Educational Attainment in Berlin, Green Lake County, Wisconsin (City)

Educational Attainment#1

Highest level of education among people aged 25 years and older.
Scope: population of Green Lake County and Berlin
Berlin
Green Lake County
0%10%20%30%40%50%60%CountHigher Degree1H.S. Diploma2No H.S. Diploma221.604278%27.360467%21.604278%21.6%80863.716578%61.237468%63.716578%63.7%2,38314.679144%11.402065%14.679144%14.7%549
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 Green Lake County at large.
Scope: population of Green Lake County and Berlin
-20%0%+20%%ref.Higher Degree1H.S. Diploma2No H.S. Diploma2-21.038343%-21.038343%-21.0%21.604%21.6%27.360%27.4%4.048354%4.048354%+4.0%63.717%63.7%61.237%61.2%28.741105%28.741105%+28.7%14.679%14.7%11.402%11.4%
% percentage with given level in Berlin
ref. percentage with given level in Green Lake County
1Post-Secondary Degree 2H.S. = High School

Detailed Educational Attainment#3

Highest level of education among people aged 25 years and older.
Scope: population of Green Lake County and Berlin
Berlin
Green Lake County
0%10%20%30%40%CountDoctorate1Professional1Master's1Bachelor's1Associate's1Some CollegeHigh School2Some H.S.3Less than H.S.3None0.534759%0.568607%0.534759%0.5%201.042781%0.942690%1.042781%1.0%393.903743%4.242107%3.903743%3.9%1469.037433%11.940745%9.037433%9.0%3387.085561%9.666318%7.085561%7.1%26517.540107%19.183002%17.540107%17.5%65646.176471%42.054467%46.176471%46.2%1,72710.828877%7.264701%10.828877%10.8%4053.315508%3.576238%3.315508%3.3%1240.534759%0.561125%0.534759%0.5%20
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 Green Lake County at large.
Scope: population of Green Lake County and Berlin
0%%ref.Doctorate1Professional1Master's1Bachelor's1Associate's1Some CollegeHigh School2Some H.S.3Less than H.S.3None-5.952716%-5.952716%-6.0%0.535%0.53%0.569%0.57%10.617520%10.617520%+10.6%1.043%1.04%0.943%0.94%-7.976308%-7.976308%-8.0%3.904%3.90%4.242%4.24%-24.314329%-24.314329%-24.3%9.037%9.04%11.941%11.9%-26.698440%-26.698440%-26.7%7.086%7.09%9.666%9.67%-8.564325%-8.564325%-8.6%17.540%17.5%19.183%19.2%9.801584%9.801584%+9.8%46.176%46.2%42.054%42.1%49.061555%49.061555%+49.1%10.829%10.8%7.265%7.26%-7.290627%-7.290627%-7.3%3.316%3.32%3.576%3.58%-4.698752%-4.698752%-4.7%0.535%0.53%0.561%0.56%
% percentage with given level in Berlin
ref. percentage with given level in Green Lake County
1Degree 2Diploma or equivialent 3H.S. = High School

Educational Attainment Sex Ratio#5

Percentage more likely men or women are to have various highest levels of education among people aged 25 years and older.
Scope: population of Green Lake County and Berlin
More Females More Males
Green Lake County
Berlin
40%20%0%20%FMHigher Degree1H.S. Diploma2No H.S. Diploma2-47.069833%-22.022127%-47.069833%47%25.556%25.6%17.377%17.4%9.241180%5.344322%9.241180%9%60.993%61.0%66.630%66.6%18.904474%21.696476%18.904474%19%13.451%13.5%15.993%16.0%
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 Green Lake County and Berlin
More Females More Males
Green Lake County
Berlin
0%500%1,000%FMDoctorate1Professional1Master's1Bachelor's1Associate's1Some CollegeHigh School2Some H.S.3Less than H.S.3None1,000.000000%314.903265%1,000.000000%> 1000%0.000%0%1.107%1.11%91.023006%440.734583%91.023006%91%0.724%0.72%1.384%1.38%-54.669614%-36.476324%-54.669614%55%4.708%4.71%3.044%3.04%-206.477765%-36.164294%-206.477765%206%13.399%13.4%4.372%4.37%-29.337323%11.087225%11.087225%11%6.725%6.73%7.471%7.47%-23.210777%-19.193470%-23.210777%23%19.296%19.3%15.661%15.7%22.235764%16.861910%22.235764%22%41.697%41.7%50.968%51.0%68.976274%54.623976%68.976274%69%8.122%8.12%13.724%13.7%-137.710443%-16.898403%-137.710443%138%4.604%4.60%1.937%1.94%-118.123814%-84.720228%-118.123814%118%0.724%0.72%0.332%0.33%
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 Green Lake County and Berlin
Berlin
Green Lake County
0%5%10%15%B.X.Total65+45-6435-4425-346.936937%11.679389%6.936937%6.9%771,1107.715814%10.048103%7.715814%7.7%1011,30911.382114%14.665997%11.382114%11.4%8473813.036021%15.338428%13.036021%13.0%76583
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 Green Lake County at large.
Scope: population of Green Lake County and Berlin
40%30%20%10%0%%ref.65+45-6435-4425-34-40.605311%-40.605311%40.6%6.937%6.94%11.679%11.7%-23.211238%-23.211238%23.2%7.716%7.72%10.048%10.0%-22.391135%-22.391135%22.4%11.382%11.4%14.666%14.7%-15.010713%-15.010713%15.0%13.036%13.0%15.338%15.3%
% percentage in Berlin with a Bachelor's degree
ref percentage in Green Lake County with a Bachelor's degree

Bachelor's Degrees Sex Ratio By Age#9

Percentage more likely men or women are to have their highest degree be a Bachelor's.
Scope: population of Green Lake County and Berlin
More Females More Males
Green Lake County
Berlin
500%400%300%200%100%0%FM65+45-6435-4425-34-561.676647%-1.396265%-561.676647%561.7%10.479%10.5%1.584%1.58%-155.586773%-31.610411%-155.586773%155.6%11.044%11.0%4.321%4.32%-361.349481%-154.510502%-361.349481%361.3%19.706%19.7%4.271%4.27%-119.290123%-27.970457%-119.290123%119.3%18.561%18.6%8.464%8.46%
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 Green Lake County and Berlin
Berlin
Green Lake County
$0k$20k$40k$60kCount%Graduate Degree1Bachelor's DegreeSome CollegeH.S. Diploma2No H.S. Diploma2Total$62,813.000000$55,184.000000$62,813.000000$62.8k2055.481%5.48%$46,172.000000$39,107.000000$46,172.000000$46.2k3389.037%9.04%$28,285.000000$32,808.000000$28,285.000000$28.3k92124.626%24.6%$23,865.000000$27,414.000000$23,865.000000$23.9k1,72746.176%46.2%$31,639.000000$28,466.000000$31,639.000000$31.6k54914.679%14.7%$30,205.000000$31,545.000000$30,205.000000$30.2k3,740100.000%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 Green Lake County and Berlin
Female Male
Green Lake County
Berlin
Shaded bar tips show excess over facing bar.
$50k$0k$50kFMGraduate Degree1Bachelor's DegreeSome CollegeH.S. Diploma2No H.S. Diploma2Total$-62,708.000000$-52,857.000000$-62,708.000000$62.7k$62,708.000000$17,366.000000$52,857.000000$3,914.000000$80,074.000000$80.1k105100$-35,114.000000$-34,896.000000$-35,114.000000$35.1k$35,114.000000$34,511.000000$34,896.000000$16,910.000000$69,625.000000$69.6k25979$-28,169.000000$-27,310.000000$-28,169.000000$28.2k$28,169.000000$2,545.000000$27,310.000000$16,101.000000$30,714.000000$30.7k503418$-20,616.000000$-21,188.000000$-20,616.000000$20.6k$20,616.000000$11,400.000000$21,188.000000$14,505.000000$32,016.000000$32.0k806921$-18,854.000000$-18,611.000000$-18,854.000000$18.9k$18,854.000000$13,396.000000$18,611.000000$12,322.000000$32,250.000000$32.3k260289$-25,253.000000$-25,277.000000$-25,253.000000$25.3k$25,253.000000$9,722.000000$25,277.000000$14,526.000000$34,975.000000$35.0k1,9331,807
F females with given highest level of educational attainment
M males with given highest level of educational attainment
1or professional degree 2H.S. = High School

Employment by Educational Attainment#12

Percentage of population that is employed by highest level of educational attainment among the population aged 25 to 64 years old.
Scope: population of Green Lake County and Berlin
Berlin
Green Lake County
0%20%40%60%80%CountBachelor's Degree1Some College2H.S. Diploma3No H.S. Diploma390.954774%82.211538%90.954774%91.0%36278.591549%80.855329%78.591549%78.6%55873.720137%75.253444%73.720137%73.7%86453.714286%57.188841%53.714286%53.7%188
Count employed people with given educational attainment aged 25 to 64 years old
1or higher 2two or four year institution 3H.S. = High School

Lacking High School Diploma By Race#13

Percent of racial or ethnic group lacking a high school diploma (or equivalent).
Scope: population of Green Lake County and Berlin
Female Male
Green Lake County
Berlin
Shaded bar tips show excess over facing bar.
40%20%0%20%40%MFWhite1Hispanic2Other1-12.297373%-9.777363%-12.297373%12.3%12.297373%1.788774%9.777363%1.986404%14.086147%14.1%242220-32.323232%-22.872340%-32.323232%32.3%32.323232%25.701459%22.872340%17.835624%58.024691%58.0%4732-35.384615%-7.115385%-31.355932%-6.144068%-42.500000%42.5%35.384615%31.355932%35.384615%35.4%2334
M number of males in category
F number of females in category
1non-Hispanic 2excluding black and Asian Hispanics

College Graduates By Race#14

Percent of racial or ethnic group with a bachelor's degree or higher.
Scope: population of Green Lake County and Berlin
Female Male
Green Lake County
Berlin
Shaded bar tips show excess over facing bar.
20%10%0%10%MFWhite1Hispanic2Other1-10.419092%-8.418247%-16.073424%-3.029799%-18.837339%18.8%10.419092%16.073424%10.419092%10.4%179337-0.000000%-9.090909%-0.884956%-5.498023%-9.090909%9.1%0.000000%0.884956%0.000000%0.0%09-0.000000%-22.500000%-3.389831%-15.776836%-22.500000%22.5%0.000000%3.389831%0.000000%0.0%018
M number of males in category
F number of females in category
1non-Hispanic 2excluding black and Asian Hispanics

Map of Educational Attainment by Tract in Berlin

Coarse: Post-Secondary Degree Educational Attainment by Tract#15

Percentage of the population 25 years and older with given highest level of educational attainment
23.66%23.80%23.93%24.07%24.20%24.34%

Coarse: High School Diploma Educational Attainment by Tract#16

Percentage of the population 25 years and older with given highest level of educational attainment
61.96%62.02%62.07%62.12%62.17%62.23%

Coarse: No High School Diploma Educational Attainment by Tract#17

Percentage of the population 25 years and older with given highest level of educational attainment
13.69%13.78%13.86%13.95%14.03%14.12%

Detailed: Doctorate Degree Educational Attainment by Tract#18

Percentage of the population 25 years and older with given highest level of educational attainment
0.45%0.58%0.71%0.83%0.96%1.09%

Detailed: Professional Degree Educational Attainment by Tract#19

Percentage of the population 25 years and older with given highest level of educational attainment
0.65%0.80%0.94%1.09%1.23%1.38%

Detailed: Master's Degree Educational Attainment by Tract#20

Percentage of the population 25 years and older with given highest level of educational attainment
2.95%3.39%3.83%4.27%4.70%5.15%

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

Percentage of the population 25 years and older with given highest level of educational attainment
9.50%9.82%10.13%10.43%10.74%11.05%

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

Percentage of the population 25 years and older with given highest level of educational attainment
6.3%6.9%7.6%8.2%8.8%9.5%

Detailed: Some College Educational Attainment by Tract#23

Percentage of the population 25 years and older with given highest level of educational attainment
15.0%16.2%17.5%18.7%19.9%21.2%

Detailed: High School Diploma or Equivalent Educational Attainment by Tract#24

Percentage of the population 25 years and older with given highest level of educational attainment
41.1%42.3%43.5%44.6%45.8%47.0%

Detailed: Some High School Educational Attainment by Tract#25

Percentage of the population 25 years and older with given highest level of educational attainment
9.11%9.56%9.99%10.43%10.87%11.31%

Detailed: Less than High School Educational Attainment by Tract#26

Percentage of the population 25 years and older with given highest level of educational attainment
2.08%2.55%3.01%3.47%3.93%4.39%

Detailed: None Educational Attainment by Tract#27

Percentage of the population 25 years and older with given highest level of educational attainment
0.30%0.37%0.43%0.49%0.55%0.61%
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Educational Attainment by County Subdivision in Wisconsin

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

No H.S. Diploma by County Subdivision#28

Percent of population 25 years of age and older without a high school diploma (or equivalent).
Scope: population of Berlin, selected other county subdivisions in Wisconsin, and entities that contain Berlin
0%5%10%15%Count#BeloitRacineMilwaukeeBerlinBerlinBerlin Area School DistrictBerlinUnited States of AmericaUnited StatesZIP Code 54923ZIP 54923Green BaySheboyganKenoshaGreen Lake CountyGreen LakeManitowocCudahyWausauEast North CentralMidwestWest AllisOshkoshBeaver DamSouth MilwaukeeS MilwaukeeMarshfieldFond du LacFitchburgWisconsinJanesvilleMenomonieGreenfieldPleasant PrairieAppletonFranklinWaukeshaTown of Grand ChuteGrand ChuteLa CrosseWisconsin RapidsCaledoniaWest BendSuperiorTown of MenashaMenashaAshwaubenonEau ClaireStevens PointHowardMount PleasantMt PleasantNeenahOak CreekGermantownOnalaskaMadisonMenomonee FallsNew BerlinOconomowocSun PrairieDe PereMuskegoWauwatosaBrookfieldMiddletonMequon18.491431%18.491431%18.5%4,197117.907441%17.907441%17.9%8,710217.485105%17.485105%17.5%63,80063.8k315.376569%15.376569%15.4%58814.679144%14.679144%14.7%54913.979646%13.979646%14.0%1,04413.020590%13.020590%13.0%27,818,38027.8M12.719298%12.719298%12.7%78312.535944%12.535944%12.5%8,414411.643417%11.643417%11.6%3,806511.549265%11.549265%11.5%7,360611.402065%11.402065%11.4%1,52411.206563%11.206563%11.2%2,609711.082337%11.082337%11.1%1,455810.776184%10.776184%10.8%2,885910.719464%10.719464%10.7%3,363,7843.36M10.244520%10.244520%10.2%4,641,8354.64M10.028497%10.028497%10.0%4,399109.995428%9.995428%10.0%4,154119.950027%9.950027%10.0%1,115129.190270%9.190270%9.2%1,379138.829004%8.829004%8.8%1,091148.713948%8.713948%8.7%2,547158.662728%8.662728%8.7%1,613168.637220%8.637220%8.6%336,096336k8.522583%8.522583%8.5%3,704178.211921%8.211921%8.2%620188.204982%8.204982%8.2%2,296197.709924%7.709924%7.7%1,111207.618904%7.618904%7.6%3,034217.392323%7.392323%7.4%1,924227.158983%7.158983%7.2%3,393237.144208%7.144208%7.1%1,133247.116644%7.116644%7.1%2,075257.048284%7.048284%7.0%889266.746719%6.746719%6.7%1,208276.565400%6.565400%6.6%1,422286.289585%6.289585%6.3%1,142296.244351%6.244351%6.2%829306.168099%6.168099%6.2%739316.128290%6.128290%6.1%2,398326.111996%6.111996%6.1%883336.065319%6.065319%6.1%780346.042598%6.042598%6.0%1,149355.863324%5.863324%5.9%1,015365.765641%5.765641%5.8%1,421375.227570%5.227570%5.2%719384.888290%4.888290%4.9%617394.836248%4.836248%4.8%7,351404.484909%4.484909%4.5%1,165414.236891%4.236891%4.2%1,267423.988090%3.988090%4.0%442433.955766%3.955766%4.0%812443.911088%3.911088%3.9%600453.554446%3.554446%3.6%598463.390471%3.390471%3.4%1,167472.806979%2.806979%2.8%761482.731305%2.731305%2.7%351492.107701%2.107701%2.1%35550
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older without a high school diploma (or equivalent).

Bachelor's Degrees by County Subdivision#29

Percent of population 25 years of age and older with a bachelor's degree or higher..
Scope: population of Berlin, selected other county subdivisions in Wisconsin, and entities that contain Berlin
0%20%40%60%Count#MequonMiddletonWauwatosaBrookfieldMadisonFitchburgOconomowocMenomonee FallsSun PrairieNew BerlinGermantownFranklinStevens PointDe PereWaukeshaOnalaskaMenomonieMuskegoPleasant PrairieLa CrosseMount PleasantMt PleasantNeenahEau ClaireAppletonTown of Grand ChuteGrand ChuteOak CreekUnited States of AmericaUnited StatesMidwestGreenfieldCaledoniaTown of MenashaMenashaHowardEast North CentralWisconsinMarshfieldWest BendAshwaubenonWausauOshkoshGreen BayWest AllisFond du LacMilwaukeeKenoshaSuperiorJanesvilleCudahyManitowocSouth MilwaukeeS MilwaukeeSheboyganBeaver DamGreen Lake CountyGreen LakeRacineBeloitWisconsin RapidsZIP Code 54923ZIP 54923Berlin Area School DistrictBerlinBerlinBerlin63.254765%63.254765%63.3%10,65410.7k158.898140%58.898140%58.9%7,569258.155142%58.155142%58.2%20,01720.0k358.053926%58.053926%58.1%15,73915.7k456.337583%56.337583%56.3%85,63285.6k546.358754%46.358754%46.4%8,632644.229902%44.229902%44.2%4,902741.080228%41.080228%41.1%10,67110.7k841.077605%41.077605%41.1%8,432940.780498%40.780498%40.8%12,19512.2k1039.610295%39.610295%39.6%5,4481137.841472%37.841472%37.8%9,8491236.471240%36.471240%36.5%5,2691336.151489%36.151489%36.2%5,5461435.550164%35.550164%35.6%16,84916.8k1535.152908%35.152908%35.2%4,4371635.139073%35.139073%35.1%2,6531733.499762%33.499762%33.5%5,6361833.074254%33.074254%33.1%4,7661932.942347%32.942347%32.9%9,6052032.747831%32.747831%32.7%6,2272132.464907%32.464907%32.5%5,6202232.432916%32.432916%32.4%12,69112.7k2332.296218%32.296218%32.3%12,86112.9k2432.202535%32.202535%32.2%5,1072531.640023%31.640023%31.6%7,7982630.315023%30.315023%30.3%64,767,78764.8M28.952816%28.952816%29.0%13,118,64213.1M28.921131%28.921131%28.9%8,0932728.919296%28.919296%28.9%5,1782828.909310%28.909310%28.9%3,8382928.794712%28.794712%28.8%3,7033028.462853%28.462853%28.5%8,931,6868.93M28.373439%28.373439%28.4%1,104,0821.10M28.348305%28.348305%28.3%3,5033127.212706%27.212706%27.2%5,8943226.525332%26.525332%26.5%3,1783325.519199%25.519199%25.5%6,8323424.478452%24.478452%24.5%10,17310.2k3524.139215%24.139215%24.1%16,20216.2k3623.980394%23.980394%24.0%10,51910.5k3723.606692%23.606692%23.6%6,9003823.517740%23.517740%23.5%85,81285.8k3922.927488%22.927488%22.9%14,61114.6k4022.415597%22.415597%22.4%4,0704122.035848%22.035848%22.0%9,5774221.471552%21.471552%21.5%2,8194321.017138%21.017138%21.0%4,8934420.519827%20.519827%20.5%3,0794519.530103%19.530103%19.5%6,3844618.623951%18.623951%18.6%2,0874717.694149%17.694149%17.7%2,36517.525031%17.525031%17.5%8,5244816.605719%16.605719%16.6%3,7694915.880441%15.880441%15.9%2,0035015.610786%15.610786%15.6%96114.957151%14.957151%15.0%1,11714.670502%14.670502%14.7%56114.518717%14.518717%14.5%543
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older with a bachelor's degree or higher..

Very Advanced Degrees by County Subdivision#30

Percent of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).
Scope: population of Berlin, selected other county subdivisions in Wisconsin, and entities that contain Berlin
0%5%10%Count#MequonMiddletonBrookfieldMadisonWauwatosaFitchburgMarshfieldMenomonieLa CrosseStevens PointOnalaskaOconomowocNew BerlinUnited States of AmericaUnited StatesMenomonee FallsSun PrairieNeenahFranklinDe PereGermantownMidwestEau ClaireEast North CentralAppletonWisconsinMuskegoPleasant PrairieBeaver DamWausauTown of Grand ChuteGrand ChuteCaledoniaMount PleasantMt PleasantTown of MenashaMenashaWaukeshaMilwaukeeGreenfieldOak CreekBeloitGreen BayKenoshaZIP Code 54923ZIP 54923Wisconsin RapidsBerlin Area School DistrictBerlinBerlinJanesvilleOshkoshBerlinSuperiorGreen Lake CountyGreen LakeFond du LacHowardCudahyWest BendWest AllisRacineManitowocSouth MilwaukeeS MilwaukeeSheboyganAshwaubenon11.084724%11.084724%11.1%1,867110.022566%10.022566%10.0%1,28829.217661%9.217661%9.2%2,49939.171173%9.171173%9.2%13,94013.9k48.094131%8.094131%8.1%2,78657.196563%7.196563%7.2%1,34065.867120%5.867120%5.9%72574.993377%4.993377%5.0%37784.777583%4.777583%4.8%1,39394.679172%4.679172%4.7%676104.547615%4.547615%4.5%574114.222683%4.222683%4.2%468123.762039%3.762039%3.8%1,125133.336158%3.336158%3.3%7,127,6737.13M3.295350%3.295350%3.3%856143.288352%3.288352%3.3%675153.188724%3.188724%3.2%552163.100626%3.100626%3.1%807173.083241%3.083241%3.1%473182.995492%2.995492%3.0%412192.893416%2.893416%2.9%1,311,0191.31M2.869921%2.869921%2.9%1,123202.855432%2.855432%2.9%896,039896k2.794937%2.794937%2.8%1,113212.703886%2.703886%2.7%105,215105k2.674750%2.674750%2.7%450222.637058%2.637058%2.6%380232.552204%2.552204%2.6%286242.416704%2.416704%2.4%647252.396116%2.396116%2.4%380262.356884%2.356884%2.4%422272.303445%2.303445%2.3%438282.244652%2.244652%2.2%298292.192214%2.192214%2.2%1,039302.043126%2.043126%2.0%7,455311.868992%1.868992%1.9%523321.809624%1.809624%1.8%446331.784377%1.784377%1.8%405341.777440%1.777440%1.8%1,193351.762204%1.762204%1.8%1,123361.738142%1.738142%1.7%1071.688734%1.688734%1.7%213371.633637%1.633637%1.6%1221.577540%1.577540%1.6%591.555418%1.555418%1.6%676381.549604%1.549604%1.5%644391.542887%1.542887%1.5%591.525582%1.525582%1.5%277401.511297%1.511297%1.5%2021.454035%1.454035%1.5%425411.384137%1.384137%1.4%178421.302460%1.302460%1.3%171431.292765%1.292765%1.3%280441.251567%1.251567%1.3%549451.155451%1.155451%1.2%562461.133972%1.133972%1.1%264470.893036%0.893036%0.9%134480.868820%0.868820%0.9%284490.784576%0.784576%0.8%9450
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).

Under-Education Sex Ratio by County Subdivision#31

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 Berlin, selected other county subdivisions in Wisconsin, and entities that contain Berlin
Female
Male
1x0x1x2xFM#De PereMenashaOshkoshFranklinCaledoniaManitowocGreen BayPleasant PrairieWauwatosaWaukeshaJanesvilleMt PleasantSuperiorStevens PointAppletonWisconsinGreen LakeRacineGrand ChuteBerlinGermantownMadisonZIP 54923BerlinMuskegoKenoshaMequonMidwestEast North CentralMilwaukeeWest BendOnalaskaUnited StatesEau ClaireWisconsin RapidsMenomonee FallsBeloitBeaver DamLa CrosseBerlinHowardOak CreekGreenfieldMiddletonFond du LacMarshfieldNew BerlinSheboyganNeenahFitchburgSun PrairieWest AllisS MilwaukeeCudahyWausauBrookfieldAshwaubenonMenomonieOconomowoc-1.000000x-1.000000x2.147134x2.147134x2.15x2.553%2.55%5.481%5.48%1-1.000000x-1.000000x1.888774x1.888774x1.89x4.337%4.34%8.192%8.19%2-1.000000x-1.000000x1.812682x1.812682x1.81x7.022%7.02%12.729%12.7%3-1.000000x-1.000000x1.578941x1.578941x1.58x5.723%5.72%9.036%9.04%4-1.000000x-1.000000x1.534399x1.534399x1.53x5.333%5.33%8.182%8.18%5-1.000000x-1.000000x1.432549x1.432549x1.43x9.294%9.29%13.313%13.3%6-1.000000x-1.000000x1.408197x1.408197x1.41x10.435%10.4%14.694%14.7%7-1.000000x-1.000000x1.380848x1.380848x1.38x6.493%6.49%8.965%8.97%8-1.000000x-1.000000x1.306431x1.306431x1.31x2.969%2.97%3.879%3.88%9-1.000000x-1.000000x1.304061x1.304061x1.30x6.240%6.24%8.137%8.14%10-1.000000x-1.000000x1.294088x1.294088x1.29x7.468%7.47%9.664%9.66%11-1.000000x-1.000000x1.293422x1.293422x1.29x5.323%5.32%6.885%6.89%12-1.000000x-1.000000x1.278895x1.278895x1.28x5.545%5.54%7.091%7.09%13-1.000000x-1.000000x1.229327x1.229327x1.23x5.499%5.50%6.760%6.76%14-1.000000x-1.000000x1.219351x1.219351x1.22x6.887%6.89%8.397%8.40%15-1.000000x-1.000000x1.219291x1.219291x1.22x7.799%7.80%9.509%9.51%-1.000000x-1.000000x1.216965x1.216965x1.22x10.296%10.3%12.530%12.5%-1.000000x-1.000000x1.214505x1.214505x1.21x16.245%16.2%19.730%19.7%16-1.000000x-1.000000x1.207489x1.207489x1.21x6.484%6.48%7.830%7.83%17-1.000000x-1.000000x1.205756x1.205756x1.21x12.677%12.7%15.286%15.3%-1.000000x-1.000000x1.203474x1.203474x1.20x4.768%4.77%5.738%5.74%18-1.000000x-1.000000x1.189278x1.189278x1.19x4.425%4.43%5.263%5.26%19-1.000000x-1.000000x1.189114x1.189114x1.19x11.637%11.6%13.838%13.8%-1.000000x-1.000000x1.189045x1.189045x1.19x13.451%13.5%15.993%16.0%-1.000000x-1.000000x1.159324x1.159324x1.16x3.296%3.30%3.822%3.82%20-1.000000x-1.000000x1.152187x1.152187x1.15x10.767%10.8%12.406%12.4%21-1.000000x-1.000000x1.145574x1.145574x1.15x1.970%1.97%2.257%2.26%22-1.000000x-1.000000x1.127915x1.127915x1.13x9.647%9.65%10.881%10.9%-1.000000x-1.000000x1.125371x1.125371x1.13x10.108%10.1%11.375%11.4%-1.000000x-1.000000x1.123984x1.123984x1.12x16.526%16.5%18.574%18.6%23-1.000000x-1.000000x1.118245x1.118245x1.12x6.211%6.21%6.945%6.95%24-1.000000x-1.000000x1.113721x1.113721x1.11x4.646%4.65%5.175%5.17%25-1.000000x-1.000000x1.109070x1.109070x1.11x12.369%12.4%13.719%13.7%-1.000000x-1.000000x1.104897x1.104897x1.10x5.834%5.83%6.446%6.45%26-1.000000x-1.000000x1.104741x1.104741x1.10x6.724%6.72%7.428%7.43%27-1.000000x-1.000000x1.077248x1.077248x1.08x4.329%4.33%4.663%4.66%28-1.000000x-1.000000x1.069954x1.069954x1.07x17.920%17.9%19.173%19.2%29-1.000000x-1.000000x1.063348x1.063348x1.06x9.653%9.65%10.265%10.3%30-1.000000x-1.000000x1.059381x1.059381x1.06x6.918%6.92%7.329%7.33%31-1.000000x-1.000000x1.058709x1.058709x1.06x14.957%15.0%15.836%15.8%-1.000000x-1.000000x1.056613x1.056613x1.06x5.903%5.90%6.237%6.24%32-1.000000x-1.000000x1.048827x1.048827x1.05x5.631%5.63%5.906%5.91%33-1.000000x-1.000000x1.046668x1.046668x1.05x8.030%8.03%8.405%8.40%34-1.000000x-1.000000x1.022109x1.022109x1.02x2.704%2.70%2.764%2.76%35-1.000000x-1.000000x1.018058x1.018058x1.02x8.641%8.64%8.797%8.80%36-1.000000x-1.000000x1.015610x1.015610x1.02x8.765%8.76%8.902%8.90%37-1.000000x-1.000000x1.012610x1.012610x1.01x4.211%4.21%4.265%4.26%38-1.000000x-1.000000x1.004509x1.004509x1.00x11.618%11.6%11.670%11.7%39-1.001253x-1.001253x1.00x1.000000x1.000000x5.867%5.87%5.859%5.86%40-1.016031x-1.016031x1.02x1.000000x1.000000x8.734%8.73%8.596%8.60%41-1.022158x-1.022158x1.02x1.000000x1.000000x3.997%4.00%3.910%3.91%42-1.024115x-1.024115x1.02x1.000000x1.000000x10.145%10.1%9.906%9.91%43-1.068390x-1.068390x1.07x1.000000x1.000000x9.477%9.48%8.871%8.87%44-1.082508x-1.082508x1.08x1.000000x1.000000x11.515%11.5%10.638%10.6%45-1.083232x-1.083232x1.08x1.000000x1.000000x11.187%11.2%10.327%10.3%46-1.121159x-1.121159x1.12x1.000000x1.000000x2.957%2.96%2.637%2.64%47-1.237978x-1.237978x1.24x1.000000x1.000000x6.794%6.79%5.488%5.49%48-1.368790x-1.368790x1.37x1.000000x1.000000x9.414%9.41%6.877%6.88%49-1.427909x-1.427909x1.43x1.000000x1.000000x4.664%4.66%3.266%3.27%50
F percentage of females in category
M percentage of males in category
# rank of county subdivision out of 50 by male-to-female sex ratio

Over-Education Sex Ratio by County Subdivision#32

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 Berlin, selected other county subdivisions in Wisconsin, and entities that contain Berlin
Female
Male
0x2x4xFM#Green LakeBerlinBerlinNeenahPleasant PrairieCudahyMenomonieOnalaskaZIP 54923MuskegoHowardMarshfieldMequonJanesvilleBerlinSheboyganRacineBeaver DamBrookfieldGreen BayBeloitStevens PointWausauFitchburgSun PrairieEau ClaireOshkoshAppletonFond du LacNew BerlinWest AllisWauwatosaWest BendEast North CentralMidwestWisconsinMt PleasantCaledoniaUnited StatesSuperiorManitowocFranklinLa CrosseS MilwaukeeMiddletonMenomonee FallsMadisonMilwaukeeDe PereGrand ChuteKenoshaGermantownWaukeshaOconomowocWisconsin RapidsMenashaGreenfieldOak CreekAshwaubenon-1.000000x-1.000000x4.868069x4.868069x4.87x0.519%0.52%2.524%2.52%-1.000000x-1.000000x3.520744x3.520744x3.52x0.700%0.70%2.466%2.47%-1.000000x-1.000000x3.438414x3.438414x3.44x0.724%0.72%2.490%2.49%-1.000000x-1.000000x3.129204x3.129204x3.13x1.585%1.59%4.960%4.96%1-1.000000x-1.000000x2.927208x2.927208x2.93x1.353%1.35%3.961%3.96%2-1.000000x-1.000000x2.631735x2.631735x2.63x0.722%0.72%1.899%1.90%3-1.000000x-1.000000x2.628013x2.628013x2.63x2.819%2.82%7.408%7.41%4-1.000000x-1.000000x2.571855x2.571855x2.57x2.645%2.64%6.802%6.80%5-1.000000x-1.000000x2.532578x2.532578x2.53x0.991%0.99%2.510%2.51%-1.000000x-1.000000x2.519338x2.519338x2.52x1.531%1.53%3.858%3.86%6-1.000000x-1.000000x2.492011x2.492011x2.49x0.802%0.80%1.999%2.00%7-1.000000x-1.000000x2.351130x2.351130x2.35x3.588%3.59%8.437%8.44%8-1.000000x-1.000000x2.345235x2.345235x2.35x6.743%6.74%15.813%15.8%9-1.000000x-1.000000x2.320788x2.320788x2.32x0.952%0.95%2.209%2.21%10-1.000000x-1.000000x2.303458x2.303458x2.30x0.990%0.99%2.279%2.28%-1.000000x-1.000000x2.236989x2.236989x2.24x0.541%0.54%1.209%1.21%11-1.000000x-1.000000x2.147202x2.147202x2.15x0.747%0.75%1.604%1.60%12-1.000000x-1.000000x2.134058x2.134058x2.13x1.646%1.65%3.514%3.51%13-1.000000x-1.000000x2.050517x2.050517x2.05x6.177%6.18%12.666%12.7%14-1.000000x-1.000000x2.006236x2.006236x2.01x1.188%1.19%2.383%2.38%15-1.000000x-1.000000x2.005610x2.005610x2.01x1.223%1.22%2.453%2.45%16-1.000000x-1.000000x1.994529x1.994529x1.99x3.154%3.15%6.290%6.29%17-1.000000x-1.000000x1.957848x1.957848x1.96x1.658%1.66%3.247%3.25%18-1.000000x-1.000000x1.808864x1.808864x1.81x5.081%5.08%9.190%9.19%19-1.000000x-1.000000x1.806537x1.806537x1.81x2.381%2.38%4.302%4.30%20-1.000000x-1.000000x1.786228x1.786228x1.79x2.083%2.08%3.720%3.72%21-1.000000x-1.000000x1.747870x1.747870x1.75x1.115%1.12%1.949%1.95%22-1.000000x-1.000000x1.733790x1.733790x1.73x2.062%2.06%3.574%3.57%23-1.000000x-1.000000x1.728996x1.728996x1.73x1.083%1.08%1.873%1.87%24-1.000000x-1.000000x1.706236x1.706236x1.71x2.810%2.81%4.794%4.79%25-1.000000x-1.000000x1.693783x1.693783x1.69x0.936%0.94%1.585%1.59%26-1.000000x-1.000000x1.663311x1.663311x1.66x6.193%6.19%10.301%10.3%27-1.000000x-1.000000x1.632200x1.632200x1.63x0.991%0.99%1.617%1.62%28-1.000000x-1.000000x1.597848x1.597848x1.60x2.216%2.22%3.541%3.54%-1.000000x-1.000000x1.589934x1.589934x1.59x2.251%2.25%3.579%3.58%-1.000000x-1.000000x1.576114x1.576114x1.58x2.109%2.11%3.323%3.32%-1.000000x-1.000000x1.557391x1.557391x1.56x1.833%1.83%2.855%2.85%29-1.000000x-1.000000x1.550147x1.550147x1.55x1.851%1.85%2.870%2.87%30-1.000000x-1.000000x1.526215x1.526215x1.53x2.660%2.66%4.060%4.06%-1.000000x-1.000000x1.516809x1.516809x1.52x1.222%1.22%1.853%1.85%31-1.000000x-1.000000x1.494707x1.494707x1.49x0.918%0.92%1.372%1.37%32-1.000000x-1.000000x1.475485x1.475485x1.48x2.501%2.50%3.691%3.69%33-1.000000x-1.000000x1.473120x1.473120x1.47x3.888%3.89%5.727%5.73%34-1.000000x-1.000000x1.458132x1.458132x1.46x0.734%0.73%1.070%1.07%35-1.000000x-1.000000x1.452651x1.452651x1.45x8.299%8.30%12.055%12.1%36-1.000000x-1.000000x1.388151x1.388151x1.39x2.789%2.79%3.872%3.87%37-1.000000x-1.000000x1.387878x1.387878x1.39x7.705%7.70%10.693%10.7%38-1.000000x-1.000000x1.368590x1.368590x1.37x1.742%1.74%2.385%2.38%39-1.000000x-1.000000x1.363936x1.363936x1.36x2.638%2.64%3.598%3.60%40-1.000000x-1.000000x1.256412x1.256412x1.26x2.128%2.13%2.674%2.67%41-1.000000x-1.000000x1.229981x1.229981x1.23x1.588%1.59%1.953%1.95%42-1.000000x-1.000000x1.211592x1.211592x1.21x2.722%2.72%3.299%3.30%43-1.000000x-1.000000x1.195990x1.195990x1.20x2.002%2.00%2.394%2.39%44-1.000000x-1.000000x1.068496x1.068496x1.07x4.087%4.09%4.367%4.37%45-1.000000x-1.000000x1.014900x1.014900x1.01x1.677%1.68%1.702%1.70%46-1.000000x-1.000000x1.008002x1.008002x1.01x2.236%2.24%2.254%2.25%47-1.098352x-1.098352x1.10x1.000000x1.000000x1.951%1.95%1.776%1.78%48-1.142247x-1.142247x1.14x1.000000x1.000000x1.927%1.93%1.687%1.69%49-1.623043x-1.623043x1.62x1.000000x1.000000x0.961%0.96%0.592%0.59%50
F percentage of females in category
M percentage of males in category
# rank of county subdivision out of 50 by male-to-female sex ratio

Educational Attainment by County Subdivision in the Midwest

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

No H.S. Diploma by County Subdivision#33

Percent of population 25 years of age and older without a high school diploma (or equivalent).
Scope: population of Berlin, selected other county subdivisions in the Midwest, and entities that contain Berlin
0%10%20%30%Count#Aurora TownshipAuroraCenter TownshipCtrKansas CityClevelandWayne TownshipWayneDetroitMilwaukeeNorth TownshipNDaytonChicagoProviso TownshipProvisoRockford TownshipRockfordSt. LouisBerlinWarrenBerlinGrand RapidsToledoBlue TownshipBerlin Area School DistrictBerlinCincinnatiAkronSt. PaulSterling HeightsSterling HtsUnited States of AmericaUnited StatesThornton TownshipThorntonZIP Code 54923ZIP 54923WichitaKaw TownshipOmahaBloomingdale TownshipBloomingdaleGreen Lake CountyGreen LakeColumbusMaine TownshipMaineTopekaMinneapolisSpringfield TownshipSpringfieldEast North CentralWorth TownshipWorthMidwestLawrence TownshipLawrenceSioux FallsWisconsinCapital TownshipCapitalWheeling TownshipWheelingPalatine TownshipPalatineSchaumburg TownshipSchaumburgLincolnWashington TownshipWashingtonOlatheFargoCedar RapidsYork TownshipMilton TownshipMiltonMadisonDowners Grove TownshipDowners GrvLisle TownshipLisleOverland ParkAnn Arbor33.464284%33.464284%33.5%29,81429.8k123.165532%23.165532%23.2%22,92622.9k222.659362%22.659362%22.7%21,21821.2k321.582420%21.582420%21.6%54,98155.0k421.037720%21.037720%21.0%18,48918.5k521.003600%21.003600%21.0%90,67890.7k617.485105%17.485105%17.5%63,80063.8k717.062713%17.062713%17.1%17,39117.4k816.928359%16.928359%16.9%14,88914.9k916.905373%16.905373%16.9%309,770310k1015.636222%15.636222%15.6%16,11016.1k1115.608074%15.608074%15.6%18,24118.2k1215.466266%15.466266%15.5%33,80433.8k1315.376569%15.376569%15.4%58815.286174%15.286174%15.3%14,05914.1k1414.679144%14.679144%14.7%54914.563179%14.563179%14.6%17,64317.6k1514.332972%14.332972%14.3%26,34326.3k1614.241047%14.241047%14.2%15,25815.3k1713.979646%13.979646%14.0%1,04413.761583%13.761583%13.8%26,28626.3k1813.591726%13.591726%13.6%17,95118.0k1913.278342%13.278342%13.3%24,61324.6k2013.132171%13.132171%13.1%12,21212.2k2113.020590%13.020590%13.0%27,818,38027.8M12.974232%12.974232%13.0%14,37014.4k2212.719298%12.719298%12.7%78312.568464%12.568464%12.6%31,23131.2k2312.455744%12.455744%12.5%15,16315.2k2412.198899%12.198899%12.2%35,05035.1k2512.171847%12.171847%12.2%9,3752611.402065%11.402065%11.4%1,52411.376979%11.376979%11.4%60,83160.8k2711.132206%11.132206%11.1%10,96511.0k2811.032803%11.032803%11.0%9,3772910.958428%10.958428%11.0%29,34729.3k3010.767091%10.767091%10.8%11,14911.1k3110.719464%10.719464%10.7%3,363,7843.36M10.678962%10.678962%10.7%11,17511.2k3210.244520%10.244520%10.2%4,641,8354.64M10.179618%10.179618%10.2%8,161339.702326%9.702326%9.7%9,123348.637220%8.637220%8.6%336,096336k8.623103%8.623103%8.6%6,837358.424707%8.424707%8.4%9,343368.392669%8.392669%8.4%6,695377.739434%7.739434%7.7%7,226387.092309%7.092309%7.1%11,88611.9k396.804680%6.804680%6.8%6,403406.424130%6.424130%6.4%5,331416.055621%6.055621%6.1%4,270425.981653%5.981653%6.0%5,099435.461095%5.461095%5.5%4,715445.266517%5.266517%5.3%4,126454.836248%4.836248%4.8%7,351464.020265%4.020265%4.0%4,166473.522812%3.522812%3.5%2,870483.377424%3.377424%3.4%4,282493.157717%3.157717%3.2%2,05750
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older without a high school diploma (or equivalent).

Bachelor's Degrees by County Subdivision#34

Percent of population 25 years of age and older with a bachelor's degree or higher..
Scope: population of Berlin, selected other county subdivisions in the Midwest, and entities that contain Berlin
0%20%40%60%Count#Ann ArborOverland ParkMilton TownshipMiltonLisle TownshipLisleMadisonDowners Grove TownshipDowners GrvWashington TownshipWashingtonPalatine TownshipPalatineYork TownshipMinneapolisOlatheWheeling TownshipWheelingSchaumburg TownshipSchaumburgKaw TownshipSt. PaulMaine TownshipMaineFargoLincolnLawrence TownshipLawrenceChicagoCapital TownshipCapitalColumbusOmahaCincinnatiSt. LouisGrand RapidsBloomingdale TownshipBloomingdaleCedar RapidsUnited States of AmericaUnited StatesSioux FallsMidwestWichitaEast North CentralWisconsinSterling HeightsSterling HtsTopekaSpringfield TownshipSpringfieldProviso TownshipProvisoWorth TownshipWorthMilwaukeeRockford TownshipRockfordAkronCenter TownshipCtrNorth TownshipNThornton TownshipThorntonToledoGreen Lake CountyGreen LakeDaytonWarrenWayne TownshipWayneKansas CityClevelandAurora TownshipAuroraBlue TownshipZIP Code 54923ZIP 54923Berlin Area School DistrictBerlinBerlinBerlinDetroit72.810169%72.810169%72.8%47,43047.4k158.823344%58.823344%58.8%74,57874.6k257.681507%57.681507%57.7%45,19045.2k356.900171%56.900171%56.9%46,35646.4k456.337583%56.337583%56.3%85,63285.6k553.762123%53.762123%53.8%55,71155.7k650.610540%50.610540%50.6%47,62347.6k749.860853%49.860853%49.9%39,77539.8k849.728972%49.728972%49.7%42,93542.9k947.670489%47.670489%47.7%127,663128k1046.512581%46.512581%46.5%38,59838.6k1146.409378%46.409378%46.4%51,46851.5k1241.792515%41.792515%41.8%39,02039.0k1341.581304%41.581304%41.6%50,61950.6k1439.969357%39.969357%40.0%74,08874.1k1539.511462%39.511462%39.5%38,91838.9k1638.241175%38.241175%38.2%26,96527.0k1737.146608%37.146608%37.1%62,25462.3k1836.577273%36.577273%36.6%29,32429.3k1936.546320%36.546320%36.5%669,666670k2036.298510%36.298510%36.3%28,78028.8k2134.685843%34.685843%34.7%185,460185k2234.651487%34.651487%34.7%99,56199.6k2333.783048%33.783048%33.8%64,52964.5k2433.007421%33.007421%33.0%72,14372.1k2532.904381%32.904381%32.9%39,86339.9k2632.623147%32.623147%32.6%25,12725.1k2731.793440%31.793440%31.8%27,10227.1k2830.315023%30.315023%30.3%64,767,78764.8M30.259813%30.259813%30.3%28,45328.5k2928.952816%28.952816%29.0%13,118,64213.1M28.877567%28.877567%28.9%71,75771.8k3028.462853%28.462853%28.5%8,931,6868.93M28.373439%28.373439%28.4%1,104,0821.10M27.532180%27.532180%27.5%25,60325.6k3127.007248%27.007248%27.0%22,95423.0k3226.964567%26.964567%27.0%27,92127.9k3326.237989%26.237989%26.2%27,03327.0k3425.217641%25.217641%25.2%26,38926.4k3523.517740%23.517740%23.5%85,81285.8k3621.592552%21.592552%21.6%25,23525.2k3720.213821%20.213821%20.2%26,69726.7k3820.139240%20.139240%20.1%19,93119.9k3919.650916%19.650916%19.7%20,02920.0k4018.971090%18.971090%19.0%21,01221.0k4118.048021%18.048021%18.0%33,17133.2k4217.694149%17.694149%17.7%2,36517.635555%17.635555%17.6%15,51115.5k4317.280259%17.280259%17.3%15,89315.9k4416.826535%16.826535%16.8%14,78814.8k4516.167409%16.167409%16.2%15,13915.1k4616.073076%16.073076%16.1%40,94640.9k4715.929601%15.929601%15.9%14,19214.2k4815.821208%15.821208%15.8%16,95117.0k4915.610786%15.610786%15.6%96114.957151%14.957151%15.0%1,11714.670502%14.670502%14.7%56114.518717%14.518717%14.5%54313.833543%13.833543%13.8%59,72359.7k50
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older with a bachelor's degree or higher..

Very Advanced Degrees by County Subdivision#35

Percent of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).
Scope: population of Berlin, selected other county subdivisions in the Midwest, and entities that contain Berlin
0%5%10%15%Count#Ann ArborMadisonDowners Grove TownshipDowners GrvWashington TownshipWashingtonMinneapolisYork TownshipOverland ParkLisle TownshipLisleSt. PaulKaw TownshipMilton TownshipMiltonSt. LouisCincinnatiLincolnChicagoFargoCapital TownshipCapitalOmahaMaine TownshipMainePalatine TownshipPalatineWheeling TownshipWheelingColumbusUnited States of AmericaUnited StatesTopekaGrand RapidsLawrence TownshipLawrenceSpringfield TownshipSpringfieldCedar RapidsMidwestEast North CentralSioux FallsOlatheWisconsinCenter TownshipCtrSchaumburg TownshipSchaumburgWichitaProviso TownshipProvisoAkronBloomingdale TownshipBloomingdaleRockford TownshipRockfordMilwaukeeWorth TownshipWorthClevelandZIP Code 54923ZIP 54923ToledoBerlin Area School DistrictBerlinBerlinNorth TownshipNBerlinGreen Lake CountyGreen LakeSterling HeightsSterling HtsKansas CityDetroitDaytonWayne TownshipWayneWarrenBlue TownshipAurora TownshipAuroraThornton TownshipThornton17.877867%17.877867%17.9%11,64611.6k19.171173%9.171173%9.2%13,94013.9k27.658384%7.658384%7.7%7,93637.306290%7.306290%7.3%6,87546.241155%6.241155%6.2%16,71416.7k56.197734%6.197734%6.2%5,35165.940071%5.940071%5.9%7,53175.933545%5.933545%5.9%4,83485.920847%5.920847%5.9%10,97511.0k95.896414%5.896414%5.9%7,178105.800061%5.800061%5.8%4,544114.880448%4.880448%4.9%10,66710.7k124.729595%4.729595%4.7%9,034134.568292%4.568292%4.6%7,656144.485379%4.485379%4.5%82,18982.2k154.336789%4.336789%4.3%3,058164.233985%4.233985%4.2%3,357174.059919%4.059919%4.1%11,66511.7k184.030539%4.030539%4.0%3,970193.487439%3.487439%3.5%2,782203.407574%3.407574%3.4%3,779213.357865%3.357865%3.4%17,95418.0k223.336158%3.336158%3.3%7,127,6737.13M3.233245%3.233245%3.2%2,748233.174629%3.174629%3.2%3,846243.083448%3.083448%3.1%2,472252.911721%2.911721%2.9%3,015262.905776%2.905776%2.9%2,477272.893416%2.893416%2.9%1,311,0191.31M2.855432%2.855432%2.9%896,039896k2.841677%2.841677%2.8%2,672282.830666%2.830666%2.8%2,349292.703886%2.703886%2.7%105,215105k2.602914%2.602914%2.6%2,576302.551250%2.551250%2.6%2,382312.519246%2.519246%2.5%6,260322.213918%2.213918%2.2%2,281332.163955%2.163955%2.2%2,858342.113682%2.113682%2.1%1,628352.067272%2.067272%2.1%2,416362.043126%2.043126%2.0%7,455371.958049%1.958049%2.0%2,049381.927780%1.927780%1.9%4,911391.738142%1.738142%1.7%1071.642065%1.642065%1.6%3,018401.633637%1.633637%1.6%1221.577540%1.577540%1.6%591.575684%1.575684%1.6%1,606411.542887%1.542887%1.5%591.511297%1.511297%1.5%2021.439893%1.439893%1.4%1,339421.388310%1.388310%1.4%1,300431.318660%1.318660%1.3%5,693441.257490%1.257490%1.3%1,106451.183365%1.183365%1.2%1,040461.047058%1.047058%1.0%963470.997751%0.997751%1.0%1,069480.936111%0.936111%0.9%834490.876686%0.876686%0.9%97150
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).

Under-Education Sex Ratio by County Subdivision#36

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 Berlin, selected other county subdivisions in the Midwest, and entities that contain Berlin
Female
Male
1x0x1xFM#Cedar RapidsLincolnDetroitOmahaToledoWisconsinGreen LakeBerlinThorntonKansas CityMadisonZIP 54923BerlinLawrenceFargoProvisoRockfordBlue TownshipWayneMidwestTopekaEast North CentralMilwaukeeKaw TownshipDaytonSioux FallsUnited StatesOlatheWorthNOverland ParkAuroraWheelingGrand RapidsSchaumburgChicagoWichitaBerlinColumbusClevelandPalatineCapitalWarrenSpringfieldYork TownshipSt. LouisWashingtonBloomingdaleCtrCincinnatiAkronAnn ArborSt. PaulLisleMinneapolisSterling HtsDowners GrvMiltonMaine-1.000000x-1.000000x1.243824x1.243824x1.24x5.354%5.35%6.660%6.66%1-1.000000x-1.000000x1.238529x1.238529x1.24x6.342%6.34%7.854%7.85%2-1.000000x-1.000000x1.237056x1.237056x1.24x18.951%19.0%23.443%23.4%3-1.000000x-1.000000x1.230289x1.230289x1.23x10.968%11.0%13.494%13.5%4-1.000000x-1.000000x1.227011x1.227011x1.23x12.945%12.9%15.884%15.9%5-1.000000x-1.000000x1.219291x1.219291x1.22x7.799%7.80%9.509%9.51%-1.000000x-1.000000x1.216965x1.216965x1.22x10.296%10.3%12.530%12.5%-1.000000x-1.000000x1.205756x1.205756x1.21x12.677%12.7%15.286%15.3%-1.000000x-1.000000x1.203250x1.203250x1.20x11.909%11.9%14.330%14.3%6-1.000000x-1.000000x1.189752x1.189752x1.19x20.748%20.7%24.685%24.7%7-1.000000x-1.000000x1.189278x1.189278x1.19x4.425%4.43%5.263%5.26%8-1.000000x-1.000000x1.189114x1.189114x1.19x11.637%11.6%13.838%13.8%-1.000000x-1.000000x1.189045x1.189045x1.19x13.451%13.5%15.993%16.0%-1.000000x-1.000000x1.181964x1.181964x1.18x9.406%9.41%11.117%11.1%9-1.000000x-1.000000x1.176963x1.176963x1.18x5.565%5.56%6.550%6.55%10-1.000000x-1.000000x1.174964x1.174964x1.17x14.460%14.5%16.990%17.0%11-1.000000x-1.000000x1.168755x1.168755x1.17x14.456%14.5%16.896%16.9%12-1.000000x-1.000000x1.161774x1.161774x1.16x13.244%13.2%15.387%15.4%13-1.000000x-1.000000x1.132245x1.132245x1.13x19.779%19.8%22.395%22.4%14-1.000000x-1.000000x1.127915x1.127915x1.13x9.647%9.65%10.881%10.9%-1.000000x-1.000000x1.125507x1.125507x1.13x10.423%10.4%11.732%11.7%15-1.000000x-1.000000x1.125371x1.125371x1.13x10.108%10.1%11.375%11.4%-1.000000x-1.000000x1.123984x1.123984x1.12x16.526%16.5%18.574%18.6%16-1.000000x-1.000000x1.115695x1.115695x1.12x11.779%11.8%13.142%13.1%17-1.000000x-1.000000x1.114342x1.114342x1.11x16.070%16.1%17.907%17.9%18-1.000000x-1.000000x1.110589x1.110589x1.11x9.201%9.20%10.219%10.2%19-1.000000x-1.000000x1.109070x1.109070x1.11x12.369%12.4%13.719%13.7%-1.000000x-1.000000x1.107847x1.107847x1.11x6.105%6.11%6.764%6.76%20-1.000000x-1.000000x1.099747x1.099747x1.10x10.199%10.2%11.216%11.2%21-1.000000x-1.000000x1.096598x1.096598x1.10x16.317%16.3%17.894%17.9%22-1.000000x-1.000000x1.095440x1.095440x1.10x3.232%3.23%3.540%3.54%23-1.000000x-1.000000x1.086583x1.086583x1.09x32.102%32.1%34.882%34.9%24-1.000000x-1.000000x1.079846x1.079846x1.08x8.111%8.11%8.758%8.76%25-1.000000x-1.000000x1.078480x1.078480x1.08x14.031%14.0%15.132%15.1%26-1.000000x-1.000000x1.077209x1.077209x1.08x7.467%7.47%8.043%8.04%27-1.000000x-1.000000x1.068021x1.068021x1.07x16.372%16.4%17.486%17.5%28-1.000000x-1.000000x1.059528x1.059528x1.06x12.215%12.2%12.942%12.9%29-1.000000x-1.000000x1.058709x1.058709x1.06x14.957%15.0%15.836%15.8%-1.000000x-1.000000x1.052237x1.052237x1.05x11.098%11.1%11.678%11.7%30-1.000000x-1.000000x1.046686x1.046686x1.05x21.119%21.1%22.105%22.1%31-1.000000x-1.000000x1.039581x1.039581x1.04x8.233%8.23%8.559%8.56%32-1.000000x-1.000000x1.039194x1.039194x1.04x8.470%8.47%8.802%8.80%33-1.000000x-1.000000x1.037373x1.037373x1.04x15.022%15.0%15.584%15.6%34-1.000000x-1.000000x1.028857x1.028857x1.03x10.622%10.6%10.928%10.9%35-1.000000x-1.000000x1.027464x1.027464x1.03x5.391%5.39%5.539%5.54%36-1.000000x-1.000000x1.018183x1.018183x1.02x15.334%15.3%15.613%15.6%37-1.000000x-1.000000x1.013146x1.013146x1.01x6.764%6.76%6.853%6.85%38-1.000000x-1.000000x1.007207x1.007207x1.01x12.130%12.1%12.217%12.2%39-1.000000x-1.000000x1.006204x1.006204x1.01x23.095%23.1%23.239%23.2%40-1.000000x-1.000000x1.001229x1.001229x1.00x13.754%13.8%13.771%13.8%41-1.001506x-1.001506x1.00x1.000000x1.000000x13.601%13.6%13.581%13.6%42-1.031649x-1.031649x1.03x1.000000x1.000000x3.205%3.21%3.107%3.11%43-1.060004x-1.060004x1.06x1.000000x1.000000x13.651%13.7%12.879%12.9%44-1.073696x-1.073696x1.07x1.000000x1.000000x3.642%3.64%3.392%3.39%45-1.092939x-1.092939x1.09x1.000000x1.000000x11.450%11.4%10.476%10.5%46-1.131063x-1.131063x1.13x1.000000x1.000000x13.912%13.9%12.300%12.3%47-1.140051x-1.140051x1.14x1.000000x1.000000x4.269%4.27%3.744%3.74%48-1.194783x-1.194783x1.19x1.000000x1.000000x5.710%5.71%4.779%4.78%49-1.208375x-1.208375x1.21x1.000000x1.000000x12.117%12.1%10.027%10.0%50
F percentage of females in category
M percentage of males in category
# rank of county subdivision out of 50 by male-to-female sex ratio

Over-Education Sex Ratio by County Subdivision#37

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 Berlin, selected other county subdivisions in the Midwest, and entities that contain Berlin
Female
Male
0x2x4xFM#Green LakeBerlinBerlinZIP 54923BerlinRockfordNDaytonSioux FallsCapitalLawrenceDowners GrvAkronLisleWichitaYork TownshipMaineWarrenWheelingBlue TownshipSpringfieldOverland ParkMiltonGrand RapidsOlatheOmahaFargoWashingtonEast North CentralLincolnMidwestBloomingdaleWisconsinKansas CityAuroraUnited StatesAnn ArborTopekaSterling HtsPalatineSchaumburgColumbusMadisonKaw TownshipMilwaukeeCedar RapidsClevelandCincinnatiSt. PaulSt. LouisChicagoWayneCtrToledoMinneapolisWorthDetroitProvisoThornton-1.000000x-1.000000x4.868069x4.868069x4.87x0.519%0.52%2.524%2.52%-1.000000x-1.000000x3.520744x3.520744x3.52x0.700%0.70%2.466%2.47%-1.000000x-1.000000x3.438414x3.438414x3.44x0.724%0.72%2.490%2.49%-1.000000x-1.000000x2.532578x2.532578x2.53x0.991%0.99%2.510%2.51%-1.000000x-1.000000x2.303458x2.303458x2.30x0.990%0.99%2.279%2.28%-1.000000x-1.000000x2.117268x2.117268x2.12x1.353%1.35%2.866%2.87%1-1.000000x-1.000000x2.111054x2.111054x2.11x1.033%1.03%2.181%2.18%2-1.000000x-1.000000x1.989047x1.989047x1.99x0.860%0.86%1.711%1.71%3-1.000000x-1.000000x1.962539x1.962539x1.96x1.928%1.93%3.783%3.78%4-1.000000x-1.000000x1.901348x1.901348x1.90x2.990%2.99%5.686%5.69%5-1.000000x-1.000000x1.879271x1.879271x1.88x2.206%2.21%4.146%4.15%6-1.000000x-1.000000x1.852471x1.852471x1.85x5.456%5.46%10.107%10.1%7-1.000000x-1.000000x1.846298x1.846298x1.85x1.550%1.55%2.862%2.86%8-1.000000x-1.000000x1.815266x1.815266x1.82x4.271%4.27%7.754%7.75%9-1.000000x-1.000000x1.792728x1.792728x1.79x1.819%1.82%3.261%3.26%10-1.000000x-1.000000x1.792314x1.792314x1.79x4.498%4.50%8.062%8.06%11-1.000000x-1.000000x1.788417x1.788417x1.79x2.939%2.94%5.256%5.26%12-1.000000x-1.000000x1.768853x1.768853x1.77x0.769%0.77%1.361%1.36%13-1.000000x-1.000000x1.766097x1.766097x1.77x2.485%2.48%4.389%4.39%14-1.000000x-1.000000x1.761699x1.761699x1.76x0.737%0.74%1.298%1.30%15-1.000000x-1.000000x1.751445x1.751445x1.75x2.146%2.15%3.759%3.76%16-1.000000x-1.000000x1.732234x1.732234x1.73x4.415%4.41%7.647%7.65%17-1.000000x-1.000000x1.695067x1.695067x1.70x4.357%4.36%7.385%7.38%18-1.000000x-1.000000x1.689013x1.689013x1.69x2.382%2.38%4.023%4.02%19-1.000000x-1.000000x1.678153x1.678153x1.68x2.131%2.13%3.576%3.58%20-1.000000x-1.000000x1.669388x1.669388x1.67x3.061%3.06%5.110%5.11%21-1.000000x-1.000000x1.627456x1.627456x1.63x3.304%3.30%5.377%5.38%22-1.000000x-1.000000x1.610803x1.610803x1.61x5.701%5.70%9.183%9.18%23-1.000000x-1.000000x1.597848x1.597848x1.60x2.216%2.22%3.541%3.54%-1.000000x-1.000000x1.596978x1.596978x1.60x3.524%3.52%5.628%5.63%24-1.000000x-1.000000x1.589934x1.589934x1.59x2.251%2.25%3.579%3.58%-1.000000x-1.000000x1.586045x1.586045x1.59x1.649%1.65%2.616%2.62%25-1.000000x-1.000000x1.576114x1.576114x1.58x2.109%2.11%3.323%3.32%-1.000000x-1.000000x1.570028x1.570028x1.57x1.087%1.09%1.707%1.71%26-1.000000x-1.000000x1.550495x1.550495x1.55x0.737%0.74%1.143%1.14%27-1.000000x-1.000000x1.526215x1.526215x1.53x2.660%2.66%4.060%4.06%-1.000000x-1.000000x1.522839x1.522839x1.52x14.269%14.3%21.730%21.7%28-1.000000x-1.000000x1.481288x1.481288x1.48x2.641%2.64%3.912%3.91%29-1.000000x-1.000000x1.476996x1.476996x1.48x1.170%1.17%1.728%1.73%30-1.000000x-1.000000x1.457167x1.457167x1.46x2.851%2.85%4.154%4.15%31-1.000000x-1.000000x1.436165x1.436165x1.44x2.115%2.11%3.037%3.04%32-1.000000x-1.000000x1.413654x1.413654x1.41x2.801%2.80%3.959%3.96%33-1.000000x-1.000000x1.387878x1.387878x1.39x7.705%7.70%10.693%10.7%34-1.000000x-1.000000x1.373250x1.373250x1.37x4.975%4.97%6.832%6.83%35-1.000000x-1.000000x1.368590x1.368590x1.37x1.742%1.74%2.385%2.38%36-1.000000x-1.000000x1.346658x1.346658x1.35x2.491%2.49%3.354%3.35%37-1.000000x-1.000000x1.286599x1.286599x1.29x1.699%1.70%2.186%2.19%38-1.000000x-1.000000x1.280610x1.280610x1.28x4.179%4.18%5.351%5.35%39-1.000000x-1.000000x1.274509x1.274509x1.27x5.228%5.23%6.663%6.66%40-1.000000x-1.000000x1.273345x1.273345x1.27x4.319%4.32%5.500%5.50%41-1.000000x-1.000000x1.238186x1.238186x1.24x4.026%4.03%4.985%4.99%42-1.000000x-1.000000x1.223931x1.223931x1.22x1.068%1.07%1.307%1.31%43-1.000000x-1.000000x1.213574x1.213574x1.21x2.357%2.36%2.860%2.86%44-1.000000x-1.000000x1.141406x1.141406x1.14x1.539%1.54%1.757%1.76%45-1.000000x-1.000000x1.124528x1.124528x1.12x5.872%5.87%6.603%6.60%46-1.000000x-1.000000x1.084697x1.084697x1.08x1.883%1.88%2.042%2.04%47-1.000000x-1.000000x1.046557x1.046557x1.05x1.291%1.29%1.351%1.35%48-1.000000x-1.000000x1.042857x1.042857x1.04x2.171%2.17%2.264%2.26%49-1.706858x-1.706858x1.71x1.000000x1.000000x1.072%1.07%0.628%0.63%50
F percentage of females in category
M percentage of males in category
# rank of county subdivision out of 50 by male-to-female sex ratio

Educational Attainment by County Subdivision in the United States

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

No H.S. Diploma by County Subdivision#38

Percent of population 25 years of age and older without a high school diploma (or equivalent).
Scope: population of Berlin, selected other county subdivisions in the United States, and entities that contain Berlin
0%10%20%Count#San Antonio CentralSan Antonio CntrlBronxSan BernardinoLos AngelesSouthwest DallasSW DallasEl PasoAnaheim-Santa Ana-Garden GroveAnaheim-Santa An…FresnoHoustonMiamiDetroitNortheast DallasNE DallasEast San Gabriel ValleyE San Gabriel VlyFort WorthBrooklynLong Beach-LakewoodLong Bch-LakewoodQueensSan Fernando ValleySan Fernando VlyMilwaukeePhiladelphiaOntarioChicagoBaltimoreOceanside-EscondidoOceanside-Escond…Las VegasBerlinPhoenixBerlinBostonBerlin Area School DistrictBerlinSacramentoOrlandoAustinDenverUnited States of AmericaUnited StatesManhattanSan DiegoTampaSan JoseZIP Code 54923ZIP 54923San FranciscoTucsonAlbuquerqueTownship 1:Charlotte1, CharlotteGreen Lake CountyGreen LakeColumbusTulsaEast North CentralSalt Lake CitySalt Lk CityTown of HempsteadHempsteadMidwestNorthwest HarrisNW HarrisWashingtonAtlantaSeattleWisconsinNortheast TarrantNE TarrantPlanoSeattle East28.998944%28.998944%29.0%126,922127k128.837398%28.837398%28.8%261,022261k227.582802%27.582802%27.6%135,754136k324.837401%24.837401%24.8%434,160434k423.987048%23.987048%24.0%141,940142k523.756417%23.756417%23.8%81,30881.3k622.645542%22.645542%22.6%248,699249k722.107626%22.107626%22.1%92,47292.5k821.922900%21.922900%21.9%457,347457k921.818150%21.818150%21.8%149,688150k1021.003600%21.003600%21.0%90,67890.7k1120.783651%20.783651%20.8%207,494207k1220.461493%20.461493%20.5%128,038128k1320.041576%20.041576%20.0%106,726107k1420.017506%20.017506%20.0%351,046351k1519.402518%19.402518%19.4%73,10573.1k1619.344706%19.344706%19.3%315,505316k1719.344408%19.344408%19.3%244,983245k1817.485105%17.485105%17.5%63,80063.8k1917.390838%17.390838%17.4%180,039180k2017.129346%17.129346%17.1%71,39771.4k2116.905373%16.905373%16.9%309,770310k2216.548703%16.548703%16.5%69,83969.8k2315.999398%15.999398%16.0%70,21470.2k2415.906523%15.906523%15.9%198,651199k2515.376569%15.376569%15.4%58814.952077%14.952077%15.0%308,569309k2614.679144%14.679144%14.7%54914.325556%14.325556%14.3%63,64263.6k2713.979646%13.979646%14.0%1,04413.900512%13.900512%13.9%103,047103k2813.679368%13.679368%13.7%53,75853.8k2913.668915%13.668915%13.7%78,23878.2k3013.638703%13.638703%13.6%63,86563.9k3113.020590%13.020590%13.0%27,818,38027.8M12.996284%12.996284%13.0%160,845161k3212.985760%12.985760%13.0%206,792207k3312.979618%12.979618%13.0%57,75857.8k3412.789590%12.789590%12.8%153,604154k3512.719298%12.719298%12.7%78312.559735%12.559735%12.6%84,02484.0k3612.262851%12.262851%12.3%70,40970.4k3712.089143%12.089143%12.1%52,21752.2k3811.553484%11.553484%11.6%61,37861.4k3911.402065%11.402065%11.4%1,52411.376979%11.376979%11.4%60,83160.8k4011.299086%11.299086%11.3%43,65343.7k4110.719464%10.719464%10.7%3,363,7843.36M10.435356%10.435356%10.4%64,29464.3k4210.384134%10.384134%10.4%54,23054.2k4310.244520%10.244520%10.2%4,641,8354.64M10.135583%10.135583%10.1%47,67947.7k4410.045421%10.045421%10.0%46,51046.5k459.538552%9.538552%9.5%37,37337.4k468.833573%8.833573%8.8%66,22066.2k478.637220%8.637220%8.6%336,096336k8.418271%8.418271%8.4%31,44331.4k485.714681%5.714681%5.7%20,64420.6k494.913852%4.913852%4.9%20,32620.3k50
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older without a high school diploma (or equivalent).

Bachelor's Degrees by County Subdivision#39

Percent of population 25 years of age and older with a bachelor's degree or higher..
Scope: population of Berlin, selected other county subdivisions in the United States, and entities that contain Berlin
0%20%40%60%Count#ManhattanSeattle EastWashingtonSan FranciscoPlanoSan JoseAtlantaSeattleBostonDenverAustinTownship 1:Charlotte1, CharlotteTown of HempsteadHempsteadSan DiegoNortheast TarrantNE TarrantNorthwest HarrisNW HarrisChicagoColumbusLos AngelesBrooklynSan Fernando ValleySan Fernando VlyNortheast DallasNE DallasSalt Lake CitySalt Lk CityAlbuquerqueTampaTucsonOceanside-EscondidoOceanside-Escond…TulsaQueensUnited States of AmericaUnited StatesHoustonBaltimoreLong Beach-LakewoodLong Bch-LakewoodMidwestPhoenixOrlandoEast North CentralAnaheim-Santa Ana-Garden GroveAnaheim-Santa An…WisconsinSacramentoEast San Gabriel ValleyE San Gabriel VlyOntarioPhiladelphiaMiamiFort WorthSouthwest DallasSW DallasMilwaukeeFresnoLas VegasEl PasoBronxGreen Lake CountyGreen LakeSan BernardinoZIP Code 54923ZIP 54923Berlin Area School DistrictBerlinSan Antonio CentralSan Antonio CntrlBerlinBerlinDetroit60.434640%60.434640%60.4%747,953748k157.691220%57.691220%57.7%238,638239k255.360186%55.360186%55.4%256,316256k354.793235%54.793235%54.8%366,564367k454.142756%54.142756%54.1%195,588196k549.985845%49.985845%50.0%600,334600k649.803731%49.803731%49.8%195,136195k749.626221%49.626221%49.6%372,018372k846.377869%46.377869%46.4%206,036206k945.718966%45.718966%45.7%214,085214k1044.843364%44.843364%44.8%256,674257k1141.989192%41.989192%42.0%223,068223k1238.767308%38.767308%38.8%202,458202k1338.701072%38.701072%38.7%616,296616k1438.547398%38.547398%38.5%143,978144k1536.877886%36.877886%36.9%173,478173k1636.546320%36.546320%36.5%669,666670k1734.685843%34.685843%34.7%185,460185k1834.593243%34.593243%34.6%604,693605k1934.081468%34.081468%34.1%597,685598k2033.231104%33.231104%33.2%420,848421k2133.191099%33.191099%33.2%331,364331k2233.118385%33.118385%33.1%204,048204k2332.636312%32.636312%32.6%140,967141k2432.512191%32.512191%32.5%144,676145k2532.087814%32.087814%32.1%184,237184k2631.198303%31.198303%31.2%136,915137k2731.110082%31.110082%31.1%120,191120k2830.595789%30.595789%30.6%499,006499k2930.315023%30.315023%30.3%64,767,78764.8M30.080133%30.080133%30.1%627,520628k3029.719611%29.719611%29.7%125,423125k3129.113198%29.113198%29.1%109,693110k3228.952816%28.952816%29.0%13,118,64213.1M28.760152%28.760152%28.8%593,529594k3328.535877%28.535877%28.5%112,142112k3428.462853%28.462853%28.5%8,931,6868.93M28.412939%28.412939%28.4%312,038312k3528.373439%28.373439%28.4%1,104,0821.10M28.231204%28.231204%28.2%209,283209k3627.276345%27.276345%27.3%170,682171k3726.758411%26.758411%26.8%111,532112k3826.349720%26.349720%26.3%272,786273k3926.011156%26.011156%26.0%178,455178k4024.665414%24.665414%24.7%131,349131k4123.764821%23.764821%23.8%140,625141k4223.517740%23.517740%23.5%85,81285.8k4322.486319%22.486319%22.5%94,05694.1k4421.702666%21.702666%21.7%271,037271k4521.071885%21.071885%21.1%72,12072.1k4619.131504%19.131504%19.1%173,169173k4717.694149%17.694149%17.7%2,36516.375473%16.375473%16.4%80,59580.6k4815.610786%15.610786%15.6%96114.957151%14.957151%15.0%1,11714.929012%14.929012%14.9%65,34165.3k4914.670502%14.670502%14.7%56114.518717%14.518717%14.5%54313.833543%13.833543%13.8%59,72359.7k50
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older with a bachelor's degree or higher..

Very Advanced Degrees by County Subdivision#40

Percent of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).
Scope: population of Berlin, selected other county subdivisions in the United States, and entities that contain Berlin
0%5%10%Count#WashingtonManhattanSan FranciscoBostonAtlantaSeattleSan JoseSeattle EastDenverSan DiegoAustinBaltimoreLos AngelesAlbuquerquePlanoChicagoTucsonTown of HempsteadHempsteadTampaMiamiNortheast DallasNE DallasSalt Lake CitySalt Lk CityHoustonPhiladelphiaSan Fernando ValleySan Fernando VlyTownship 1:Charlotte1, CharlotteOceanside-EscondidoOceanside-Escond…BrooklynSacramentoColumbusUnited States of AmericaUnited StatesTulsaPhoenixLong Beach-LakewoodLong Bch-LakewoodMidwestOrlandoEast North CentralFresnoAnaheim-Santa Ana-Garden GroveAnaheim-Santa An…QueensWisconsinNorthwest HarrisNW HarrisNortheast TarrantNE TarrantEast San Gabriel ValleyE San Gabriel VlyOntarioFort WorthLas VegasMilwaukeeSan BernardinoSan Antonio CentralSan Antonio CntrlEl PasoZIP Code 54923ZIP 54923Southwest DallasSW DallasBronxBerlin Area School DistrictBerlinBerlinBerlinGreen Lake CountyGreen LakeDetroit12.461852%12.461852%12.5%57,69857.7k110.788423%10.788423%10.8%133,520134k27.558053%7.558053%7.6%50,56350.6k37.340604%7.340604%7.3%32,61132.6k46.889819%6.889819%6.9%26,99527.0k56.641855%6.641855%6.6%49,79049.8k66.255912%6.255912%6.3%75,13475.1k76.036065%6.036065%6.0%24,96825.0k85.725842%5.725842%5.7%26,81226.8k95.247128%5.247128%5.2%83,55883.6k105.058711%5.058711%5.1%28,95529.0k114.934352%4.934352%4.9%20,82420.8k124.659072%4.659072%4.7%81,44181.4k134.631274%4.631274%4.6%20,00420.0k144.617088%4.617088%4.6%16,67916.7k154.485379%4.485379%4.5%82,18982.2k164.461087%4.461087%4.5%25,61425.6k174.441262%4.441262%4.4%23,19423.2k184.325266%4.325266%4.3%19,24719.2k194.025531%4.025531%4.0%27,61827.6k203.827408%3.827408%3.8%38,21138.2k213.792624%3.792624%3.8%23,36723.4k223.737871%3.737871%3.7%77,97878.0k233.720350%3.720350%3.7%38,51538.5k243.601468%3.601468%3.6%45,61045.6k253.490252%3.490252%3.5%18,54218.5k263.466073%3.466073%3.5%15,21115.2k273.384967%3.384967%3.4%59,36259.4k283.380196%3.380196%3.4%25,05825.1k293.357865%3.357865%3.4%17,95418.0k303.336158%3.336158%3.3%7,127,6737.13M3.140490%3.140490%3.1%12,13312.1k313.010825%3.010825%3.0%62,13562.1k323.009440%3.009440%3.0%11,33911.3k332.893416%2.893416%2.9%1,311,0191.31M2.893233%2.893233%2.9%11,37011.4k342.855432%2.855432%2.9%896,039896k2.828959%2.828959%2.8%11,83311.8k352.763004%2.763004%2.8%30,34430.3k362.756960%2.756960%2.8%44,96545.0k372.703886%2.703886%2.7%105,215105k2.682967%2.682967%2.7%12,62112.6k382.630994%2.630994%2.6%9,827392.484535%2.484535%2.5%15,54715.5k402.324315%2.324315%2.3%9,688412.173239%2.173239%2.2%11,57311.6k422.155077%2.155077%2.2%26,91426.9k432.043126%2.043126%2.0%7,455441.807306%1.807306%1.8%8,895451.792414%1.792414%1.8%7,845461.745764%1.745764%1.7%5,975471.738142%1.738142%1.7%1071.704476%1.704476%1.7%10,08610.1k481.664253%1.664253%1.7%15,06415.1k491.633637%1.633637%1.6%1221.577540%1.577540%1.6%591.542887%1.542887%1.5%591.511297%1.511297%1.5%2021.318660%1.318660%1.3%5,69350
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).

Under-Education Sex Ratio by County Subdivision#41

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 Berlin, selected other county subdivisions in the United States, and entities that contain Berlin
Female
Male
1x0x1xFM#1, CharlotteDetroitWisconsinGreen LakeBerlinZIP 54923BerlinBaltimoreTulsaSW DallasMidwestFresnoEast North CentralMilwaukeeUnited StatesNE DallasHoustonHempsteadOrlandoPhiladelphiaOntarioSan BernardinoAustinAtlantaFort WorthPhoenixChicagoAlbuquerqueWashingtonBerlinSacramentoColumbusSalt Lk CityDenverNE TarrantTampaOceanside-EscondidoOceanside-Escond…NW HarrisBronxPlanoBrooklynSan Antonio CntrlSan Fernando VlyTucsonAnaheim-Santa Ana-Gdn GrvAnaheim-Santa An…Los AngelesLas VegasBostonE San Gabriel VlyQueensMiamiManhattanSeattleLong Bch-LakewoodSeattle EastSan JoseSan DiegoSan FranciscoEl Paso-1.000000x-1.000000x1.285784x1.285784x1.29x10.185%10.2%13.096%13.1%1-1.000000x-1.000000x1.237056x1.237056x1.24x18.951%19.0%23.443%23.4%2-1.000000x-1.000000x1.219291x1.219291x1.22x7.799%7.80%9.509%9.51%-1.000000x-1.000000x1.216965x1.216965x1.22x10.296%10.3%12.530%12.5%-1.000000x-1.000000x1.205756x1.205756x1.21x12.677%12.7%15.286%15.3%-1.000000x-1.000000x1.189114x1.189114x1.19x11.637%11.6%13.838%13.8%-1.000000x-1.000000x1.189045x1.189045x1.19x13.451%13.5%15.993%16.0%-1.000000x-1.000000x1.179669x1.179669x1.18x15.289%15.3%18.036%18.0%3-1.000000x-1.000000x1.177766x1.177766x1.18x10.417%10.4%12.268%12.3%4-1.000000x-1.000000x1.160109x1.160109x1.16x22.304%22.3%25.875%25.9%5-1.000000x-1.000000x1.127915x1.127915x1.13x9.647%9.65%10.881%10.9%-1.000000x-1.000000x1.127206x1.127206x1.13x20.830%20.8%23.479%23.5%6-1.000000x-1.000000x1.125371x1.125371x1.13x10.108%10.1%11.375%11.4%-1.000000x-1.000000x1.123984x1.123984x1.12x16.526%16.5%18.574%18.6%7-1.000000x-1.000000x1.109070x1.109070x1.11x12.369%12.4%13.719%13.7%-1.000000x-1.000000x1.099797x1.099797x1.10x19.814%19.8%21.791%21.8%8-1.000000x-1.000000x1.099188x1.099188x1.10x20.902%20.9%22.975%23.0%9-1.000000x-1.000000x1.092101x1.092101x1.09x9.951%9.95%10.868%10.9%10-1.000000x-1.000000x1.090284x1.090284x1.09x13.111%13.1%14.294%14.3%11-1.000000x-1.000000x1.090163x1.090163x1.09x16.700%16.7%18.206%18.2%12-1.000000x-1.000000x1.088515x1.088515x1.09x16.417%16.4%17.871%17.9%13-1.000000x-1.000000x1.081887x1.081887x1.08x26.536%26.5%28.709%28.7%14-1.000000x-1.000000x1.078150x1.078150x1.08x13.148%13.1%14.176%14.2%15-1.000000x-1.000000x1.073220x1.073220x1.07x9.215%9.21%9.889%9.89%16-1.000000x-1.000000x1.071348x1.071348x1.07x19.379%19.4%20.762%20.8%17-1.000000x-1.000000x1.069008x1.069008x1.07x14.467%14.5%15.465%15.5%18-1.000000x-1.000000x1.068021x1.068021x1.07x16.372%16.4%17.486%17.5%19-1.000000x-1.000000x1.066879x1.066879x1.07x11.714%11.7%12.497%12.5%20-1.000000x-1.000000x1.064309x1.064309x1.06x9.751%9.75%10.378%10.4%21-1.000000x-1.000000x1.058709x1.058709x1.06x14.957%15.0%15.836%15.8%-1.000000x-1.000000x1.053268x1.053268x1.05x13.558%13.6%14.280%14.3%22-1.000000x-1.000000x1.052237x1.052237x1.05x11.098%11.1%11.678%11.7%23-1.000000x-1.000000x1.051272x1.051272x1.05x10.176%10.2%10.697%10.7%24-1.000000x-1.000000x1.049933x1.049933x1.05x13.307%13.3%13.971%14.0%25-1.000000x-1.000000x1.040742x1.040742x1.04x8.257%8.26%8.594%8.59%26-1.000000x-1.000000x1.040003x1.040003x1.04x12.734%12.7%13.244%13.2%27-1.000000x-1.000000x1.039910x1.039910x1.04x15.694%15.7%16.321%16.3%28-1.000000x-1.000000x1.038394x1.038394x1.04x9.953%9.95%10.335%10.3%29-1.000000x-1.000000x1.030539x1.030539x1.03x28.448%28.4%29.316%29.3%30-1.000000x-1.000000x1.023151x1.023151x1.02x5.652%5.65%5.783%5.78%31-1.000000x-1.000000x1.018960x1.018960x1.02x19.845%19.8%20.221%20.2%32-1.000000x-1.000000x1.003929x1.003929x1.00x28.944%28.9%29.058%29.1%33-1.000000x-1.000000x1.003840x1.003840x1.00x19.308%19.3%19.383%19.4%34-1.006471x-1.006471x1.01x1.000000x1.000000x12.301%12.3%12.222%12.2%35-1.008020x-1.008020x1.01x1.000000x1.000000x22.734%22.7%22.553%22.6%36-1.013004x-1.013004x1.01x1.000000x1.000000x24.995%25.0%24.674%24.7%37-1.016645x-1.016645x1.02x1.000000x1.000000x16.036%16.0%15.774%15.8%38-1.022333x-1.022333x1.02x1.000000x1.000000x14.476%14.5%14.159%14.2%39-1.026902x-1.026902x1.03x1.000000x1.000000x20.723%20.7%20.180%20.2%40-1.027762x-1.027762x1.03x1.000000x1.000000x19.596%19.6%19.067%19.1%41-1.030897x-1.030897x1.03x1.000000x1.000000x22.136%22.1%21.473%21.5%42-1.044246x-1.044246x1.04x1.000000x1.000000x13.260%13.3%12.698%12.7%43-1.049689x-1.049689x1.05x1.000000x1.000000x9.047%9.05%8.619%8.62%44-1.056864x-1.056864x1.06x1.000000x1.000000x19.921%19.9%18.849%18.8%45-1.057675x-1.057675x1.06x1.000000x1.000000x5.050%5.05%4.774%4.77%46-1.127548x-1.127548x1.13x1.000000x1.000000x13.555%13.6%12.021%12.0%47-1.168454x-1.168454x1.17x1.000000x1.000000x13.975%14.0%11.960%12.0%48-1.228758x-1.228758x1.23x1.000000x1.000000x13.883%13.9%11.298%11.3%49-1.276282x-1.276282x1.28x1.000000x1.000000x26.394%26.4%20.680%20.7%50
F percentage of females in category
M percentage of males in category
# rank of county subdivision out of 50 by male-to-female sex ratio

Over-Education Sex Ratio by County Subdivision#42

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 Berlin, selected other county subdivisions in the United States, and entities that contain Berlin
Female
Male
0x2x4xFM#Green LakeBerlinBerlinZIP 54923BerlinEl PasoSalt Lk CityPlanoTulsaAlbuquerqueNE DallasFort WorthOrlandoPhoenixTucson1, CharlotteEast North CentralMidwestNW HarrisLas VegasWisconsinSeattle EastSan Antonio CntrlSan DiegoUnited StatesSan JoseHempsteadFresnoNE TarrantTampaSan Fernando VlyE San Gabriel VlyHoustonSan BernardinoColumbusMiamiAtlantaMilwaukeeAnaheim-Santa Ana-Gdn GrvAnaheim-Santa An…SacramentoPhiladelphiaOceanside-EscondidoOceanside-Escond…Los AngelesAustinBaltimoreWashingtonQueensSW DallasBrooklynManhattanChicagoSeattleBostonBronxOntarioLong Bch-LakewoodDenverSan FranciscoDetroit-1.000000x-1.000000x4.868069x4.868069x4.87x0.519%0.52%2.524%2.52%-1.000000x-1.000000x3.520744x3.520744x3.52x0.700%0.70%2.466%2.47%-1.000000x-1.000000x3.438414x3.438414x3.44x0.724%0.72%2.490%2.49%-1.000000x-1.000000x2.532578x2.532578x2.53x0.991%0.99%2.510%2.51%-1.000000x-1.000000x2.303458x2.303458x2.30x0.990%0.99%2.279%2.28%-1.000000x-1.000000x2.132933x2.132933x2.13x1.146%1.15%2.445%2.44%1-1.000000x-1.000000x2.053360x2.053360x2.05x2.488%2.49%5.109%5.11%2-1.000000x-1.000000x1.782054x1.782054x1.78x3.355%3.35%5.978%5.98%3-1.000000x-1.000000x1.720683x1.720683x1.72x2.338%2.34%4.022%4.02%4-1.000000x-1.000000x1.707718x1.707718x1.71x3.458%3.46%5.905%5.91%5-1.000000x-1.000000x1.692229x1.692229x1.69x2.857%2.86%4.836%4.84%6-1.000000x-1.000000x1.684272x1.684272x1.68x1.637%1.64%2.757%2.76%7-1.000000x-1.000000x1.660799x1.660799x1.66x2.196%2.20%3.647%3.65%8-1.000000x-1.000000x1.659024x1.659024x1.66x2.280%2.28%3.783%3.78%9-1.000000x-1.000000x1.621815x1.621815x1.62x3.429%3.43%5.561%5.56%10-1.000000x-1.000000x1.611479x1.611479x1.61x2.711%2.71%4.369%4.37%11-1.000000x-1.000000x1.597848x1.597848x1.60x2.216%2.22%3.541%3.54%-1.000000x-1.000000x1.589934x1.589934x1.59x2.251%2.25%3.579%3.58%-1.000000x-1.000000x1.579303x1.579303x1.58x2.100%2.10%3.317%3.32%12-1.000000x-1.000000x1.576623x1.576623x1.58x1.677%1.68%2.643%2.64%13-1.000000x-1.000000x1.576114x1.576114x1.58x2.109%2.11%3.323%3.32%-1.000000x-1.000000x1.557664x1.557664x1.56x4.733%4.73%7.372%7.37%14-1.000000x-1.000000x1.540473x1.540473x1.54x1.423%1.42%2.192%2.19%15-1.000000x-1.000000x1.529565x1.529565x1.53x4.164%4.16%6.370%6.37%16-1.000000x-1.000000x1.526215x1.526215x1.53x2.660%2.66%4.060%4.06%-1.000000x-1.000000x1.514156x1.514156x1.51x4.979%4.98%7.539%7.54%17-1.000000x-1.000000x1.488724x1.488724x1.49x3.608%3.61%5.371%5.37%18-1.000000x-1.000000x1.484269x1.484269x1.48x2.293%2.29%3.404%3.40%19-1.000000x-1.000000x1.481801x1.481801x1.48x2.138%2.14%3.168%3.17%20-1.000000x-1.000000x1.476874x1.476874x1.48x3.518%3.52%5.196%5.20%21-1.000000x-1.000000x1.460302x1.460302x1.46x2.944%2.94%4.299%4.30%22-1.000000x-1.000000x1.451775x1.451775x1.45x2.041%2.04%2.963%2.96%23-1.000000x-1.000000x1.424636x1.424636x1.42x3.092%3.09%4.404%4.40%24-1.000000x-1.000000x1.423621x1.423621x1.42x1.501%1.50%2.137%2.14%25-1.000000x-1.000000x1.413654x1.413654x1.41x2.801%2.80%3.959%3.96%26-1.000000x-1.000000x1.395174x1.395174x1.40x3.384%3.38%4.722%4.72%27-1.000000x-1.000000x1.391590x1.391590x1.39x5.799%5.80%8.070%8.07%28-1.000000x-1.000000x1.368590x1.368590x1.37x1.742%1.74%2.385%2.38%29-1.000000x-1.000000x1.362600x1.362600x1.36x2.347%2.35%3.199%3.20%30-1.000000x-1.000000x1.359928x1.359928x1.36x2.888%2.89%3.927%3.93%31-1.000000x-1.000000x1.341930x1.341930x1.34x3.216%3.22%4.316%4.32%32-1.000000x-1.000000x1.310218x1.310218x1.31x3.011%3.01%3.945%3.95%33-1.000000x-1.000000x1.308108x1.308108x1.31x4.045%4.05%5.292%5.29%34-1.000000x-1.000000x1.303834x1.303834x1.30x4.384%4.38%5.716%5.72%35-1.000000x-1.000000x1.303196x1.303196x1.30x4.332%4.33%5.645%5.65%36-1.000000x-1.000000x1.300117x1.300117x1.30x10.922%10.9%14.199%14.2%37-1.000000x-1.000000x1.285200x1.285200x1.29x2.428%2.43%3.121%3.12%38-1.000000x-1.000000x1.265486x1.265486x1.27x1.515%1.51%1.917%1.92%39-1.000000x-1.000000x1.262281x1.262281x1.26x3.021%3.02%3.814%3.81%40-1.000000x-1.000000x1.245683x1.245683x1.25x9.673%9.67%12.050%12.1%41-1.000000x-1.000000x1.238186x1.238186x1.24x4.026%4.03%4.985%4.99%42-1.000000x-1.000000x1.228890x1.228890x1.23x5.961%5.96%7.326%7.33%43-1.000000x-1.000000x1.221037x1.221037x1.22x6.643%6.64%8.112%8.11%44-1.000000x-1.000000x1.202385x1.202385x1.20x1.526%1.53%1.834%1.83%45-1.000000x-1.000000x1.198236x1.198236x1.20x2.119%2.12%2.539%2.54%46-1.000000x-1.000000x1.181998x1.181998x1.18x2.766%2.77%3.269%3.27%47-1.000000x-1.000000x1.129665x1.129665x1.13x5.378%5.38%6.075%6.08%48-1.000000x-1.000000x1.098720x1.098720x1.10x7.194%7.19%7.905%7.90%49-1.000000x-1.000000x1.046557x1.046557x1.05x1.291%1.29%1.351%1.35%50
F percentage of females in category
M percentage of males in category
# rank of county subdivision out of 50 by male-to-female sex ratio

Definitions

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

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

The coarse levels of educational attainment are as follows:

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

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

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State:
Wisconsin
County:
Green Lake
City:
Berlin
ZIP Code:
54923
Unified School District:
Berlin
Congressional District:
WI-6
State Senate District:
WI-14
Assembly District:
WI-41
Neighboring Towns:
Aurora, Berlin
Nearby Towns:
Brooklyn, Nepeuskun, Poy Sippi, Ripon, Rushford, Seneca, St. Marie, Warren