Educational Attainment in Berlin, Coos County, New Hampshire (City)

Educational Attainment#1

Highest level of education among people aged 25 years and older.
Scope: population of Coos County and Berlin
Berlin
Coos County
0%10%20%30%40%50%60%CountHigher Degree1H.S. Diploma2No H.S. Diploma222.731368%28.305325%22.731368%22.7%1,76662.556314%59.562665%62.556314%62.6%4,86014.712318%12.132011%14.712318%14.7%1,143
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 Coos County at large.
Scope: population of Coos County and Berlin
-20%0%+20%%ref.Higher Degree1H.S. Diploma2No H.S. Diploma2-19.692255%-19.692255%-19.7%22.731%22.7%28.305%28.3%5.026050%5.026050%+5.0%62.556%62.6%59.563%59.6%21.268591%21.268591%+21.3%14.712%14.7%12.132%12.1%
% percentage with given level in Berlin
ref. percentage with given level in Coos 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 Coos County and Berlin
Berlin
Coos County
0%10%20%30%40%CountDoctorate1Professional1Master's1Bachelor's1Associate's1Some CollegeHigh School2Some H.S.3Less than H.S.3None0.296048%0.599312%0.296048%0.3%230.154460%0.854424%0.154460%0.2%121.750547%4.579874%1.750547%1.8%1369.756725%11.723021%9.756725%9.8%75810.773587%10.548694%10.773587%10.8%83718.367872%20.380644%18.367872%18.4%1,42744.188441%39.182021%44.188441%44.2%3,43310.130004%8.807451%10.130004%10.1%7873.784271%2.810285%3.784271%3.8%2940.798044%0.514274%0.798044%0.8%62
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 Coos County at large.
Scope: population of Coos County and Berlin
-50%0%+50%%ref.Doctorate1Professional1Master's1Bachelor's1Associate's1Some CollegeHigh School2Some H.S.3Less than H.S.3None-50.601924%-50.601924%-50.6%0.296%0.30%0.599%0.60%-81.922320%-81.922320%-81.9%0.154%0.15%0.854%0.85%-61.777401%-61.777401%-61.8%1.751%1.75%4.580%4.58%-16.772941%-16.772941%-16.8%9.757%9.76%11.723%11.7%2.131954%2.131954%+2.1%10.774%10.8%10.549%10.5%-9.875898%-9.875898%-9.9%18.368%18.4%20.381%20.4%12.777342%12.777342%+12.8%44.188%44.2%39.182%39.2%15.016297%15.016297%+15.0%10.130%10.1%8.807%8.81%34.657879%34.657879%+34.7%3.784%3.78%2.810%2.81%55.178617%55.178617%+55.2%0.798%0.80%0.514%0.51%
% percentage with given level in Berlin
ref. percentage with given level in Coos 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 Coos County and Berlin
More Females More Males
Coos County
Berlin
50%0%FMHigher Degree1H.S. Diploma2No H.S. Diploma2-80.301163%-32.480435%-80.301163%80%30.587%30.6%16.964%17.0%24.585802%9.901735%24.585802%25%54.789%54.8%68.259%68.3%1.041264%21.796788%1.041264%1%14.625%14.6%14.777%14.8%
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 Coos County and Berlin
More Females More Males
Coos County
Berlin
1k%0k%1k%FMDoctorate1Professional1Master's1Bachelor's1Associate's1Some CollegeHigh School2Some H.S.3Less than H.S.3None1,000.000000%19.926013%1,000.000000%> 1000%0.000%0%0.513%0.51%-1,000.000000%-1,000.000000%> 1000%39.833387%0.334%0.33%0.022%0.02%-57.832506%-63.507944%-57.832506%0k%2.220%2.22%1.406%1.41%-144.778805%-52.290954%-144.778805%0k%14.807%14.8%6.049%6.05%-47.393165%-12.072180%-47.393165%0k%13.226%13.2%8.973%8.97%-5.864972%14.332957%14.332957%0k%16.966%17.0%19.397%19.4%29.184748%19.009290%29.184748%0k%37.823%37.8%48.862%48.9%30.746466%36.963880%30.746466%0k%8.604%8.60%11.250%11.3%-94.748837%-18.494523%-94.748837%0k%5.260%5.26%2.701%2.70%8.654464%28.201451%8.654464%0k%0.760%0.76%0.826%0.83%
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 Coos County and Berlin
Berlin
Coos County
0%5%10%15%B.X.Total65+45-6435-4425-343.715170%7.801214%3.715170%3.7%721,93812.631962%12.935180%12.631962%12.6%3472,7477.534247%10.801753%7.534247%7.5%1211,60614.749662%16.905034%14.749662%14.7%2181,478
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 Coos County at large.
Scope: population of Coos County and Berlin
50%40%30%20%10%0%%ref.65+45-6435-4425-34-52.377021%-52.377021%52.4%3.715%3.72%7.801%7.80%-2.344132%-2.344132%2.3%12.632%12.6%12.935%12.9%-30.249779%-30.249779%30.2%7.534%7.53%10.802%10.8%-12.749886%-12.749886%12.7%14.750%14.7%16.905%16.9%
% percentage in Berlin with a Bachelor's degree
ref percentage in Coos 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 Coos County and Berlin
More Females More Males
Coos County
Berlin
200%100%0%FM65+45-6435-4425-34-48.496155%-48.496155%48.5%5.485735%4.291%4.29%2.889%2.89%-164.713819%-70.475307%-164.713819%164.7%19.707%19.7%7.445%7.44%-171.288948%-26.000224%-171.288948%171.3%13.294%13.3%4.900%4.90%-287.279790%-155.175116%-287.279790%287.3%29.522%29.5%7.623%7.62%
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 Coos County and Berlin
Berlin
Coos County
$0k$10k$20k$30kCount%Bachelor's DegreeSome CollegeH.S. Diploma2No H.S. Diploma2Total$37,365.000000$36,824.000000$37,365.000000$37.4k7589.757%9.76%$33,727.000000$30,439.000000$33,727.000000$33.7k2,26429.141%29.1%$26,897.000000$26,180.000000$26,897.000000$26.9k3,43344.188%44.2%$15,491.000000$20,161.000000$15,491.000000$15.5k1,14314.712%14.7%$30,500.000000$29,537.000000$30,500.000000$30.5k7,769100.000%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 Coos County and Berlin
Female Male
Coos County
Berlin
Shaded bar tips show excess over facing bar.
$20k$0k$20k$40kFMBachelor's DegreeSome CollegeH.S. Diploma2Total$-36,385.000000$-36,804.000000$-36,385.000000$36.4k$36,385.000000$7,740.000000$36,804.000000$56.000000$44,125.000000$44.1k487271$-28,426.000000$-26,281.000000$-28,426.000000$28.4k$28,426.000000$12,824.000000$26,281.000000$11,341.000000$41,250.000000$41.3k9931,271$-21,552.000000$-21,274.000000$-21,552.000000$21.6k$21,552.000000$14,157.000000$21,274.000000$10,511.000000$35,709.000000$35.7k1,2442,189$-26,160.000000$-26,042.000000$-26,160.000000$26.2k$26,160.000000$9,720.000000$26,042.000000$6,997.000000$35,880.000000$35.9k3,2894,480
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 Coos County and Berlin
Berlin
Coos County
0%20%40%60%80%100%CountBachelor's Degree1Some College2H.S. Diploma3No H.S. Diploma30.000000%0.000000%0.000000%0.0%00.000000%0.000000%0.000000%0.0%0100.000000%100.000000%100.000000%100.0%270.000000%0.000000%0.000000%0.0%0
Count members of the armed forces with the given level of educational attainment
1or higher 2two or four year institution 3H.S. = High School

Employment by Educational Attainment#13

Percentage of population that is employed by highest level of educational attainment among the population aged 25 to 64 years old.
Scope: population of Coos County and Berlin
Berlin
Coos County
0%20%40%60%80%CountBachelor's Degree1Some College2H.S. Diploma3No H.S. Diploma374.050633%82.719377%74.050633%74.1%58571.389941%74.983563%71.389941%71.4%1,32050.470733%62.498114%50.470733%50.5%1,23320.827770%38.001162%20.827770%20.8%156
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 Coos County and Berlin
Female Male
Coos County
Berlin
Shaded bar tips show excess over facing bar.
10%0%10%20%30%40%MFWhite1Hispanic2Other1-12.576687%-2.155319%-10.986606%-14.732006%14.7%12.576687%10.986606%1.609859%12.576687%12.6%451481-0.000000%-7.936508%0.000000%0.0%0.000000%33.033033%7.936508%22.118137%33.033033%33.0%1100-0.000000%-5.769231%0.000000%0.0%0.000000%41.346154%5.769231%25.277701%41.346154%41.3%860
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 Coos County and Berlin
Female Male
Coos County
Berlin
Shaded bar tips show excess over facing bar.
100%80%60%40%20%0%MFWhite1Hispanic2Other1-9.592861%-7.436235%-15.509086%-5.693750%-17.029096%17.0%9.592861%15.509086%9.592861%9.6%344556-2.402402%-97.597598%-2.459016%-62.620349%-100.000000%100.0%2.402402%2.459016%2.402402%2.4%84-0.000000%-55.000000%-4.332130%-11.052485%-55.000000%55.0%0.000000%4.332130%0.000000%0.0%011
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#16

Percentage of the population 25 years and older with given highest level of educational attainment
16.8%19.9%22.9%25.9%29.0%32.0%

Coarse: High School Diploma Educational Attainment by Tract#17

Percentage of the population 25 years and older with given highest level of educational attainment
56.0%58.1%60.1%62.1%64.1%66.2%

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

Percentage of the population 25 years and older with given highest level of educational attainment
11.9%13.0%14.0%15.0%16.0%17.1%

Detailed: Doctorate Degree Educational Attainment by Tract#19

Percentage of the population 25 years and older with given highest level of educational attainment
0.00%0.08%0.16%0.24%0.32%0.40%

Detailed: Professional Degree Educational Attainment by Tract#20

Percentage of the population 25 years and older with given highest level of educational attainment
0.00%0.06%0.13%0.19%0.26%0.32%

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

Percentage of the population 25 years and older with given highest level of educational attainment
0.83%1.13%1.44%1.74%2.04%2.35%

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

Percentage of the population 25 years and older with given highest level of educational attainment
6.5%8.1%9.6%11.1%12.6%14.1%

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

Percentage of the population 25 years and older with given highest level of educational attainment
6.0%7.9%9.7%11.5%13.4%15.2%

Detailed: Some College Educational Attainment by Tract#24

Percentage of the population 25 years and older with given highest level of educational attainment
14.3%15.4%16.5%17.5%18.6%19.7%

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

Percentage of the population 25 years and older with given highest level of educational attainment
36.5%39.3%42.1%44.9%47.7%50.5%

Detailed: Some High School Educational Attainment by Tract#26

Percentage of the population 25 years and older with given highest level of educational attainment
7.6%8.7%9.8%10.8%11.9%13.0%

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

Percentage of the population 25 years and older with given highest level of educational attainment
2.8%3.6%4.3%5.0%5.7%6.5%

Detailed: None Educational Attainment by Tract#28

Percentage of the population 25 years and older with given highest level of educational attainment
0.00%0.21%0.43%0.64%0.86%1.08%
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Educational Attainment by County Subdivision in the Berlin Area

There are 62 county subdivisions in the Berlin Area. This section compares Berlin to the 50 most populous county subdivisions in the Berlin Area and to those entities that contain or substantially overlap with Berlin. The least populous of the compared county subdivisions has a population of 0.

No H.S. Diploma by County Subdivision#29

Percent of population 25 years of age and older without a high school diploma (or equivalent).
Scope: population of Berlin, selected other county subdivisions in the Berlin Area, and entities that contain Berlin
0%20%40%60%Count#Town of FerdinandFerdinandCambridge TownshipCambridgePinkhams GrantPinkhamsTown of StratfordStratfordGreens GrantTown of CanaanCanaanTown of BloomfieldBloomfieldTown of DaltonDaltonTown of East HavenE HvnTown of LunenburgLunenburgTown of StewartstownStewartstownTown of GranbyGranbyTown of BrightonBrightonWentworthTown of MaidstoneMaidstoneBerlinBerlin School DistrictBerlinBerlinTown of NortonNortonTown of DummerDummerTown of ConcordConcordUnited States of AmericaUnited StatesBerlin Metro AreaBerlin AreaTown of NorthumberlandNorthumberlandTown of StarkTown of ClarksvilleClarksvilleDixville TownshipDixvilleCoos CountyCoosTown of ColumbiaColumbiaTown of ColebrookColebrookTown of WhitefieldWhitefieldNortheastTown of LemingtonLemingtonTown of AverillAverillTown of JeffersonJeffersonNew EnglandTown of CarrollCarrollTown of ErrolTown of MilanTown of PittsburgPittsburgTown of GorhamGorhamTown of LancasterLancasterNew HampshireTown of GuildhallGuildhallTown of RandolphRandolphTown of ShelburneShelburneTown of BrunswickBrunswickTown of VictoryVictoryThompson and Meserves PurchaseThompson and Me…Millsfield TownshipMillsfield62.500000%62.500000%62.5%5155.555556%55.555556%55.6%5242.857143%42.857143%42.9%3326.077586%26.077586%26.1%121425.000000%25.000000%25.0%2520.918367%20.918367%20.9%164619.889503%19.889503%19.9%36719.397117%19.397117%19.4%148819.230769%19.230769%19.2%45916.056911%16.056911%16.1%1581015.841584%15.841584%15.8%1121115.384615%15.384615%15.4%141215.226337%15.226337%15.2%1111315.151515%15.151515%15.2%51415.116279%15.116279%15.1%261514.712318%14.712318%14.7%1,14314.712318%14.712318%14.7%1,14314.712318%14.712318%14.7%1,1431614.406780%14.406780%14.4%171714.285714%14.285714%14.3%281813.918630%13.918630%13.9%1301913.020590%13.020590%13.0%27,818,38027.8M12.703983%12.703983%12.7%3,72912.667479%12.667479%12.7%2082012.557078%12.557078%12.6%552112.554113%12.554113%12.6%292212.500000%12.500000%12.5%12312.132011%12.132011%12.1%2,99612.000000%12.000000%12.0%662411.992945%11.992945%12.0%2042511.728395%11.728395%11.7%1902611.614335%11.614335%11.6%4,487,0854.49M11.428571%11.428571%11.4%122710.526316%10.526316%10.5%22810.000000%10.000000%10.0%77299.657137%9.657137%9.7%981,894982k9.163987%9.163987%9.2%57308.974359%8.974359%9.0%21318.615682%8.615682%8.6%89328.380682%8.380682%8.4%59337.911240%7.911240%7.9%164347.451140%7.451140%7.5%183357.430090%7.430090%7.4%69,27469.3k6.547619%6.547619%6.5%11364.093567%4.093567%4.1%14373.973510%3.973510%4.0%12383.225806%3.225806%3.2%2390.000000%0.000000%0.0%0400.000000%0.000000%0.0%0410.000000%0.000000%0.0%042
Count number of people in category
# rank of county subdivision out of 42 by percentage of population 25 years of age and older without a high school diploma (or equivalent).

Bachelor's Degrees by County Subdivision#30

Percent of population 25 years of age and older with a bachelor's degree or higher..
Scope: population of Berlin, selected other county subdivisions in the Berlin Area, and entities that contain Berlin
0%10%20%30%40%50%Count#Town of RandolphRandolphDixville TownshipDixvilleCambridge TownshipCambridgeTown of ShelburneShelburneNew EnglandNew HampshireNortheastTown of GuildhallGuildhallUnited States of AmericaUnited StatesTown of MaidstoneMaidstoneTown of VictoryVictoryTown of JeffersonJeffersonTown of CarrollCarrollTown of East HavenE HvnTown of LancasterLancasterTown of GorhamGorhamTown of ColebrookColebrookTown of MilanTown of ErrolTown of WhitefieldWhitefieldTown of DummerDummerCoos CountyCoosBerlin Metro AreaBerlin AreaTown of BloomfieldBloomfieldTown of ColumbiaColumbiaTown of BrunswickBrunswickTown of NortonNortonTown of PittsburgPittsburgTown of AverillAverillTown of LunenburgLunenburgTown of BrightonBrightonTown of DaltonDaltonTown of ClarksvilleClarksvilleTown of StarkTown of ConcordConcordTown of CanaanCanaanBerlinBerlin School DistrictBerlinBerlinTown of LemingtonLemingtonTown of NorthumberlandNorthumberlandTown of StratfordStratfordTown of StewartstownStewartstownTown of GranbyGranbyWentworthTown of FerdinandFerdinandGreens GrantPinkhams GrantPinkhamsThompson and Meserves PurchaseThompson and Me…Millsfield TownshipMillsfield50.877193%50.877193%50.9%174150.000000%50.000000%50.0%4244.444444%44.444444%44.4%4339.072848%39.072848%39.1%118437.962191%37.962191%38.0%3,859,8243.86M35.467167%35.467167%35.5%330,676331k34.780899%34.780899%34.8%13,437,26113.4M32.738095%32.738095%32.7%55530.315023%30.315023%30.3%64,767,78764.8M29.069767%29.069767%29.1%50628.985507%28.985507%29.0%20728.701299%28.701299%28.7%221826.848875%26.848875%26.8%167926.495726%26.495726%26.5%621023.900651%23.900651%23.9%5871122.817173%22.817173%22.8%4731222.692534%22.692534%22.7%3861320.329138%20.329138%20.3%2101420.085470%20.085470%20.1%471519.629630%19.629630%19.6%3181618.877551%18.877551%18.9%371717.756631%17.756631%17.8%4,38517.456478%17.456478%17.5%5,12416.574586%16.574586%16.6%301816.363636%16.363636%16.4%901916.129032%16.129032%16.1%102016.101695%16.101695%16.1%192116.051136%16.051136%16.1%1132215.789474%15.789474%15.8%32315.040650%15.040650%15.0%1482414.814815%14.814815%14.8%1082514.809961%14.809961%14.8%1132614.285714%14.285714%14.3%332713.242009%13.242009%13.2%582813.062099%13.062099%13.1%1222912.117347%12.117347%12.1%953011.957781%11.957781%12.0%92911.957781%11.957781%12.0%92911.957781%11.957781%12.0%9293111.428571%11.428571%11.4%123211.084044%11.084044%11.1%1823310.560345%10.560345%10.6%493410.183876%10.183876%10.2%72355.494505%5.494505%5.5%5360.000000%0.000000%0.0%0370.000000%0.000000%0.0%0380.000000%0.000000%0.0%0390.000000%0.000000%0.0%0400.000000%0.000000%0.0%0410.000000%0.000000%0.0%042
Count number of people in category
# rank of county subdivision out of 42 by percentage of population 25 years of age and older with a bachelor's degree or higher..

Very Advanced Degrees by County Subdivision#31

Percent of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).
Scope: population of Berlin, selected other county subdivisions in the Berlin Area, and entities that contain Berlin
0%2%4%6%8%Count#Town of GuildhallGuildhallTown of RandolphRandolphNew EnglandNortheastTown of ShelburneShelburneTown of GorhamGorhamTown of LancasterLancasterUnited States of AmericaUnited StatesNew HampshireTown of CarrollCarrollTown of ColebrookColebrookTown of GranbyGranbyTown of LemingtonLemingtonTown of ColumbiaColumbiaTown of WhitefieldWhitefieldTown of CanaanCanaanCoos CountyCoosTown of VictoryVictoryBerlin Metro AreaBerlin AreaTown of East HavenE HvnTown of ConcordConcordTown of JeffersonJeffersonTown of MaidstoneMaidstoneTown of DummerDummerTown of LunenburgLunenburgTown of NortonNortonTown of DaltonDaltonTown of StratfordStratfordTown of StewartstownStewartstownTown of NorthumberlandNorthumberlandTown of StarkBerlinBerlin School DistrictBerlinBerlinTown of BrightonBrightonTown of MilanTown of PittsburgPittsburgTown of ClarksvilleClarksvilleTown of ErrolTown of BloomfieldBloomfieldTown of BrunswickBrunswickWentworthTown of AverillAverillTown of FerdinandFerdinandDixville TownshipDixvilleGreens GrantPinkhams GrantPinkhamsCambridge TownshipCambridgeThompson and Meserves PurchaseThompson and Me…Millsfield TownshipMillsfield9.523810%9.523810%9.5%1618.187135%8.187135%8.2%2824.645397%4.645397%4.6%472,323472k4.085016%4.085016%4.1%1,578,2061.58M3.973510%3.973510%4.0%1233.521466%3.521466%3.5%7343.379479%3.379479%3.4%8353.336158%3.336158%3.3%7,127,6737.13M3.279047%3.279047%3.3%30,57230.6k2.733119%2.733119%2.7%1762.233980%2.233980%2.2%3872.197802%2.197802%2.2%281.904762%1.904762%1.9%291.636364%1.636364%1.6%9101.604938%1.604938%1.6%26111.530612%1.530612%1.5%12121.453736%1.453736%1.5%3591.449275%1.449275%1.4%1131.434266%1.434266%1.4%4211.282051%1.282051%1.3%3141.177730%1.177730%1.2%11151.168831%1.168831%1.2%9161.162791%1.162791%1.2%2171.020408%1.020408%1.0%2180.914634%0.914634%0.9%9190.847458%0.847458%0.8%1200.786370%0.786370%0.8%6210.646552%0.646552%0.6%3220.565771%0.565771%0.6%4230.548112%0.548112%0.5%9240.456621%0.456621%0.5%2250.450508%0.450508%0.5%350.450508%0.450508%0.5%350.450508%0.450508%0.5%35260.411523%0.411523%0.4%3270.290416%0.290416%0.3%3280.000000%0.000000%0.0%0290.000000%0.000000%0.0%0300.000000%0.000000%0.0%0310.000000%0.000000%0.0%0320.000000%0.000000%0.0%0330.000000%0.000000%0.0%0340.000000%0.000000%0.0%0350.000000%0.000000%0.0%0360.000000%0.000000%0.0%0370.000000%0.000000%0.0%0380.000000%0.000000%0.0%0390.000000%0.000000%0.0%0400.000000%0.000000%0.0%0410.000000%0.000000%0.0%042
Count number of people in category
# rank of county subdivision out of 42 by percentage of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).

Under-Education Sex Ratio by County Subdivision#32

Percentage more likely men are than women to not have a high school diploma (or equivalent) among people aged 25 years and older.
Scope: population of Berlin, selected other county subdivisions in the Berlin Area, and entities that contain Berlin
Female
Male
10x5x0x5x10xFM#BrunswickAverillFerdinandJeffersonColumbiaPittsburgNorthumberlandColebrookTown of ErrolLancasterTown of StarkLunenburgGranbyLemingtonGuildhallDummerNew HampshireBloomfieldConcordBrightonDaltonBerlin AreaCoosMaidstoneNew EnglandUnited StatesGorhamNortheastE HvnStratfordCanaanCarrollBerlinBerlinBerlinNortonWhitefieldRandolphTown of MilanStewartstownWentworthShelburneClarksvilleDixvilleCambridge-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%6.897%6.90%1-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%16.667%16.7%2-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%83.333%83.3%3-1.000000x-1.000000x3.279888x3.279888x3.28x4.854%4.85%15.922%15.9%4-1.000000x-1.000000x2.316901x2.316901x2.32x7.143%7.14%16.549%16.5%5-1.000000x-1.000000x2.204934x2.204934x2.20x5.120%5.12%11.290%11.3%6-1.000000x-1.000000x2.157539x2.157539x2.16x7.995%8.00%17.250%17.2%7-1.000000x-1.000000x2.128114x2.128114x2.13x7.692%7.69%16.370%16.4%8-1.000000x-1.000000x2.000000x2.000000x2.00x5.769%5.77%11.538%11.5%9-1.000000x-1.000000x1.973990x1.973990x1.97x5.020%5.02%9.910%9.91%10-1.000000x-1.000000x1.665339x1.665339x1.67x9.091%9.09%15.139%15.1%11-1.000000x-1.000000x1.564133x1.564133x1.56x12.575%12.6%19.669%19.7%12-1.000000x-1.000000x1.542857x1.542857x1.54x11.905%11.9%18.367%18.4%13-1.000000x-1.000000x1.426923x1.426923x1.43x9.434%9.43%13.462%13.5%14-1.000000x-1.000000x1.418182x1.418182x1.42x5.495%5.49%7.792%7.79%15-1.000000x-1.000000x1.395410x1.395410x1.40x11.828%11.8%16.505%16.5%16-1.000000x-1.000000x1.314783x1.314783x1.31x6.441%6.44%8.468%8.47%-1.000000x-1.000000x1.292135x1.292135x1.29x17.391%17.4%22.472%22.5%17-1.000000x-1.000000x1.283261x1.283261x1.28x12.241%12.2%15.708%15.7%18-1.000000x-1.000000x1.271261x1.271261x1.27x13.441%13.4%17.087%17.1%19-1.000000x-1.000000x1.262788x1.262788x1.26x17.215%17.2%21.739%21.7%20-1.000000x-1.000000x1.225085x1.225085x1.23x11.361%11.4%13.919%13.9%-1.000000x-1.000000x1.217968x1.217968x1.22x10.877%10.9%13.248%13.2%-1.000000x-1.000000x1.185771x1.185771x1.19x13.750%13.8%16.304%16.3%21-1.000000x-1.000000x1.129206x1.129206x1.13x9.096%9.10%10.271%10.3%-1.000000x-1.000000x1.109070x1.109070x1.11x12.369%12.4%13.719%13.7%-1.000000x-1.000000x1.092351x1.092351x1.09x7.556%7.56%8.254%8.25%22-1.000000x-1.000000x1.074442x1.074442x1.07x11.216%11.2%12.051%12.1%-1.000000x-1.000000x1.049180x1.049180x1.05x18.750%18.8%19.672%19.7%23-1.000000x-1.000000x1.037536x1.037536x1.04x25.571%25.6%26.531%26.5%24-1.000000x-1.000000x1.028444x1.028444x1.03x20.604%20.6%21.190%21.2%25-1.000000x-1.000000x1.021470x1.021470x1.02x9.059%9.06%9.254%9.25%26-1.000000x-1.000000x1.010413x1.010413x1.01x14.625%14.6%14.777%14.8%-1.000000x-1.000000x1.010413x1.010413x1.01x14.625%14.6%14.777%14.8%-1.000000x-1.000000x1.010413x1.010413x1.01x14.625%14.6%14.777%14.8%27-1.205357x-1.205357x1.21x1.000000x1.000000x15.625%15.6%12.963%13.0%28-1.206320x-1.206320x1.21x1.000000x1.000000x12.824%12.8%10.630%10.6%29-1.235294x-1.235294x1.24x1.000000x1.000000x4.575%4.58%3.704%3.70%30-1.361380x-1.361380x1.36x1.000000x1.000000x9.980%9.98%7.331%7.33%31-1.776365x-1.776365x1.78x1.000000x1.000000x20.344%20.3%11.453%11.5%32-2.307692x-2.307692x2.31x1.000000x1.000000x23.077%23.1%10.000%10.0%33-3.040000x-3.040000x3.04x1.000000x1.000000x6.000%6.00%1.974%1.97%34-3.365854x-3.365854x3.37x1.000000x1.000000x18.699%18.7%5.556%5.56%35-10.000000x-10.000000x> 10.0x1.000000x1.000000x33.333%33.3%0.000%0%36-10.000000x-10.000000x> 10.0x1.000000x1.000000x100.000%100%0.000%0%37
F percentage of females in category
M percentage of males in category
# rank of county subdivision out of 37 by male-to-female sex ratio

Over-Education Sex Ratio by County Subdivision#33

Percentage more likely men are than women to have a professional or doctorate degree (e.g., MBA, PhD, or MD) among people aged 25 years and older.
Scope: population of Berlin, selected other county subdivisions in the Berlin Area, and entities that contain Berlin
Female
Male
10x5x0x5x10xFM#DaltonStewartstownStratfordTown of StarkE HvnDummerLemingtonNortonVictoryRandolphColumbiaShelburneGorhamLunenburgBerlinBerlinBerlinUnited StatesNew HampshireNortheastNew EnglandCoosCarrollBerlin AreaGuildhallLancasterConcordNorthumberlandColebrookWhitefieldTown of MilanCanaanBrightonJeffersonMaidstoneGranby-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%1.630%1.63%1-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%1.117%1.12%2-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%1.224%1.22%3-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%0.797%0.80%4-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%2.459%2.46%5-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%1.942%1.94%6-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%3.846%3.85%7-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%1.852%1.85%8-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%2.326%2.33%9-1.000000x-1.000000x10.000000x10.000000x> 10.0x1.307%1.31%13.757%13.8%10-1.000000x-1.000000x7.492958x7.492958x7.49x0.376%0.38%2.817%2.82%11-1.000000x-1.000000x4.934211x4.934211x4.93x1.333%1.33%6.579%6.58%12-1.000000x-1.000000x2.954090x2.954090x2.95x1.766%1.77%5.218%5.22%13-1.000000x-1.000000x2.074534x2.074534x2.07x0.599%0.60%1.242%1.24%14-1.000000x-1.000000x1.601786x1.601786x1.60x0.334%0.33%0.536%0.54%-1.000000x-1.000000x1.601786x1.601786x1.60x0.334%0.33%0.536%0.54%-1.000000x-1.000000x1.601786x1.601786x1.60x0.334%0.33%0.536%0.54%15-1.000000x-1.000000x1.526215x1.526215x1.53x2.660%2.66%4.060%4.06%-1.000000x-1.000000x1.494911x1.494911x1.49x2.641%2.64%3.948%3.95%-1.000000x-1.000000x1.486326x1.486326x1.49x3.316%3.32%4.929%4.93%-1.000000x-1.000000x1.447839x1.447839x1.45x3.827%3.83%5.541%5.54%-1.000000x-1.000000x1.311840x1.311840x1.31x1.248%1.25%1.637%1.64%-1.000000x-1.000000x1.223881x1.223881x1.22x2.439%2.44%2.985%2.99%16-1.000000x-1.000000x1.199574x1.199574x1.20x1.298%1.30%1.557%1.56%-1.000000x-1.000000x1.181818x1.181818x1.18x8.791%8.79%10.390%10.4%17-1.062814x-1.062814x1.06x1.000000x1.000000x3.482%3.48%3.276%3.28%18-1.125311x-1.125311x1.13x1.000000x1.000000x1.245%1.24%1.106%1.11%19-1.274600x-1.274600x1.27x1.000000x1.000000x0.615%0.62%0.483%0.48%20-1.889457x-1.889457x1.89x1.000000x1.000000x2.914%2.91%1.542%1.54%21-2.707592x-2.707592x2.71x1.000000x1.000000x2.343%2.34%0.865%0.87%22-10.000000x-10.000000x> 10.0x1.000000x1.000000x0.599%0.60%0.000%0%23-10.000000x-10.000000x> 10.0x1.000000x1.000000x3.297%3.30%0.000%0%24-10.000000x-10.000000x> 10.0x1.000000x1.000000x0.806%0.81%0.000%0%25-10.000000x-10.000000x> 10.0x1.000000x1.000000x2.184%2.18%0.000%0%26-10.000000x-10.000000x> 10.0x1.000000x1.000000x2.500%2.50%0.000%0%27-10.000000x-10.000000x> 10.0x1.000000x1.000000x4.762%4.76%0.000%0%28
F percentage of females in category
M percentage of males in category
# rank of county subdivision out of 28 by male-to-female sex ratio

Educational Attainment by County Subdivision in New Hampshire

There are 260 county subdivisions in New Hampshire. This section compares Berlin to the 50 most populous county subdivisions in New Hampshire and to those entities that contain or substantially overlap with Berlin. The least populous of the compared county subdivisions has a population of 6,451.

No H.S. Diploma by County Subdivision#34

Percent of population 25 years of age and older without a high school diploma (or equivalent).
Scope: population of Berlin, selected other county subdivisions in New Hampshire, and entities that contain Berlin
0%5%10%Count#Town of BelmontBelmontBerlinBerlin School DistrictBerlinBerlinUnited States of AmericaUnited StatesBerlin Metro AreaBerlin AreaClaremontManchesterCoos CountyCoosLaconiaNortheastFranklinRochesterTown of SwanzeySwanzeyTown of EppingEppingTown of FarmingtonFarmingtonTown of SeabrookSeabrookNew EnglandNashuaTown of GoffstownGoffstownTown of SalemTown of PlymouthPlymouthTown of HudsonHudsonConcordTown of PelhamPelhamTown of RaymondRaymondTown of LitchfieldLitchfieldDoverSomersworthNew HampshireTown of PembrokePembrokeLebanonTown of GilfordGilfordTown of BarringtonBarringtonTown of NewmarketNewmarketKeeneTown of PlaistowPlaistowTown of HooksettHooksettTown of DerryTown of MilfordMilfordTown of ConwayConwayTown of LondonderryLondonderryTown of WeareTown of ExeterExeterPortsmouthTown of HampsteadHampsteadTown of MerrimackMerrimackTown of WindhamWindhamTown of BedfordBedfordTown of AtkinsonAtkinsonTown of BowTown of PeterboroughPeterboroughTown of StrathamStrathamTown of HamptonHamptonTown of HanoverHanoverTown of AmherstAmherstTown of HollisHollisTown of DurhamDurham14.988245%14.988245%15.0%765114.712318%14.712318%14.7%1,14314.712318%14.712318%14.7%1,14314.712318%14.712318%14.7%1,143213.020590%13.020590%13.0%27,818,38027.8M12.703983%12.703983%12.7%3,72912.676835%12.676835%12.7%1,147312.589518%12.589518%12.6%9,616412.132011%12.132011%12.1%2,99611.646822%11.646822%11.6%1,389511.614335%11.614335%11.6%4,487,0854.49M11.193402%11.193402%11.2%665610.746213%10.746213%10.7%2,320710.279681%10.279681%10.3%555810.061983%10.061983%10.1%487910.044150%10.044150%10.0%4551010.023620%10.023620%10.0%679119.657137%9.657137%9.7%981,894982k9.642857%9.642857%9.6%5,913128.493035%8.493035%8.5%1,006138.336130%8.336130%8.3%1,739147.885906%7.885906%7.9%235157.818595%7.818595%7.8%1,343167.768343%7.768343%7.8%2,342177.764079%7.764079%7.8%699187.696669%7.696669%7.7%543197.692308%7.692308%7.7%426207.534024%7.534024%7.5%1,622217.465105%7.465105%7.5%599227.430090%7.430090%7.4%69,27469.3k7.403672%7.403672%7.4%367236.444598%6.444598%6.4%652246.421849%6.421849%6.4%348256.410466%6.410466%6.4%392266.261358%6.261358%6.3%379276.121050%6.121050%6.1%893285.991546%5.991546%6.0%326295.822354%5.822354%5.8%548305.668384%5.668384%5.7%1,309315.177931%5.177931%5.2%534325.102041%5.102041%5.1%370335.095916%5.095916%5.1%866344.994055%4.994055%5.0%294354.793110%4.793110%4.8%512364.508495%4.508495%4.5%743374.314803%4.314803%4.3%267383.898314%3.898314%3.9%710393.887622%3.887622%3.9%375403.476755%3.476755%3.5%522413.257329%3.257329%3.3%160423.012382%3.012382%3.0%163432.882438%2.882438%2.9%140442.217036%2.217036%2.2%114452.154538%2.154538%2.2%249461.907453%1.907453%1.9%108471.558054%1.558054%1.6%115481.527388%1.527388%1.5%87490.899888%0.899888%0.9%4050
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older without a high school diploma (or equivalent).

Bachelor's Degrees by County Subdivision#35

Percent of population 25 years of age and older with a bachelor's degree or higher..
Scope: population of Berlin, selected other county subdivisions in New Hampshire, and entities that contain Berlin
0%20%40%60%80%Count#Town of HanoverHanoverTown of DurhamDurhamTown of HollisHollisTown of AmherstAmherstTown of StrathamStrathamTown of BedfordBedfordPortsmouthTown of PeterboroughPeterboroughTown of BowTown of WindhamWindhamTown of HamptonHamptonTown of ExeterExeterLebanonTown of AtkinsonAtkinsonTown of MerrimackMerrimackTown of NewmarketNewmarketDoverTown of LondonderryLondonderryKeeneTown of HampsteadHampsteadTown of PlymouthPlymouthTown of GilfordGilfordNew EnglandTown of HooksettHooksettConcordTown of BarringtonBarringtonTown of HudsonHudsonNew HampshireTown of MilfordMilfordTown of LitchfieldLitchfieldNashuaNortheastTown of SalemTown of WeareTown of ConwayConwayUnited States of AmericaUnited StatesTown of EppingEppingTown of PelhamPelhamTown of GoffstownGoffstownSomersworthTown of PembrokePembrokeManchesterTown of DerryLaconiaTown of SwanzeySwanzeyTown of PlaistowPlaistowTown of RaymondRaymondRochesterTown of FarmingtonFarmingtonTown of BelmontBelmontClaremontCoos CountyCoosBerlin Metro AreaBerlin AreaFranklinTown of SeabrookSeabrookBerlinBerlin School DistrictBerlinBerlin80.713529%80.713529%80.7%4,570176.400450%76.400450%76.4%3,396264.220506%64.220506%64.2%3,658363.622815%63.622815%63.6%4,696463.029949%63.029949%63.0%3,241558.685227%58.685227%58.7%8,811657.633495%57.633495%57.6%9,498754.066296%54.066296%54.1%2,626852.042136%52.042136%52.0%2,816949.574953%49.574953%49.6%4,7821048.905425%48.905425%48.9%5,6521147.060476%47.060476%47.1%5,0271246.911140%46.911140%46.9%4,7461345.012215%45.012215%45.0%2,2111444.374897%44.374897%44.4%8,0821542.706096%42.706096%42.7%2,5851642.607646%42.607646%42.6%9,1731741.938331%41.938331%41.9%7,1271840.318048%40.318048%40.3%5,8821940.061409%40.061409%40.1%2,4792038.489933%38.489933%38.5%1,1472138.438826%38.438826%38.4%2,0832237.962191%37.962191%38.0%3,859,8243.86M37.930302%37.930302%37.9%3,5702337.103622%37.103622%37.1%11,18611.2k2435.797220%35.797220%35.8%2,1892535.687256%35.687256%35.7%6,1302635.467167%35.467167%35.5%330,676331k35.334044%35.334044%35.3%3,6442735.301553%35.301553%35.3%1,9552834.928245%34.928245%34.9%21,41821.4k2934.780899%34.780899%34.8%13,437,26113.4M34.101913%34.101913%34.1%7,1143033.004926%33.004926%33.0%1,9433131.756757%31.756757%31.8%2,3033230.315023%30.315023%30.3%64,767,78764.8M30.082645%30.082645%30.1%1,4563329.645674%29.645674%29.6%2,6693429.573660%29.573660%29.6%3,5033528.128116%28.128116%28.1%2,2573628.041154%28.041154%28.0%1,3903727.975544%27.975544%28.0%21,36821.4k3827.787641%27.787641%27.8%6,4173925.113198%25.113198%25.1%2,9954024.652713%24.652713%24.7%1,3314124.168351%24.168351%24.2%1,3154223.742027%23.742027%23.7%1,6754321.978785%21.978785%22.0%4,7454418.432671%18.432671%18.4%8354518.181818%18.181818%18.2%9284617.860301%17.860301%17.9%1,6164717.756631%17.756631%17.8%4,38517.456478%17.456478%17.5%5,12416.731190%16.731190%16.7%9944815.264246%15.264246%15.3%1,0344911.957781%11.957781%12.0%92911.957781%11.957781%12.0%92911.957781%11.957781%12.0%92950
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older with a bachelor's degree or higher..

Very Advanced Degrees by County Subdivision#36

Percent of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).
Scope: population of Berlin, selected other county subdivisions in New Hampshire, and entities that contain Berlin
0%5%10%15%20%Count#Town of HanoverHanoverTown of DurhamDurhamLebanonTown of HollisHollisTown of PeterboroughPeterboroughTown of BowTown of PlymouthPlymouthTown of AmherstAmherstTown of BedfordBedfordKeeneTown of StrathamStrathamPortsmouthTown of GilfordGilfordTown of ExeterExeterNew EnglandConcordTown of HamptonHamptonTown of BarringtonBarringtonTown of WindhamWindhamNortheastTown of AtkinsonAtkinsonDoverUnited States of AmericaUnited StatesNew HampshireTown of HampsteadHampsteadTown of EppingEppingLaconiaTown of NewmarketNewmarketTown of PlaistowPlaistowTown of MerrimackMerrimackTown of LondonderryLondonderryTown of HudsonHudsonTown of SalemTown of SwanzeySwanzeyTown of GoffstownGoffstownTown of HooksettHooksettTown of WeareNashuaSomersworthTown of ConwayConwayManchesterTown of PembrokePembrokeTown of PelhamPelhamTown of DerryTown of FarmingtonFarmingtonCoos CountyCoosBerlin Metro AreaBerlin AreaTown of MilfordMilfordTown of LitchfieldLitchfieldTown of BelmontBelmontTown of SeabrookSeabrookFranklinRochesterClaremontTown of RaymondRaymondBerlinBerlin School DistrictBerlinBerlin21.759096%21.759096%21.8%1,232114.803150%14.803150%14.8%658213.175843%13.175843%13.2%1,33338.567416%8.567416%8.6%48848.420836%8.420836%8.4%40957.244502%7.244502%7.2%39266.845638%6.845638%6.8%20476.435442%6.435442%6.4%47586.187558%6.187558%6.2%92995.887998%5.887998%5.9%859105.756515%5.756515%5.8%296115.345874%5.345874%5.3%881124.964016%4.964016%5.0%269134.802471%4.802471%4.8%513144.645397%4.645397%4.6%472,323472k4.640440%4.640440%4.6%1,399154.482132%4.482132%4.5%518164.268193%4.268193%4.3%261174.250467%4.250467%4.3%410184.085016%4.085016%4.1%1,578,2061.58M3.929153%3.929153%3.9%193193.530122%3.530122%3.5%760203.336158%3.336158%3.3%7,127,6737.13M3.279047%3.279047%3.3%30,57230.6k2.763413%2.763413%2.8%171212.747934%2.747934%2.7%133222.716753%2.716753%2.7%324232.709400%2.709400%2.7%164242.609814%2.609814%2.6%142252.553121%2.553121%2.6%465262.430270%2.430270%2.4%413272.427665%2.427665%2.4%417282.353674%2.353674%2.4%491292.333766%2.333766%2.3%126302.321655%2.321655%2.3%275312.294943%2.294943%2.3%216322.276202%2.276202%2.3%134332.075995%2.075995%2.1%1,273341.994018%1.994018%2.0%160351.875345%1.875345%1.9%136361.813278%1.813278%1.8%1,385371.634053%1.634053%1.6%81381.588359%1.588359%1.6%143391.485299%1.485299%1.5%343401.456954%1.456954%1.5%66411.453736%1.453736%1.5%3591.434266%1.434266%1.4%4211.367206%1.367206%1.4%141421.354280%1.354280%1.4%75431.155956%1.155956%1.2%59440.930027%0.930027%0.9%63450.807945%0.807945%0.8%48460.611422%0.611422%0.6%132470.596817%0.596817%0.6%54480.566974%0.566974%0.6%40490.450508%0.450508%0.5%350.450508%0.450508%0.5%350.450508%0.450508%0.5%3550
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).

Under-Education Sex Ratio by County Subdivision#37

Percentage more likely men are than women to not have a high school diploma (or equivalent) among people aged 25 years and older.
Scope: population of Berlin, selected other county subdivisions in New Hampshire, and entities that contain Berlin
Female
Male
0x5x10xFM#HollisPlaistowTown of WeareAtkinsonFarmingtonTown of BowFranklinEppingPelhamMilfordExeterSeabrookLebanonHamptonRaymondBelmontSomersworthLitchfieldConcordHudsonDoverBarringtonNew HampshireAmherstLondonderryClaremontPeterboroughDurhamBerlin AreaCoosGoffstownLaconiaNashuaNew EnglandUnited StatesManchesterRochesterSwanzeyTown of DerryNortheastTown of SalemPembrokeBerlinBerlinBerlinKeenePlymouthConwayBedfordHanoverHooksettHampsteadPortsmouthWindhamMerrimackGilfordNewmarketStratham-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%3.035%3.03%1-1.000000x-1.000000x3.740299x3.740299x3.74x2.598%2.60%9.718%9.72%2-1.000000x-1.000000x3.182459x3.182459x3.18x2.420%2.42%7.700%7.70%3-1.000000x-1.000000x2.429991x2.429991x2.43x1.939%1.94%4.713%4.71%4-1.000000x-1.000000x2.416781x2.416781x2.42x5.877%5.88%14.204%14.2%5-1.000000x-1.000000x2.366711x2.366711x2.37x1.828%1.83%4.326%4.33%6-1.000000x-1.000000x2.168901x2.168901x2.17x7.148%7.15%15.502%15.5%7-1.000000x-1.000000x2.149802x2.149802x2.15x6.504%6.50%13.982%14.0%8-1.000000x-1.000000x2.033310x2.033310x2.03x5.151%5.15%10.473%10.5%9-1.000000x-1.000000x2.004856x2.004856x2.00x3.496%3.50%7.010%7.01%10-1.000000x-1.000000x1.954798x1.954798x1.95x3.312%3.31%6.474%6.47%11-1.000000x-1.000000x1.897601x1.897601x1.90x7.070%7.07%13.416%13.4%12-1.000000x-1.000000x1.849318x1.849318x1.85x4.570%4.57%8.451%8.45%13-1.000000x-1.000000x1.793244x1.793244x1.79x1.577%1.58%2.827%2.83%14-1.000000x-1.000000x1.770294x1.770294x1.77x5.538%5.54%9.804%9.80%15-1.000000x-1.000000x1.695899x1.695899x1.70x11.386%11.4%19.310%19.3%16-1.000000x-1.000000x1.587518x1.587518x1.59x5.823%5.82%9.244%9.24%17-1.000000x-1.000000x1.566661x1.566661x1.57x6.001%6.00%9.401%9.40%18-1.000000x-1.000000x1.542618x1.542618x1.54x6.145%6.15%9.480%9.48%19-1.000000x-1.000000x1.399149x1.399149x1.40x6.566%6.57%9.187%9.19%20-1.000000x-1.000000x1.323424x1.323424x1.32x6.519%6.52%8.628%8.63%21-1.000000x-1.000000x1.315857x1.315857x1.32x5.543%5.54%7.294%7.29%22-1.000000x-1.000000x1.314783x1.314783x1.31x6.441%6.44%8.468%8.47%-1.000000x-1.000000x1.311332x1.311332x1.31x1.359%1.36%1.782%1.78%23-1.000000x-1.000000x1.304666x1.304666x1.30x4.449%4.45%5.804%5.80%24-1.000000x-1.000000x1.246243x1.246243x1.25x11.332%11.3%14.122%14.1%25-1.000000x-1.000000x1.242382x1.242382x1.24x2.601%2.60%3.232%3.23%26-1.000000x-1.000000x1.234936x1.234936x1.23x0.806%0.81%0.995%1.00%27-1.000000x-1.000000x1.225085x1.225085x1.23x11.361%11.4%13.919%13.9%-1.000000x-1.000000x1.217968x1.217968x1.22x10.877%10.9%13.248%13.2%-1.000000x-1.000000x1.186905x1.186905x1.19x7.792%7.79%9.249%9.25%28-1.000000x-1.000000x1.178847x1.178847x1.18x10.726%10.7%12.644%12.6%29-1.000000x-1.000000x1.169494x1.169494x1.17x8.913%8.91%10.424%10.4%30-1.000000x-1.000000x1.129206x1.129206x1.13x9.096%9.10%10.271%10.3%-1.000000x-1.000000x1.109070x1.109070x1.11x12.369%12.4%13.719%13.7%-1.000000x-1.000000x1.097386x1.097386x1.10x12.006%12.0%13.176%13.2%31-1.000000x-1.000000x1.093215x1.093215x1.09x10.284%10.3%11.242%11.2%32-1.000000x-1.000000x1.088073x1.088073x1.09x9.843%9.84%10.710%10.7%33-1.000000x-1.000000x1.081915x1.081915x1.08x5.454%5.45%5.900%5.90%34-1.000000x-1.000000x1.074442x1.074442x1.07x11.216%11.2%12.051%12.1%-1.000000x-1.000000x1.054108x1.054108x1.05x8.126%8.13%8.565%8.57%35-1.000000x-1.000000x1.026363x1.026363x1.03x7.310%7.31%7.503%7.50%36-1.000000x-1.000000x1.010413x1.010413x1.01x14.625%14.6%14.777%14.8%-1.000000x-1.000000x1.010413x1.010413x1.01x14.625%14.6%14.777%14.8%-1.000000x-1.000000x1.010413x1.010413x1.01x14.625%14.6%14.777%14.8%37-1.000000x-1.000000x1.005675x1.005675x1.01x6.105%6.10%6.139%6.14%38-1.013819x-1.013819x1.01x1.000000x1.000000x7.936%7.94%7.827%7.83%39-1.048880x-1.048880x1.05x1.000000x1.000000x5.221%5.22%4.977%4.98%40-1.054671x-1.054671x1.05x1.000000x1.000000x3.564%3.56%3.379%3.38%41-1.075066x-1.075066x1.08x1.000000x1.000000x1.971%1.97%1.833%1.83%42-1.144854x-1.144854x1.14x1.000000x1.000000x6.193%6.19%5.410%5.41%43-1.306993x-1.306993x1.31x1.000000x1.000000x4.856%4.86%3.715%3.72%44-1.327790x-1.327790x1.33x1.000000x1.000000x5.147%5.15%3.876%3.88%45-1.363961x-1.363961x1.36x1.000000x1.000000x4.491%4.49%3.293%3.29%46-1.500088x-1.500088x1.50x1.000000x1.000000x4.653%4.65%3.102%3.10%47-1.785180x-1.785180x1.79x1.000000x1.000000x7.972%7.97%4.466%4.47%48-2.342638x-2.342638x2.34x1.000000x1.000000x8.834%8.83%3.771%3.77%49-2.568487x-2.568487x2.57x1.000000x1.000000x3.193%3.19%1.243%1.24%50
F percentage of females in category
M percentage of males in category
# rank of county subdivision out of 50 by male-to-female sex ratio

Over-Education Sex Ratio by County Subdivision#38

Percentage more likely men are than women to have a professional or doctorate degree (e.g., MBA, PhD, or MD) among people aged 25 years and older.
Scope: population of Berlin, selected other county subdivisions in New Hampshire, and entities that contain Berlin
Female
Male
10x5x0x5xFM#PlaistowGilfordSeabrookPlymouthDurhamLaconiaBedfordBelmontWindhamHanoverTown of WeareTown of BowAtkinsonRochesterDoverHamptonLondonderryNashuaHollisManchesterSwanzeyAmherstBerlinBerlinBerlinExeterHooksettUnited StatesNew HampshireNortheastConcordNew EnglandTown of SalemGoffstownKeeneRaymondCoosBarringtonStrathamBerlin AreaFranklinPortsmouthNewmarketPeterboroughConwayLebanonHampsteadHudsonTown of DerryMerrimackPelhamPembrokeMilfordEppingSomersworthClaremontLitchfieldFarmington-1.000000x-1.000000x6.328540x6.328540x6.33x0.737%0.74%4.666%4.67%1-1.000000x-1.000000x5.809013x5.809013x5.81x1.588%1.59%9.224%9.22%2-1.000000x-1.000000x4.417039x4.417039x4.42x0.359%0.36%1.586%1.59%3-1.000000x-1.000000x3.732514x3.732514x3.73x3.038%3.04%11.339%11.3%4-1.000000x-1.000000x3.481793x3.481793x3.48x6.625%6.62%23.066%23.1%5-1.000000x-1.000000x3.248341x3.248341x3.25x1.306%1.31%4.244%4.24%6-1.000000x-1.000000x2.813156x2.813156x2.81x3.337%3.34%9.388%9.39%7-1.000000x-1.000000x2.733333x2.733333x2.73x0.647%0.65%1.767%1.77%8-1.000000x-1.000000x2.558017x2.558017x2.56x2.381%2.38%6.092%6.09%9-1.000000x-1.000000x2.239823x2.239823x2.24x13.830%13.8%30.978%31.0%10-1.000000x-1.000000x2.079079x2.079079x2.08x1.492%1.49%3.101%3.10%11-1.000000x-1.000000x1.973696x1.973696x1.97x4.956%4.96%9.782%9.78%12-1.000000x-1.000000x1.897945x1.897945x1.90x2.754%2.75%5.227%5.23%13-1.000000x-1.000000x1.816983x1.816983x1.82x0.439%0.44%0.797%0.80%14-1.000000x-1.000000x1.806265x1.806265x1.81x2.543%2.54%4.594%4.59%15-1.000000x-1.000000x1.805938x1.805938x1.81x3.266%3.27%5.898%5.90%16-1.000000x-1.000000x1.802536x1.802536x1.80x1.757%1.76%3.167%3.17%17-1.000000x-1.000000x1.695023x1.695023x1.70x1.554%1.55%2.635%2.63%18-1.000000x-1.000000x1.688432x1.688432x1.69x6.363%6.36%10.743%10.7%19-1.000000x-1.000000x1.681608x1.681608x1.68x1.353%1.35%2.276%2.28%20-1.000000x-1.000000x1.659199x1.659199x1.66x1.752%1.75%2.908%2.91%21-1.000000x-1.000000x1.652273x1.652273x1.65x4.922%4.92%8.132%8.13%22-1.000000x-1.000000x1.601786x1.601786x1.60x0.334%0.33%0.536%0.54%-1.000000x-1.000000x1.601786x1.601786x1.60x0.334%0.33%0.536%0.54%-1.000000x-1.000000x1.601786x1.601786x1.60x0.334%0.33%0.536%0.54%23-1.000000x-1.000000x1.534901x1.534901x1.53x3.840%3.84%5.894%5.89%24-1.000000x-1.000000x1.528410x1.528410x1.53x1.836%1.84%2.806%2.81%25-1.000000x-1.000000x1.526215x1.526215x1.53x2.660%2.66%4.060%4.06%-1.000000x-1.000000x1.494911x1.494911x1.49x2.641%2.64%3.948%3.95%-1.000000x-1.000000x1.486326x1.486326x1.49x3.316%3.32%4.929%4.93%-1.000000x-1.000000x1.476160x1.476160x1.48x3.767%3.77%5.561%5.56%26-1.000000x-1.000000x1.447839x1.447839x1.45x3.827%3.83%5.541%5.54%-1.000000x-1.000000x1.434299x1.434299x1.43x1.949%1.95%2.795%2.80%27-1.000000x-1.000000x1.393449x1.393449x1.39x1.952%1.95%2.720%2.72%28-1.000000x-1.000000x1.369269x1.369269x1.37x5.014%5.01%6.865%6.87%29-1.000000x-1.000000x1.320728x1.320728x1.32x0.488%0.49%0.644%0.64%30-1.000000x-1.000000x1.311840x1.311840x1.31x1.248%1.25%1.637%1.64%-1.000000x-1.000000x1.272690x1.272690x1.27x3.760%3.76%4.785%4.79%31-1.000000x-1.000000x1.222707x1.222707x1.22x5.179%5.18%6.333%6.33%32-1.000000x-1.000000x1.199574x1.199574x1.20x1.298%1.30%1.557%1.56%-1.000000x-1.000000x1.157607x1.157607x1.16x0.751%0.75%0.869%0.87%33-1.000000x-1.000000x1.121951x1.121951x1.12x5.037%5.04%5.651%5.65%34-1.000000x-1.000000x1.120628x1.120628x1.12x2.553%2.55%2.861%2.86%35-1.000000x-1.000000x1.056868x1.056868x1.06x8.213%8.21%8.680%8.68%36-1.000000x-1.000000x1.050905x1.050905x1.05x1.830%1.83%1.923%1.92%37-1.000000x-1.000000x1.021541x1.021541x1.02x13.040%13.0%13.321%13.3%38-1.025638x-1.025638x1.03x1.000000x1.000000x2.797%2.80%2.727%2.73%39-1.061898x-1.061898x1.06x1.000000x1.000000x2.497%2.50%2.352%2.35%40-1.109654x-1.109654x1.11x1.000000x1.000000x1.559%1.56%1.405%1.41%41-1.448267x-1.448267x1.45x1.000000x1.000000x3.006%3.01%2.076%2.08%42-1.498983x-1.498983x1.50x1.000000x1.000000x1.899%1.90%1.267%1.27%43-1.681648x-1.681648x1.68x1.000000x1.000000x2.033%2.03%1.209%1.21%44-2.092150x-2.092150x2.09x1.000000x1.000000x1.823%1.82%0.871%0.87%45-2.187947x-2.187947x2.19x1.000000x1.000000x3.705%3.71%1.693%1.69%46-2.962793x-2.962793x2.96x1.000000x1.000000x2.924%2.92%0.987%0.99%47-3.638808x-3.638808x3.64x1.000000x1.000000x0.918%0.92%0.252%0.25%48-10.000000x-10.000000x> 10.0x1.000000x1.000000x2.695%2.69%0.000%0%49-10.000000x-10.000000x> 10.0x1.000000x1.000000x2.916%2.92%0.000%0%50
F percentage of females in category
M percentage of males in category
# rank of county subdivision out of 50 by male-to-female sex ratio

Educational Attainment by County Subdivision in the Northeast

There are 5,785 county subdivisions in the Northeast. This section compares Berlin to the 50 most populous county subdivisions in the Northeast and to those entities that contain or substantially overlap with Berlin. The least populous of the compared county subdivisions has a population of 91,133.

No H.S. Diploma by County Subdivision#39

Percent of population 25 years of age and older without a high school diploma (or equivalent).
Scope: population of Berlin, selected other county subdivisions in the Northeast, and entities that contain Berlin
0%5%10%15%20%25%Count#BronxPatersonTown of HartfordHartfordNew BedfordElizabethNewarkProvidenceTown of BridgeportBridgeportSpringfieldAllentownTown of WaterburyWaterburyLynnLowellBrooklynQueensRochesterSyracuseBrocktonTown of RamapoRamapoPhiladelphiaYonkersBuffaloTown of New HavenNew HvnLakewood TownshipLakewoodWorcesterBerlinBerlin School DistrictBerlinBerlinTown of IslipBostonJersey CityUnited States of AmericaUnited StatesManhattanErieBerlin Metro AreaBerlin AreaManchesterTown of BabylonBabylonCoos CountyCoosNortheastStaten IslandQuincyTown of StamfordStamfordTown of HempsteadHempsteadAlbanyNew EnglandWoodbridge TownshipWoodbridgeTown of North HempsteadN HempsteadTown of BrookhavenBrookhavenPittsburghEdison TownshipEdisonToms River TownshipToms RivTown of GreeceGreeceNew HampshireTown of HuntingtonHuntingtonTown of GreenburghGreenburghCambridgeTown of Oyster BayOyster BayTown of AmherstAmherstTown of SmithtownSmithtown28.837398%28.837398%28.8%261,022261k128.603478%28.603478%28.6%26,13726.1k227.891028%27.891028%27.9%20,66020.7k327.365251%27.365251%27.4%17,71917.7k426.935430%26.935430%26.9%21,72121.7k526.717922%26.717922%26.7%47,54047.5k623.799210%23.799210%23.8%25,05225.1k723.641452%23.641452%23.6%22,13122.1k822.848722%22.848722%22.8%21,31921.3k921.725192%21.725192%21.7%15,92515.9k1020.889554%20.889554%20.9%14,52214.5k1120.689714%20.689714%20.7%12,22712.2k1220.275184%20.275184%20.3%14,22014.2k1320.017506%20.017506%20.0%351,046351k1419.344706%19.344706%19.3%315,505316k1519.239011%19.239011%19.2%25,40825.4k1619.000219%19.000219%19.0%16,47316.5k1718.575453%18.575453%18.6%11,40711.4k1817.423749%17.423749%17.4%12,58512.6k1917.390838%17.390838%17.4%180,039180k2016.804756%16.804756%16.8%22,98023.0k2116.749688%16.749688%16.7%27,74127.7k2216.300427%16.300427%16.3%13,24113.2k2316.179368%16.179368%16.2%7,1442415.555125%15.555125%15.6%18,48418.5k2514.712318%14.712318%14.7%1,14314.712318%14.712318%14.7%1,14314.712318%14.712318%14.7%1,14314.649584%14.649584%14.6%32,58832.6k2614.325556%14.325556%14.3%63,64263.6k2714.106563%14.106563%14.1%25,82725.8k2813.020590%13.020590%13.0%27,818,38027.8M12.996284%12.996284%13.0%160,845161k2912.909782%12.909782%12.9%8,3843012.703983%12.703983%12.7%3,72912.589518%12.589518%12.6%9,6163112.329428%12.329428%12.3%18,13418.1k3212.132011%12.132011%12.1%2,99611.614335%11.614335%11.6%4,487,0854.49M11.118888%11.118888%11.1%36,06336.1k3311.019146%11.019146%11.0%7,6953410.953993%10.953993%11.0%9,8073510.384134%10.384134%10.4%54,23054.2k3610.256196%10.256196%10.3%6,145379.657137%9.657137%9.7%981,894982k9.010786%9.010786%9.0%6,625388.911497%8.911497%8.9%14,26914.3k398.603165%8.603165%8.6%28,07628.1k408.043576%8.043576%8.0%16,40616.4k417.965713%7.965713%8.0%5,836427.603506%7.603506%7.6%4,953437.434661%7.434661%7.4%5,274447.430090%7.430090%7.4%69,27469.3k7.370929%7.370929%7.4%10,45510.5k457.208489%7.208489%7.2%4,660465.858411%5.858411%5.9%4,275475.758981%5.758981%5.8%11,95012.0k484.592814%4.592814%4.6%3,835494.565854%4.565854%4.6%3,74450
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older without a high school diploma (or equivalent).

Bachelor's Degrees by County Subdivision#40

Percent of population 25 years of age and older with a bachelor's degree or higher..
Scope: population of Berlin, selected other county subdivisions in the Northeast, and entities that contain Berlin
0%20%40%60%Count#CambridgeTown of GreenburghGreenburghManhattanEdison TownshipEdisonTown of AmherstAmherstTown of North HempsteadN HempsteadTown of HuntingtonHuntingtonTown of Oyster BayOyster BayTown of StamfordStamfordBostonTown of SmithtownSmithtownJersey CityQuincyPittsburghTown of HempsteadHempsteadNew EnglandAlbanyNew HampshireNortheastWoodbridge TownshipWoodbridgeTown of New HavenNew HvnBrooklynTown of RamapoRamapoTown of BrookhavenBrookhavenYonkersToms River TownshipToms RivStaten IslandQueensUnited States of AmericaUnited StatesWorcesterProvidenceTown of GreeceGreeceManchesterTown of IslipLakewood TownshipLakewoodSyracusePhiladelphiaTown of BabylonBabylonBuffaloRochesterLowellErieLynnBronxTown of BridgeportBridgeportSpringfieldCoos CountyCoosBerlin Metro AreaBerlin AreaBrocktonTown of HartfordHartfordNew BedfordAllentownTown of WaterburyWaterburyNewarkBerlinBerlin School DistrictBerlinBerlinElizabethPaterson74.864332%74.864332%74.9%54,63054.6k161.467067%61.467067%61.5%39,73639.7k260.434640%60.434640%60.4%747,953748k354.244922%54.244922%54.2%39,74239.7k454.117365%54.117365%54.1%45,18845.2k553.266008%53.266008%53.3%85,28985.3k650.346515%50.346515%50.3%71,41271.4k748.123874%48.123874%48.1%99,85899.9k847.268483%47.268483%47.3%42,31942.3k946.377869%46.377869%46.4%206,036206k1046.287805%46.287805%46.3%37,95638.0k1144.105197%44.105197%44.1%80,75080.8k1242.147695%42.147695%42.1%29,43329.4k1340.731207%40.731207%40.7%83,07783.1k1438.767308%38.767308%38.8%202,458202k1537.962191%37.962191%38.0%3,859,8243.86M37.277810%37.277810%37.3%22,33522.3k1635.467167%35.467167%35.5%330,676331k34.780899%34.780899%34.8%13,437,26113.4M34.631340%34.631340%34.6%25,46225.5k1734.235698%34.235698%34.2%27,81027.8k1834.081468%34.081468%34.1%597,685598k1932.475875%32.475875%32.5%23,45723.5k2032.119689%32.119689%32.1%104,821105k2132.032147%32.032147%32.0%43,80343.8k2231.493222%31.493222%31.5%20,51520.5k2331.359684%31.359684%31.4%101,712102k2430.595789%30.595789%30.6%499,006499k2530.315023%30.315023%30.3%64,767,78764.8M29.720018%29.720018%29.7%35,31635.3k2629.442164%29.442164%29.4%30,99231.0k2728.513632%28.513632%28.5%20,22720.2k2827.975544%27.975544%28.0%21,36821.4k2927.874579%27.874579%27.9%62,00762.0k3026.896161%26.896161%26.9%11,87611.9k3126.804231%26.804231%26.8%23,23923.2k3226.349720%26.349720%26.3%272,786273k3325.418993%25.418993%25.4%37,38637.4k3425.263101%25.263101%25.3%41,84141.8k3523.661076%23.661076%23.7%31,24831.2k3622.302702%22.302702%22.3%15,64215.6k3721.735984%21.735984%21.7%14,11614.1k3819.566137%19.566137%19.6%11,56311.6k3919.131504%19.131504%19.1%173,169173k4017.869695%17.869695%17.9%16,72816.7k4117.800761%17.800761%17.8%16,60916.6k4217.756631%17.756631%17.8%4,38517.456478%17.456478%17.5%5,12417.271084%17.271084%17.3%10,60610.6k4316.703567%16.703567%16.7%12,37312.4k4415.806950%15.806950%15.8%10,23510.2k4515.372023%15.372023%15.4%11,26811.3k4615.070917%15.070917%15.1%10,47710.5k4713.654578%13.654578%13.7%24,29624.3k4811.957781%11.957781%12.0%92911.957781%11.957781%12.0%92911.957781%11.957781%12.0%92911.763247%11.763247%11.8%9,4864910.403055%10.403055%10.4%9,50650
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older with a bachelor's degree or higher..

Very Advanced Degrees by County Subdivision#41

Percent of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).
Scope: population of Berlin, selected other county subdivisions in the Northeast, and entities that contain Berlin
0%5%10%15%Count#CambridgeTown of GreenburghGreenburghManhattanTown of North HempsteadN HempsteadTown of AmherstAmherstTown of New HavenNew HvnTown of HuntingtonHuntingtonPittsburghBostonTown of Oyster BayOyster BayTown of StamfordStamfordProvidenceTown of SmithtownSmithtownAlbanyEdison TownshipEdisonNew EnglandTown of HempsteadHempsteadJersey CitySyracuseNortheastTown of RamapoRamapoTown of BrookhavenBrookhavenPhiladelphiaQuincyWorcesterYonkersBrooklynUnited States of AmericaUnited StatesNew HampshireBuffaloStaten IslandQueensToms River TownshipToms RivRochesterTown of IslipTown of HartfordHartfordTown of GreeceGreeceWoodbridge TownshipWoodbridgeLakewood TownshipLakewoodLowellManchesterTown of BridgeportBridgeportBronxAllentownTown of BabylonBabylonErieSpringfieldCoos CountyCoosBerlin Metro AreaBerlin AreaLynnTown of WaterburyWaterburyNew BedfordNewarkElizabethBrocktonPatersonBerlinBerlin School DistrictBerlinBerlin19.696596%19.696596%19.7%14,37314.4k111.932680%11.932680%11.9%7,714210.788423%10.788423%10.8%133,520134k310.319825%10.319825%10.3%16,52416.5k49.511377%9.511377%9.5%7,94258.607551%8.607551%8.6%6,99267.591599%7.591599%7.6%10,76810.8k77.432194%7.432194%7.4%15,15915.2k87.340604%7.340604%7.3%32,61132.6k96.073676%6.073676%6.1%12,60312.6k105.972366%5.972366%6.0%5,347115.846253%5.846253%5.8%6,154125.571951%5.571951%5.6%4,569135.285822%5.285822%5.3%3,167145.170343%5.170343%5.2%3,788154.645397%4.645397%4.6%472,323472k4.441262%4.441262%4.4%23,19423.2k164.296365%4.296365%4.3%7,866174.250337%4.250337%4.3%3,685184.085016%4.085016%4.1%1,578,2061.58M4.063465%4.063465%4.1%2,935193.952259%3.952259%4.0%12,89812.9k203.720350%3.720350%3.7%38,51538.5k213.698824%3.698824%3.7%2,583223.571519%3.571519%3.6%4,244233.426766%3.426766%3.4%4,686243.384967%3.384967%3.4%59,36259.4k253.336158%3.336158%3.3%7,127,6737.13M3.279047%3.279047%3.3%30,57230.6k3.202492%3.202492%3.2%5,304263.037245%3.037245%3.0%9,851272.756960%2.756960%2.8%44,96545.0k282.735604%2.735604%2.7%1,782292.719873%2.719873%2.7%3,592302.384356%2.384356%2.4%5,304312.259902%2.259902%2.3%1,674322.249852%2.249852%2.2%1,596332.147627%2.147627%2.1%1,579342.040539%2.040539%2.0%901351.961931%1.961931%2.0%1,376361.813278%1.813278%1.8%1,385371.680358%1.680358%1.7%1,573381.664253%1.664253%1.7%15,06415.1k391.607050%1.607050%1.6%1,178401.603220%1.603220%1.6%2,358411.599864%1.599864%1.6%1,039421.501527%1.501527%1.5%1,401431.453736%1.453736%1.5%3591.434266%1.434266%1.4%4211.189570%1.189570%1.2%703441.165166%1.165166%1.2%810451.153668%1.153668%1.2%747461.070628%1.070628%1.1%1,905471.051574%1.051574%1.1%848481.035679%1.035679%1.0%636490.572354%0.572354%0.6%523500.450508%0.450508%0.5%350.450508%0.450508%0.5%350.450508%0.450508%0.5%35
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).

Under-Education Sex Ratio by County Subdivision#42

Percentage more likely men are than women to not have a high school diploma (or equivalent) among people aged 25 years and older.
Scope: population of Berlin, selected other county subdivisions in the Northeast, and entities that contain Berlin
Female
Male
1x0x1xFM#New HampshireStamfordGreenburghSpringfieldBerlin AreaCoosNewarkGreeceRamapoBrookhavenNew EnglandBridgeportNew BedfordWorcesterUnited StatesTown of IslipManchesterRochesterHempsteadPhiladelphiaHuntingtonNew HvnYonkersSyracuseElizabethNortheastProvidenceBabylonN HempsteadToms RivWaterburyAllentownLynnHartfordErieBronxLakewoodBrooklynPatersonBerlinBerlinBerlinStaten IslandAlbanyBrocktonBostonQueensManhattanBuffaloPittsburghOyster BayLowellWoodbridgeJersey CityQuincySmithtownAmherstCambridgeEdison-1.000000x-1.000000x1.314783x1.314783x1.31x6.441%6.44%8.468%8.47%-1.000000x-1.000000x1.289374x1.289374x1.29x9.609%9.61%12.390%12.4%1-1.000000x-1.000000x1.269590x1.269590x1.27x6.408%6.41%8.136%8.14%2-1.000000x-1.000000x1.257718x1.257718x1.26x20.468%20.5%25.743%25.7%3-1.000000x-1.000000x1.225085x1.225085x1.23x11.361%11.4%13.919%13.9%-1.000000x-1.000000x1.217968x1.217968x1.22x10.877%10.9%13.248%13.2%-1.000000x-1.000000x1.160031x1.160031x1.16x24.796%24.8%28.764%28.8%4-1.000000x-1.000000x1.148263x1.148263x1.15x6.949%6.95%7.980%7.98%5-1.000000x-1.000000x1.130956x1.130956x1.13x16.378%16.4%18.523%18.5%6-1.000000x-1.000000x1.130425x1.130425x1.13x8.092%8.09%9.147%9.15%7-1.000000x-1.000000x1.129206x1.129206x1.13x9.096%9.10%10.271%10.3%-1.000000x-1.000000x1.126520x1.126520x1.13x22.316%22.3%25.139%25.1%8-1.000000x-1.000000x1.111286x1.111286x1.11x26.024%26.0%28.920%28.9%9-1.000000x-1.000000x1.110069x1.110069x1.11x14.771%14.8%16.397%16.4%10-1.000000x-1.000000x1.109070x1.109070x1.11x12.369%12.4%13.719%13.7%-1.000000x-1.000000x1.102369x1.102369x1.10x13.961%14.0%15.390%15.4%11-1.000000x-1.000000x1.097386x1.097386x1.10x12.006%12.0%13.176%13.2%12-1.000000x-1.000000x1.092586x1.092586x1.09x18.427%18.4%20.133%20.1%13-1.000000x-1.000000x1.092101x1.092101x1.09x9.951%9.95%10.868%10.9%14-1.000000x-1.000000x1.090163x1.090163x1.09x16.700%16.7%18.206%18.2%15-1.000000x-1.000000x1.086755x1.086755x1.09x7.076%7.08%7.690%7.69%16-1.000000x-1.000000x1.085150x1.085150x1.09x15.699%15.7%17.035%17.0%17-1.000000x-1.000000x1.083417x1.083417x1.08x16.184%16.2%17.534%17.5%18-1.000000x-1.000000x1.079690x1.079690x1.08x18.321%18.3%19.780%19.8%19-1.000000x-1.000000x1.077654x1.077654x1.08x25.951%26.0%27.966%28.0%20-1.000000x-1.000000x1.074442x1.074442x1.07x11.216%11.2%12.051%12.1%-1.000000x-1.000000x1.056204x1.056204x1.06x23.167%23.2%24.469%24.5%21-1.000000x-1.000000x1.052862x1.052862x1.05x12.028%12.0%12.664%12.7%22-1.000000x-1.000000x1.049383x1.049383x1.05x8.711%8.71%9.141%9.14%23-1.000000x-1.000000x1.047109x1.047109x1.05x7.436%7.44%7.786%7.79%24-1.000000x-1.000000x1.047067x1.047067x1.05x20.442%20.4%21.404%21.4%25-1.000000x-1.000000x1.046856x1.046856x1.05x21.252%21.3%22.248%22.2%26-1.000000x-1.000000x1.040899x1.040899x1.04x20.290%20.3%21.120%21.1%27-1.000000x-1.000000x1.039426x1.039426x1.04x27.388%27.4%28.468%28.5%28-1.000000x-1.000000x1.033360x1.033360x1.03x12.706%12.7%13.130%13.1%29-1.000000x-1.000000x1.030539x1.030539x1.03x28.448%28.4%29.316%29.3%30-1.000000x-1.000000x1.022095x1.022095x1.02x16.005%16.0%16.358%16.4%31-1.000000x-1.000000x1.018960x1.018960x1.02x19.845%19.8%20.221%20.2%32-1.000000x-1.000000x1.016806x1.016806x1.02x28.378%28.4%28.855%28.9%33-1.000000x-1.000000x1.010413x1.010413x1.01x14.625%14.6%14.777%14.8%-1.000000x-1.000000x1.010413x1.010413x1.01x14.625%14.6%14.777%14.8%-1.000000x-1.000000x1.010413x1.010413x1.01x14.625%14.6%14.777%14.8%-1.000000x-1.000000x1.004211x1.004211x1.00x11.097%11.1%11.144%11.1%34-1.015553x-1.015553x1.02x1.000000x1.000000x10.330%10.3%10.172%10.2%35-1.016098x-1.016098x1.02x1.000000x1.000000x18.712%18.7%18.416%18.4%36-1.022333x-1.022333x1.02x1.000000x1.000000x14.476%14.5%14.159%14.2%37-1.027762x-1.027762x1.03x1.000000x1.000000x19.596%19.6%19.067%19.1%38-1.044246x-1.044246x1.04x1.000000x1.000000x13.260%13.3%12.698%12.7%39-1.048932x-1.048932x1.05x1.000000x1.000000x17.120%17.1%16.322%16.3%40-1.054084x-1.054084x1.05x1.000000x1.000000x8.249%8.25%7.826%7.83%41-1.065498x-1.065498x1.07x1.000000x1.000000x5.933%5.93%5.568%5.57%42-1.082021x-1.082021x1.08x1.000000x1.000000x21.048%21.0%19.452%19.5%43-1.092845x-1.092845x1.09x1.000000x1.000000x9.423%9.42%8.623%8.62%44-1.106483x-1.106483x1.11x1.000000x1.000000x14.808%14.8%13.383%13.4%45-1.113634x-1.113634x1.11x1.000000x1.000000x11.579%11.6%10.397%10.4%46-1.188832x-1.188832x1.19x1.000000x1.000000x4.943%4.94%4.158%4.16%47-1.191205x-1.191205x1.19x1.000000x1.000000x4.962%4.96%4.165%4.17%48-1.302480x-1.302480x1.30x1.000000x1.000000x6.597%6.60%5.065%5.06%49-1.377298x-1.377298x1.38x1.000000x1.000000x9.172%9.17%6.659%6.66%50
F percentage of females in category
M percentage of males in category
# rank of county subdivision out of 50 by male-to-female sex ratio

Over-Education Sex Ratio by County Subdivision#43

Percentage more likely men are than women to have a professional or doctorate degree (e.g., MBA, PhD, or MD) among people aged 25 years and older.
Scope: population of Berlin, selected other county subdivisions in the Northeast, and entities that contain Berlin
Female
Male
1x0x1x2xFM#LakewoodAllentownToms RivWoodbridgeSmithtownHuntingtonBrookhavenAmherstStamfordOyster BayGreenburghManchesterBerlinBerlinBerlinElizabethBuffaloNew BedfordN HempsteadSyracuseEdisonUnited StatesNew HampshireHempsteadNortheastRamapoAlbanyNew EnglandGreeceHartfordQuincyRochesterPittsburghPhiladelphiaProvidenceBridgeportCoosQueensCambridgeLowellBrooklynManhattanPatersonStaten IslandBostonSpringfieldWaterburyErieLynnBronxBerlin AreaTown of IslipJersey CityBabylonNew HvnYonkersNewarkWorcesterBrockton-1.000000x-1.000000x2.794240x2.794240x2.79x1.082%1.08%3.024%3.02%1-1.000000x-1.000000x1.966185x1.966185x1.97x1.102%1.10%2.166%2.17%2-1.000000x-1.000000x1.866111x1.866111x1.87x1.933%1.93%3.608%3.61%3-1.000000x-1.000000x1.800589x1.800589x1.80x1.521%1.52%2.738%2.74%4-1.000000x-1.000000x1.796128x1.796128x1.80x4.030%4.03%7.238%7.24%5-1.000000x-1.000000x1.783986x1.783986x1.78x5.517%5.52%9.842%9.84%6-1.000000x-1.000000x1.779979x1.779979x1.78x2.869%2.87%5.106%5.11%7-1.000000x-1.000000x1.771370x1.771370x1.77x7.007%7.01%12.411%12.4%8-1.000000x-1.000000x1.765297x1.765297x1.77x4.359%4.36%7.695%7.69%9-1.000000x-1.000000x1.747049x1.747049x1.75x4.477%4.48%7.822%7.82%10-1.000000x-1.000000x1.685185x1.685185x1.69x9.057%9.06%15.263%15.3%11-1.000000x-1.000000x1.681608x1.681608x1.68x1.353%1.35%2.276%2.28%12-1.000000x-1.000000x1.601786x1.601786x1.60x0.334%0.33%0.536%0.54%-1.000000x-1.000000x1.601786x1.601786x1.60x0.334%0.33%0.536%0.54%-1.000000x-1.000000x1.601786x1.601786x1.60x0.334%0.33%0.536%0.54%-1.000000x-1.000000x1.556739x1.556739x1.56x0.827%0.83%1.287%1.29%13-1.000000x-1.000000x1.547792x1.547792x1.55x2.553%2.55%3.952%3.95%14-1.000000x-1.000000x1.546996x1.546996x1.55x0.920%0.92%1.424%1.42%15-1.000000x-1.000000x1.545980x1.545980x1.55x8.227%8.23%12.719%12.7%16-1.000000x-1.000000x1.539638x1.539638x1.54x3.397%3.40%5.230%5.23%17-1.000000x-1.000000x1.526951x1.526951x1.53x4.127%4.13%6.301%6.30%18-1.000000x-1.000000x1.526215x1.526215x1.53x2.660%2.66%4.060%4.06%-1.000000x-1.000000x1.494911x1.494911x1.49x2.641%2.64%3.948%3.95%-1.000000x-1.000000x1.488724x1.488724x1.49x3.608%3.61%5.371%5.37%19-1.000000x-1.000000x1.486326x1.486326x1.49x3.316%3.32%4.929%4.93%-1.000000x-1.000000x1.473331x1.473331x1.47x3.302%3.30%4.864%4.86%20-1.000000x-1.000000x1.463655x1.463655x1.46x4.342%4.34%6.355%6.35%21-1.000000x-1.000000x1.447839x1.447839x1.45x3.827%3.83%5.541%5.54%-1.000000x-1.000000x1.440372x1.440372x1.44x1.863%1.86%2.684%2.68%22-1.000000x-1.000000x1.439109x1.439109x1.44x1.876%1.88%2.700%2.70%23-1.000000x-1.000000x1.422215x1.422215x1.42x3.082%3.08%4.384%4.38%24-1.000000x-1.000000x1.407741x1.407741x1.41x2.278%2.28%3.207%3.21%25-1.000000x-1.000000x1.398688x1.398688x1.40x6.228%6.23%8.711%8.71%26-1.000000x-1.000000x1.341930x1.341930x1.34x3.216%3.22%4.316%4.32%27-1.000000x-1.000000x1.338337x1.338337x1.34x5.022%5.02%6.721%6.72%28-1.000000x-1.000000x1.315069x1.315069x1.32x1.464%1.46%1.925%1.93%29-1.000000x-1.000000x1.311840x1.311840x1.31x1.248%1.25%1.637%1.64%-1.000000x-1.000000x1.285200x1.285200x1.29x2.428%2.43%3.121%3.12%30-1.000000x-1.000000x1.275829x1.275829x1.28x17.386%17.4%22.181%22.2%31-1.000000x-1.000000x1.264337x1.264337x1.26x1.739%1.74%2.199%2.20%32-1.000000x-1.000000x1.262281x1.262281x1.26x3.021%3.02%3.814%3.81%33-1.000000x-1.000000x1.245683x1.245683x1.25x9.673%9.67%12.050%12.1%34-1.000000x-1.000000x1.231387x1.231387x1.23x0.516%0.52%0.635%0.64%35-1.000000x-1.000000x1.229783x1.229783x1.23x2.740%2.74%3.370%3.37%36-1.000000x-1.000000x1.221037x1.221037x1.22x6.643%6.64%8.112%8.11%37-1.000000x-1.000000x1.213642x1.213642x1.21x1.369%1.37%1.662%1.66%38-1.000000x-1.000000x1.211475x1.211475x1.21x1.061%1.06%1.285%1.29%39-1.000000x-1.000000x1.210953x1.210953x1.21x1.452%1.45%1.759%1.76%40-1.000000x-1.000000x1.204417x1.204417x1.20x1.083%1.08%1.304%1.30%41-1.000000x-1.000000x1.202385x1.202385x1.20x1.526%1.53%1.834%1.83%42-1.000000x-1.000000x1.199574x1.199574x1.20x1.298%1.30%1.557%1.56%-1.000000x-1.000000x1.168032x1.168032x1.17x2.206%2.21%2.576%2.58%43-1.000000x-1.000000x1.165264x1.165264x1.17x3.973%3.97%4.630%4.63%44-1.000000x-1.000000x1.157113x1.157113x1.16x1.492%1.49%1.726%1.73%45-1.000000x-1.000000x1.135572x1.135572x1.14x8.112%8.11%9.212%9.21%46-1.000000x-1.000000x1.127265x1.127265x1.13x3.237%3.24%3.649%3.65%47-1.000000x-1.000000x1.113365x1.113365x1.11x1.015%1.01%1.130%1.13%48-1.000000x-1.000000x1.051874x1.051874x1.05x3.484%3.48%3.665%3.67%49-1.041380x-1.041380x1.04x1.000000x1.000000x1.055%1.06%1.013%1.01%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#44

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 VegasPhoenixBerlinBerlin School DistrictBerlinBerlinBostonSacramentoOrlandoAustinDenverUnited States of AmericaUnited StatesManhattanSan DiegoTampaSan JoseBerlin Metro AreaBerlin AreaSan FranciscoTucsonCoos CountyCoosAlbuquerqueNortheastTownship 1:Charlotte1, CharlotteColumbusTulsaSalt Lake CitySalt Lk CityTown of HempsteadHempsteadNorthwest HarrisNW HarrisWashingtonNew EnglandAtlantaSeattleNortheast TarrantNE TarrantNew HampshirePlanoSeattle East28.998944%28.998944%29.0%126,922127k128.837398%28.837398%28.8%261,022261k227.582802%27.582802%27.6%135,754136k324.837401%24.837401%24.8%434,160434k423.987048%23.987048%24.0%141,940142k523.756417%23.756417%23.8%81,30881.3k622.645542%22.645542%22.6%248,699249k722.107626%22.107626%22.1%92,47292.5k821.922900%21.922900%21.9%457,347457k921.818150%21.818150%21.8%149,688150k1021.003600%21.003600%21.0%90,67890.7k1120.783651%20.783651%20.8%207,494207k1220.461493%20.461493%20.5%128,038128k1320.041576%20.041576%20.0%106,726107k1420.017506%20.017506%20.0%351,046351k1519.402518%19.402518%19.4%73,10573.1k1619.344706%19.344706%19.3%315,505316k1719.344408%19.344408%19.3%244,983245k1817.485105%17.485105%17.5%63,80063.8k1917.390838%17.390838%17.4%180,039180k2017.129346%17.129346%17.1%71,39771.4k2116.905373%16.905373%16.9%309,770310k2216.548703%16.548703%16.5%69,83969.8k2315.999398%15.999398%16.0%70,21470.2k2415.906523%15.906523%15.9%198,651199k2514.952077%14.952077%15.0%308,569309k2614.712318%14.712318%14.7%1,14314.712318%14.712318%14.7%1,14314.712318%14.712318%14.7%1,14314.325556%14.325556%14.3%63,64263.6k2713.900512%13.900512%13.9%103,047103k2813.679368%13.679368%13.7%53,75853.8k2913.668915%13.668915%13.7%78,23878.2k3013.638703%13.638703%13.6%63,86563.9k3113.020590%13.020590%13.0%27,818,38027.8M12.996284%12.996284%13.0%160,845161k3212.985760%12.985760%13.0%206,792207k3312.979618%12.979618%13.0%57,75857.8k3412.789590%12.789590%12.8%153,604154k3512.703983%12.703983%12.7%3,72912.559735%12.559735%12.6%84,02484.0k3612.262851%12.262851%12.3%70,40970.4k3712.132011%12.132011%12.1%2,99612.089143%12.089143%12.1%52,21752.2k3811.614335%11.614335%11.6%4,487,0854.49M11.553484%11.553484%11.6%61,37861.4k3911.376979%11.376979%11.4%60,83160.8k4011.299086%11.299086%11.3%43,65343.7k4110.435356%10.435356%10.4%64,29464.3k4210.384134%10.384134%10.4%54,23054.2k4310.135583%10.135583%10.1%47,67947.7k4410.045421%10.045421%10.0%46,51046.5k459.657137%9.657137%9.7%981,894982k9.538552%9.538552%9.5%37,37337.4k468.833573%8.833573%8.8%66,22066.2k478.418271%8.418271%8.4%31,44331.4k487.430090%7.430090%7.4%69,27469.3k5.714681%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#45

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 TarrantNew EnglandNorthwest HarrisNW HarrisChicagoNew HampshireNortheastColumbusLos AngelesBrooklynSan Fernando ValleySan Fernando VlyNortheast DallasNE DallasSalt Lake CitySalt Lk CityAlbuquerqueTampaTucsonOceanside-EscondidoOceanside-Escond…TulsaQueensUnited States of AmericaUnited StatesHoustonBaltimoreLong Beach-LakewoodLong Bch-LakewoodPhoenixOrlandoAnaheim-Santa Ana-Garden GroveAnaheim-Santa An…SacramentoEast San Gabriel ValleyE San Gabriel VlyOntarioPhiladelphiaMiamiFort WorthSouthwest DallasSW DallasMilwaukeeFresnoLas VegasEl PasoBronxCoos CountyCoosBerlin Metro AreaBerlin AreaSan BernardinoSan Antonio CentralSan Antonio CntrlDetroitBerlinBerlin School DistrictBerlinBerlin60.434640%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%143,978144k1537.962191%37.962191%38.0%3,859,8243.86M36.877886%36.877886%36.9%173,478173k1636.546320%36.546320%36.5%669,666670k1735.467167%35.467167%35.5%330,676331k34.780899%34.780899%34.8%13,437,26113.4M34.685843%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%109,693110k3228.760152%28.760152%28.8%593,529594k3328.535877%28.535877%28.5%112,142112k3428.412939%28.412939%28.4%312,038312k3528.231204%28.231204%28.2%209,283209k3627.276345%27.276345%27.3%170,682171k3726.758411%26.758411%26.8%111,532112k3826.349720%26.349720%26.3%272,786273k3926.011156%26.011156%26.0%178,455178k4024.665414%24.665414%24.7%131,349131k4123.764821%23.764821%23.8%140,625141k4223.517740%23.517740%23.5%85,81285.8k4322.486319%22.486319%22.5%94,05694.1k4421.702666%21.702666%21.7%271,037271k4521.071885%21.071885%21.1%72,12072.1k4619.131504%19.131504%19.1%173,169173k4717.756631%17.756631%17.8%4,38517.456478%17.456478%17.5%5,12416.375473%16.375473%16.4%80,59580.6k4814.929012%14.929012%14.9%65,34165.3k4913.833543%13.833543%13.8%59,72359.7k5011.957781%11.957781%12.0%92911.957781%11.957781%12.0%92911.957781%11.957781%12.0%929
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older with a bachelor's degree or higher..

Very Advanced Degrees by County Subdivision#46

Percent of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).
Scope: population of Berlin, selected other county subdivisions in the United States, and entities that contain Berlin
0%5%10%Count#WashingtonManhattanSan FranciscoBostonAtlantaSeattleSan JoseSeattle EastDenverSan DiegoAustinBaltimoreLos AngelesNew EnglandAlbuquerquePlanoChicagoTucsonTown of HempsteadHempsteadTampaNortheastMiamiNortheast DallasNE DallasSalt Lake CitySalt Lk CityHoustonPhiladelphiaSan Fernando ValleySan Fernando VlyTownship 1:Charlotte1, CharlotteOceanside-EscondidoOceanside-Escond…BrooklynSacramentoColumbusUnited States of AmericaUnited StatesNew HampshireTulsaPhoenixLong Beach-LakewoodLong Bch-LakewoodOrlandoFresnoAnaheim-Santa Ana-Garden GroveAnaheim-Santa An…QueensNorthwest HarrisNW HarrisNortheast TarrantNE TarrantEast San Gabriel ValleyE San Gabriel VlyOntarioFort WorthLas VegasMilwaukeeSan BernardinoSan Antonio CentralSan Antonio CntrlEl PasoSouthwest DallasSW DallasBronxCoos CountyCoosBerlin Metro AreaBerlin AreaDetroitBerlinBerlin School DistrictBerlinBerlin12.461852%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%81,44181.4k134.645397%4.645397%4.6%472,323472k4.631274%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%19,24719.2k194.085016%4.085016%4.1%1,578,2061.58M4.025531%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%7,127,6737.13M3.279047%3.279047%3.3%30,57230.6k3.140490%3.140490%3.1%12,13312.1k313.010825%3.010825%3.0%62,13562.1k323.009440%3.009440%3.0%11,33911.3k332.893233%2.893233%2.9%11,37011.4k342.828959%2.828959%2.8%11,83311.8k352.763004%2.763004%2.8%30,34430.3k362.756960%2.756960%2.8%44,96545.0k372.682967%2.682967%2.7%12,62112.6k382.630994%2.630994%2.6%9,827392.484535%2.484535%2.5%15,54715.5k402.324315%2.324315%2.3%9,688412.173239%2.173239%2.2%11,57311.6k422.155077%2.155077%2.2%26,91426.9k432.043126%2.043126%2.0%7,455441.807306%1.807306%1.8%8,895451.792414%1.792414%1.8%7,845461.745764%1.745764%1.7%5,975471.704476%1.704476%1.7%10,08610.1k481.664253%1.664253%1.7%15,06415.1k491.453736%1.453736%1.5%3591.434266%1.434266%1.4%4211.318660%1.318660%1.3%5,693500.450508%0.450508%0.5%350.450508%0.450508%0.5%350.450508%0.450508%0.5%35
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).

Under-Education Sex Ratio by County Subdivision#47

Percentage more likely men are than women to not have a high school diploma (or equivalent) among people aged 25 years and older.
Scope: population of Berlin, selected other county subdivisions in the United States, and entities that contain Berlin
Female
Male
1x0x1xFM#New Hampshire1, CharlotteDetroitBerlin AreaCoosBaltimoreTulsaSW DallasNew EnglandFresnoMilwaukeeUnited StatesNE DallasHoustonHempsteadOrlandoPhiladelphiaOntarioSan BernardinoAustinNortheastAtlantaFort WorthPhoenixChicagoAlbuquerqueWashingtonSacramentoColumbusSalt Lk CityDenverNE TarrantTampaOceanside-EscondidoOceanside-Escond…NW HarrisBronxPlanoBrooklynBerlinBerlinBerlinSan 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-1.000000x1.314783x1.314783x1.31x6.441%6.44%8.468%8.47%-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-1.000000x1.225085x1.225085x1.23x11.361%11.4%13.919%13.9%-1.000000x-1.000000x1.217968x1.217968x1.22x10.877%10.9%13.248%13.2%-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-1.000000x1.129206x1.129206x1.13x9.096%9.10%10.271%10.3%-1.000000x-1.000000x1.127206x1.127206x1.13x20.830%20.8%23.479%23.5%6-1.000000x-1.000000x1.123984x1.123984x1.12x16.526%16.5%18.574%18.6%7-1.000000x-1.000000x1.109070x1.109070x1.11x12.369%12.4%13.719%13.7%-1.000000x-1.000000x1.099797x1.099797x1.10x19.814%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-1.000000x1.074442x1.074442x1.07x11.216%11.2%12.051%12.1%-1.000000x-1.000000x1.073220x1.073220x1.07x9.215%9.21%9.889%9.89%16-1.000000x-1.000000x1.071348x1.071348x1.07x19.379%19.4%20.762%20.8%17-1.000000x-1.000000x1.069008x1.069008x1.07x14.467%14.5%15.465%15.5%18-1.000000x-1.000000x1.068021x1.068021x1.07x16.372%16.4%17.486%17.5%19-1.000000x-1.000000x1.066879x1.066879x1.07x11.714%11.7%12.497%12.5%20-1.000000x-1.000000x1.064309x1.064309x1.06x9.751%9.75%10.378%10.4%21-1.000000x-1.000000x1.053268x1.053268x1.05x13.558%13.6%14.280%14.3%22-1.000000x-1.000000x1.052237x1.052237x1.05x11.098%11.1%11.678%11.7%23-1.000000x-1.000000x1.051272x1.051272x1.05x10.176%10.2%10.697%10.7%24-1.000000x-1.000000x1.049933x1.049933x1.05x13.307%13.3%13.971%14.0%25-1.000000x-1.000000x1.040742x1.040742x1.04x8.257%8.26%8.594%8.59%26-1.000000x-1.000000x1.040003x1.040003x1.04x12.734%12.7%13.244%13.2%27-1.000000x-1.000000x1.039910x1.039910x1.04x15.694%15.7%16.321%16.3%28-1.000000x-1.000000x1.038394x1.038394x1.04x9.953%9.95%10.335%10.3%29-1.000000x-1.000000x1.030539x1.030539x1.03x28.448%28.4%29.316%29.3%30-1.000000x-1.000000x1.023151x1.023151x1.02x5.652%5.65%5.783%5.78%31-1.000000x-1.000000x1.018960x1.018960x1.02x19.845%19.8%20.221%20.2%32-1.000000x-1.000000x1.010413x1.010413x1.01x14.625%14.6%14.777%14.8%-1.000000x-1.000000x1.010413x1.010413x1.01x14.625%14.6%14.777%14.8%-1.000000x-1.000000x1.010413x1.010413x1.01x14.625%14.6%14.777%14.8%-1.000000x-1.000000x1.003929x1.003929x1.00x28.944%28.9%29.058%29.1%33-1.000000x-1.000000x1.003840x1.003840x1.00x19.308%19.3%19.383%19.4%34-1.006471x-1.006471x1.01x1.000000x1.000000x12.301%12.3%12.222%12.2%35-1.008020x-1.008020x1.01x1.000000x1.000000x22.734%22.7%22.553%22.6%36-1.013004x-1.013004x1.01x1.000000x1.000000x24.995%25.0%24.674%24.7%37-1.016645x-1.016645x1.02x1.000000x1.000000x16.036%16.0%15.774%15.8%38-1.022333x-1.022333x1.02x1.000000x1.000000x14.476%14.5%14.159%14.2%39-1.026902x-1.026902x1.03x1.000000x1.000000x20.723%20.7%20.180%20.2%40-1.027762x-1.027762x1.03x1.000000x1.000000x19.596%19.6%19.067%19.1%41-1.030897x-1.030897x1.03x1.000000x1.000000x22.136%22.1%21.473%21.5%42-1.044246x-1.044246x1.04x1.000000x1.000000x13.260%13.3%12.698%12.7%43-1.049689x-1.049689x1.05x1.000000x1.000000x9.047%9.05%8.619%8.62%44-1.056864x-1.056864x1.06x1.000000x1.000000x19.921%19.9%18.849%18.8%45-1.057675x-1.057675x1.06x1.000000x1.000000x5.050%5.05%4.774%4.77%46-1.127548x-1.127548x1.13x1.000000x1.000000x13.555%13.6%12.021%12.0%47-1.168454x-1.168454x1.17x1.000000x1.000000x13.975%14.0%11.960%12.0%48-1.228758x-1.228758x1.23x1.000000x1.000000x13.883%13.9%11.298%11.3%49-1.276282x-1.276282x1.28x1.000000x1.000000x26.394%26.4%20.680%20.7%50
F percentage of females in category
M percentage of males in category
# rank of county subdivision out of 50 by male-to-female sex ratio

Over-Education Sex Ratio by County Subdivision#48

Percentage more likely men are than women to have a professional or doctorate degree (e.g., MBA, PhD, or MD) among people aged 25 years and older.
Scope: population of Berlin, selected other county subdivisions in the United States, and entities that contain Berlin
Female
Male
1x0x1x2xFM#El PasoSalt Lk CityPlanoTulsaAlbuquerqueNE DallasFort WorthOrlandoPhoenixTucson1, CharlotteBerlinBerlinBerlinNW HarrisLas VegasSeattle EastSan Antonio CntrlSan DiegoUnited StatesSan JoseNew HampshireHempsteadNortheastFresnoNE TarrantTampaSan Fernando VlyE San Gabriel VlyNew EnglandHoustonSan BernardinoColumbusMiamiAtlantaMilwaukeeAnaheim-Santa Ana-Gdn GrvAnaheim-Santa An…SacramentoPhiladelphiaCoosOceanside-EscondidoOceanside-Escond…Los AngelesAustinBaltimoreWashingtonQueensSW DallasBrooklynManhattanChicagoSeattleBostonBronxBerlin AreaOntarioLong Bch-LakewoodDenverSan FranciscoDetroit-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-1.000000x1.601786x1.601786x1.60x0.334%0.33%0.536%0.54%-1.000000x-1.000000x1.601786x1.601786x1.60x0.334%0.33%0.536%0.54%-1.000000x-1.000000x1.601786x1.601786x1.60x0.334%0.33%0.536%0.54%-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-1.000000x1.557664x1.557664x1.56x4.733%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-1.000000x1.494911x1.494911x1.49x2.641%2.64%3.948%3.95%-1.000000x-1.000000x1.488724x1.488724x1.49x3.608%3.61%5.371%5.37%18-1.000000x-1.000000x1.486326x1.486326x1.49x3.316%3.32%4.929%4.93%-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-1.000000x1.447839x1.447839x1.45x3.827%3.83%5.541%5.54%-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-1.000000x1.311840x1.311840x1.31x1.248%1.25%1.637%1.64%-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-1.000000x1.199574x1.199574x1.20x1.298%1.30%1.557%1.56%-1.000000x-1.000000x1.198236x1.198236x1.20x2.119%2.12%2.539%2.54%46-1.000000x-1.000000x1.181998x1.181998x1.18x2.766%2.77%3.269%3.27%47-1.000000x-1.000000x1.129665x1.129665x1.13x5.378%5.38%6.075%6.08%48-1.000000x-1.000000x1.098720x1.098720x1.10x7.194%7.19%7.905%7.90%49-1.000000x-1.000000x1.046557x1.046557x1.05x1.291%1.29%1.351%1.35%50
F percentage of females in category
M percentage of males in category
# rank of county subdivision out of 50 by male-to-female sex ratio

Definitions

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

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

The coarse levels of educational attainment are as follows:

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

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

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Demographics

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More Maps to Explore

State:
New Hampshire
County:
Coos
Metro Area:
Berlin Area
City:
Berlin
ZIP Code:
03570
Unified School District:
Berlin
Congressional District:
NH-2
State Senate District:
NH-1
State House District:
NH-Coos County No. 3
Neighboring Towns:
Gorham, Milan, Randolph
Neighboring Townships:
Kilkenny, Success
Nearby Grants:
Greens, Low and Burbanks
Nearby Locations:
Martins
Nearby Purchases:
Thompson and Meserves
Nearby Towns:
Dummer, Jefferson, Lancaster, Northumberland, Shelburne, Stark