Educational Attainment in Brown County, Minnesota (County)

Educational Attainment#1

Highest level of education among people aged 25 years and older.
Scope: population of Minnesota and Brown County
Brown County
Minnesota
0%10%20%30%40%50%CountHigher Degree1H.S. Diploma2No H.S. Diploma231.577432%45.216942%31.577432%31.6%5,48559.556707%47.407004%59.556707%59.6%10,34510.3k8.865861%7.376055%8.865861%8.9%1,540
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 Minnesota at large.
Scope: population of Minnesota and Brown County
-20%0%+20%%ref.Higher Degree1H.S. Diploma2No H.S. Diploma2-30.164600%-30.164600%-30.2%31.577%31.6%45.217%45.2%25.628499%25.628499%+25.6%59.557%59.6%47.407%47.4%20.197874%20.197874%+20.2%8.866%8.87%7.376%7.38%
% percentage with given level in Brown County
ref. percentage with given level in Minnesota
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 Minnesota and Brown County
Brown County
Minnesota
0%10%20%30%CountDoctorate1Professional1Master's1Bachelor's1Associate's1Some CollegeHigh School2Some H.S.3Less than H.S.3None0.765688%1.366389%0.765688%0.8%1331.393207%2.092359%1.393207%1.4%2423.390904%8.000226%3.390904%3.4%58915.342545%22.781635%15.342545%15.3%2,66510.685089%10.976332%10.685089%10.7%1,85621.755901%21.730308%21.755901%21.8%3,77937.800806%25.676696%37.800806%37.8%6,5664.899252%4.319913%4.899252%4.9%8513.402418%1.957001%3.402418%3.4%5910.564191%1.099141%0.564191%0.6%98
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 Minnesota at large.
Scope: population of Minnesota and Brown County
-50%0%+50%%ref.Doctorate1Professional1Master's1Bachelor's1Associate's1Some CollegeHigh School2Some H.S.3Less than H.S.3None-43.962670%-43.962670%-44.0%0.766%0.77%1.366%1.37%-33.414557%-33.414557%-33.4%1.393%1.39%2.092%2.09%-57.614900%-57.614900%-57.6%3.391%3.39%8.000%8.00%-32.653891%-32.653891%-32.7%15.343%15.3%22.782%22.8%-2.653374%-2.653374%-2.7%10.685%10.7%10.976%11.0%0.117775%0.117775%+0.1%21.756%21.8%21.730%21.7%47.218344%47.218344%+47.2%37.801%37.8%25.677%25.7%13.410887%13.410887%+13.4%4.899%4.90%4.320%4.32%73.858772%73.858772%+73.9%3.402%3.40%1.957%1.96%-48.669792%-48.669792%-48.7%0.564%0.56%1.099%1.10%
% percentage with given level in Brown County
ref. percentage with given level in Minnesota
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 Minnesota and Brown County
More Females More Males
Minnesota
Brown County
5%0%5%10%FMHigher Degree1H.S. Diploma2No H.S. Diploma2-7.094129%1.207197%1.207197%1%31.393%31.4%31.772%31.8%0.325258%4.644972%0.325258%0%59.463%59.5%59.656%59.7%-6.677859%-6.677859%7%13.638813%9.144%9.14%8.571%8.57%
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 Minnesota and Brown County
More Females More Males
Minnesota
Brown County
0%100%200%FMDoctorate1Professional1Master's1Bachelor's1Associate's1Some CollegeHigh School2Some H.S.3Less than H.S.3None65.002736%46.084775%65.002736%65%0.582%0.58%0.960%0.96%200.969129%49.436197%200.969129%201%0.705%0.71%2.122%2.12%-22.131208%21.778175%21.778175%22%3.067%3.07%3.734%3.73%-11.308757%-6.225334%-11.308757%11%16.139%16.1%14.499%14.5%-4.251161%-14.436796%-4.251161%4%10.901%10.9%10.456%10.5%-1.393757%1.697168%1.697168%2%21.578%21.6%21.944%21.9%-0.458233%-0.458233%0%10.026271%37.885%37.9%37.712%37.7%6.176924%29.029778%6.176924%6%4.757%4.76%5.050%5.05%-45.049967%-45.049967%45%5.463227%4.007%4.01%2.762%2.76%-26.769029%99.393284%99.393284%99%0.381%0.38%0.759%0.76%
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 Minnesota and Brown County
Brown County
Minnesota
0%5%10%15%20%25%B.X.Total65+45-6435-4425-347.894737%15.674649%7.894737%7.9%3995,05415.388975%21.754200%15.388975%15.4%1,0867,05719.349659%26.172525%19.349659%19.3%4822,49125.216763%29.184434%25.216763%25.2%6982,768
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 Minnesota at large.
Scope: population of Minnesota and Brown County
40%30%20%10%0%%ref.65+45-6435-4425-34-49.633726%-49.633726%49.6%7.895%7.89%15.675%15.7%-29.259749%-29.259749%29.3%15.389%15.4%21.754%21.8%-26.068810%-26.068810%26.1%19.350%19.3%26.173%26.2%-13.595162%-13.595162%13.6%25.217%25.2%29.184%29.2%
% percentage in Brown County with a Bachelor's degree
ref percentage in Minnesota 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 Minnesota and Brown County
More Females More Males
Minnesota
Brown County
20%0%20%FM65+45-6435-4425-3434.360390%20.814223%34.360390%34.4%6.868%6.87%9.227%9.23%-25.223779%-6.871300%-25.223779%25.2%17.123%17.1%13.674%13.7%-36.959755%-16.463598%-36.959755%37.0%22.451%22.5%16.392%16.4%-18.994861%-19.935695%-18.994861%19.0%27.454%27.5%23.071%23.1%
F female degree holders as a percentage of all females
M male degree holders as a percentage of all males

Median Earnings by Educational Attainment#10

Among population 25 years old and over with earnings.
Scope: population of Minnesota and Brown County
Brown County
Minnesota
$0k$20k$40k$60kCount%Graduate Degree1Bachelor's DegreeSome CollegeH.S. Diploma2No H.S. Diploma2Total$52,008.000000$68,001.000000$52,008.000000$52.0k9645.550%5.55%$41,794.000000$52,072.000000$41,794.000000$41.8k2,66515.343%15.3%$35,369.000000$36,939.000000$35,369.000000$35.4k5,63532.441%32.4%$29,565.000000$31,011.000000$29,565.000000$29.6k6,56637.801%37.8%$20,904.000000$22,379.000000$20,904.000000$20.9k1,5408.866%8.87%$35,118.000000$40,804.000000$35,118.000000$35.1k17,37017.4k100.000%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 Minnesota and Brown County
Female Male
Minnesota
Brown County
Shaded bar tips show excess over facing bar.
$50k$0k$50kFMGraduate Degree1Bachelor's DegreeSome CollegeH.S. Diploma2No H.S. Diploma2Total$-48,712.000000$-60,699.000000$-48,712.000000$48.7k$48,712.000000$12,046.000000$60,699.000000$20,223.000000$60,758.000000$60.8k389575$-34,167.000000$-43,209.000000$-34,167.000000$34.2k$34,167.000000$19,323.000000$43,209.000000$20,301.000000$53,490.000000$53.5k1,4421,223$-26,029.000000$-30,960.000000$-26,029.000000$26.0k$26,029.000000$19,605.000000$30,960.000000$13,760.000000$45,634.000000$45.6k2,9022,733$-22,468.000000$-24,260.000000$-22,468.000000$22.5k$22,468.000000$13,611.000000$24,260.000000$12,346.000000$36,079.000000$36.1k3,3853,181$-20,764.000000$-17,131.000000$-20,764.000000$20.8k$20,764.000000$247.000000$17,131.000000$9,376.000000$21,011.000000$21.0k817723$-26,873.000000$-34,315.000000$-26,873.000000$26.9k$26,873.000000$15,105.000000$34,315.000000$12,949.000000$41,978.000000$42.0k8,9358,435
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 Minnesota and Brown County
Brown County
Minnesota
0%20%40%60%80%100%CountBachelor's Degree1Some College2H.S. Diploma3No H.S. Diploma30.000000%0.000000%0.0%35.183299%0100.000000%56.313646%100.000000%100.0%20.000000%0.000000%0.0%8.503055%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 Minnesota and Brown County
Brown County
Minnesota
0%20%40%60%80%CountBachelor's Degree1Some College2H.S. Diploma3No H.S. Diploma388.244979%87.405591%88.244979%88.2%2,68089.133722%81.736852%89.133722%89.1%4,12682.008266%74.314958%82.008266%82.0%3,37371.135940%58.425001%71.135940%71.1%382
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 Minnesota and Brown County
Female Male
Minnesota
Brown County
Shaded bar tips show excess over facing bar.
30%20%10%0%10%20%30%MFWhite1BlackAsianHispanic2Other1-8.234860%-0.299743%-4.270697%-8.534603%8.5%8.234860%4.270697%1.199676%8.234860%8.2%669735-0.000000%-15.996843%-5.794594%0.000000%0.0%0.000000%0.000000%15.996843%0.000000%0.0%00-0.000000%-17.242336%-6.032412%0.000000%0.0%0.000000%0.000000%17.242336%0.000000%0.0%00-26.455026%-5.165527%-32.943822%-31.620553%31.6%26.455026%32.943822%5.005995%26.455026%26.5%5080-2.083333%-21.417113%-2.083333%2.1%2.083333%31.250000%21.417113%5.201726%33.333333%33.3%322
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 Minnesota and Brown County
Female Male
Minnesota
Brown County
Shaded bar tips show excess over facing bar.
40%20%0%20%40%MFWhite1BlackAsianHispanic2Other1-20.575941%-34.661162%-1.797325%-20.575941%20.6%20.575941%1.334448%34.661162%21.910389%21.9%1,7801,772-0.000000%-18.524426%0.000000%0.0%0.000000%0.000000%18.524426%2.990804%0.000000%0.0%00-9.302326%-41.369118%-9.302326%9.3%9.302326%12.697674%41.369118%3.173947%22.000000%22.0%114-0.000000%-18.972332%-15.584176%-2.395113%-18.972332%19.0%0.000000%15.584176%0.000000%0.0%048-7.291667%-38.541667%-17.924863%-3.708263%-45.833333%45.8%7.291667%17.924863%7.291667%7.3%744
M number of males in category
F number of females in category
1non-Hispanic 2excluding black and Asian Hispanics

Map of Educational Attainment by County Subdivision in Brown County

Coarse: Post-Secondary Degree Educational Attainment by County Subdivision#16

Percentage of the population 25 years and older with given highest level of educational attainment
13.3%17.7%22.1%26.5%30.9%35.4%

Coarse: High School Diploma Educational Attainment by County Subdivision#17

Percentage of the population 25 years and older with given highest level of educational attainment
53.3%58.1%62.9%67.7%72.5%77.3%

Coarse: No High School Diploma Educational Attainment by County Subdivision#18

Percentage of the population 25 years and older with given highest level of educational attainment
3.0%7.8%12.5%17.2%21.9%26.7%

Detailed: Doctorate Degree Educational Attainment by County Subdivision#19

Percentage of the population 25 years and older with given highest level of educational attainment
0.0%0.9%1.8%2.7%3.6%4.5%

Detailed: Professional Degree Educational Attainment by County Subdivision#20

Percentage of the population 25 years and older with given highest level of educational attainment
0.0%0.8%1.6%2.4%3.1%4.0%

Detailed: Master's Degree Educational Attainment by County Subdivision#21

Percentage of the population 25 years and older with given highest level of educational attainment
0.0%1.5%3.0%4.6%6.1%7.7%

Detailed: Bachelor's Degree Educational Attainment by County Subdivision#22

Percentage of the population 25 years and older with given highest level of educational attainment
5.7%8.5%11.3%14.2%17.0%19.8%

Detailed: Associate's Degree Educational Attainment by County Subdivision#23

Percentage of the population 25 years and older with given highest level of educational attainment
0.0%3.5%7.0%10.5%13.9%17.5%

Detailed: Some College Educational Attainment by County Subdivision#24

Percentage of the population 25 years and older with given highest level of educational attainment
4%10%16%21%27%33%

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

Percentage of the population 25 years and older with given highest level of educational attainment
29%35%41%46%52%58%

Detailed: Some High School Educational Attainment by County Subdivision#26

Percentage of the population 25 years and older with given highest level of educational attainment
0.4%3.0%5.6%8.2%10.8%13.4%

Detailed: Less than High School Educational Attainment by County Subdivision#27

Percentage of the population 25 years and older with given highest level of educational attainment
0.0%2.7%5.3%8.0%10.7%13.4%

Detailed: None Educational Attainment by County Subdivision#28

Percentage of the population 25 years and older with given highest level of educational attainment
0.0%1.3%2.7%4.0%5.3%6.7%
Road Data ©OpenStreetMap

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Map of Educational Attainment by Tract in Brown County

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

Percentage of the population 25 years and older with given highest level of educational attainment
22.1%26.9%31.6%36.3%41.0%45.8%

Coarse: High School Diploma Educational Attainment by Tract#30

Percentage of the population 25 years and older with given highest level of educational attainment
51.1%54.3%57.4%60.5%63.7%66.9%

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

Percentage of the population 25 years and older with given highest level of educational attainment
3.1%5.2%7.2%9.2%11.2%13.3%

Detailed: Doctorate Degree Educational Attainment by Tract#32

Percentage of the population 25 years and older with given highest level of educational attainment
0.00%0.38%0.76%1.14%1.53%1.91%

Detailed: Professional Degree Educational Attainment by Tract#33

Percentage of the population 25 years and older with given highest level of educational attainment
0.0%0.5%1.1%1.6%2.2%2.8%

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

Percentage of the population 25 years and older with given highest level of educational attainment
1.1%2.2%3.2%4.2%5.2%6.3%

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

Percentage of the population 25 years and older with given highest level of educational attainment
10.8%13.6%16.5%19.3%22.1%25.0%

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

Percentage of the population 25 years and older with given highest level of educational attainment
5.0%7.4%9.8%12.1%14.5%16.9%

Detailed: Some College Educational Attainment by Tract#37

Percentage of the population 25 years and older with given highest level of educational attainment
17.1%19.2%21.2%23.2%25.2%27.3%

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

Percentage of the population 25 years and older with given highest level of educational attainment
25.0%30.0%34.9%39.8%44.8%49.7%

Detailed: Some High School Educational Attainment by Tract#39

Percentage of the population 25 years and older with given highest level of educational attainment
2.2%3.7%5.1%6.5%8.0%9.5%

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

Percentage of the population 25 years and older with given highest level of educational attainment
0.6%2.0%3.4%4.7%6.1%7.5%

Detailed: None Educational Attainment by Tract#41

Percentage of the population 25 years and older with given highest level of educational attainment
0.22%0.48%0.73%0.97%1.22%1.47%
Road Data ©OpenStreetMap

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Educational Attainment by Place in Brown County

There are 8 places that are fully or partially contained within Brown County (7 fully and 1 partially). This section compares all 8 of those to each other, Brown County, and other entities that contain or substantially overlap with Brown County.

No H.S. Diploma by Place#42

Percent of population 25 years of age and older without a high school diploma (or equivalent).
Scope: population of Brown County, selected places in Brown County, and entities that contain Brown County
0%5%10%15%20%25%Count#CobdenEvanSleepy EyeSpringfieldUnited States of AmericaUnited StatesSearlesComfreyMidwestWest North CentralNew Ulm Metro AreaNew Ulm AreaBrown CountyBrownNew UlmMinnesotaHanska26.666667%26.666667%26.7%4117.777778%17.777778%17.8%8213.806452%13.806452%13.8%321313.347609%13.347609%13.3%187413.020590%13.020590%13.0%27,818,38027.8M11.764706%11.764706%11.8%16510.902256%10.902256%10.9%29610.244520%10.244520%10.2%4,641,8354.64M9.174633%9.174633%9.2%1,278,0511.28M8.865861%8.865861%8.9%1,5408.865861%8.865861%8.9%1,5408.022346%8.022346%8.0%71877.376055%7.376055%7.4%270,121270k6.617647%6.617647%6.6%188
Count number of people in category
# rank of place out of 8 by percentage of population 25 years of age and older without a high school diploma (or equivalent).

Bachelor's Degrees by Place#43

Percent of population 25 years of age and older with a bachelor's degree or higher..
Scope: population of Brown County, selected places in Brown County, and entities that contain Brown County
0%10%20%30%Count#MinnesotaUnited States of AmericaUnited StatesWest North CentralMidwestNew UlmSleepy EyeComfreyNew Ulm Metro AreaNew Ulm AreaBrown CountyBrownEvanSpringfieldCobdenHanskaSearles34.240609%34.240609%34.2%1,253,9371.25M30.315023%30.315023%30.3%64,767,78764.8M30.056536%30.056536%30.1%4,186,9564.19M28.952816%28.952816%29.0%13,118,64213.1M24.357542%24.357542%24.4%2,180122.494624%22.494624%22.5%523221.428571%21.428571%21.4%57320.892343%20.892343%20.9%3,62920.892343%20.892343%20.9%3,62920.000000%20.000000%20.0%9413.490364%13.490364%13.5%189513.333333%13.333333%13.3%2610.294118%10.294118%10.3%2878.088235%8.088235%8.1%118
Count number of people in category
# rank of place out of 8 by percentage of population 25 years of age and older with a bachelor's degree or higher..

Very Advanced Degrees by Place#44

Percent of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).
Scope: population of Brown County, selected places in Brown County, and entities that contain Brown County
0%1%2%3%4%Count#EvanSleepy EyeMinnesotaUnited States of AmericaUnited StatesWest North CentralMidwestNew UlmNew Ulm Metro AreaNew Ulm AreaBrown CountyBrownSpringfieldComfreyHanskaSearlesCobden4.444444%4.444444%4.4%214.258065%4.258065%4.3%9923.458748%3.458748%3.5%126,664127k3.336158%3.336158%3.3%7,127,6737.13M2.978981%2.978981%3.0%414,980415k2.893416%2.893416%2.9%1,311,0191.31M2.391061%2.391061%2.4%21432.158895%2.158895%2.2%3752.158895%2.158895%2.2%3751.855817%1.855817%1.9%2640.751880%0.751880%0.8%250.000000%0.000000%0.0%060.000000%0.000000%0.0%070.000000%0.000000%0.0%08
Count number of people in category
# rank of place out of 8 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 Place#45

Percentage more likely men are than women to not have a high school diploma (or equivalent) among people aged 25 years and older.
Scope: population of Brown County, selected places in Brown County, and entities that contain Brown County
Female
Male
10x5x0xFM#HanskaWest North CentralMinnesotaMidwestComfreyUnited StatesSpringfieldNew UlmNew Ulm AreaBrownEvanSleepy EyeSearlesCobden-1.000000x-1.000000x4.784173x4.784173x4.78x2.256%2.26%10.791%10.8%1-1.000000x-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-1.000000x1.120879x1.120879x1.12x10.294%10.3%11.538%11.5%2-1.000000x-1.000000x1.109070x1.109070x1.11x12.369%12.4%13.719%13.7%-1.000000x-1.000000x1.011264x1.011264x1.01x13.283%13.3%13.433%13.4%3-1.031327x-1.031327x1.03x1.000000x1.000000x8.142%8.14%7.895%7.89%4-1.066779x-1.066779x1.07x1.000000x1.000000x9.144%9.14%8.571%8.57%-1.066779x-1.066779x1.07x1.000000x1.000000x9.144%9.14%8.571%8.57%-1.217949x-1.217949x1.22x1.000000x1.000000x19.231%19.2%15.789%15.8%5-1.684928x-1.684928x1.68x1.000000x1.000000x16.929%16.9%10.047%10.0%6-2.786667x-2.786667x2.79x1.000000x1.000000x18.333%18.3%6.579%6.58%7-10.000000x-10.000000x> 10.0x1.000000x1.000000x44.444%44.4%0.000%0%8
F percentage of females in category
M percentage of males in category
# rank of place out of 8 by male-to-female sex ratio

Over-Education Sex Ratio by Place#46

Percentage more likely men are than women to have a professional or doctorate degree (e.g., MBA, PhD, or MD) among people aged 25 years and older.
Scope: population of Brown County, selected places in Brown County, and entities that contain Brown County
Female
Male
10x5x0x5x10xFM#ComfreyNew UlmNew Ulm AreaBrownSleepy EyeMidwestWest North CentralUnited StatesMinnesotaSpringfieldEvan-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%1.538%1.54%1-1.000000x-1.000000x3.238288x3.238288x3.24x1.148%1.15%3.717%3.72%2-1.000000x-1.000000x2.394887x2.394887x2.39x1.287%1.29%3.082%3.08%-1.000000x-1.000000x2.394887x2.394887x2.39x1.287%1.29%3.082%3.08%-1.000000x-1.000000x2.106635x2.106635x2.11x2.835%2.83%5.972%5.97%3-1.000000x-1.000000x1.589934x1.589934x1.59x2.251%2.25%3.579%3.58%-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-1.000000x1.323383x1.323383x1.32x1.629%1.63%2.156%2.16%4-10.000000x-10.000000x> 10.0x1.000000x1.000000x7.692%7.69%0.000%0%5
F percentage of females in category
M percentage of males in category
# rank of place out of 5 by male-to-female sex ratio

Educational Attainment by County Subdivision in Brown County

There are 23 county subdivisions in Brown County. This section compares all 23 of those to each other, Brown County, and other entities that contain or substantially overlap with Brown County.

No H.S. Diploma by County Subdivision#47

Percent of population 25 years of age and older without a high school diploma (or equivalent).
Scope: population of Brown County, selected county subdivisions in Brown County, and entities that contain Brown County
0%5%10%15%20%25%Count#CobdenEvanSleepy EyeSpringfieldStately TownshipStatelyUnited States of AmericaUnited StatesMidwestComfreyLinden TownshipLindenWest North CentralNew Ulm Metro AreaNew Ulm AreaBrown CountyBrownMulligan TownshipMulliganSigel TownshipSigelNew UlmLeavenworth TownshipLeavenworthCottonwood TownshipCottonwoodMinnesotaAlbin TownshipAlbinHanskaEden TownshipStark TownshipStarkBashaw TownshipBashawHome TownshipPrairieville TownshipPrairievilleBurnstown TownshipBurnstownLake Hanska TownshipLk HanskaNorth Star TownshipN StarMilford TownshipMilford26.666667%26.666667%26.7%4117.777778%17.777778%17.8%8213.806452%13.806452%13.8%321313.347609%13.347609%13.3%187413.286713%13.286713%13.3%19513.020590%13.020590%13.0%27,818,38027.8M10.244520%10.244520%10.2%4,641,8354.64M10.041841%10.041841%10.0%2469.803922%9.803922%9.8%2079.174633%9.174633%9.2%1,278,0511.28M8.865861%8.865861%8.9%1,5408.865861%8.865861%8.9%1,5408.275862%8.275862%8.3%1288.108108%8.108108%8.1%2798.022346%8.022346%8.0%718107.657658%7.657658%7.7%17117.491289%7.491289%7.5%43127.376055%7.376055%7.4%270,121270k6.837607%6.837607%6.8%16136.617647%6.617647%6.6%18146.315789%6.315789%6.3%12156.024096%6.024096%6.0%15165.882353%5.882353%5.9%11175.851064%5.851064%5.9%22184.938272%4.938272%4.9%8194.575163%4.575163%4.6%7203.809524%3.809524%3.8%8213.208556%3.208556%3.2%6223.068592%3.068592%3.1%1723
Count number of people in category
# rank of county subdivision out of 23 by percentage of population 25 years of age and older without a high school diploma (or equivalent).

Bachelor's Degrees by County Subdivision#48

Percent of population 25 years of age and older with a bachelor's degree or higher..
Scope: population of Brown County, selected county subdivisions in Brown County, and entities that contain Brown County
0%10%20%30%Count#MinnesotaUnited States of AmericaUnited StatesWest North CentralMidwestLake Hanska TownshipLk HanskaNew UlmSleepy EyeMilford TownshipMilfordComfreyNew Ulm Metro AreaNew Ulm AreaBrown CountyBrownEvanBashaw TownshipBashawHome TownshipBurnstown TownshipBurnstownLinden TownshipLindenEden TownshipNorth Star TownshipN StarCottonwood TownshipCottonwoodAlbin TownshipAlbinStark TownshipStarkSpringfieldCobdenStately TownshipStatelyHanskaMulligan TownshipMulliganPrairieville TownshipPrairievilleLeavenworth TownshipLeavenworthSigel TownshipSigel34.240609%34.240609%34.2%1,253,9371.25M30.315023%30.315023%30.3%64,767,78764.8M30.056536%30.056536%30.1%4,186,9564.19M28.952816%28.952816%29.0%13,118,64213.1M24.761905%24.761905%24.8%52124.357542%24.357542%24.4%2,180222.494624%22.494624%22.5%523322.021661%22.021661%22.0%122421.757322%21.757322%21.8%52520.892343%20.892343%20.9%3,62920.892343%20.892343%20.9%3,62920.000000%20.000000%20.0%9619.786096%19.786096%19.8%37717.819149%17.819149%17.8%67817.647059%17.647059%17.6%27917.156863%17.156863%17.2%351016.842105%16.842105%16.8%321115.508021%15.508021%15.5%291214.808362%14.808362%14.8%851314.529915%14.529915%14.5%341414.457831%14.457831%14.5%361513.490364%13.490364%13.5%1891613.333333%13.333333%13.3%21712.587413%12.587413%12.6%181810.294118%10.294118%10.3%28199.655172%9.655172%9.7%14209.259259%9.259259%9.3%15218.558559%8.558559%8.6%19227.207207%7.207207%7.2%2423
Count number of people in category
# rank of county subdivision out of 23 by percentage of population 25 years of age and older with a bachelor's degree or higher..

Very Advanced Degrees by County Subdivision#49

Percent of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).
Scope: population of Brown County, selected county subdivisions in Brown County, and entities that contain Brown County
0%1%2%3%4%Count#Burnstown TownshipBurnstownEvanSleepy EyeMinnesotaUnited States of AmericaUnited StatesWest North CentralMidwestNew UlmNew Ulm Metro AreaNew Ulm AreaBrown CountyBrownSpringfieldNorth Star TownshipN StarHome TownshipMilford TownshipMilfordAlbin TownshipAlbinComfreyStately TownshipStatelyLinden TownshipLindenLeavenworth TownshipLeavenworthStark TownshipStarkCottonwood TownshipCottonwoodSigel TownshipSigelHanskaBashaw TownshipBashawLake Hanska TownshipLk HanskaEden TownshipPrairieville TownshipPrairievilleMulligan TownshipMulliganCobden4.575163%4.575163%4.6%714.444444%4.444444%4.4%224.258065%4.258065%4.3%9933.458748%3.458748%3.5%126,664127k3.336158%3.336158%3.3%7,127,6737.13M2.978981%2.978981%3.0%414,980415k2.893416%2.893416%2.9%1,311,0191.31M2.391061%2.391061%2.4%21442.158895%2.158895%2.2%3752.158895%2.158895%2.2%3751.855817%1.855817%1.9%2651.604278%1.604278%1.6%361.595745%1.595745%1.6%671.263538%1.263538%1.3%780.854701%0.854701%0.9%290.836820%0.836820%0.8%2100.699301%0.699301%0.7%1110.490196%0.490196%0.5%1120.450450%0.450450%0.5%1130.401606%0.401606%0.4%1140.348432%0.348432%0.3%2150.300300%0.300300%0.3%1160.000000%0.000000%0.0%0170.000000%0.000000%0.0%0180.000000%0.000000%0.0%0190.000000%0.000000%0.0%0200.000000%0.000000%0.0%0210.000000%0.000000%0.0%0220.000000%0.000000%0.0%023
Count number of people in category
# rank of county subdivision out of 23 by percentage of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).

Under-Education Sex Ratio by County Subdivision#50

Percentage more likely men are than women to not have a high school diploma (or equivalent) among people aged 25 years and older.
Scope: population of Brown County, selected county subdivisions in Brown County, and entities that contain Brown County
Female
Male
10x5x0x5xFM#StatelyHanskaMilfordLeavenworthBurnstownEden TownshipAlbinHome TownshipN StarLindenSigelCottonwoodStarkWest North CentralMinnesotaMidwestBashawUnited StatesSpringfieldNew UlmNew Ulm AreaBrownLk HanskaEvanComfreySleepy EyePrairievilleMulliganCobden-1.000000x-1.000000x6.886076x6.886076x6.89x3.125%3.13%21.519%21.5%1-1.000000x-1.000000x4.784173x4.784173x4.78x2.256%2.26%10.791%10.8%2-1.000000x-1.000000x4.700483x4.700483x4.70x1.079%1.08%5.072%5.07%3-1.000000x-1.000000x3.302564x3.302564x3.30x3.261%3.26%10.769%10.8%4-1.000000x-1.000000x2.600000x2.600000x2.60x2.564%2.56%6.667%6.67%5-1.000000x-1.000000x1.958333x1.958333x1.96x4.255%4.26%8.333%8.33%6-1.000000x-1.000000x1.878788x1.878788x1.88x4.839%4.84%9.091%9.09%7-1.000000x-1.000000x1.826179x1.826179x1.83x4.046%4.05%7.389%7.39%8-1.000000x-1.000000x1.816327x1.816327x1.82x2.247%2.25%4.082%4.08%9-1.000000x-1.000000x1.587013x1.587013x1.59x7.447%7.45%11.818%11.8%10-1.000000x-1.000000x1.361522x1.361522x1.36x6.832%6.83%9.302%9.30%11-1.000000x-1.000000x1.233553x1.233553x1.23x6.667%6.67%8.224%8.22%12-1.000000x-1.000000x1.148936x1.148936x1.15x5.556%5.56%6.383%6.38%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-1.000000x1.127915x1.127915x1.13x9.647%9.65%10.881%10.9%-1.000000x-1.000000x1.113402x1.113402x1.11x5.556%5.56%6.186%6.19%14-1.000000x-1.000000x1.109070x1.109070x1.11x12.369%12.4%13.719%13.7%-1.000000x-1.000000x1.011264x1.011264x1.01x13.283%13.3%13.433%13.4%15-1.031327x-1.031327x1.03x1.000000x1.000000x8.142%8.14%7.895%7.89%16-1.066779x-1.066779x1.07x1.000000x1.000000x9.144%9.14%8.571%8.57%-1.066779x-1.066779x1.07x1.000000x1.000000x9.144%9.14%8.571%8.57%-1.079208x-1.079208x1.08x1.000000x1.000000x3.960%3.96%3.670%3.67%17-1.217949x-1.217949x1.22x1.000000x1.000000x19.231%19.2%15.789%15.8%18-1.298387x-1.298387x1.30x1.000000x1.000000x11.290%11.3%8.696%8.70%19-1.684928x-1.684928x1.68x1.000000x1.000000x16.929%16.9%10.047%10.0%20-1.794872x-1.794872x1.79x1.000000x1.000000x6.410%6.41%3.571%3.57%21-3.904762x-3.904762x3.90x1.000000x1.000000x14.286%14.3%3.659%3.66%22-10.000000x-10.000000x> 10.0x1.000000x1.000000x44.444%44.4%0.000%0%23
F percentage of females in category
M percentage of males in category
# rank of county subdivision out of 23 by male-to-female sex ratio

Over-Education Sex Ratio by County Subdivision#51

Percentage more likely men are than women to have a professional or doctorate degree (e.g., MBA, PhD, or MD) among people aged 25 years and older.
Scope: population of Brown County, selected county subdivisions in Brown County, and entities that contain Brown County
Female
Male
10x5x0x5x10xFM#CottonwoodSigelComfreyLeavenworthN StarBurnstownNew UlmMilfordNew Ulm AreaBrownSleepy EyeMidwestWest North CentralUnited StatesMinnesotaSpringfieldHome TownshipStarkAlbinLindenStatelyEvan-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%0.658%0.66%1-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%0.581%0.58%2-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%1.739%1.74%3-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%0.769%0.77%4-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%3.061%3.06%5-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%9.333%9.33%6-1.000000x-1.000000x3.238288x3.238288x3.24x1.148%1.15%3.717%3.72%7-1.000000x-1.000000x2.518116x2.518116x2.52x0.719%0.72%1.812%1.81%8-1.000000x-1.000000x2.394887x2.394887x2.39x1.287%1.29%3.082%3.08%-1.000000x-1.000000x2.394887x2.394887x2.39x1.287%1.29%3.082%3.08%-1.000000x-1.000000x2.106635x2.106635x2.11x2.835%2.83%5.972%5.97%9-1.000000x-1.000000x1.589934x1.589934x1.59x2.251%2.25%3.579%3.58%-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-1.000000x1.323383x1.323383x1.32x1.629%1.63%2.156%2.16%10-2.346821x-2.346821x2.35x1.000000x1.000000x2.312%2.31%0.985%0.99%11-10.000000x-10.000000x> 10.0x1.000000x1.000000x0.926%0.93%0.000%0%12-10.000000x-10.000000x> 10.0x1.000000x1.000000x1.613%1.61%0.000%0%13-10.000000x-10.000000x> 10.0x1.000000x1.000000x1.064%1.06%0.000%0%14-10.000000x-10.000000x> 10.0x1.000000x1.000000x1.563%1.56%0.000%0%15-10.000000x-10.000000x> 10.0x1.000000x1.000000x7.692%7.69%0.000%0%16
F percentage of females in category
M percentage of males in category
# rank of county subdivision out of 16 by male-to-female sex ratio

Educational Attainment by County in Minnesota

There are 87 counties in Minnesota. This section compares Brown County to the 50 most populous counties in Minnesota and to those entities that contain or substantially overlap with Brown County. The least populous of the compared counties has a population of 19,034.

No H.S. Diploma by County#52

Percent of population 25 years of age and older without a high school diploma (or equivalent).
Scope: population of Brown County, selected other counties in Minnesota, and entities that contain Brown County
0%5%10%15%20%Count#Nobles CountyNoblesMower CountyMowerUnited States of AmericaUnited StatesTodd CountyToddKandiyohi CountyKandiyohiFreeborn CountyFreebornPine CountyPineMorrison CountyMorrisonMidwestMille Lacs CountyMille LacsRice CountyRiceMartin CountyMartinBeltrami CountyBeltramiRamsey CountyRamseyLe Sueur CountyLe SueurFillmore CountyFillmoreWest North CentralPolk CountyPolkMcLeod CountyMcLeodNew Ulm Metro AreaNew Ulm AreaBrown CountyBrownIsanti CountyIsantiCass CountyCassOtter Tail CountyOtter TailMeeker CountyMeekerWaseca CountyWasecaHubbard CountyHubbardStearns CountyStearnsBenton CountyBentonSteele CountySteeleLyon CountyLyonBecker CountyBeckerWinona CountyWinonaMinnesotaHennepin CountyHennepinWabasha CountyWabashaGoodhue CountyGoodhueItasca CountyItascaAnoka CountyAnokaCrow Wing CountyCrow WingSt. Louis CountySt. LouisNicollet CountyNicolletChisago CountyChisagoBlue Earth CountyBlue EarthCarlton CountyCarltonWright CountyWrightDodge CountyDodgeOlmsted CountyOlmstedClay CountyClaySherburne CountySherburneDakota CountyDakotaDouglas CountyDouglasScott CountyScottCarver CountyCarverWashington CountyWashington22.731505%22.731505%22.7%3,174113.044972%13.044972%13.0%3,417213.020590%13.020590%13.0%27,818,38027.8M12.206884%12.206884%12.2%2,025311.767175%11.767175%11.8%3,364411.054220%11.054220%11.1%2,418510.945959%10.945959%10.9%2,305610.644208%10.644208%10.6%2,414710.244520%10.244520%10.2%4,641,8354.64M10.124655%10.124655%10.1%1,79589.946485%9.946485%9.9%4,08999.891183%9.891183%9.9%1,418109.774955%9.774955%9.8%2,693119.707847%9.707847%9.7%33,97334.0k129.236394%9.236394%9.2%1,743139.222022%9.222022%9.2%1,330149.174633%9.174633%9.2%1,278,0511.28M8.927976%8.927976%8.9%1,873158.891768%8.891768%8.9%2,196168.865861%8.865861%8.9%1,5408.865861%8.865861%8.9%1,540178.835464%8.835464%8.8%2,308188.654264%8.654264%8.7%1,791198.273548%8.273548%8.3%3,402208.048889%8.048889%8.0%1,271218.045278%8.045278%8.0%1,059227.967382%7.967382%8.0%1,192237.919702%7.919702%7.9%7,480247.742738%7.742738%7.7%2,055257.613152%7.613152%7.6%1,857267.605788%7.605788%7.6%1,251277.576089%7.576089%7.6%1,730287.495972%7.495972%7.5%2,326297.376055%7.376055%7.4%270,121270k7.173605%7.173605%7.2%59,66059.7k306.811536%6.811536%6.8%1,025316.738113%6.738113%6.7%2,188326.702965%6.702965%6.7%2,179336.524509%6.524509%6.5%15,00215.0k346.519258%6.519258%6.5%2,913356.493917%6.493917%6.5%8,834366.438108%6.438108%6.4%1,384376.245958%6.245958%6.2%2,318385.782358%5.782358%5.8%2,194395.780300%5.780300%5.8%1,426405.768514%5.768514%5.8%4,799415.739196%5.739196%5.7%757425.720978%5.720978%5.7%5,789435.586350%5.586350%5.6%2,066445.536456%5.536456%5.5%3,237455.344224%5.344224%5.3%14,71514.7k465.162101%5.162101%5.2%1,355475.103301%5.103301%5.1%4,545484.267072%4.267072%4.3%2,665494.033635%4.033635%4.0%6,71150
Count number of people in category
# rank of county 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#53

Percent of population 25 years of age and older with a bachelor's degree or higher..
Scope: population of Brown County, selected other counties in Minnesota, and entities that contain Brown County
0%10%20%30%40%Count#Hennepin CountyHennepinCarver CountyCarverWashington CountyWashingtonOlmsted CountyOlmstedRamsey CountyRamseyDakota CountyDakotaScott CountyScottMinnesotaClay CountyClayNicollet CountyNicolletBlue Earth CountyBlue EarthUnited States of AmericaUnited StatesWest North CentralWinona CountyWinonaMidwestAnoka CountyAnokaSt. Louis CountySt. LouisRice CountyRiceBeltrami CountyBeltramiLyon CountyLyonWright CountyWrightSherburne CountySherburneStearns CountyStearnsHubbard CountyHubbardDouglas CountyDouglasSteele CountySteeleGoodhue CountyGoodhueCrow Wing CountyCrow WingOtter Tail CountyOtter TailPolk CountyPolkDodge CountyDodgeBecker CountyBeckerKandiyohi CountyKandiyohiItasca CountyItascaBenton CountyBentonChisago CountyChisagoCarlton CountyCarltonLe Sueur CountyLe SueurWabasha CountyWabashaNew Ulm Metro AreaNew Ulm AreaBrown CountyBrownCass CountyCassFillmore CountyFillmoreMower CountyMowerWaseca CountyWasecaMeeker CountyMeekerMartin CountyMartinIsanti CountyIsantiMcLeod CountyMcLeodFreeborn CountyFreebornMorrison CountyMorrisonMille Lacs CountyMille LacsTodd CountyToddPine CountyPineNobles CountyNobles47.581343%47.581343%47.6%395,715396k146.042751%46.042751%46.0%28,75628.8k242.301173%42.301173%42.3%70,37970.4k341.992707%41.992707%42.0%42,49242.5k441.002246%41.002246%41.0%143,489143k540.723604%40.723604%40.7%112,130112k638.846845%38.846845%38.8%34,59734.6k734.240609%34.240609%34.2%1,253,9371.25M33.009761%33.009761%33.0%12,20812.2k832.260315%32.260315%32.3%6,935931.663284%31.663284%31.7%12,01412.0k1030.315023%30.315023%30.3%64,767,78764.8M30.056536%30.056536%30.1%4,186,9564.19M29.278118%29.278118%29.3%9,0851128.952816%28.952816%29.0%13,118,64213.1M28.225614%28.225614%28.2%64,90064.9k1227.750211%27.750211%27.8%37,75037.8k1327.231817%27.231817%27.2%11,19511.2k1426.798548%26.798548%26.8%7,3831526.775292%26.775292%26.8%4,4041626.760665%26.760665%26.8%22,26322.3k1726.715925%26.715925%26.7%15,62015.6k1825.948670%25.948670%25.9%24,50824.5k1925.392688%25.392688%25.4%3,7992025.056193%25.056193%25.1%6,5772124.786815%24.786815%24.8%6,0462224.347130%24.347130%24.3%7,9062324.190408%24.190408%24.2%10,80910.8k2424.057005%24.057005%24.1%9,8922523.871491%23.871491%23.9%5,0082623.836240%23.836240%23.8%3,1442723.726735%23.726735%23.7%5,4182822.516440%22.516440%22.5%6,4372922.256060%22.256060%22.3%7,2353022.207151%22.207151%22.2%5,8943122.030610%22.030610%22.0%8,1763221.986218%21.986218%22.0%5,4243321.366117%21.366117%21.4%4,0323421.238703%21.238703%21.2%3,1963520.892343%20.892343%20.9%3,62920.892343%20.892343%20.9%3,6293620.869775%20.869775%20.9%4,3193720.399390%20.399390%20.4%2,9423820.004581%20.004581%20.0%5,2403919.858695%19.858695%19.9%2,6144018.896840%18.896840%18.9%2,9844118.470982%18.470982%18.5%2,6484217.690070%17.690070%17.7%4,6214317.313844%17.313844%17.3%4,2764416.755052%16.755052%16.8%3,6654516.151506%16.151506%16.2%3,6634615.618478%15.618478%15.6%2,7694715.353548%15.353548%15.4%2,5474813.780986%13.780986%13.8%2,9024913.507126%13.507126%13.5%1,88650
Count number of people in category
# rank of county 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#54

Percent of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).
Scope: population of Brown County, selected other counties in Minnesota, and entities that contain Brown County
0%2%4%6%Count#Olmsted CountyOlmstedRamsey CountyRamseyHennepin CountyHennepinWashington CountyWashingtonNicollet CountyNicolletMinnesotaBeltrami CountyBeltramiRice CountyRiceUnited States of AmericaUnited StatesBlue Earth CountyBlue EarthDakota CountyDakotaWinona CountyWinonaWest North CentralMidwestCarver CountyCarverSt. Louis CountySt. LouisStearns CountyStearnsKandiyohi CountyKandiyohiLyon CountyLyonBecker CountyBeckerCrow Wing CountyCrow WingHubbard CountyHubbardClay CountyClayDouglas CountyDouglasMower CountyMowerOtter Tail CountyOtter TailNew Ulm Metro AreaNew Ulm AreaBrown CountyBrownScott CountyScottGoodhue CountyGoodhueWright CountyWrightItasca CountyItascaPolk CountyPolkWabasha CountyWabashaAnoka CountyAnokaBenton CountyBentonChisago CountyChisagoSherburne CountySherburneLe Sueur CountyLe SueurCass CountyCassSteele CountySteeleMeeker CountyMeekerFillmore CountyFillmoreFreeborn CountyFreebornDodge CountyDodgeMcLeod CountyMcLeodNobles CountyNoblesMartin CountyMartinMorrison CountyMorrisonCarlton CountyCarltonWaseca CountyWasecaIsanti CountyIsantiMille Lacs CountyMille LacsTodd CountyToddPine CountyPine7.785431%7.785431%7.8%7,87815.718752%5.718752%5.7%20,01320.0k25.193709%5.193709%5.2%43,19443.2k34.495240%4.495240%4.5%7,47944.033121%4.033121%4.0%86753.458748%3.458748%3.5%126,664127k3.419238%3.419238%3.4%94263.371442%3.371442%3.4%1,38673.336158%3.336158%3.3%7,127,6737.13M3.326042%3.326042%3.3%1,26283.172758%3.172758%3.2%8,73693.074444%3.074444%3.1%954102.978981%2.978981%3.0%414,980415k2.893416%2.893416%2.9%1,311,0191.31M2.826035%2.826035%2.8%1,765112.813982%2.813982%2.8%3,828122.795189%2.795189%2.8%2,640132.529033%2.529033%2.5%723142.504864%2.504864%2.5%412152.465513%2.465513%2.5%563162.394647%2.394647%2.4%1,070172.359468%2.359468%2.4%353182.198307%2.198307%2.2%813192.179131%2.179131%2.2%572202.176071%2.176071%2.2%570212.164450%2.164450%2.2%890222.158895%2.158895%2.2%3752.158895%2.158895%2.2%375232.107568%2.107568%2.1%1,877241.970929%1.970929%2.0%640251.852319%1.852319%1.9%1,541261.818014%1.818014%1.8%591271.811335%1.811335%1.8%380281.774322%1.774322%1.8%267291.760513%1.760513%1.8%4,048301.703026%1.703026%1.7%452311.681397%1.681397%1.7%624321.655635%1.655635%1.7%968331.626835%1.626835%1.6%307341.589756%1.589756%1.6%329351.484093%1.484093%1.5%362361.424862%1.424862%1.4%225371.393704%1.393704%1.4%201381.371491%1.371491%1.4%300391.349507%1.349507%1.3%178401.319998%1.319998%1.3%326411.310607%1.310607%1.3%183421.283482%1.283482%1.3%184431.230213%1.230213%1.2%279441.171463%1.171463%1.2%289451.086378%1.086378%1.1%143461.002986%1.002986%1.0%262470.975802%0.975802%1.0%173480.916270%0.916270%0.9%152490.797797%0.797797%0.8%16850
Count number of people in category
# rank of county 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#55

Percentage more likely men are than women to not have a high school diploma (or equivalent) among people aged 25 years and older.
Scope: population of Brown County, selected other counties in Minnesota, and entities that contain Brown County
Female
Male
1x0x1xFM#SherburneChisagoClayGoodhueBeckerBeltramiToddItascaSteeleWasecaHubbardWabashaMille LacsMowerPineMeekerNicolletWrightIsantiDouglasFreebornMartinNoblesCarltonCarverCassFillmoreRiceMcLeodWinonaMorrisonCrow WingAnokaKandiyohiDodgeLe SueurOtter TailWest North CentralMinnesotaMidwestScottBlue EarthUnited StatesStearnsSt. LouisWashingtonBentonOlmstedPolkRamseyDakotaHennepinLyonNew Ulm AreaBrown-1.000000x-1.000000x1.854741x1.854741x1.85x3.863%3.86%7.165%7.17%1-1.000000x-1.000000x1.772080x1.772080x1.77x4.473%4.47%7.927%7.93%2-1.000000x-1.000000x1.572235x1.572235x1.57x4.356%4.36%6.849%6.85%3-1.000000x-1.000000x1.556218x1.556218x1.56x5.302%5.30%8.251%8.25%4-1.000000x-1.000000x1.516852x1.516852x1.52x6.023%6.02%9.136%9.14%5-1.000000x-1.000000x1.503775x1.503775x1.50x7.839%7.84%11.788%11.8%6-1.000000x-1.000000x1.488318x1.488318x1.49x9.782%9.78%14.559%14.6%7-1.000000x-1.000000x1.485888x1.485888x1.49x5.397%5.40%8.020%8.02%8-1.000000x-1.000000x1.468955x1.468955x1.47x6.194%6.19%9.099%9.10%9-1.000000x-1.000000x1.429519x1.429519x1.43x6.696%6.70%9.572%9.57%10-1.000000x-1.000000x1.404540x1.404540x1.40x6.627%6.63%9.309%9.31%11-1.000000x-1.000000x1.398839x1.398839x1.40x5.688%5.69%7.957%7.96%12-1.000000x-1.000000x1.369736x1.369736x1.37x8.563%8.56%11.728%11.7%13-1.000000x-1.000000x1.335628x1.335628x1.34x11.205%11.2%14.966%15.0%14-1.000000x-1.000000x1.332015x1.332015x1.33x9.296%9.30%12.382%12.4%15-1.000000x-1.000000x1.329371x1.329371x1.33x6.907%6.91%9.181%9.18%16-1.000000x-1.000000x1.328471x1.328471x1.33x5.525%5.52%7.340%7.34%17-1.000000x-1.000000x1.323303x1.323303x1.32x4.969%4.97%6.576%6.58%18-1.000000x-1.000000x1.308424x1.308424x1.31x7.652%7.65%10.011%10.0%19-1.000000x-1.000000x1.303635x1.303635x1.30x4.496%4.50%5.861%5.86%20-1.000000x-1.000000x1.288121x1.288121x1.29x9.679%9.68%12.468%12.5%21-1.000000x-1.000000x1.277833x1.277833x1.28x8.705%8.71%11.124%11.1%22-1.000000x-1.000000x1.270560x1.270560x1.27x19.947%19.9%25.344%25.3%23-1.000000x-1.000000x1.269162x1.269162x1.27x5.075%5.08%6.441%6.44%24-1.000000x-1.000000x1.261501x1.261501x1.26x3.783%3.78%4.772%4.77%25-1.000000x-1.000000x1.246667x1.246667x1.25x7.695%7.70%9.593%9.59%26-1.000000x-1.000000x1.218895x1.218895x1.22x8.324%8.32%10.146%10.1%27-1.000000x-1.000000x1.216255x1.216255x1.22x8.956%8.96%10.893%10.9%28-1.000000x-1.000000x1.212928x1.212928x1.21x8.054%8.05%9.769%9.77%29-1.000000x-1.000000x1.208433x1.208433x1.21x6.792%6.79%8.208%8.21%30-1.000000x-1.000000x1.202863x1.202863x1.20x9.663%9.66%11.623%11.6%31-1.000000x-1.000000x1.200288x1.200288x1.20x5.934%5.93%7.123%7.12%32-1.000000x-1.000000x1.199939x1.199939x1.20x5.938%5.94%7.125%7.13%33-1.000000x-1.000000x1.195753x1.195753x1.20x10.733%10.7%12.834%12.8%34-1.000000x-1.000000x1.195088x1.195088x1.20x5.231%5.23%6.251%6.25%35-1.000000x-1.000000x1.191641x1.191641x1.19x8.421%8.42%10.035%10.0%36-1.000000x-1.000000x1.180118x1.180118x1.18x7.597%7.60%8.966%8.97%37-1.000000x-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-1.000000x1.117122x1.117122x1.12x4.825%4.83%5.390%5.39%38-1.000000x-1.000000x1.109674x1.109674x1.11x5.482%5.48%6.083%6.08%39-1.000000x-1.000000x1.109070x1.109070x1.11x12.369%12.4%13.719%13.7%-1.000000x-1.000000x1.099862x1.099862x1.10x7.542%7.54%8.295%8.30%40-1.000000x-1.000000x1.089583x1.089583x1.09x6.217%6.22%6.774%6.77%41-1.000000x-1.000000x1.087828x1.087828x1.09x3.869%3.87%4.208%4.21%42-1.000000x-1.000000x1.064444x1.064444x1.06x7.501%7.50%7.984%7.98%43-1.000000x-1.000000x1.055151x1.055151x1.06x5.573%5.57%5.880%5.88%44-1.000000x-1.000000x1.022657x1.022657x1.02x8.829%8.83%9.029%9.03%45-1.000000x-1.000000x1.006778x1.006778x1.01x9.677%9.68%9.742%9.74%46-1.000000x-1.000000x1.003455x1.003455x1.00x5.335%5.34%5.354%5.35%47-1.016401x-1.016401x1.02x1.000000x1.000000x7.230%7.23%7.114%7.11%48-1.046342x-1.046342x1.05x1.000000x1.000000x7.775%7.78%7.431%7.43%49-1.066779x-1.066779x1.07x1.000000x1.000000x9.144%9.14%8.571%8.57%-1.066779x-1.066779x1.07x1.000000x1.000000x9.144%9.14%8.571%8.57%50
F percentage of females in category
M percentage of males in category
# rank of county out of 50 by male-to-female sex ratio

Over-Education Sex Ratio by County#56

Percentage more likely men are than women to have a professional or doctorate degree (e.g., MBA, PhD, or MD) among people aged 25 years and older.
Scope: population of Brown County, selected other counties in Minnesota, and entities that contain Brown County
Female
Male
1x0x1x2x3xFM#MartinOtter TailMeekerKandiyohiCassNew Ulm AreaBrownWasecaWinonaPolkDouglasFillmoreBeckerOlmstedWabashaNoblesSteeleWashingtonClayFreebornBlue EarthMowerMidwestHubbardWest North CentralWrightGoodhueMille LacsUnited StatesAnokaRamseyPineSt. LouisCrow WingMinnesotaBentonHennepinStearnsItascaScottDakotaLyonCarverIsantiToddNicolletChisagoBeltramiRiceSherburneMcLeodLe SueurDodgeMorrisonCarlton-1.000000x-1.000000x3.306737x3.306737x3.31x0.602%0.60%1.991%1.99%1-1.000000x-1.000000x2.679076x2.679076x2.68x1.183%1.18%3.169%3.17%2-1.000000x-1.000000x2.440738x2.440738x2.44x0.827%0.83%2.018%2.02%3-1.000000x-1.000000x2.437342x2.437342x2.44x1.481%1.48%3.610%3.61%4-1.000000x-1.000000x2.412505x2.412505x2.41x0.928%0.93%2.238%2.24%5-1.000000x-1.000000x2.394887x2.394887x2.39x1.287%1.29%3.082%3.08%-1.000000x-1.000000x2.394887x2.394887x2.39x1.287%1.29%3.082%3.08%6-1.000000x-1.000000x2.312181x2.312181x2.31x0.672%0.67%1.555%1.55%7-1.000000x-1.000000x2.216484x2.216484x2.22x1.916%1.92%4.247%4.25%8-1.000000x-1.000000x2.203958x2.203958x2.20x1.134%1.13%2.500%2.50%9-1.000000x-1.000000x2.124662x2.124662x2.12x1.407%1.41%2.989%2.99%10-1.000000x-1.000000x2.105903x2.105903x2.11x0.902%0.90%1.900%1.90%11-1.000000x-1.000000x1.822168x1.822168x1.82x1.748%1.75%3.186%3.19%12-1.000000x-1.000000x1.681240x1.681240x1.68x5.861%5.86%9.854%9.85%13-1.000000x-1.000000x1.674879x1.674879x1.67x1.330%1.33%2.227%2.23%14-1.000000x-1.000000x1.662747x1.662747x1.66x0.977%0.98%1.624%1.62%15-1.000000x-1.000000x1.661053x1.661053x1.66x1.122%1.12%1.864%1.86%16-1.000000x-1.000000x1.649216x1.649216x1.65x3.417%3.42%5.636%5.64%17-1.000000x-1.000000x1.639544x1.639544x1.64x1.671%1.67%2.740%2.74%18-1.000000x-1.000000x1.630023x1.630023x1.63x1.046%1.05%1.706%1.71%19-1.000000x-1.000000x1.629253x1.629253x1.63x2.530%2.53%4.122%4.12%20-1.000000x-1.000000x1.612378x1.612378x1.61x1.674%1.67%2.700%2.70%21-1.000000x-1.000000x1.589934x1.589934x1.59x2.251%2.25%3.579%3.58%-1.000000x-1.000000x1.578118x1.578118x1.58x1.831%1.83%2.889%2.89%22-1.000000x-1.000000x1.572017x1.572017x1.57x2.329%2.33%3.662%3.66%-1.000000x-1.000000x1.570700x1.570700x1.57x1.443%1.44%2.266%2.27%23-1.000000x-1.000000x1.569228x1.569228x1.57x1.543%1.54%2.421%2.42%24-1.000000x-1.000000x1.547391x1.547391x1.55x0.768%0.77%1.189%1.19%25-1.000000x-1.000000x1.526215x1.526215x1.53x2.660%2.66%4.060%4.06%-1.000000x-1.000000x1.523149x1.523149x1.52x1.399%1.40%2.131%2.13%26-1.000000x-1.000000x1.500145x1.500145x1.50x4.618%4.62%6.928%6.93%27-1.000000x-1.000000x1.488261x1.488261x1.49x0.633%0.63%0.942%0.94%28-1.000000x-1.000000x1.487208x1.487208x1.49x2.265%2.26%3.368%3.37%29-1.000000x-1.000000x1.483973x1.483973x1.48x1.934%1.93%2.870%2.87%30-1.000000x-1.000000x1.481015x1.481015x1.48x2.798%2.80%4.144%4.14%-1.000000x-1.000000x1.468727x1.468727x1.47x1.380%1.38%2.026%2.03%31-1.000000x-1.000000x1.413446x1.413446x1.41x4.324%4.32%6.112%6.11%32-1.000000x-1.000000x1.391736x1.391736x1.39x2.337%2.34%3.252%3.25%33-1.000000x-1.000000x1.385205x1.385205x1.39x1.525%1.53%2.113%2.11%34-1.000000x-1.000000x1.366530x1.366530x1.37x1.785%1.79%2.440%2.44%35-1.000000x-1.000000x1.360675x1.360675x1.36x2.703%2.70%3.678%3.68%36-1.000000x-1.000000x1.345451x1.345451x1.35x2.141%2.14%2.881%2.88%37-1.000000x-1.000000x1.325915x1.325915x1.33x2.437%2.44%3.232%3.23%38-1.000000x-1.000000x1.309730x1.309730x1.31x0.868%0.87%1.137%1.14%39-1.000000x-1.000000x1.298249x1.298249x1.30x0.796%0.80%1.033%1.03%40-1.000000x-1.000000x1.271055x1.271055x1.27x3.549%3.55%4.511%4.51%41-1.000000x-1.000000x1.251393x1.251393x1.25x1.489%1.49%1.864%1.86%42-1.000000x-1.000000x1.248954x1.248954x1.25x3.047%3.05%3.806%3.81%43-1.000000x-1.000000x1.248003x1.248003x1.25x2.992%2.99%3.734%3.73%44-1.000000x-1.000000x1.207534x1.207534x1.21x1.498%1.50%1.809%1.81%45-1.000000x-1.000000x1.199895x1.199895x1.20x1.203%1.20%1.443%1.44%46-1.000000x-1.000000x1.122442x1.122442x1.12x1.532%1.53%1.720%1.72%47-1.000000x-1.000000x1.028949x1.028949x1.03x1.330%1.33%1.369%1.37%48-1.253864x-1.253864x1.25x1.000000x1.000000x1.369%1.37%1.092%1.09%49-1.954634x-1.954634x1.95x1.000000x1.000000x1.566%1.57%0.801%0.80%50
F percentage of females in category
M percentage of males in category
# rank of county out of 50 by male-to-female sex ratio

Educational Attainment by County in the United States

There are 3,142 counties in the United States. This section compares Brown County to the 50 most populous counties in the United States and to those entities that contain or substantially overlap with Brown County. The least populous of the compared counties has a population of 941,618.

No H.S. Diploma by County#57

Percent of population 25 years of age and older without a high school diploma (or equivalent).
Scope: population of Brown County, selected other counties in the United States, and entities that contain Brown County
0%10%20%Count#Bronx CountyBronxFresno CountyFresnoLos Angeles CountyLos AngelesDallas CountyDallasSan Bernardino CountySan BernardinoKings CountyKingsHarris CountyHarrisRiverside CountyRiversideMiami-Dade CountyMiami-DadeQueens CountyQueensPhiladelphia CountyPhiladelphiaBexar CountyBexarOrange CountyOrangeClark CountyClarkWayne CountyWayneTarrant CountyTarrantCook CountyCookSan Diego CountySan DiegoSacramento CountySacramentoMilwaukee CountyMilwaukeeMaricopa CountyMaricopaUnited States of AmericaUnited StatesNew York CountyNew YorkSanta Clara CountySanta ClaraAlameda CountyAlamedaWestchester CountyWestchesterOrange CountyOrangePima CountyPimaHillsborough CountyHillsboroughPalm Beach CountyPalm BeachTravis CountyTravisBroward CountyBrowardCuyahoga CountyCuyahogaContra Costa CountyContra CostaMecklenburg CountyMecklenburgMidwestSalt Lake CountySalt LakeFairfield CountyFairfieldSuffolk CountySuffolkFranklin CountyFranklinWest North CentralNassau CountyNassauHonolulu CountyHonoluluNew Ulm Metro AreaNew Ulm AreaBrown CountyBrownMontgomery CountyMontgomeryFulton CountyFultonFairfax CountyFairfaxWake CountyWakeKing CountyKingMinnesotaMiddlesex CountyMiddlesexHennepin CountyHennepinSt. Louis CountySt. LouisOakland CountyOaklandAllegheny CountyAllegheny28.837398%28.837398%28.8%261,022261k126.224410%26.224410%26.2%151,875152k222.282470%22.282470%22.3%1,495,6171.50M321.975765%21.975765%22.0%349,434349k421.207718%21.207718%21.2%274,381274k520.017506%20.017506%20.0%351,046351k619.839074%19.839074%19.8%554,024554k719.521191%19.521191%19.5%286,746287k819.375775%19.375775%19.4%362,252362k919.344706%19.344706%19.3%315,505316k1017.390838%17.390838%17.4%180,039180k1116.576437%16.576437%16.6%194,124194k1215.490423%15.490423%15.5%325,372325k1315.108430%15.108430%15.1%210,261210k1414.881687%14.881687%14.9%173,869174k1514.774230%14.774230%14.8%182,543183k1614.189351%14.189351%14.2%503,252503k1713.598133%13.598133%13.6%293,959294k1813.220947%13.220947%13.2%129,386129k1913.092854%13.092854%13.1%81,52281.5k2013.051927%13.051927%13.1%348,801349k2113.020590%13.020590%13.0%27,818,38027.8M12.996284%12.996284%13.0%160,845161k2212.928824%12.928824%12.9%166,105166k2312.700590%12.700590%12.7%141,393141k2412.397264%12.397264%12.4%81,98182.0k2512.319191%12.319191%12.3%101,664102k2612.252238%12.252238%12.3%81,21881.2k2712.196236%12.196236%12.2%108,416108k2812.054893%12.054893%12.1%122,162122k2911.841956%11.841956%11.8%90,92190.9k3011.688725%11.688725%11.7%152,462152k3111.473065%11.473065%11.5%100,034100k3210.940787%10.940787%10.9%82,37182.4k3310.377895%10.377895%10.4%69,51069.5k3410.244520%10.244520%10.2%4,641,8354.64M10.238253%10.238253%10.2%69,21169.2k3510.103521%10.103521%10.1%64,29864.3k369.992975%9.992975%10.0%102,414102k379.640656%9.640656%9.6%78,29978.3k389.174633%9.174633%9.2%1,278,0511.28M9.121758%9.121758%9.1%85,26785.3k398.945780%8.945780%8.9%60,28460.3k408.865861%8.865861%8.9%1,5408.865861%8.865861%8.9%1,5408.836226%8.836226%8.8%62,20562.2k418.677323%8.677323%8.7%57,57157.6k428.282040%8.282040%8.3%63,67163.7k437.696387%7.696387%7.7%50,50850.5k447.543133%7.543133%7.5%110,490110k457.376055%7.376055%7.4%270,121270k7.360151%7.360151%7.4%80,37880.4k467.173605%7.173605%7.2%59,66059.7k477.049887%7.049887%7.0%48,46648.5k486.540987%6.540987%6.5%56,30256.3k496.132273%6.132273%6.1%53,97454.0k50
Count number of people in category
# rank of county 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#58

Percent of population 25 years of age and older with a bachelor's degree or higher..
Scope: population of Brown County, selected other counties in the United States, and entities that contain Brown County
0%20%40%60%Count#New York CountyNew YorkFairfax CountyFairfaxMontgomery CountyMontgomeryMiddlesex CountyMiddlesexWake CountyWakeFulton CountyFultonSanta Clara CountySanta ClaraKing CountyKingHennepin CountyHennepinWestchester CountyWestchesterTravis CountyTravisFairfield CountyFairfieldOakland CountyOaklandAlameda CountyAlamedaNassau CountyNassauMecklenburg CountyMecklenburgSt. Louis CountySt. LouisContra Costa CountyContra CostaAllegheny CountyAlleghenyOrange CountyOrangeFranklin CountyFranklinSan Diego CountySan DiegoCook CountyCookSuffolk CountySuffolkMinnesotaPalm Beach CountyPalm BeachKings CountyKingsHonolulu CountyHonoluluSalt Lake CountySalt LakeOrange CountyOrangeHillsborough CountyHillsboroughBroward CountyBrowardMaricopa CountyMaricopaCuyahoga CountyCuyahogaPima CountyPimaLos Angeles CountyLos AngelesTarrant CountyTarrantQueens CountyQueensUnited States of AmericaUnited StatesHarris CountyHarrisWest North CentralMilwaukee CountyMilwaukeeDallas CountyDallasSacramento CountySacramentoMidwestMiami-Dade CountyMiami-DadeBexar CountyBexarPhiladelphia CountyPhiladelphiaClark CountyClarkWayne CountyWayneRiverside CountyRiversideNew Ulm Metro AreaNew Ulm AreaBrown CountyBrownFresno CountyFresnoSan Bernardino CountySan BernardinoBronx CountyBronx60.434640%60.434640%60.4%747,953748k160.260099%60.260099%60.3%463,270463k258.105449%58.105449%58.1%409,049409k353.004569%53.004569%53.0%578,847579k450.070856%50.070856%50.1%328,593329k549.806094%49.806094%49.8%330,446330k649.103299%49.103299%49.1%630,862631k749.055555%49.055555%49.1%718,554719k847.581343%47.581343%47.6%395,715396k947.303651%47.303651%47.3%312,811313k1046.446606%46.446606%46.4%356,611357k1146.362462%46.362462%46.4%295,047295k1245.020952%45.020952%45.0%387,521388k1343.887830%43.887830%43.9%488,594489k1443.543885%43.543885%43.5%407,033407k1543.097901%43.097901%43.1%288,665289k1642.382090%42.382090%42.4%291,365291k1740.269631%40.269631%40.3%303,182303k1839.069581%39.069581%39.1%343,876344k1938.447168%38.447168%38.4%807,572808k2038.352941%38.352941%38.4%311,493311k2136.494430%36.494430%36.5%788,922789k2236.471153%36.471153%36.5%1,293,5181.29M2334.384794%34.384794%34.4%352,396352k2434.240609%34.240609%34.2%1,253,9371.25M34.188819%34.188819%34.2%346,463346k2534.081468%34.081468%34.1%597,685598k2633.350646%33.350646%33.4%224,744225k2732.800693%32.800693%32.8%221,734222k2831.922850%31.922850%31.9%263,443263k2931.433296%31.433296%31.4%279,420279k3031.015731%31.015731%31.0%404,554405k3130.968863%30.968863%31.0%827,615828k3230.891280%30.891280%30.9%269,342269k3330.800609%30.800609%30.8%204,172204k3430.764105%30.764105%30.8%2,064,9112.06M3530.734653%30.734653%30.7%379,742380k3630.595789%30.595789%30.6%499,006499k3730.315023%30.315023%30.3%64,767,78764.8M30.076273%30.076273%30.1%839,907840k3830.056536%30.056536%30.1%4,186,9564.19M29.748251%29.748251%29.7%185,226185k3929.683200%29.683200%29.7%471,989472k4029.283682%29.283682%29.3%286,583287k4128.952816%28.952816%29.0%13,118,64213.1M27.281635%27.281635%27.3%510,061510k4226.926164%26.926164%26.9%315,328315k4326.349720%26.349720%26.3%272,786273k4422.823853%22.823853%22.8%317,635318k4522.338065%22.338065%22.3%260,985261k4621.189043%21.189043%21.2%311,245311k4720.892343%20.892343%20.9%3,62920.892343%20.892343%20.9%3,62919.731980%19.731980%19.7%114,275114k4819.317210%19.317210%19.3%249,922250k4919.131504%19.131504%19.1%173,169173k50
Count number of people in category
# rank of county 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#59

Percent of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).
Scope: population of Brown County, selected other counties in the United States, and entities that contain Brown County
0%5%10%Count#Montgomery CountyMontgomeryNew York CountyNew YorkMiddlesex CountyMiddlesexFairfax CountyFairfaxWestchester CountyWestchesterSanta Clara CountySanta ClaraNassau CountyNassauAlameda CountyAlamedaFulton CountyFultonKing CountyKingFairfield CountyFairfieldSt. Louis CountySt. LouisOakland CountyOaklandHennepin CountyHennepinTravis CountyTravisAllegheny CountyAlleghenyContra Costa CountyContra CostaWake CountyWakeSan Diego CountySan DiegoPalm Beach CountyPalm BeachOrange CountyOrangeFranklin CountyFranklinCook CountyCookCuyahoga CountyCuyahogaPima CountyPimaHonolulu CountyHonoluluSuffolk CountySuffolkMiami-Dade CountyMiami-DadeSalt Lake CountySalt LakePhiladelphia CountyPhiladelphiaLos Angeles CountyLos AngelesMecklenburg CountyMecklenburgBroward CountyBrowardHillsborough CountyHillsboroughMinnesotaKings CountyKingsHarris CountyHarrisUnited States of AmericaUnited StatesSacramento CountySacramentoMaricopa CountyMaricopaDallas CountyDallasOrange CountyOrangeMilwaukee CountyMilwaukeeWest North CentralMidwestBexar CountyBexarQueens CountyQueensFresno CountyFresnoTarrant CountyTarrantClark CountyClarkRiverside CountyRiversideWayne CountyWayneNew Ulm Metro AreaNew Ulm AreaBrown CountyBrownSan Bernardino CountySan BernardinoBronx CountyBronx12.399695%12.399695%12.4%87,29187.3k110.788423%10.788423%10.8%133,520134k28.541485%8.541485%8.5%93,27993.3k37.784891%7.784891%7.8%59,84959.8k47.604460%7.604460%7.6%50,28750.3k56.177550%6.177550%6.2%79,36779.4k65.833659%5.833659%5.8%54,53154.5k75.762347%5.762347%5.8%64,15164.2k85.719518%5.719518%5.7%37,94737.9k95.673632%5.673632%5.7%83,10683.1k105.463614%5.463614%5.5%34,77034.8k115.244723%5.244723%5.2%36,05636.1k125.214131%5.214131%5.2%44,88144.9k135.193709%5.193709%5.2%43,19443.2k145.061951%5.061951%5.1%38,86538.9k155.039180%5.039180%5.0%44,35344.4k164.956168%4.956168%5.0%37,31437.3k174.892146%4.892146%4.9%32,10532.1k184.749001%4.749001%4.7%102,662103k194.475020%4.475020%4.5%45,34945.3k204.348784%4.348784%4.3%91,34591.3k214.335519%4.335519%4.3%35,21235.2k224.239617%4.239617%4.2%150,366150k234.184410%4.184410%4.2%36,48436.5k244.139192%4.139192%4.1%27,43827.4k253.970725%3.970725%4.0%26,75826.8k263.962200%3.962200%4.0%40,60740.6k273.784527%3.784527%3.8%70,75670.8k283.768025%3.768025%3.8%25,47225.5k293.720350%3.720350%3.7%38,51538.5k303.604427%3.604427%3.6%241,932242k313.598297%3.598297%3.6%24,10124.1k323.517075%3.517075%3.5%45,87545.9k333.474402%3.474402%3.5%30,88530.9k343.458748%3.458748%3.5%126,664127k3.384967%3.384967%3.4%59,36259.4k353.344637%3.344637%3.3%93,40293.4k363.336158%3.336158%3.3%7,127,6737.13M3.266254%3.266254%3.3%31,96532.0k373.113482%3.113482%3.1%83,20583.2k383.037379%3.037379%3.0%48,29748.3k392.990491%2.990491%3.0%24,67924.7k402.985811%2.985811%3.0%18,59118.6k412.978981%2.978981%3.0%414,980415k2.893416%2.893416%2.9%1,311,0191.31M2.818073%2.818073%2.8%33,00233.0k422.756960%2.756960%2.8%44,96545.0k432.392530%2.392530%2.4%13,85613.9k442.368743%2.368743%2.4%29,26729.3k452.315475%2.315475%2.3%32,22432.2k462.260473%2.260473%2.3%33,20433.2k472.178386%2.178386%2.2%25,45125.5k482.158895%2.158895%2.2%3752.158895%2.158895%2.2%3751.852789%1.852789%1.9%23,97124.0k491.664253%1.664253%1.7%15,06415.1k50
Count number of people in category
# rank of county 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#60

Percentage more likely men are than women to not have a high school diploma (or equivalent) among people aged 25 years and older.
Scope: population of Brown County, selected other counties in the United States, and entities that contain Brown County
Female
Male
1x0x1xFM#MecklenburgPalm BeachWakeWestchesterFairfieldContra CostaWest North CentralMinnesotaHillsboroughFresnoMidwestDallasSuffolkMilwaukeeWayneUnited StatesOrangeHarrisFultonPhiladelphiaSan BernardinoTarrantCookMaricopaCuyahogaTravisBrowardRiversideOaklandNassauSalt LakeFranklinSacramentoMontgomeryBronxMiddlesexKingsFairfaxBexarPimaKingLos AngelesClarkOrangeSt. LouisHennepinMiami-DadeQueensAlamedaAlleghenyNew YorkNew Ulm AreaBrownSan DiegoSanta ClaraHonolulu-1.000000x-1.000000x1.282326x1.282326x1.28x9.163%9.16%11.750%11.7%1-1.000000x-1.000000x1.244689x1.244689x1.24x10.804%10.8%13.447%13.4%2-1.000000x-1.000000x1.180227x1.180227x1.18x7.089%7.09%8.367%8.37%3-1.000000x-1.000000x1.161379x1.161379x1.16x11.523%11.5%13.383%13.4%4-1.000000x-1.000000x1.158198x1.158198x1.16x9.397%9.40%10.884%10.9%5-1.000000x-1.000000x1.145263x1.145263x1.15x10.231%10.2%11.718%11.7%6-1.000000x-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-1.000000x1.132218x1.132218x1.13x11.472%11.5%12.989%13.0%7-1.000000x-1.000000x1.130389x1.130389x1.13x24.647%24.6%27.860%27.9%8-1.000000x-1.000000x1.127915x1.127915x1.13x9.647%9.65%10.881%10.9%-1.000000x-1.000000x1.120951x1.120951x1.12x20.762%20.8%23.273%23.3%9-1.000000x-1.000000x1.117209x1.117209x1.12x9.458%9.46%10.567%10.6%10-1.000000x-1.000000x1.111013x1.111013x1.11x12.441%12.4%13.822%13.8%11-1.000000x-1.000000x1.109962x1.109962x1.11x14.154%14.2%15.710%15.7%12-1.000000x-1.000000x1.109070x1.109070x1.11x12.369%12.4%13.719%13.7%-1.000000x-1.000000x1.101852x1.101852x1.10x11.740%11.7%12.936%12.9%13-1.000000x-1.000000x1.098530x1.098530x1.10x18.925%18.9%20.790%20.8%14-1.000000x-1.000000x1.090368x1.090368x1.09x8.321%8.32%9.073%9.07%15-1.000000x-1.000000x1.090163x1.090163x1.09x16.700%16.7%18.206%18.2%16-1.000000x-1.000000x1.084622x1.084622x1.08x20.369%20.4%22.092%22.1%17-1.000000x-1.000000x1.079174x1.079174x1.08x14.234%14.2%15.361%15.4%18-1.000000x-1.000000x1.079067x1.079067x1.08x13.676%13.7%14.757%14.8%19-1.000000x-1.000000x1.072566x1.072566x1.07x12.608%12.6%13.523%13.5%20-1.000000x-1.000000x1.068330x1.068330x1.07x11.121%11.1%11.881%11.9%21-1.000000x-1.000000x1.066137x1.066137x1.07x11.462%11.5%12.220%12.2%22-1.000000x-1.000000x1.065180x1.065180x1.07x11.337%11.3%12.076%12.1%23-1.000000x-1.000000x1.064463x1.064463x1.06x18.923%18.9%20.143%20.1%24-1.000000x-1.000000x1.062700x1.062700x1.06x6.352%6.35%6.750%6.75%25-1.000000x-1.000000x1.061865x1.061865x1.06x8.863%8.86%9.411%9.41%26-1.000000x-1.000000x1.061606x1.061606x1.06x9.934%9.93%10.546%10.5%27-1.000000x-1.000000x1.059046x1.059046x1.06x9.376%9.38%9.930%9.93%28-1.000000x-1.000000x1.056584x1.056584x1.06x12.873%12.9%13.601%13.6%29-1.000000x-1.000000x1.048432x1.048432x1.05x8.640%8.64%9.059%9.06%30-1.000000x-1.000000x1.030539x1.030539x1.03x28.448%28.4%29.316%29.3%31-1.000000x-1.000000x1.025105x1.025105x1.03x7.273%7.27%7.455%7.46%32-1.000000x-1.000000x1.018960x1.018960x1.02x19.845%19.8%20.221%20.2%33-1.000000x-1.000000x1.016052x1.016052x1.02x8.218%8.22%8.350%8.35%34-1.000000x-1.000000x1.009187x1.009187x1.01x16.504%16.5%16.655%16.7%35-1.000000x-1.000000x1.001235x1.001235x1.00x12.245%12.2%12.260%12.3%36-1.004399x-1.004399x1.00x1.000000x1.000000x7.560%7.56%7.526%7.53%37-1.004399x-1.004399x1.00x1.000000x1.000000x22.330%22.3%22.232%22.2%38-1.008231x-1.008231x1.01x1.000000x1.000000x15.170%15.2%15.046%15.0%39-1.015422x-1.015422x1.02x1.000000x1.000000x15.605%15.6%15.368%15.4%40-1.015859x-1.015859x1.02x1.000000x1.000000x7.101%7.10%6.990%6.99%41-1.016401x-1.016401x1.02x1.000000x1.000000x7.230%7.23%7.114%7.11%42-1.022059x-1.022059x1.02x1.000000x1.000000x19.576%19.6%19.154%19.2%43-1.027762x-1.027762x1.03x1.000000x1.000000x19.596%19.6%19.067%19.1%44-1.029280x-1.029280x1.03x1.000000x1.000000x12.877%12.9%12.511%12.5%45-1.033862x-1.033862x1.03x1.000000x1.000000x6.229%6.23%6.025%6.02%46-1.044246x-1.044246x1.04x1.000000x1.000000x13.260%13.3%12.698%12.7%47-1.066779x-1.066779x1.07x1.000000x1.000000x9.144%9.14%8.571%8.57%-1.066779x-1.066779x1.07x1.000000x1.000000x9.144%9.14%8.571%8.57%-1.097207x-1.097207x1.10x1.000000x1.000000x14.217%14.2%12.958%13.0%48-1.110312x-1.110312x1.11x1.000000x1.000000x13.602%13.6%12.250%12.3%49-1.156494x-1.156494x1.16x1.000000x1.000000x9.584%9.58%8.287%8.29%50
F percentage of females in category
M percentage of males in category
# rank of county out of 50 by male-to-female sex ratio

Over-Education Sex Ratio by County#61

Percentage more likely men are than women to have a professional or doctorate degree (e.g., MBA, PhD, or MD) among people aged 25 years and older.
Scope: population of Brown County, selected other counties in the United States, and entities that contain Brown County
Female
Male
1x0x1x2xFM#New Ulm AreaBrownPalm BeachSalt LakeSt. LouisOaklandMaricopaCuyahogaOrangeBexarMontgomeryPimaSuffolkRiversideDallasWestchesterTarrantFairfieldAlleghenyMidwestNassauBrowardClarkWest North CentralFranklinMecklenburgFairfaxWayneUnited StatesSanta ClaraFultonContra CostaMilwaukeeSan DiegoMinnesotaOrangeFresnoHillsboroughHarrisMiami-DadeHennepinTravisLos AngelesCookWakeAlamedaMiddlesexKingPhiladelphiaSan BernardinoHonoluluQueensSacramentoKingsNew YorkBronx-1.000000x-1.000000x2.394887x2.394887x2.39x1.287%1.29%3.082%3.08%-1.000000x-1.000000x2.394887x2.394887x2.39x1.287%1.29%3.082%3.08%-1.000000x-1.000000x2.101230x2.101230x2.10x2.942%2.94%6.181%6.18%1-1.000000x-1.000000x2.085261x2.085261x2.09x2.448%2.45%5.105%5.11%2-1.000000x-1.000000x1.898944x1.898944x1.90x3.714%3.71%7.052%7.05%3-1.000000x-1.000000x1.827444x1.827444x1.83x3.743%3.74%6.840%6.84%4-1.000000x-1.000000x1.685640x1.685640x1.69x2.336%2.34%3.937%3.94%5-1.000000x-1.000000x1.683297x1.683297x1.68x3.179%3.18%5.351%5.35%6-1.000000x-1.000000x1.678378x1.678378x1.68x2.251%2.25%3.778%3.78%7-1.000000x-1.000000x1.660749x1.660749x1.66x2.139%2.14%3.552%3.55%8-1.000000x-1.000000x1.654377x1.654377x1.65x9.490%9.49%15.700%15.7%9-1.000000x-1.000000x1.652714x1.652714x1.65x3.148%3.15%5.202%5.20%10-1.000000x-1.000000x1.626700x1.626700x1.63x3.043%3.04%4.950%4.95%11-1.000000x-1.000000x1.619416x1.619416x1.62x1.734%1.73%2.808%2.81%12-1.000000x-1.000000x1.609547x1.609547x1.61x2.346%2.35%3.776%3.78%13-1.000000x-1.000000x1.607280x1.607280x1.61x5.915%5.92%9.508%9.51%14-1.000000x-1.000000x1.602206x1.602206x1.60x1.838%1.84%2.945%2.95%15-1.000000x-1.000000x1.600562x1.600562x1.60x4.251%4.25%6.804%6.80%16-1.000000x-1.000000x1.596070x1.596070x1.60x3.932%3.93%6.276%6.28%17-1.000000x-1.000000x1.589934x1.589934x1.59x2.251%2.25%3.579%3.58%-1.000000x-1.000000x1.577713x1.577713x1.58x4.582%4.58%7.229%7.23%18-1.000000x-1.000000x1.575810x1.575810x1.58x2.760%2.76%4.350%4.35%19-1.000000x-1.000000x1.574188x1.574188x1.57x1.803%1.80%2.838%2.84%20-1.000000x-1.000000x1.572017x1.572017x1.57x2.329%2.33%3.662%3.66%-1.000000x-1.000000x1.567965x1.567965x1.57x3.409%3.41%5.346%5.35%21-1.000000x-1.000000x1.566566x1.566566x1.57x2.842%2.84%4.452%4.45%22-1.000000x-1.000000x1.562801x1.562801x1.56x6.111%6.11%9.551%9.55%23-1.000000x-1.000000x1.545600x1.545600x1.55x1.736%1.74%2.683%2.68%24-1.000000x-1.000000x1.526215x1.526215x1.53x2.660%2.66%4.060%4.06%-1.000000x-1.000000x1.513974x1.513974x1.51x4.919%4.92%7.447%7.45%25-1.000000x-1.000000x1.510882x1.510882x1.51x4.604%4.60%6.956%6.96%26-1.000000x-1.000000x1.494007x1.494007x1.49x4.011%4.01%5.992%5.99%27-1.000000x-1.000000x1.492516x1.492516x1.49x2.423%2.42%3.616%3.62%28-1.000000x-1.000000x1.488172x1.488172x1.49x3.830%3.83%5.700%5.70%29-1.000000x-1.000000x1.481015x1.481015x1.48x2.798%2.80%4.144%4.14%-1.000000x-1.000000x1.475755x1.475755x1.48x3.533%3.53%5.214%5.21%30-1.000000x-1.000000x1.471877x1.471877x1.47x1.943%1.94%2.859%2.86%31-1.000000x-1.000000x1.467166x1.467166x1.47x2.841%2.84%4.168%4.17%32-1.000000x-1.000000x1.442161x1.442161x1.44x2.749%2.75%3.965%3.96%33-1.000000x-1.000000x1.414670x1.414670x1.41x3.162%3.16%4.473%4.47%34-1.000000x-1.000000x1.413446x1.413446x1.41x4.324%4.32%6.112%6.11%35-1.000000x-1.000000x1.407975x1.407975x1.41x4.203%4.20%5.918%5.92%36-1.000000x-1.000000x1.390984x1.390984x1.39x3.031%3.03%4.216%4.22%37-1.000000x-1.000000x1.383306x1.383306x1.38x3.586%3.59%4.961%4.96%38-1.000000x-1.000000x1.367936x1.367936x1.37x4.164%4.16%5.696%5.70%39-1.000000x-1.000000x1.362517x1.362517x1.36x4.905%4.91%6.683%6.68%40-1.000000x-1.000000x1.361790x1.361790x1.36x7.280%7.28%9.914%9.91%41-1.000000x-1.000000x1.345994x1.345994x1.35x4.845%4.84%6.521%6.52%42-1.000000x-1.000000x1.341930x1.341930x1.34x3.216%3.22%4.316%4.32%43-1.000000x-1.000000x1.317072x1.317072x1.32x1.605%1.61%2.114%2.11%44-1.000000x-1.000000x1.300801x1.300801x1.30x3.459%3.46%4.499%4.50%45-1.000000x-1.000000x1.285200x1.285200x1.29x2.428%2.43%3.121%3.12%46-1.000000x-1.000000x1.281324x1.281324x1.28x2.879%2.88%3.689%3.69%47-1.000000x-1.000000x1.262281x1.262281x1.26x3.021%3.02%3.814%3.81%48-1.000000x-1.000000x1.245683x1.245683x1.25x9.673%9.67%12.050%12.1%49-1.000000x-1.000000x1.202385x1.202385x1.20x1.526%1.53%1.834%1.83%50
F percentage of females in category
M percentage of males in category
# rank of county 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

Principal City:
New Ulm
Cities:
Cobden, Comfrey, Evan, Hanska, New Ulm, Sleepy Eye, Springfield
Townships:
Albin, Bashaw, Burnstown, Cottonwood, Eden, Home, Lake Hanska, Leavenworth, Linden, Milford, Mulligan, North Star, Prairieville, Sigel, Stark, Stately
Unincorporated Places:
Searles
ZIP Codes:
55333, 56019, 56041, 56062, 56073, 56081, 56083, 56085, 56087, 56266
Unified School Districts:
Cedar Mountain, Comfrey, Madelia, New Ulm, Red Rock, Sleepy Eye, Springfield, St. James
Congressional District:
MN-1
State Senate District:
MN-16
State House District:
MN-16B
Neighboring Counties:
Blue Earth, Cottonwood, Nicollet, Redwood, Renville, Watonwan
Nearby Counties:
Emmet, Faribault, Jackson, Martin, McLeod, Meeker, Sibley