Educational Attainment in Lena, Oconto County, Wisconsin (Village)

Educational Attainment#1

Highest level of education among people aged 25 years and older.
Scope: population of Oconto County and Lena
Lena
Oconto County
0%20%40%60%CountHigher Degree1H.S. Diploma2No H.S. Diploma218.428184%26.962783%18.428184%18.4%6869.105691%63.429957%69.105691%69.1%25512.466125%9.607260%12.466125%12.5%46
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 Oconto County at large.
Scope: population of Oconto County and Lena
-20%0%+20%%ref.Higher Degree1H.S. Diploma2No H.S. Diploma2-31.653257%-31.653257%-31.7%18.428%18.4%26.963%27.0%8.948034%8.948034%+8.9%69.106%69.1%63.430%63.4%29.757341%29.757341%+29.8%12.466%12.5%9.607%9.61%
% percentage with given level in Lena
ref. percentage with given level in Oconto 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 Oconto County and Lena
Lena
Oconto County
0%10%20%30%40%50%CountDoctorate1Professional1Master's1Bachelor's1Associate's1Some CollegeHigh School2Some H.S.3Less than H.S.3None0.000000%0.000000%0.0%0.282891%00.542005%0.793563%0.542005%0.5%21.355014%4.111099%1.355014%1.4%54.878049%11.007017%4.878049%4.9%1811.653117%10.768213%11.653117%11.7%4315.176152%19.471693%15.176152%15.2%5653.929539%43.958264%53.929539%53.9%1994.065041%6.157464%4.065041%4.1%155.691057%2.656233%5.691057%5.7%212.710027%0.793563%2.710027%2.7%10
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 Oconto County at large.
Scope: population of Oconto County and Lena
-200%0%+200%%ref.Doctorate1Professional1Master's1Bachelor's1Associate's1Some CollegeHigh School2Some H.S.3Less than H.S.3None-100.000000%-100.000000%-100.0%0.000%0%0.283%0.28%-31.699789%-31.699789%-31.7%0.542%0.54%0.794%0.79%-67.040113%-67.040113%-67.0%1.355%1.36%4.111%4.11%-55.682373%-55.682373%-55.7%4.878%4.88%11.007%11.0%8.217734%8.217734%+8.2%11.653%11.7%10.768%10.8%-22.060439%-22.060439%-22.1%15.176%15.2%19.472%19.5%22.683504%22.683504%+22.7%53.930%53.9%43.958%44.0%-33.981897%-33.981897%-34.0%4.065%4.07%6.157%6.16%114.252943%114.252943%+114.3%5.691%5.69%2.656%2.66%241.501054%241.501054%+241.5%2.710%2.71%0.794%0.79%
% percentage with given level in Lena
ref. percentage with given level in Oconto 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 Oconto County and Lena
More Females More Males
Oconto County
Lena
50%0%FMHigher Degree1H.S. Diploma2No H.S. Diploma2-6.820809%-25.667368%-6.820809%7%19.075%19.1%17.857%17.9%14.506343%5.053432%14.506343%15%64.162%64.2%73.469%73.5%-93.267596%-93.267596%93%37.430385%16.763%16.8%8.673%8.67%
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 Oconto County and Lena
More Females More Males
Oconto County
Lena
1,000%500%0%FMProfessional1Master's1Bachelor's1Associate's1Some CollegeHigh School2Some H.S.3Less than H.S.3None-1,000.000000%-3.582648%-1,000.000000%> 1000%1.156%1.16%0.000%0%-30.576913%32.397959%32.397959%32%1.156%1.16%1.531%1.53%-34.403251%76.530612%76.530612%77%3.468%3.47%6.122%6.12%-30.289017%-19.325385%-30.289017%30%13.295%13.3%10.204%10.2%-120.626711%-19.583219%-120.626711%121%21.387%21.4%9.694%9.69%49.096801%16.265707%49.096801%49%42.775%42.8%63.776%63.8%0.874636%59.476396%0.874636%1%4.046%4.05%4.082%4.08%-126.589595%-126.589595%127%3.456830%8.092%8.09%3.571%3.57%-353.179191%-353.179191%353%16.243566%4.624%4.62%1.020%1.02%
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 Oconto County and Lena
Lena
Oconto County
0%5%10%15%B.X.Total65+45-6435-4425-345.194805%6.785044%5.194805%5.2%4773.149606%10.664933%3.149606%3.1%41270.000000%0.000000%0.0%15.967927%0347.633588%14.262069%7.633588%7.6%10131
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 Oconto County at large.
Scope: population of Oconto County and Lena
100%80%60%40%20%0%%ref.65+45-6435-4425-34-23.437414%-23.437414%23.4%5.195%5.19%6.785%6.79%-70.467640%-70.467640%70.5%3.150%3.15%10.665%10.7%-100.000000%-100.000000%100.0%0.000%0%15.968%16.0%-46.476295%-46.476295%46.5%7.634%7.63%14.262%14.3%
% percentage in Lena with a Bachelor's degree
ref percentage in Oconto 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 Oconto County and Lena
More Females More Males
Oconto County
Lena
0%100%200%FM65+45-6425-348.108108%15.881790%8.108108%8.1%5.000%5.00%5.405%5.41%-11.666667%-25.640760%-11.666667%11.7%3.333%3.33%2.985%2.99%-74.198114%217.808219%217.808219%217.8%3.448%3.45%10.959%11.0%
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 Oconto County and Lena
Lena
Oconto County
$0k$20k$40kCount%Graduate Degree1Bachelor's DegreeSome CollegeH.S. Diploma2No H.S. Diploma2Total$48,750.000000$58,393.000000$48,750.000000$48.8k71.897%1.90%$33,750.000000$47,792.000000$33,750.000000$33.8k184.878%4.88%$32,500.000000$35,147.000000$32,500.000000$32.5k9926.829%26.8%$31,029.000000$32,397.000000$31,029.000000$31.0k19953.930%53.9%$23,036.000000$25,773.000000$23,036.000000$23.0k4612.466%12.5%$31,000.000000$35,715.000000$31,000.000000$31.0k369100.000%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 Oconto County and Lena
Female Male
Oconto County
Lena
Shaded bar tips show excess over facing bar.
$20k$0k$20k$40kFMSome CollegeH.S. Diploma2Total$-28,750.000000$-27,427.000000$-28,750.000000$28.8k$28,750.000000$13,125.000000$27,427.000000$19,215.000000$41,875.000000$41.9k6039$-30,789.000000$-25,315.000000$-30,789.000000$30.8k$30,789.000000$544.000000$25,315.000000$13,535.000000$31,333.000000$31.3k74125$-30,250.000000$-29,678.000000$-30,250.000000$30.3k$30,250.000000$2,000.000000$29,678.000000$12,064.000000$32,250.000000$32.3k173196
F females with given highest level of educational attainment
M males with given highest level of educational attainment
1or professional degree 2H.S. = High School

Employment by Educational Attainment#12

Percentage of population that is employed by highest level of educational attainment among the population aged 25 to 64 years old.
Scope: population of Oconto County and Lena
Lena
Oconto County
0%20%40%60%80%100%CountBachelor's Degree1Some College2H.S. Diploma3No H.S. Diploma3100.000000%88.330542%100.000000%100.0%2182.142857%82.163188%82.142857%82.1%6989.808917%75.595806%89.808917%89.8%14150.000000%58.418541%50.000000%50.0%15
Count employed people with given educational attainment aged 25 to 64 years old
1or higher 2two or four year institution 3H.S. = High School

Lacking High School Diploma By Race#13

Percent of racial or ethnic group lacking a high school diploma (or equivalent).
Scope: population of Oconto County and Lena
Female Male
Oconto County
Lena
Shaded bar tips show excess over facing bar.
100%50%0%50%100%MFWhite1Hispanic2Other1-8.571429%-6.997434%-7.708414%-15.568862%15.6%8.571429%7.708414%2.918698%8.571429%8.6%1526-100.000000%-37.575758%-1.212121%-100.000000%100.0%100.000000%0.000000%37.575758%100.000000%100.0%23-0.000000%-20.723684%0.000000%0.0%0.000000%0.000000%20.723684%8.858309%0.000000%0.0%00
M number of males in category
F number of females in category
1non-Hispanic 2excluding black and Asian Hispanics

College Graduates By Race#14

Percent of racial or ethnic group with a bachelor's degree or higher.
Scope: population of Oconto County and Lena
Female Male
Oconto County
Lena
Shaded bar tips show excess over facing bar.
15%10%5%0%5%10%MFWhite1Hispanic2Other1-5.988024%-13.909125%-4.408052%-5.988024%6.0%5.988024%2.583405%13.909125%8.571429%8.6%1510-0.000000%-1.818182%0.000000%0.0%0.000000%0.000000%1.818182%7.272727%0.000000%0.0%00-0.000000%-10.289389%-9.447453%0.000000%0.0%0.000000%0.000000%10.289389%0.000000%0.0%00
M number of males in category
F number of females in category
1non-Hispanic 2excluding black and Asian Hispanics

Educational Attainment by County Subdivision in the Green Bay Area

There are 69 county subdivisions in the Green Bay Area. This section compares Lena to the 50 most populous county subdivisions in the Green Bay Area and to those entities that contain or substantially overlap with Lena. The least populous of the compared county subdivisions has a population of 914.

No H.S. Diploma by County Subdivision#15

Percent of population 25 years of age and older without a high school diploma (or equivalent).
Scope: population of Lena, selected other county subdivisions in the Green Bay Area, and entities that contain Lena
0%5%10%15%Count#Town of BrazeauBrazeauTown of Little RiverLittle RivTown of RiverviewRiverviewGillettTown of MorrisonMorrisonTown of MontpelierMontpelierTown of LincolnLincolnUnited States of AmericaUnited StatesTown of West KewauneeW KewauneeGreen BayLenaLenaTown of StilesStilesLena School DistrictLena100800Tract 100800Town of GillettGillettEast North CentralTown of HumboldtHumboldtZIP Code 54139ZIP 54139MidwestTown of HollandHollandTown of CarltonCarltonTown of PensaukeePensaukeeTown of OcontoOcontoTown of WrightstownWrightstownOconto CountyOcontoOcontoDenmarkBellevueAlgomaTown of EatonGreen Bay Metro AreaGreen BayWisconsinAllouezOconto FallsTown of Red RiverRed RivTown of ScottTown of MorganMorganTown of Green BayGrn BayTown of Oconto FallsOconto FallsTown of FranklinFranklinHobartTown of AbramsAbramsAshwaubenonHowardTown of GlenmoreGlenmoreWrightstownTown of LuxemburgLuxemburgLuxemburgTown of Little SuamicoLittle SuamicoTown of New DenmarkNew DenmarkKewauneeTown of RocklandRocklandTown of PittsfieldPittsfieldTown of CascoTown of ChasePulaskiDe PereSuamicoTown of LedgeviewLedgeviewTown of LawrenceLawrence16.600000%16.600000%16.6%166115.607735%15.607735%15.6%113213.748531%13.748531%13.7%117313.501647%13.501647%13.5%123413.487476%13.487476%13.5%140513.287514%13.287514%13.3%116613.050314%13.050314%13.1%83713.020590%13.020590%13.0%27,818,38027.8M12.660732%12.660732%12.7%128812.535944%12.535944%12.5%8,414912.466125%12.466125%12.5%4612.466125%12.466125%12.5%4612.066116%12.066116%12.1%1461012.044199%12.044199%12.0%21810.810811%10.810811%10.8%18810.749646%10.749646%10.7%761110.719464%10.719464%10.7%3,363,7843.36M10.662177%10.662177%10.7%951210.321716%10.321716%10.3%23110.244520%10.244520%10.2%4,641,8354.64M10.227273%10.227273%10.2%991310.146862%10.146862%10.1%761410.130391%10.130391%10.1%101159.783728%9.783728%9.8%95169.711286%9.711286%9.7%148179.607260%9.607260%9.6%2,6159.403311%9.403311%9.4%301189.357143%9.357143%9.4%131199.323378%9.323378%9.3%999209.187750%9.187750%9.2%207219.176030%9.176030%9.2%98228.685969%8.685969%8.7%18,36918.4k8.637220%8.637220%8.6%336,096336k8.512097%8.512097%8.5%869238.349057%8.349057%8.3%177247.905138%7.905138%7.9%80256.977598%6.977598%7.0%190266.929348%6.929348%6.9%51276.866077%6.866077%6.9%101286.549708%6.549708%6.5%56296.486486%6.486486%6.5%48306.319703%6.319703%6.3%306316.208426%6.208426%6.2%84326.168099%6.168099%6.2%739336.065319%6.065319%6.1%780345.790109%5.790109%5.8%48355.394191%5.394191%5.4%104365.327414%5.327414%5.3%48375.283505%5.283505%5.3%82384.992390%4.992390%5.0%164394.878049%4.878049%4.9%50404.569892%4.569892%4.6%102414.506803%4.506803%4.5%53424.465710%4.465710%4.5%84434.126214%4.126214%4.1%34444.116095%4.116095%4.1%78454.051079%4.051079%4.1%92463.911088%3.911088%3.9%600473.395282%3.395282%3.4%285483.142019%3.142019%3.1%150490.893123%0.893123%0.9%3050
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#16

Percent of population 25 years of age and older with a bachelor's degree or higher..
Scope: population of Lena, selected other county subdivisions in the Green Bay Area, and entities that contain Lena
0%10%20%30%40%Count#Town of LedgeviewLedgeviewHobartAllouezDe PereTown of LawrenceLawrenceSuamicoTown of RocklandRocklandWrightstownUnited States of AmericaUnited StatesTown of PittsfieldPittsfieldMidwestHowardEast North CentralWisconsinAshwaubenonGreen Bay Metro AreaGreen BayTown of Green BayGrn BayBellevueTown of ScottTown of Little SuamicoLittle SuamicoTown of Red RiverRed RivGreen BayTown of Oconto FallsOconto FallsPulaskiTown of ChaseKewauneeTown of New DenmarkNew DenmarkLuxemburgDenmarkTown of GlenmoreGlenmoreTown of WrightstownWrightstownOconto FallsOcontoTown of EatonTown of AbramsAbramsTown of OcontoOcontoOconto CountyOcontoTown of PensaukeePensaukeeAlgomaTown of StilesStilesTown of HollandHollandTown of RiverviewRiverviewTown of FranklinFranklinTown of Little RiverLittle RivTown of MontpelierMontpelierZIP Code 54139ZIP 54139Town of West KewauneeW KewauneeTown of LuxemburgLuxemburgTown of MorganMorganLena School DistrictLenaTown of CascoTown of HumboldtHumboldtTown of MorrisonMorrisonTown of CarltonCarlton100800Tract 100800GillettTown of LincolnLincolnTown of GillettGillettTown of BrazeauBrazeauLenaLena45.831588%45.831588%45.8%2,188141.821561%41.821561%41.8%2,025236.575571%36.575571%36.6%3,734336.151489%36.151489%36.2%5,546435.695147%35.695147%35.7%1,199534.774839%34.774839%34.8%2,919631.717687%31.717687%31.7%373730.757261%30.757261%30.8%593830.315023%30.315023%30.3%64,767,78764.8M29.346093%29.346093%29.3%552928.952816%28.952816%29.0%13,118,64213.1M28.794712%28.794712%28.8%3,7031028.462853%28.462853%28.5%8,931,6868.93M28.373439%28.373439%28.4%1,104,0821.10M26.525332%26.525332%26.5%3,1781125.916521%25.916521%25.9%54,80854.8k25.900748%25.900748%25.9%3811224.965002%24.965002%25.0%2,6751324.935733%24.935733%24.9%6791424.809741%24.809741%24.8%8151524.802372%24.802372%24.8%2511624.139215%24.139215%24.1%16,20216.2k1723.040936%23.040936%23.0%1971821.664465%21.664465%21.7%4921921.635884%21.635884%21.6%4102021.057348%21.057348%21.1%4702120.878049%20.878049%20.9%2142220.231959%20.231959%20.2%3142320.142857%20.142857%20.1%2822419.662244%19.662244%19.7%1632519.553806%19.553806%19.6%2982617.311321%17.311321%17.3%3672716.744767%16.744767%16.7%5362816.573034%16.573034%16.6%1772916.555802%16.555802%16.6%2243016.271885%16.271885%16.3%1583116.194570%16.194570%16.2%4,40816.148445%16.148445%16.1%1613216.111851%16.111851%16.1%3633315.867769%15.867769%15.9%1923415.599174%15.599174%15.6%1513515.158637%15.158637%15.2%1293614.864865%14.864865%14.9%1103714.502762%14.502762%14.5%1053813.631157%13.631157%13.6%1193913.538874%13.538874%13.5%30313.155292%13.155292%13.2%1334013.096559%13.096559%13.1%1184112.635870%12.635870%12.6%934212.265193%12.265193%12.3%22212.257282%12.257282%12.3%1014312.008979%12.008979%12.0%1074411.849711%11.849711%11.8%1234511.348465%11.348465%11.3%854610.523289%10.523289%10.5%1839.989023%9.989023%10.0%91479.591195%9.591195%9.6%61489.476662%9.476662%9.5%67497.900000%7.900000%7.9%79506.775068%6.775068%6.8%256.775068%6.775068%6.8%25
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#17

Percent of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).
Scope: population of Lena, selected other county subdivisions in the Green Bay Area, and entities that contain Lena
0%1%2%3%4%5%Count#Town of LawrenceLawrenceTown of LedgeviewLedgeviewAllouezTown of ScottTown of RocklandRocklandUnited States of AmericaUnited StatesHobartOconto FallsDe PereTown of Red RiverRed RivMidwestEast North CentralWisconsinKewauneeSuamicoTown of Oconto FallsOconto FallsTown of StilesStilesTown of PittsfieldPittsfieldGreen Bay Metro AreaGreen BayOcontoGreen BayTown of Green BayGrn BayWrightstownTown of Little SuamicoLittle SuamicoTown of LincolnLincolnTown of RiverviewRiverviewHowardTown of MontpelierMontpelierTown of WrightstownWrightstownOconto CountyOcontoZIP Code 54139ZIP 54139GillettTown of New DenmarkNew DenmarkAshwaubenonTown of LuxemburgLuxemburgLuxemburgBellevueTown of EatonTown of FranklinFranklinTown of MorrisonMorrisonLena School DistrictLenaTown of GlenmoreGlenmoreTown of PensaukeePensaukeeTown of BrazeauBrazeauTown of West KewauneeW KewauneeTown of MorganMorganLenaLenaTown of HollandHollandTown of CarltonCarltonTown of CascoTown of OcontoOcontoTown of Chase100800Tract 100800Town of AbramsAbramsPulaskiAlgomaDenmarkTown of HumboldtHumboldtTown of Little RiverLittle RivTown of GillettGillett5.180113%5.180113%5.2%17415.027231%5.027231%5.0%24024.358899%4.358899%4.4%44533.782593%3.782593%3.8%10343.401361%3.401361%3.4%4053.336158%3.336158%3.3%7,127,6737.13M3.118546%3.118546%3.1%15163.113208%3.113208%3.1%6673.083241%3.083241%3.1%47383.063241%3.063241%3.1%3192.893416%2.893416%2.9%1,311,0191.31M2.855432%2.855432%2.9%896,039896k2.703886%2.703886%2.7%105,215105k2.553763%2.553763%2.6%57102.406481%2.406481%2.4%202112.222222%2.222222%2.2%19122.066116%2.066116%2.1%25131.913876%1.913876%1.9%36141.879146%1.879146%1.9%3,9741.780694%1.780694%1.8%57151.777440%1.777440%1.8%1,193161.699524%1.699524%1.7%25171.504149%1.504149%1.5%29181.491629%1.491629%1.5%49191.415094%1.415094%1.4%9201.410106%1.410106%1.4%12211.384137%1.384137%1.4%178221.260023%1.260023%1.3%11231.246719%1.246719%1.2%19241.076454%1.076454%1.1%2931.027703%1.027703%1.0%230.987925%0.987925%1.0%9250.878049%0.878049%0.9%9260.784576%0.784576%0.8%94270.776915%0.776915%0.8%7280.773196%0.773196%0.8%12290.765282%0.765282%0.8%82300.749064%0.749064%0.7%8310.675676%0.675676%0.7%5320.674374%0.674374%0.7%7330.662983%0.662983%0.7%120.603136%0.603136%0.6%5340.601805%0.601805%0.6%6350.600000%0.600000%0.6%6360.593472%0.593472%0.6%6370.543478%0.543478%0.5%4380.542005%0.542005%0.5%20.542005%0.542005%0.5%20.516529%0.516529%0.5%5390.400534%0.400534%0.4%3400.364078%0.364078%0.4%3410.308960%0.308960%0.3%3420.263852%0.263852%0.3%5430.230017%0.230017%0.2%40.221729%0.221729%0.2%3440.000000%0.000000%0.0%0450.000000%0.000000%0.0%0460.000000%0.000000%0.0%0470.000000%0.000000%0.0%0480.000000%0.000000%0.0%0490.000000%0.000000%0.0%050
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#18

Percentage more likely men are than women to not have a high school diploma (or equivalent) among people aged 25 years and older.
Scope: population of Lena, selected other county subdivisions in the Green Bay Area, and entities that contain Lena
Female
Male
10x5x0xFM#RocklandOcontoPittsfieldDenmarkMorganCarltonGlenmoreDe PereTown of ScottOcontoNew DenmarkLincolnRiverviewZIP 54139Little SuamicoHollandGillettOconto FallsMontpelierLenaTown of EatonGreen BayLittle RivGillettOcontoHumboldtTract 100800Green BayRed RivWisconsinStilesBrazeauFranklinW KewauneeMidwestEast North CentralLuxemburgTown of ChaseUnited StatesWrightstownSuamicoHowardPensaukeeLuxemburgLedgeviewMorrisonAbramsGrn BayAllouezWrightstownAshwaubenonTown of CascoBellevueAlgomaHobartOconto FallsPulaskiKewauneeLenaLenaLawrence-1.000000x-1.000000x2.953846x2.953846x2.95x2.257%2.26%6.667%6.67%1-1.000000x-1.000000x2.571364x2.571364x2.57x5.318%5.32%13.674%13.7%2-1.000000x-1.000000x2.518677x2.518677x2.52x2.542%2.54%6.403%6.40%3-1.000000x-1.000000x2.355563x2.355563x2.36x5.699%5.70%13.424%13.4%4-1.000000x-1.000000x2.297872x2.297872x2.30x4.167%4.17%9.574%9.57%5-1.000000x-1.000000x2.283739x2.283739x2.28x6.094%6.09%13.918%13.9%6-1.000000x-1.000000x2.259169x2.259169x2.26x3.571%3.57%8.068%8.07%7-1.000000x-1.000000x2.147134x2.147134x2.15x2.553%2.55%5.481%5.48%8-1.000000x-1.000000x2.063668x2.063668x2.06x4.460%4.46%9.204%9.20%9-1.000000x-1.000000x1.859538x1.859538x1.86x6.832%6.83%12.705%12.7%10-1.000000x-1.000000x1.837743x1.837743x1.84x3.455%3.45%6.349%6.35%11-1.000000x-1.000000x1.781857x1.781857x1.78x9.325%9.32%16.615%16.6%12-1.000000x-1.000000x1.739652x1.739652x1.74x9.951%9.95%17.312%17.3%13-1.000000x-1.000000x1.719865x1.719865x1.72x7.498%7.50%12.895%12.9%-1.000000x-1.000000x1.671027x1.671027x1.67x3.697%3.70%6.177%6.18%14-1.000000x-1.000000x1.640228x1.640228x1.64x7.606%7.61%12.476%12.5%15-1.000000x-1.000000x1.581086x1.581086x1.58x8.150%8.15%12.887%12.9%16-1.000000x-1.000000x1.457645x1.457645x1.46x5.301%5.30%7.727%7.73%17-1.000000x-1.000000x1.449249x1.449249x1.45x10.660%10.7%15.449%15.4%18-1.000000x-1.000000x1.440914x1.440914x1.44x9.779%9.78%14.090%14.1%-1.000000x-1.000000x1.440913x1.440913x1.44x7.486%7.49%10.786%10.8%19-1.000000x-1.000000x1.408197x1.408197x1.41x10.435%10.4%14.694%14.7%20-1.000000x-1.000000x1.398582x1.398582x1.40x12.931%12.9%18.085%18.1%21-1.000000x-1.000000x1.374407x1.374407x1.37x11.379%11.4%15.639%15.6%22-1.000000x-1.000000x1.374304x1.374304x1.37x8.070%8.07%11.091%11.1%-1.000000x-1.000000x1.363631x1.363631x1.36x8.986%8.99%12.254%12.3%23-1.000000x-1.000000x1.284848x1.284848x1.28x9.434%9.43%12.121%12.1%-1.000000x-1.000000x1.245810x1.245810x1.25x7.746%7.75%9.650%9.65%-1.000000x-1.000000x1.226145x1.226145x1.23x7.085%7.09%8.687%8.69%24-1.000000x-1.000000x1.219291x1.219291x1.22x7.799%7.80%9.509%9.51%-1.000000x-1.000000x1.210467x1.210467x1.21x10.830%10.8%13.110%13.1%25-1.000000x-1.000000x1.208490x1.208490x1.21x15.030%15.0%18.164%18.2%26-1.000000x-1.000000x1.201139x1.201139x1.20x5.898%5.90%7.084%7.08%27-1.000000x-1.000000x1.144599x1.144599x1.14x11.811%11.8%13.519%13.5%28-1.000000x-1.000000x1.127915x1.127915x1.13x9.647%9.65%10.881%10.9%-1.000000x-1.000000x1.125371x1.125371x1.13x10.108%10.1%11.375%11.4%-1.000000x-1.000000x1.112689x1.112689x1.11x5.024%5.02%5.590%5.59%29-1.000000x-1.000000x1.111622x1.111622x1.11x3.899%3.90%4.334%4.33%30-1.000000x-1.000000x1.109070x1.109070x1.11x12.369%12.4%13.719%13.7%-1.000000x-1.000000x1.088361x1.088361x1.09x9.280%9.28%10.100%10.1%31-1.000000x-1.000000x1.058399x1.058399x1.06x3.299%3.30%3.492%3.49%32-1.000000x-1.000000x1.056613x1.056613x1.06x5.903%5.90%6.237%6.24%33-1.000000x-1.000000x1.053928x1.053928x1.05x9.853%9.85%10.385%10.4%34-1.017857x-1.017857x1.02x1.000000x1.000000x5.328%5.33%5.235%5.23%35-1.069705x-1.069705x1.07x1.000000x1.000000x3.246%3.25%3.034%3.03%36-1.095584x-1.095584x1.10x1.000000x1.000000x14.095%14.1%12.865%12.9%37-1.127994x-1.127994x1.13x1.000000x1.000000x6.587%6.59%5.839%5.84%38-1.178462x-1.178462x1.18x1.000000x1.000000x7.461%7.46%6.331%6.33%39-1.228382x-1.228382x1.23x1.000000x1.000000x9.398%9.40%7.651%7.65%40-1.229865x-1.229865x1.23x1.000000x1.000000x5.943%5.94%4.832%4.83%41-1.237978x-1.237978x1.24x1.000000x1.000000x6.794%6.79%5.488%5.49%42-1.251923x-1.251923x1.25x1.000000x1.000000x4.615%4.62%3.687%3.69%43-1.346928x-1.346928x1.35x1.000000x1.000000x10.654%10.7%7.910%7.91%44-1.366355x-1.366355x1.37x1.000000x1.000000x10.586%10.6%7.748%7.75%45-1.466824x-1.466824x1.47x1.000000x1.000000x7.457%7.46%5.084%5.08%46-1.555556x-1.555556x1.56x1.000000x1.000000x10.000%10.0%6.429%6.43%47-1.735089x-1.735089x1.74x1.000000x1.000000x4.957%4.96%2.857%2.86%48-1.821001x-1.821001x1.82x1.000000x1.000000x5.784%5.78%3.176%3.18%49-1.932676x-1.932676x1.93x1.000000x1.000000x16.763%16.8%8.673%8.67%-1.932676x-1.932676x1.93x1.000000x1.000000x16.763%16.8%8.673%8.67%-10.000000x-10.000000x> 10.0x1.000000x1.000000x1.877%1.88%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

Over-Education Sex Ratio by County Subdivision#19

Percentage more likely men are than women to have a professional or doctorate degree (e.g., MBA, PhD, or MD) among people aged 25 years and older.
Scope: population of Lena, selected other county subdivisions in the Green Bay Area, and entities that contain Lena
Female
Male
10x5x0x5x10xFM#KewauneeNew DenmarkOcontoOconto FallsGlenmoreMontpelierTown of CascoTown of ScottStilesRed RivLenaZIP 54139HollandOcontoRiverviewMorrisonWrightstownHowardLuxemburgLedgeviewLawrenceGillettGreen BayAllouezGreen BaySuamicoEast North CentralMidwestTown of EatonWisconsinUnited StatesRocklandDe PereWrightstownPittsfieldLuxemburgOcontoOconto FallsW KewauneeGrn BayTract 100800PensaukeeFranklinAshwaubenonHobartBellevueBrazeauLincolnLenaLenaLittle SuamicoTown of ChaseAbramsCarltonMorgan-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%5.486%5.49%1-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%1.786%1.79%2-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%0.615%0.61%3-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%4.318%4.32%4-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%1.222%1.22%5-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%2.296%2.30%6-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%0.691%0.69%7-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.548%0.55%6.644%6.64%8-1.000000x-1.000000x9.711890x9.711890x9.71x0.361%0.36%3.506%3.51%9-1.000000x-1.000000x8.900901x8.900901x8.90x0.607%0.61%5.405%5.41%10-1.000000x-1.000000x4.516299x4.516299x4.52x0.233%0.23%1.052%1.05%-1.000000x-1.000000x4.328138x4.328138x4.33x0.375%0.37%1.623%1.62%-1.000000x-1.000000x3.431862x3.431862x3.43x0.224%0.22%0.768%0.77%11-1.000000x-1.000000x3.210771x3.210771x3.21x0.856%0.86%2.748%2.75%12-1.000000x-1.000000x2.815490x2.815490x2.82x0.728%0.73%2.050%2.05%13-1.000000x-1.000000x2.558480x2.558480x2.56x0.381%0.38%0.975%0.97%14-1.000000x-1.000000x2.520698x2.520698x2.52x0.693%0.69%1.746%1.75%15-1.000000x-1.000000x2.492011x2.492011x2.49x0.802%0.80%1.999%2.00%16-1.000000x-1.000000x2.166443x2.166443x2.17x0.496%0.50%1.074%1.07%17-1.000000x-1.000000x2.041817x2.041817x2.04x3.328%3.33%6.795%6.79%18-1.000000x-1.000000x2.016531x2.016531x2.02x3.379%3.38%6.814%6.81%19-1.000000x-1.000000x2.013216x2.013216x2.01x0.656%0.66%1.322%1.32%20-1.000000x-1.000000x2.006236x2.006236x2.01x1.188%1.19%2.383%2.38%21-1.000000x-1.000000x1.991366x1.991366x1.99x2.901%2.90%5.777%5.78%22-1.000000x-1.000000x1.720824x1.720824x1.72x1.386%1.39%2.385%2.38%-1.000000x-1.000000x1.601911x1.601911x1.60x1.851%1.85%2.966%2.97%23-1.000000x-1.000000x1.597848x1.597848x1.60x2.216%2.22%3.541%3.54%-1.000000x-1.000000x1.589934x1.589934x1.59x2.251%2.25%3.579%3.58%-1.000000x-1.000000x1.587447x1.587447x1.59x0.576%0.58%0.914%0.91%24-1.000000x-1.000000x1.576114x1.576114x1.58x2.109%2.11%3.323%3.32%-1.000000x-1.000000x1.526215x1.526215x1.53x2.660%2.66%4.060%4.06%-1.000000x-1.000000x1.440000x1.440000x1.44x2.778%2.78%4.000%4.00%25-1.000000x-1.000000x1.363936x1.363936x1.36x2.638%2.64%3.598%3.60%26-1.000000x-1.000000x1.261797x1.261797x1.26x1.332%1.33%1.681%1.68%27-1.000000x-1.000000x1.259338x1.259338x1.26x1.695%1.69%2.134%2.13%28-1.000000x-1.000000x1.153899x1.153899x1.15x0.718%0.72%0.828%0.83%29-1.000000x-1.000000x1.084340x1.084340x1.08x1.032%1.03%1.119%1.12%-1.000000x-1.000000x1.030321x1.030321x1.03x3.070%3.07%3.163%3.16%30-1.000000x-1.000000x1.009940x1.009940x1.01x0.591%0.59%0.596%0.60%31-1.025052x-1.025052x1.03x1.000000x1.000000x1.722%1.72%1.680%1.68%32-1.050708x-1.050708x1.05x1.000000x1.000000x0.236%0.24%0.224%0.22%-1.090147x-1.090147x1.09x1.000000x1.000000x0.629%0.63%0.577%0.58%33-1.475871x-1.475871x1.48x1.000000x1.000000x0.804%0.80%0.545%0.54%34-1.623043x-1.623043x1.62x1.000000x1.000000x0.961%0.96%0.592%0.59%35-1.653790x-1.653790x1.65x1.000000x1.000000x3.848%3.85%2.327%2.33%36-1.720627x-1.720627x1.72x1.000000x1.000000x0.960%0.96%0.558%0.56%37-2.008016x-2.008016x2.01x1.000000x1.000000x0.802%0.80%0.399%0.40%38-2.090032x-2.090032x2.09x1.000000x1.000000x1.929%1.93%0.923%0.92%39-10.000000x-10.000000x> 10.0x1.000000x1.000000x1.156%1.16%0.000%0%-10.000000x-10.000000x> 10.0x1.000000x1.000000x1.156%1.16%0.000%0%-10.000000x-10.000000x> 10.0x1.000000x1.000000x3.123%3.12%0.000%0%40-10.000000x-10.000000x> 10.0x1.000000x1.000000x0.527%0.53%0.000%0%41-10.000000x-10.000000x> 10.0x1.000000x1.000000x0.449%0.45%0.000%0%42-10.000000x-10.000000x> 10.0x1.000000x1.000000x0.831%0.83%0.000%0%43-10.000000x-10.000000x> 10.0x1.000000x1.000000x1.111%1.11%0.000%0%44
F percentage of females in category
M percentage of males in category
# rank of county subdivision out of 44 by male-to-female sex ratio

Educational Attainment by County Subdivision in Wisconsin

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

No H.S. Diploma by County Subdivision#20

Percent of population 25 years of age and older without a high school diploma (or equivalent).
Scope: population of Lena, selected other county subdivisions in Wisconsin, and entities that contain Lena
0%5%10%15%Count#BeloitRacineMilwaukeeUnited States of AmericaUnited StatesGreen BayLenaLenaLena School DistrictLenaSheboyganKenoshaManitowocCudahy100800Tract 100800WausauEast North CentralZIP Code 54139ZIP 54139MidwestWest AllisOshkoshBeaver DamOconto CountyOcontoSouth MilwaukeeS MilwaukeeMarshfieldFond du LacGreen Bay Metro AreaGreen BayFitchburgWisconsinJanesvilleMenomonieGreenfieldPleasant PrairieAppletonFranklinWaukeshaTown of Grand ChuteGrand ChuteLa CrosseWisconsin RapidsCaledoniaWest BendSuperiorTown of MenashaMenashaAshwaubenonEau ClaireStevens PointHowardMount PleasantMt PleasantNeenahOak CreekGermantownOnalaskaMadisonMenomonee FallsNew BerlinOconomowocSun PrairieDe PereMuskegoWauwatosaBrookfieldMiddletonMequon18.491431%18.491431%18.5%4,197117.907441%17.907441%17.9%8,710217.485105%17.485105%17.5%63,80063.8k313.020590%13.020590%13.0%27,818,38027.8M12.535944%12.535944%12.5%8,414412.466125%12.466125%12.5%4612.466125%12.466125%12.5%4612.044199%12.044199%12.0%21811.643417%11.643417%11.6%3,806511.549265%11.549265%11.5%7,360611.206563%11.206563%11.2%2,609711.082337%11.082337%11.1%1,455810.810811%10.810811%10.8%18810.776184%10.776184%10.8%2,885910.719464%10.719464%10.7%3,363,7843.36M10.321716%10.321716%10.3%23110.244520%10.244520%10.2%4,641,8354.64M10.028497%10.028497%10.0%4,399109.995428%9.995428%10.0%4,154119.950027%9.950027%10.0%1,115129.607260%9.607260%9.6%2,6159.190270%9.190270%9.2%1,379138.829004%8.829004%8.8%1,091148.713948%8.713948%8.7%2,547158.685969%8.685969%8.7%18,36918.4k8.662728%8.662728%8.7%1,613168.637220%8.637220%8.6%336,096336k8.522583%8.522583%8.5%3,704178.211921%8.211921%8.2%620188.204982%8.204982%8.2%2,296197.709924%7.709924%7.7%1,111207.618904%7.618904%7.6%3,034217.392323%7.392323%7.4%1,924227.158983%7.158983%7.2%3,393237.144208%7.144208%7.1%1,133247.116644%7.116644%7.1%2,075257.048284%7.048284%7.0%889266.746719%6.746719%6.7%1,208276.565400%6.565400%6.6%1,422286.289585%6.289585%6.3%1,142296.244351%6.244351%6.2%829306.168099%6.168099%6.2%739316.128290%6.128290%6.1%2,398326.111996%6.111996%6.1%883336.065319%6.065319%6.1%780346.042598%6.042598%6.0%1,149355.863324%5.863324%5.9%1,015365.765641%5.765641%5.8%1,421375.227570%5.227570%5.2%719384.888290%4.888290%4.9%617394.836248%4.836248%4.8%7,351404.484909%4.484909%4.5%1,165414.236891%4.236891%4.2%1,267423.988090%3.988090%4.0%442433.955766%3.955766%4.0%812443.911088%3.911088%3.9%600453.554446%3.554446%3.6%598463.390471%3.390471%3.4%1,167472.806979%2.806979%2.8%761482.731305%2.731305%2.7%351492.107701%2.107701%2.1%35550
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older without a high school diploma (or equivalent).

Bachelor's Degrees by County Subdivision#21

Percent of population 25 years of age and older with a bachelor's degree or higher..
Scope: population of Lena, selected other county subdivisions in Wisconsin, and entities that contain Lena
0%20%40%60%Count#MequonMiddletonWauwatosaBrookfieldMadisonFitchburgOconomowocMenomonee FallsSun PrairieNew BerlinGermantownFranklinStevens PointDe PereWaukeshaOnalaskaMenomonieMuskegoPleasant PrairieLa CrosseMount PleasantMt PleasantNeenahEau ClaireAppletonTown of Grand ChuteGrand ChuteOak CreekUnited States of AmericaUnited StatesMidwestGreenfieldCaledoniaTown of MenashaMenashaHowardEast North CentralWisconsinMarshfieldWest BendAshwaubenonGreen Bay Metro AreaGreen BayWausauOshkoshGreen BayWest AllisFond du LacMilwaukeeKenoshaSuperiorJanesvilleCudahyManitowocSouth MilwaukeeS MilwaukeeSheboyganBeaver DamRacineBeloitOconto CountyOcontoWisconsin RapidsZIP Code 54139ZIP 54139Lena School DistrictLena100800Tract 100800LenaLena63.254765%63.254765%63.3%10,65410.7k158.898140%58.898140%58.9%7,569258.155142%58.155142%58.2%20,01720.0k358.053926%58.053926%58.1%15,73915.7k456.337583%56.337583%56.3%85,63285.6k546.358754%46.358754%46.4%8,632644.229902%44.229902%44.2%4,902741.080228%41.080228%41.1%10,67110.7k841.077605%41.077605%41.1%8,432940.780498%40.780498%40.8%12,19512.2k1039.610295%39.610295%39.6%5,4481137.841472%37.841472%37.8%9,8491236.471240%36.471240%36.5%5,2691336.151489%36.151489%36.2%5,5461435.550164%35.550164%35.6%16,84916.8k1535.152908%35.152908%35.2%4,4371635.139073%35.139073%35.1%2,6531733.499762%33.499762%33.5%5,6361833.074254%33.074254%33.1%4,7661932.942347%32.942347%32.9%9,6052032.747831%32.747831%32.7%6,2272132.464907%32.464907%32.5%5,6202232.432916%32.432916%32.4%12,69112.7k2332.296218%32.296218%32.3%12,86112.9k2432.202535%32.202535%32.2%5,1072531.640023%31.640023%31.6%7,7982630.315023%30.315023%30.3%64,767,78764.8M28.952816%28.952816%29.0%13,118,64213.1M28.921131%28.921131%28.9%8,0932728.919296%28.919296%28.9%5,1782828.909310%28.909310%28.9%3,8382928.794712%28.794712%28.8%3,7033028.462853%28.462853%28.5%8,931,6868.93M28.373439%28.373439%28.4%1,104,0821.10M28.348305%28.348305%28.3%3,5033127.212706%27.212706%27.2%5,8943226.525332%26.525332%26.5%3,1783325.916521%25.916521%25.9%54,80854.8k25.519199%25.519199%25.5%6,8323424.478452%24.478452%24.5%10,17310.2k3524.139215%24.139215%24.1%16,20216.2k3623.980394%23.980394%24.0%10,51910.5k3723.606692%23.606692%23.6%6,9003823.517740%23.517740%23.5%85,81285.8k3922.927488%22.927488%22.9%14,61114.6k4022.415597%22.415597%22.4%4,0704122.035848%22.035848%22.0%9,5774221.471552%21.471552%21.5%2,8194321.017138%21.017138%21.0%4,8934420.519827%20.519827%20.5%3,0794519.530103%19.530103%19.5%6,3844618.623951%18.623951%18.6%2,0874717.525031%17.525031%17.5%8,5244816.605719%16.605719%16.6%3,7694916.194570%16.194570%16.2%4,40815.880441%15.880441%15.9%2,0035013.538874%13.538874%13.5%30312.265193%12.265193%12.3%22210.523289%10.523289%10.5%1836.775068%6.775068%6.8%256.775068%6.775068%6.8%25
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older with a bachelor's degree or higher..

Very Advanced Degrees by County Subdivision#22

Percent of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).
Scope: population of Lena, selected other county subdivisions in Wisconsin, and entities that contain Lena
0%5%10%Count#MequonMiddletonBrookfieldMadisonWauwatosaFitchburgMarshfieldMenomonieLa CrosseStevens PointOnalaskaOconomowocNew BerlinUnited States of AmericaUnited StatesMenomonee FallsSun PrairieNeenahFranklinDe PereGermantownMidwestEau ClaireEast North CentralAppletonWisconsinMuskegoPleasant PrairieBeaver DamWausauTown of Grand ChuteGrand ChuteCaledoniaMount PleasantMt PleasantTown of MenashaMenashaWaukeshaMilwaukeeGreen Bay Metro AreaGreen BayGreenfieldOak CreekBeloitGreen BayKenoshaWisconsin RapidsJanesvilleOshkoshSuperiorFond du LacHowardCudahyWest BendWest AllisRacineManitowocOconto CountyOcontoZIP Code 54139ZIP 54139South MilwaukeeS MilwaukeeSheboyganAshwaubenonLena School DistrictLenaLenaLena100800Tract 10080011.084724%11.084724%11.1%1,867110.022566%10.022566%10.0%1,28829.217661%9.217661%9.2%2,49939.171173%9.171173%9.2%13,94013.9k48.094131%8.094131%8.1%2,78657.196563%7.196563%7.2%1,34065.867120%5.867120%5.9%72574.993377%4.993377%5.0%37784.777583%4.777583%4.8%1,39394.679172%4.679172%4.7%676104.547615%4.547615%4.5%574114.222683%4.222683%4.2%468123.762039%3.762039%3.8%1,125133.336158%3.336158%3.3%7,127,6737.13M3.295350%3.295350%3.3%856143.288352%3.288352%3.3%675153.188724%3.188724%3.2%552163.100626%3.100626%3.1%807173.083241%3.083241%3.1%473182.995492%2.995492%3.0%412192.893416%2.893416%2.9%1,311,0191.31M2.869921%2.869921%2.9%1,123202.855432%2.855432%2.9%896,039896k2.794937%2.794937%2.8%1,113212.703886%2.703886%2.7%105,215105k2.674750%2.674750%2.7%450222.637058%2.637058%2.6%380232.552204%2.552204%2.6%286242.416704%2.416704%2.4%647252.396116%2.396116%2.4%380262.356884%2.356884%2.4%422272.303445%2.303445%2.3%438282.244652%2.244652%2.2%298292.192214%2.192214%2.2%1,039302.043126%2.043126%2.0%7,455311.879146%1.879146%1.9%3,9741.868992%1.868992%1.9%523321.809624%1.809624%1.8%446331.784377%1.784377%1.8%405341.777440%1.777440%1.8%1,193351.762204%1.762204%1.8%1,123361.688734%1.688734%1.7%213371.555418%1.555418%1.6%676381.549604%1.549604%1.5%644391.525582%1.525582%1.5%277401.454035%1.454035%1.5%425411.384137%1.384137%1.4%178421.302460%1.302460%1.3%171431.292765%1.292765%1.3%280441.251567%1.251567%1.3%549451.155451%1.155451%1.2%562461.133972%1.133972%1.1%264471.076454%1.076454%1.1%2931.027703%1.027703%1.0%230.893036%0.893036%0.9%134480.868820%0.868820%0.9%284490.784576%0.784576%0.8%94500.662983%0.662983%0.7%120.542005%0.542005%0.5%20.542005%0.542005%0.5%20.230017%0.230017%0.2%4
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).

Under-Education Sex Ratio by County Subdivision#23

Percentage more likely men are than women to not have a high school diploma (or equivalent) among people aged 25 years and older.
Scope: population of Lena, selected other county subdivisions in Wisconsin, and entities that contain Lena
Female
Male
1x0x1x2xFM#De PereMenashaOshkoshZIP 54139FranklinCaledoniaLenaManitowocGreen BayPleasant PrairieOcontoWauwatosaWaukeshaJanesvilleMt PleasantTract 100800SuperiorGreen BayStevens PointAppletonWisconsinRacineGrand ChuteGermantownMadisonMuskegoKenoshaMequonMidwestEast North CentralMilwaukeeWest BendOnalaskaUnited StatesEau ClaireWisconsin RapidsMenomonee FallsBeloitBeaver DamLa CrosseHowardOak CreekGreenfieldMiddletonFond du LacMarshfieldNew BerlinSheboyganNeenahFitchburgSun PrairieWest AllisS MilwaukeeCudahyWausauBrookfieldAshwaubenonMenomonieOconomowocLenaLena-1.000000x-1.000000x2.147134x2.147134x2.15x2.553%2.55%5.481%5.48%1-1.000000x-1.000000x1.888774x1.888774x1.89x4.337%4.34%8.192%8.19%2-1.000000x-1.000000x1.812682x1.812682x1.81x7.022%7.02%12.729%12.7%3-1.000000x-1.000000x1.719865x1.719865x1.72x7.498%7.50%12.895%12.9%-1.000000x-1.000000x1.578941x1.578941x1.58x5.723%5.72%9.036%9.04%4-1.000000x-1.000000x1.534399x1.534399x1.53x5.333%5.33%8.182%8.18%5-1.000000x-1.000000x1.440914x1.440914x1.44x9.779%9.78%14.090%14.1%-1.000000x-1.000000x1.432549x1.432549x1.43x9.294%9.29%13.313%13.3%6-1.000000x-1.000000x1.408197x1.408197x1.41x10.435%10.4%14.694%14.7%7-1.000000x-1.000000x1.380848x1.380848x1.38x6.493%6.49%8.965%8.97%8-1.000000x-1.000000x1.374304x1.374304x1.37x8.070%8.07%11.091%11.1%-1.000000x-1.000000x1.306431x1.306431x1.31x2.969%2.97%3.879%3.88%9-1.000000x-1.000000x1.304061x1.304061x1.30x6.240%6.24%8.137%8.14%10-1.000000x-1.000000x1.294088x1.294088x1.29x7.468%7.47%9.664%9.66%11-1.000000x-1.000000x1.293422x1.293422x1.29x5.323%5.32%6.885%6.89%12-1.000000x-1.000000x1.284848x1.284848x1.28x9.434%9.43%12.121%12.1%-1.000000x-1.000000x1.278895x1.278895x1.28x5.545%5.54%7.091%7.09%13-1.000000x-1.000000x1.245810x1.245810x1.25x7.746%7.75%9.650%9.65%-1.000000x-1.000000x1.229327x1.229327x1.23x5.499%5.50%6.760%6.76%14-1.000000x-1.000000x1.219351x1.219351x1.22x6.887%6.89%8.397%8.40%15-1.000000x-1.000000x1.219291x1.219291x1.22x7.799%7.80%9.509%9.51%-1.000000x-1.000000x1.214505x1.214505x1.21x16.245%16.2%19.730%19.7%16-1.000000x-1.000000x1.207489x1.207489x1.21x6.484%6.48%7.830%7.83%17-1.000000x-1.000000x1.203474x1.203474x1.20x4.768%4.77%5.738%5.74%18-1.000000x-1.000000x1.189278x1.189278x1.19x4.425%4.43%5.263%5.26%19-1.000000x-1.000000x1.159324x1.159324x1.16x3.296%3.30%3.822%3.82%20-1.000000x-1.000000x1.152187x1.152187x1.15x10.767%10.8%12.406%12.4%21-1.000000x-1.000000x1.145574x1.145574x1.15x1.970%1.97%2.257%2.26%22-1.000000x-1.000000x1.127915x1.127915x1.13x9.647%9.65%10.881%10.9%-1.000000x-1.000000x1.125371x1.125371x1.13x10.108%10.1%11.375%11.4%-1.000000x-1.000000x1.123984x1.123984x1.12x16.526%16.5%18.574%18.6%23-1.000000x-1.000000x1.118245x1.118245x1.12x6.211%6.21%6.945%6.95%24-1.000000x-1.000000x1.113721x1.113721x1.11x4.646%4.65%5.175%5.17%25-1.000000x-1.000000x1.109070x1.109070x1.11x12.369%12.4%13.719%13.7%-1.000000x-1.000000x1.104897x1.104897x1.10x5.834%5.83%6.446%6.45%26-1.000000x-1.000000x1.104741x1.104741x1.10x6.724%6.72%7.428%7.43%27-1.000000x-1.000000x1.077248x1.077248x1.08x4.329%4.33%4.663%4.66%28-1.000000x-1.000000x1.069954x1.069954x1.07x17.920%17.9%19.173%19.2%29-1.000000x-1.000000x1.063348x1.063348x1.06x9.653%9.65%10.265%10.3%30-1.000000x-1.000000x1.059381x1.059381x1.06x6.918%6.92%7.329%7.33%31-1.000000x-1.000000x1.056613x1.056613x1.06x5.903%5.90%6.237%6.24%32-1.000000x-1.000000x1.048827x1.048827x1.05x5.631%5.63%5.906%5.91%33-1.000000x-1.000000x1.046668x1.046668x1.05x8.030%8.03%8.405%8.40%34-1.000000x-1.000000x1.022109x1.022109x1.02x2.704%2.70%2.764%2.76%35-1.000000x-1.000000x1.018058x1.018058x1.02x8.641%8.64%8.797%8.80%36-1.000000x-1.000000x1.015610x1.015610x1.02x8.765%8.76%8.902%8.90%37-1.000000x-1.000000x1.012610x1.012610x1.01x4.211%4.21%4.265%4.26%38-1.000000x-1.000000x1.004509x1.004509x1.00x11.618%11.6%11.670%11.7%39-1.001253x-1.001253x1.00x1.000000x1.000000x5.867%5.87%5.859%5.86%40-1.016031x-1.016031x1.02x1.000000x1.000000x8.734%8.73%8.596%8.60%41-1.022158x-1.022158x1.02x1.000000x1.000000x3.997%4.00%3.910%3.91%42-1.024115x-1.024115x1.02x1.000000x1.000000x10.145%10.1%9.906%9.91%43-1.068390x-1.068390x1.07x1.000000x1.000000x9.477%9.48%8.871%8.87%44-1.082508x-1.082508x1.08x1.000000x1.000000x11.515%11.5%10.638%10.6%45-1.083232x-1.083232x1.08x1.000000x1.000000x11.187%11.2%10.327%10.3%46-1.121159x-1.121159x1.12x1.000000x1.000000x2.957%2.96%2.637%2.64%47-1.237978x-1.237978x1.24x1.000000x1.000000x6.794%6.79%5.488%5.49%48-1.368790x-1.368790x1.37x1.000000x1.000000x9.414%9.41%6.877%6.88%49-1.427909x-1.427909x1.43x1.000000x1.000000x4.664%4.66%3.266%3.27%50-1.932676x-1.932676x1.93x1.000000x1.000000x16.763%16.8%8.673%8.67%-1.932676x-1.932676x1.93x1.000000x1.000000x16.763%16.8%8.673%8.67%
F percentage of females in category
M percentage of males in category
# rank of county subdivision out of 50 by male-to-female sex ratio

Over-Education Sex Ratio by County Subdivision#24

Percentage more likely men are than women to have a professional or doctorate degree (e.g., MBA, PhD, or MD) among people aged 25 years and older.
Scope: population of Lena, selected other county subdivisions in Wisconsin, and entities that contain Lena
Female
Male
10x5x0xFM#LenaZIP 54139NeenahPleasant PrairieCudahyMenomonieOnalaskaMuskegoHowardMarshfieldMequonJanesvilleSheboyganRacineBeaver DamBrookfieldGreen BayBeloitStevens PointWausauFitchburgSun PrairieEau ClaireOshkoshAppletonFond du LacGreen BayNew BerlinWest AllisWauwatosaWest BendEast North CentralMidwestWisconsinMt PleasantCaledoniaUnited StatesSuperiorManitowocFranklinLa CrosseS MilwaukeeMiddletonMenomonee FallsMadisonMilwaukeeDe PereGrand ChuteKenoshaGermantownWaukeshaOcontoOconomowocWisconsin RapidsMenashaTract 100800GreenfieldOak CreekAshwaubenonLenaLena-1.000000x-1.000000x4.516299x4.516299x4.52x0.233%0.23%1.052%1.05%-1.000000x-1.000000x4.328138x4.328138x4.33x0.375%0.37%1.623%1.62%-1.000000x-1.000000x3.129204x3.129204x3.13x1.585%1.59%4.960%4.96%1-1.000000x-1.000000x2.927208x2.927208x2.93x1.353%1.35%3.961%3.96%2-1.000000x-1.000000x2.631735x2.631735x2.63x0.722%0.72%1.899%1.90%3-1.000000x-1.000000x2.628013x2.628013x2.63x2.819%2.82%7.408%7.41%4-1.000000x-1.000000x2.571855x2.571855x2.57x2.645%2.64%6.802%6.80%5-1.000000x-1.000000x2.519338x2.519338x2.52x1.531%1.53%3.858%3.86%6-1.000000x-1.000000x2.492011x2.492011x2.49x0.802%0.80%1.999%2.00%7-1.000000x-1.000000x2.351130x2.351130x2.35x3.588%3.59%8.437%8.44%8-1.000000x-1.000000x2.345235x2.345235x2.35x6.743%6.74%15.813%15.8%9-1.000000x-1.000000x2.320788x2.320788x2.32x0.952%0.95%2.209%2.21%10-1.000000x-1.000000x2.236989x2.236989x2.24x0.541%0.54%1.209%1.21%11-1.000000x-1.000000x2.147202x2.147202x2.15x0.747%0.75%1.604%1.60%12-1.000000x-1.000000x2.134058x2.134058x2.13x1.646%1.65%3.514%3.51%13-1.000000x-1.000000x2.050517x2.050517x2.05x6.177%6.18%12.666%12.7%14-1.000000x-1.000000x2.006236x2.006236x2.01x1.188%1.19%2.383%2.38%15-1.000000x-1.000000x2.005610x2.005610x2.01x1.223%1.22%2.453%2.45%16-1.000000x-1.000000x1.994529x1.994529x1.99x3.154%3.15%6.290%6.29%17-1.000000x-1.000000x1.957848x1.957848x1.96x1.658%1.66%3.247%3.25%18-1.000000x-1.000000x1.808864x1.808864x1.81x5.081%5.08%9.190%9.19%19-1.000000x-1.000000x1.806537x1.806537x1.81x2.381%2.38%4.302%4.30%20-1.000000x-1.000000x1.786228x1.786228x1.79x2.083%2.08%3.720%3.72%21-1.000000x-1.000000x1.747870x1.747870x1.75x1.115%1.12%1.949%1.95%22-1.000000x-1.000000x1.733790x1.733790x1.73x2.062%2.06%3.574%3.57%23-1.000000x-1.000000x1.728996x1.728996x1.73x1.083%1.08%1.873%1.87%24-1.000000x-1.000000x1.720824x1.720824x1.72x1.386%1.39%2.385%2.38%-1.000000x-1.000000x1.706236x1.706236x1.71x2.810%2.81%4.794%4.79%25-1.000000x-1.000000x1.693783x1.693783x1.69x0.936%0.94%1.585%1.59%26-1.000000x-1.000000x1.663311x1.663311x1.66x6.193%6.19%10.301%10.3%27-1.000000x-1.000000x1.632200x1.632200x1.63x0.991%0.99%1.617%1.62%28-1.000000x-1.000000x1.597848x1.597848x1.60x2.216%2.22%3.541%3.54%-1.000000x-1.000000x1.589934x1.589934x1.59x2.251%2.25%3.579%3.58%-1.000000x-1.000000x1.576114x1.576114x1.58x2.109%2.11%3.323%3.32%-1.000000x-1.000000x1.557391x1.557391x1.56x1.833%1.83%2.855%2.85%29-1.000000x-1.000000x1.550147x1.550147x1.55x1.851%1.85%2.870%2.87%30-1.000000x-1.000000x1.526215x1.526215x1.53x2.660%2.66%4.060%4.06%-1.000000x-1.000000x1.516809x1.516809x1.52x1.222%1.22%1.853%1.85%31-1.000000x-1.000000x1.494707x1.494707x1.49x0.918%0.92%1.372%1.37%32-1.000000x-1.000000x1.475485x1.475485x1.48x2.501%2.50%3.691%3.69%33-1.000000x-1.000000x1.473120x1.473120x1.47x3.888%3.89%5.727%5.73%34-1.000000x-1.000000x1.458132x1.458132x1.46x0.734%0.73%1.070%1.07%35-1.000000x-1.000000x1.452651x1.452651x1.45x8.299%8.30%12.055%12.1%36-1.000000x-1.000000x1.388151x1.388151x1.39x2.789%2.79%3.872%3.87%37-1.000000x-1.000000x1.387878x1.387878x1.39x7.705%7.70%10.693%10.7%38-1.000000x-1.000000x1.368590x1.368590x1.37x1.742%1.74%2.385%2.38%39-1.000000x-1.000000x1.363936x1.363936x1.36x2.638%2.64%3.598%3.60%40-1.000000x-1.000000x1.256412x1.256412x1.26x2.128%2.13%2.674%2.67%41-1.000000x-1.000000x1.229981x1.229981x1.23x1.588%1.59%1.953%1.95%42-1.000000x-1.000000x1.211592x1.211592x1.21x2.722%2.72%3.299%3.30%43-1.000000x-1.000000x1.195990x1.195990x1.20x2.002%2.00%2.394%2.39%44-1.000000x-1.000000x1.084340x1.084340x1.08x1.032%1.03%1.119%1.12%-1.000000x-1.000000x1.068496x1.068496x1.07x4.087%4.09%4.367%4.37%45-1.000000x-1.000000x1.014900x1.014900x1.01x1.677%1.68%1.702%1.70%46-1.000000x-1.000000x1.008002x1.008002x1.01x2.236%2.24%2.254%2.25%47-1.050708x-1.050708x1.05x1.000000x1.000000x0.236%0.24%0.224%0.22%-1.098352x-1.098352x1.10x1.000000x1.000000x1.951%1.95%1.776%1.78%48-1.142247x-1.142247x1.14x1.000000x1.000000x1.927%1.93%1.687%1.69%49-1.623043x-1.623043x1.62x1.000000x1.000000x0.961%0.96%0.592%0.59%50-10.000000x-10.000000x> 10.0x1.000000x1.000000x1.156%1.16%0.000%0%-10.000000x-10.000000x> 10.0x1.000000x1.000000x1.156%1.16%0.000%0%
F percentage of females in category
M percentage of males in category
# rank of county subdivision out of 50 by male-to-female sex ratio

Educational Attainment by County Subdivision in the Midwest

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

No H.S. Diploma by County Subdivision#25

Percent of population 25 years of age and older without a high school diploma (or equivalent).
Scope: population of Lena, selected other county subdivisions in the Midwest, and entities that contain Lena
0%10%20%30%Count#Aurora TownshipAuroraCenter TownshipCtrKansas CityClevelandWayne TownshipWayneDetroitMilwaukeeNorth TownshipNDaytonChicagoProviso TownshipProvisoRockford TownshipRockfordSt. LouisWarrenGrand RapidsToledoBlue TownshipCincinnatiAkronSt. PaulSterling HeightsSterling HtsUnited States of AmericaUnited StatesThornton TownshipThorntonWichitaLenaLenaKaw TownshipOmahaBloomingdale TownshipBloomingdaleLena School DistrictLenaColumbusMaine TownshipMaineTopekaMinneapolis100800Tract 100800Springfield TownshipSpringfieldEast North CentralWorth TownshipWorthZIP Code 54139ZIP 54139MidwestLawrence TownshipLawrenceSioux FallsOconto CountyOcontoGreen Bay Metro AreaGreen BayWisconsinCapital TownshipCapitalWheeling TownshipWheelingPalatine TownshipPalatineSchaumburg TownshipSchaumburgLincolnWashington TownshipWashingtonOlatheFargoCedar RapidsYork TownshipMilton TownshipMiltonMadisonDowners Grove TownshipDowners GrvLisle TownshipLisleOverland ParkAnn Arbor33.464284%33.464284%33.5%29,81429.8k123.165532%23.165532%23.2%22,92622.9k222.659362%22.659362%22.7%21,21821.2k321.582420%21.582420%21.6%54,98155.0k421.037720%21.037720%21.0%18,48918.5k521.003600%21.003600%21.0%90,67890.7k617.485105%17.485105%17.5%63,80063.8k717.062713%17.062713%17.1%17,39117.4k816.928359%16.928359%16.9%14,88914.9k916.905373%16.905373%16.9%309,770310k1015.636222%15.636222%15.6%16,11016.1k1115.608074%15.608074%15.6%18,24118.2k1215.466266%15.466266%15.5%33,80433.8k1315.286174%15.286174%15.3%14,05914.1k1414.563179%14.563179%14.6%17,64317.6k1514.332972%14.332972%14.3%26,34326.3k1614.241047%14.241047%14.2%15,25815.3k1713.761583%13.761583%13.8%26,28626.3k1813.591726%13.591726%13.6%17,95118.0k1913.278342%13.278342%13.3%24,61324.6k2013.132171%13.132171%13.1%12,21212.2k2113.020590%13.020590%13.0%27,818,38027.8M12.974232%12.974232%13.0%14,37014.4k2212.568464%12.568464%12.6%31,23131.2k2312.466125%12.466125%12.5%4612.466125%12.466125%12.5%4612.455744%12.455744%12.5%15,16315.2k2412.198899%12.198899%12.2%35,05035.1k2512.171847%12.171847%12.2%9,3752612.044199%12.044199%12.0%21811.376979%11.376979%11.4%60,83160.8k2711.132206%11.132206%11.1%10,96511.0k2811.032803%11.032803%11.0%9,3772910.958428%10.958428%11.0%29,34729.3k3010.810811%10.810811%10.8%18810.767091%10.767091%10.8%11,14911.1k3110.719464%10.719464%10.7%3,363,7843.36M10.678962%10.678962%10.7%11,17511.2k3210.321716%10.321716%10.3%23110.244520%10.244520%10.2%4,641,8354.64M10.179618%10.179618%10.2%8,161339.702326%9.702326%9.7%9,123349.607260%9.607260%9.6%2,6158.685969%8.685969%8.7%18,36918.4k8.637220%8.637220%8.6%336,096336k8.623103%8.623103%8.6%6,837358.424707%8.424707%8.4%9,343368.392669%8.392669%8.4%6,695377.739434%7.739434%7.7%7,226387.092309%7.092309%7.1%11,88611.9k396.804680%6.804680%6.8%6,403406.424130%6.424130%6.4%5,331416.055621%6.055621%6.1%4,270425.981653%5.981653%6.0%5,099435.461095%5.461095%5.5%4,715445.266517%5.266517%5.3%4,126454.836248%4.836248%4.8%7,351464.020265%4.020265%4.0%4,166473.522812%3.522812%3.5%2,870483.377424%3.377424%3.4%4,282493.157717%3.157717%3.2%2,05750
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older without a high school diploma (or equivalent).

Bachelor's Degrees by County Subdivision#26

Percent of population 25 years of age and older with a bachelor's degree or higher..
Scope: population of Lena, selected other county subdivisions in the Midwest, and entities that contain Lena
0%20%40%60%Count#Ann ArborOverland ParkMilton TownshipMiltonLisle TownshipLisleMadisonDowners Grove TownshipDowners GrvWashington TownshipWashingtonPalatine TownshipPalatineYork TownshipMinneapolisOlatheWheeling TownshipWheelingSchaumburg TownshipSchaumburgKaw TownshipSt. PaulMaine TownshipMaineFargoLincolnLawrence TownshipLawrenceChicagoCapital TownshipCapitalColumbusOmahaCincinnatiSt. LouisGrand RapidsBloomingdale TownshipBloomingdaleCedar RapidsUnited States of AmericaUnited StatesSioux FallsMidwestWichitaEast North CentralWisconsinSterling HeightsSterling HtsTopekaSpringfield TownshipSpringfieldProviso TownshipProvisoGreen Bay Metro AreaGreen BayWorth TownshipWorthMilwaukeeRockford TownshipRockfordAkronCenter TownshipCtrNorth TownshipNThornton TownshipThorntonToledoDaytonWarrenWayne TownshipWayneOconto CountyOcontoKansas CityClevelandAurora TownshipAuroraBlue TownshipDetroitZIP Code 54139ZIP 54139Lena School DistrictLena100800Tract 100800LenaLena72.810169%72.810169%72.8%47,43047.4k158.823344%58.823344%58.8%74,57874.6k257.681507%57.681507%57.7%45,19045.2k356.900171%56.900171%56.9%46,35646.4k456.337583%56.337583%56.3%85,63285.6k553.762123%53.762123%53.8%55,71155.7k650.610540%50.610540%50.6%47,62347.6k749.860853%49.860853%49.9%39,77539.8k849.728972%49.728972%49.7%42,93542.9k947.670489%47.670489%47.7%127,663128k1046.512581%46.512581%46.5%38,59838.6k1146.409378%46.409378%46.4%51,46851.5k1241.792515%41.792515%41.8%39,02039.0k1341.581304%41.581304%41.6%50,61950.6k1439.969357%39.969357%40.0%74,08874.1k1539.511462%39.511462%39.5%38,91838.9k1638.241175%38.241175%38.2%26,96527.0k1737.146608%37.146608%37.1%62,25462.3k1836.577273%36.577273%36.6%29,32429.3k1936.546320%36.546320%36.5%669,666670k2036.298510%36.298510%36.3%28,78028.8k2134.685843%34.685843%34.7%185,460185k2234.651487%34.651487%34.7%99,56199.6k2333.783048%33.783048%33.8%64,52964.5k2433.007421%33.007421%33.0%72,14372.1k2532.904381%32.904381%32.9%39,86339.9k2632.623147%32.623147%32.6%25,12725.1k2731.793440%31.793440%31.8%27,10227.1k2830.315023%30.315023%30.3%64,767,78764.8M30.259813%30.259813%30.3%28,45328.5k2928.952816%28.952816%29.0%13,118,64213.1M28.877567%28.877567%28.9%71,75771.8k3028.462853%28.462853%28.5%8,931,6868.93M28.373439%28.373439%28.4%1,104,0821.10M27.532180%27.532180%27.5%25,60325.6k3127.007248%27.007248%27.0%22,95423.0k3226.964567%26.964567%27.0%27,92127.9k3326.237989%26.237989%26.2%27,03327.0k3425.916521%25.916521%25.9%54,80854.8k25.217641%25.217641%25.2%26,38926.4k3523.517740%23.517740%23.5%85,81285.8k3621.592552%21.592552%21.6%25,23525.2k3720.213821%20.213821%20.2%26,69726.7k3820.139240%20.139240%20.1%19,93119.9k3919.650916%19.650916%19.7%20,02920.0k4018.971090%18.971090%19.0%21,01221.0k4118.048021%18.048021%18.0%33,17133.2k4217.635555%17.635555%17.6%15,51115.5k4317.280259%17.280259%17.3%15,89315.9k4416.826535%16.826535%16.8%14,78814.8k4516.194570%16.194570%16.2%4,40816.167409%16.167409%16.2%15,13915.1k4616.073076%16.073076%16.1%40,94640.9k4715.929601%15.929601%15.9%14,19214.2k4815.821208%15.821208%15.8%16,95117.0k4913.833543%13.833543%13.8%59,72359.7k5013.538874%13.538874%13.5%30312.265193%12.265193%12.3%22210.523289%10.523289%10.5%1836.775068%6.775068%6.8%256.775068%6.775068%6.8%25
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older with a bachelor's degree or higher..

Very Advanced Degrees by County Subdivision#27

Percent of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).
Scope: population of Lena, selected other county subdivisions in the Midwest, and entities that contain Lena
0%5%10%15%Count#Ann ArborMadisonDowners Grove TownshipDowners GrvWashington TownshipWashingtonMinneapolisYork TownshipOverland ParkLisle TownshipLisleSt. PaulKaw TownshipMilton TownshipMiltonSt. LouisCincinnatiLincolnChicagoFargoCapital TownshipCapitalOmahaMaine TownshipMainePalatine TownshipPalatineWheeling TownshipWheelingColumbusUnited States of AmericaUnited StatesTopekaGrand RapidsLawrence TownshipLawrenceSpringfield TownshipSpringfieldCedar RapidsMidwestEast North CentralSioux FallsOlatheWisconsinCenter TownshipCtrSchaumburg TownshipSchaumburgWichitaProviso TownshipProvisoAkronBloomingdale TownshipBloomingdaleRockford TownshipRockfordMilwaukeeWorth TownshipWorthClevelandGreen Bay Metro AreaGreen BayToledoNorth TownshipNSterling HeightsSterling HtsKansas CityDetroitDaytonWayne TownshipWayneOconto CountyOcontoWarrenZIP Code 54139ZIP 54139Blue TownshipAurora TownshipAuroraThornton TownshipThorntonLena School DistrictLenaLenaLena100800Tract 10080017.877867%17.877867%17.9%11,64611.6k19.171173%9.171173%9.2%13,94013.9k27.658384%7.658384%7.7%7,93637.306290%7.306290%7.3%6,87546.241155%6.241155%6.2%16,71416.7k56.197734%6.197734%6.2%5,35165.940071%5.940071%5.9%7,53175.933545%5.933545%5.9%4,83485.920847%5.920847%5.9%10,97511.0k95.896414%5.896414%5.9%7,178105.800061%5.800061%5.8%4,544114.880448%4.880448%4.9%10,66710.7k124.729595%4.729595%4.7%9,034134.568292%4.568292%4.6%7,656144.485379%4.485379%4.5%82,18982.2k154.336789%4.336789%4.3%3,058164.233985%4.233985%4.2%3,357174.059919%4.059919%4.1%11,66511.7k184.030539%4.030539%4.0%3,970193.487439%3.487439%3.5%2,782203.407574%3.407574%3.4%3,779213.357865%3.357865%3.4%17,95418.0k223.336158%3.336158%3.3%7,127,6737.13M3.233245%3.233245%3.2%2,748233.174629%3.174629%3.2%3,846243.083448%3.083448%3.1%2,472252.911721%2.911721%2.9%3,015262.905776%2.905776%2.9%2,477272.893416%2.893416%2.9%1,311,0191.31M2.855432%2.855432%2.9%896,039896k2.841677%2.841677%2.8%2,672282.830666%2.830666%2.8%2,349292.703886%2.703886%2.7%105,215105k2.602914%2.602914%2.6%2,576302.551250%2.551250%2.6%2,382312.519246%2.519246%2.5%6,260322.213918%2.213918%2.2%2,281332.163955%2.163955%2.2%2,858342.113682%2.113682%2.1%1,628352.067272%2.067272%2.1%2,416362.043126%2.043126%2.0%7,455371.958049%1.958049%2.0%2,049381.927780%1.927780%1.9%4,911391.879146%1.879146%1.9%3,9741.642065%1.642065%1.6%3,018401.575684%1.575684%1.6%1,606411.439893%1.439893%1.4%1,339421.388310%1.388310%1.4%1,300431.318660%1.318660%1.3%5,693441.257490%1.257490%1.3%1,106451.183365%1.183365%1.2%1,040461.076454%1.076454%1.1%2931.047058%1.047058%1.0%963471.027703%1.027703%1.0%230.997751%0.997751%1.0%1,069480.936111%0.936111%0.9%834490.876686%0.876686%0.9%971500.662983%0.662983%0.7%120.542005%0.542005%0.5%20.542005%0.542005%0.5%20.230017%0.230017%0.2%4
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).

Under-Education Sex Ratio by County Subdivision#28

Percentage more likely men are than women to not have a high school diploma (or equivalent) among people aged 25 years and older.
Scope: population of Lena, selected other county subdivisions in the Midwest, and entities that contain Lena
Female
Male
1x0x1xFM#ZIP 54139LenaOcontoTract 100800Green BayCedar RapidsLincolnDetroitOmahaToledoWisconsinThorntonKansas CityMadisonLawrenceFargoProvisoRockfordBlue TownshipWayneMidwestTopekaEast North CentralMilwaukeeKaw TownshipDaytonSioux FallsUnited StatesOlatheWorthNOverland ParkAuroraWheelingGrand RapidsSchaumburgChicagoWichitaColumbusClevelandPalatineCapitalWarrenSpringfieldYork TownshipSt. LouisWashingtonBloomingdaleCtrCincinnatiAkronAnn ArborSt. PaulLisleMinneapolisSterling HtsDowners GrvMiltonMaineLenaLena-1.000000x-1.000000x1.719865x1.719865x1.72x7.498%7.50%12.895%12.9%-1.000000x-1.000000x1.440914x1.440914x1.44x9.779%9.78%14.090%14.1%-1.000000x-1.000000x1.374304x1.374304x1.37x8.070%8.07%11.091%11.1%-1.000000x-1.000000x1.284848x1.284848x1.28x9.434%9.43%12.121%12.1%-1.000000x-1.000000x1.245810x1.245810x1.25x7.746%7.75%9.650%9.65%-1.000000x-1.000000x1.243824x1.243824x1.24x5.354%5.35%6.660%6.66%1-1.000000x-1.000000x1.238529x1.238529x1.24x6.342%6.34%7.854%7.85%2-1.000000x-1.000000x1.237056x1.237056x1.24x18.951%19.0%23.443%23.4%3-1.000000x-1.000000x1.230289x1.230289x1.23x10.968%11.0%13.494%13.5%4-1.000000x-1.000000x1.227011x1.227011x1.23x12.945%12.9%15.884%15.9%5-1.000000x-1.000000x1.219291x1.219291x1.22x7.799%7.80%9.509%9.51%-1.000000x-1.000000x1.203250x1.203250x1.20x11.909%11.9%14.330%14.3%6-1.000000x-1.000000x1.189752x1.189752x1.19x20.748%20.7%24.685%24.7%7-1.000000x-1.000000x1.189278x1.189278x1.19x4.425%4.43%5.263%5.26%8-1.000000x-1.000000x1.181964x1.181964x1.18x9.406%9.41%11.117%11.1%9-1.000000x-1.000000x1.176963x1.176963x1.18x5.565%5.56%6.550%6.55%10-1.000000x-1.000000x1.174964x1.174964x1.17x14.460%14.5%16.990%17.0%11-1.000000x-1.000000x1.168755x1.168755x1.17x14.456%14.5%16.896%16.9%12-1.000000x-1.000000x1.161774x1.161774x1.16x13.244%13.2%15.387%15.4%13-1.000000x-1.000000x1.132245x1.132245x1.13x19.779%19.8%22.395%22.4%14-1.000000x-1.000000x1.127915x1.127915x1.13x9.647%9.65%10.881%10.9%-1.000000x-1.000000x1.125507x1.125507x1.13x10.423%10.4%11.732%11.7%15-1.000000x-1.000000x1.125371x1.125371x1.13x10.108%10.1%11.375%11.4%-1.000000x-1.000000x1.123984x1.123984x1.12x16.526%16.5%18.574%18.6%16-1.000000x-1.000000x1.115695x1.115695x1.12x11.779%11.8%13.142%13.1%17-1.000000x-1.000000x1.114342x1.114342x1.11x16.070%16.1%17.907%17.9%18-1.000000x-1.000000x1.110589x1.110589x1.11x9.201%9.20%10.219%10.2%19-1.000000x-1.000000x1.109070x1.109070x1.11x12.369%12.4%13.719%13.7%-1.000000x-1.000000x1.107847x1.107847x1.11x6.105%6.11%6.764%6.76%20-1.000000x-1.000000x1.099747x1.099747x1.10x10.199%10.2%11.216%11.2%21-1.000000x-1.000000x1.096598x1.096598x1.10x16.317%16.3%17.894%17.9%22-1.000000x-1.000000x1.095440x1.095440x1.10x3.232%3.23%3.540%3.54%23-1.000000x-1.000000x1.086583x1.086583x1.09x32.102%32.1%34.882%34.9%24-1.000000x-1.000000x1.079846x1.079846x1.08x8.111%8.11%8.758%8.76%25-1.000000x-1.000000x1.078480x1.078480x1.08x14.031%14.0%15.132%15.1%26-1.000000x-1.000000x1.077209x1.077209x1.08x7.467%7.47%8.043%8.04%27-1.000000x-1.000000x1.068021x1.068021x1.07x16.372%16.4%17.486%17.5%28-1.000000x-1.000000x1.059528x1.059528x1.06x12.215%12.2%12.942%12.9%29-1.000000x-1.000000x1.052237x1.052237x1.05x11.098%11.1%11.678%11.7%30-1.000000x-1.000000x1.046686x1.046686x1.05x21.119%21.1%22.105%22.1%31-1.000000x-1.000000x1.039581x1.039581x1.04x8.233%8.23%8.559%8.56%32-1.000000x-1.000000x1.039194x1.039194x1.04x8.470%8.47%8.802%8.80%33-1.000000x-1.000000x1.037373x1.037373x1.04x15.022%15.0%15.584%15.6%34-1.000000x-1.000000x1.028857x1.028857x1.03x10.622%10.6%10.928%10.9%35-1.000000x-1.000000x1.027464x1.027464x1.03x5.391%5.39%5.539%5.54%36-1.000000x-1.000000x1.018183x1.018183x1.02x15.334%15.3%15.613%15.6%37-1.000000x-1.000000x1.013146x1.013146x1.01x6.764%6.76%6.853%6.85%38-1.000000x-1.000000x1.007207x1.007207x1.01x12.130%12.1%12.217%12.2%39-1.000000x-1.000000x1.006204x1.006204x1.01x23.095%23.1%23.239%23.2%40-1.000000x-1.000000x1.001229x1.001229x1.00x13.754%13.8%13.771%13.8%41-1.001506x-1.001506x1.00x1.000000x1.000000x13.601%13.6%13.581%13.6%42-1.031649x-1.031649x1.03x1.000000x1.000000x3.205%3.21%3.107%3.11%43-1.060004x-1.060004x1.06x1.000000x1.000000x13.651%13.7%12.879%12.9%44-1.073696x-1.073696x1.07x1.000000x1.000000x3.642%3.64%3.392%3.39%45-1.092939x-1.092939x1.09x1.000000x1.000000x11.450%11.4%10.476%10.5%46-1.131063x-1.131063x1.13x1.000000x1.000000x13.912%13.9%12.300%12.3%47-1.140051x-1.140051x1.14x1.000000x1.000000x4.269%4.27%3.744%3.74%48-1.194783x-1.194783x1.19x1.000000x1.000000x5.710%5.71%4.779%4.78%49-1.208375x-1.208375x1.21x1.000000x1.000000x12.117%12.1%10.027%10.0%50-1.932676x-1.932676x1.93x1.000000x1.000000x16.763%16.8%8.673%8.67%-1.932676x-1.932676x1.93x1.000000x1.000000x16.763%16.8%8.673%8.67%
F percentage of females in category
M percentage of males in category
# rank of county subdivision out of 50 by male-to-female sex ratio

Over-Education Sex Ratio by County Subdivision#29

Percentage more likely men are than women to have a professional or doctorate degree (e.g., MBA, PhD, or MD) among people aged 25 years and older.
Scope: population of Lena, selected other county subdivisions in the Midwest, and entities that contain Lena
Female
Male
10x5x0xFM#LenaZIP 54139RockfordNDaytonSioux FallsCapitalLawrenceDowners GrvAkronLisleWichitaYork TownshipMaineWarrenWheelingBlue TownshipSpringfieldOverland ParkGreen BayMiltonGrand RapidsOlatheOmahaFargoWashingtonEast North CentralLincolnMidwestBloomingdaleWisconsinKansas CityAuroraUnited StatesAnn ArborTopekaSterling HtsPalatineSchaumburgColumbusMadisonKaw TownshipMilwaukeeCedar RapidsClevelandCincinnatiSt. PaulSt. LouisChicagoWayneCtrToledoMinneapolisWorthOcontoDetroitProvisoTract 100800ThorntonLenaLena-1.000000x-1.000000x4.516299x4.516299x4.52x0.233%0.23%1.052%1.05%-1.000000x-1.000000x4.328138x4.328138x4.33x0.375%0.37%1.623%1.62%-1.000000x-1.000000x2.117268x2.117268x2.12x1.353%1.35%2.866%2.87%1-1.000000x-1.000000x2.111054x2.111054x2.11x1.033%1.03%2.181%2.18%2-1.000000x-1.000000x1.989047x1.989047x1.99x0.860%0.86%1.711%1.71%3-1.000000x-1.000000x1.962539x1.962539x1.96x1.928%1.93%3.783%3.78%4-1.000000x-1.000000x1.901348x1.901348x1.90x2.990%2.99%5.686%5.69%5-1.000000x-1.000000x1.879271x1.879271x1.88x2.206%2.21%4.146%4.15%6-1.000000x-1.000000x1.852471x1.852471x1.85x5.456%5.46%10.107%10.1%7-1.000000x-1.000000x1.846298x1.846298x1.85x1.550%1.55%2.862%2.86%8-1.000000x-1.000000x1.815266x1.815266x1.82x4.271%4.27%7.754%7.75%9-1.000000x-1.000000x1.792728x1.792728x1.79x1.819%1.82%3.261%3.26%10-1.000000x-1.000000x1.792314x1.792314x1.79x4.498%4.50%8.062%8.06%11-1.000000x-1.000000x1.788417x1.788417x1.79x2.939%2.94%5.256%5.26%12-1.000000x-1.000000x1.768853x1.768853x1.77x0.769%0.77%1.361%1.36%13-1.000000x-1.000000x1.766097x1.766097x1.77x2.485%2.48%4.389%4.39%14-1.000000x-1.000000x1.761699x1.761699x1.76x0.737%0.74%1.298%1.30%15-1.000000x-1.000000x1.751445x1.751445x1.75x2.146%2.15%3.759%3.76%16-1.000000x-1.000000x1.732234x1.732234x1.73x4.415%4.41%7.647%7.65%17-1.000000x-1.000000x1.720824x1.720824x1.72x1.386%1.39%2.385%2.38%-1.000000x-1.000000x1.695067x1.695067x1.70x4.357%4.36%7.385%7.38%18-1.000000x-1.000000x1.689013x1.689013x1.69x2.382%2.38%4.023%4.02%19-1.000000x-1.000000x1.678153x1.678153x1.68x2.131%2.13%3.576%3.58%20-1.000000x-1.000000x1.669388x1.669388x1.67x3.061%3.06%5.110%5.11%21-1.000000x-1.000000x1.627456x1.627456x1.63x3.304%3.30%5.377%5.38%22-1.000000x-1.000000x1.610803x1.610803x1.61x5.701%5.70%9.183%9.18%23-1.000000x-1.000000x1.597848x1.597848x1.60x2.216%2.22%3.541%3.54%-1.000000x-1.000000x1.596978x1.596978x1.60x3.524%3.52%5.628%5.63%24-1.000000x-1.000000x1.589934x1.589934x1.59x2.251%2.25%3.579%3.58%-1.000000x-1.000000x1.586045x1.586045x1.59x1.649%1.65%2.616%2.62%25-1.000000x-1.000000x1.576114x1.576114x1.58x2.109%2.11%3.323%3.32%-1.000000x-1.000000x1.570028x1.570028x1.57x1.087%1.09%1.707%1.71%26-1.000000x-1.000000x1.550495x1.550495x1.55x0.737%0.74%1.143%1.14%27-1.000000x-1.000000x1.526215x1.526215x1.53x2.660%2.66%4.060%4.06%-1.000000x-1.000000x1.522839x1.522839x1.52x14.269%14.3%21.730%21.7%28-1.000000x-1.000000x1.481288x1.481288x1.48x2.641%2.64%3.912%3.91%29-1.000000x-1.000000x1.476996x1.476996x1.48x1.170%1.17%1.728%1.73%30-1.000000x-1.000000x1.457167x1.457167x1.46x2.851%2.85%4.154%4.15%31-1.000000x-1.000000x1.436165x1.436165x1.44x2.115%2.11%3.037%3.04%32-1.000000x-1.000000x1.413654x1.413654x1.41x2.801%2.80%3.959%3.96%33-1.000000x-1.000000x1.387878x1.387878x1.39x7.705%7.70%10.693%10.7%34-1.000000x-1.000000x1.373250x1.373250x1.37x4.975%4.97%6.832%6.83%35-1.000000x-1.000000x1.368590x1.368590x1.37x1.742%1.74%2.385%2.38%36-1.000000x-1.000000x1.346658x1.346658x1.35x2.491%2.49%3.354%3.35%37-1.000000x-1.000000x1.286599x1.286599x1.29x1.699%1.70%2.186%2.19%38-1.000000x-1.000000x1.280610x1.280610x1.28x4.179%4.18%5.351%5.35%39-1.000000x-1.000000x1.274509x1.274509x1.27x5.228%5.23%6.663%6.66%40-1.000000x-1.000000x1.273345x1.273345x1.27x4.319%4.32%5.500%5.50%41-1.000000x-1.000000x1.238186x1.238186x1.24x4.026%4.03%4.985%4.99%42-1.000000x-1.000000x1.223931x1.223931x1.22x1.068%1.07%1.307%1.31%43-1.000000x-1.000000x1.213574x1.213574x1.21x2.357%2.36%2.860%2.86%44-1.000000x-1.000000x1.141406x1.141406x1.14x1.539%1.54%1.757%1.76%45-1.000000x-1.000000x1.124528x1.124528x1.12x5.872%5.87%6.603%6.60%46-1.000000x-1.000000x1.084697x1.084697x1.08x1.883%1.88%2.042%2.04%47-1.000000x-1.000000x1.084340x1.084340x1.08x1.032%1.03%1.119%1.12%-1.000000x-1.000000x1.046557x1.046557x1.05x1.291%1.29%1.351%1.35%48-1.000000x-1.000000x1.042857x1.042857x1.04x2.171%2.17%2.264%2.26%49-1.050708x-1.050708x1.05x1.000000x1.000000x0.236%0.24%0.224%0.22%-1.706858x-1.706858x1.71x1.000000x1.000000x1.072%1.07%0.628%0.63%50-10.000000x-10.000000x> 10.0x1.000000x1.000000x1.156%1.16%0.000%0%-10.000000x-10.000000x> 10.0x1.000000x1.000000x1.156%1.16%0.000%0%
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 Lena to the 50 most populous county subdivisions in the United States and to those entities that contain or substantially overlap with Lena. The least populous of the compared county subdivisions has a population of 547,300.

No H.S. Diploma by County Subdivision#30

Percent of population 25 years of age and older without a high school diploma (or equivalent).
Scope: population of Lena, selected other county subdivisions in the United States, and entities that contain Lena
0%10%20%Count#San Antonio CentralSan Antonio CntrlBronxSan BernardinoLos AngelesSouthwest DallasSW DallasEl PasoAnaheim-Santa Ana-Garden GroveAnaheim-Santa An…FresnoHoustonMiamiDetroitNortheast DallasNE DallasEast San Gabriel ValleyE San Gabriel VlyFort WorthBrooklynLong Beach-LakewoodLong Bch-LakewoodQueensSan Fernando ValleySan Fernando VlyMilwaukeePhiladelphiaOntarioChicagoBaltimoreOceanside-EscondidoOceanside-Escond…Las VegasPhoenixBostonSacramentoOrlandoAustinDenverUnited States of AmericaUnited StatesManhattanSan DiegoTampaSan JoseSan FranciscoLenaLenaTucsonAlbuquerqueLena School DistrictLenaTownship 1:Charlotte1, CharlotteColumbusTulsa100800Tract 100800East North CentralSalt Lake CitySalt Lk CityTown of HempsteadHempsteadZIP Code 54139ZIP 54139MidwestNorthwest HarrisNW HarrisWashingtonOconto CountyOcontoAtlantaSeattleGreen Bay Metro AreaGreen BayWisconsinNortheast TarrantNE TarrantPlanoSeattle East28.998944%28.998944%29.0%126,922127k128.837398%28.837398%28.8%261,022261k227.582802%27.582802%27.6%135,754136k324.837401%24.837401%24.8%434,160434k423.987048%23.987048%24.0%141,940142k523.756417%23.756417%23.8%81,30881.3k622.645542%22.645542%22.6%248,699249k722.107626%22.107626%22.1%92,47292.5k821.922900%21.922900%21.9%457,347457k921.818150%21.818150%21.8%149,688150k1021.003600%21.003600%21.0%90,67890.7k1120.783651%20.783651%20.8%207,494207k1220.461493%20.461493%20.5%128,038128k1320.041576%20.041576%20.0%106,726107k1420.017506%20.017506%20.0%351,046351k1519.402518%19.402518%19.4%73,10573.1k1619.344706%19.344706%19.3%315,505316k1719.344408%19.344408%19.3%244,983245k1817.485105%17.485105%17.5%63,80063.8k1917.390838%17.390838%17.4%180,039180k2017.129346%17.129346%17.1%71,39771.4k2116.905373%16.905373%16.9%309,770310k2216.548703%16.548703%16.5%69,83969.8k2315.999398%15.999398%16.0%70,21470.2k2415.906523%15.906523%15.9%198,651199k2514.952077%14.952077%15.0%308,569309k2614.325556%14.325556%14.3%63,64263.6k2713.900512%13.900512%13.9%103,047103k2813.679368%13.679368%13.7%53,75853.8k2913.668915%13.668915%13.7%78,23878.2k3013.638703%13.638703%13.6%63,86563.9k3113.020590%13.020590%13.0%27,818,38027.8M12.996284%12.996284%13.0%160,845161k3212.985760%12.985760%13.0%206,792207k3312.979618%12.979618%13.0%57,75857.8k3412.789590%12.789590%12.8%153,604154k3512.559735%12.559735%12.6%84,02484.0k3612.466125%12.466125%12.5%4612.466125%12.466125%12.5%4612.262851%12.262851%12.3%70,40970.4k3712.089143%12.089143%12.1%52,21752.2k3812.044199%12.044199%12.0%21811.553484%11.553484%11.6%61,37861.4k3911.376979%11.376979%11.4%60,83160.8k4011.299086%11.299086%11.3%43,65343.7k4110.810811%10.810811%10.8%18810.719464%10.719464%10.7%3,363,7843.36M10.435356%10.435356%10.4%64,29464.3k4210.384134%10.384134%10.4%54,23054.2k4310.321716%10.321716%10.3%23110.244520%10.244520%10.2%4,641,8354.64M10.135583%10.135583%10.1%47,67947.7k4410.045421%10.045421%10.0%46,51046.5k459.607260%9.607260%9.6%2,6159.538552%9.538552%9.5%37,37337.4k468.833573%8.833573%8.8%66,22066.2k478.685969%8.685969%8.7%18,36918.4k8.637220%8.637220%8.6%336,096336k8.418271%8.418271%8.4%31,44331.4k485.714681%5.714681%5.7%20,64420.6k494.913852%4.913852%4.9%20,32620.3k50
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older without a high school diploma (or equivalent).

Bachelor's Degrees by County Subdivision#31

Percent of population 25 years of age and older with a bachelor's degree or higher..
Scope: population of Lena, selected other county subdivisions in the United States, and entities that contain Lena
0%20%40%60%Count#ManhattanSeattle EastWashingtonSan FranciscoPlanoSan JoseAtlantaSeattleBostonDenverAustinTownship 1:Charlotte1, CharlotteTown of HempsteadHempsteadSan DiegoNortheast TarrantNE TarrantNorthwest HarrisNW HarrisChicagoColumbusLos AngelesBrooklynSan Fernando ValleySan Fernando VlyNortheast DallasNE DallasSalt Lake CitySalt Lk CityAlbuquerqueTampaTucsonOceanside-EscondidoOceanside-Escond…TulsaQueensUnited States of AmericaUnited StatesHoustonBaltimoreLong Beach-LakewoodLong Bch-LakewoodMidwestPhoenixOrlandoEast North CentralAnaheim-Santa Ana-Garden GroveAnaheim-Santa An…WisconsinSacramentoEast San Gabriel ValleyE San Gabriel VlyOntarioPhiladelphiaMiamiGreen Bay Metro AreaGreen BayFort WorthSouthwest DallasSW DallasMilwaukeeFresnoLas VegasEl PasoBronxSan BernardinoOconto CountyOcontoSan Antonio CentralSan Antonio CntrlDetroitZIP Code 54139ZIP 54139Lena School DistrictLena100800Tract 100800LenaLena60.434640%60.434640%60.4%747,953748k157.691220%57.691220%57.7%238,638239k255.360186%55.360186%55.4%256,316256k354.793235%54.793235%54.8%366,564367k454.142756%54.142756%54.1%195,588196k549.985845%49.985845%50.0%600,334600k649.803731%49.803731%49.8%195,136195k749.626221%49.626221%49.6%372,018372k846.377869%46.377869%46.4%206,036206k945.718966%45.718966%45.7%214,085214k1044.843364%44.843364%44.8%256,674257k1141.989192%41.989192%42.0%223,068223k1238.767308%38.767308%38.8%202,458202k1338.701072%38.701072%38.7%616,296616k1438.547398%38.547398%38.5%143,978144k1536.877886%36.877886%36.9%173,478173k1636.546320%36.546320%36.5%669,666670k1734.685843%34.685843%34.7%185,460185k1834.593243%34.593243%34.6%604,693605k1934.081468%34.081468%34.1%597,685598k2033.231104%33.231104%33.2%420,848421k2133.191099%33.191099%33.2%331,364331k2233.118385%33.118385%33.1%204,048204k2332.636312%32.636312%32.6%140,967141k2432.512191%32.512191%32.5%144,676145k2532.087814%32.087814%32.1%184,237184k2631.198303%31.198303%31.2%136,915137k2731.110082%31.110082%31.1%120,191120k2830.595789%30.595789%30.6%499,006499k2930.315023%30.315023%30.3%64,767,78764.8M30.080133%30.080133%30.1%627,520628k3029.719611%29.719611%29.7%125,423125k3129.113198%29.113198%29.1%109,693110k3228.952816%28.952816%29.0%13,118,64213.1M28.760152%28.760152%28.8%593,529594k3328.535877%28.535877%28.5%112,142112k3428.462853%28.462853%28.5%8,931,6868.93M28.412939%28.412939%28.4%312,038312k3528.373439%28.373439%28.4%1,104,0821.10M28.231204%28.231204%28.2%209,283209k3627.276345%27.276345%27.3%170,682171k3726.758411%26.758411%26.8%111,532112k3826.349720%26.349720%26.3%272,786273k3926.011156%26.011156%26.0%178,455178k4025.916521%25.916521%25.9%54,80854.8k24.665414%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%173,169173k4716.375473%16.375473%16.4%80,59580.6k4816.194570%16.194570%16.2%4,40814.929012%14.929012%14.9%65,34165.3k4913.833543%13.833543%13.8%59,72359.7k5013.538874%13.538874%13.5%30312.265193%12.265193%12.3%22210.523289%10.523289%10.5%1836.775068%6.775068%6.8%256.775068%6.775068%6.8%25
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older with a bachelor's degree or higher..

Very Advanced Degrees by County Subdivision#32

Percent of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).
Scope: population of Lena, selected other county subdivisions in the United States, and entities that contain Lena
0%5%10%Count#WashingtonManhattanSan FranciscoBostonAtlantaSeattleSan JoseSeattle EastDenverSan DiegoAustinBaltimoreLos AngelesAlbuquerquePlanoChicagoTucsonTown of HempsteadHempsteadTampaMiamiNortheast DallasNE DallasSalt Lake CitySalt Lk CityHoustonPhiladelphiaSan Fernando ValleySan Fernando VlyTownship 1:Charlotte1, CharlotteOceanside-EscondidoOceanside-Escond…BrooklynSacramentoColumbusUnited States of AmericaUnited StatesTulsaPhoenixLong Beach-LakewoodLong Bch-LakewoodMidwestOrlandoEast North CentralFresnoAnaheim-Santa Ana-Garden GroveAnaheim-Santa An…QueensWisconsinNorthwest HarrisNW HarrisNortheast TarrantNE TarrantEast San Gabriel ValleyE San Gabriel VlyOntarioFort WorthLas VegasMilwaukeeGreen Bay Metro AreaGreen BaySan BernardinoSan Antonio CentralSan Antonio CntrlEl PasoSouthwest DallasSW DallasBronxDetroitOconto CountyOcontoZIP Code 54139ZIP 54139Lena School DistrictLenaLenaLena100800Tract 10080012.461852%12.461852%12.5%57,69857.7k110.788423%10.788423%10.8%133,520134k27.558053%7.558053%7.6%50,56350.6k37.340604%7.340604%7.3%32,61132.6k46.889819%6.889819%6.9%26,99527.0k56.641855%6.641855%6.6%49,79049.8k66.255912%6.255912%6.3%75,13475.1k76.036065%6.036065%6.0%24,96825.0k85.725842%5.725842%5.7%26,81226.8k95.247128%5.247128%5.2%83,55883.6k105.058711%5.058711%5.1%28,95529.0k114.934352%4.934352%4.9%20,82420.8k124.659072%4.659072%4.7%81,44181.4k134.631274%4.631274%4.6%20,00420.0k144.617088%4.617088%4.6%16,67916.7k154.485379%4.485379%4.5%82,18982.2k164.461087%4.461087%4.5%25,61425.6k174.441262%4.441262%4.4%23,19423.2k184.325266%4.325266%4.3%19,24719.2k194.025531%4.025531%4.0%27,61827.6k203.827408%3.827408%3.8%38,21138.2k213.792624%3.792624%3.8%23,36723.4k223.737871%3.737871%3.7%77,97878.0k233.720350%3.720350%3.7%38,51538.5k243.601468%3.601468%3.6%45,61045.6k253.490252%3.490252%3.5%18,54218.5k263.466073%3.466073%3.5%15,21115.2k273.384967%3.384967%3.4%59,36259.4k283.380196%3.380196%3.4%25,05825.1k293.357865%3.357865%3.4%17,95418.0k303.336158%3.336158%3.3%7,127,6737.13M3.140490%3.140490%3.1%12,13312.1k313.010825%3.010825%3.0%62,13562.1k323.009440%3.009440%3.0%11,33911.3k332.893416%2.893416%2.9%1,311,0191.31M2.893233%2.893233%2.9%11,37011.4k342.855432%2.855432%2.9%896,039896k2.828959%2.828959%2.8%11,83311.8k352.763004%2.763004%2.8%30,34430.3k362.756960%2.756960%2.8%44,96545.0k372.703886%2.703886%2.7%105,215105k2.682967%2.682967%2.7%12,62112.6k382.630994%2.630994%2.6%9,827392.484535%2.484535%2.5%15,54715.5k402.324315%2.324315%2.3%9,688412.173239%2.173239%2.2%11,57311.6k422.155077%2.155077%2.2%26,91426.9k432.043126%2.043126%2.0%7,455441.879146%1.879146%1.9%3,9741.807306%1.807306%1.8%8,895451.792414%1.792414%1.8%7,845461.745764%1.745764%1.7%5,975471.704476%1.704476%1.7%10,08610.1k481.664253%1.664253%1.7%15,06415.1k491.318660%1.318660%1.3%5,693501.076454%1.076454%1.1%2931.027703%1.027703%1.0%230.662983%0.662983%0.7%120.542005%0.542005%0.5%20.542005%0.542005%0.5%20.230017%0.230017%0.2%4
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).

Under-Education Sex Ratio by County Subdivision#33

Percentage more likely men are than women to not have a high school diploma (or equivalent) among people aged 25 years and older.
Scope: population of Lena, selected other county subdivisions in the United States, and entities that contain Lena
Female
Male
1x0x1xFM#ZIP 54139LenaOconto1, CharlotteTract 100800Green BayDetroitWisconsinBaltimoreTulsaSW DallasMidwestFresnoEast North CentralMilwaukeeUnited StatesNE DallasHoustonHempsteadOrlandoPhiladelphiaOntarioSan BernardinoAustinAtlantaFort WorthPhoenixChicagoAlbuquerqueWashingtonSacramentoColumbusSalt Lk CityDenverNE TarrantTampaOceanside-EscondidoOceanside-Escond…NW HarrisBronxPlanoBrooklynSan Antonio CntrlSan Fernando VlyTucsonAnaheim-Santa Ana-Gdn GrvAnaheim-Santa An…Los AngelesLas VegasBostonE San Gabriel VlyQueensMiamiManhattanSeattleLong Bch-LakewoodSeattle EastSan JoseSan DiegoSan FranciscoEl PasoLenaLena-1.000000x-1.000000x1.719865x1.719865x1.72x7.498%7.50%12.895%12.9%-1.000000x-1.000000x1.440914x1.440914x1.44x9.779%9.78%14.090%14.1%-1.000000x-1.000000x1.374304x1.374304x1.37x8.070%8.07%11.091%11.1%-1.000000x-1.000000x1.285784x1.285784x1.29x10.185%10.2%13.096%13.1%1-1.000000x-1.000000x1.284848x1.284848x1.28x9.434%9.43%12.121%12.1%-1.000000x-1.000000x1.245810x1.245810x1.25x7.746%7.75%9.650%9.65%-1.000000x-1.000000x1.237056x1.237056x1.24x18.951%19.0%23.443%23.4%2-1.000000x-1.000000x1.219291x1.219291x1.22x7.799%7.80%9.509%9.51%-1.000000x-1.000000x1.179669x1.179669x1.18x15.289%15.3%18.036%18.0%3-1.000000x-1.000000x1.177766x1.177766x1.18x10.417%10.4%12.268%12.3%4-1.000000x-1.000000x1.160109x1.160109x1.16x22.304%22.3%25.875%25.9%5-1.000000x-1.000000x1.127915x1.127915x1.13x9.647%9.65%10.881%10.9%-1.000000x-1.000000x1.127206x1.127206x1.13x20.830%20.8%23.479%23.5%6-1.000000x-1.000000x1.125371x1.125371x1.13x10.108%10.1%11.375%11.4%-1.000000x-1.000000x1.123984x1.123984x1.12x16.526%16.5%18.574%18.6%7-1.000000x-1.000000x1.109070x1.109070x1.11x12.369%12.4%13.719%13.7%-1.000000x-1.000000x1.099797x1.099797x1.10x19.814%19.8%21.791%21.8%8-1.000000x-1.000000x1.099188x1.099188x1.10x20.902%20.9%22.975%23.0%9-1.000000x-1.000000x1.092101x1.092101x1.09x9.951%9.95%10.868%10.9%10-1.000000x-1.000000x1.090284x1.090284x1.09x13.111%13.1%14.294%14.3%11-1.000000x-1.000000x1.090163x1.090163x1.09x16.700%16.7%18.206%18.2%12-1.000000x-1.000000x1.088515x1.088515x1.09x16.417%16.4%17.871%17.9%13-1.000000x-1.000000x1.081887x1.081887x1.08x26.536%26.5%28.709%28.7%14-1.000000x-1.000000x1.078150x1.078150x1.08x13.148%13.1%14.176%14.2%15-1.000000x-1.000000x1.073220x1.073220x1.07x9.215%9.21%9.889%9.89%16-1.000000x-1.000000x1.071348x1.071348x1.07x19.379%19.4%20.762%20.8%17-1.000000x-1.000000x1.069008x1.069008x1.07x14.467%14.5%15.465%15.5%18-1.000000x-1.000000x1.068021x1.068021x1.07x16.372%16.4%17.486%17.5%19-1.000000x-1.000000x1.066879x1.066879x1.07x11.714%11.7%12.497%12.5%20-1.000000x-1.000000x1.064309x1.064309x1.06x9.751%9.75%10.378%10.4%21-1.000000x-1.000000x1.053268x1.053268x1.05x13.558%13.6%14.280%14.3%22-1.000000x-1.000000x1.052237x1.052237x1.05x11.098%11.1%11.678%11.7%23-1.000000x-1.000000x1.051272x1.051272x1.05x10.176%10.2%10.697%10.7%24-1.000000x-1.000000x1.049933x1.049933x1.05x13.307%13.3%13.971%14.0%25-1.000000x-1.000000x1.040742x1.040742x1.04x8.257%8.26%8.594%8.59%26-1.000000x-1.000000x1.040003x1.040003x1.04x12.734%12.7%13.244%13.2%27-1.000000x-1.000000x1.039910x1.039910x1.04x15.694%15.7%16.321%16.3%28-1.000000x-1.000000x1.038394x1.038394x1.04x9.953%9.95%10.335%10.3%29-1.000000x-1.000000x1.030539x1.030539x1.03x28.448%28.4%29.316%29.3%30-1.000000x-1.000000x1.023151x1.023151x1.02x5.652%5.65%5.783%5.78%31-1.000000x-1.000000x1.018960x1.018960x1.02x19.845%19.8%20.221%20.2%32-1.000000x-1.000000x1.003929x1.003929x1.00x28.944%28.9%29.058%29.1%33-1.000000x-1.000000x1.003840x1.003840x1.00x19.308%19.3%19.383%19.4%34-1.006471x-1.006471x1.01x1.000000x1.000000x12.301%12.3%12.222%12.2%35-1.008020x-1.008020x1.01x1.000000x1.000000x22.734%22.7%22.553%22.6%36-1.013004x-1.013004x1.01x1.000000x1.000000x24.995%25.0%24.674%24.7%37-1.016645x-1.016645x1.02x1.000000x1.000000x16.036%16.0%15.774%15.8%38-1.022333x-1.022333x1.02x1.000000x1.000000x14.476%14.5%14.159%14.2%39-1.026902x-1.026902x1.03x1.000000x1.000000x20.723%20.7%20.180%20.2%40-1.027762x-1.027762x1.03x1.000000x1.000000x19.596%19.6%19.067%19.1%41-1.030897x-1.030897x1.03x1.000000x1.000000x22.136%22.1%21.473%21.5%42-1.044246x-1.044246x1.04x1.000000x1.000000x13.260%13.3%12.698%12.7%43-1.049689x-1.049689x1.05x1.000000x1.000000x9.047%9.05%8.619%8.62%44-1.056864x-1.056864x1.06x1.000000x1.000000x19.921%19.9%18.849%18.8%45-1.057675x-1.057675x1.06x1.000000x1.000000x5.050%5.05%4.774%4.77%46-1.127548x-1.127548x1.13x1.000000x1.000000x13.555%13.6%12.021%12.0%47-1.168454x-1.168454x1.17x1.000000x1.000000x13.975%14.0%11.960%12.0%48-1.228758x-1.228758x1.23x1.000000x1.000000x13.883%13.9%11.298%11.3%49-1.276282x-1.276282x1.28x1.000000x1.000000x26.394%26.4%20.680%20.7%50-1.932676x-1.932676x1.93x1.000000x1.000000x16.763%16.8%8.673%8.67%-1.932676x-1.932676x1.93x1.000000x1.000000x16.763%16.8%8.673%8.67%
F percentage of females in category
M percentage of males in category
# rank of county subdivision out of 50 by male-to-female sex ratio

Over-Education Sex Ratio by County Subdivision#34

Percentage more likely men are than women to have a professional or doctorate degree (e.g., MBA, PhD, or MD) among people aged 25 years and older.
Scope: population of Lena, selected other county subdivisions in the United States, and entities that contain Lena
Female
Male
10x5x0xFM#LenaZIP 54139El PasoSalt Lk CityPlanoGreen BayTulsaAlbuquerqueNE DallasFort WorthOrlandoPhoenixTucson1, CharlotteEast North CentralMidwestNW HarrisLas VegasWisconsinSeattle EastSan Antonio CntrlSan DiegoUnited StatesSan JoseHempsteadFresnoNE TarrantTampaSan Fernando VlyE San Gabriel VlyHoustonSan BernardinoColumbusMiamiAtlantaMilwaukeeAnaheim-Santa Ana-Gdn GrvAnaheim-Santa An…SacramentoPhiladelphiaOceanside-EscondidoOceanside-Escond…Los AngelesAustinBaltimoreWashingtonQueensSW DallasBrooklynManhattanChicagoSeattleBostonBronxOntarioLong Bch-LakewoodDenverSan FranciscoOcontoDetroitTract 100800LenaLena-1.000000x-1.000000x4.516299x4.516299x4.52x0.233%0.23%1.052%1.05%-1.000000x-1.000000x4.328138x4.328138x4.33x0.375%0.37%1.623%1.62%-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-1.000000x1.720824x1.720824x1.72x1.386%1.39%2.385%2.38%-1.000000x-1.000000x1.720683x1.720683x1.72x2.338%2.34%4.022%4.02%4-1.000000x-1.000000x1.707718x1.707718x1.71x3.458%3.46%5.905%5.91%5-1.000000x-1.000000x1.692229x1.692229x1.69x2.857%2.86%4.836%4.84%6-1.000000x-1.000000x1.684272x1.684272x1.68x1.637%1.64%2.757%2.76%7-1.000000x-1.000000x1.660799x1.660799x1.66x2.196%2.20%3.647%3.65%8-1.000000x-1.000000x1.659024x1.659024x1.66x2.280%2.28%3.783%3.78%9-1.000000x-1.000000x1.621815x1.621815x1.62x3.429%3.43%5.561%5.56%10-1.000000x-1.000000x1.611479x1.611479x1.61x2.711%2.71%4.369%4.37%11-1.000000x-1.000000x1.597848x1.597848x1.60x2.216%2.22%3.541%3.54%-1.000000x-1.000000x1.589934x1.589934x1.59x2.251%2.25%3.579%3.58%-1.000000x-1.000000x1.579303x1.579303x1.58x2.100%2.10%3.317%3.32%12-1.000000x-1.000000x1.576623x1.576623x1.58x1.677%1.68%2.643%2.64%13-1.000000x-1.000000x1.576114x1.576114x1.58x2.109%2.11%3.323%3.32%-1.000000x-1.000000x1.557664x1.557664x1.56x4.733%4.73%7.372%7.37%14-1.000000x-1.000000x1.540473x1.540473x1.54x1.423%1.42%2.192%2.19%15-1.000000x-1.000000x1.529565x1.529565x1.53x4.164%4.16%6.370%6.37%16-1.000000x-1.000000x1.526215x1.526215x1.53x2.660%2.66%4.060%4.06%-1.000000x-1.000000x1.514156x1.514156x1.51x4.979%4.98%7.539%7.54%17-1.000000x-1.000000x1.488724x1.488724x1.49x3.608%3.61%5.371%5.37%18-1.000000x-1.000000x1.484269x1.484269x1.48x2.293%2.29%3.404%3.40%19-1.000000x-1.000000x1.481801x1.481801x1.48x2.138%2.14%3.168%3.17%20-1.000000x-1.000000x1.476874x1.476874x1.48x3.518%3.52%5.196%5.20%21-1.000000x-1.000000x1.460302x1.460302x1.46x2.944%2.94%4.299%4.30%22-1.000000x-1.000000x1.451775x1.451775x1.45x2.041%2.04%2.963%2.96%23-1.000000x-1.000000x1.424636x1.424636x1.42x3.092%3.09%4.404%4.40%24-1.000000x-1.000000x1.423621x1.423621x1.42x1.501%1.50%2.137%2.14%25-1.000000x-1.000000x1.413654x1.413654x1.41x2.801%2.80%3.959%3.96%26-1.000000x-1.000000x1.395174x1.395174x1.40x3.384%3.38%4.722%4.72%27-1.000000x-1.000000x1.391590x1.391590x1.39x5.799%5.80%8.070%8.07%28-1.000000x-1.000000x1.368590x1.368590x1.37x1.742%1.74%2.385%2.38%29-1.000000x-1.000000x1.362600x1.362600x1.36x2.347%2.35%3.199%3.20%30-1.000000x-1.000000x1.359928x1.359928x1.36x2.888%2.89%3.927%3.93%31-1.000000x-1.000000x1.341930x1.341930x1.34x3.216%3.22%4.316%4.32%32-1.000000x-1.000000x1.310218x1.310218x1.31x3.011%3.01%3.945%3.95%33-1.000000x-1.000000x1.308108x1.308108x1.31x4.045%4.05%5.292%5.29%34-1.000000x-1.000000x1.303834x1.303834x1.30x4.384%4.38%5.716%5.72%35-1.000000x-1.000000x1.303196x1.303196x1.30x4.332%4.33%5.645%5.65%36-1.000000x-1.000000x1.300117x1.300117x1.30x10.922%10.9%14.199%14.2%37-1.000000x-1.000000x1.285200x1.285200x1.29x2.428%2.43%3.121%3.12%38-1.000000x-1.000000x1.265486x1.265486x1.27x1.515%1.51%1.917%1.92%39-1.000000x-1.000000x1.262281x1.262281x1.26x3.021%3.02%3.814%3.81%40-1.000000x-1.000000x1.245683x1.245683x1.25x9.673%9.67%12.050%12.1%41-1.000000x-1.000000x1.238186x1.238186x1.24x4.026%4.03%4.985%4.99%42-1.000000x-1.000000x1.228890x1.228890x1.23x5.961%5.96%7.326%7.33%43-1.000000x-1.000000x1.221037x1.221037x1.22x6.643%6.64%8.112%8.11%44-1.000000x-1.000000x1.202385x1.202385x1.20x1.526%1.53%1.834%1.83%45-1.000000x-1.000000x1.198236x1.198236x1.20x2.119%2.12%2.539%2.54%46-1.000000x-1.000000x1.181998x1.181998x1.18x2.766%2.77%3.269%3.27%47-1.000000x-1.000000x1.129665x1.129665x1.13x5.378%5.38%6.075%6.08%48-1.000000x-1.000000x1.098720x1.098720x1.10x7.194%7.19%7.905%7.90%49-1.000000x-1.000000x1.084340x1.084340x1.08x1.032%1.03%1.119%1.12%-1.000000x-1.000000x1.046557x1.046557x1.05x1.291%1.29%1.351%1.35%50-1.050708x-1.050708x1.05x1.000000x1.000000x0.236%0.24%0.224%0.22%-10.000000x-10.000000x> 10.0x1.000000x1.000000x1.156%1.16%0.000%0%-10.000000x-10.000000x> 10.0x1.000000x1.000000x1.156%1.16%0.000%0%
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.

More Topics to Explore

Demographics

Income

Education

More Maps to Explore

State:
Wisconsin
County:
Oconto
Metro Area:
Green Bay Area
Village:
Lena
ZIP Code:
54139
Unified School District:
Lena
Congressional District:
WI-8
State Senate District:
WI-12
Assembly District:
WI-36
Neighboring Towns:
Lena
Nearby Towns:
Little River, Oconto, Oconto Falls, Pound, Spruce, Stiles