Educational Attainment in Brown County, Wisconsin (County)

Educational Attainment#1

Highest level of education among people aged 25 years and older.
Scope: population of Wisconsin and Brown County
Brown County
Wisconsin
0%10%20%30%40%50%CountHigher Degree1H.S. Diploma2No H.S. Diploma240.567299%38.686675%40.567299%40.6%68,87868.9k50.830747%52.676105%50.830747%50.8%86,30486.3k8.601954%8.637220%8.601954%8.6%14,60514.6k
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 Wisconsin at large.
Scope: population of Wisconsin and Brown County
-4%-2%0%+2%+4%%ref.Higher Degree1H.S. Diploma2No H.S. Diploma24.861168%4.861168%+4.9%40.567%40.6%38.687%38.7%-3.503217%-3.503217%-3.5%50.831%50.8%52.676%52.7%-0.408301%-0.408301%-0.4%8.602%8.60%8.637%8.64%
% percentage with given level in Brown County
ref. percentage with given level in Wisconsin
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 Wisconsin and Brown County
Brown County
Wisconsin
0%5%10%15%20%25%30%CountDoctorate1Professional1Master's1Bachelor's1Associate's1Some CollegeHigh School2Some H.S.3Less than H.S.3None0.615477%1.094506%0.615477%0.6%1,0451.456531%1.609379%1.456531%1.5%2,4735.844970%6.922399%5.844970%5.8%9,92420.326645%18.747154%20.326645%20.3%34,51234.5k12.323676%10.313236%12.323676%12.3%20,92420.9k19.558623%20.983992%19.558623%19.6%33,20833.2k31.272123%31.692113%31.272123%31.3%53,09653.1k5.251874%5.657202%5.251874%5.3%8,9172.308775%2.130908%2.308775%2.3%3,9201.041305%0.849110%1.041305%1.0%1,768
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 Wisconsin at large.
Scope: population of Wisconsin and Brown County
-40%-20%-0%+20%+40%%ref.Doctorate1Professional1Master's1Bachelor's1Associate's1Some CollegeHigh School2Some H.S.3Less than H.S.3None-43.766700%-43.766700%-43.8%0.615%0.62%1.095%1.09%-9.497349%-9.497349%-9.5%1.457%1.46%1.609%1.61%-15.564384%-15.564384%-15.6%5.845%5.84%6.922%6.92%8.425229%8.425229%+8.4%20.327%20.3%18.747%18.7%19.493786%19.493786%+19.5%12.324%12.3%10.313%10.3%-6.792646%-6.792646%-6.8%19.559%19.6%20.984%21.0%-1.325220%-1.325220%-1.3%31.272%31.3%31.692%31.7%-7.164813%-7.164813%-7.2%5.252%5.25%5.657%5.66%8.347011%8.347011%+8.3%2.309%2.31%2.131%2.13%22.634877%22.634877%+22.6%1.041%1.04%0.849%0.85%
% percentage with given level in Brown County
ref. percentage with given level in Wisconsin
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 Wisconsin and Brown County
More Females More Males
Wisconsin
Brown County
0%10%20%FMHigher Degree1H.S. Diploma2No H.S. Diploma2-2.688512%-9.820753%-2.688512%3%41.095%41.1%40.019%40.0%-1.483048%-1.483048%1%3.687318%51.198%51.2%50.450%50.4%23.668046%21.929118%23.668046%24%7.707%7.71%9.531%9.53%
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 Wisconsin and Brown County
More Females More Males
Wisconsin
Brown County
20%0%20%40%60%FMDoctorate1Professional1Master's1Bachelor's1Associate's1Some CollegeHigh School2Some H.S.3Less than H.S.3None66.089404%49.112245%66.089404%66%0.465%0.46%0.772%0.77%76.502209%63.725126%76.502209%77%1.059%1.06%1.869%1.87%-25.492063%-26.714257%-25.492063%25%6.492%6.49%5.173%5.17%-8.454394%-10.314398%-8.454394%8%21.135%21.1%19.487%19.5%-14.230343%6.471560%6.471560%6%11.944%11.9%12.717%12.7%-4.717945%-1.828461%-4.717945%5%20.001%20.0%19.100%19.1%0.490161%7.484254%0.490161%0%31.197%31.2%31.350%31.4%25.407916%27.756322%25.407916%25%4.670%4.67%5.856%5.86%6.412666%11.346432%6.412666%6%2.238%2.24%2.382%2.38%61.843277%12.366663%61.843277%62%0.799%0.80%1.293%1.29%
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 Wisconsin and Brown County
Brown County
Wisconsin
0%5%10%15%20%25%B.X.Total65+45-6435-4425-3412.290853%12.755764%12.290853%12.3%4,12133,52933.5k19.386034%17.674080%19.386034%19.4%13,33113.3k68,76668.8k24.855921%22.171538%24.855921%24.9%8,02232,27432.3k25.663013%25.037795%25.663013%25.7%9,03835,21835.2k
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 Wisconsin at large.
Scope: population of Wisconsin and Brown County
0%5%10%%ref.65+45-6435-4425-34-3.644717%-3.644717%3.6%12.291%12.3%12.756%12.8%9.686238%9.686238%9.7%19.386%19.4%17.674%17.7%12.107340%12.107340%12.1%24.856%24.9%22.172%22.2%2.497096%2.497096%2.5%25.663%25.7%25.038%25.0%
% percentage in Brown County with a Bachelor's degree
ref percentage in Wisconsin 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 Wisconsin and Brown County
More Females More Males
Wisconsin
Brown County
30%20%10%0%10%FM65+45-6435-4425-3417.211180%15.252186%17.211180%17.2%11.428%11.4%13.394%13.4%-11.318408%-8.291196%-11.318408%11.3%20.418%20.4%18.342%18.3%-1.389225%-22.719305%-1.389225%1.4%25.030%25.0%24.687%24.7%-35.058172%-29.514910%-35.058172%35.1%29.594%29.6%21.912%21.9%
F female degree holders as a percentage of all females
M male degree holders as a percentage of all males

Median Earnings by Educational Attainment#10

Among population 25 years old and over with earnings.
Scope: population of Wisconsin and Brown County
Brown County
Wisconsin
$0k$20k$40k$60kCount%Graduate Degree1Bachelor's DegreeSome CollegeH.S. Diploma2No H.S. Diploma2Total$61,103.000000$61,842.000000$61,103.000000$61.1k13,44213.4k7.917%7.92%$48,411.000000$48,286.000000$48,411.000000$48.4k34,51234.5k20.327%20.3%$35,251.000000$34,771.000000$35,251.000000$35.3k54,13254.1k31.882%31.9%$30,328.000000$30,475.000000$30,328.000000$30.3k53,09653.1k31.272%31.3%$24,793.000000$22,317.000000$24,793.000000$24.8k14,60514.6k8.602%8.60%$36,932.000000$36,855.000000$36,932.000000$36.9k169,787170k100.000%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 Wisconsin and Brown County
Female Male
Wisconsin
Brown County
Shaded bar tips show excess over facing bar.
$50k$0k$50kFMGraduate Degree1Bachelor's DegreeSome CollegeH.S. Diploma2No H.S. Diploma2Total$-53,960.000000$-55,037.000000$-53,960.000000$54.0k$53,960.000000$20,305.000000$55,037.000000$18,141.000000$74,265.000000$74.3k6,9336,509$-40,560.000000$-40,915.000000$-40,560.000000$40.6k$40,560.000000$20,780.000000$40,915.000000$18,355.000000$61,340.000000$61.3k18,28018.3k16,23216.2k$-29,002.000000$-28,362.000000$-29,002.000000$29.0k$29,002.000000$13,952.000000$28,362.000000$14,055.000000$42,954.000000$43.0k27,63027.6k26,50226.5k$-23,721.000000$-23,872.000000$-23,721.000000$23.7k$23,721.000000$12,614.000000$23,872.000000$12,519.000000$36,335.000000$36.3k26,98327.0k26,11326.1k$-18,048.000000$-16,775.000000$-18,048.000000$18.0k$18,048.000000$9,205.000000$16,775.000000$9,472.000000$27,253.000000$27.3k6,6667,939$-30,906.000000$-30,829.000000$-30,906.000000$30.9k$30,906.000000$12,327.000000$30,829.000000$12,328.000000$43,233.000000$43.2k86,49286.5k83,29583.3k
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 Wisconsin and Brown County
Brown County
Wisconsin
0%10%20%30%40%50%60%CountBachelor's Degree1Some College2H.S. Diploma3No H.S. Diploma340.000000%32.763533%40.000000%40.0%2460.000000%54.226021%60.000000%60.0%360.000000%0.000000%0.0%12.203229%00.000000%0.000000%0.0%0.807217%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 Wisconsin and Brown County
Brown County
Wisconsin
0%20%40%60%80%CountBachelor's Degree1Some College2H.S. Diploma3No H.S. Diploma387.434313%85.899471%87.434313%87.4%35,93935.9k81.330412%79.335494%81.330412%81.3%37,86537.9k73.234681%73.240943%73.234681%73.2%27,76427.8k55.352798%53.971506%55.352798%55.4%5,915
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 Wisconsin and Brown County
Female Male
Wisconsin
Brown County
Shaded bar tips show excess over facing bar.
20%0%20%40%MFWhite1BlackAsianHispanic2Other1-5.354217%-5.697819%-5.354217%5.4%5.354217%1.180940%5.697819%1.469036%6.535157%6.5%4,7014,085-11.305071%-17.429079%-11.305071%11.3%11.305071%2.215210%17.429079%2.936718%13.520280%13.5%270136-17.422313%-3.871360%-14.441272%-4.641233%-21.293673%21.3%17.422313%14.441272%17.422313%17.4%342451-37.393703%-31.307944%-37.393703%37.4%37.393703%7.009282%31.307944%5.178771%44.402985%44.4%2,2611,627-27.580546%-22.693686%-27.580546%27.6%27.580546%1.326983%22.693686%3.979967%28.907529%28.9%1,4131,344
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 Wisconsin and Brown County
Female Male
Wisconsin
Brown County
Shaded bar tips show excess over facing bar.
40%20%0%20%40%MFWhite1BlackAsianHispanic2Other1-29.100286%-1.435135%-28.711494%-2.079187%-30.535422%30.5%29.100286%28.711494%29.100286%29.1%20,93320.9k23,29723.3k-12.551953%-11.717867%-3.588054%-12.551953%12.6%12.551953%3.772533%11.717867%16.324487%16.3%326151-32.813975%-44.377167%-32.813975%32.8%32.813975%1.877823%44.377167%4.100638%34.691798%34.7%681695-7.875098%-2.927016%-10.433533%-4.583778%-10.802114%10.8%7.875098%10.433533%7.875098%7.9%401470-11.783961%-3.093938%-13.316792%-4.610459%-14.877899%14.9%11.783961%13.316792%11.783961%11.8%576725
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
25%31%37%44%50%56%

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
41.2%45.8%50.3%54.9%59.4%64.0%

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
0.8%3.4%5.9%8.4%11.0%13.5%

Detailed: Doctorate Degree Educational Attainment by County Subdivision#19

Percentage of the population 25 years and older with given highest level of educational attainment
0.00%0.46%0.93%1.39%1.85%2.32%

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%1.0%2.0%3.0%4.0%5.1%

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
1.3%3.3%5.3%7.2%9.2%11.2%

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
8.9%13.1%17.2%21.4%25.5%29.7%

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
9.2%10.8%12.3%13.8%15.3%16.9%

Detailed: Some College Educational Attainment by County Subdivision#24

Percentage of the population 25 years and older with given highest level of educational attainment
14.9%17.7%20.5%23.2%26.0%28.8%

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
21%27%32%37%42%48%

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
0.8%2.5%4.0%5.6%7.2%8.8%

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%0.8%1.7%2.5%3.3%4.2%

Detailed: None Educational Attainment by County Subdivision#28

Percentage of the population 25 years and older with given highest level of educational attainment
0.00%0.35%0.71%1.06%1.42%1.77%
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
0%13%26%39%52%65%

Coarse: High School Diploma Educational Attainment by Tract#30

Percentage of the population 25 years and older with given highest level of educational attainment
33%40%47%54%61%68%

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
1%8%14%20%26%33%

Detailed: Doctorate Degree Educational Attainment by Tract#32

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: Professional Degree Educational Attainment by Tract#33

Percentage of the population 25 years and older with given highest level of educational attainment
0.0%1.3%2.6%3.9%5.2%6.6%

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

Percentage of the population 25 years and older with given highest level of educational attainment
0.0%2.5%5.0%7.5%10.0%12.5%

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

Percentage of the population 25 years and older with given highest level of educational attainment
0%7%15%22%30%38%

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

Percentage of the population 25 years and older with given highest level of educational attainment
0.0%3.5%6.9%10.4%13.9%17.4%

Detailed: Some College Educational Attainment by Tract#37

Percentage of the population 25 years and older with given highest level of educational attainment
9.1%12.5%15.9%19.3%22.7%26.1%

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
15%24%33%41%50%59%

Detailed: Some High School Educational Attainment by Tract#39

Percentage of the population 25 years and older with given highest level of educational attainment
0.7%4.5%8.3%12.1%16.0%19.8%

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

Percentage of the population 25 years and older with given highest level of educational attainment
0.0%2.7%5.4%8.0%10.7%13.4%

Detailed: None Educational Attainment by Tract#41

Percentage of the population 25 years and older with given highest level of educational attainment
0.0%1.0%2.0%3.0%4.0%5.1%
Road Data ©OpenStreetMap

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Educational Attainment by Place in Brown County

There are 13 places that are fully or partially contained within Brown County (9 fully and 4 partially). This section compares all 13 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%Count#GreenleafUnited States of AmericaUnited StatesGreen BayEast North CentralMidwestDenmarkBellevueGreen Bay Metro AreaGreen BayWisconsinBrown CountyBrownAllouezHobartAshwaubenonHowardWrightstownDe PerePulaskiSuamicoDyckesville18.421053%18.421053%18.4%91113.020590%13.020590%13.0%27,818,38027.8M12.535944%12.535944%12.5%8,414210.719464%10.719464%10.7%3,363,7843.36M10.244520%10.244520%10.2%4,641,8354.64M9.357143%9.357143%9.4%13139.323378%9.323378%9.3%99948.685969%8.685969%8.7%18,36918.4k8.637220%8.637220%8.6%336,096336k8.601954%8.601954%8.6%14,60514.6k8.512097%8.512097%8.5%86956.319703%6.319703%6.3%30666.168099%6.168099%6.2%73976.065319%6.065319%6.1%78085.063291%5.063291%5.1%10493.911088%3.911088%3.9%600103.898305%3.898305%3.9%92113.395282%3.395282%3.4%285121.477833%1.477833%1.5%613
Count number of people in category
# rank of place out of 13 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%40%50%Count#DyckesvilleHobartAllouezDe PereSuamicoWrightstownUnited States of AmericaUnited StatesMidwestHowardEast North CentralWisconsinBrown CountyBrownAshwaubenonGreen Bay Metro AreaGreen BayBellevueGreen BayPulaskiDenmarkGreenleaf50.738916%50.738916%50.7%206141.821561%41.821561%41.8%2,025236.575571%36.575571%36.6%3,734336.151489%36.151489%36.2%5,546434.774839%34.774839%34.8%2,919531.791626%31.791626%31.8%653630.315023%30.315023%30.3%64,767,78764.8M28.952816%28.952816%29.0%13,118,64213.1M28.794712%28.794712%28.8%3,703728.462853%28.462853%28.5%8,931,6868.93M28.373439%28.373439%28.4%1,104,0821.10M28.243623%28.243623%28.2%47,95448.0k26.525332%26.525332%26.5%3,178825.916521%25.916521%25.9%54,80854.8k24.965002%24.965002%25.0%2,675924.139215%24.139215%24.1%16,20216.2k1022.245763%22.245763%22.2%5251120.142857%20.142857%20.1%282129.109312%9.109312%9.1%4513
Count number of people in category
# rank of place out of 13 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#AllouezUnited States of AmericaUnited StatesHobartDe PereMidwestEast North CentralWisconsinSuamicoDyckesvilleBrown CountyBrownGreen Bay Metro AreaGreen BayWrightstownGreen BayHowardAshwaubenonBellevuePulaskiDenmarkGreenleaf4.358899%4.358899%4.4%44513.336158%3.336158%3.3%7,127,6737.13M3.118546%3.118546%3.1%15123.083241%3.083241%3.1%47332.893416%2.893416%2.9%1,311,0191.31M2.855432%2.855432%2.9%896,039896k2.703886%2.703886%2.7%105,215105k2.406481%2.406481%2.4%20242.216749%2.216749%2.2%952.072008%2.072008%2.1%3,5181.879146%1.879146%1.9%3,9741.801363%1.801363%1.8%3761.777440%1.777440%1.8%1,19371.384137%1.384137%1.4%17880.784576%0.784576%0.8%9490.765282%0.765282%0.8%82100.000000%0.000000%0.0%0110.000000%0.000000%0.0%0120.000000%0.000000%0.0%013
Count number of people in category
# rank of place out of 13 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
0x5x10xFM#DyckesvilleDenmarkDe PereGreen BayGreen BayBrownWisconsinMidwestEast North CentralUnited StatesSuamicoHowardGreenleafWrightstownAllouezAshwaubenonBellevueHobartPulaski-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%2.830%2.83%1-1.000000x-1.000000x2.355563x2.355563x2.36x5.699%5.70%13.424%13.4%2-1.000000x-1.000000x2.147134x2.147134x2.15x2.553%2.55%5.481%5.48%3-1.000000x-1.000000x1.408197x1.408197x1.41x10.435%10.4%14.694%14.7%4-1.000000x-1.000000x1.245810x1.245810x1.25x7.746%7.75%9.650%9.65%-1.000000x-1.000000x1.236680x1.236680x1.24x7.707%7.71%9.531%9.53%-1.000000x-1.000000x1.219291x1.219291x1.22x7.799%7.80%9.509%9.51%-1.000000x-1.000000x1.127915x1.127915x1.13x9.647%9.65%10.881%10.9%-1.000000x-1.000000x1.125371x1.125371x1.13x10.108%10.1%11.375%11.4%-1.000000x-1.000000x1.109070x1.109070x1.11x12.369%12.4%13.719%13.7%-1.000000x-1.000000x1.058399x1.058399x1.06x3.299%3.30%3.492%3.49%5-1.000000x-1.000000x1.056613x1.056613x1.06x5.903%5.90%6.237%6.24%6-1.137678x-1.137678x1.14x1.000000x1.000000x19.731%19.7%17.343%17.3%7-1.212699x-1.212699x1.21x1.000000x1.000000x5.540%5.54%4.568%4.57%8-1.228382x-1.228382x1.23x1.000000x1.000000x9.398%9.40%7.651%7.65%9-1.237978x-1.237978x1.24x1.000000x1.000000x6.794%6.79%5.488%5.49%10-1.346928x-1.346928x1.35x1.000000x1.000000x10.654%10.7%7.910%7.91%11-1.466824x-1.466824x1.47x1.000000x1.000000x7.457%7.46%5.084%5.08%12-1.742878x-1.742878x1.74x1.000000x1.000000x4.780%4.78%2.742%2.74%13
F percentage of females in category
M percentage of males in category
# rank of place out of 13 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
1x0x1x2xFM#HowardGreen BayAllouezDyckesvilleBrownGreen BaySuamicoEast North CentralMidwestWisconsinUnited StatesDe PereWrightstownAshwaubenonHobartBellevue-1.000000x-1.000000x2.492011x2.492011x2.49x0.802%0.80%1.999%2.00%1-1.000000x-1.000000x2.006236x2.006236x2.01x1.188%1.19%2.383%2.38%2-1.000000x-1.000000x1.991366x1.991366x1.99x2.901%2.90%5.777%5.78%3-1.000000x-1.000000x1.830189x1.830189x1.83x1.546%1.55%2.830%2.83%4-1.000000x-1.000000x1.733262x1.733262x1.73x1.524%1.52%2.641%2.64%-1.000000x-1.000000x1.720824x1.720824x1.72x1.386%1.39%2.385%2.38%-1.000000x-1.000000x1.601911x1.601911x1.60x1.851%1.85%2.966%2.97%5-1.000000x-1.000000x1.597848x1.597848x1.60x2.216%2.22%3.541%3.54%-1.000000x-1.000000x1.589934x1.589934x1.59x2.251%2.25%3.579%3.58%-1.000000x-1.000000x1.576114x1.576114x1.58x2.109%2.11%3.323%3.32%-1.000000x-1.000000x1.526215x1.526215x1.53x2.660%2.66%4.060%4.06%-1.000000x-1.000000x1.363936x1.363936x1.36x2.638%2.64%3.598%3.60%6-1.000000x-1.000000x1.097484x1.097484x1.10x1.719%1.72%1.887%1.89%7-1.623043x-1.623043x1.62x1.000000x1.000000x0.961%0.96%0.592%0.59%8-1.653790x-1.653790x1.65x1.000000x1.000000x3.848%3.85%2.327%2.33%9-1.720627x-1.720627x1.72x1.000000x1.000000x0.960%0.96%0.558%0.56%10
F percentage of females in category
M percentage of males in category
# rank of place out of 10 by male-to-female sex ratio

Educational Attainment by County Subdivision in Brown County

There are 24 county subdivisions in Brown County. This section compares all 24 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%Count#Town of MorrisonMorrisonUnited States of AmericaUnited StatesGreen BayEast North CentralTown of HumboldtHumboldtMidwestTown of HollandHollandTown of WrightstownWrightstownDenmarkBellevueTown of EatonGreen Bay Metro AreaGreen BayWisconsinBrown CountyBrownAllouezTown of ScottTown of Green BayGrn BayHobartAshwaubenonHowardTown of GlenmoreGlenmoreWrightstownTown of New DenmarkNew DenmarkTown of RocklandRocklandTown of PittsfieldPittsfieldPulaskiDe PereSuamicoTown of LedgeviewLedgeviewTown of LawrenceLawrence13.487476%13.487476%13.5%140113.020590%13.020590%13.0%27,818,38027.8M12.535944%12.535944%12.5%8,414210.719464%10.719464%10.7%3,363,7843.36M10.662177%10.662177%10.7%95310.244520%10.244520%10.2%4,641,8354.64M10.227273%10.227273%10.2%9949.711286%9.711286%9.7%14859.357143%9.357143%9.4%13169.323378%9.323378%9.3%99979.176030%9.176030%9.2%9888.685969%8.685969%8.7%18,36918.4k8.637220%8.637220%8.6%336,096336k8.601954%8.601954%8.6%14,60514.6k8.512097%8.512097%8.5%86996.977598%6.977598%7.0%190106.866077%6.866077%6.9%101116.319703%6.319703%6.3%306126.168099%6.168099%6.2%739136.065319%6.065319%6.1%780145.790109%5.790109%5.8%48155.394191%5.394191%5.4%104164.878049%4.878049%4.9%50174.506803%4.506803%4.5%53184.465710%4.465710%4.5%84194.051079%4.051079%4.1%92203.911088%3.911088%3.9%600213.395282%3.395282%3.4%285223.142019%3.142019%3.1%150230.893123%0.893123%0.9%3024
Count number of people in category
# rank of county subdivision out of 24 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%40%Count#Town of LedgeviewLedgeviewHobartAllouezDe PereTown of LawrenceLawrenceSuamicoTown of RocklandRocklandWrightstownUnited States of AmericaUnited StatesTown of PittsfieldPittsfieldMidwestHowardEast North CentralWisconsinBrown CountyBrownAshwaubenonGreen Bay Metro AreaGreen BayTown of Green BayGrn BayBellevueTown of ScottGreen BayPulaskiTown of New DenmarkNew DenmarkDenmarkTown of GlenmoreGlenmoreTown of WrightstownWrightstownTown of EatonTown of HollandHollandTown of HumboldtHumboldtTown of MorrisonMorrison45.831588%45.831588%45.8%2,188141.821561%41.821561%41.8%2,025236.575571%36.575571%36.6%3,734336.151489%36.151489%36.2%5,546435.695147%35.695147%35.7%1,199534.774839%34.774839%34.8%2,919631.717687%31.717687%31.7%373730.757261%30.757261%30.8%593830.315023%30.315023%30.3%64,767,78764.8M29.346093%29.346093%29.3%552928.952816%28.952816%29.0%13,118,64213.1M28.794712%28.794712%28.8%3,7031028.462853%28.462853%28.5%8,931,6868.93M28.373439%28.373439%28.4%1,104,0821.10M28.243623%28.243623%28.2%47,95448.0k26.525332%26.525332%26.5%3,1781125.916521%25.916521%25.9%54,80854.8k25.900748%25.900748%25.9%3811224.965002%24.965002%25.0%2,6751324.935733%24.935733%24.9%6791424.139215%24.139215%24.1%16,20216.2k1521.664465%21.664465%21.7%4921620.878049%20.878049%20.9%2141720.142857%20.142857%20.1%2821819.662244%19.662244%19.7%1631919.553806%19.553806%19.6%2982016.573034%16.573034%16.6%1772115.599174%15.599174%15.6%1512212.008979%12.008979%12.0%1072311.849711%11.849711%11.8%12324
Count number of people in category
# rank of county subdivision out of 24 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%5%Count#Town of LawrenceLawrenceTown of LedgeviewLedgeviewAllouezTown of ScottTown of RocklandRocklandUnited States of AmericaUnited StatesHobartDe PereMidwestEast North CentralWisconsinSuamicoBrown CountyBrownTown of PittsfieldPittsfieldGreen Bay Metro AreaGreen BayGreen BayTown of Green BayGrn BayWrightstownHowardTown of WrightstownWrightstownTown of New DenmarkNew DenmarkAshwaubenonBellevueTown of EatonTown of MorrisonMorrisonTown of GlenmoreGlenmoreTown of HollandHollandPulaskiDenmarkTown of HumboldtHumboldt5.180113%5.180113%5.2%17415.027231%5.027231%5.0%24024.358899%4.358899%4.4%44533.782593%3.782593%3.8%10343.401361%3.401361%3.4%4053.336158%3.336158%3.3%7,127,6737.13M3.118546%3.118546%3.1%15163.083241%3.083241%3.1%47372.893416%2.893416%2.9%1,311,0191.31M2.855432%2.855432%2.9%896,039896k2.703886%2.703886%2.7%105,215105k2.406481%2.406481%2.4%20282.072008%2.072008%2.1%3,5181.913876%1.913876%1.9%3691.879146%1.879146%1.9%3,9741.777440%1.777440%1.8%1,193101.699524%1.699524%1.7%25111.504149%1.504149%1.5%29121.384137%1.384137%1.4%178131.246719%1.246719%1.2%19140.878049%0.878049%0.9%9150.784576%0.784576%0.8%94160.765282%0.765282%0.8%82170.749064%0.749064%0.7%8180.674374%0.674374%0.7%7190.603136%0.603136%0.6%5200.516529%0.516529%0.5%5210.000000%0.000000%0.0%0220.000000%0.000000%0.0%0230.000000%0.000000%0.0%024
Count number of people in category
# rank of county subdivision out of 24 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
10x5x0xFM#RocklandPittsfieldDenmarkGlenmoreDe PereTown of ScottNew DenmarkHollandTown of EatonGreen BayHumboldtGreen BayBrownWisconsinMidwestEast North CentralUnited StatesWrightstownSuamicoHowardLedgeviewMorrisonGrn BayAllouezWrightstownAshwaubenonBellevueHobartPulaskiLawrence-1.000000x-1.000000x2.953846x2.953846x2.95x2.257%2.26%6.667%6.67%1-1.000000x-1.000000x2.518677x2.518677x2.52x2.542%2.54%6.403%6.40%2-1.000000x-1.000000x2.355563x2.355563x2.36x5.699%5.70%13.424%13.4%3-1.000000x-1.000000x2.259169x2.259169x2.26x3.571%3.57%8.068%8.07%4-1.000000x-1.000000x2.147134x2.147134x2.15x2.553%2.55%5.481%5.48%5-1.000000x-1.000000x2.063668x2.063668x2.06x4.460%4.46%9.204%9.20%6-1.000000x-1.000000x1.837743x1.837743x1.84x3.455%3.45%6.349%6.35%7-1.000000x-1.000000x1.640228x1.640228x1.64x7.606%7.61%12.476%12.5%8-1.000000x-1.000000x1.440913x1.440913x1.44x7.486%7.49%10.786%10.8%9-1.000000x-1.000000x1.408197x1.408197x1.41x10.435%10.4%14.694%14.7%10-1.000000x-1.000000x1.363631x1.363631x1.36x8.986%8.99%12.254%12.3%11-1.000000x-1.000000x1.245810x1.245810x1.25x7.746%7.75%9.650%9.65%-1.000000x-1.000000x1.236680x1.236680x1.24x7.707%7.71%9.531%9.53%-1.000000x-1.000000x1.219291x1.219291x1.22x7.799%7.80%9.509%9.51%-1.000000x-1.000000x1.127915x1.127915x1.13x9.647%9.65%10.881%10.9%-1.000000x-1.000000x1.125371x1.125371x1.13x10.108%10.1%11.375%11.4%-1.000000x-1.000000x1.109070x1.109070x1.11x12.369%12.4%13.719%13.7%-1.000000x-1.000000x1.088361x1.088361x1.09x9.280%9.28%10.100%10.1%12-1.000000x-1.000000x1.058399x1.058399x1.06x3.299%3.30%3.492%3.49%13-1.000000x-1.000000x1.056613x1.056613x1.06x5.903%5.90%6.237%6.24%14-1.069705x-1.069705x1.07x1.000000x1.000000x3.246%3.25%3.034%3.03%15-1.095584x-1.095584x1.10x1.000000x1.000000x14.095%14.1%12.865%12.9%16-1.178462x-1.178462x1.18x1.000000x1.000000x7.461%7.46%6.331%6.33%17-1.228382x-1.228382x1.23x1.000000x1.000000x9.398%9.40%7.651%7.65%18-1.229865x-1.229865x1.23x1.000000x1.000000x5.943%5.94%4.832%4.83%19-1.237978x-1.237978x1.24x1.000000x1.000000x6.794%6.79%5.488%5.49%20-1.346928x-1.346928x1.35x1.000000x1.000000x10.654%10.7%7.910%7.91%21-1.466824x-1.466824x1.47x1.000000x1.000000x7.457%7.46%5.084%5.08%22-1.735089x-1.735089x1.74x1.000000x1.000000x4.957%4.96%2.857%2.86%23-10.000000x-10.000000x> 10.0x1.000000x1.000000x1.877%1.88%0.000%0%24
F percentage of females in category
M percentage of males in category
# rank of county subdivision out of 24 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
0x5x10xFM#New DenmarkGlenmoreTown of ScottHollandMorrisonWrightstownHowardLedgeviewLawrenceGreen BayAllouezBrownGreen BaySuamicoEast North CentralMidwestTown of EatonWisconsinUnited StatesRocklandDe PereWrightstownPittsfieldGrn BayAshwaubenonHobartBellevue-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%1.786%1.79%1-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%1.222%1.22%2-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.548%0.55%6.644%6.64%3-1.000000x-1.000000x3.431862x3.431862x3.43x0.224%0.22%0.768%0.77%4-1.000000x-1.000000x2.558480x2.558480x2.56x0.381%0.38%0.975%0.97%5-1.000000x-1.000000x2.520698x2.520698x2.52x0.693%0.69%1.746%1.75%6-1.000000x-1.000000x2.492011x2.492011x2.49x0.802%0.80%1.999%2.00%7-1.000000x-1.000000x2.041817x2.041817x2.04x3.328%3.33%6.795%6.79%8-1.000000x-1.000000x2.016531x2.016531x2.02x3.379%3.38%6.814%6.81%9-1.000000x-1.000000x2.006236x2.006236x2.01x1.188%1.19%2.383%2.38%10-1.000000x-1.000000x1.991366x1.991366x1.99x2.901%2.90%5.777%5.78%11-1.000000x-1.000000x1.733262x1.733262x1.73x1.524%1.52%2.641%2.64%-1.000000x-1.000000x1.720824x1.720824x1.72x1.386%1.39%2.385%2.38%-1.000000x-1.000000x1.601911x1.601911x1.60x1.851%1.85%2.966%2.97%12-1.000000x-1.000000x1.597848x1.597848x1.60x2.216%2.22%3.541%3.54%-1.000000x-1.000000x1.589934x1.589934x1.59x2.251%2.25%3.579%3.58%-1.000000x-1.000000x1.587447x1.587447x1.59x0.576%0.58%0.914%0.91%13-1.000000x-1.000000x1.576114x1.576114x1.58x2.109%2.11%3.323%3.32%-1.000000x-1.000000x1.526215x1.526215x1.53x2.660%2.66%4.060%4.06%-1.000000x-1.000000x1.440000x1.440000x1.44x2.778%2.78%4.000%4.00%14-1.000000x-1.000000x1.363936x1.363936x1.36x2.638%2.64%3.598%3.60%15-1.000000x-1.000000x1.261797x1.261797x1.26x1.332%1.33%1.681%1.68%16-1.000000x-1.000000x1.259338x1.259338x1.26x1.695%1.69%2.134%2.13%17-1.025052x-1.025052x1.03x1.000000x1.000000x1.722%1.72%1.680%1.68%18-1.623043x-1.623043x1.62x1.000000x1.000000x0.961%0.96%0.592%0.59%19-1.653790x-1.653790x1.65x1.000000x1.000000x3.848%3.85%2.327%2.33%20-1.720627x-1.720627x1.72x1.000000x1.000000x0.960%0.96%0.558%0.56%21
F percentage of females in category
M percentage of males in category
# rank of county subdivision out of 21 by male-to-female sex ratio

Educational Attainment by County in the Green Bay Area

There are 3 counties in the Green Bay Area. This section compares Brown County to all of the counties in the Green Bay Area and to those entities that contain or substantially overlap with Brown County.

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 the Green Bay Area, and entities that contain Brown County
0%5%10%Count#United States of AmericaUnited StatesEast North CentralMidwestOconto CountyOcontoGreen Bay Metro AreaGreen BayWisconsinBrown CountyBrownKewaunee CountyKewaunee13.020590%13.020590%13.0%27,818,38027.8M10.719464%10.719464%10.7%3,363,7843.36M10.244520%10.244520%10.2%4,641,8354.64M9.607260%9.607260%9.6%2,61518.685969%8.685969%8.7%18,36918.4k8.637220%8.637220%8.6%336,096336k8.601954%8.601954%8.6%14,60514.6k27.938921%7.938921%7.9%1,1493
Count number of people in category
# rank of county out of 3 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 the Green Bay Area, and entities that contain Brown County
0%10%20%30%Count#United States of AmericaUnited StatesMidwestEast North CentralWisconsinBrown CountyBrownGreen Bay Metro AreaGreen BayKewaunee CountyKewauneeOconto CountyOconto30.315023%30.315023%30.3%64,767,78764.8M28.952816%28.952816%29.0%13,118,64213.1M28.462853%28.462853%28.5%8,931,6868.93M28.373439%28.373439%28.4%1,104,0821.10M28.243623%28.243623%28.2%47,95448.0k125.916521%25.916521%25.9%54,80854.8k16.900435%16.900435%16.9%2,446216.194570%16.194570%16.2%4,4083
Count number of people in category
# rank of county out of 3 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 the Green Bay Area, and entities that contain Brown County
0%1%2%3%Count#United States of AmericaUnited StatesMidwestEast North CentralWisconsinBrown CountyBrownGreen Bay Metro AreaGreen BayKewaunee CountyKewauneeOconto CountyOconto3.336158%3.336158%3.3%7,127,6737.13M2.893416%2.893416%2.9%1,311,0191.31M2.855432%2.855432%2.9%896,039896k2.703886%2.703886%2.7%105,215105k2.072008%2.072008%2.1%3,51811.879146%1.879146%1.9%3,9741.126235%1.126235%1.1%16321.076454%1.076454%1.1%2933
Count number of people in category
# rank of county out of 3 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 the Green Bay Area, and entities that contain Brown County
Female
Male
1x0x1xFM#OcontoGreen BayBrownWisconsinMidwestEast North CentralUnited StatesKewaunee-1.000000x-1.000000x1.374304x1.374304x1.37x8.070%8.07%11.091%11.1%1-1.000000x-1.000000x1.245810x1.245810x1.25x7.746%7.75%9.650%9.65%-1.000000x-1.000000x1.236680x1.236680x1.24x7.707%7.71%9.531%9.53%2-1.000000x-1.000000x1.219291x1.219291x1.22x7.799%7.80%9.509%9.51%-1.000000x-1.000000x1.127915x1.127915x1.13x9.647%9.65%10.881%10.9%-1.000000x-1.000000x1.125371x1.125371x1.13x10.108%10.1%11.375%11.4%-1.000000x-1.000000x1.109070x1.109070x1.11x12.369%12.4%13.719%13.7%-1.000000x-1.000000x1.085821x1.085821x1.09x7.611%7.61%8.264%8.26%3
F percentage of females in category
M percentage of males in category
# rank of county out of 3 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 the Green Bay Area, and entities that contain Brown County
Female
Male
1x0x1x2x3x4xFM#KewauneeBrownGreen BayEast North CentralMidwestWisconsinUnited StatesOconto-1.000000x-1.000000x4.790215x4.790215x4.79x0.388%0.39%1.860%1.86%1-1.000000x-1.000000x1.733262x1.733262x1.73x1.524%1.52%2.641%2.64%2-1.000000x-1.000000x1.720824x1.720824x1.72x1.386%1.39%2.385%2.38%-1.000000x-1.000000x1.597848x1.597848x1.60x2.216%2.22%3.541%3.54%-1.000000x-1.000000x1.589934x1.589934x1.59x2.251%2.25%3.579%3.58%-1.000000x-1.000000x1.576114x1.576114x1.58x2.109%2.11%3.323%3.32%-1.000000x-1.000000x1.526215x1.526215x1.53x2.660%2.66%4.060%4.06%-1.000000x-1.000000x1.084340x1.084340x1.08x1.032%1.03%1.119%1.12%3
F percentage of females in category
M percentage of males in category
# rank of county out of 3 by male-to-female sex ratio

Educational Attainment by County in Wisconsin

There are 72 counties in Wisconsin. This section compares Brown County to the 50 most populous counties in Wisconsin and to those entities that contain or substantially overlap with Brown County. The least populous of the compared counties has a population of 20,566.

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 Wisconsin, and entities that contain Brown County
0%5%10%15%Count#Clark CountyClarkJuneau CountyJuneauWaushara CountyWausharaMilwaukee CountyMilwaukeeUnited States of AmericaUnited StatesVernon CountyVernonJackson CountyJacksonRacine CountyRacineDodge CountyDodgeEast North CentralRock CountyRockTrempealeau CountyTrempealeauMidwestBarron CountyBarronKenosha CountyKenoshaMonroe CountyMonroeLincoln CountyLincolnOconto CountyOcontoShawano CountyShawanoWaupaca CountyWaupacaSauk CountySaukManitowoc CountyManitowocWalworth CountyWalworthJefferson CountyJeffersonMarathon CountyMarathonGreen Bay Metro AreaGreen BayWisconsinMarinette CountyMarinetteGrant CountyGrantBrown CountyBrownFond du Lac CountyFond du LacSheboygan CountySheboyganOneida CountyOneidaWinnebago CountyWinnebagoChippewa CountyChippewaGreen CountyGreenWood CountyWoodVilas CountyVilasCalumet CountyCalumetColumbia CountyColumbiaPolk CountyPolkDunn CountyDunnEau Claire CountyEau ClairePortage CountyPortageIowa CountyIowaOutagamie CountyOutagamieDouglas CountyDouglasDoor CountyDoorWashington CountyWashingtonLa Crosse CountyLa CrossePierce CountyPierceDane CountyDaneSt. Croix CountySt. CroixWaukesha CountyWaukeshaOzaukee CountyOzaukee18.376088%18.376088%18.4%3,990113.948397%13.948397%13.9%2,676213.760962%13.760962%13.8%2,495313.092854%13.092854%13.1%81,52281.5k413.020590%13.020590%13.0%27,818,38027.8M11.937598%11.937598%11.9%2,441511.792912%11.792912%11.8%1,697611.170104%11.170104%11.2%14,74814.7k710.956491%10.956491%11.0%6,905810.719464%10.719464%10.7%3,363,7843.36M10.591406%10.591406%10.6%11,47611.5k910.579732%10.579732%10.6%2,1371010.244520%10.244520%10.2%4,641,8354.64M10.080658%10.080658%10.1%3,2621110.003168%10.003168%10.0%11,05311.1k129.792887%9.792887%9.8%2,993139.699758%9.699758%9.7%2,003149.607260%9.607260%9.6%2,615159.364060%9.364060%9.4%2,755169.145423%9.145423%9.1%3,401179.112219%9.112219%9.1%4,004189.100310%9.100310%9.1%5,192199.074810%9.074810%9.1%6,098208.872860%8.872860%8.9%5,068218.851943%8.851943%8.9%8,210228.685969%8.685969%8.7%18,36918.4k8.637220%8.637220%8.6%336,096336k8.627217%8.627217%8.6%2,598238.619607%8.619607%8.6%2,745248.601954%8.601954%8.6%14,60514.6k258.427102%8.427102%8.4%5,939268.367242%8.367242%8.4%6,683277.965352%7.965352%8.0%2,161287.893714%7.893714%7.9%8,936297.879569%7.879569%7.9%3,486307.788090%7.788090%7.8%2,014317.658332%7.658332%7.7%3,988327.548309%7.548309%7.5%1,250337.361483%7.361483%7.4%2,446347.225680%7.225680%7.2%2,879357.209656%7.209656%7.2%2,228367.133617%7.133617%7.1%1,930376.868874%6.868874%6.9%4,373386.784049%6.784049%6.8%3,040396.566661%6.566661%6.6%1,090406.470675%6.470675%6.5%7,873416.427874%6.427874%6.4%1,974426.365714%6.365714%6.4%1,365436.072757%6.072757%6.1%5,649445.474767%5.474767%5.5%4,066455.314614%5.314614%5.3%1,359464.746468%4.746468%4.7%15,98916.0k474.242959%4.242959%4.2%2,454484.116150%4.116150%4.1%11,37011.4k493.651213%3.651213%3.7%2,21350
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 Wisconsin, and entities that contain Brown County
0%10%20%30%40%Count#Dane CountyDaneOzaukee CountyOzaukeeWaukesha CountyWaukeshaSt. Croix CountySt. CroixLa Crosse CountyLa CrosseDoor CountyDoorEau Claire CountyEau ClaireUnited States of AmericaUnited StatesPortage CountyPortageMilwaukee CountyMilwaukeeWashington CountyWashingtonMidwestCalumet CountyCalumetEast North CentralWisconsinBrown CountyBrownWalworth CountyWalworthPierce CountyPierceOutagamie CountyOutagamieWinnebago CountyWinnebagoVilas CountyVilasDunn CountyDunnOneida CountyOneidaGreen Bay Metro AreaGreen BayKenosha CountyKenoshaRacine CountyRacineMarathon CountyMarathonSheboygan CountySheboyganJefferson CountyJeffersonIowa CountyIowaDouglas CountyDouglasGreen CountyGreenColumbia CountyColumbiaSauk CountySaukFond du Lac CountyFond du LacGrant CountyGrantVernon CountyVernonRock CountyRockWood CountyWoodManitowoc CountyManitowocPolk CountyPolkChippewa CountyChippewaTrempealeau CountyTrempealeauBarron CountyBarronMonroe CountyMonroeWaupaca CountyWaupacaDodge CountyDodgeOconto CountyOcontoLincoln CountyLincolnShawano CountyShawanoWaushara CountyWausharaMarinette CountyMarinetteJackson CountyJacksonJuneau CountyJuneauClark CountyClark49.026156%49.026156%49.0%165,150165k146.663917%46.663917%46.7%28,28328.3k241.623436%41.623436%41.6%114,976115k333.399035%33.399035%33.4%19,31719.3k432.470243%32.470243%32.5%24,11524.1k531.324908%31.324908%31.3%6,717630.750503%30.750503%30.8%19,57719.6k730.315023%30.315023%30.3%64,767,78764.8M30.305059%30.305059%30.3%13,58013.6k829.748251%29.748251%29.7%185,226185k929.422072%29.422072%29.4%27,36927.4k1028.952816%28.952816%29.0%13,118,64213.1M28.702561%28.702561%28.7%9,5371128.462853%28.462853%28.5%8,931,6868.93M28.373439%28.373439%28.4%1,104,0821.10M28.243623%28.243623%28.2%47,95448.0k1227.818206%27.818206%27.8%18,69318.7k1327.816667%27.816667%27.8%7,1131427.785357%27.785357%27.8%33,80733.8k1526.886859%26.886859%26.9%30,43730.4k1626.811594%26.811594%26.8%4,4401726.627241%26.627241%26.6%7,2041826.247696%26.247696%26.2%7,1211925.916521%25.916521%25.9%54,80854.8k24.646364%24.646364%24.6%27,23327.2k2023.972400%23.972400%24.0%31,65131.7k2123.939061%23.939061%23.9%22,20322.2k2223.621840%23.621840%23.6%18,86718.9k2323.470710%23.470710%23.5%13,40613.4k2423.037532%23.037532%23.0%3,8242522.777597%22.777597%22.8%6,9952622.687548%22.687548%22.7%5,8672722.675936%22.675936%22.7%9,0352822.323115%22.323115%22.3%9,8092921.924087%21.924087%21.9%15,45115.5k3021.337060%21.337060%21.3%6,7953121.214789%21.214789%21.2%4,3383220.765653%20.765653%20.8%22,50022.5k3320.382533%20.382533%20.4%10,61410.6k3419.658914%19.658914%19.7%11,21611.2k3519.600039%19.600039%19.6%6,0573619.278497%19.278497%19.3%8,5293719.253428%19.253428%19.3%3,8893818.214407%18.214407%18.2%5,8943918.178844%18.178844%18.2%5,5564017.664300%17.664300%17.7%6,5694116.254641%16.254641%16.3%10,24410.2k4216.194570%16.194570%16.2%4,4084315.961259%15.961259%16.0%3,2964415.597702%15.597702%15.6%4,5894515.084662%15.084662%15.1%2,7354614.508202%14.508202%14.5%4,3694713.870744%13.870744%13.9%1,9964812.921553%12.921553%12.9%2,4794911.476995%11.476995%11.5%2,49250
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 Wisconsin, and entities that contain Brown County
0%2%4%6%Count#Dane CountyDaneOzaukee CountyOzaukeeLa Crosse CountyLa CrosseWaukesha CountyWaukeshaUnited States of AmericaUnited StatesDoor CountyDoorEau Claire CountyEau ClairePortage CountyPortageMilwaukee CountyMilwaukeeMidwestEast North CentralDunn CountyDunnWisconsinVilas CountyVilasSt. Croix CountySt. CroixOneida CountyOneidaWalworth CountyWalworthWood CountyWoodGrant CountyGrantMarathon CountyMarathonBrown CountyBrownWinnebago CountyWinnebagoIowa CountyIowaGreen CountyGreenBarron CountyBarronVernon CountyVernonGreen Bay Metro AreaGreen BayOutagamie CountyOutagamieKenosha CountyKenoshaPierce CountyPierceSauk CountySaukColumbia CountyColumbiaJefferson CountyJeffersonWashington CountyWashingtonRacine CountyRacineRock CountyRockDouglas CountyDouglasChippewa CountyChippewaSheboygan CountySheboyganFond du Lac CountyFond du LacPolk CountyPolkMonroe CountyMonroeCalumet CountyCalumetMarinette CountyMarinetteDodge CountyDodgeShawano CountyShawanoLincoln CountyLincolnOconto CountyOcontoManitowoc CountyManitowocWaupaca CountyWaupacaJackson CountyJacksonJuneau CountyJuneauTrempealeau CountyTrempealeauWaushara CountyWausharaClark CountyClark6.978843%6.978843%7.0%23,50923.5k15.805973%5.805973%5.8%3,51924.130985%4.130985%4.1%3,06833.942743%3.942743%3.9%10,89110.9k43.336158%3.336158%3.3%7,127,6737.13M3.143217%3.143217%3.1%67453.130498%3.130498%3.1%1,99363.030506%3.030506%3.0%1,35872.985811%2.985811%3.0%18,59118.6k82.893416%2.893416%2.9%1,311,0191.31M2.855432%2.855432%2.9%896,039896k2.786916%2.786916%2.8%75492.703886%2.703886%2.7%105,215105k2.644928%2.644928%2.6%438102.636720%2.636720%2.6%1,525112.631773%2.631773%2.6%714122.573032%2.573032%2.6%1,729132.536775%2.536775%2.5%1,321142.213779%2.213779%2.2%705152.197352%2.197352%2.2%2,038162.072008%2.072008%2.1%3,518172.028197%2.028197%2.0%2,296182.012169%2.012169%2.0%334191.956690%1.956690%2.0%506201.912914%1.912914%1.9%619211.907277%1.907277%1.9%390221.879146%1.879146%1.9%3,9741.866494%1.866494%1.9%2,271231.856193%1.856193%1.9%2,051241.849752%1.849752%1.8%473251.847932%1.847932%1.8%812261.744303%1.744303%1.7%695271.735005%1.735005%1.7%991281.704973%1.704973%1.7%1,586291.651885%1.651885%1.7%2,181301.557885%1.557885%1.6%1,688311.549984%1.549984%1.5%476321.491829%1.491829%1.5%660331.476130%1.476130%1.5%1,179341.464349%1.464349%1.5%1,032351.459405%1.459405%1.5%451361.456009%1.456009%1.5%445371.390435%1.390435%1.4%462381.321644%1.321644%1.3%398391.304306%1.304306%1.3%822401.291594%1.291594%1.3%380411.099274%1.099274%1.1%227421.076454%1.076454%1.1%293431.074440%1.074440%1.1%613441.070238%1.070238%1.1%398451.063238%1.063238%1.1%153461.042481%1.042481%1.0%200470.955493%0.955493%1.0%193480.932105%0.932105%0.9%169490.801363%0.801363%0.8%17450
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 Wisconsin, and entities that contain Brown County
Female
Male
1x0x1xFM#LincolnGrantDoorWinnebagoTrempealeauPierceChippewaJacksonShawanoGreenMonroeManitowocOcontoJuneauWaupacaClarkDouglasRacineSaukIowaPolkWalworthColumbiaOutagamieOneidaVilasDunnKenoshaGreen BayFond du LacDodgePortageBrownWoodWisconsinBarronCalumetMarathonRockDaneWausharaWaukeshaSheboyganMidwestWashingtonEast North CentralMilwaukeeUnited StatesVernonJeffersonEau ClaireMarinetteSt. CroixLa CrosseOzaukee-1.000000x-1.000000x1.701366x1.701366x1.70x7.198%7.20%12.247%12.2%1-1.000000x-1.000000x1.611247x1.611247x1.61x6.600%6.60%10.635%10.6%2-1.000000x-1.000000x1.599739x1.599739x1.60x4.927%4.93%7.882%7.88%3-1.000000x-1.000000x1.548094x1.548094x1.55x6.189%6.19%9.581%9.58%4-1.000000x-1.000000x1.543397x1.543397x1.54x8.305%8.31%12.818%12.8%5-1.000000x-1.000000x1.493476x1.493476x1.49x4.256%4.26%6.357%6.36%6-1.000000x-1.000000x1.457826x1.457826x1.46x6.371%6.37%9.288%9.29%7-1.000000x-1.000000x1.449841x1.449841x1.45x9.497%9.50%13.769%13.8%8-1.000000x-1.000000x1.432451x1.432451x1.43x7.710%7.71%11.044%11.0%9-1.000000x-1.000000x1.408297x1.408297x1.41x6.491%6.49%9.141%9.14%10-1.000000x-1.000000x1.405780x1.405780x1.41x8.136%8.14%11.438%11.4%11-1.000000x-1.000000x1.389119x1.389119x1.39x7.638%7.64%10.610%10.6%12-1.000000x-1.000000x1.374304x1.374304x1.37x8.070%8.07%11.091%11.1%13-1.000000x-1.000000x1.372407x1.372407x1.37x11.643%11.6%15.979%16.0%14-1.000000x-1.000000x1.345859x1.345859x1.35x7.796%7.80%10.492%10.5%15-1.000000x-1.000000x1.344554x1.344554x1.34x15.666%15.7%21.064%21.1%16-1.000000x-1.000000x1.343519x1.343519x1.34x5.497%5.50%7.385%7.39%17-1.000000x-1.000000x1.324710x1.324710x1.32x9.652%9.65%12.786%12.8%18-1.000000x-1.000000x1.317657x1.317657x1.32x7.885%7.89%10.390%10.4%19-1.000000x-1.000000x1.317393x1.317393x1.32x5.673%5.67%7.473%7.47%20-1.000000x-1.000000x1.317139x1.317139x1.32x6.222%6.22%8.196%8.20%21-1.000000x-1.000000x1.312179x1.312179x1.31x7.868%7.87%10.324%10.3%22-1.000000x-1.000000x1.312059x1.312059x1.31x6.240%6.24%8.187%8.19%23-1.000000x-1.000000x1.304911x1.304911x1.30x5.628%5.63%7.345%7.34%24-1.000000x-1.000000x1.304731x1.304731x1.30x6.919%6.92%9.027%9.03%25-1.000000x-1.000000x1.271978x1.271978x1.27x6.646%6.65%8.453%8.45%26-1.000000x-1.000000x1.264913x1.264913x1.26x6.297%6.30%7.965%7.96%27-1.000000x-1.000000x1.259401x1.259401x1.26x8.885%8.88%11.190%11.2%28-1.000000x-1.000000x1.245810x1.245810x1.25x7.746%7.75%9.650%9.65%-1.000000x-1.000000x1.243849x1.243849x1.24x7.537%7.54%9.375%9.37%29-1.000000x-1.000000x1.242121x1.242121x1.24x9.722%9.72%12.076%12.1%30-1.000000x-1.000000x1.236850x1.236850x1.24x6.069%6.07%7.506%7.51%31-1.000000x-1.000000x1.236680x1.236680x1.24x7.707%7.71%9.531%9.53%32-1.000000x-1.000000x1.235773x1.235773x1.24x6.872%6.87%8.492%8.49%33-1.000000x-1.000000x1.219291x1.219291x1.22x7.799%7.80%9.509%9.51%-1.000000x-1.000000x1.205037x1.205037x1.21x9.154%9.15%11.030%11.0%34-1.000000x-1.000000x1.202432x1.202432x1.20x6.690%6.69%8.044%8.04%35-1.000000x-1.000000x1.194678x1.194678x1.19x8.073%8.07%9.644%9.64%36-1.000000x-1.000000x1.191494x1.191494x1.19x9.696%9.70%11.553%11.6%37-1.000000x-1.000000x1.187155x1.187155x1.19x4.348%4.35%5.162%5.16%38-1.000000x-1.000000x1.183552x1.183552x1.18x12.548%12.5%14.851%14.9%39-1.000000x-1.000000x1.142369x1.142369x1.14x3.851%3.85%4.400%4.40%40-1.000000x-1.000000x1.140135x1.140135x1.14x7.823%7.82%8.920%8.92%41-1.000000x-1.000000x1.127915x1.127915x1.13x9.647%9.65%10.881%10.9%-1.000000x-1.000000x1.127252x1.127252x1.13x5.716%5.72%6.443%6.44%42-1.000000x-1.000000x1.125371x1.125371x1.13x10.108%10.1%11.375%11.4%-1.000000x-1.000000x1.111013x1.111013x1.11x12.441%12.4%13.822%13.8%43-1.000000x-1.000000x1.109070x1.109070x1.11x12.369%12.4%13.719%13.7%-1.000000x-1.000000x1.106354x1.106354x1.11x11.340%11.3%12.546%12.5%44-1.000000x-1.000000x1.074639x1.074639x1.07x8.559%8.56%9.197%9.20%45-1.000000x-1.000000x1.070745x1.070745x1.07x6.639%6.64%7.109%7.11%46-1.000000x-1.000000x1.047262x1.047262x1.05x8.430%8.43%8.828%8.83%47-1.000000x-1.000000x1.019047x1.019047x1.02x4.203%4.20%4.283%4.28%48-1.003452x-1.003452x1.00x1.000000x1.000000x5.484%5.48%5.465%5.47%49-1.036965x-1.036965x1.04x1.000000x1.000000x3.715%3.71%3.582%3.58%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 Wisconsin, and entities that contain Brown County
Female
Male
1x0x1x2xFM#PortageJuneauOneidaWinnebagoSheboyganLincolnEau ClaireFond du LacPolkClarkSaukWaupacaOzaukeeWoodManitowocShawanoVilasSt. CroixWalworthMarinetteRockBrownGreen BayDunnWaukeshaDouglasBarronCalumetJeffersonGrantLa CrosseRacineColumbiaEast North CentralMidwestWisconsinKenoshaUnited StatesGreenTrempealeauMilwaukeeMonroeWausharaDoorOutagamieMarathonDanePierceWashingtonVernonDodgeIowaOcontoChippewaJackson-1.000000x-1.000000x2.277540x2.277540x2.28x1.853%1.85%4.219%4.22%1-1.000000x-1.000000x2.264652x2.264652x2.26x0.623%0.62%1.412%1.41%2-1.000000x-1.000000x2.218029x2.218029x2.22x1.640%1.64%3.637%3.64%3-1.000000x-1.000000x2.174213x2.174213x2.17x1.275%1.28%2.773%2.77%4-1.000000x-1.000000x2.031853x2.031853x2.03x0.976%0.98%1.984%1.98%5-1.000000x-1.000000x2.023351x2.023351x2.02x0.729%0.73%1.476%1.48%6-1.000000x-1.000000x2.013470x2.013470x2.01x2.093%2.09%4.215%4.21%7-1.000000x-1.000000x1.953821x1.953821x1.95x1.002%1.00%1.957%1.96%8-1.000000x-1.000000x1.945823x1.945823x1.95x0.991%0.99%1.928%1.93%9-1.000000x-1.000000x1.933595x1.933595x1.93x0.546%0.55%1.055%1.06%10-1.000000x-1.000000x1.895621x1.895621x1.90x1.285%1.28%2.435%2.43%11-1.000000x-1.000000x1.880009x1.880009x1.88x0.743%0.74%1.397%1.40%12-1.000000x-1.000000x1.872688x1.872688x1.87x4.090%4.09%7.659%7.66%13-1.000000x-1.000000x1.814669x1.814669x1.81x1.818%1.82%3.299%3.30%14-1.000000x-1.000000x1.806143x1.806143x1.81x0.769%0.77%1.390%1.39%15-1.000000x-1.000000x1.801551x1.801551x1.80x0.924%0.92%1.665%1.66%16-1.000000x-1.000000x1.794571x1.794571x1.79x1.894%1.89%3.398%3.40%17-1.000000x-1.000000x1.774639x1.774639x1.77x1.907%1.91%3.384%3.38%18-1.000000x-1.000000x1.769950x1.769950x1.77x1.867%1.87%3.304%3.30%19-1.000000x-1.000000x1.739302x1.739302x1.74x0.967%0.97%1.683%1.68%20-1.000000x-1.000000x1.733327x1.733327x1.73x1.151%1.15%1.995%2.00%21-1.000000x-1.000000x1.733262x1.733262x1.73x1.524%1.52%2.641%2.64%22-1.000000x-1.000000x1.720824x1.720824x1.72x1.386%1.39%2.385%2.38%-1.000000x-1.000000x1.701002x1.701002x1.70x2.062%2.06%3.507%3.51%23-1.000000x-1.000000x1.695850x1.695850x1.70x2.951%2.95%5.005%5.00%24-1.000000x-1.000000x1.676561x1.676561x1.68x1.162%1.16%1.949%1.95%25-1.000000x-1.000000x1.674221x1.674221x1.67x1.435%1.44%2.403%2.40%26-1.000000x-1.000000x1.653118x1.653118x1.65x1.050%1.05%1.736%1.74%27-1.000000x-1.000000x1.652660x1.652660x1.65x1.313%1.31%2.170%2.17%28-1.000000x-1.000000x1.647269x1.647269x1.65x1.672%1.67%2.754%2.75%29-1.000000x-1.000000x1.645663x1.645663x1.65x3.144%3.14%5.174%5.17%30-1.000000x-1.000000x1.641913x1.641913x1.64x1.260%1.26%2.069%2.07%31-1.000000x-1.000000x1.632754x1.632754x1.63x1.321%1.32%2.157%2.16%32-1.000000x-1.000000x1.597848x1.597848x1.60x2.216%2.22%3.541%3.54%-1.000000x-1.000000x1.589934x1.589934x1.59x2.251%2.25%3.579%3.58%-1.000000x-1.000000x1.576114x1.576114x1.58x2.109%2.11%3.323%3.32%-1.000000x-1.000000x1.529626x1.529626x1.53x1.477%1.48%2.259%2.26%33-1.000000x-1.000000x1.526215x1.526215x1.53x2.660%2.66%4.060%4.06%-1.000000x-1.000000x1.519133x1.519133x1.52x1.560%1.56%2.370%2.37%34-1.000000x-1.000000x1.514826x1.514826x1.51x0.759%0.76%1.149%1.15%35-1.000000x-1.000000x1.492516x1.492516x1.49x2.423%2.42%3.616%3.62%36-1.000000x-1.000000x1.489534x1.489534x1.49x1.169%1.17%1.741%1.74%37-1.000000x-1.000000x1.474810x1.474810x1.47x0.746%0.75%1.100%1.10%38-1.000000x-1.000000x1.464487x1.464487x1.46x2.563%2.56%3.754%3.75%39-1.000000x-1.000000x1.455713x1.455713x1.46x1.525%1.53%2.220%2.22%40-1.000000x-1.000000x1.452508x1.452508x1.45x1.795%1.79%2.607%2.61%41-1.000000x-1.000000x1.404212x1.404212x1.40x5.827%5.83%8.182%8.18%42-1.000000x-1.000000x1.403843x1.403843x1.40x1.537%1.54%2.158%2.16%43-1.000000x-1.000000x1.374225x1.374225x1.37x1.441%1.44%1.980%1.98%44-1.000000x-1.000000x1.357719x1.357719x1.36x1.620%1.62%2.199%2.20%45-1.000000x-1.000000x1.235296x1.235296x1.24x1.161%1.16%1.434%1.43%46-1.000000x-1.000000x1.129194x1.129194x1.13x1.891%1.89%2.135%2.14%47-1.000000x-1.000000x1.084340x1.084340x1.08x1.032%1.03%1.119%1.12%48-1.000000x-1.000000x1.080157x1.080157x1.08x1.432%1.43%1.547%1.55%49-1.147189x-1.147189x1.15x1.000000x1.000000x1.142%1.14%0.995%1.00%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#62

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 CostaEast North CentralMecklenburg CountyMecklenburgMidwestSalt Lake CountySalt LakeFairfield CountyFairfieldSuffolk CountySuffolkFranklin CountyFranklinNassau CountyNassauHonolulu CountyHonoluluMontgomery CountyMontgomeryGreen Bay Metro AreaGreen BayFulton CountyFultonWisconsinBrown CountyBrownFairfax CountyFairfaxWake CountyWakeKing CountyKingMiddlesex 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%82,37182.4k3310.719464%10.719464%10.7%3,363,7843.36M10.377895%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%78,29978.3k389.121758%9.121758%9.1%85,26785.3k398.945780%8.945780%8.9%60,28460.3k408.836226%8.836226%8.8%62,20562.2k418.685969%8.685969%8.7%18,36918.4k8.677323%8.677323%8.7%57,57157.6k428.637220%8.637220%8.6%336,096336k8.601954%8.601954%8.6%14,60514.6k8.282040%8.282040%8.3%63,67163.7k437.696387%7.696387%7.7%50,50850.5k447.543133%7.543133%7.5%110,490110k457.360151%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#63

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 CountySuffolkPalm Beach CountyPalm BeachKings CountyKingsHonolulu CountyHonoluluSalt Lake CountySalt LakeOrange CountyOrangeHillsborough CountyHillsboroughBroward CountyBrowardMaricopa CountyMaricopaCuyahoga CountyCuyahogaPima CountyPimaLos Angeles CountyLos AngelesTarrant CountyTarrantQueens CountyQueensUnited States of AmericaUnited StatesHarris CountyHarrisMilwaukee CountyMilwaukeeDallas CountyDallasSacramento CountySacramentoMidwestEast North CentralWisconsinBrown CountyBrownMiami-Dade CountyMiami-DadeBexar CountyBexarPhiladelphia CountyPhiladelphiaGreen Bay Metro AreaGreen BayClark CountyClarkWayne CountyWayneRiverside CountyRiversideFresno 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%352,396352k2434.188819%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%839,907840k3829.748251%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%13,118,64213.1M28.462853%28.462853%28.5%8,931,6868.93M28.373439%28.373439%28.4%1,104,0821.10M28.243623%28.243623%28.2%47,95448.0k27.281635%27.281635%27.3%510,061510k4226.926164%26.926164%26.9%315,328315k4326.349720%26.349720%26.3%272,786273k4425.916521%25.916521%25.9%54,80854.8k22.823853%22.823853%22.8%317,635318k4522.338065%22.338065%22.3%260,985261k4621.189043%21.189043%21.2%311,245311k4719.731980%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#64

Percent of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).
Scope: population of 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 CountyHillsboroughKings CountyKingsHarris CountyHarrisUnited States of AmericaUnited StatesSacramento CountySacramentoMaricopa CountyMaricopaDallas CountyDallasOrange CountyOrangeMilwaukee CountyMilwaukeeMidwestEast North CentralBexar CountyBexarQueens CountyQueensWisconsinFresno CountyFresnoTarrant CountyTarrantClark CountyClarkRiverside CountyRiversideWayne CountyWayneBrown CountyBrownGreen Bay Metro AreaGreen BaySan 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%30,88530.9k343.384967%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%18,59118.6k412.893416%2.893416%2.9%1,311,0191.31M2.855432%2.855432%2.9%896,039896k2.818073%2.818073%2.8%33,00233.0k422.756960%2.756960%2.8%44,96545.0k432.703886%2.703886%2.7%105,215105k2.392530%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%25,45125.5k482.072008%2.072008%2.1%3,5181.879146%1.879146%1.9%3,9741.852789%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#65

Percentage more likely men are than women to not have a high school diploma (or equivalent) among people aged 25 years and older.
Scope: population of Brown County, selected other counties in the United States, and entities that contain Brown County
Female
Male
1x0x1xFM#MecklenburgGreen BayPalm BeachBrownWisconsinWakeWestchesterFairfieldContra CostaHillsboroughFresnoMidwestEast North CentralDallasSuffolkMilwaukeeWayneUnited StatesOrangeHarrisFultonPhiladelphiaSan BernardinoTarrantCookMaricopaCuyahogaTravisBrowardRiversideOaklandNassauSalt LakeFranklinSacramentoMontgomeryBronxMiddlesexKingsFairfaxBexarPimaKingLos AngelesClarkOrangeSt. LouisHennepinMiami-DadeQueensAlamedaAlleghenyNew YorkSan DiegoSanta ClaraHonolulu-1.000000x-1.000000x1.282326x1.282326x1.28x9.163%9.16%11.750%11.7%1-1.000000x-1.000000x1.245810x1.245810x1.25x7.746%7.75%9.650%9.65%-1.000000x-1.000000x1.244689x1.244689x1.24x10.804%10.8%13.447%13.4%2-1.000000x-1.000000x1.236680x1.236680x1.24x7.707%7.71%9.531%9.53%-1.000000x-1.000000x1.219291x1.219291x1.22x7.799%7.80%9.509%9.51%-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-1.000000x1.132218x1.132218x1.13x11.472%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-1.000000x1.125371x1.125371x1.13x10.108%10.1%11.375%11.4%-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%47-1.097207x-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#66

Percentage more likely men are than women to have a professional or doctorate degree (e.g., MBA, PhD, or MD) among people aged 25 years and older.
Scope: population of Brown County, selected other counties in the United States, and entities that contain Brown County
Female
Male
1x0x1x2xFM#Palm BeachSalt LakeSt. LouisOaklandBrownGreen BayMaricopaCuyahogaOrangeBexarMontgomeryPimaSuffolkRiversideDallasWestchesterTarrantFairfieldEast North CentralAlleghenyMidwestNassauWisconsinBrowardClarkFranklinMecklenburgFairfaxWayneUnited StatesSanta ClaraFultonContra CostaMilwaukeeSan DiegoOrangeFresnoHillsboroughHarrisMiami-DadeHennepinTravisLos AngelesCookWakeAlamedaMiddlesexKingPhiladelphiaSan BernardinoHonoluluQueensSacramentoKingsNew YorkBronx-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-1.000000x1.733262x1.733262x1.73x1.524%1.52%2.641%2.64%-1.000000x-1.000000x1.720824x1.720824x1.72x1.386%1.39%2.385%2.38%-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-1.000000x1.597848x1.597848x1.60x2.216%2.22%3.541%3.54%-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-1.000000x1.576114x1.576114x1.58x2.109%2.11%3.323%3.32%-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-1.000000x1.567965x1.567965x1.57x3.409%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-1.000000x1.475755x1.475755x1.48x3.533%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:
Green Bay
Cities:
De Pere, Green Bay
Towns:
Eaton, Glenmore, Green Bay, Holland, Humboldt, Lawrence, Ledgeview, Morrison, New Denmark, Pittsfield, Rockland, Scott, Wrightstown
Unincorporated Places:
Dyckesville, Greenleaf
Villages:
Allouez, Ashwaubenon, Bellevue, Denmark, Hobart, Howard, Pulaski, Suamico, Wrightstown
ZIP Codes:
54110, 54115, 54126, 54130, 54155, 54162, 54165, 54173, 54180, 54208, 54217, 54229, 54301, 54302, 54303, 54304, 54307, 54311, 54313
Unified School Districts:
Ashwaubenon, Brillion, De Pere, Denmark, Green Bay, Howard-Suamico, Kaukauna, Luxemburg-Casco, Pulaski, Reedsville, West De Pere, Wrightstown
Congressional District:
WI-8
State Senate Districts:
WI-1, WI-2, WI-30
Assembly Districts:
WI-1, WI-2, WI-4, WI-5, WI-6, WI-88, WI-89, WI-90
Neighboring Counties:
Calumet, Door, Kewaunee, Manitowoc, Oconto, Outagamie, Shawano
Nearby Counties:
Fond du Lac, Marinette, Menominee, Sheboygan, Winnebago