Educational Attainment in the Chester Township, Wabasha County, Minnesota (Township)

Educational Attainment#1

Highest level of education among people aged 25 years and older.
Scope: population of Wabasha County and the Chester Township
Chester Township
Wabasha County
0%10%20%30%40%50%60%CountHigher Degree1H.S. Diploma2No H.S. Diploma227.083333%32.416268%27.083333%27.1%7857.986111%60.772196%57.986111%58.0%16714.930556%6.811536%14.930556%14.9%43
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 Wabasha County at large.
Scope: population of Wabasha County and the Chester Township
-100%0%+100%%ref.Higher Degree1H.S. Diploma2No H.S. Diploma2-16.451415%-16.451415%-16.5%27.083%27.1%32.416%32.4%-4.584472%-4.584472%-4.6%57.986%58.0%60.772%60.8%119.195122%119.195122%+119.2%14.931%14.9%6.812%6.81%
% percentage with given level in the Chester Township
ref. percentage with given level in Wabasha 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 Wabasha County and the Chester Township
Chester Township
Wabasha County
0%10%20%30%CountDoctorate1Professional1Master's1Bachelor's1Associate's1Some CollegeHigh School2Some H.S.3Less than H.S.3None0.000000%0.000000%0.0%0.744285%00.694444%1.030037%0.694444%0.7%23.125000%4.817916%3.125000%3.1%914.930556%14.646465%14.930556%14.9%438.333333%11.177565%8.333333%8.3%2418.055556%23.637693%18.055556%18.1%5239.930556%37.134503%39.930556%39.9%1157.638889%4.525518%7.638889%7.6%227.291667%1.847422%7.291667%7.3%210.000000%0.000000%0.0%0.438596%0
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 Wabasha County at large.
Scope: population of Wabasha County and the Chester Township
-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%0.744%0.74%-32.580645%-32.580645%-32.6%0.694%0.69%1.030%1.03%-35.137931%-35.137931%-35.1%3.125%3.13%4.818%4.82%1.939655%1.939655%+1.9%14.931%14.9%14.646%14.6%-25.445898%-25.445898%-25.4%8.333%8.33%11.178%11.2%-23.615406%-23.615406%-23.6%18.056%18.1%23.638%23.6%7.529528%7.529528%+7.5%39.931%39.9%37.135%37.1%68.795888%68.795888%+68.8%7.639%7.64%4.526%4.53%294.694245%294.694245%+294.7%7.292%7.29%1.847%1.85%-100.000000%-100.000000%-100.0%0.000%0%0.439%0.44%
% percentage with given level in the Chester Township
ref. percentage with given level in Wabasha 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 Wabasha County and the Chester Township
More Females More Males
Wabasha County
Chester Township
0%100%FMHigher Degree1H.S. Diploma2No H.S. Diploma2-96.926714%-21.750148%-96.926714%97%36.170%36.2%18.367%18.4%6.845776%6.952576%6.845776%7%56.028%56.0%59.864%59.9%179.035250%39.883859%179.035250%179%7.801%7.80%21.769%21.8%
F females in category as a percentage of all females
M males in category as a percentage of all males
1Post-Secondary Degree 2H.S. = High School

Detailed Educational Attainment Sex Ratio#6

Percentage more likely men or women are to have various highest levels of education among people aged 25 years and older.
Scope: population of Wabasha County and the Chester Township
More Females More Males
Wabasha County
Chester Township
0%500%1,000%FMProfessional1Master's1Bachelor's1Associate's1Some CollegeHigh School2Some H.S.3Less than H.S.31,000.000000%165.427688%1,000.000000%> 1000%0.000%0%1.361%1.36%-108.510638%-38.230126%-108.510638%109%4.255%4.26%2.041%2.04%-75.930851%-27.160577%-75.930851%76%19.149%19.1%10.884%10.9%-212.765957%-21.943314%-212.765957%213%12.766%12.8%4.082%4.08%-14.964676%3.591837%3.591837%4%17.730%17.7%18.367%18.4%8.352230%22.021847%8.352230%8%38.298%38.3%41.497%41.5%38.548753%10.970466%38.548753%39%6.383%6.38%8.844%8.84%811.224490%106.025878%811.224490%811%1.418%1.42%12.925%12.9%
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 Wabasha County and the Chester Township
Chester Township
Wabasha County
0%5%10%15%20%25%B.X.Total65+45-6435-4425-3410.344828%12.640239%10.344828%10.3%65814.465409%14.590859%14.465409%14.5%2315910.344828%17.776853%10.344828%10.3%32926.190476%15.035273%26.190476%26.2%1142
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 Wabasha County at large.
Scope: population of Wabasha County and the Chester Township
40%20%0%20%40%60%%ref.65+45-6435-4425-34-18.159559%-18.159559%18.2%10.345%10.3%12.640%12.6%-0.859787%-0.859787%0.9%14.465%14.5%14.591%14.6%-41.807316%-41.807316%41.8%10.345%10.3%17.777%17.8%74.193548%74.193548%74.2%26.190%26.2%15.035%15.0%
% percentage in the Chester Township with a Bachelor's degree
ref percentage in Wabasha 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 Wabasha County and the Chester Township
More Females More Males
Wabasha County
Chester Township
1,000%500%0%FM65+45-6435-4425-34-74.193548%-74.193548%74.2%19.769168%12.903%12.9%7.407%7.41%-57.083333%-39.467073%-57.083333%57.1%18.056%18.1%11.494%11.5%-1,000.000000%-77.837385%-1,000.000000%> 1000%20.000%20.0%0.000%0%-44.565217%-27.226043%-44.565217%44.6%30.435%30.4%21.053%21.1%
F female degree holders as a percentage of all females
M male degree holders as a percentage of all males

Median Earnings by Educational Attainment#10

Among population 25 years old and over with earnings.
Scope: population of Wabasha County and the Chester Township
Chester Township
Wabasha County
$0k$20k$40k$60k$80kCount%Graduate Degree1Bachelor's DegreeSome CollegeH.S. Diploma2No H.S. Diploma2Total$93,125.000000$54,492.000000$93,125.000000$93.1k113.819%3.82%$53,750.000000$51,649.000000$53,750.000000$53.8k4314.931%14.9%$47,125.000000$38,272.000000$47,125.000000$47.1k7626.389%26.4%$41,591.000000$31,770.000000$41,591.000000$41.6k11539.931%39.9%$45,000.000000$22,639.000000$45,000.000000$45.0k4314.931%14.9%$47,083.000000$37,953.000000$47,083.000000$47.1k288100.000%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 Wabasha County and the Chester Township
Female Male
Wabasha County
Chester Township
Shaded bar tips show excess over facing bar.
$50k$0k$50k$100k$150kFMGraduate Degree1Bachelor's DegreeSome CollegeH.S. Diploma2Total$-38,750.000000$-50,739.000000$-38,750.000000$38.8k$38,750.000000$115,625.000000$50,739.000000$20,511.000000$154,375.000000$154.4k65$-43,750.000000$-48,625.000000$-43,750.000000$43.8k$43,750.000000$26,250.000000$48,625.000000$8,607.000000$70,000.000000$70.0k2716$-45,000.000000$-32,356.000000$-45,000.000000$45.0k$45,000.000000$7,083.000000$32,356.000000$13,649.000000$52,083.000000$52.1k4333$-40,313.000000$-25,332.000000$-40,313.000000$40.3k$40,313.000000$8,687.000000$25,332.000000$13,145.000000$49,000.000000$49.0k5461$-41,136.000000$-32,016.000000$-41,136.000000$41.1k$41,136.000000$10,180.000000$32,016.000000$10,882.000000$51,316.000000$51.3k141147
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 Wabasha County and the Chester Township
Chester Township
Wabasha County
0%20%40%60%80%CountBachelor's Degree1Some College2H.S. Diploma3No H.S. Diploma391.111111%89.619520%91.111111%91.1%4198.571429%85.166240%98.571429%98.6%6969.565217%80.214043%69.565217%69.6%6478.260870%59.958932%78.260870%78.3%18
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 Wabasha County and the Chester Township
Female Male
Wabasha County
Chester Township
Shaded bar tips show excess over facing bar.
5%0%5%10%15%20%MFWhite1-7.801418%-5.639201%-7.801418%7.8%7.801418%13.967289%5.639201%2.142141%21.768707%21.8%3211
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 Wabasha County and the Chester Township
Female Male
Wabasha County
Chester Township
Shaded bar tips show excess over facing bar.
20%10%0%10%MFWhite1-14.285714%-9.118541%-18.895552%-4.605680%-23.404255%23.4%14.285714%18.895552%14.285714%14.3%2133
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 Rochester Area

There are 110 county subdivisions in the Rochester Area. This section compares the Chester Township to the 50 most populous county subdivisions in the Rochester Area and to those entities that contain or substantially overlap with the Chester Township. The least populous of the compared county subdivisions has a population of 564.

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 the Chester Township, selected other county subdivisions in the Rochester Area, and entities that contain the Chester Township
0%5%10%15%Count#ClaremontChester TownshipChesterWest ConcordUnited States of AmericaUnited StatesMabelDodge CenterMazeppaMidwestChatfieldHarmonySpring ValleyWest North Central490400Tract 490400RushfordRock Dell TownshipRock DellSalem TownshipSalemOrion TownshipOrionLake CityWabashaMinnesotaElginWabasha CountyWabashaMazeppa TownshipMazeppaPrestonRochesterRushford VillageRushford VlgRochester Metro AreaRochesterConcord TownshipConcordWasioja TownshipWasiojaMantorvilleEyotaStewartvilleGillford TownshipGillfordPleasant Grove TownshipPleasant GrvMilton TownshipMiltonZumbro TownshipZumbroDoverKalmar TownshipKalmarHayfieldCascade TownshipCascadeElgin TownshipElginLanesboroMarion TownshipMarionHigh Forest TownshipHigh FrstPlainviewVernon TownshipVernonGreenfield TownshipGreenfieldOronoco TownshipOronocoChatfieldKassonHaverhill TownshipHaverhillPine IslandOronocoRochester TownshipRochesterCanisteo TownshipCanisteoByronNew Haven TownshipNew HvnMantorville TownshipMantorville18.316832%18.316832%18.3%74114.930556%14.930556%14.9%4313.939394%13.939394%13.9%69213.020590%13.020590%13.0%27,818,38027.8M12.307692%12.307692%12.3%72311.764706%11.764706%11.8%190411.028037%11.028037%11.0%59510.244520%10.244520%10.2%4,641,8354.64M9.739130%9.739130%9.7%11269.494451%9.494451%9.5%7779.388511%9.388511%9.4%15289.174633%9.174633%9.2%1,278,0511.28M8.872582%8.872582%8.9%2668.491281%8.491281%8.5%11298.466819%8.466819%8.5%37108.264463%8.264463%8.3%70117.862903%7.862903%7.9%39127.784055%7.784055%7.8%248137.642998%7.642998%7.6%155147.376055%7.376055%7.4%270,121270k7.355021%7.355021%7.4%52156.811536%6.811536%6.8%1,0256.776557%6.776557%6.8%37166.494845%6.494845%6.5%63176.300465%6.300465%6.3%4,713186.230032%6.230032%6.2%39196.187739%6.187739%6.2%8,9016.088993%6.088993%6.1%26205.722892%5.722892%5.7%38215.412720%5.412720%5.4%40225.407464%5.407464%5.4%71235.383443%5.383443%5.4%212245.263158%5.263158%5.3%20255.226481%5.226481%5.2%30265.113636%5.113636%5.1%27275.098039%5.098039%5.1%26284.990020%4.990020%5.0%25294.949381%4.949381%4.9%44304.855491%4.855491%4.9%42314.724771%4.724771%4.7%103324.661017%4.661017%4.7%22334.424779%4.424779%4.4%25344.410701%4.410701%4.4%122354.257908%4.257908%4.3%35363.976722%3.976722%4.0%82373.516484%3.516484%3.5%16383.378378%3.378378%3.4%35393.324468%3.324468%3.3%50403.070761%3.070761%3.1%23412.830688%2.830688%2.8%107422.283105%2.283105%2.3%25432.257336%2.257336%2.3%10441.991614%1.991614%2.0%19451.907131%1.907131%1.9%23461.694915%1.694915%1.7%8471.534944%1.534944%1.5%47481.240695%1.240695%1.2%10490.485044%0.485044%0.5%650
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 the Chester Township, selected other county subdivisions in the Rochester Area, and entities that contain the Chester Township
0%20%40%60%Count#Rochester TownshipRochesterPine IslandHaverhill TownshipHaverhillCascade TownshipCascadeOronoco TownshipOronocoOronocoRochesterMantorville TownshipMantorvilleByronCanisteo TownshipCanisteoRochester Metro AreaRochesterLanesboroMinnesotaSalem TownshipSalemNew Haven TownshipNew HvnKalmar TownshipKalmarMarion TownshipMarionUnited States of AmericaUnited StatesWest North CentralMidwestGillford TownshipGillfordChatfieldZumbro TownshipZumbroChatfieldHigh Forest TownshipHigh FrstMazeppa TownshipMazeppaStewartvilleVernon TownshipVernonPrestonRushford VillageRushford VlgEyotaKassonMantorvilleElgin TownshipElginWabashaOrion TownshipOrion490400Tract 490400Milton TownshipMiltonWasioja TownshipWasiojaPleasant Grove TownshipPleasant GrvElginWabasha CountyWabashaConcord TownshipConcordHarmonyPlainviewLake CityRock Dell TownshipRock DellDoverChester TownshipChesterMazeppaHayfieldDodge CenterGreenfield TownshipGreenfieldRushfordMabelWest ConcordSpring ValleyClaremont66.749585%66.749585%66.7%805160.948081%60.948081%60.9%270258.082192%58.082192%58.1%636357.981651%57.981651%58.0%1,264447.007979%47.007979%47.0%707546.331237%46.331237%46.3%442643.718250%43.718250%43.7%32,70332.7k741.632983%41.632983%41.6%515839.712606%39.712606%39.7%1,216938.771186%38.771186%38.8%1831035.991908%35.991908%36.0%51,77451.8k34.867257%34.867257%34.9%1971134.240609%34.240609%34.2%1,253,9371.25M34.120425%34.120425%34.1%2891232.878412%32.878412%32.9%2651332.733408%32.733408%32.7%2911431.742589%31.742589%31.7%8781530.315023%30.315023%30.3%64,767,78764.8M30.056536%30.056536%30.1%4,186,9564.19M28.952816%28.952816%29.0%13,118,64213.1M28.947368%28.947368%28.9%1101628.782609%28.782609%28.8%3311728.431373%28.431373%28.4%1451828.037383%28.037383%28.0%2101927.980535%27.980535%28.0%2302027.472527%27.472527%27.5%1502127.323514%27.323514%27.3%1,0762227.252747%27.252747%27.3%1242326.804124%26.804124%26.8%2602426.677316%26.677316%26.7%1672525.894897%25.894897%25.9%3402625.026455%25.026455%25.0%9462724.898512%24.898512%24.9%1842824.152542%24.152542%24.2%1142924.112426%24.112426%24.1%4893023.991935%23.991935%24.0%1193123.849233%23.849233%23.8%71523.106061%23.106061%23.1%1223222.439759%22.439759%22.4%1493322.125436%22.125436%22.1%1273421.357850%21.357850%21.4%1513521.238703%21.238703%21.2%3,19621.077283%21.077283%21.1%903620.961776%20.961776%21.0%1703720.659554%20.659554%20.7%4263820.087884%20.087884%20.1%6403919.221968%19.221968%19.2%844018.962076%18.962076%19.0%954118.750000%18.750000%18.8%5418.317757%18.317757%18.3%984217.109827%17.109827%17.1%1484316.842105%16.842105%16.8%2724416.119691%16.119691%16.1%1674515.466262%15.466262%15.5%2044615.213675%15.213675%15.2%894714.545455%14.545455%14.5%724813.773935%13.773935%13.8%223491.732673%1.732673%1.7%750
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 the Chester Township, selected other county subdivisions in the Rochester Area, and entities that contain the Chester Township
0%10%20%Count#Rochester TownshipRochesterHaverhill TownshipHaverhillCascade TownshipCascadeRochesterZumbro TownshipZumbroOronoco TownshipOronocoRochester Metro AreaRochesterWabashaMantorville TownshipMantorvilleByronOronocoLanesboroSalem TownshipSalemCanisteo TownshipCanisteoMinnesotaUnited States of AmericaUnited StatesWest North CentralPine IslandMidwestOrion TownshipOrionNew Haven TownshipNew HvnRock Dell TownshipRock DellSpring ValleyElgin490400Tract 490400HarmonyMarion TownshipMarionMazeppa TownshipMazeppaMazeppaWabasha CountyWabashaRushford VillageRushford VlgKalmar TownshipKalmarDoverElgin TownshipElginMilton TownshipMiltonChatfieldPleasant Grove TownshipPleasant GrvKassonPrestonHigh Forest TownshipHigh FrstGreenfield TownshipGreenfieldWasioja TownshipWasiojaLake CityConcord TownshipConcordEyotaVernon TownshipVernonMantorvilleChatfieldStewartvilleChester TownshipChesterWest ConcordRushfordDodge CenterHayfieldMabelGillford TownshipGillfordPlainviewClaremont27.114428%27.114428%27.1%327115.981735%15.981735%16.0%175211.788991%11.788991%11.8%25738.768248%8.768248%8.8%6,55947.254902%7.254902%7.3%3757.247340%7.247340%7.2%10965.925658%5.925658%5.9%8,5245.078895%5.078895%5.1%10374.688763%4.688763%4.7%5884.604833%4.604833%4.6%14194.297694%4.297694%4.3%41104.247788%4.247788%4.2%24114.014168%4.014168%4.0%34123.601695%3.601695%3.6%17133.458748%3.458748%3.5%126,664127k3.336158%3.336158%3.3%7,127,6737.13M2.978981%2.978981%3.0%414,980415k2.934537%2.934537%2.9%13142.893416%2.893416%2.9%1,311,0191.31M2.822581%2.822581%2.8%14152.481390%2.481390%2.5%20162.288330%2.288330%2.3%10172.285361%2.285361%2.3%37182.263083%2.263083%2.3%16192.234823%2.234823%2.2%672.096178%2.096178%2.1%17202.060738%2.060738%2.1%57212.014652%2.014652%2.0%11221.869159%1.869159%1.9%10231.774322%1.774322%1.8%2671.757188%1.757188%1.8%11241.687289%1.687289%1.7%15251.596806%1.596806%1.6%8261.483051%1.483051%1.5%7271.325758%1.325758%1.3%7281.304348%1.304348%1.3%15291.219512%1.219512%1.2%7301.164021%1.164021%1.2%44311.134021%1.134021%1.1%11321.094891%1.094891%1.1%9331.061776%1.061776%1.1%11341.054217%1.054217%1.1%7351.035782%1.035782%1.0%33360.936768%0.936768%0.9%4370.913938%0.913938%0.9%12380.879121%0.879121%0.9%4390.811908%0.811908%0.8%6400.801068%0.801068%0.8%6410.787202%0.787202%0.8%31420.694444%0.694444%0.7%20.404040%0.404040%0.4%2430.379075%0.379075%0.4%5440.371517%0.371517%0.4%6450.346821%0.346821%0.3%3460.341880%0.341880%0.3%2470.263158%0.263158%0.3%1480.096993%0.096993%0.1%2490.000000%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 the Chester Township, selected other county subdivisions in the Rochester Area, and entities that contain the Chester Township
Female
Male
0x5x10xFM#MantorvilleOronocoPine IslandHaverhillElginByronGillfordRock DellZumbroCanisteoChesterLanesboroPrestonSalemStewartvilleEyotaPleasant GrvCascadeOronocoDodge CenterConcordGreenfieldTract 490400MiltonMazeppaWasiojaElginKassonLake CityRushford VlgMantorvilleWabashaSpring ValleyNew HvnChatfieldWabashaWest North CentralMinnesotaMidwestRochesterUnited StatesRochesterDoverChatfieldMabelOrionRochesterHigh FrstVernonHarmonyKalmarClaremontRushfordMazeppaWest ConcordPlainviewMarionHayfield-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%0.972%0.97%1-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%3.983%3.98%2-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%4.367%4.37%3-1.000000x-1.000000x5.890988x5.890988x5.89x0.691%0.69%4.070%4.07%4-1.000000x-1.000000x5.868027x5.868027x5.87x1.322%1.32%7.755%7.76%5-1.000000x-1.000000x5.469595x5.469595x5.47x0.494%0.49%2.703%2.70%6-1.000000x-1.000000x4.837398x4.837398x4.84x1.714%1.71%8.293%8.29%7-1.000000x-1.000000x3.353524x3.353524x3.35x3.810%3.81%12.775%12.8%8-1.000000x-1.000000x3.053571x3.053571x3.05x2.593%2.59%7.917%7.92%9-1.000000x-1.000000x2.900000x2.900000x2.90x0.862%0.86%2.500%2.50%10-1.000000x-1.000000x2.790353x2.790353x2.79x7.801%7.80%21.769%21.8%-1.000000x-1.000000x2.583333x2.583333x2.58x2.581%2.58%6.667%6.67%11-1.000000x-1.000000x2.364035x2.364035x2.36x3.878%3.88%9.167%9.17%12-1.000000x-1.000000x2.361045x2.361045x2.36x4.930%4.93%11.639%11.6%13-1.000000x-1.000000x2.260510x2.260510x2.26x3.401%3.40%7.688%7.69%14-1.000000x-1.000000x1.916903x1.916903x1.92x3.768%3.77%7.223%7.22%15-1.000000x-1.000000x1.905063x1.905063x1.91x3.488%3.49%6.646%6.65%16-1.000000x-1.000000x1.770740x1.770740x1.77x3.407%3.41%6.033%6.03%17-1.000000x-1.000000x1.768347x1.768347x1.77x2.400%2.40%4.244%4.24%18-1.000000x-1.000000x1.724528x1.724528x1.72x8.747%8.75%15.085%15.1%19-1.000000x-1.000000x1.695802x1.695802x1.70x4.455%4.46%7.556%7.56%20-1.000000x-1.000000x1.615675x1.615675x1.62x2.569%2.57%4.151%4.15%21-1.000000x-1.000000x1.611979x1.611979x1.61x6.770%6.77%10.914%10.9%-1.000000x-1.000000x1.545455x1.545455x1.55x4.044%4.04%6.250%6.25%22-1.000000x-1.000000x1.543174x1.543174x1.54x8.594%8.59%13.262%13.3%23-1.000000x-1.000000x1.478895x1.478895x1.48x4.601%4.60%6.805%6.80%24-1.000000x-1.000000x1.463610x1.463610x1.46x6.011%6.01%8.798%8.80%25-1.000000x-1.000000x1.414541x1.414541x1.41x2.358%2.36%3.335%3.34%26-1.000000x-1.000000x1.412175x1.412175x1.41x6.483%6.48%9.155%9.16%27-1.000000x-1.000000x1.410206x1.410206x1.41x5.161%5.16%7.278%7.28%28-1.000000x-1.000000x1.401832x1.401832x1.40x4.482%4.48%6.283%6.28%29-1.000000x-1.000000x1.398839x1.398839x1.40x5.688%5.69%7.957%7.96%-1.000000x-1.000000x1.390301x1.390301x1.39x7.949%7.95%11.052%11.1%30-1.000000x-1.000000x1.279310x1.279310x1.28x1.078%1.08%1.379%1.38%31-1.000000x-1.000000x1.277470x1.277470x1.28x2.723%2.72%3.478%3.48%32-1.000000x-1.000000x1.247188x1.247188x1.25x6.842%6.84%8.533%8.53%33-1.000000x-1.000000x1.137506x1.137506x1.14x8.598%8.60%9.780%9.78%-1.000000x-1.000000x1.136388x1.136388x1.14x6.913%6.91%7.856%7.86%-1.000000x-1.000000x1.127915x1.127915x1.13x9.647%9.65%10.881%10.9%-1.000000x-1.000000x1.127663x1.127663x1.13x5.826%5.83%6.570%6.57%-1.000000x-1.000000x1.109070x1.109070x1.11x12.369%12.4%13.719%13.7%-1.000000x-1.000000x1.087297x1.087297x1.09x1.827%1.83%1.987%1.99%34-1.003846x-1.003846x1.00x1.000000x1.000000x5.000%5.00%4.981%4.98%35-1.011771x-1.011771x1.01x1.000000x1.000000x9.791%9.79%9.677%9.68%36-1.032780x-1.032780x1.03x1.000000x1.000000x12.465%12.5%12.069%12.1%37-1.035789x-1.035789x1.04x1.000000x1.000000x8.000%8.00%7.724%7.72%38-1.041504x-1.041504x1.04x1.000000x1.000000x6.423%6.42%6.167%6.17%39-1.069179x-1.069179x1.07x1.000000x1.000000x4.401%4.40%4.116%4.12%40-1.077626x-1.077626x1.08x1.000000x1.000000x3.653%3.65%3.390%3.39%41-1.239849x-1.239849x1.24x1.000000x1.000000x10.441%10.4%8.421%8.42%42-1.263741x-1.263741x1.26x1.000000x1.000000x5.543%5.54%4.386%4.39%43-1.395275x-1.395275x1.40x1.000000x1.000000x21.839%21.8%15.652%15.7%44-1.464862x-1.464862x1.46x1.000000x1.000000x9.972%9.97%6.807%6.81%45-1.679365x-1.679365x1.68x1.000000x1.000000x8.519%8.52%5.072%5.07%46-1.757212x-1.757212x1.76x1.000000x1.000000x17.917%17.9%10.196%10.2%47-1.840826x-1.840826x1.84x1.000000x1.000000x5.118%5.12%2.781%2.78%48-2.022434x-2.022434x2.02x1.000000x1.000000x5.778%5.78%2.857%2.86%49-3.672953x-3.672953x3.67x1.000000x1.000000x7.328%7.33%1.995%2.00%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 the Chester Township, selected other county subdivisions in the Rochester Area, and entities that contain the Chester Township
Female
Male
10x5x0x5x10xFM#ChesterPlainviewChatfieldDoverWest ConcordMabelGillfordSalemRushford VlgKalmarLake CitySpring ValleyLanesboroByronWabashaMiltonNew HvnMarionCanisteoElginRochesterCascadeHarmonyPrestonHaverhillWabashaRochesterRochesterMantorvilleMidwestWest North CentralUnited StatesMinnesotaOronocoRock DellOronocoMazeppaKassonMantorvilleConcordZumbroTract 490400ElginHigh FrstWasiojaPleasant GrvChatfieldEyotaGreenfieldOrionStewartvilleDodge CenterRushfordHayfieldMazeppaPine IslandVernon-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%1.361%1.36%-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%0.199%0.20%1-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%1.739%1.74%2-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%3.065%3.07%3-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%0.784%0.78%4-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%0.862%0.86%5-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%0.488%0.49%6-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.704%0.70%7.363%7.36%7-1.000000x-1.000000x4.414557x4.414557x4.41x0.645%0.65%2.848%2.85%8-1.000000x-1.000000x3.798246x3.798246x3.80x0.693%0.69%2.632%2.63%9-1.000000x-1.000000x3.294246x3.294246x3.29x0.489%0.49%1.612%1.61%10-1.000000x-1.000000x3.120639x3.120639x3.12x1.152%1.15%3.595%3.60%11-1.000000x-1.000000x2.952381x2.952381x2.95x2.258%2.26%6.667%6.67%12-1.000000x-1.000000x2.934378x2.934378x2.93x2.409%2.41%7.069%7.07%13-1.000000x-1.000000x2.701734x2.701734x2.70x2.812%2.81%7.596%7.60%14-1.000000x-1.000000x2.656250x2.656250x2.66x0.735%0.74%1.953%1.95%15-1.000000x-1.000000x2.558621x2.558621x2.56x1.348%1.35%3.448%3.45%16-1.000000x-1.000000x2.461133x2.461133x2.46x1.224%1.22%3.012%3.01%17-1.000000x-1.000000x2.320000x2.320000x2.32x2.155%2.16%5.000%5.00%18-1.000000x-1.000000x2.316327x2.316327x2.32x0.881%0.88%2.041%2.04%19-1.000000x-1.000000x2.198578x2.198578x2.20x16.944%16.9%37.252%37.3%20-1.000000x-1.000000x2.118540x2.118540x2.12x7.551%7.55%15.996%16.0%21-1.000000x-1.000000x2.079386x2.079386x2.08x1.392%1.39%2.895%2.89%22-1.000000x-1.000000x1.786458x1.786458x1.79x0.816%0.82%1.458%1.46%23-1.000000x-1.000000x1.683140x1.683140x1.68x12.090%12.1%20.349%20.3%24-1.000000x-1.000000x1.674879x1.674879x1.67x1.330%1.33%2.227%2.23%-1.000000x-1.000000x1.656189x1.656189x1.66x6.670%6.67%11.046%11.0%25-1.000000x-1.000000x1.652184x1.652184x1.65x4.500%4.50%7.434%7.43%-1.000000x-1.000000x1.644320x1.644320x1.64x3.548%3.55%5.835%5.83%26-1.000000x-1.000000x1.589934x1.589934x1.59x2.251%2.25%3.579%3.58%-1.000000x-1.000000x1.572017x1.572017x1.57x2.329%2.33%3.662%3.66%-1.000000x-1.000000x1.526215x1.526215x1.53x2.660%2.66%4.060%4.06%-1.000000x-1.000000x1.481015x1.481015x1.48x2.798%2.80%4.144%4.14%-1.000000x-1.000000x1.411765x1.411765x1.41x3.564%3.56%5.031%5.03%27-1.000000x-1.000000x1.387665x1.387665x1.39x1.905%1.90%2.643%2.64%28-1.000000x-1.000000x1.217994x1.217994x1.22x6.533%6.53%7.958%7.96%29-1.000000x-1.000000x1.173913x1.173913x1.17x1.852%1.85%2.174%2.17%30-1.026751x-1.026751x1.03x1.000000x1.000000x1.179%1.18%1.148%1.15%31-1.070028x-1.070028x1.07x1.000000x1.000000x0.840%0.84%0.785%0.79%32-1.113861x-1.113861x1.11x1.000000x1.000000x0.990%0.99%0.889%0.89%33-1.166667x-1.166667x1.17x1.000000x1.000000x7.778%7.78%6.667%6.67%34-1.195885x-1.195885x1.20x1.000000x1.000000x2.437%2.44%2.038%2.04%-1.197892x-1.197892x1.20x1.000000x1.000000x2.459%2.46%2.053%2.05%35-1.262225x-1.262225x1.26x1.000000x1.000000x1.222%1.22%0.969%0.97%36-1.382413x-1.382413x1.38x1.000000x1.000000x1.227%1.23%0.888%0.89%37-1.633075x-1.633075x1.63x1.000000x1.000000x1.550%1.55%0.949%0.95%38-1.691814x-1.691814x1.69x1.000000x1.000000x1.605%1.61%0.949%0.95%39-1.805797x-1.805797x1.81x1.000000x1.000000x1.159%1.16%0.642%0.64%40-2.793149x-2.793149x2.79x1.000000x1.000000x1.581%1.58%0.566%0.57%41-5.904000x-5.904000x5.90x1.000000x1.000000x4.800%4.80%0.813%0.81%42-10.000000x-10.000000x> 10.0x1.000000x1.000000x1.464%1.46%0.000%0%43-10.000000x-10.000000x> 10.0x1.000000x1.000000x0.709%0.71%0.000%0%44-10.000000x-10.000000x> 10.0x1.000000x1.000000x0.712%0.71%0.000%0%45-10.000000x-10.000000x> 10.0x1.000000x1.000000x0.647%0.65%0.000%0%46-10.000000x-10.000000x> 10.0x1.000000x1.000000x3.906%3.91%0.000%0%47-10.000000x-10.000000x> 10.0x1.000000x1.000000x6.075%6.07%0.000%0%48-10.000000x-10.000000x> 10.0x1.000000x1.000000x1.826%1.83%0.000%0%49
F percentage of females in category
M percentage of males in category
# rank of county subdivision out of 49 by male-to-female sex ratio

Educational Attainment by County Subdivision in Minnesota

There are 2,761 county subdivisions in Minnesota. This section compares the Chester Township to the 50 most populous county subdivisions in Minnesota and to those entities that contain or substantially overlap with the Chester Township. The least populous of the compared county subdivisions has a population of 22,226.

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 the Chester Township, selected other county subdivisions in Minnesota, and entities that contain the Chester Township
0%5%10%15%Count#FaribaultAustinBrooklyn CenterBrooklyn CtrChester TownshipChesterSt. PaulUnited States of AmericaUnited StatesRichfieldMinneapolisMidwestBrooklyn ParkFridleyWest North Central490400Tract 490400WinonaMaplewoodInver Grove HeightsInver Grv HtsShakopeeBloomingtonSt. CloudCrystalMinnesotaOwatonnaCoon RapidsRosevilleWabasha CountyWabashaDuluthRochesterBurnsvilleRochester Metro AreaRochesterHastingsMankatoNew BrightonOakdaleChaskaMoorheadBlaineApple ValleyCottage GroveElk RiverSavageFarmingtonSt. Louis ParkSt. Louis PkAndoverRamseyEaganWhite Bear LakeWhite Bear LkPrior LakeRosemountLakevilleEden PrairieShoreviewChamplinWoodburyPlymouthMinnetonkaChanhassenMaple GroveEdina16.891386%16.891386%16.9%2,706116.529027%16.529027%16.5%2,682216.036673%16.036673%16.0%3,131314.930556%14.930556%14.9%4313.278342%13.278342%13.3%24,61324.6k413.020590%13.020590%13.0%27,818,38027.8M11.017383%11.017383%11.0%2,795510.958428%10.958428%11.0%29,34729.3k610.244520%10.244520%10.2%4,641,8354.64M10.167910%10.167910%10.2%5,01479.793424%9.793424%9.8%1,81189.174633%9.174633%9.2%1,278,0511.28M8.872582%8.872582%8.9%2667.914094%7.914094%7.9%1,20597.910263%7.910263%7.9%2,172107.772967%7.772967%7.8%1,831117.542599%7.542599%7.5%1,837127.540581%7.540581%7.5%4,729137.521396%7.521396%7.5%2,285147.446682%7.446682%7.4%1,250157.376055%7.376055%7.4%270,121270k7.196882%7.196882%7.2%1,237167.021578%7.021578%7.0%3,023176.821133%6.821133%6.8%1,681186.811536%6.811536%6.8%1,0256.456536%6.456536%6.5%3,427196.300465%6.300465%6.3%4,713206.224589%6.224589%6.2%2,572216.187739%6.187739%6.2%8,9016.110006%6.110006%6.1%952225.855251%5.855251%5.9%1,220235.686185%5.686185%5.7%873245.387794%5.387794%5.4%1,017255.326215%5.326215%5.3%858265.311348%5.311348%5.3%1,253275.219035%5.219035%5.2%2,154284.998974%4.998974%5.0%1,705294.937132%4.937132%4.9%1,123304.603205%4.603205%4.6%721314.312955%4.312955%4.3%812324.216911%4.216911%4.2%584334.052866%4.052866%4.1%1,429344.031177%4.031177%4.0%812353.724508%3.724508%3.7%610363.667395%3.667395%3.7%1,646373.645924%3.645924%3.6%631383.629499%3.629499%3.6%596393.564652%3.564652%3.6%526403.487209%3.487209%3.5%1,325413.205970%3.205970%3.2%1,392423.194655%3.194655%3.2%612433.108874%3.108874%3.1%488443.024874%3.024874%3.0%1,317452.612169%2.612169%2.6%1,406462.317073%2.317073%2.3%893472.309237%2.309237%2.3%368482.095945%2.095945%2.1%966492.079742%2.079742%2.1%74850
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 the Chester Township, selected other county subdivisions in Minnesota, and entities that contain the Chester Township
0%20%40%60%Count#EdinaEden PrairieChanhassenMinnetonkaWoodburyPlymouthSt. Louis ParkSt. Louis PkShoreviewMaple GroveEaganLakevilleMinneapolisNew BrightonRosevillePrior LakeChaskaRosemountRochesterApple ValleySavageBloomingtonSt. PaulBurnsvilleChamplinMoorheadRichfieldShakopeeMankatoRochester Metro AreaRochesterFarmingtonDuluthInver Grove HeightsInver Grv HtsWinonaMinnesotaAndoverWhite Bear LakeWhite Bear LkBlaineOakdaleElk RiverCottage GroveCrystalUnited States of AmericaUnited StatesWest North CentralMaplewoodBrooklyn ParkSt. CloudMidwestRamseyHastingsOwatonnaFridleyCoon Rapids490400Tract 490400AustinWabasha CountyWabashaBrooklyn CenterBrooklyn CtrFaribaultChester TownshipChester68.687093%68.687093%68.7%24,70424.7k162.175545%62.175545%62.2%26,99627.0k260.253514%60.253514%60.3%9,602358.886871%58.886871%58.9%22,69522.7k458.692207%58.692207%58.7%25,55425.6k557.488156%57.488156%57.5%30,94330.9k655.889276%55.889276%55.9%19,70619.7k754.601451%54.601451%54.6%10,46010.5k850.665018%50.665018%50.7%23,35123.4k950.398824%50.398824%50.4%22,62022.6k1048.278766%48.278766%48.3%18,34418.3k1147.670489%47.670489%47.7%127,663128k1247.267635%47.267635%47.3%7,2571346.445382%46.445382%46.4%11,44611.4k1445.472261%45.472261%45.5%7,4671544.248557%44.248557%44.2%7,1281644.076986%44.076986%44.1%6,5041743.718250%43.718250%43.7%32,70332.7k1843.384056%43.384056%43.4%14,79714.8k1943.102990%43.102990%43.1%8,1152040.791530%40.791530%40.8%25,58225.6k2139.969357%39.969357%40.0%74,08874.1k2238.511617%38.511617%38.5%15,91315.9k2337.561317%37.561317%37.6%5,8962437.153999%37.153999%37.2%8,7652536.544602%36.544602%36.5%9,2712636.468898%36.468898%36.5%8,8822736.144174%36.144174%36.1%7,5312835.991908%35.991908%36.0%51,77451.8k35.764315%35.764315%35.8%4,9532935.389427%35.389427%35.4%18,78418.8k3034.649346%34.649346%34.6%8,1623134.244056%34.244056%34.2%5,2143234.240609%34.240609%34.2%1,253,9371.25M34.091248%34.091248%34.1%6,8673333.633790%33.633790%33.6%5,8213433.485172%33.485172%33.5%13,82013.8k3531.447341%31.447341%31.4%5,9363630.760391%30.760391%30.8%4,8183730.616372%30.616372%30.6%6,9643830.400334%30.400334%30.4%5,1033930.315023%30.315023%30.3%64,767,78764.8M30.056536%30.056536%30.1%4,186,9564.19M30.016753%30.016753%30.0%8,2424029.516142%29.516142%29.5%14,55514.6k4129.150757%29.150757%29.2%8,8564228.952816%28.952816%29.0%13,118,64213.1M28.410062%28.410062%28.4%4,6534328.059816%28.059816%28.1%4,3724427.682104%27.682104%27.7%4,7584527.190136%27.190136%27.2%5,0284625.993543%25.993543%26.0%11,19111.2k4723.849233%23.849233%23.8%71521.410083%21.410083%21.4%3,4744821.238703%21.238703%21.2%3,19620.631018%20.631018%20.6%4,0284918.795256%18.795256%18.8%3,0115018.750000%18.750000%18.8%54
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 the Chester Township, selected other county subdivisions in Minnesota, and entities that contain the Chester Township
0%2%4%6%8%10%Count#EdinaRochesterShoreviewRosevilleMinnetonkaWoodburyEden PrairieMinneapolisRochester Metro AreaRochesterSt. PaulPlymouthSt. Louis ParkSt. Louis PkNew BrightonEaganDuluthWinonaMankatoChanhassenMaple GroveMaplewoodLakevilleChamplinMinnesotaSt. CloudUnited States of AmericaUnited StatesBloomingtonWest North CentralApple ValleyMidwestAustinChaskaWhite Bear LakeWhite Bear LkInver Grove HeightsInver Grv HtsMoorheadBlaineBurnsville490400Tract 490400Prior LakeRosemountFridleyShakopeeRichfieldSavageWabasha CountyWabashaOakdaleRamseyBrooklyn ParkCottage GroveCrystalOwatonnaAndoverFaribaultFarmingtonElk RiverCoon RapidsBrooklyn CenterBrooklyn CtrHastingsChester TownshipChester11.352388%11.352388%11.4%4,08318.768248%8.768248%8.8%6,55927.532495%7.532495%7.5%1,44337.458205%7.458205%7.5%1,83847.368967%7.368967%7.4%2,84057.214222%7.214222%7.2%3,14166.425758%6.425758%6.4%2,79076.241155%6.241155%6.2%16,71416.7k85.925658%5.925658%5.9%8,5245.920847%5.920847%5.9%10,97511.0k95.718532%5.718532%5.7%3,078105.249723%5.249723%5.2%1,851114.722204%4.722204%4.7%725124.400428%4.400428%4.4%1,975134.278609%4.278609%4.3%2,271144.236175%4.236175%4.2%645154.218660%4.218660%4.2%879163.852912%3.852912%3.9%614173.692855%3.692855%3.7%1,702183.590939%3.590939%3.6%986193.521423%3.521423%3.5%1,338203.510225%3.510225%3.5%551213.458748%3.458748%3.5%126,664127k3.367347%3.367347%3.4%1,023223.336158%3.336158%3.3%7,127,6737.13M3.138055%3.138055%3.1%1,968232.978981%2.978981%3.0%414,980415k2.958337%2.958337%3.0%1,009242.893416%2.893416%2.9%1,311,0191.31M2.884260%2.884260%2.9%468252.874170%2.874170%2.9%463262.692552%2.692552%2.7%466272.623535%2.623535%2.6%618282.564537%2.564537%2.6%605292.500485%2.500485%2.5%1,032302.405615%2.405615%2.4%994312.234823%2.234823%2.2%672.174045%2.174045%2.2%357322.134725%2.134725%2.1%315332.103612%2.103612%2.1%389342.003695%2.003695%2.0%488351.876306%1.876306%1.9%476361.859032%1.859032%1.9%350371.774322%1.774322%1.8%2671.769443%1.769443%1.8%334381.727928%1.727928%1.7%283391.673021%1.673021%1.7%825401.653038%1.653038%1.7%376411.638270%1.638270%1.6%275421.605771%1.605771%1.6%276431.558854%1.558854%1.6%314441.510612%1.510612%1.5%242451.509134%1.509134%1.5%209461.283279%1.283279%1.3%201471.272850%1.272850%1.3%548481.126818%1.126818%1.1%220491.123163%1.123163%1.1%175500.694444%0.694444%0.7%2
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 the Chester Township, selected other county subdivisions in Minnesota, and entities that contain the Chester Township
Female
Male
1x0x1x2xFM#ChesterFarmingtonTract 490400RamseyEden PrairieMoorheadOwatonnaMaplewoodElk RiverWabashaSt. Louis PkShoreviewShakopeeAustinHastingsFridleyCoon RapidsDuluthBrooklyn CtrRichfieldFaribaultWest North CentralMinnesotaMidwestRochesterPrior LakeChanhassenUnited StatesChamplinBlaineAndoverCrystalCottage GroveLakevilleRosemountWinonaRochesterBloomingtonSt. PaulBurnsvilleEaganMinneapolisInver Grv HtsMankatoApple ValleyMaple GroveChaskaSt. CloudWoodburyRosevilleOakdaleBrooklyn ParkEdinaPlymouthMinnetonkaWhite Bear LkSavageNew Brighton-1.000000x-1.000000x2.790353x2.790353x2.79x7.801%7.80%21.769%21.8%-1.000000x-1.000000x2.003868x2.003868x2.00x2.835%2.84%5.681%5.68%1-1.000000x-1.000000x1.611979x1.611979x1.61x6.770%6.77%10.914%10.9%-1.000000x-1.000000x1.569928x1.569928x1.57x2.887%2.89%4.532%4.53%2-1.000000x-1.000000x1.513482x1.513482x1.51x2.564%2.56%3.881%3.88%3-1.000000x-1.000000x1.505859x1.505859x1.51x4.258%4.26%6.411%6.41%4-1.000000x-1.000000x1.416944x1.416944x1.42x5.995%6.00%8.495%8.49%5-1.000000x-1.000000x1.413357x1.413357x1.41x6.619%6.62%9.355%9.36%6-1.000000x-1.000000x1.411657x1.411657x1.41x3.821%3.82%5.394%5.39%7-1.000000x-1.000000x1.398839x1.398839x1.40x5.688%5.69%7.957%7.96%-1.000000x-1.000000x1.398134x1.398134x1.40x3.411%3.41%4.769%4.77%8-1.000000x-1.000000x1.317049x1.317049x1.32x2.784%2.78%3.666%3.67%9-1.000000x-1.000000x1.299444x1.299444x1.30x6.595%6.59%8.569%8.57%10-1.000000x-1.000000x1.289646x1.289646x1.29x14.496%14.5%18.694%18.7%11-1.000000x-1.000000x1.288751x1.288751x1.29x5.348%5.35%6.892%6.89%12-1.000000x-1.000000x1.269201x1.269201x1.27x8.625%8.62%10.946%10.9%13-1.000000x-1.000000x1.245609x1.245609x1.25x6.293%6.29%7.839%7.84%14-1.000000x-1.000000x1.237646x1.237646x1.24x5.794%5.79%7.171%7.17%15-1.000000x-1.000000x1.171442x1.171442x1.17x14.825%14.8%17.367%17.4%16-1.000000x-1.000000x1.163628x1.163628x1.16x10.209%10.2%11.880%11.9%17-1.000000x-1.000000x1.151611x1.151611x1.15x15.625%15.6%17.994%18.0%18-1.000000x-1.000000x1.137506x1.137506x1.14x8.598%8.60%9.780%9.78%-1.000000x-1.000000x1.136388x1.136388x1.14x6.913%6.91%7.856%7.86%-1.000000x-1.000000x1.127915x1.127915x1.13x9.647%9.65%10.881%10.9%-1.000000x-1.000000x1.127663x1.127663x1.13x5.826%5.83%6.570%6.57%-1.000000x-1.000000x1.126917x1.126917x1.13x3.416%3.42%3.849%3.85%19-1.000000x-1.000000x1.122496x1.122496x1.12x2.180%2.18%2.448%2.45%20-1.000000x-1.000000x1.109070x1.109070x1.11x12.369%12.4%13.719%13.7%-1.000000x-1.000000x1.101837x1.101837x1.10x2.962%2.96%3.263%3.26%21-1.000000x-1.000000x1.079970x1.079970x1.08x5.025%5.03%5.427%5.43%22-1.000000x-1.000000x1.079583x1.079583x1.08x3.877%3.88%4.185%4.19%23-1.000000x-1.000000x1.078552x1.078552x1.08x7.176%7.18%7.740%7.74%24-1.000000x-1.000000x1.037512x1.037512x1.04x4.848%4.85%5.030%5.03%25-1.000000x-1.000000x1.032815x1.032815x1.03x3.432%3.43%3.544%3.54%26-1.000159x-1.000159x1.00x1.000000x1.000000x3.565%3.56%3.564%3.56%27-1.021534x-1.021534x1.02x1.000000x1.000000x7.996%8.00%7.828%7.83%28-1.041504x-1.041504x1.04x1.000000x1.000000x6.423%6.42%6.167%6.17%29-1.052680x-1.052680x1.05x1.000000x1.000000x7.724%7.72%7.337%7.34%30-1.060004x-1.060004x1.06x1.000000x1.000000x13.651%13.7%12.879%12.9%31-1.063523x-1.063523x1.06x1.000000x1.000000x6.407%6.41%6.024%6.02%32-1.064491x-1.064491x1.06x1.000000x1.000000x3.778%3.78%3.549%3.55%33-1.092939x-1.092939x1.09x1.000000x1.000000x11.450%11.4%10.476%10.5%34-1.106734x-1.106734x1.11x1.000000x1.000000x8.152%8.15%7.366%7.37%35-1.109043x-1.109043x1.11x1.000000x1.000000x6.154%6.15%5.549%5.55%36-1.118002x-1.118002x1.12x1.000000x1.000000x5.261%5.26%4.705%4.71%37-1.121003x-1.121003x1.12x1.000000x1.000000x2.209%2.21%1.971%1.97%38-1.127409x-1.127409x1.13x1.000000x1.000000x5.637%5.64%5.000%5.00%39-1.137927x-1.137927x1.14x1.000000x1.000000x8.019%8.02%7.047%7.05%40-1.150185x-1.150185x1.15x1.000000x1.000000x3.224%3.22%2.803%2.80%41-1.159893x-1.159893x1.16x1.000000x1.000000x7.291%7.29%6.286%6.29%42-1.170896x-1.170896x1.17x1.000000x1.000000x5.763%5.76%4.922%4.92%43-1.209052x-1.209052x1.21x1.000000x1.000000x11.076%11.1%9.161%9.16%44-1.212019x-1.212019x1.21x1.000000x1.000000x2.263%2.26%1.867%1.87%45-1.236671x-1.236671x1.24x1.000000x1.000000x2.877%2.88%2.327%2.33%46-1.242432x-1.242432x1.24x1.000000x1.000000x2.550%2.55%2.053%2.05%47-1.253553x-1.253553x1.25x1.000000x1.000000x4.017%4.02%3.204%3.20%48-1.284305x-1.284305x1.28x1.000000x1.000000x4.851%4.85%3.777%3.78%49-1.669127x-1.669127x1.67x1.000000x1.000000x7.046%7.05%4.221%4.22%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#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 the Chester Township, selected other county subdivisions in Minnesota, and entities that contain the Chester Township
Female
Male
0x5x10xFM#ChesterWinonaWhite Bear LkRosemountAndoverShoreviewMaple GroveOakdaleShakopeeEdinaFridleyEden PrairieOwatonnaMankatoHastingsRamseyMaplewoodMinnetonkaNew BrightonWabashaRochesterMoorheadRochesterWoodburyMidwestPlymouthWest North CentralRosevilleRichfieldChaskaSt. CloudAustinCrystalUnited StatesCoon RapidsCottage GroveMinnesotaDuluthSt. Louis PkFaribaultInver Grv HtsEaganBrooklyn CtrSt. PaulPrior LakeFarmingtonSavageBrooklyn ParkLakevilleBlaineMinneapolisChamplinApple ValleyBurnsvilleBloomingtonChanhassenTract 490400Elk River-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%1.361%1.36%-1.000000x-1.000000x3.549966x3.549966x3.55x1.887%1.89%6.698%6.70%1-1.000000x-1.000000x2.892036x2.892036x2.89x1.445%1.45%4.179%4.18%2-1.000000x-1.000000x2.517561x2.517561x2.52x1.236%1.24%3.112%3.11%3-1.000000x-1.000000x2.444960x2.444960x2.44x0.905%0.90%2.212%2.21%4-1.000000x-1.000000x2.158302x2.158302x2.16x4.894%4.89%10.562%10.6%5-1.000000x-1.000000x2.044267x2.044267x2.04x2.469%2.47%5.048%5.05%6-1.000000x-1.000000x2.027520x2.027520x2.03x1.214%1.21%2.461%2.46%7-1.000000x-1.000000x1.989459x1.989459x1.99x1.358%1.36%2.702%2.70%8-1.000000x-1.000000x1.952817x1.952817x1.95x7.877%7.88%15.382%15.4%9-1.000000x-1.000000x1.877228x1.877228x1.88x1.459%1.46%2.739%2.74%10-1.000000x-1.000000x1.843636x1.843636x1.84x4.554%4.55%8.396%8.40%11-1.000000x-1.000000x1.842122x1.842122x1.84x1.143%1.14%2.106%2.11%12-1.000000x-1.000000x1.831940x1.831940x1.83x2.992%2.99%5.480%5.48%13-1.000000x-1.000000x1.824245x1.824245x1.82x0.798%0.80%1.456%1.46%14-1.000000x-1.000000x1.818953x1.818953x1.82x1.219%1.22%2.218%2.22%15-1.000000x-1.000000x1.816195x1.816195x1.82x2.593%2.59%4.709%4.71%16-1.000000x-1.000000x1.778120x1.778120x1.78x5.399%5.40%9.600%9.60%17-1.000000x-1.000000x1.712068x1.712068x1.71x3.517%3.52%6.021%6.02%18-1.000000x-1.000000x1.674879x1.674879x1.67x1.330%1.33%2.227%2.23%-1.000000x-1.000000x1.656189x1.656189x1.66x6.670%6.67%11.046%11.0%19-1.000000x-1.000000x1.655114x1.655114x1.66x1.942%1.94%3.214%3.21%20-1.000000x-1.000000x1.652184x1.652184x1.65x4.500%4.50%7.434%7.43%-1.000000x-1.000000x1.596470x1.596470x1.60x5.629%5.63%8.987%8.99%21-1.000000x-1.000000x1.589934x1.589934x1.59x2.251%2.25%3.579%3.58%-1.000000x-1.000000x1.583257x1.583257x1.58x4.465%4.46%7.069%7.07%22-1.000000x-1.000000x1.572017x1.572017x1.57x2.329%2.33%3.662%3.66%-1.000000x-1.000000x1.559618x1.559618x1.56x5.912%5.91%9.220%9.22%23-1.000000x-1.000000x1.551084x1.551084x1.55x1.481%1.48%2.298%2.30%24-1.000000x-1.000000x1.548982x1.548982x1.55x2.267%2.27%3.511%3.51%25-1.000000x-1.000000x1.544665x1.544665x1.54x2.633%2.63%4.067%4.07%26-1.000000x-1.000000x1.544387x1.544387x1.54x2.283%2.28%3.525%3.53%27-1.000000x-1.000000x1.532997x1.532997x1.53x1.305%1.30%2.000%2.00%28-1.000000x-1.000000x1.526215x1.526215x1.53x2.660%2.66%4.060%4.06%-1.000000x-1.000000x1.506415x1.506415x1.51x1.028%1.03%1.548%1.55%29-1.000000x-1.000000x1.492523x1.492523x1.49x1.332%1.33%1.989%1.99%30-1.000000x-1.000000x1.481015x1.481015x1.48x2.798%2.80%4.144%4.14%-1.000000x-1.000000x1.465286x1.465286x1.47x3.496%3.50%5.123%5.12%31-1.000000x-1.000000x1.442441x1.442441x1.44x4.342%4.34%6.262%6.26%32-1.000000x-1.000000x1.419491x1.419491x1.42x1.234%1.23%1.752%1.75%33-1.000000x-1.000000x1.410631x1.410631x1.41x2.190%2.19%3.089%3.09%34-1.000000x-1.000000x1.383309x1.383309x1.38x3.713%3.71%5.137%5.14%35-1.000000x-1.000000x1.367180x1.367180x1.37x0.959%0.96%1.311%1.31%36-1.000000x-1.000000x1.274509x1.274509x1.27x5.228%5.23%6.663%6.66%37-1.000000x-1.000000x1.248780x1.248780x1.25x1.936%1.94%2.418%2.42%38-1.000000x-1.000000x1.247281x1.247281x1.25x1.347%1.35%1.681%1.68%39-1.000000x-1.000000x1.240291x1.240291x1.24x1.659%1.66%2.058%2.06%40-1.000000x-1.000000x1.220015x1.220015x1.22x1.515%1.52%1.848%1.85%41-1.000000x-1.000000x1.179960x1.179960x1.18x3.234%3.23%3.816%3.82%42-1.000000x-1.000000x1.160580x1.160580x1.16x2.321%2.32%2.693%2.69%43-1.000000x-1.000000x1.124528x1.124528x1.12x5.872%5.87%6.603%6.60%44-1.000000x-1.000000x1.068161x1.068161x1.07x3.397%3.40%3.629%3.63%45-1.000000x-1.000000x1.031011x1.031011x1.03x2.916%2.92%3.006%3.01%46-1.000000x-1.000000x1.023622x1.023622x1.02x2.379%2.38%2.435%2.44%47-1.000000x-1.000000x1.018945x1.018945x1.02x3.110%3.11%3.169%3.17%48-1.019385x-1.019385x1.02x1.000000x1.000000x3.889%3.89%3.815%3.81%49-1.195885x-1.195885x1.20x1.000000x1.000000x2.437%2.44%2.038%2.04%-2.497130x-2.497130x2.50x1.000000x1.000000x1.828%1.83%0.732%0.73%50
F percentage of females in category
M percentage of males in category
# rank of county subdivision out of 50 by male-to-female sex ratio

Educational Attainment by County Subdivision in the Midwest

There are 19,478 county subdivisions in the Midwest. This section compares the Chester Township to the 50 most populous county subdivisions in the Midwest and to those entities that contain or substantially overlap with the Chester Township. 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 the Chester Township, selected other county subdivisions in the Midwest, and entities that contain the Chester Township
0%10%20%30%Count#Aurora TownshipAuroraCenter TownshipCtrKansas CityClevelandWayne TownshipWayneDetroitMilwaukeeNorth TownshipNDaytonChicagoProviso TownshipProvisoRockford TownshipRockfordSt. LouisWarrenChester TownshipChesterGrand RapidsToledoBlue TownshipCincinnatiAkronSt. PaulSterling HeightsSterling HtsUnited States of AmericaUnited StatesThornton TownshipThorntonWichitaKaw TownshipOmahaBloomingdale TownshipBloomingdaleColumbusMaine TownshipMaineTopekaMinneapolisSpringfield TownshipSpringfieldWorth TownshipWorthMidwestLawrence TownshipLawrenceSioux FallsWest North Central490400Tract 490400Capital TownshipCapitalWheeling TownshipWheelingPalatine TownshipPalatineSchaumburg TownshipSchaumburgMinnesotaLincolnWabasha CountyWabashaWashington TownshipWashingtonOlatheRochester Metro AreaRochesterFargoCedar 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%14,05914.1k1414.930556%14.930556%14.9%4314.563179%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%31,23131.2k2312.455744%12.455744%12.5%15,16315.2k2412.198899%12.198899%12.2%35,05035.1k2512.171847%12.171847%12.2%9,3752611.376979%11.376979%11.4%60,83160.8k2711.132206%11.132206%11.1%10,96511.0k2811.032803%11.032803%11.0%9,3772910.958428%10.958428%11.0%29,34729.3k3010.767091%10.767091%10.8%11,14911.1k3110.678962%10.678962%10.7%11,17511.2k3210.244520%10.244520%10.2%4,641,8354.64M10.179618%10.179618%10.2%8,161339.702326%9.702326%9.7%9,123349.174633%9.174633%9.2%1,278,0511.28M8.872582%8.872582%8.9%2668.623103%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%7,226387.376055%7.376055%7.4%270,121270k7.092309%7.092309%7.1%11,88611.9k396.811536%6.811536%6.8%1,0256.804680%6.804680%6.8%6,403406.424130%6.424130%6.4%5,331416.187739%6.187739%6.2%8,9016.055621%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 the Chester Township, selected other county subdivisions in the Midwest, and entities that contain the Chester Township
0%20%40%60%Count#Ann ArborOverland ParkMilton TownshipMiltonLisle TownshipLisleMadisonDowners Grove TownshipDowners GrvWashington TownshipWashingtonPalatine TownshipPalatineYork TownshipMinneapolisOlatheWheeling TownshipWheelingSchaumburg TownshipSchaumburgKaw TownshipSt. PaulMaine TownshipMaineFargoLincolnLawrence TownshipLawrenceChicagoCapital TownshipCapitalRochester Metro AreaRochesterColumbusOmahaMinnesotaCincinnatiSt. LouisGrand RapidsBloomingdale TownshipBloomingdaleCedar RapidsUnited States of AmericaUnited StatesSioux FallsWest North CentralMidwestWichitaSterling HeightsSterling HtsTopekaSpringfield TownshipSpringfieldProviso TownshipProvisoWorth TownshipWorth490400Tract 490400MilwaukeeRockford TownshipRockfordWabasha CountyWabashaAkronCenter TownshipCtrNorth TownshipNThornton TownshipThorntonChester TownshipChesterToledoDaytonWarrenWayne TownshipWayneKansas CityClevelandAurora TownshipAuroraBlue TownshipDetroit72.810169%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%28,78028.8k2135.991908%35.991908%36.0%51,77451.8k34.685843%34.685843%34.7%185,460185k2234.651487%34.651487%34.7%99,56199.6k2334.240609%34.240609%34.2%1,253,9371.25M33.783048%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%28,45328.5k2930.056536%30.056536%30.1%4,186,9564.19M28.952816%28.952816%29.0%13,118,64213.1M28.877567%28.877567%28.9%71,75771.8k3027.532180%27.532180%27.5%25,60325.6k3127.007248%27.007248%27.0%22,95423.0k3226.964567%26.964567%27.0%27,92127.9k3326.237989%26.237989%26.2%27,03327.0k3425.217641%25.217641%25.2%26,38926.4k3523.849233%23.849233%23.8%71523.517740%23.517740%23.5%85,81285.8k3621.592552%21.592552%21.6%25,23525.2k3721.238703%21.238703%21.2%3,19620.213821%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%21,01221.0k4118.750000%18.750000%18.8%5418.048021%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%14,78814.8k4516.167409%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%59,72359.7k50
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older with a bachelor's degree or higher..

Very Advanced Degrees by County Subdivision#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 the Chester Township, selected other county subdivisions in the Midwest, and entities that contain the Chester Township
0%5%10%15%Count#Ann ArborMadisonDowners Grove TownshipDowners GrvWashington TownshipWashingtonMinneapolisYork TownshipOverland ParkLisle TownshipLisleRochester Metro AreaRochesterSt. PaulKaw TownshipMilton TownshipMiltonSt. LouisCincinnatiLincolnChicagoFargoCapital TownshipCapitalOmahaMaine TownshipMainePalatine TownshipPalatineMinnesotaWheeling TownshipWheelingColumbusUnited States of AmericaUnited StatesTopekaGrand RapidsLawrence TownshipLawrenceWest North CentralSpringfield TownshipSpringfieldCedar RapidsMidwestSioux FallsOlatheCenter TownshipCtrSchaumburg TownshipSchaumburgWichita490400Tract 490400Proviso TownshipProvisoAkronBloomingdale TownshipBloomingdaleRockford TownshipRockfordMilwaukeeWorth TownshipWorthClevelandWabasha CountyWabashaToledoNorth TownshipNSterling HeightsSterling HtsKansas CityDetroitDaytonWayne TownshipWayneWarrenBlue TownshipAurora TownshipAuroraThornton TownshipThorntonChester TownshipChester17.877867%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%4,83485.925658%5.925658%5.9%8,5245.920847%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%2,782203.458748%3.458748%3.5%126,664127k3.407574%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%2,472252.978981%2.978981%3.0%414,980415k2.911721%2.911721%2.9%3,015262.905776%2.905776%2.9%2,477272.893416%2.893416%2.9%1,311,0191.31M2.841677%2.841677%2.8%2,672282.830666%2.830666%2.8%2,349292.602914%2.602914%2.6%2,576302.551250%2.551250%2.6%2,382312.519246%2.519246%2.5%6,260322.234823%2.234823%2.2%672.213918%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%4,911391.774322%1.774322%1.8%2671.642065%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%1,040461.047058%1.047058%1.0%963470.997751%0.997751%1.0%1,069480.936111%0.936111%0.9%834490.876686%0.876686%0.9%971500.694444%0.694444%0.7%2
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 the Chester Township, selected other county subdivisions in the Midwest, and entities that contain the Chester Township
Female
Male
1x0x1x2xFM#ChesterTract 490400WabashaCedar RapidsLincolnDetroitOmahaToledoThorntonKansas CityMadisonLawrenceFargoProvisoRockfordBlue TownshipWest North CentralMinnesotaWayneMidwestRochesterTopekaMilwaukeeKaw TownshipDaytonSioux FallsUnited StatesOlatheWorthNOverland ParkAuroraWheelingGrand RapidsSchaumburgChicagoWichitaColumbusClevelandPalatineCapitalWarrenSpringfieldYork TownshipSt. LouisWashingtonBloomingdaleCtrCincinnatiAkronAnn ArborSt. PaulLisleMinneapolisSterling HtsDowners GrvMiltonMaine-1.000000x-1.000000x2.790353x2.790353x2.79x7.801%7.80%21.769%21.8%-1.000000x-1.000000x1.611979x1.611979x1.61x6.770%6.77%10.914%10.9%-1.000000x-1.000000x1.398839x1.398839x1.40x5.688%5.69%7.957%7.96%-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-1.000000x1.203250x1.203250x1.20x11.909%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-1.000000x1.137506x1.137506x1.14x8.598%8.60%9.780%9.78%-1.000000x-1.000000x1.136388x1.136388x1.14x6.913%6.91%7.856%7.86%-1.000000x-1.000000x1.132245x1.132245x1.13x19.779%19.8%22.395%22.4%14-1.000000x-1.000000x1.127915x1.127915x1.13x9.647%9.65%10.881%10.9%-1.000000x-1.000000x1.127663x1.127663x1.13x5.826%5.83%6.570%6.57%-1.000000x-1.000000x1.125507x1.125507x1.13x10.423%10.4%11.732%11.7%15-1.000000x-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
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 the Chester Township, selected other county subdivisions in the Midwest, and entities that contain the Chester Township
Female
Male
0x5x10xFM#ChesterRockfordNDaytonSioux FallsCapitalLawrenceDowners GrvAkronLisleWichitaYork TownshipMaineWarrenWheelingBlue TownshipSpringfieldOverland ParkMiltonGrand RapidsOlatheWabashaOmahaRochesterFargoWashingtonLincolnMidwestBloomingdaleWest North CentralKansas CityAuroraUnited StatesAnn ArborTopekaMinnesotaSterling HtsPalatineSchaumburgColumbusMadisonKaw TownshipMilwaukeeCedar RapidsClevelandCincinnatiSt. PaulSt. LouisChicagoWayneCtrToledoMinneapolisWorthDetroitProvisoTract 490400Thornton-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%1.361%1.36%-1.000000x-1.000000x2.117268x2.117268x2.12x1.353%1.35%2.866%2.87%1-1.000000x-1.000000x2.111054x2.111054x2.11x1.033%1.03%2.181%2.18%2-1.000000x-1.000000x1.989047x1.989047x1.99x0.860%0.86%1.711%1.71%3-1.000000x-1.000000x1.962539x1.962539x1.96x1.928%1.93%3.783%3.78%4-1.000000x-1.000000x1.901348x1.901348x1.90x2.990%2.99%5.686%5.69%5-1.000000x-1.000000x1.879271x1.879271x1.88x2.206%2.21%4.146%4.15%6-1.000000x-1.000000x1.852471x1.852471x1.85x5.456%5.46%10.107%10.1%7-1.000000x-1.000000x1.846298x1.846298x1.85x1.550%1.55%2.862%2.86%8-1.000000x-1.000000x1.815266x1.815266x1.82x4.271%4.27%7.754%7.75%9-1.000000x-1.000000x1.792728x1.792728x1.79x1.819%1.82%3.261%3.26%10-1.000000x-1.000000x1.792314x1.792314x1.79x4.498%4.50%8.062%8.06%11-1.000000x-1.000000x1.788417x1.788417x1.79x2.939%2.94%5.256%5.26%12-1.000000x-1.000000x1.768853x1.768853x1.77x0.769%0.77%1.361%1.36%13-1.000000x-1.000000x1.766097x1.766097x1.77x2.485%2.48%4.389%4.39%14-1.000000x-1.000000x1.761699x1.761699x1.76x0.737%0.74%1.298%1.30%15-1.000000x-1.000000x1.751445x1.751445x1.75x2.146%2.15%3.759%3.76%16-1.000000x-1.000000x1.732234x1.732234x1.73x4.415%4.41%7.647%7.65%17-1.000000x-1.000000x1.695067x1.695067x1.70x4.357%4.36%7.385%7.38%18-1.000000x-1.000000x1.689013x1.689013x1.69x2.382%2.38%4.023%4.02%19-1.000000x-1.000000x1.678153x1.678153x1.68x2.131%2.13%3.576%3.58%20-1.000000x-1.000000x1.674879x1.674879x1.67x1.330%1.33%2.227%2.23%-1.000000x-1.000000x1.669388x1.669388x1.67x3.061%3.06%5.110%5.11%21-1.000000x-1.000000x1.652184x1.652184x1.65x4.500%4.50%7.434%7.43%-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-1.000000x1.596978x1.596978x1.60x3.524%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-1.000000x1.572017x1.572017x1.57x2.329%2.33%3.662%3.66%-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-1.000000x1.481015x1.481015x1.48x2.798%2.80%4.144%4.14%-1.000000x-1.000000x1.476996x1.476996x1.48x1.170%1.17%1.728%1.73%30-1.000000x-1.000000x1.457167x1.457167x1.46x2.851%2.85%4.154%4.15%31-1.000000x-1.000000x1.436165x1.436165x1.44x2.115%2.11%3.037%3.04%32-1.000000x-1.000000x1.413654x1.413654x1.41x2.801%2.80%3.959%3.96%33-1.000000x-1.000000x1.387878x1.387878x1.39x7.705%7.70%10.693%10.7%34-1.000000x-1.000000x1.373250x1.373250x1.37x4.975%4.97%6.832%6.83%35-1.000000x-1.000000x1.368590x1.368590x1.37x1.742%1.74%2.385%2.38%36-1.000000x-1.000000x1.346658x1.346658x1.35x2.491%2.49%3.354%3.35%37-1.000000x-1.000000x1.286599x1.286599x1.29x1.699%1.70%2.186%2.19%38-1.000000x-1.000000x1.280610x1.280610x1.28x4.179%4.18%5.351%5.35%39-1.000000x-1.000000x1.274509x1.274509x1.27x5.228%5.23%6.663%6.66%40-1.000000x-1.000000x1.273345x1.273345x1.27x4.319%4.32%5.500%5.50%41-1.000000x-1.000000x1.238186x1.238186x1.24x4.026%4.03%4.985%4.99%42-1.000000x-1.000000x1.223931x1.223931x1.22x1.068%1.07%1.307%1.31%43-1.000000x-1.000000x1.213574x1.213574x1.21x2.357%2.36%2.860%2.86%44-1.000000x-1.000000x1.141406x1.141406x1.14x1.539%1.54%1.757%1.76%45-1.000000x-1.000000x1.124528x1.124528x1.12x5.872%5.87%6.603%6.60%46-1.000000x-1.000000x1.084697x1.084697x1.08x1.883%1.88%2.042%2.04%47-1.000000x-1.000000x1.046557x1.046557x1.05x1.291%1.29%1.351%1.35%48-1.000000x-1.000000x1.042857x1.042857x1.04x2.171%2.17%2.264%2.26%49-1.195885x-1.195885x1.20x1.000000x1.000000x2.437%2.44%2.038%2.04%-1.706858x-1.706858x1.71x1.000000x1.000000x1.072%1.07%0.628%0.63%50
F percentage of females in category
M percentage of males in category
# rank of county subdivision out of 50 by male-to-female sex ratio

Educational Attainment by County Subdivision in the United States

There are 35,600 county subdivisions in the United States. This section compares the Chester Township to the 50 most populous county subdivisions in the United States and to those entities that contain or substantially overlap with the Chester Township. 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 the Chester Township, selected other county subdivisions in the United States, and entities that contain the Chester Township
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 VegasPhoenixChester TownshipChesterBostonSacramentoOrlandoAustinDenverUnited States of AmericaUnited StatesManhattanSan DiegoTampaSan JoseSan FranciscoTucsonAlbuquerqueTownship 1:Charlotte1, CharlotteColumbusTulsaSalt Lake CitySalt Lk CityTown of HempsteadHempsteadMidwestNorthwest HarrisNW HarrisWashingtonAtlantaWest North Central490400Tract 490400SeattleNortheast TarrantNE TarrantMinnesotaWabasha CountyWabashaRochester Metro AreaRochesterPlanoSeattle 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%308,569309k2614.930556%14.930556%14.9%4314.325556%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%84,02484.0k3612.262851%12.262851%12.3%70,40970.4k3712.089143%12.089143%12.1%52,21752.2k3811.553484%11.553484%11.6%61,37861.4k3911.376979%11.376979%11.4%60,83160.8k4011.299086%11.299086%11.3%43,65343.7k4110.435356%10.435356%10.4%64,29464.3k4210.384134%10.384134%10.4%54,23054.2k4310.244520%10.244520%10.2%4,641,8354.64M10.135583%10.135583%10.1%47,67947.7k4410.045421%10.045421%10.0%46,51046.5k459.538552%9.538552%9.5%37,37337.4k469.174633%9.174633%9.2%1,278,0511.28M8.872582%8.872582%8.9%2668.833573%8.833573%8.8%66,22066.2k478.418271%8.418271%8.4%31,44331.4k487.376055%7.376055%7.4%270,121270k6.811536%6.811536%6.8%1,0256.187739%6.187739%6.2%8,9015.714681%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 the Chester Township, selected other county subdivisions in the United States, and entities that contain the Chester Township
0%20%40%60%Count#ManhattanSeattle EastWashingtonSan FranciscoPlanoSan JoseAtlantaSeattleBostonDenverAustinTownship 1:Charlotte1, CharlotteTown of HempsteadHempsteadSan DiegoNortheast TarrantNE TarrantNorthwest HarrisNW HarrisChicagoRochester Metro AreaRochesterColumbusLos AngelesMinnesotaBrooklynSan Fernando ValleySan Fernando VlyNortheast DallasNE DallasSalt Lake CitySalt Lk CityAlbuquerqueTampaTucsonOceanside-EscondidoOceanside-Escond…TulsaQueensUnited States of AmericaUnited StatesHoustonWest North CentralBaltimoreLong Beach-LakewoodLong Bch-LakewoodMidwestPhoenixOrlandoAnaheim-Santa Ana-Garden GroveAnaheim-Santa An…SacramentoEast San Gabriel ValleyE San Gabriel VlyOntarioPhiladelphiaMiamiFort Worth490400Tract 490400Southwest DallasSW DallasMilwaukeeFresnoLas VegasWabasha CountyWabashaEl PasoBronxChester TownshipChesterSan BernardinoSan Antonio CentralSan Antonio CntrlDetroit60.434640%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%669,666670k1735.991908%35.991908%36.0%51,77451.8k34.685843%34.685843%34.7%185,460185k1834.593243%34.593243%34.6%604,693605k1934.240609%34.240609%34.2%1,253,9371.25M34.081468%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%627,520628k3030.056536%30.056536%30.1%4,186,9564.19M29.719611%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%112,142112k3428.412939%28.412939%28.4%312,038312k3528.231204%28.231204%28.2%209,283209k3627.276345%27.276345%27.3%170,682171k3726.758411%26.758411%26.8%111,532112k3826.349720%26.349720%26.3%272,786273k3926.011156%26.011156%26.0%178,455178k4024.665414%24.665414%24.7%131,349131k4123.849233%23.849233%23.8%71523.764821%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%271,037271k4521.238703%21.238703%21.2%3,19621.071885%21.071885%21.1%72,12072.1k4619.131504%19.131504%19.1%173,169173k4718.750000%18.750000%18.8%5416.375473%16.375473%16.4%80,59580.6k4814.929012%14.929012%14.9%65,34165.3k4913.833543%13.833543%13.8%59,72359.7k50
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older with a bachelor's degree or higher..

Very Advanced Degrees by County Subdivision#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 the Chester Township, selected other county subdivisions in the United States, and entities that contain the Chester Township
0%5%10%Count#WashingtonManhattanSan FranciscoBostonAtlantaSeattleSan JoseSeattle EastRochester Metro AreaRochesterDenverSan DiegoAustinBaltimoreLos AngelesAlbuquerquePlanoChicagoTucsonTown of HempsteadHempsteadTampaMiamiNortheast DallasNE DallasSalt Lake CitySalt Lk CityHoustonPhiladelphiaSan Fernando ValleySan Fernando VlyTownship 1:Charlotte1, CharlotteOceanside-EscondidoOceanside-Escond…MinnesotaBrooklynSacramentoColumbusUnited States of AmericaUnited StatesTulsaPhoenixLong Beach-LakewoodLong Bch-LakewoodWest North CentralMidwestOrlandoFresnoAnaheim-Santa Ana-Garden GroveAnaheim-Santa An…QueensNorthwest HarrisNW HarrisNortheast TarrantNE TarrantEast San Gabriel ValleyE San Gabriel VlyOntario490400Tract 490400Fort WorthLas VegasMilwaukeeSan BernardinoSan Antonio CentralSan Antonio CntrlWabasha CountyWabashaEl PasoSouthwest DallasSW DallasBronxDetroitChester TownshipChester12.461852%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%24,96825.0k85.925658%5.925658%5.9%8,5245.725842%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%15,21115.2k273.458748%3.458748%3.5%126,664127k3.384967%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%11,33911.3k332.978981%2.978981%3.0%414,980415k2.893416%2.893416%2.9%1,311,0191.31M2.893233%2.893233%2.9%11,37011.4k342.828959%2.828959%2.8%11,83311.8k352.763004%2.763004%2.8%30,34430.3k362.756960%2.756960%2.8%44,96545.0k372.682967%2.682967%2.7%12,62112.6k382.630994%2.630994%2.6%9,827392.484535%2.484535%2.5%15,54715.5k402.324315%2.324315%2.3%9,688412.234823%2.234823%2.2%672.173239%2.173239%2.2%11,57311.6k422.155077%2.155077%2.2%26,91426.9k432.043126%2.043126%2.0%7,455441.807306%1.807306%1.8%8,895451.792414%1.792414%1.8%7,845461.774322%1.774322%1.8%2671.745764%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%5,693500.694444%0.694444%0.7%2
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 the Chester Township, selected other county subdivisions in the United States, and entities that contain the Chester Township
Female
Male
1x0x1x2xFM#ChesterTract 490400Wabasha1, CharlotteDetroitBaltimoreTulsaSW DallasWest North CentralMinnesotaMidwestRochesterFresnoMilwaukeeUnited 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 Paso-1.000000x-1.000000x2.790353x2.790353x2.79x7.801%7.80%21.769%21.8%-1.000000x-1.000000x1.611979x1.611979x1.61x6.770%6.77%10.914%10.9%-1.000000x-1.000000x1.398839x1.398839x1.40x5.688%5.69%7.957%7.96%-1.000000x-1.000000x1.285784x1.285784x1.29x10.185%10.2%13.096%13.1%1-1.000000x-1.000000x1.237056x1.237056x1.24x18.951%19.0%23.443%23.4%2-1.000000x-1.000000x1.179669x1.179669x1.18x15.289%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-1.000000x1.137506x1.137506x1.14x8.598%8.60%9.780%9.78%-1.000000x-1.000000x1.136388x1.136388x1.14x6.913%6.91%7.856%7.86%-1.000000x-1.000000x1.127915x1.127915x1.13x9.647%9.65%10.881%10.9%-1.000000x-1.000000x1.127663x1.127663x1.13x5.826%5.83%6.570%6.57%-1.000000x-1.000000x1.127206x1.127206x1.13x20.830%20.8%23.479%23.5%6-1.000000x-1.000000x1.123984x1.123984x1.12x16.526%16.5%18.574%18.6%7-1.000000x-1.000000x1.109070x1.109070x1.11x12.369%12.4%13.719%13.7%-1.000000x-1.000000x1.099797x1.099797x1.10x19.814%19.8%21.791%21.8%8-1.000000x-1.000000x1.099188x1.099188x1.10x20.902%20.9%22.975%23.0%9-1.000000x-1.000000x1.092101x1.092101x1.09x9.951%9.95%10.868%10.9%10-1.000000x-1.000000x1.090284x1.090284x1.09x13.111%13.1%14.294%14.3%11-1.000000x-1.000000x1.090163x1.090163x1.09x16.700%16.7%18.206%18.2%12-1.000000x-1.000000x1.088515x1.088515x1.09x16.417%16.4%17.871%17.9%13-1.000000x-1.000000x1.081887x1.081887x1.08x26.536%26.5%28.709%28.7%14-1.000000x-1.000000x1.078150x1.078150x1.08x13.148%13.1%14.176%14.2%15-1.000000x-1.000000x1.073220x1.073220x1.07x9.215%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
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 the Chester Township, selected other county subdivisions in the United States, and entities that contain the Chester Township
Female
Male
0x5x10xFM#ChesterEl PasoSalt Lk CityPlanoTulsaAlbuquerqueNE DallasFort WorthWabashaOrlandoPhoenixRochesterTucson1, CharlotteMidwestNW HarrisLas VegasWest North CentralSeattle EastSan Antonio CntrlSan DiegoUnited StatesSan JoseHempsteadFresnoNE TarrantMinnesotaTampaSan Fernando VlyE San Gabriel VlyHoustonSan BernardinoColumbusMiamiAtlantaMilwaukeeAnaheim-Santa Ana-Gdn GrvAnaheim-Santa An…SacramentoPhiladelphiaOceanside-EscondidoOceanside-Escond…Los AngelesAustinBaltimoreWashingtonQueensSW DallasBrooklynManhattanChicagoSeattleBostonBronxOntarioLong Bch-LakewoodDenverSan FranciscoDetroitTract 490400-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%1.361%1.36%-1.000000x-1.000000x2.132933x2.132933x2.13x1.146%1.15%2.445%2.44%1-1.000000x-1.000000x2.053360x2.053360x2.05x2.488%2.49%5.109%5.11%2-1.000000x-1.000000x1.782054x1.782054x1.78x3.355%3.35%5.978%5.98%3-1.000000x-1.000000x1.720683x1.720683x1.72x2.338%2.34%4.022%4.02%4-1.000000x-1.000000x1.707718x1.707718x1.71x3.458%3.46%5.905%5.91%5-1.000000x-1.000000x1.692229x1.692229x1.69x2.857%2.86%4.836%4.84%6-1.000000x-1.000000x1.684272x1.684272x1.68x1.637%1.64%2.757%2.76%7-1.000000x-1.000000x1.674879x1.674879x1.67x1.330%1.33%2.227%2.23%-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-1.000000x1.652184x1.652184x1.65x4.500%4.50%7.434%7.43%-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-1.000000x1.589934x1.589934x1.59x2.251%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-1.000000x1.572017x1.572017x1.57x2.329%2.33%3.662%3.66%-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-1.000000x1.481015x1.481015x1.48x2.798%2.80%4.144%4.14%-1.000000x-1.000000x1.476874x1.476874x1.48x3.518%3.52%5.196%5.20%21-1.000000x-1.000000x1.460302x1.460302x1.46x2.944%2.94%4.299%4.30%22-1.000000x-1.000000x1.451775x1.451775x1.45x2.041%2.04%2.963%2.96%23-1.000000x-1.000000x1.424636x1.424636x1.42x3.092%3.09%4.404%4.40%24-1.000000x-1.000000x1.423621x1.423621x1.42x1.501%1.50%2.137%2.14%25-1.000000x-1.000000x1.413654x1.413654x1.41x2.801%2.80%3.959%3.96%26-1.000000x-1.000000x1.395174x1.395174x1.40x3.384%3.38%4.722%4.72%27-1.000000x-1.000000x1.391590x1.391590x1.39x5.799%5.80%8.070%8.07%28-1.000000x-1.000000x1.368590x1.368590x1.37x1.742%1.74%2.385%2.38%29-1.000000x-1.000000x1.362600x1.362600x1.36x2.347%2.35%3.199%3.20%30-1.000000x-1.000000x1.359928x1.359928x1.36x2.888%2.89%3.927%3.93%31-1.000000x-1.000000x1.341930x1.341930x1.34x3.216%3.22%4.316%4.32%32-1.000000x-1.000000x1.310218x1.310218x1.31x3.011%3.01%3.945%3.95%33-1.000000x-1.000000x1.308108x1.308108x1.31x4.045%4.05%5.292%5.29%34-1.000000x-1.000000x1.303834x1.303834x1.30x4.384%4.38%5.716%5.72%35-1.000000x-1.000000x1.303196x1.303196x1.30x4.332%4.33%5.645%5.65%36-1.000000x-1.000000x1.300117x1.300117x1.30x10.922%10.9%14.199%14.2%37-1.000000x-1.000000x1.285200x1.285200x1.29x2.428%2.43%3.121%3.12%38-1.000000x-1.000000x1.265486x1.265486x1.27x1.515%1.51%1.917%1.92%39-1.000000x-1.000000x1.262281x1.262281x1.26x3.021%3.02%3.814%3.81%40-1.000000x-1.000000x1.245683x1.245683x1.25x9.673%9.67%12.050%12.1%41-1.000000x-1.000000x1.238186x1.238186x1.24x4.026%4.03%4.985%4.99%42-1.000000x-1.000000x1.228890x1.228890x1.23x5.961%5.96%7.326%7.33%43-1.000000x-1.000000x1.221037x1.221037x1.22x6.643%6.64%8.112%8.11%44-1.000000x-1.000000x1.202385x1.202385x1.20x1.526%1.53%1.834%1.83%45-1.000000x-1.000000x1.198236x1.198236x1.20x2.119%2.12%2.539%2.54%46-1.000000x-1.000000x1.181998x1.181998x1.18x2.766%2.77%3.269%3.27%47-1.000000x-1.000000x1.129665x1.129665x1.13x5.378%5.38%6.075%6.08%48-1.000000x-1.000000x1.098720x1.098720x1.10x7.194%7.19%7.905%7.90%49-1.000000x-1.000000x1.046557x1.046557x1.05x1.291%1.29%1.351%1.35%50-1.195885x-1.195885x1.20x1.000000x1.000000x2.437%2.44%2.038%2.04%
F percentage of females in category
M percentage of males in category
# rank of county subdivision out of 50 by male-to-female sex ratio

Definitions

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

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

The coarse levels of educational attainment are as follows:

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

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

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Demographics

Income

Education

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State:
Minnesota
County:
Wabasha
Metro Area:
Rochester Area
ZIP Codes:
55027, 55041, 55956, 55991
Unified School Districts:
Goodhue, Lake City, Zumbrota-Mazeppa
Congressional District:
MN-2
State Senate District:
MN-21
State House District:
MN-21B
Neighboring Cities:
Bellechester, Mazeppa, Zumbro Falls
Neighboring Townships:
Belvidere, Gillford, Goodhue, Mazeppa, Mount Pleasant, Pine Island, Zumbro, Zumbrota
Nearby Townships:
Hyde Park, Oronoco, West Albany