%80.463193%84.615385%84.6%44100.000000%61.002549%100.000000%100.0%10
Count employed people with given educational attainment aged 25 to 64 years old
1or higher 2two or four year institution 3H.S. = High School

Lacking High School Diploma By Race#13

Percent of racial or ethnic group lacking a high school diploma (or equivalent).
Scope: population of Winona County and Dakota
Female Male
Winona County
Dakota
Shaded bar tips show excess over facing bar.
6%4%2%0%2%4%6%8%MFWhite1-4.950495%-6.547134%-4.950495%5.0%4.950495%4.698628%6.547134%1.509738%9.649123%9.6%115
M number of males in category
F number of females in category
1non-Hispanic 2excluding black and Asian Hispanics

College Graduates By Race#14

Percent of racial or ethnic group with a bachelor's degree or higher.
Scope: population of Winona County and Dakota
Female Male
Winona County
Dakota
Shaded bar tips show excess over facing bar.
30%20%10%0%10%20%MFWhite1-15.789474%-1.042209%-28.331475%-3.589199%-16.831683%16.8%15.789474%28.331475%15.789474%15.8%1817
M number of males in category
F number of females in category
1non-Hispanic 2excluding black and Asian Hispanics

Educational Attainment by County Subdivision in the Winona Area

There are 32 county subdivisions in the Winona Area. This section compares Dakota to all of the county subdivisions in the Winona Area and to those entities that contain or substantially overlap with Dakota.

No H.S. Diploma by County Subdivision#15

Percent of population 25 years of age and older without a high school diploma (or equivalent).
Scope: population of Dakota, selected other county subdivisions in the Winona Area, and entities that contain Dakota
0%5%10%15%Count#Saratoga TownshipSaratogaUnited States of AmericaUnited StatesHillsdale TownshipHillsdaleLewistonElbaMidwestPleasant Hill TownshipPleasant HlSt. Charles TownshipSt. CharlesElba TownshipWest North CentralUticaZIP Code 55925ZIP 55925Whitewater TownshipWhitewaterUtica TownshipUticaAlturaWinonaWiscoy TownshipWiscoyMount Vernon TownshipMt VernonWinona Metro AreaWinona AreaWinona CountyWinonaDakotaDakotaWinona Area Public School DistrictWinona AreaMinnesotaNew Hartford TownshipNew HartfordWarren TownshipWarrenHart TownshipRichmond TownshipRichmondSt. CharlesRollingstone TownshipRollingstoneGoodviewHomer TownshipHomerStockton670800Tract 670800Wilson TownshipWilsonFremont TownshipFremontNorton TownshipNortonMinnesota CityDresbach TownshipDresbachMinneiskaRollingstone16.617211%16.617211%16.6%56113.020590%13.020590%13.0%27,818,38027.8M11.378205%11.378205%11.4%71210.388350%10.388350%10.4%107310.280374%10.280374%10.3%11410.244520%10.244520%10.2%4,641,8354.64M9.917355%9.917355%9.9%3659.462916%9.462916%9.5%3769.401709%9.401709%9.4%2279.174633%9.174633%9.2%1,278,0511.28M9.090909%9.090909%9.1%1688.910891%8.910891%8.9%728.695652%8.695652%8.7%1098.231707%8.231707%8.2%27107.988981%7.988981%8.0%29117.914094%7.914094%7.9%1,205127.906977%7.906977%7.9%17137.647059%7.647059%7.6%13147.495972%7.495972%7.5%2,3267.495972%7.495972%7.5%2,3267.441860%7.441860%7.4%167.441860%7.441860%7.4%16157.391159%7.391159%7.4%1,7697.376055%7.376055%7.4%270,121270k7.350689%7.350689%7.4%48166.823529%6.823529%6.8%29176.637168%6.637168%6.6%15186.237817%6.237817%6.2%32196.162587%6.162587%6.2%141206.126482%6.126482%6.1%31216.087896%6.087896%6.1%169226.087824%6.087824%6.1%61236.030151%6.030151%6.0%24245.293222%5.293222%5.3%2785.174353%5.174353%5.2%46255.022831%5.022831%5.0%11264.430380%4.430380%4.4%14274.166667%4.166667%4.2%5284.153355%4.153355%4.2%13294.081633%4.081633%4.1%2302.708804%2.708804%2.7%1231
Count number of people in category
# rank of county subdivision out of 31 by percentage of population 25 years of age and older without a high school diploma (or equivalent).

Bachelor's Degrees by County Subdivision#16

Percent of population 25 years of age and older with a bachelor's degree or higher..
Scope: population of Dakota, selected other county subdivisions in the Winona Area, and entities that contain Dakota
0%10%20%30%Count#Dresbach TownshipDresbach670800Tract 670800WinonaMinnesotaHomer TownshipHomerWhitewater TownshipWhitewaterWilson TownshipWilsonWinona Area Public School DistrictWinona AreaSt. Charles TownshipSt. CharlesUnited States of AmericaUnited StatesWest North CentralWinona Metro AreaWinona AreaWinona CountyWinonaUtica TownshipUticaMidwestRollingstoneWiscoy TownshipWiscoyNorton TownshipNortonMinneiskaWarren TownshipWarrenMount Vernon TownshipMt VernonNew Hartford TownshipNew HartfordGoodviewElba TownshipSt. CharlesRichmond TownshipRichmondSaratoga TownshipSaratogaAlturaStocktonRollingstone TownshipRollingstoneLewistonZIP Code 55925ZIP 55925Fremont TownshipFremontHillsdale TownshipHillsdaleDakotaDakotaUticaMinnesota CityPleasant Hill TownshipPleasant HlHart TownshipElba38.658147%38.658147%38.7%121134.729627%34.729627%34.7%1,82434.244056%34.244056%34.2%5,214234.240609%34.240609%34.2%1,253,9371.25M34.031936%34.031936%34.0%341333.913043%33.913043%33.9%39432.845894%32.845894%32.8%292530.914181%30.914181%30.9%7,39930.434783%30.434783%30.4%119630.315023%30.315023%30.3%64,767,78764.8M30.056536%30.056536%30.1%4,186,9564.19M29.278118%29.278118%29.3%9,08529.278118%29.278118%29.3%9,08529.268293%29.268293%29.3%96728.952816%28.952816%29.0%13,118,64213.1M28.442438%28.442438%28.4%126828.372093%28.372093%28.4%61927.848101%27.848101%27.8%881026.530612%26.530612%26.5%131125.176471%25.176471%25.2%1071224.705882%24.705882%24.7%421324.655436%24.655436%24.7%1611424.603746%24.603746%24.6%6831524.358974%24.358974%24.4%571624.300699%24.300699%24.3%5561722.417154%22.417154%22.4%1151821.958457%21.958457%22.0%741921.212121%21.212121%21.2%772021.105528%21.105528%21.1%842120.948617%20.948617%20.9%1062220.291262%20.291262%20.3%2092319.183168%19.183168%19.2%15517.808219%17.808219%17.8%392417.147436%17.147436%17.1%1072516.279070%16.279070%16.3%3516.279070%16.279070%16.3%352614.772727%14.772727%14.8%262713.333333%13.333333%13.3%162813.223140%13.223140%13.2%482911.946903%11.946903%11.9%27305.607477%5.607477%5.6%631
Count number of people in category
# rank of county subdivision out of 31 by percentage of population 25 years of age and older with a bachelor's degree or higher..

Very Advanced Degrees by County Subdivision#17

Percent of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).
Scope: population of Dakota, selected other county subdivisions in the Winona Area, and entities that contain Dakota
0%2%4%6%Count#Dresbach TownshipDresbachWilson TownshipWilson670800Tract 670800Wiscoy TownshipWiscoyWinonaHomer TownshipHomerSt. Charles TownshipSt. CharlesWinona Area Public School DistrictWinona AreaMinnesotaElba TownshipUnited States of AmericaUnited StatesMinnesota CityRichmond TownshipRichmondWinona Metro AreaWinona AreaWinona CountyWinonaWest North CentralMidwestWarren TownshipWarrenHillsdale TownshipHillsdaleSaratoga TownshipSaratogaRollingstone TownshipRollingstoneUtica TownshipUticaDakotaDakotaNew Hartford TownshipNew HartfordPleasant Hill TownshipPleasant HlLewistonZIP Code 55925ZIP 55925Fremont TownshipFremontRollingstoneWhitewater TownshipWhitewaterStocktonGoodviewNorton TownshipNortonSt. CharlesAlturaUticaHart TownshipMount Vernon TownshipMt VernonElbaMinneiska6.709265%6.709265%6.7%2116.636670%6.636670%6.6%5926.169078%6.169078%6.2%3245.581395%5.581395%5.6%1234.236175%4.236175%4.2%64543.692615%3.692615%3.7%3753.580563%3.580563%3.6%1463.518008%3.518008%3.5%8423.458748%3.458748%3.5%126,664127k3.418803%3.418803%3.4%873.336158%3.336158%3.3%7,127,6737.13M3.333333%3.333333%3.3%483.313840%3.313840%3.3%1793.074444%3.074444%3.1%9543.074444%3.074444%3.1%9542.978981%2.978981%3.0%414,980415k2.893416%2.893416%2.9%1,311,0191.31M2.823529%2.823529%2.8%12102.724359%2.724359%2.7%17112.670623%2.670623%2.7%9122.569170%2.569170%2.6%13132.134146%2.134146%2.1%7141.860465%1.860465%1.9%41.860465%1.860465%1.9%4151.837672%1.837672%1.8%12161.101928%1.101928%1.1%4171.067961%1.067961%1.1%11180.990099%0.990099%1.0%80.913242%0.913242%0.9%2190.902935%0.902935%0.9%4200.869565%0.869565%0.9%1210.753769%0.753769%0.8%3220.720461%0.720461%0.7%20230.632911%0.632911%0.6%2240.611888%0.611888%0.6%14250.550964%0.550964%0.6%2260.000000%0.000000%0.0%0270.000000%0.000000%0.0%0280.000000%0.000000%0.0%0290.000000%0.000000%0.0%0300.000000%0.000000%0.0%031
Count number of people in category
# rank of county subdivision out of 31 by percentage of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).

Under-Education Sex Ratio by County Subdivision#18

Percentage more likely men are than women to not have a high school diploma (or equivalent) among people aged 25 years and older.
Scope: population of Dakota, selected other county subdivisions in the Winona Area, and entities that contain Dakota
Female
Male
0x5x10xFM#Elba TownshipMinneiskaNortonWiscoyHart TownshipUticaUticaMt VernonElbaFremontRichmondMinnesota CityAlturaWhitewaterDakotaDakotaHomerHillsdaleZIP 55925St. CharlesGoodviewRollingstoneStocktonNew HartfordDresbachTract 670800St. CharlesWinona AreaWinonaPleasant HlWest North CentralMinnesotaMidwestRollingstoneUnited StatesWinona AreaSaratogaWarrenLewistonWinonaWilson-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%18.333%18.3%1-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%7.143%7.14%2-1.000000x-1.000000x6.897959x6.897959x6.90x1.183%1.18%8.163%8.16%3-1.000000x-1.000000x6.400862x6.400862x6.40x2.020%2.02%12.931%12.9%4-1.000000x-1.000000x5.949153x5.949153x5.95x1.852%1.85%11.017%11.0%5-1.000000x-1.000000x4.746032x4.746032x4.75x3.261%3.26%15.476%15.5%6-1.000000x-1.000000x4.139645x4.139645x4.14x3.145%3.14%13.018%13.0%7-1.000000x-1.000000x3.412698x3.412698x3.41x3.488%3.49%11.905%11.9%8-1.000000x-1.000000x3.393443x3.393443x3.39x4.348%4.35%14.754%14.8%9-1.000000x-1.000000x3.199219x3.199219x3.20x2.198%2.20%7.031%7.03%10-1.000000x-1.000000x3.139717x3.139717x3.14x2.917%2.92%9.158%9.16%11-1.000000x-1.000000x2.956522x2.956522x2.96x1.961%1.96%5.797%5.80%12-1.000000x-1.000000x2.309613x2.309613x2.31x4.865%4.86%11.236%11.2%13-1.000000x-1.000000x2.214689x2.214689x2.21x5.357%5.36%11.864%11.9%14-1.000000x-1.000000x1.949123x1.949123x1.95x4.950%4.95%9.649%9.65%-1.000000x-1.000000x1.949123x1.949123x1.95x4.950%4.95%9.649%9.65%15-1.000000x-1.000000x1.703345x1.703345x1.70x4.481%4.48%7.632%7.63%16-1.000000x-1.000000x1.676803x1.676803x1.68x8.273%8.27%13.873%13.9%17-1.000000x-1.000000x1.675440x1.675440x1.68x6.616%6.62%11.084%11.1%-1.000000x-1.000000x1.583688x1.583688x1.58x7.389%7.39%11.702%11.7%18-1.000000x-1.000000x1.500609x1.500609x1.50x4.862%4.86%7.296%7.30%19-1.000000x-1.000000x1.451884x1.451884x1.45x5.019%5.02%7.287%7.29%20-1.000000x-1.000000x1.372139x1.372139x1.37x5.076%5.08%6.965%6.97%21-1.000000x-1.000000x1.328955x1.328955x1.33x6.289%6.29%8.358%8.36%22-1.000000x-1.000000x1.328655x1.328655x1.33x3.521%3.52%4.678%4.68%23-1.000000x-1.000000x1.292097x1.292097x1.29x4.609%4.61%5.955%5.96%-1.000000x-1.000000x1.238690x1.238690x1.24x5.523%5.52%6.841%6.84%24-1.000000x-1.000000x1.208433x1.208433x1.21x6.792%6.79%8.208%8.21%-1.000000x-1.000000x1.208433x1.208433x1.21x6.792%6.79%8.208%8.21%-1.000000x-1.000000x1.179695x1.179695x1.18x9.036%9.04%10.660%10.7%25-1.000000x-1.000000x1.137506x1.137506x1.14x8.598%8.60%9.780%9.78%-1.000000x-1.000000x1.136388x1.136388x1.14x6.913%6.91%7.856%7.86%-1.000000x-1.000000x1.127915x1.127915x1.13x9.647%9.65%10.881%10.9%-1.000000x-1.000000x1.119617x1.119617x1.12x2.564%2.56%2.871%2.87%26-1.000000x-1.000000x1.109070x1.109070x1.11x12.369%12.4%13.719%13.7%-1.000000x-1.000000x1.108477x1.108477x1.11x7.014%7.01%7.775%7.77%-1.000000x-1.000000x1.080467x1.080467x1.08x15.976%16.0%17.262%17.3%27-1.000000x-1.000000x1.036706x1.036706x1.04x6.699%6.70%6.944%6.94%28-1.000255x-1.000255x1.00x1.000000x1.000000x10.390%10.4%10.387%10.4%29-1.021534x-1.021534x1.02x1.000000x1.000000x7.996%8.00%7.828%7.83%30-2.625594x-2.625594x2.63x1.000000x1.000000x7.551%7.55%2.876%2.88%31
F percentage of females in category
M percentage of males in category
# rank of county subdivision out of 31 by male-to-female sex ratio

Over-Education Sex Ratio by County Subdivision#19

Percentage more likely men are than women to have a professional or doctorate degree (e.g., MBA, PhD, or MD) among people aged 25 years and older.
Scope: population of Dakota, selected other county subdivisions in the Winona Area, and entities that contain Dakota
Female
Male
10x5x0x5x10xFM#StocktonAlturaNortonWhitewaterWinonaRollingstoneLewistonNew HartfordTract 670800DakotaDakotaDresbachHillsdaleWinona AreaWinona AreaWinonaSt. CharlesMidwestElba TownshipZIP 55925West North CentralUnited StatesMinnesotaSt. CharlesHomerWiscoyPleasant HlWilsonMinnesota CityRichmondSaratogaRollingstoneWarrenGoodviewUticaFremont-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%1.493%1.49%1-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%1.124%1.12%2-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%1.361%1.36%3-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%1.695%1.69%4-1.000000x-1.000000x3.549966x3.549966x3.55x1.887%1.89%6.698%6.70%5-1.000000x-1.000000x3.358852x3.358852x3.36x0.427%0.43%1.435%1.44%6-1.000000x-1.000000x2.927359x2.927359x2.93x0.557%0.56%1.629%1.63%7-1.000000x-1.000000x2.847761x2.847761x2.85x0.943%0.94%2.687%2.69%8-1.000000x-1.000000x2.676230x2.676230x2.68x3.331%3.33%8.914%8.91%-1.000000x-1.000000x2.657895x2.657895x2.66x0.990%0.99%2.632%2.63%-1.000000x-1.000000x2.657895x2.657895x2.66x0.990%0.99%2.632%2.63%9-1.000000x-1.000000x2.657310x2.657310x2.66x3.521%3.52%9.357%9.36%10-1.000000x-1.000000x2.611272x2.611272x2.61x1.439%1.44%3.757%3.76%11-1.000000x-1.000000x2.378740x2.378740x2.38x2.089%2.09%4.970%4.97%-1.000000x-1.000000x2.216484x2.216484x2.22x1.916%1.92%4.247%4.25%-1.000000x-1.000000x2.216484x2.216484x2.22x1.916%1.92%4.247%4.25%-1.000000x-1.000000x1.943617x1.943617x1.94x2.463%2.46%4.787%4.79%12-1.000000x-1.000000x1.589934x1.589934x1.59x2.251%2.25%3.579%3.58%-1.000000x-1.000000x1.583333x1.583333x1.58x2.632%2.63%4.167%4.17%13-1.000000x-1.000000x1.578313x1.578313x1.58x0.763%0.76%1.205%1.20%-1.000000x-1.000000x1.572017x1.572017x1.57x2.329%2.33%3.662%3.66%-1.000000x-1.000000x1.526215x1.526215x1.53x2.660%2.66%4.060%4.06%-1.000000x-1.000000x1.481015x1.481015x1.48x2.798%2.80%4.144%4.14%-1.000000x-1.000000x1.412541x1.412541x1.41x0.510%0.51%0.720%0.72%14-1.000000x-1.000000x1.409263x1.409263x1.41x3.055%3.05%4.305%4.31%15-1.171717x-1.171717x1.17x1.000000x1.000000x6.061%6.06%5.172%5.17%16-1.186747x-1.186747x1.19x1.000000x1.000000x1.205%1.20%1.015%1.02%17-1.225867x-1.225867x1.23x1.000000x1.000000x7.323%7.32%5.973%5.97%18-1.352941x-1.352941x1.35x1.000000x1.000000x3.922%3.92%2.899%2.90%19-1.625000x-1.625000x1.63x1.000000x1.000000x4.167%4.17%2.564%2.56%20-1.988166x-1.988166x1.99x1.000000x1.000000x3.550%3.55%1.786%1.79%21-2.145753x-2.145753x2.15x1.000000x1.000000x3.475%3.47%1.619%1.62%22-5.167464x-5.167464x5.17x1.000000x1.000000x4.785%4.78%0.926%0.93%23-10.000000x-10.000000x> 10.0x1.000000x1.000000x1.451%1.45%0.000%0%24-10.000000x-10.000000x> 10.0x1.000000x1.000000x4.403%4.40%0.000%0%25-10.000000x-10.000000x> 10.0x1.000000x1.000000x2.198%2.20%0.000%0%26
F percentage of females in category
M percentage of males in category
# rank of county subdivision out of 26 by male-to-female sex ratio

Educational Attainment by County Subdivision in Minnesota

There are 2,761 county subdivisions in Minnesota. This section compares Dakota to the 50 most populous county subdivisions in Minnesota and to those entities that contain or substantially overlap with Dakota. The least populous of the compared county subdivisions has a population of 22,226.

No H.S. Diploma by County Subdivision#20

Percent of population 25 years of age and older without a high school diploma (or equivalent).
Scope: population of Dakota, selected other county subdivisions in Minnesota, and entities that contain Dakota
0%5%10%15%Count#FaribaultAustinBrooklyn CenterBrooklyn CtrSt. PaulUnited States of AmericaUnited StatesRichfieldMinneapolisMidwestBrooklyn ParkFridleyWest North CentralZIP Code 55925ZIP 55925WinonaMaplewoodInver Grove HeightsInver Grv HtsShakopeeBloomingtonSt. CloudWinona Metro AreaWinona AreaWinona CountyWinonaCrystalDakotaDakotaWinona Area Public School DistrictWinona AreaMinnesotaOwatonnaCoon RapidsRosevilleDuluthRochesterBurnsvilleHastingsMankatoNew BrightonOakdaleChaskaMoorhead670800Tract 670800BlaineApple ValleyCottage GroveElk RiverSavageFarmingtonSt. Louis ParkSt. Louis PkAndoverRamseyEaganWhite Bear LakeWhite Bear LkPrior LakeRosemountLakevilleEden PrairieShoreviewChamplinWoodburyPlymouthMinnetonkaChanhassenMaple GroveEdina16.891386%16.891386%16.9%2,706116.529027%16.529027%16.5%2,682216.036673%16.036673%16.0%3,131313.278342%13.278342%13.3%24,61324.6k413.020590%13.020590%13.0%27,818,38027.8M11.017383%11.017383%11.0%2,795510.958428%10.958428%11.0%29,34729.3k610.244520%10.244520%10.2%4,641,8354.64M10.167910%10.167910%10.2%5,01479.793424%9.793424%9.8%1,81189.174633%9.174633%9.2%1,278,0511.28M8.910891%8.910891%8.9%727.914094%7.914094%7.9%1,20597.910263%7.910263%7.9%2,172107.772967%7.772967%7.8%1,831117.542599%7.542599%7.5%1,837127.540581%7.540581%7.5%4,729137.521396%7.521396%7.5%2,285147.495972%7.495972%7.5%2,3267.495972%7.495972%7.5%2,3267.446682%7.446682%7.4%1,250157.441860%7.441860%7.4%167.441860%7.441860%7.4%167.391159%7.391159%7.4%1,7697.376055%7.376055%7.4%270,121270k7.196882%7.196882%7.2%1,237167.021578%7.021578%7.0%3,023176.821133%6.821133%6.8%1,681186.456536%6.456536%6.5%3,427196.300465%6.300465%6.3%4,713206.224589%6.224589%6.2%2,572216.110006%6.110006%6.1%952225.855251%5.855251%5.9%1,220235.686185%5.686185%5.7%873245.387794%5.387794%5.4%1,017255.326215%5.326215%5.3%858265.311348%5.311348%5.3%1,253275.293222%5.293222%5.3%2785.219035%5.219035%5.2%2,154284.998974%4.998974%5.0%1,705294.937132%4.937132%4.9%1,123304.603205%4.603205%4.6%721314.312955%4.312955%4.3%812324.216911%4.216911%4.2%584334.052866%4.052866%4.1%1,429344.031177%4.031177%4.0%812353.724508%3.724508%3.7%610363.667395%3.667395%3.7%1,646373.645924%3.645924%3.6%631383.629499%3.629499%3.6%596393.564652%3.564652%3.6%526403.487209%3.487209%3.5%1,325413.205970%3.205970%3.2%1,392423.194655%3.194655%3.2%612433.108874%3.108874%3.1%488443.024874%3.024874%3.0%1,317452.612169%2.612169%2.6%1,406462.317073%2.317073%2.3%893472.309237%2.309237%2.3%368482.095945%2.095945%2.1%966492.079742%2.079742%2.1%74850
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older without a high school diploma (or equivalent).

Bachelor's Degrees by County Subdivision#21

Percent of population 25 years of age and older with a bachelor's degree or higher..
Scope: population of Dakota, selected other county subdivisions in Minnesota, and entities that contain Dakota
0%20%40%60%Count#EdinaEden PrairieChanhassenMinnetonkaWoodburyPlymouthSt. Louis ParkSt. Louis PkShoreviewMaple GroveEaganLakevilleMinneapolisNew BrightonRosevillePrior LakeChaskaRosemountRochesterApple ValleySavageBloomingtonSt. PaulBurnsvilleChamplinMoorheadRichfieldShakopeeMankatoFarmingtonDuluth670800Tract 670800Inver Grove HeightsInver Grv HtsWinonaMinnesotaAndoverWhite Bear LakeWhite Bear LkBlaineOakdaleWinona Area Public School DistrictWinona AreaElk RiverCottage GroveCrystalUnited States of AmericaUnited StatesWest North CentralMaplewoodBrooklyn ParkWinona Metro AreaWinona AreaWinona CountyWinonaSt. CloudMidwestRamseyHastingsOwatonnaFridleyCoon RapidsAustinBrooklyn CenterBrooklyn CtrZIP Code 55925ZIP 55925FaribaultDakotaDakota68.687093%68.687093%68.7%24,70424.7k162.175545%62.175545%62.2%26,99627.0k260.253514%60.253514%60.3%9,602358.886871%58.886871%58.9%22,69522.7k458.692207%58.692207%58.7%25,55425.6k557.488156%57.488156%57.5%30,94330.9k655.889276%55.889276%55.9%19,70619.7k754.601451%54.601451%54.6%10,46010.5k850.665018%50.665018%50.7%23,35123.4k950.398824%50.398824%50.4%22,62022.6k1048.278766%48.278766%48.3%18,34418.3k1147.670489%47.670489%47.7%127,663128k1247.267635%47.267635%47.3%7,2571346.445382%46.445382%46.4%11,44611.4k1445.472261%45.472261%45.5%7,4671544.248557%44.248557%44.2%7,1281644.076986%44.076986%44.1%6,5041743.718250%43.718250%43.7%32,70332.7k1843.384056%43.384056%43.4%14,79714.8k1943.102990%43.102990%43.1%8,1152040.791530%40.791530%40.8%25,58225.6k2139.969357%39.969357%40.0%74,08874.1k2238.511617%38.511617%38.5%15,91315.9k2337.561317%37.561317%37.6%5,8962437.153999%37.153999%37.2%8,7652536.544602%36.544602%36.5%9,2712636.468898%36.468898%36.5%8,8822736.144174%36.144174%36.1%7,5312835.764315%35.764315%35.8%4,9532935.389427%35.389427%35.4%18,78418.8k3034.729627%34.729627%34.7%1,82434.649346%34.649346%34.6%8,1623134.244056%34.244056%34.2%5,2143234.240609%34.240609%34.2%1,253,9371.25M34.091248%34.091248%34.1%6,8673333.633790%33.633790%33.6%5,8213433.485172%33.485172%33.5%13,82013.8k3531.447341%31.447341%31.4%5,9363630.914181%30.914181%30.9%7,39930.760391%30.760391%30.8%4,8183730.616372%30.616372%30.6%6,9643830.400334%30.400334%30.4%5,1033930.315023%30.315023%30.3%64,767,78764.8M30.056536%30.056536%30.1%4,186,9564.19M30.016753%30.016753%30.0%8,2424029.516142%29.516142%29.5%14,55514.6k4129.278118%29.278118%29.3%9,08529.278118%29.278118%29.3%9,08529.150757%29.150757%29.2%8,8564228.952816%28.952816%29.0%13,118,64213.1M28.410062%28.410062%28.4%4,6534328.059816%28.059816%28.1%4,3724427.682104%27.682104%27.7%4,7584527.190136%27.190136%27.2%5,0284625.993543%25.993543%26.0%11,19111.2k4721.410083%21.410083%21.4%3,4744820.631018%20.631018%20.6%4,0284919.183168%19.183168%19.2%15518.795256%18.795256%18.8%3,0115016.279070%16.279070%16.3%3516.279070%16.279070%16.3%35
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older with a bachelor's degree or higher..

Very Advanced Degrees by County Subdivision#22

Percent of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).
Scope: population of Dakota, selected other county subdivisions in Minnesota, and entities that contain Dakota
0%5%10%Count#EdinaRochesterShoreviewRosevilleMinnetonkaWoodburyEden PrairieMinneapolis670800Tract 670800St. PaulPlymouthSt. Louis ParkSt. Louis PkNew BrightonEaganDuluthWinonaMankatoChanhassenMaple GroveMaplewoodLakevilleWinona Area Public School DistrictWinona AreaChamplinMinnesotaSt. CloudUnited States of AmericaUnited StatesBloomingtonWinona Metro AreaWinona AreaWinona CountyWinonaWest North CentralApple ValleyMidwestAustinChaskaWhite Bear LakeWhite Bear LkInver Grove HeightsInver Grv HtsMoorheadBlaineBurnsvillePrior LakeRosemountFridleyShakopeeRichfieldDakotaDakotaSavageOakdaleRamseyBrooklyn ParkCottage GroveCrystalOwatonnaAndoverFaribaultFarmingtonElk RiverCoon RapidsBrooklyn CenterBrooklyn CtrHastingsZIP Code 55925ZIP 5592511.352388%11.352388%11.4%4,08318.768248%8.768248%8.8%6,55927.532495%7.532495%7.5%1,44337.458205%7.458205%7.5%1,83847.368967%7.368967%7.4%2,84057.214222%7.214222%7.2%3,14166.425758%6.425758%6.4%2,79076.241155%6.241155%6.2%16,71416.7k86.169078%6.169078%6.2%3245.920847%5.920847%5.9%10,97511.0k95.718532%5.718532%5.7%3,078105.249723%5.249723%5.2%1,851114.722204%4.722204%4.7%725124.400428%4.400428%4.4%1,975134.278609%4.278609%4.3%2,271144.236175%4.236175%4.2%645154.218660%4.218660%4.2%879163.852912%3.852912%3.9%614173.692855%3.692855%3.7%1,702183.590939%3.590939%3.6%986193.521423%3.521423%3.5%1,338203.518008%3.518008%3.5%8423.510225%3.510225%3.5%551213.458748%3.458748%3.5%126,664127k3.367347%3.367347%3.4%1,023223.336158%3.336158%3.3%7,127,6737.13M3.138055%3.138055%3.1%1,968233.074444%3.074444%3.1%9543.074444%3.074444%3.1%9542.978981%2.978981%3.0%414,980415k2.958337%2.958337%3.0%1,009242.893416%2.893416%2.9%1,311,0191.31M2.884260%2.884260%2.9%468252.874170%2.874170%2.9%463262.692552%2.692552%2.7%466272.623535%2.623535%2.6%618282.564537%2.564537%2.6%605292.500485%2.500485%2.5%1,032302.405615%2.405615%2.4%994312.174045%2.174045%2.2%357322.134725%2.134725%2.1%315332.103612%2.103612%2.1%389342.003695%2.003695%2.0%488351.876306%1.876306%1.9%476361.860465%1.860465%1.9%41.860465%1.860465%1.9%41.859032%1.859032%1.9%350371.769443%1.769443%1.8%334381.727928%1.727928%1.7%283391.673021%1.673021%1.7%825401.653038%1.653038%1.7%376411.638270%1.638270%1.6%275421.605771%1.605771%1.6%276431.558854%1.558854%1.6%314441.510612%1.510612%1.5%242451.509134%1.509134%1.5%209461.283279%1.283279%1.3%201471.272850%1.272850%1.3%548481.126818%1.126818%1.1%220491.123163%1.123163%1.1%175500.990099%0.990099%1.0%8
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).

Under-Education Sex Ratio by County Subdivision#23

Percentage more likely men are than women to not have a high school diploma (or equivalent) among people aged 25 years and older.
Scope: population of Dakota, selected other county subdivisions in Minnesota, and entities that contain Dakota
Female
Male
1x0x1x2xFM#FarmingtonDakotaDakotaZIP 55925RamseyEden PrairieMoorheadOwatonnaMaplewoodElk RiverSt. Louis PkShoreviewShakopeeTract 670800AustinHastingsFridleyCoon RapidsDuluthWinona AreaWinonaBrooklyn CtrRichfieldFaribaultWest North CentralMinnesotaMidwestPrior LakeChanhassenUnited StatesWinona AreaChamplinBlaineAndoverCrystalCottage GroveLakevilleRosemountWinonaRochesterBloomingtonSt. PaulBurnsvilleEaganMinneapolisInver Grv HtsMankatoApple ValleyMaple GroveChaskaSt. CloudWoodburyRosevilleOakdaleBrooklyn ParkEdinaPlymouthMinnetonkaWhite Bear LkSavageNew Brighton-1.000000x-1.000000x2.003868x2.003868x2.00x2.835%2.84%5.681%5.68%1-1.000000x-1.000000x1.949123x1.949123x1.95x4.950%4.95%9.649%9.65%-1.000000x-1.000000x1.949123x1.949123x1.95x4.950%4.95%9.649%9.65%-1.000000x-1.000000x1.675440x1.675440x1.68x6.616%6.62%11.084%11.1%-1.000000x-1.000000x1.569928x1.569928x1.57x2.887%2.89%4.532%4.53%2-1.000000x-1.000000x1.513482x1.513482x1.51x2.564%2.56%3.881%3.88%3-1.000000x-1.000000x1.505859x1.505859x1.51x4.258%4.26%6.411%6.41%4-1.000000x-1.000000x1.416944x1.416944x1.42x5.995%6.00%8.495%8.49%5-1.000000x-1.000000x1.413357x1.413357x1.41x6.619%6.62%9.355%9.36%6-1.000000x-1.000000x1.411657x1.411657x1.41x3.821%3.82%5.394%5.39%7-1.000000x-1.000000x1.398134x1.398134x1.40x3.411%3.41%4.769%4.77%8-1.000000x-1.000000x1.317049x1.317049x1.32x2.784%2.78%3.666%3.67%9-1.000000x-1.000000x1.299444x1.299444x1.30x6.595%6.59%8.569%8.57%10-1.000000x-1.000000x1.292097x1.292097x1.29x4.609%4.61%5.955%5.96%-1.000000x-1.000000x1.289646x1.289646x1.29x14.496%14.5%18.694%18.7%11-1.000000x-1.000000x1.288751x1.288751x1.29x5.348%5.35%6.892%6.89%12-1.000000x-1.000000x1.269201x1.269201x1.27x8.625%8.62%10.946%10.9%13-1.000000x-1.000000x1.245609x1.245609x1.25x6.293%6.29%7.839%7.84%14-1.000000x-1.000000x1.237646x1.237646x1.24x5.794%5.79%7.171%7.17%15-1.000000x-1.000000x1.208433x1.208433x1.21x6.792%6.79%8.208%8.21%-1.000000x-1.000000x1.208433x1.208433x1.21x6.792%6.79%8.208%8.21%-1.000000x-1.000000x1.171442x1.171442x1.17x14.825%14.8%17.367%17.4%16-1.000000x-1.000000x1.163628x1.163628x1.16x10.209%10.2%11.880%11.9%17-1.000000x-1.000000x1.151611x1.151611x1.15x15.625%15.6%17.994%18.0%18-1.000000x-1.000000x1.137506x1.137506x1.14x8.598%8.60%9.780%9.78%-1.000000x-1.000000x1.136388x1.136388x1.14x6.913%6.91%7.856%7.86%-1.000000x-1.000000x1.127915x1.127915x1.13x9.647%9.65%10.881%10.9%-1.000000x-1.000000x1.126917x1.126917x1.13x3.416%3.42%3.849%3.85%19-1.000000x-1.000000x1.122496x1.122496x1.12x2.180%2.18%2.448%2.45%20-1.000000x-1.000000x1.109070x1.109070x1.11x12.369%12.4%13.719%13.7%-1.000000x-1.000000x1.108477x1.108477x1.11x7.014%7.01%7.775%7.77%-1.000000x-1.000000x1.101837x1.101837x1.10x2.962%2.96%3.263%3.26%21-1.000000x-1.000000x1.079970x1.079970x1.08x5.025%5.03%5.427%5.43%22-1.000000x-1.000000x1.079583x1.079583x1.08x3.877%3.88%4.185%4.19%23-1.000000x-1.000000x1.078552x1.078552x1.08x7.176%7.18%7.740%7.74%24-1.000000x-1.000000x1.037512x1.037512x1.04x4.848%4.85%5.030%5.03%25-1.000000x-1.000000x1.032815x1.032815x1.03x3.432%3.43%3.544%3.54%26-1.000159x-1.000159x1.00x1.000000x1.000000x3.565%3.56%3.564%3.56%27-1.021534x-1.021534x1.02x1.000000x1.000000x7.996%8.00%7.828%7.83%28-1.041504x-1.041504x1.04x1.000000x1.000000x6.423%6.42%6.167%6.17%29-1.052680x-1.052680x1.05x1.000000x1.000000x7.724%7.72%7.337%7.34%30-1.060004x-1.060004x1.06x1.000000x1.000000x13.651%13.7%12.879%12.9%31-1.063523x-1.063523x1.06x1.000000x1.000000x6.407%6.41%6.024%6.02%32-1.064491x-1.064491x1.06x1.000000x1.000000x3.778%3.78%3.549%3.55%33-1.092939x-1.092939x1.09x1.000000x1.000000x11.450%11.4%10.476%10.5%34-1.106734x-1.106734x1.11x1.000000x1.000000x8.152%8.15%7.366%7.37%35-1.109043x-1.109043x1.11x1.000000x1.000000x6.154%6.15%5.549%5.55%36-1.118002x-1.118002x1.12x1.000000x1.000000x5.261%5.26%4.705%4.71%37-1.121003x-1.121003x1.12x1.000000x1.000000x2.209%2.21%1.971%1.97%38-1.127409x-1.127409x1.13x1.000000x1.000000x5.637%5.64%5.000%5.00%39-1.137927x-1.137927x1.14x1.000000x1.000000x8.019%8.02%7.047%7.05%40-1.150185x-1.150185x1.15x1.000000x1.000000x3.224%3.22%2.803%2.80%41-1.159893x-1.159893x1.16x1.000000x1.000000x7.291%7.29%6.286%6.29%42-1.170896x-1.170896x1.17x1.000000x1.000000x5.763%5.76%4.922%4.92%43-1.209052x-1.209052x1.21x1.000000x1.000000x11.076%11.1%9.161%9.16%44-1.212019x-1.212019x1.21x1.000000x1.000000x2.263%2.26%1.867%1.87%45-1.236671x-1.236671x1.24x1.000000x1.000000x2.877%2.88%2.327%2.33%46-1.242432x-1.242432x1.24x1.000000x1.000000x2.550%2.55%2.053%2.05%47-1.253553x-1.253553x1.25x1.000000x1.000000x4.017%4.02%3.204%3.20%48-1.284305x-1.284305x1.28x1.000000x1.000000x4.851%4.85%3.777%3.78%49-1.669127x-1.669127x1.67x1.000000x1.000000x7.046%7.05%4.221%4.22%50
F percentage of females in category
M percentage of males in category
# rank of county subdivision out of 50 by male-to-female sex ratio

Over-Education Sex Ratio by County Subdivision#24

Percentage more likely men are than women to have a professional or doctorate degree (e.g., MBA, PhD, or MD) among people aged 25 years and older.
Scope: population of Dakota, selected other county subdivisions in Minnesota, and entities that contain Dakota
Female
Male
2x0x2xFM#WinonaWhite Bear LkTract 670800DakotaDakotaRosemountAndoverWinona AreaWinona AreaWinonaShoreviewMaple GroveOakdaleShakopeeEdinaFridleyEden PrairieOwatonnaMankatoHastingsRamseyMaplewoodMinnetonkaNew BrightonRochesterMoorheadWoodburyMidwestPlymouthZIP 55925West North CentralRosevilleRichfieldChaskaSt. CloudAustinCrystalUnited StatesCoon RapidsCottage GroveMinnesotaDuluthSt. Louis PkFaribaultInver Grv HtsEaganBrooklyn CtrSt. PaulPrior LakeFarmingtonSavageBrooklyn ParkLakevilleBlaineMinneapolisChamplinApple ValleyBurnsvilleBloomingtonChanhassenElk River-1.000000x-1.000000x3.549966x3.549966x3.55x1.887%1.89%6.698%6.70%1-1.000000x-1.000000x2.892036x2.892036x2.89x1.445%1.45%4.179%4.18%2-1.000000x-1.000000x2.676230x2.676230x2.68x3.331%3.33%8.914%8.91%-1.000000x-1.000000x2.657895x2.657895x2.66x0.990%0.99%2.632%2.63%-1.000000x-1.000000x2.657895x2.657895x2.66x0.990%0.99%2.632%2.63%-1.000000x-1.000000x2.517561x2.517561x2.52x1.236%1.24%3.112%3.11%3-1.000000x-1.000000x2.444960x2.444960x2.44x0.905%0.90%2.212%2.21%4-1.000000x-1.000000x2.378740x2.378740x2.38x2.089%2.09%4.970%4.97%-1.000000x-1.000000x2.216484x2.216484x2.22x1.916%1.92%4.247%4.25%-1.000000x-1.000000x2.216484x2.216484x2.22x1.916%1.92%4.247%4.25%-1.000000x-1.000000x2.158302x2.158302x2.16x4.894%4.89%10.562%10.6%5-1.000000x-1.000000x2.044267x2.044267x2.04x2.469%2.47%5.048%5.05%6-1.000000x-1.000000x2.027520x2.027520x2.03x1.214%1.21%2.461%2.46%7-1.000000x-1.000000x1.989459x1.989459x1.99x1.358%1.36%2.702%2.70%8-1.000000x-1.000000x1.952817x1.952817x1.95x7.877%7.88%15.382%15.4%9-1.000000x-1.000000x1.877228x1.877228x1.88x1.459%1.46%2.739%2.74%10-1.000000x-1.000000x1.843636x1.843636x1.84x4.554%4.55%8.396%8.40%11-1.000000x-1.000000x1.842122x1.842122x1.84x1.143%1.14%2.106%2.11%12-1.000000x-1.000000x1.831940x1.831940x1.83x2.992%2.99%5.480%5.48%13-1.000000x-1.000000x1.824245x1.824245x1.82x0.798%0.80%1.456%1.46%14-1.000000x-1.000000x1.818953x1.818953x1.82x1.219%1.22%2.218%2.22%15-1.000000x-1.000000x1.816195x1.816195x1.82x2.593%2.59%4.709%4.71%16-1.000000x-1.000000x1.778120x1.778120x1.78x5.399%5.40%9.600%9.60%17-1.000000x-1.000000x1.712068x1.712068x1.71x3.517%3.52%6.021%6.02%18-1.000000x-1.000000x1.656189x1.656189x1.66x6.670%6.67%11.046%11.0%19-1.000000x-1.000000x1.655114x1.655114x1.66x1.942%1.94%3.214%3.21%20-1.000000x-1.000000x1.596470x1.596470x1.60x5.629%5.63%8.987%8.99%21-1.000000x-1.000000x1.589934x1.589934x1.59x2.251%2.25%3.579%3.58%-1.000000x-1.000000x1.583257x1.583257x1.58x4.465%4.46%7.069%7.07%22-1.000000x-1.000000x1.578313x1.578313x1.58x0.763%0.76%1.205%1.20%-1.000000x-1.000000x1.572017x1.572017x1.57x2.329%2.33%3.662%3.66%-1.000000x-1.000000x1.559618x1.559618x1.56x5.912%5.91%9.220%9.22%23-1.000000x-1.000000x1.551084x1.551084x1.55x1.481%1.48%2.298%2.30%24-1.000000x-1.000000x1.548982x1.548982x1.55x2.267%2.27%3.511%3.51%25-1.000000x-1.000000x1.544665x1.544665x1.54x2.633%2.63%4.067%4.07%26-1.000000x-1.000000x1.544387x1.544387x1.54x2.283%2.28%3.525%3.53%27-1.000000x-1.000000x1.532997x1.532997x1.53x1.305%1.30%2.000%2.00%28-1.000000x-1.000000x1.526215x1.526215x1.53x2.660%2.66%4.060%4.06%-1.000000x-1.000000x1.506415x1.506415x1.51x1.028%1.03%1.548%1.55%29-1.000000x-1.000000x1.492523x1.492523x1.49x1.332%1.33%1.989%1.99%30-1.000000x-1.000000x1.481015x1.481015x1.48x2.798%2.80%4.144%4.14%-1.000000x-1.000000x1.465286x1.465286x1.47x3.496%3.50%5.123%5.12%31-1.000000x-1.000000x1.442441x1.442441x1.44x4.342%4.34%6.262%6.26%32-1.000000x-1.000000x1.419491x1.419491x1.42x1.234%1.23%1.752%1.75%33-1.000000x-1.000000x1.410631x1.410631x1.41x2.190%2.19%3.089%3.09%34-1.000000x-1.000000x1.383309x1.383309x1.38x3.713%3.71%5.137%5.14%35-1.000000x-1.000000x1.367180x1.367180x1.37x0.959%0.96%1.311%1.31%36-1.000000x-1.000000x1.274509x1.274509x1.27x5.228%5.23%6.663%6.66%37-1.000000x-1.000000x1.248780x1.248780x1.25x1.936%1.94%2.418%2.42%38-1.000000x-1.000000x1.247281x1.247281x1.25x1.347%1.35%1.681%1.68%39-1.000000x-1.000000x1.240291x1.240291x1.24x1.659%1.66%2.058%2.06%40-1.000000x-1.000000x1.220015x1.220015x1.22x1.515%1.52%1.848%1.85%41-1.000000x-1.000000x1.179960x1.179960x1.18x3.234%3.23%3.816%3.82%42-1.000000x-1.000000x1.160580x1.160580x1.16x2.321%2.32%2.693%2.69%43-1.000000x-1.000000x1.124528x1.124528x1.12x5.872%5.87%6.603%6.60%44-1.000000x-1.000000x1.068161x1.068161x1.07x3.397%3.40%3.629%3.63%45-1.000000x-1.000000x1.031011x1.031011x1.03x2.916%2.92%3.006%3.01%46-1.000000x-1.000000x1.023622x1.023622x1.02x2.379%2.38%2.435%2.44%47-1.000000x-1.000000x1.018945x1.018945x1.02x3.110%3.11%3.169%3.17%48-1.019385x-1.019385x1.02x1.000000x1.000000x3.889%3.89%3.815%3.81%49-2.497130x-2.497130x2.50x1.000000x1.000000x1.828%1.83%0.732%0.73%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 Dakota to the 50 most populous county subdivisions in the Midwest and to those entities that contain or substantially overlap with Dakota. The least populous of the compared county subdivisions has a population of 112,821.

No H.S. Diploma by County Subdivision#25

Percent of population 25 years of age and older without a high school diploma (or equivalent).
Scope: population of Dakota, selected other county subdivisions in the Midwest, and entities that contain Dakota
0%10%20%30%Count#Aurora TownshipAuroraCenter TownshipCtrKansas CityClevelandWayne TownshipWayneDetroitMilwaukeeNorth TownshipNDaytonChicagoProviso TownshipProvisoRockford TownshipRockfordSt. LouisWarrenGrand RapidsToledoBlue TownshipCincinnatiAkronSt. PaulSterling HeightsSterling HtsUnited States of AmericaUnited StatesThornton TownshipThorntonWichitaKaw TownshipOmahaBloomingdale TownshipBloomingdaleColumbusMaine TownshipMaineTopekaMinneapolisSpringfield TownshipSpringfieldWorth TownshipWorthMidwestLawrence TownshipLawrenceSioux FallsWest North CentralZIP Code 55925ZIP 55925Capital TownshipCapitalWheeling TownshipWheelingPalatine TownshipPalatineSchaumburg TownshipSchaumburgWinona Metro AreaWinona AreaWinona CountyWinonaDakotaDakotaWinona Area Public School DistrictWinona AreaMinnesotaLincolnWashington TownshipWashingtonOlatheFargoCedar RapidsYork Township670800Tract 670800Milton TownshipMiltonMadisonDowners Grove TownshipDowners GrvLisle TownshipLisleOverland ParkAnn Arbor33.464284%33.464284%33.5%29,81429.8k123.165532%23.165532%23.2%22,92622.9k222.659362%22.659362%22.7%21,21821.2k321.582420%21.582420%21.6%54,98155.0k421.037720%21.037720%21.0%18,48918.5k521.003600%21.003600%21.0%90,67890.7k617.485105%17.485105%17.5%63,80063.8k717.062713%17.062713%17.1%17,39117.4k816.928359%16.928359%16.9%14,88914.9k916.905373%16.905373%16.9%309,770310k1015.636222%15.636222%15.6%16,11016.1k1115.608074%15.608074%15.6%18,24118.2k1215.466266%15.466266%15.5%33,80433.8k1315.286174%15.286174%15.3%14,05914.1k1414.563179%14.563179%14.6%17,64317.6k1514.332972%14.332972%14.3%26,34326.3k1614.241047%14.241047%14.2%15,25815.3k1713.761583%13.761583%13.8%26,28626.3k1813.591726%13.591726%13.6%17,95118.0k1913.278342%13.278342%13.3%24,61324.6k2013.132171%13.132171%13.1%12,21212.2k2113.020590%13.020590%13.0%27,818,38027.8M12.974232%12.974232%13.0%14,37014.4k2212.568464%12.568464%12.6%31,23131.2k2312.455744%12.455744%12.5%15,16315.2k2412.198899%12.198899%12.2%35,05035.1k2512.171847%12.171847%12.2%9,3752611.376979%11.376979%11.4%60,83160.8k2711.132206%11.132206%11.1%10,96511.0k2811.032803%11.032803%11.0%9,3772910.958428%10.958428%11.0%29,34729.3k3010.767091%10.767091%10.8%11,14911.1k3110.678962%10.678962%10.7%11,17511.2k3210.244520%10.244520%10.2%4,641,8354.64M10.179618%10.179618%10.2%8,161339.702326%9.702326%9.7%9,123349.174633%9.174633%9.2%1,278,0511.28M8.910891%8.910891%8.9%728.623103%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%7,226387.495972%7.495972%7.5%2,3267.495972%7.495972%7.5%2,3267.441860%7.441860%7.4%167.441860%7.441860%7.4%167.391159%7.391159%7.4%1,7697.376055%7.376055%7.4%270,121270k7.092309%7.092309%7.1%11,88611.9k396.804680%6.804680%6.8%6,403406.424130%6.424130%6.4%5,331416.055621%6.055621%6.1%4,270425.981653%5.981653%6.0%5,099435.461095%5.461095%5.5%4,715445.293222%5.293222%5.3%2785.266517%5.266517%5.3%4,126454.836248%4.836248%4.8%7,351464.020265%4.020265%4.0%4,166473.522812%3.522812%3.5%2,870483.377424%3.377424%3.4%4,282493.157717%3.157717%3.2%2,05750
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older without a high school diploma (or equivalent).

Bachelor's Degrees by County Subdivision#26

Percent of population 25 years of age and older with a bachelor's degree or higher..
Scope: population of Dakota, selected other county subdivisions in the Midwest, and entities that contain Dakota
0%20%40%60%Count#Ann ArborOverland ParkMilton TownshipMiltonLisle TownshipLisleMadisonDowners Grove TownshipDowners GrvWashington TownshipWashingtonPalatine TownshipPalatineYork TownshipMinneapolisOlatheWheeling TownshipWheelingSchaumburg TownshipSchaumburgKaw TownshipSt. PaulMaine TownshipMaineFargoLincolnLawrence TownshipLawrenceChicagoCapital TownshipCapital670800Tract 670800ColumbusOmahaMinnesotaCincinnatiSt. LouisGrand RapidsBloomingdale TownshipBloomingdaleCedar RapidsWinona Area Public School DistrictWinona AreaUnited States of AmericaUnited StatesSioux FallsWest North CentralWinona Metro AreaWinona AreaWinona CountyWinonaMidwestWichitaSterling HeightsSterling HtsTopekaSpringfield TownshipSpringfieldProviso TownshipProvisoWorth TownshipWorthMilwaukeeRockford TownshipRockfordAkronCenter TownshipCtrNorth TownshipNZIP Code 55925ZIP 55925Thornton TownshipThorntonToledoDaytonWarrenWayne TownshipWayneDakotaDakotaKansas CityClevelandAurora TownshipAuroraBlue TownshipDetroit72.810169%72.810169%72.8%47,43047.4k158.823344%58.823344%58.8%74,57874.6k257.681507%57.681507%57.7%45,19045.2k356.900171%56.900171%56.9%46,35646.4k456.337583%56.337583%56.3%85,63285.6k553.762123%53.762123%53.8%55,71155.7k650.610540%50.610540%50.6%47,62347.6k749.860853%49.860853%49.9%39,77539.8k849.728972%49.728972%49.7%42,93542.9k947.670489%47.670489%47.7%127,663128k1046.512581%46.512581%46.5%38,59838.6k1146.409378%46.409378%46.4%51,46851.5k1241.792515%41.792515%41.8%39,02039.0k1341.581304%41.581304%41.6%50,61950.6k1439.969357%39.969357%40.0%74,08874.1k1539.511462%39.511462%39.5%38,91838.9k1638.241175%38.241175%38.2%26,96527.0k1737.146608%37.146608%37.1%62,25462.3k1836.577273%36.577273%36.6%29,32429.3k1936.546320%36.546320%36.5%669,666670k2036.298510%36.298510%36.3%28,78028.8k2134.729627%34.729627%34.7%1,82434.685843%34.685843%34.7%185,460185k2234.651487%34.651487%34.7%99,56199.6k2334.240609%34.240609%34.2%1,253,9371.25M33.783048%33.783048%33.8%64,52964.5k2433.007421%33.007421%33.0%72,14372.1k2532.904381%32.904381%32.9%39,86339.9k2632.623147%32.623147%32.6%25,12725.1k2731.793440%31.793440%31.8%27,10227.1k2830.914181%30.914181%30.9%7,39930.315023%30.315023%30.3%64,767,78764.8M30.259813%30.259813%30.3%28,45328.5k2930.056536%30.056536%30.1%4,186,9564.19M29.278118%29.278118%29.3%9,08529.278118%29.278118%29.3%9,08528.952816%28.952816%29.0%13,118,64213.1M28.877567%28.877567%28.9%71,75771.8k3027.532180%27.532180%27.5%25,60325.6k3127.007248%27.007248%27.0%22,95423.0k3226.964567%26.964567%27.0%27,92127.9k3326.237989%26.237989%26.2%27,03327.0k3425.217641%25.217641%25.2%26,38926.4k3523.517740%23.517740%23.5%85,81285.8k3621.592552%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%20,02920.0k4019.183168%19.183168%19.2%15518.971090%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%14,78814.8k4516.279070%16.279070%16.3%3516.279070%16.279070%16.3%3516.167409%16.167409%16.2%15,13915.1k4616.073076%16.073076%16.1%40,94640.9k4715.929601%15.929601%15.9%14,19214.2k4815.821208%15.821208%15.8%16,95117.0k4913.833543%13.833543%13.8%59,72359.7k50
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older with a bachelor's degree or higher..

Very Advanced Degrees by County Subdivision#27

Percent of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).
Scope: population of Dakota, selected other county subdivisions in the Midwest, and entities that contain Dakota
0%5%10%15%Count#Ann ArborMadisonDowners Grove TownshipDowners GrvWashington TownshipWashingtonMinneapolisYork Township670800Tract 670800Overland ParkLisle TownshipLisleSt. PaulKaw TownshipMilton TownshipMiltonSt. LouisCincinnatiLincolnChicagoFargoCapital TownshipCapitalOmahaMaine TownshipMaineWinona Area Public School DistrictWinona AreaPalatine TownshipPalatineMinnesotaWheeling TownshipWheelingColumbusUnited States of AmericaUnited StatesTopekaGrand RapidsLawrence TownshipLawrenceWinona Metro AreaWinona AreaWinona CountyWinonaWest North CentralSpringfield TownshipSpringfieldCedar RapidsMidwestSioux FallsOlatheCenter TownshipCtrSchaumburg TownshipSchaumburgWichitaProviso TownshipProvisoAkronBloomingdale TownshipBloomingdaleRockford TownshipRockfordMilwaukeeWorth TownshipWorthClevelandDakotaDakotaToledoNorth TownshipNSterling HeightsSterling HtsKansas CityDetroitDaytonWayne TownshipWayneWarrenBlue TownshipZIP Code 55925ZIP 55925Aurora 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%5,35166.169078%6.169078%6.2%3245.940071%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%3,970193.518008%3.518008%3.5%8423.487439%3.487439%3.5%2,782203.458748%3.458748%3.5%126,664127k3.407574%3.407574%3.4%3,779213.357865%3.357865%3.4%17,95418.0k223.336158%3.336158%3.3%7,127,6737.13M3.233245%3.233245%3.2%2,748233.174629%3.174629%3.2%3,846243.083448%3.083448%3.1%2,472253.074444%3.074444%3.1%9543.074444%3.074444%3.1%9542.978981%2.978981%3.0%414,980415k2.911721%2.911721%2.9%3,015262.905776%2.905776%2.9%2,477272.893416%2.893416%2.9%1,311,0191.31M2.841677%2.841677%2.8%2,672282.830666%2.830666%2.8%2,349292.602914%2.602914%2.6%2,576302.551250%2.551250%2.6%2,382312.519246%2.519246%2.5%6,260322.213918%2.213918%2.2%2,281332.163955%2.163955%2.2%2,858342.113682%2.113682%2.1%1,628352.067272%2.067272%2.1%2,416362.043126%2.043126%2.0%7,455371.958049%1.958049%2.0%2,049381.927780%1.927780%1.9%4,911391.860465%1.860465%1.9%41.860465%1.860465%1.9%41.642065%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%1,069480.990099%0.990099%1.0%80.936111%0.936111%0.9%834490.876686%0.876686%0.9%97150
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).

Under-Education Sex Ratio by County Subdivision#28

Percentage more likely men are than women to not have a high school diploma (or equivalent) among people aged 25 years and older.
Scope: population of Dakota, selected other county subdivisions in the Midwest, and entities that contain Dakota
Female
Male
1x0x1xFM#DakotaDakotaZIP 55925Tract 670800Cedar RapidsLincolnDetroitOmahaToledoWinona AreaWinonaThorntonKansas CityMadisonLawrenceFargoProvisoRockfordBlue TownshipWest North CentralMinnesotaWayneMidwestTopekaMilwaukeeKaw TownshipDaytonSioux FallsUnited StatesWinona AreaOlatheWorthNOverland ParkAuroraWheelingGrand RapidsSchaumburgChicagoWichitaColumbusClevelandPalatineCapitalWarrenSpringfieldYork TownshipSt. LouisWashingtonBloomingdaleCtrCincinnatiAkronAnn ArborSt. PaulLisleMinneapolisSterling HtsDowners GrvMiltonMaine-1.000000x-1.000000x1.949123x1.949123x1.95x4.950%4.95%9.649%9.65%-1.000000x-1.000000x1.949123x1.949123x1.95x4.950%4.95%9.649%9.65%-1.000000x-1.000000x1.675440x1.675440x1.68x6.616%6.62%11.084%11.1%-1.000000x-1.000000x1.292097x1.292097x1.29x4.609%4.61%5.955%5.96%-1.000000x-1.000000x1.243824x1.243824x1.24x5.354%5.35%6.660%6.66%1-1.000000x-1.000000x1.238529x1.238529x1.24x6.342%6.34%7.854%7.85%2-1.000000x-1.000000x1.237056x1.237056x1.24x18.951%19.0%23.443%23.4%3-1.000000x-1.000000x1.230289x1.230289x1.23x10.968%11.0%13.494%13.5%4-1.000000x-1.000000x1.227011x1.227011x1.23x12.945%12.9%15.884%15.9%5-1.000000x-1.000000x1.208433x1.208433x1.21x6.792%6.79%8.208%8.21%-1.000000x-1.000000x1.208433x1.208433x1.21x6.792%6.79%8.208%8.21%-1.000000x-1.000000x1.203250x1.203250x1.20x11.909%11.9%14.330%14.3%6-1.000000x-1.000000x1.189752x1.189752x1.19x20.748%20.7%24.685%24.7%7-1.000000x-1.000000x1.189278x1.189278x1.19x4.425%4.43%5.263%5.26%8-1.000000x-1.000000x1.181964x1.181964x1.18x9.406%9.41%11.117%11.1%9-1.000000x-1.000000x1.176963x1.176963x1.18x5.565%5.56%6.550%6.55%10-1.000000x-1.000000x1.174964x1.174964x1.17x14.460%14.5%16.990%17.0%11-1.000000x-1.000000x1.168755x1.168755x1.17x14.456%14.5%16.896%16.9%12-1.000000x-1.000000x1.161774x1.161774x1.16x13.244%13.2%15.387%15.4%13-1.000000x-1.000000x1.137506x1.137506x1.14x8.598%8.60%9.780%9.78%-1.000000x-1.000000x1.136388x1.136388x1.14x6.913%6.91%7.856%7.86%-1.000000x-1.000000x1.132245x1.132245x1.13x19.779%19.8%22.395%22.4%14-1.000000x-1.000000x1.127915x1.127915x1.13x9.647%9.65%10.881%10.9%-1.000000x-1.000000x1.125507x1.125507x1.13x10.423%10.4%11.732%11.7%15-1.000000x-1.000000x1.123984x1.123984x1.12x16.526%16.5%18.574%18.6%16-1.000000x-1.000000x1.115695x1.115695x1.12x11.779%11.8%13.142%13.1%17-1.000000x-1.000000x1.114342x1.114342x1.11x16.070%16.1%17.907%17.9%18-1.000000x-1.000000x1.110589x1.110589x1.11x9.201%9.20%10.219%10.2%19-1.000000x-1.000000x1.109070x1.109070x1.11x12.369%12.4%13.719%13.7%-1.000000x-1.000000x1.108477x1.108477x1.11x7.014%7.01%7.775%7.77%-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#29

Percentage more likely men are than women to have a professional or doctorate degree (e.g., MBA, PhD, or MD) among people aged 25 years and older.
Scope: population of Dakota, selected other county subdivisions in the Midwest, and entities that contain Dakota
Female
Male
1x0x1x2xFM#Tract 670800DakotaDakotaWinona AreaWinona AreaWinonaRockfordNDaytonSioux FallsCapitalLawrenceDowners GrvAkronLisleWichitaYork TownshipMaineWarrenWheelingBlue TownshipSpringfieldOverland ParkMiltonGrand RapidsOlatheOmahaFargoWashingtonLincolnMidwestBloomingdaleZIP 55925West North CentralKansas CityAuroraUnited StatesAnn ArborTopekaMinnesotaSterling HtsPalatineSchaumburgColumbusMadisonKaw TownshipMilwaukeeCedar RapidsClevelandCincinnatiSt. PaulSt. LouisChicagoWayneCtrToledoMinneapolisWorthDetroitProvisoThornton-1.000000x-1.000000x2.676230x2.676230x2.68x3.331%3.33%8.914%8.91%-1.000000x-1.000000x2.657895x2.657895x2.66x0.990%0.99%2.632%2.63%-1.000000x-1.000000x2.657895x2.657895x2.66x0.990%0.99%2.632%2.63%-1.000000x-1.000000x2.378740x2.378740x2.38x2.089%2.09%4.970%4.97%-1.000000x-1.000000x2.216484x2.216484x2.22x1.916%1.92%4.247%4.25%-1.000000x-1.000000x2.216484x2.216484x2.22x1.916%1.92%4.247%4.25%-1.000000x-1.000000x2.117268x2.117268x2.12x1.353%1.35%2.866%2.87%1-1.000000x-1.000000x2.111054x2.111054x2.11x1.033%1.03%2.181%2.18%2-1.000000x-1.000000x1.989047x1.989047x1.99x0.860%0.86%1.711%1.71%3-1.000000x-1.000000x1.962539x1.962539x1.96x1.928%1.93%3.783%3.78%4-1.000000x-1.000000x1.901348x1.901348x1.90x2.990%2.99%5.686%5.69%5-1.000000x-1.000000x1.879271x1.879271x1.88x2.206%2.21%4.146%4.15%6-1.000000x-1.000000x1.852471x1.852471x1.85x5.456%5.46%10.107%10.1%7-1.000000x-1.000000x1.846298x1.846298x1.85x1.550%1.55%2.862%2.86%8-1.000000x-1.000000x1.815266x1.815266x1.82x4.271%4.27%7.754%7.75%9-1.000000x-1.000000x1.792728x1.792728x1.79x1.819%1.82%3.261%3.26%10-1.000000x-1.000000x1.792314x1.792314x1.79x4.498%4.50%8.062%8.06%11-1.000000x-1.000000x1.788417x1.788417x1.79x2.939%2.94%5.256%5.26%12-1.000000x-1.000000x1.768853x1.768853x1.77x0.769%0.77%1.361%1.36%13-1.000000x-1.000000x1.766097x1.766097x1.77x2.485%2.48%4.389%4.39%14-1.000000x-1.000000x1.761699x1.761699x1.76x0.737%0.74%1.298%1.30%15-1.000000x-1.000000x1.751445x1.751445x1.75x2.146%2.15%3.759%3.76%16-1.000000x-1.000000x1.732234x1.732234x1.73x4.415%4.41%7.647%7.65%17-1.000000x-1.000000x1.695067x1.695067x1.70x4.357%4.36%7.385%7.38%18-1.000000x-1.000000x1.689013x1.689013x1.69x2.382%2.38%4.023%4.02%19-1.000000x-1.000000x1.678153x1.678153x1.68x2.131%2.13%3.576%3.58%20-1.000000x-1.000000x1.669388x1.669388x1.67x3.061%3.06%5.110%5.11%21-1.000000x-1.000000x1.627456x1.627456x1.63x3.304%3.30%5.377%5.38%22-1.000000x-1.000000x1.610803x1.610803x1.61x5.701%5.70%9.183%9.18%23-1.000000x-1.000000x1.596978x1.596978x1.60x3.524%3.52%5.628%5.63%24-1.000000x-1.000000x1.589934x1.589934x1.59x2.251%2.25%3.579%3.58%-1.000000x-1.000000x1.586045x1.586045x1.59x1.649%1.65%2.616%2.62%25-1.000000x-1.000000x1.578313x1.578313x1.58x0.763%0.76%1.205%1.20%-1.000000x-1.000000x1.572017x1.572017x1.57x2.329%2.33%3.662%3.66%-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-1.000000x1.481015x1.481015x1.48x2.798%2.80%4.144%4.14%-1.000000x-1.000000x1.476996x1.476996x1.48x1.170%1.17%1.728%1.73%30-1.000000x-1.000000x1.457167x1.457167x1.46x2.851%2.85%4.154%4.15%31-1.000000x-1.000000x1.436165x1.436165x1.44x2.115%2.11%3.037%3.04%32-1.000000x-1.000000x1.413654x1.413654x1.41x2.801%2.80%3.959%3.96%33-1.000000x-1.000000x1.387878x1.387878x1.39x7.705%7.70%10.693%10.7%34-1.000000x-1.000000x1.373250x1.373250x1.37x4.975%4.97%6.832%6.83%35-1.000000x-1.000000x1.368590x1.368590x1.37x1.742%1.74%2.385%2.38%36-1.000000x-1.000000x1.346658x1.346658x1.35x2.491%2.49%3.354%3.35%37-1.000000x-1.000000x1.286599x1.286599x1.29x1.699%1.70%2.186%2.19%38-1.000000x-1.000000x1.280610x1.280610x1.28x4.179%4.18%5.351%5.35%39-1.000000x-1.000000x1.274509x1.274509x1.27x5.228%5.23%6.663%6.66%40-1.000000x-1.000000x1.273345x1.273345x1.27x4.319%4.32%5.500%5.50%41-1.000000x-1.000000x1.238186x1.238186x1.24x4.026%4.03%4.985%4.99%42-1.000000x-1.000000x1.223931x1.223931x1.22x1.068%1.07%1.307%1.31%43-1.000000x-1.000000x1.213574x1.213574x1.21x2.357%2.36%2.860%2.86%44-1.000000x-1.000000x1.141406x1.141406x1.14x1.539%1.54%1.757%1.76%45-1.000000x-1.000000x1.124528x1.124528x1.12x5.872%5.87%6.603%6.60%46-1.000000x-1.000000x1.084697x1.084697x1.08x1.883%1.88%2.042%2.04%47-1.000000x-1.000000x1.046557x1.046557x1.05x1.291%1.29%1.351%1.35%48-1.000000x-1.000000x1.042857x1.042857x1.04x2.171%2.17%2.264%2.26%49-1.706858x-1.706858x1.71x1.000000x1.000000x1.072%1.07%0.628%0.63%50
F percentage of females in category
M percentage of males in category
# rank of county subdivision out of 50 by male-to-female sex ratio

Educational Attainment by County Subdivision in the United States

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

No H.S. Diploma by County Subdivision#30

Percent of population 25 years of age and older without a high school diploma (or equivalent).
Scope: population of Dakota, selected other county subdivisions in the United States, and entities that contain Dakota
0%10%20%Count#San Antonio CentralSan Antonio CntrlBronxSan BernardinoLos AngelesSouthwest DallasSW DallasEl PasoAnaheim-Santa Ana-Garden GroveAnaheim-Santa An…FresnoHoustonMiamiDetroitNortheast DallasNE DallasEast San Gabriel ValleyE San Gabriel VlyFort WorthBrooklynLong Beach-LakewoodLong Bch-LakewoodQueensSan Fernando ValleySan Fernando VlyMilwaukeePhiladelphiaOntarioChicagoBaltimoreOceanside-EscondidoOceanside-Escond…Las VegasPhoenixBostonSacramentoOrlandoAustinDenverUnited States of AmericaUnited StatesManhattanSan DiegoTampaSan JoseSan FranciscoTucsonAlbuquerqueTownship 1:Charlotte1, CharlotteColumbusTulsaSalt Lake CitySalt Lk CityTown of HempsteadHempsteadMidwestNorthwest HarrisNW HarrisWashingtonAtlantaWest North CentralZIP Code 55925ZIP 55925SeattleNortheast TarrantNE TarrantWinona Metro AreaWinona AreaWinona CountyWinonaDakotaDakotaWinona Area Public School DistrictWinona AreaMinnesotaPlano670800Tract 670800Seattle East28.998944%28.998944%29.0%126,922127k128.837398%28.837398%28.8%261,022261k227.582802%27.582802%27.6%135,754136k324.837401%24.837401%24.8%434,160434k423.987048%23.987048%24.0%141,940142k523.756417%23.756417%23.8%81,30881.3k622.645542%22.645542%22.6%248,699249k722.107626%22.107626%22.1%92,47292.5k821.922900%21.922900%21.9%457,347457k921.818150%21.818150%21.8%149,688150k1021.003600%21.003600%21.0%90,67890.7k1120.783651%20.783651%20.8%207,494207k1220.461493%20.461493%20.5%128,038128k1320.041576%20.041576%20.0%106,726107k1420.017506%20.017506%20.0%351,046351k1519.402518%19.402518%19.4%73,10573.1k1619.344706%19.344706%19.3%315,505316k1719.344408%19.344408%19.3%244,983245k1817.485105%17.485105%17.5%63,80063.8k1917.390838%17.390838%17.4%180,039180k2017.129346%17.129346%17.1%71,39771.4k2116.905373%16.905373%16.9%309,770310k2216.548703%16.548703%16.5%69,83969.8k2315.999398%15.999398%16.0%70,21470.2k2415.906523%15.906523%15.9%198,651199k2514.952077%14.952077%15.0%308,569309k2614.325556%14.325556%14.3%63,64263.6k2713.900512%13.900512%13.9%103,047103k2813.679368%13.679368%13.7%53,75853.8k2913.668915%13.668915%13.7%78,23878.2k3013.638703%13.638703%13.6%63,86563.9k3113.020590%13.020590%13.0%27,818,38027.8M12.996284%12.996284%13.0%160,845161k3212.985760%12.985760%13.0%206,792207k3312.979618%12.979618%13.0%57,75857.8k3412.789590%12.789590%12.8%153,604154k3512.559735%12.559735%12.6%84,02484.0k3612.262851%12.262851%12.3%70,40970.4k3712.089143%12.089143%12.1%52,21752.2k3811.553484%11.553484%11.6%61,37861.4k3911.376979%11.376979%11.4%60,83160.8k4011.299086%11.299086%11.3%43,65343.7k4110.435356%10.435356%10.4%64,29464.3k4210.384134%10.384134%10.4%54,23054.2k4310.244520%10.244520%10.2%4,641,8354.64M10.135583%10.135583%10.1%47,67947.7k4410.045421%10.045421%10.0%46,51046.5k459.538552%9.538552%9.5%37,37337.4k469.174633%9.174633%9.2%1,278,0511.28M8.910891%8.910891%8.9%728.833573%8.833573%8.8%66,22066.2k478.418271%8.418271%8.4%31,44331.4k487.495972%7.495972%7.5%2,3267.495972%7.495972%7.5%2,3267.441860%7.441860%7.4%167.441860%7.441860%7.4%167.391159%7.391159%7.4%1,7697.376055%7.376055%7.4%270,121270k5.714681%5.714681%5.7%20,64420.6k495.293222%5.293222%5.3%2784.913852%4.913852%4.9%20,32620.3k50
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older without a high school diploma (or equivalent).

Bachelor's Degrees by County Subdivision#31

Percent of population 25 years of age and older with a bachelor's degree or higher..
Scope: population of Dakota, selected other county subdivisions in the United States, and entities that contain Dakota
0%20%40%60%Count#ManhattanSeattle EastWashingtonSan FranciscoPlanoSan JoseAtlantaSeattleBostonDenverAustinTownship 1:Charlotte1, CharlotteTown of HempsteadHempsteadSan DiegoNortheast TarrantNE TarrantNorthwest HarrisNW HarrisChicago670800Tract 670800ColumbusLos AngelesMinnesotaBrooklynSan Fernando ValleySan Fernando VlyNortheast DallasNE DallasSalt Lake CitySalt Lk CityAlbuquerqueTampaTucsonOceanside-EscondidoOceanside-Escond…TulsaWinona Area Public School DistrictWinona AreaQueensUnited States of AmericaUnited StatesHoustonWest North CentralBaltimoreWinona Metro AreaWinona AreaWinona CountyWinonaLong Beach-LakewoodLong Bch-LakewoodMidwestPhoenixOrlandoAnaheim-Santa Ana-Garden GroveAnaheim-Santa An…SacramentoEast San Gabriel ValleyE San Gabriel VlyOntarioPhiladelphiaMiamiFort WorthSouthwest DallasSW DallasMilwaukeeFresnoLas VegasEl PasoZIP Code 55925ZIP 55925BronxSan BernardinoDakotaDakotaSan Antonio CentralSan Antonio CntrlDetroit60.434640%60.434640%60.4%747,953748k157.691220%57.691220%57.7%238,638239k255.360186%55.360186%55.4%256,316256k354.793235%54.793235%54.8%366,564367k454.142756%54.142756%54.1%195,588196k549.985845%49.985845%50.0%600,334600k649.803731%49.803731%49.8%195,136195k749.626221%49.626221%49.6%372,018372k846.377869%46.377869%46.4%206,036206k945.718966%45.718966%45.7%214,085214k1044.843364%44.843364%44.8%256,674257k1141.989192%41.989192%42.0%223,068223k1238.767308%38.767308%38.8%202,458202k1338.701072%38.701072%38.7%616,296616k1438.547398%38.547398%38.5%143,978144k1536.877886%36.877886%36.9%173,478173k1636.546320%36.546320%36.5%669,666670k1734.729627%34.729627%34.7%1,82434.685843%34.685843%34.7%185,460185k1834.593243%34.593243%34.6%604,693605k1934.240609%34.240609%34.2%1,253,9371.25M34.081468%34.081468%34.1%597,685598k2033.231104%33.231104%33.2%420,848421k2133.191099%33.191099%33.2%331,364331k2233.118385%33.118385%33.1%204,048204k2332.636312%32.636312%32.6%140,967141k2432.512191%32.512191%32.5%144,676145k2532.087814%32.087814%32.1%184,237184k2631.198303%31.198303%31.2%136,915137k2731.110082%31.110082%31.1%120,191120k2830.914181%30.914181%30.9%7,39930.595789%30.595789%30.6%499,006499k2930.315023%30.315023%30.3%64,767,78764.8M30.080133%30.080133%30.1%627,520628k3030.056536%30.056536%30.1%4,186,9564.19M29.719611%29.719611%29.7%125,423125k3129.278118%29.278118%29.3%9,08529.278118%29.278118%29.3%9,08529.113198%29.113198%29.1%109,693110k3228.952816%28.952816%29.0%13,118,64213.1M28.760152%28.760152%28.8%593,529594k3328.535877%28.535877%28.5%112,142112k3428.412939%28.412939%28.4%312,038312k3528.231204%28.231204%28.2%209,283209k3627.276345%27.276345%27.3%170,682171k3726.758411%26.758411%26.8%111,532112k3826.349720%26.349720%26.3%272,786273k3926.011156%26.011156%26.0%178,455178k4024.665414%24.665414%24.7%131,349131k4123.764821%23.764821%23.8%140,625141k4223.517740%23.517740%23.5%85,81285.8k4322.486319%22.486319%22.5%94,05694.1k4421.702666%21.702666%21.7%271,037271k4521.071885%21.071885%21.1%72,12072.1k4619.183168%19.183168%19.2%15519.131504%19.131504%19.1%173,169173k4716.375473%16.375473%16.4%80,59580.6k4816.279070%16.279070%16.3%3516.279070%16.279070%16.3%3514.929012%14.929012%14.9%65,34165.3k4913.833543%13.833543%13.8%59,72359.7k50
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older with a bachelor's degree or higher..

Very Advanced Degrees by County Subdivision#32

Percent of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).
Scope: population of Dakota, selected other county subdivisions in the United States, and entities that contain Dakota
0%5%10%Count#WashingtonManhattanSan FranciscoBostonAtlantaSeattleSan Jose670800Tract 670800Seattle EastDenverSan DiegoAustinBaltimoreLos AngelesAlbuquerquePlanoChicagoTucsonTown of HempsteadHempsteadTampaMiamiNortheast DallasNE DallasSalt Lake CitySalt Lk CityHoustonPhiladelphiaSan Fernando ValleySan Fernando VlyWinona Area Public School DistrictWinona AreaTownship 1:Charlotte1, CharlotteOceanside-EscondidoOceanside-Escond…MinnesotaBrooklynSacramentoColumbusUnited States of AmericaUnited StatesTulsaWinona Metro AreaWinona AreaWinona CountyWinonaPhoenixLong Beach-LakewoodLong Bch-LakewoodWest North CentralMidwestOrlandoFresnoAnaheim-Santa Ana-Garden GroveAnaheim-Santa An…QueensNorthwest HarrisNW HarrisNortheast TarrantNE TarrantEast San Gabriel ValleyE San Gabriel VlyOntarioFort WorthLas VegasMilwaukeeDakotaDakotaSan BernardinoSan Antonio CentralSan Antonio CntrlEl PasoSouthwest DallasSW DallasBronxDetroitZIP Code 55925ZIP 5592512.461852%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%75,13475.1k76.169078%6.169078%6.2%3246.036065%6.036065%6.0%24,96825.0k85.725842%5.725842%5.7%26,81226.8k95.247128%5.247128%5.2%83,55883.6k105.058711%5.058711%5.1%28,95529.0k114.934352%4.934352%4.9%20,82420.8k124.659072%4.659072%4.7%81,44181.4k134.631274%4.631274%4.6%20,00420.0k144.617088%4.617088%4.6%16,67916.7k154.485379%4.485379%4.5%82,18982.2k164.461087%4.461087%4.5%25,61425.6k174.441262%4.441262%4.4%23,19423.2k184.325266%4.325266%4.3%19,24719.2k194.025531%4.025531%4.0%27,61827.6k203.827408%3.827408%3.8%38,21138.2k213.792624%3.792624%3.8%23,36723.4k223.737871%3.737871%3.7%77,97878.0k233.720350%3.720350%3.7%38,51538.5k243.601468%3.601468%3.6%45,61045.6k253.518008%3.518008%3.5%8423.490252%3.490252%3.5%18,54218.5k263.466073%3.466073%3.5%15,21115.2k273.458748%3.458748%3.5%126,664127k3.384967%3.384967%3.4%59,36259.4k283.380196%3.380196%3.4%25,05825.1k293.357865%3.357865%3.4%17,95418.0k303.336158%3.336158%3.3%7,127,6737.13M3.140490%3.140490%3.1%12,13312.1k313.074444%3.074444%3.1%9543.074444%3.074444%3.1%9543.010825%3.010825%3.0%62,13562.1k323.009440%3.009440%3.0%11,33911.3k332.978981%2.978981%3.0%414,980415k2.893416%2.893416%2.9%1,311,0191.31M2.893233%2.893233%2.9%11,37011.4k342.828959%2.828959%2.8%11,83311.8k352.763004%2.763004%2.8%30,34430.3k362.756960%2.756960%2.8%44,96545.0k372.682967%2.682967%2.7%12,62112.6k382.630994%2.630994%2.6%9,827392.484535%2.484535%2.5%15,54715.5k402.324315%2.324315%2.3%9,688412.173239%2.173239%2.2%11,57311.6k422.155077%2.155077%2.2%26,91426.9k432.043126%2.043126%2.0%7,455441.860465%1.860465%1.9%41.860465%1.860465%1.9%41.807306%1.807306%1.8%8,895451.792414%1.792414%1.8%7,845461.745764%1.745764%1.7%5,975471.704476%1.704476%1.7%10,08610.1k481.664253%1.664253%1.7%15,06415.1k491.318660%1.318660%1.3%5,693500.990099%0.990099%1.0%8
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).

Under-Education Sex Ratio by County Subdivision#33

Percentage more likely men are than women to not have a high school diploma (or equivalent) among people aged 25 years and older.
Scope: population of Dakota, selected other county subdivisions in the United States, and entities that contain Dakota
Female
Male
1x0x1xFM#DakotaDakotaZIP 55925Tract 6708001, CharlotteDetroitWinona AreaWinonaBaltimoreTulsaSW DallasWest North CentralMinnesotaMidwestFresnoMilwaukeeUnited StatesWinona AreaNE 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-1.000000x1.949123x1.949123x1.95x4.950%4.95%9.649%9.65%-1.000000x-1.000000x1.949123x1.949123x1.95x4.950%4.95%9.649%9.65%-1.000000x-1.000000x1.675440x1.675440x1.68x6.616%6.62%11.084%11.1%-1.000000x-1.000000x1.292097x1.292097x1.29x4.609%4.61%5.955%5.96%-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-1.000000x1.208433x1.208433x1.21x6.792%6.79%8.208%8.21%-1.000000x-1.000000x1.208433x1.208433x1.21x6.792%6.79%8.208%8.21%-1.000000x-1.000000x1.179669x1.179669x1.18x15.289%15.3%18.036%18.0%3-1.000000x-1.000000x1.177766x1.177766x1.18x10.417%10.4%12.268%12.3%4-1.000000x-1.000000x1.160109x1.160109x1.16x22.304%22.3%25.875%25.9%5-1.000000x-1.000000x1.137506x1.137506x1.14x8.598%8.60%9.780%9.78%-1.000000x-1.000000x1.136388x1.136388x1.14x6.913%6.91%7.856%7.86%-1.000000x-1.000000x1.127915x1.127915x1.13x9.647%9.65%10.881%10.9%-1.000000x-1.000000x1.127206x1.127206x1.13x20.830%20.8%23.479%23.5%6-1.000000x-1.000000x1.123984x1.123984x1.12x16.526%16.5%18.574%18.6%7-1.000000x-1.000000x1.109070x1.109070x1.11x12.369%12.4%13.719%13.7%-1.000000x-1.000000x1.108477x1.108477x1.11x7.014%7.01%7.775%7.77%-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#34

Percentage more likely men are than women to have a professional or doctorate degree (e.g., MBA, PhD, or MD) among people aged 25 years and older.
Scope: population of Dakota, selected other county subdivisions in the United States, and entities that contain Dakota
Female
Male
1x0x1x2xFM#Tract 670800DakotaDakotaWinona AreaWinona AreaWinonaEl PasoSalt Lk CityPlanoTulsaAlbuquerqueNE DallasFort WorthOrlandoPhoenixTucson1, CharlotteMidwestNW HarrisZIP 55925Las VegasWest North CentralSeattle EastSan Antonio CntrlSan DiegoUnited StatesSan JoseHempsteadFresnoNE TarrantMinnesotaTampaSan Fernando VlyE San Gabriel VlyHoustonSan BernardinoColumbusMiamiAtlantaMilwaukeeAnaheim-Santa Ana-Gdn GrvAnaheim-Santa An…SacramentoPhiladelphiaOceanside-EscondidoOceanside-Escond…Los AngelesAustinBaltimoreWashingtonQueensSW DallasBrooklynManhattanChicagoSeattleBostonBronxOntarioLong Bch-LakewoodDenverSan FranciscoDetroit-1.000000x-1.000000x2.676230x2.676230x2.68x3.331%3.33%8.914%8.91%-1.000000x-1.000000x2.657895x2.657895x2.66x0.990%0.99%2.632%2.63%-1.000000x-1.000000x2.657895x2.657895x2.66x0.990%0.99%2.632%2.63%-1.000000x-1.000000x2.378740x2.378740x2.38x2.089%2.09%4.970%4.97%-1.000000x-1.000000x2.216484x2.216484x2.22x1.916%1.92%4.247%4.25%-1.000000x-1.000000x2.216484x2.216484x2.22x1.916%1.92%4.247%4.25%-1.000000x-1.000000x2.132933x2.132933x2.13x1.146%1.15%2.445%2.44%1-1.000000x-1.000000x2.053360x2.053360x2.05x2.488%2.49%5.109%5.11%2-1.000000x-1.000000x1.782054x1.782054x1.78x3.355%3.35%5.978%5.98%3-1.000000x-1.000000x1.720683x1.720683x1.72x2.338%2.34%4.022%4.02%4-1.000000x-1.000000x1.707718x1.707718x1.71x3.458%3.46%5.905%5.91%5-1.000000x-1.000000x1.692229x1.692229x1.69x2.857%2.86%4.836%4.84%6-1.000000x-1.000000x1.684272x1.684272x1.68x1.637%1.64%2.757%2.76%7-1.000000x-1.000000x1.660799x1.660799x1.66x2.196%2.20%3.647%3.65%8-1.000000x-1.000000x1.659024x1.659024x1.66x2.280%2.28%3.783%3.78%9-1.000000x-1.000000x1.621815x1.621815x1.62x3.429%3.43%5.561%5.56%10-1.000000x-1.000000x1.611479x1.611479x1.61x2.711%2.71%4.369%4.37%11-1.000000x-1.000000x1.589934x1.589934x1.59x2.251%2.25%3.579%3.58%-1.000000x-1.000000x1.579303x1.579303x1.58x2.100%2.10%3.317%3.32%12-1.000000x-1.000000x1.578313x1.578313x1.58x0.763%0.76%1.205%1.20%-1.000000x-1.000000x1.576623x1.576623x1.58x1.677%1.68%2.643%2.64%13-1.000000x-1.000000x1.572017x1.572017x1.57x2.329%2.33%3.662%3.66%-1.000000x-1.000000x1.557664x1.557664x1.56x4.733%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-1.000000x1.481015x1.481015x1.48x2.798%2.80%4.144%4.14%-1.000000x-1.000000x1.476874x1.476874x1.48x3.518%3.52%5.196%5.20%21-1.000000x-1.000000x1.460302x1.460302x1.46x2.944%2.94%4.299%4.30%22-1.000000x-1.000000x1.451775x1.451775x1.45x2.041%2.04%2.963%2.96%23-1.000000x-1.000000x1.424636x1.424636x1.42x3.092%3.09%4.404%4.40%24-1.000000x-1.000000x1.423621x1.423621x1.42x1.501%1.50%2.137%2.14%25-1.000000x-1.000000x1.413654x1.413654x1.41x2.801%2.80%3.959%3.96%26-1.000000x-1.000000x1.395174x1.395174x1.40x3.384%3.38%4.722%4.72%27-1.000000x-1.000000x1.391590x1.391590x1.39x5.799%5.80%8.070%8.07%28-1.000000x-1.000000x1.368590x1.368590x1.37x1.742%1.74%2.385%2.38%29-1.000000x-1.000000x1.362600x1.362600x1.36x2.347%2.35%3.199%3.20%30-1.000000x-1.000000x1.359928x1.359928x1.36x2.888%2.89%3.927%3.93%31-1.000000x-1.000000x1.341930x1.341930x1.34x3.216%3.22%4.316%4.32%32-1.000000x-1.000000x1.310218x1.310218x1.31x3.011%3.01%3.945%3.95%33-1.000000x-1.000000x1.308108x1.308108x1.31x4.045%4.05%5.292%5.29%34-1.000000x-1.000000x1.303834x1.303834x1.30x4.384%4.38%5.716%5.72%35-1.000000x-1.000000x1.303196x1.303196x1.30x4.332%4.33%5.645%5.65%36-1.000000x-1.000000x1.300117x1.300117x1.30x10.922%10.9%14.199%14.2%37-1.000000x-1.000000x1.285200x1.285200x1.29x2.428%2.43%3.121%3.12%38-1.000000x-1.000000x1.265486x1.265486x1.27x1.515%1.51%1.917%1.92%39-1.000000x-1.000000x1.262281x1.262281x1.26x3.021%3.02%3.814%3.81%40-1.000000x-1.000000x1.245683x1.245683x1.25x9.673%9.67%12.050%12.1%41-1.000000x-1.000000x1.238186x1.238186x1.24x4.026%4.03%4.985%4.99%42-1.000000x-1.000000x1.228890x1.228890x1.23x5.961%5.96%7.326%7.33%43-1.000000x-1.000000x1.221037x1.221037x1.22x6.643%6.64%8.112%8.11%44-1.000000x-1.000000x1.202385x1.202385x1.20x1.526%1.53%1.834%1.83%45-1.000000x-1.000000x1.198236x1.198236x1.20x2.119%2.12%2.539%2.54%46-1.000000x-1.000000x1.181998x1.181998x1.18x2.766%2.77%3.269%3.27%47-1.000000x-1.000000x1.129665x1.129665x1.13x5.378%5.38%6.075%6.08%48-1.000000x-1.000000x1.098720x1.098720x1.10x7.194%7.19%7.905%7.90%49-1.000000x-1.000000x1.046557x1.046557x1.05x1.291%1.29%1.351%1.35%50
F percentage of females in category
M percentage of males in category
# rank of county subdivision out of 50 by male-to-female sex ratio

Definitions

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

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

The coarse levels of educational attainment are as follows:

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

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

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Demographics

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More Maps to Explore

State:
Minnesota
County:
Winona
Metro Area:
Winona Area
City:
Dakota
ZIP Code:
55925
Unified School District:
Winona Area
Congressional District:
MN-1
State Senate District:
MN-28
State House District:
MN-28A
Neighboring Towns:
Campbell, Onalaska
Neighboring Townships:
Dresbach, New Hartford
Nearby Towns:
Caledonia, Holland
Nearby Townships:
La Crescent, Pleasant Hill, Richmond