Educational Attainment in the Chester Township, Lake County, South Dakota (Township)

Educational Attainment#1

Highest level of education among people aged 25 years and older.
Scope: population of Lake County and the Chester Township
Chester Township
Lake County
0%10%20%30%40%50%CountHigher Degree1H.S. Diploma2No H.S. Diploma240.936864%43.030156%40.936864%40.9%20152.138493%50.962819%52.138493%52.1%2566.924644%6.007024%6.924644%6.9%34
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 Lake County at large.
Scope: population of Lake County and the Chester Township
-10%0%+10%%ref.Higher Degree1H.S. Diploma2No H.S. Diploma2-4.864711%-4.864711%-4.9%40.937%40.9%43.030%43.0%2.306924%2.306924%+2.3%52.138%52.1%50.963%51.0%15.275770%15.275770%+15.3%6.925%6.92%6.007%6.01%
% percentage with given level in the Chester Township
ref. percentage with given level in Lake County
1Post-Secondary Degree 2H.S. = High School

Detailed Educational Attainment#3

Highest level of education among people aged 25 years and older.
Scope: population of Lake County and the Chester Township
Chester Township
Lake County
0%5%10%15%20%25%30%CountDoctorate1Professional1Master's1Bachelor's1Associate's1Some CollegeHigh School2Some H.S.3Less than H.S.3None0.000000%0.000000%0.0%2.155747%01.221996%0.944653%1.221996%1.2%65.498982%5.680029%5.498982%5.5%2716.496945%24.427758%16.496945%16.5%8117.718941%9.821969%17.718941%17.7%8723.828921%18.832506%23.828921%23.8%11728.309572%32.130314%28.309572%28.3%1395.295316%3.923943%5.295316%5.3%261.629328%1.634976%1.629328%1.6%80.000000%0.000000%0.0%0.448105%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 Lake County at large.
Scope: population of Lake County and the Chester Township
-100%0%+100%%ref.Doctorate1Professional1Master's1Bachelor's1Associate's1Some CollegeHigh School2Some H.S.3Less than H.S.3None-100.000000%-100.000000%-100.0%0.000%0%2.156%2.16%29.359235%29.359235%+29.4%1.222%1.22%0.945%0.94%-3.187438%-3.187438%-3.2%5.499%5.50%5.680%5.68%-32.466398%-32.466398%-32.5%16.497%16.5%24.428%24.4%80.401104%80.401104%+80.4%17.719%17.7%9.822%9.82%26.530802%26.530802%+26.5%23.829%23.8%18.833%18.8%-11.891391%-11.891391%-11.9%28.310%28.3%32.130%32.1%34.948832%34.948832%+34.9%5.295%5.30%3.924%3.92%-0.345478%-0.345478%-0.3%1.629%1.63%1.635%1.63%-100.000000%-100.000000%-100.0%0.000%0%0.448%0.45%
% percentage with given level in the Chester Township
ref. percentage with given level in Lake County
1Degree 2Diploma or equivialent 3H.S. = High School

Educational Attainment Sex Ratio#5

Percentage more likely men or women are to have various highest levels of education among people aged 25 years and older.
Scope: population of Lake County and the Chester Township
More Females More Males
Lake County
Chester Township
0%50%100%FMHigher Degree1H.S. Diploma2No H.S. Diploma2-31.051253%-4.102547%-31.051253%31%46.502%46.5%35.484%35.5%-2.845859%11.048387%11.048387%11%49.383%49.4%54.839%54.8%135.161290%71.901301%135.161290%135%4.115%4.12%9.677%9.68%
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 Lake County and the Chester Township
More Females More Males
Lake County
Chester Township
0%500%1,000%FMProfessional1Master's1Bachelor's1Associate's1Some CollegeHigh School2Some H.S.3Less than H.S.3-2.057613%-2.057613%2%62.581126%1.235%1.23%1.210%1.21%-142.386831%-142.386831%142%19.701366%7.819%7.82%3.226%3.23%-21.229440%0.433468%0.433468%0%16.461%16.5%16.532%16.5%-44.581619%-44.581619%45%11.873511%20.988%21.0%14.516%14.5%-43.177573%22.479839%22.479839%22%21.399%21.4%26.210%26.2%2.306689%17.935895%2.306689%2%27.984%28.0%28.629%28.6%56.774194%188.664449%56.774194%57%4.115%4.12%6.452%6.45%-88.367498%1,000.000000%1,000.000000%> 1000%0.000%0%3.226%3.23%
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 Lake County and the Chester Township
Chester Township
Lake County
0%10%20%30%40%B.X.Total65+45-6435-4425-3410.294118%18.181818%10.294118%10.3%1413611.453744%24.478720%11.453744%11.5%2622725.609756%36.752899%25.609756%25.6%218243.478261%25.285481%43.478261%43.5%2046
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 Lake County at large.
Scope: population of Lake County and the Chester Township
40%20%0%20%40%60%%ref.65+45-6435-4425-34-43.382353%-43.382353%43.4%10.294%10.3%18.182%18.2%-53.209382%-53.209382%53.2%11.454%11.5%24.479%24.5%-30.319086%-30.319086%30.3%25.610%25.6%36.753%36.8%71.949509%71.949509%71.9%43.478%43.5%25.285%25.3%
% percentage in the Chester Township with a Bachelor's degree
ref percentage in Lake County with a Bachelor's degree

Bachelor's Degrees Sex Ratio By Age#9

Percentage more likely men or women are to have their highest degree be a Bachelor's.
Scope: population of Lake County and the Chester Township
More Females More Males
Lake County
Chester Township
50%0%50%100%150%FM65+45-6435-4425-34-12.360112%150.000000%150.000000%150.0%5.882%5.88%14.706%14.7%-67.112299%-47.518003%-67.112299%67.1%14.706%14.7%8.800%8.80%-1.082944%126.744186%126.744186%126.7%15.385%15.4%34.884%34.9%-5.882353%-8.868093%-5.882353%5.9%44.118%44.1%41.667%41.7%
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 Lake County and the Chester Township
Chester Township
Lake County
$0k$20k$40kCount%Graduate Degree1Bachelor's DegreeSome CollegeH.S. Diploma2No H.S. Diploma2Total$50,625.000000$50,250.000000$50,625.000000$50.6k336.721%6.72%$43,125.000000$39,388.000000$43,125.000000$43.1k8116.497%16.5%$36,771.000000$31,187.000000$36,771.000000$36.8k20441.548%41.5%$35,781.000000$29,479.000000$35,781.000000$35.8k13928.310%28.3%$NaN$32,500.000000$32,500.000000$32.5k346.925%6.92%$37,292.000000$33,837.000000$37,292.000000$37.3k491100.000%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 Lake County and the Chester Township
Female Male
Lake County
Chester Township
Shaded bar tips show excess over facing bar.
$0k$100k$200kFMGraduate Degree1Some CollegeH.S. Diploma2Total$-48,750.000000$-48,500.000000$-48,750.000000$48.8k$48,750.000000$201,251.000000$48,500.000000$4,380.000000$250,001.000000$250.0k2211$-35,368.000000$-26,778.000000$-35,368.000000$35.4k$35,368.000000$9,132.000000$26,778.000000$9,908.000000$44,500.000000$44.5k103101$-32,589.000000$-23,614.000000$-32,589.000000$32.6k$32,589.000000$8,786.000000$23,614.000000$14,915.000000$41,375.000000$41.4k6871$-33,553.000000$-28,344.000000$-33,553.000000$33.6k$33,553.000000$9,682.000000$28,344.000000$11,218.000000$43,235.000000$43.2k243248
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 Lake County and the Chester Township
Chester Township
Lake County
0%20%40%60%80%CountBachelor's Degree1Some College2H.S. Diploma3No H.S. Diploma377.173913%83.950617%77.173913%77.2%7181.875000%83.825900%81.875000%81.9%13176.543210%74.869110%76.543210%76.5%6263.636364%58.024691%63.636364%63.6%14
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 Lake County and the Chester Township
Female Male
Lake County
Chester Township
Shaded bar tips show excess over facing bar.
4%2%0%2%4%6%8%MFWhite1-4.149378%-4.397801%-4.149378%4.1%4.149378%5.528042%4.397801%2.584621%9.677419%9.7%2410
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 Lake County and the Chester Township
Female Male
Lake County
Chester Township
Shaded bar tips show excess over facing bar.
30%20%10%0%10%20%30%MFWhite1-20.967742%-4.758399%-32.202148%-2.855323%-25.726141%25.7%20.967742%32.202148%20.967742%21.0%5262
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 South Dakota

There are 1,335 county subdivisions in South Dakota. This section compares the Chester Township to the 50 most populous county subdivisions in South Dakota 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 2,278.

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 South Dakota, and entities that contain the Chester Township
0%5%10%15%20%25%Count#West ToddEast Oglala LakotaE Oglala LakotaEast CorsonWest Oglala LakotaW Oglala LakotaHuronSissetonEast ToddWinnerMobridgeNorth DeweyUnited States of AmericaUnited StatesNorth Sioux CityN Sioux CityMidwestLeadMilbankFort PierreMitchellPierreSioux FallsCantonSturgisWest North CentralWest ButteYanktonSouth DakotaBox ElderAberdeenWatertownRapid CityHot SpringsWest CusterChamberlainBelle FourcheChester TownshipChesterMadisonSouthwest MeadeSW MeadeWest YanktonLake CountyLakeRedfieldChester School District 39-1Chester 39-1HartfordCentral PenningtonCntrl PenningtonSpearfishDell Rapids960300Tract 960300VermillionSplit Rock TownshipSplit RockBig Sioux TownshipBig SiouxMount RushmoreMt RushmoreBrookingsBox ElderSioux FallsWest HughesNorth LawrenceN LawrenceHarrisburgBrandonSpringdale TownshipSpringdaleTea26.419857%26.419857%26.4%628123.352855%23.352855%23.4%638221.846154%21.846154%21.8%284321.305273%21.305273%21.3%901419.339458%19.339458%19.3%1,663517.559524%17.559524%17.6%295614.750151%14.750151%14.8%245714.250125%14.250125%14.3%286813.656041%13.656041%13.7%347913.483764%13.483764%13.5%2451013.020590%13.020590%13.0%27,818,38027.8M12.222888%12.222888%12.2%2041110.244520%10.244520%10.2%4,641,8354.64M10.186389%10.186389%10.2%2351210.160920%10.160920%10.2%2211310.089400%10.089400%10.1%158149.976200%9.976200%10.0%1,006159.786495%9.786495%9.8%958169.702326%9.702326%9.7%9,123179.388840%9.388840%9.4%212189.364909%9.364909%9.4%435199.174633%9.174633%9.2%1,278,0511.28M8.965929%8.965929%9.0%150208.859746%8.859746%8.9%885218.813537%8.813537%8.8%49,05549.1k8.696917%8.696917%8.7%299228.481745%8.481745%8.5%1,524238.084058%8.084058%8.1%1,181247.926704%7.926704%7.9%3,850257.445632%7.445632%7.4%202267.441592%7.441592%7.4%258277.435159%7.435159%7.4%129287.221350%7.221350%7.2%276296.924644%6.924644%6.9%346.674392%6.674392%6.7%288306.256121%6.256121%6.3%511316.090226%6.090226%6.1%162326.007024%6.007024%6.0%4965.858171%5.858171%5.9%114335.518946%5.518946%5.5%675.492639%5.492639%5.5%97345.278205%5.278205%5.3%480355.231536%5.231536%5.2%357365.117271%5.117271%5.1%120375.113025%5.113025%5.1%954.908504%4.908504%4.9%228384.757548%4.757548%4.8%104394.303279%4.303279%4.3%105404.091154%4.091154%4.1%228413.850760%3.850760%3.9%418423.776824%3.776824%3.8%44433.667391%3.667391%3.7%591443.335250%3.335250%3.3%58453.233720%3.233720%3.2%145462.122642%2.122642%2.1%63471.887113%1.887113%1.9%111481.596114%1.596114%1.6%23491.520000%1.520000%1.5%3850
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 South Dakota, and entities that contain the Chester Township
0%20%40%Count#VermillionSioux FallsHarrisburgBig Sioux TownshipBig SiouxBrookingsSplit Rock TownshipSplit RockWest HughesMount RushmoreMt RushmoreSpringdale TownshipSpringdaleNorth LawrenceN LawrenceTea960300Tract 960300HartfordBrandonMadisonLake CountyLakeSpearfishPierreRapid CityUnited States of AmericaUnited StatesSioux FallsWest North CentralYanktonWest CusterChamberlainMidwestAberdeenLeadSouth DakotaSouthwest MeadeSW MeadeFort PierreChester School District 39-1Chester 39-1MitchellDell RapidsWest YanktonWest ButteWinnerChester TownshipChesterHot SpringsMobridgeEast ToddNorth Sioux CityN Sioux CityCantonWatertownBox ElderHuronSturgisCentral PenningtonCntrl PenningtonSissetonBelle FourcheRedfieldBox ElderNorth DeweyEast CorsonMilbankEast Oglala LakotaE Oglala LakotaWest ToddWest Oglala LakotaW Oglala Lakota55.026911%55.026911%55.0%2,556152.057090%52.057090%52.1%8,389247.843666%47.843666%47.8%1,420347.745902%47.745902%47.7%1,165447.250115%47.250115%47.3%5,129545.059469%45.059469%45.1%985642.955722%42.955722%43.0%747742.436749%42.436749%42.4%2,365841.498959%41.498959%41.5%598938.157895%38.157895%38.2%1,7111037.040000%37.040000%37.0%9261136.437029%36.437029%36.4%67734.767837%34.767837%34.8%6141233.764026%33.764026%33.8%1,9861333.534183%33.534183%33.5%1,4471433.208187%33.208187%33.2%2,74233.015826%33.015826%33.0%2,2531532.516089%32.516089%32.5%3,1831630.533251%30.533251%30.5%14,83014.8k1730.315023%30.315023%30.3%64,767,78764.8M30.259813%30.259813%30.3%28,45328.5k1830.056536%30.056536%30.1%4,186,9564.19M29.842827%29.842827%29.8%2,9811929.622152%29.622152%29.6%1,0272029.452450%29.452450%29.5%5112128.952816%28.952816%29.0%13,118,64213.1M28.317008%28.317008%28.3%5,0882227.568270%27.568270%27.6%6362327.450336%27.450336%27.5%152,785153k27.215965%27.215965%27.2%2,2232427.075351%27.075351%27.1%4242527.018122%27.018122%27.0%32826.824673%26.824673%26.8%2,7052626.652452%26.652452%26.7%6252726.578947%26.578947%26.6%7072825.582785%25.582785%25.6%4282924.065770%24.065770%24.1%4833023.217923%23.217923%23.2%11422.889790%22.889790%22.9%6213122.077922%22.077922%22.1%5613221.733895%21.733895%21.7%3613321.569802%21.569802%21.6%3603420.992028%20.992028%21.0%4743520.898077%20.898077%20.9%3,0533620.600858%20.600858%20.6%2403720.002326%20.002326%20.0%1,7203819.763186%19.763186%19.8%9183918.803607%18.803607%18.8%1,7104018.452381%18.452381%18.5%3104118.158032%18.158032%18.2%6944218.088386%18.088386%18.1%3524317.626527%17.626527%17.6%6064413.538800%13.538800%13.5%2464513.076923%13.076923%13.1%1704612.413793%12.413793%12.4%2704711.713031%11.713031%11.7%3204810.769878%10.769878%10.8%2564910.711752%10.711752%10.7%45350
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 South Dakota, and entities that contain the Chester Township
0%5%10%Count#VermillionBig Sioux TownshipBig SiouxBrookingsMount RushmoreMt RushmoreSplit Rock TownshipSplit RockSpringdale TownshipSpringdaleSioux FallsWest HughesFort PierreWinnerSpearfishMadisonMobridgeHarrisburgTeaWest YanktonUnited States of AmericaUnited StatesHot SpringsPierreLake CountyLakeYanktonWest North CentralChamberlainRapid CityMidwestSioux FallsNorth LawrenceN Lawrence960300Tract 960300RedfieldWest CusterSouth DakotaAberdeenSouthwest MeadeSW MeadeHartfordBrandonCentral PenningtonCntrl PenningtonSissetonBox ElderNorth Sioux CityN Sioux CityMitchellChester School District 39-1Chester 39-1CantonLeadSturgisChester TownshipChesterWest ToddWatertownDell RapidsBelle FourcheMilbankNorth DeweyHuronEast ToddWest Oglala LakotaW Oglala LakotaBox ElderEast Oglala LakotaE Oglala LakotaEast CorsonWest Butte13.842842%13.842842%13.8%643110.737705%10.737705%10.7%26226.927683%6.927683%6.9%75236.352055%6.352055%6.4%35446.129918%6.129918%6.1%13455.968078%5.968078%6.0%8665.963388%5.963388%6.0%96174.715354%4.715354%4.7%8284.150702%4.150702%4.2%6593.986049%3.986049%4.0%80103.898007%3.898007%3.9%266113.777520%3.777520%3.8%163123.541913%3.541913%3.5%90133.537736%3.537736%3.5%105143.400000%3.400000%3.4%85153.345865%3.345865%3.3%89163.336158%3.336158%3.3%7,127,6737.13M3.243642%3.243642%3.2%88173.197467%3.197467%3.2%313183.100400%3.100400%3.1%2563.003304%3.003304%3.0%300192.978981%2.978981%3.0%414,980415k2.939481%2.939481%2.9%51202.927733%2.927733%2.9%1,422212.893416%2.893416%2.9%1,311,0191.31M2.841677%2.841677%2.8%2,672222.720785%2.720785%2.7%122232.637244%2.637244%2.6%492.569373%2.569373%2.6%50242.567061%2.567061%2.6%89252.514252%2.514252%2.5%13,99414.0k2.254007%2.254007%2.3%405262.252693%2.252693%2.3%184272.151755%2.151755%2.2%38282.006120%2.006120%2.0%118291.792391%1.792391%1.8%163301.785714%1.785714%1.8%30311.774287%1.774287%1.8%61321.437987%1.437987%1.4%24331.388338%1.388338%1.4%140341.317957%1.317957%1.3%161.284322%1.284322%1.3%29351.257044%1.257044%1.3%29361.227126%1.227126%1.2%57371.221996%1.221996%1.2%61.177955%1.177955%1.2%28380.937778%0.937778%0.9%137390.724947%0.724947%0.7%17400.627943%0.627943%0.6%24410.459770%0.459770%0.5%10420.440286%0.440286%0.4%8430.430283%0.430283%0.4%37440.421433%0.421433%0.4%7450.401986%0.401986%0.4%17460.257511%0.257511%0.3%3470.000000%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 the Chester Township, selected other county subdivisions in South Dakota, and entities that contain the Chester Township
Female
Male
10x5x0x5xFM#West ButteSW MeadeCantonWest HughesHarrisburgDell RapidsChesterHot SpringsSplit RockSioux FallsWest CusterLakeBox ElderHartfordWest YanktonN Sioux CityMt RushmoreVermillionW Oglala LakotaSturgisWest ToddMitchellMilbankFort PierreTract 960300ChamberlainWatertownSissetonN LawrenceMadisonRedfieldSouth DakotaAberdeenRapid CitySpringdaleChester 39-1West North CentralMidwestSioux FallsUnited StatesHuronNorth DeweySpearfishLeadMobridgeEast ToddBelle FourcheWinnerBrookingsYanktonE Oglala LakotaEast CorsonTeaPierreCntrl PenningtonBrandonBox ElderBig Sioux-1.000000x-1.000000x5.219970x5.219970x5.22x2.829%2.83%14.767%14.8%1-1.000000x-1.000000x4.945813x4.945813x4.95x2.085%2.09%10.314%10.3%2-1.000000x-1.000000x4.258030x4.258030x4.26x3.493%3.49%14.872%14.9%3-1.000000x-1.000000x4.113585x4.113585x4.11x1.290%1.29%5.305%5.30%4-1.000000x-1.000000x3.814476x3.814476x3.81x0.929%0.93%3.545%3.55%5-1.000000x-1.000000x3.106771x3.106771x3.11x2.515%2.51%7.813%7.81%6-1.000000x-1.000000x2.351613x2.351613x2.35x4.115%4.12%9.677%9.68%-1.000000x-1.000000x2.001333x2.001333x2.00x4.974%4.97%9.955%9.96%7-1.000000x-1.000000x1.875257x1.875257x1.88x3.263%3.26%6.119%6.12%8-1.000000x-1.000000x1.757060x1.757060x1.76x2.689%2.69%4.724%4.72%9-1.000000x-1.000000x1.724210x1.724210x1.72x5.515%5.52%9.510%9.51%10-1.000000x-1.000000x1.719013x1.719013x1.72x4.396%4.40%7.557%7.56%-1.000000x-1.000000x1.607070x1.607070x1.61x6.697%6.70%10.763%10.8%11-1.000000x-1.000000x1.586684x1.586684x1.59x4.215%4.22%6.689%6.69%12-1.000000x-1.000000x1.541746x1.541746x1.54x4.769%4.77%7.353%7.35%13-1.000000x-1.000000x1.524572x1.524572x1.52x9.646%9.65%14.706%14.7%14-1.000000x-1.000000x1.515325x1.515325x1.52x3.261%3.26%4.942%4.94%15-1.000000x-1.000000x1.498461x1.498461x1.50x3.906%3.91%5.853%5.85%16-1.000000x-1.000000x1.494353x1.494353x1.49x17.285%17.3%25.829%25.8%17-1.000000x-1.000000x1.480208x1.480208x1.48x7.668%7.67%11.350%11.3%18-1.000000x-1.000000x1.477030x1.477030x1.48x21.515%21.5%31.778%31.8%19-1.000000x-1.000000x1.448467x1.448467x1.45x8.208%8.21%11.889%11.9%20-1.000000x-1.000000x1.413342x1.413342x1.41x8.453%8.45%11.947%11.9%21-1.000000x-1.000000x1.389522x1.389522x1.39x8.389%8.39%11.656%11.7%22-1.000000x-1.000000x1.327602x1.327602x1.33x4.343%4.34%5.765%5.77%-1.000000x-1.000000x1.320837x1.320837x1.32x6.455%6.46%8.526%8.53%23-1.000000x-1.000000x1.318828x1.318828x1.32x7.013%7.01%9.249%9.25%24-1.000000x-1.000000x1.293077x1.293077x1.29x15.428%15.4%19.949%19.9%25-1.000000x-1.000000x1.285433x1.285433x1.29x2.828%2.83%3.635%3.63%26-1.000000x-1.000000x1.265403x1.265403x1.27x5.906%5.91%7.474%7.47%27-1.000000x-1.000000x1.255401x1.255401x1.26x5.273%5.27%6.619%6.62%28-1.000000x-1.000000x1.244888x1.244888x1.24x7.858%7.86%9.783%9.78%-1.000000x-1.000000x1.187620x1.187620x1.19x7.786%7.79%9.247%9.25%29-1.000000x-1.000000x1.168092x1.168092x1.17x7.323%7.32%8.554%8.55%30-1.000000x-1.000000x1.164868x1.164868x1.16x1.468%1.47%1.711%1.71%31-1.000000x-1.000000x1.143280x1.143280x1.14x5.137%5.14%5.873%5.87%-1.000000x-1.000000x1.137506x1.137506x1.14x8.598%8.60%9.780%9.78%-1.000000x-1.000000x1.127915x1.127915x1.13x9.647%9.65%10.881%10.9%-1.000000x-1.000000x1.110589x1.110589x1.11x9.201%9.20%10.219%10.2%32-1.000000x-1.000000x1.109070x1.109070x1.11x12.369%12.4%13.719%13.7%-1.000000x-1.000000x1.100283x1.100283x1.10x18.463%18.5%20.314%20.3%33-1.000000x-1.000000x1.036666x1.036666x1.04x13.258%13.3%13.744%13.7%34-1.000000x-1.000000x1.028284x1.028284x1.03x5.163%5.16%5.309%5.31%35-1.000000x-1.000000x1.012928x1.012928x1.01x10.121%10.1%10.252%10.3%36-1.010176x-1.010176x1.01x1.000000x1.000000x13.723%13.7%13.584%13.6%37-1.080159x-1.080159x1.08x1.000000x1.000000x15.295%15.3%14.160%14.2%38-1.103812x-1.103812x1.10x1.000000x1.000000x7.553%7.55%6.842%6.84%39-1.208183x-1.208183x1.21x1.000000x1.000000x15.516%15.5%12.842%12.8%40-1.222914x-1.222914x1.22x1.000000x1.000000x4.243%4.24%3.470%3.47%41-1.234367x-1.234367x1.23x1.000000x1.000000x9.838%9.84%7.970%7.97%42-1.415104x-1.415104x1.42x1.000000x1.000000x27.121%27.1%19.165%19.2%43-1.422449x-1.422449x1.42x1.000000x1.000000x25.746%25.7%18.100%18.1%44-1.596464x-1.596464x1.60x1.000000x1.000000x1.830%1.83%1.146%1.15%45-1.657419x-1.657419x1.66x1.000000x1.000000x12.036%12.0%7.262%7.26%46-1.799878x-1.799878x1.80x1.000000x1.000000x6.782%6.78%3.768%3.77%47-1.923915x-1.923915x1.92x1.000000x1.000000x2.453%2.45%1.275%1.27%48-10.000000x-10.000000x> 10.0x1.000000x1.000000x7.737%7.74%0.617%0.62%49-10.000000x-10.000000x> 10.0x1.000000x1.000000x8.801%8.80%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 the Chester Township, selected other county subdivisions in South Dakota, and entities that contain the Chester Township
Female
Male
10x5x0x5x10xFM#North DeweyMilbankEast ToddTract 960300RedfieldWatertownN Sioux CityWinnerWest YanktonHot SpringsFort PierreHuronChamberlainAberdeenPierreCntrl PenningtonMt RushmoreBelle FourcheSpearfishSW MeadeVermillionSplit RockBrookingsSioux FallsMitchellCantonBig SiouxSturgisSioux FallsSouth DakotaMobridgeMidwestWest North CentralUnited StatesRapid CityBox ElderWest ToddLakeBrandonN LawrenceChesterTeaYanktonWest CusterMadisonChester 39-1SpringdaleLeadDell RapidsHarrisburgHartfordSissetonWest HughesW Oglala LakotaBox Elder-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%0.948%0.95%1-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%0.941%0.94%2-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%0.877%0.88%3-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.352%0.35%4.573%4.57%-1.000000x-1.000000x5.200946x5.200946x5.20x0.909%0.91%4.728%4.73%4-1.000000x-1.000000x5.124982x5.124982x5.12x0.315%0.32%1.615%1.62%5-1.000000x-1.000000x4.817647x4.817647x4.82x0.488%0.49%2.353%2.35%6-1.000000x-1.000000x4.450526x4.450526x4.45x1.514%1.51%6.737%6.74%7-1.000000x-1.000000x4.361213x4.361213x4.36x1.231%1.23%5.368%5.37%8-1.000000x-1.000000x3.688238x3.688238x3.69x1.390%1.39%5.126%5.13%9-1.000000x-1.000000x3.685890x3.685890x3.69x1.731%1.73%6.380%6.38%10-1.000000x-1.000000x3.460356x3.460356x3.46x0.199%0.20%0.688%0.69%11-1.000000x-1.000000x3.254193x3.254193x3.25x1.422%1.42%4.629%4.63%12-1.000000x-1.000000x3.026479x3.026479x3.03x1.147%1.15%3.472%3.47%13-1.000000x-1.000000x2.914741x2.914741x2.91x1.681%1.68%4.899%4.90%14-1.000000x-1.000000x2.553567x2.553567x2.55x1.010%1.01%2.578%2.58%15-1.000000x-1.000000x2.366289x2.366289x2.37x3.793%3.79%8.975%8.98%16-1.000000x-1.000000x2.287156x2.287156x2.29x0.392%0.39%0.897%0.90%17-1.000000x-1.000000x2.199787x2.199787x2.20x2.499%2.50%5.498%5.50%18-1.000000x-1.000000x2.167794x2.167794x2.17x1.415%1.42%3.068%3.07%19-1.000000x-1.000000x2.132400x2.132400x2.13x8.744%8.74%18.645%18.6%20-1.000000x-1.000000x2.066050x2.066050x2.07x3.935%3.93%8.129%8.13%21-1.000000x-1.000000x2.048101x2.048101x2.05x4.523%4.52%9.264%9.26%22-1.000000x-1.000000x1.962539x1.962539x1.96x1.928%1.93%3.783%3.78%23-1.000000x-1.000000x1.946378x1.946378x1.95x0.954%0.95%1.858%1.86%24-1.000000x-1.000000x1.766838x1.766838x1.77x0.919%0.92%1.624%1.62%25-1.000000x-1.000000x1.738512x1.738512x1.74x7.795%7.80%13.553%13.6%26-1.000000x-1.000000x1.728895x1.728895x1.73x0.919%0.92%1.588%1.59%27-1.000000x-1.000000x1.673245x1.673245x1.67x4.505%4.51%7.538%7.54%28-1.000000x-1.000000x1.656908x1.656908x1.66x1.896%1.90%3.141%3.14%-1.000000x-1.000000x1.619067x1.619067x1.62x2.729%2.73%4.419%4.42%29-1.000000x-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-1.000000x1.504887x1.504887x1.50x2.347%2.35%3.532%3.53%30-1.000000x-1.000000x1.487688x1.487688x1.49x1.431%1.43%2.129%2.13%31-1.000000x-1.000000x1.456573x1.456573x1.46x0.967%0.97%1.408%1.41%32-1.000000x-1.000000x1.318591x1.318591x1.32x2.667%2.67%3.517%3.52%-1.000000x-1.000000x1.082861x1.082861x1.08x1.929%1.93%2.089%2.09%33-1.000000x-1.000000x1.054544x1.054544x1.05x2.648%2.65%2.793%2.79%34-1.020576x-1.020576x1.02x1.000000x1.000000x1.235%1.23%1.210%1.21%-1.129941x-1.129941x1.13x1.000000x1.000000x3.587%3.59%3.175%3.17%35-1.144745x-1.144745x1.14x1.000000x1.000000x3.216%3.22%2.810%2.81%36-1.250139x-1.250139x1.25x1.000000x1.000000x2.841%2.84%2.273%2.27%37-1.308470x-1.308470x1.31x1.000000x1.000000x4.271%4.27%3.264%3.26%38-1.386986x-1.386986x1.39x1.000000x1.000000x1.541%1.54%1.111%1.11%-1.550008x-1.550008x1.55x1.000000x1.000000x7.342%7.34%4.737%4.74%39-1.629286x-1.629286x1.63x1.000000x1.000000x1.557%1.56%0.956%0.96%40-1.770327x-1.770327x1.77x1.000000x1.000000x0.922%0.92%0.521%0.52%41-2.097274x-2.097274x2.10x1.000000x1.000000x4.647%4.65%2.216%2.22%42-2.313817x-2.313817x2.31x1.000000x1.000000x3.044%3.04%1.316%1.32%43-2.452703x-2.452703x2.45x1.000000x1.000000x2.477%2.48%1.010%1.01%44-5.513031x-5.513031x5.51x1.000000x1.000000x8.089%8.09%1.467%1.47%45-10.000000x-10.000000x> 10.0x1.000000x1.000000x0.759%0.76%0.000%0%46-10.000000x-10.000000x> 10.0x1.000000x1.000000x0.580%0.58%0.000%0%47
F percentage of females in category
M percentage of males in category
# rank of county subdivision out of 47 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#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 the Midwest, and entities that contain the Chester Township
0%10%20%30%Count#Aurora TownshipAuroraCenter TownshipCtrKansas CityClevelandWayne TownshipWayneDetroitMilwaukeeNorth TownshipNDaytonChicagoProviso TownshipProvisoRockford TownshipRockfordSt. LouisWarrenGrand RapidsToledoBlue TownshipCincinnatiAkronSt. PaulSterling HeightsSterling HtsUnited States of AmericaUnited StatesThornton TownshipThorntonWichitaKaw TownshipOmahaBloomingdale TownshipBloomingdaleColumbusMaine TownshipMaineTopekaMinneapolisSpringfield TownshipSpringfieldWorth TownshipWorthMidwestLawrence TownshipLawrenceSioux FallsWest North CentralSouth DakotaCapital TownshipCapitalWheeling TownshipWheelingPalatine TownshipPalatineSchaumburg TownshipSchaumburgLincolnChester TownshipChesterWashington TownshipWashingtonOlatheFargoLake CountyLakeCedar RapidsChester School District 39-1Chester 39-1York TownshipMilton TownshipMilton960300Tract 960300MadisonDowners 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%31,23131.2k2312.455744%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%1,278,0511.28M8.813537%8.813537%8.8%49,05549.1k8.623103%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%11,88611.9k396.924644%6.924644%6.9%346.804680%6.804680%6.8%6,403406.424130%6.424130%6.4%5,331416.055621%6.055621%6.1%4,270426.007024%6.007024%6.0%4965.981653%5.981653%6.0%5,099435.518946%5.518946%5.5%675.461095%5.461095%5.5%4,715445.266517%5.266517%5.3%4,126455.113025%5.113025%5.1%954.836248%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#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 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 TownshipLawrenceChicago960300Tract 960300Capital TownshipCapitalColumbusOmahaCincinnatiLake CountyLakeSt. LouisGrand RapidsBloomingdale TownshipBloomingdaleCedar RapidsUnited States of AmericaUnited StatesSioux FallsWest North CentralMidwestWichitaSterling HeightsSterling HtsSouth DakotaChester School District 39-1Chester 39-1TopekaSpringfield TownshipSpringfieldProviso TownshipProvisoWorth TownshipWorthMilwaukeeChester TownshipChesterRockford TownshipRockfordAkronCenter TownshipCtrNorth TownshipNThornton TownshipThorntonToledoDaytonWarrenWayne 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%669,666670k2036.437029%36.437029%36.4%67736.298510%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%64,52964.5k2433.208187%33.208187%33.2%2,74233.007421%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%25,60325.6k3127.450336%27.450336%27.5%152,785153k27.018122%27.018122%27.0%32827.007248%27.007248%27.0%22,95423.0k3226.964567%26.964567%27.0%27,92127.9k3326.237989%26.237989%26.2%27,03327.0k3425.217641%25.217641%25.2%26,38926.4k3523.517740%23.517740%23.5%85,81285.8k3623.217923%23.217923%23.2%11421.592552%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%14,78814.8k4516.167409%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#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 the Midwest, and entities that contain the Chester Township
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 RapidsLake CountyLakeLawrence TownshipLawrenceWest North CentralSpringfield TownshipSpringfieldCedar RapidsMidwestSioux FallsOlathe960300Tract 960300Center TownshipCtrSchaumburg TownshipSchaumburgWichitaSouth DakotaProviso TownshipProvisoAkronBloomingdale TownshipBloomingdaleRockford TownshipRockfordMilwaukeeWorth TownshipWorthClevelandToledoNorth TownshipNSterling HeightsSterling HtsKansas CityDetroitChester School District 39-1Chester 39-1DaytonChester TownshipChesterWayne TownshipWayneWarrenBlue TownshipAurora TownshipAuroraThornton TownshipThornton17.877867%17.877867%17.9%11,64611.6k19.171173%9.171173%9.2%13,94013.9k27.658384%7.658384%7.7%7,93637.306290%7.306290%7.3%6,87546.241155%6.241155%6.2%16,71416.7k56.197734%6.197734%6.2%5,35165.940071%5.940071%5.9%7,53175.933545%5.933545%5.9%4,83485.920847%5.920847%5.9%10,97511.0k95.896414%5.896414%5.9%7,178105.800061%5.800061%5.8%4,544114.880448%4.880448%4.9%10,66710.7k124.729595%4.729595%4.7%9,034134.568292%4.568292%4.6%7,656144.485379%4.485379%4.5%82,18982.2k154.336789%4.336789%4.3%3,058164.233985%4.233985%4.2%3,357174.059919%4.059919%4.1%11,66511.7k184.030539%4.030539%4.0%3,970193.487439%3.487439%3.5%2,782203.407574%3.407574%3.4%3,779213.357865%3.357865%3.4%17,95418.0k223.336158%3.336158%3.3%7,127,6737.13M3.233245%3.233245%3.2%2,748233.174629%3.174629%3.2%3,846243.100400%3.100400%3.1%2563.083448%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%2,349292.637244%2.637244%2.6%492.602914%2.602914%2.6%2,576302.551250%2.551250%2.6%2,382312.519246%2.519246%2.5%6,260322.514252%2.514252%2.5%13,99414.0k2.213918%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%4,911391.642065%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%5,693441.317957%1.317957%1.3%161.257490%1.257490%1.3%1,106451.221996%1.221996%1.2%61.183365%1.183365%1.2%1,040461.047058%1.047058%1.0%963470.997751%0.997751%1.0%1,069480.936111%0.936111%0.9%834490.876686%0.876686%0.9%97150
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).

Under-Education Sex Ratio by County Subdivision#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 the Midwest, and entities that contain the Chester Township
Female
Male
1x0x1x2xFM#ChesterLakeTract 960300South DakotaCedar RapidsLincolnDetroitOmahaToledoThorntonKansas CityMadisonLawrenceFargoProvisoRockfordBlue TownshipChester 39-1West North CentralWayneMidwestTopekaMilwaukeeKaw TownshipDaytonSioux FallsUnited StatesOlatheWorthNOverland ParkAuroraWheelingGrand RapidsSchaumburgChicagoWichitaColumbusClevelandPalatineCapitalWarrenSpringfieldYork TownshipSt. LouisWashingtonBloomingdaleCtrCincinnatiAkronAnn ArborSt. PaulLisleMinneapolisSterling HtsDowners GrvMiltonMaine-1.000000x-1.000000x2.351613x2.351613x2.35x4.115%4.12%9.677%9.68%-1.000000x-1.000000x1.719013x1.719013x1.72x4.396%4.40%7.557%7.56%-1.000000x-1.000000x1.327602x1.327602x1.33x4.343%4.34%5.765%5.77%-1.000000x-1.000000x1.244888x1.244888x1.24x7.858%7.86%9.783%9.78%-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-1.000000x1.143280x1.143280x1.14x5.137%5.14%5.873%5.87%-1.000000x-1.000000x1.137506x1.137506x1.14x8.598%8.60%9.780%9.78%-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-1.000000x1.123984x1.123984x1.12x16.526%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#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 the Midwest, and entities that contain the Chester Township
Female
Male
0x5x10xFM#Tract 960300RockfordNDaytonSioux FallsCapitalLawrenceDowners GrvAkronLisleWichitaYork TownshipMaineWarrenWheelingBlue TownshipSpringfieldOverland ParkMiltonGrand RapidsOlatheOmahaSouth DakotaFargoWashingtonLincolnMidwestBloomingdaleWest North CentralKansas CityAuroraUnited StatesAnn ArborTopekaSterling HtsPalatineSchaumburgColumbusMadisonKaw TownshipMilwaukeeCedar RapidsLakeClevelandCincinnatiSt. PaulSt. LouisChicagoWayneCtrToledoMinneapolisWorthDetroitProvisoChesterChester 39-1Thornton-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.352%0.35%4.573%4.57%-1.000000x-1.000000x2.117268x2.117268x2.12x1.353%1.35%2.866%2.87%1-1.000000x-1.000000x2.111054x2.111054x2.11x1.033%1.03%2.181%2.18%2-1.000000x-1.000000x1.989047x1.989047x1.99x0.860%0.86%1.711%1.71%3-1.000000x-1.000000x1.962539x1.962539x1.96x1.928%1.93%3.783%3.78%4-1.000000x-1.000000x1.901348x1.901348x1.90x2.990%2.99%5.686%5.69%5-1.000000x-1.000000x1.879271x1.879271x1.88x2.206%2.21%4.146%4.15%6-1.000000x-1.000000x1.852471x1.852471x1.85x5.456%5.46%10.107%10.1%7-1.000000x-1.000000x1.846298x1.846298x1.85x1.550%1.55%2.862%2.86%8-1.000000x-1.000000x1.815266x1.815266x1.82x4.271%4.27%7.754%7.75%9-1.000000x-1.000000x1.792728x1.792728x1.79x1.819%1.82%3.261%3.26%10-1.000000x-1.000000x1.792314x1.792314x1.79x4.498%4.50%8.062%8.06%11-1.000000x-1.000000x1.788417x1.788417x1.79x2.939%2.94%5.256%5.26%12-1.000000x-1.000000x1.768853x1.768853x1.77x0.769%0.77%1.361%1.36%13-1.000000x-1.000000x1.766097x1.766097x1.77x2.485%2.48%4.389%4.39%14-1.000000x-1.000000x1.761699x1.761699x1.76x0.737%0.74%1.298%1.30%15-1.000000x-1.000000x1.751445x1.751445x1.75x2.146%2.15%3.759%3.76%16-1.000000x-1.000000x1.732234x1.732234x1.73x4.415%4.41%7.647%7.65%17-1.000000x-1.000000x1.695067x1.695067x1.70x4.357%4.36%7.385%7.38%18-1.000000x-1.000000x1.689013x1.689013x1.69x2.382%2.38%4.023%4.02%19-1.000000x-1.000000x1.678153x1.678153x1.68x2.131%2.13%3.576%3.58%20-1.000000x-1.000000x1.669388x1.669388x1.67x3.061%3.06%5.110%5.11%21-1.000000x-1.000000x1.656908x1.656908x1.66x1.896%1.90%3.141%3.14%-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-1.000000x1.476996x1.476996x1.48x1.170%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-1.000000x1.318591x1.318591x1.32x2.667%2.67%3.517%3.52%-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%49-1.020576x-1.020576x1.02x1.000000x1.000000x1.235%1.23%1.210%1.21%-1.386986x-1.386986x1.39x1.000000x1.000000x1.541%1.54%1.111%1.11%-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#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 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 VegasPhoenixBostonSacramentoOrlandoAustinDenverUnited States of AmericaUnited StatesManhattanSan DiegoTampaSan JoseSan FranciscoTucsonAlbuquerqueTownship 1:Charlotte1, CharlotteColumbusTulsaSalt Lake CitySalt Lk CityTown of HempsteadHempsteadMidwestNorthwest HarrisNW HarrisWashingtonAtlantaWest North CentralSeattleSouth DakotaNortheast TarrantNE TarrantChester TownshipChesterLake CountyLakePlanoChester School District 39-1Chester 39-1960300Tract 960300Seattle 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%84,02484.0k3612.262851%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%1,278,0511.28M8.833573%8.833573%8.8%66,22066.2k478.813537%8.813537%8.8%49,05549.1k8.418271%8.418271%8.4%31,44331.4k486.924644%6.924644%6.9%346.007024%6.007024%6.0%4965.714681%5.714681%5.7%20,64420.6k495.518946%5.518946%5.5%675.113025%5.113025%5.1%954.913852%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#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 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 HarrisChicago960300Tract 960300ColumbusLos AngelesBrooklynSan Fernando ValleySan Fernando VlyLake CountyLakeNortheast 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…SacramentoSouth DakotaEast San Gabriel ValleyE San Gabriel VlyChester School District 39-1Chester 39-1OntarioPhiladelphiaMiamiFort WorthSouthwest DallasSW DallasMilwaukeeChester TownshipChesterFresnoLas VegasEl PasoBronxSan 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%669,666670k1736.437029%36.437029%36.4%67734.685843%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%420,848421k2133.208187%33.208187%33.2%2,74233.191099%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%209,283209k3627.450336%27.450336%27.5%152,785153k27.276345%27.276345%27.3%170,682171k3727.018122%27.018122%27.0%32826.758411%26.758411%26.8%111,532112k3826.349720%26.349720%26.3%272,786273k3926.011156%26.011156%26.0%178,455178k4024.665414%24.665414%24.7%131,349131k4123.764821%23.764821%23.8%140,625141k4223.517740%23.517740%23.5%85,81285.8k4323.217923%23.217923%23.2%11422.486319%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%80,59580.6k4814.929012%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#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 United States, and entities that contain the Chester Township
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 StatesTulsaLake CountyLakePhoenixLong Beach-LakewoodLong Bch-LakewoodWest North CentralMidwestOrlandoFresnoAnaheim-Santa Ana-Garden GroveAnaheim-Santa An…QueensNorthwest HarrisNW Harris960300Tract 960300Northeast TarrantNE TarrantSouth DakotaEast San Gabriel ValleyE San Gabriel VlyOntarioFort WorthLas VegasMilwaukeeSan BernardinoSan Antonio CentralSan Antonio CntrlEl PasoSouthwest DallasSW DallasBronxDetroitChester School District 39-1Chester 39-1Chester 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%24,96825.0k85.725842%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%12,13312.1k313.100400%3.100400%3.1%2563.010825%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%12,62112.6k382.637244%2.637244%2.6%492.630994%2.630994%2.6%9,827392.514252%2.514252%2.5%13,99414.0k2.484535%2.484535%2.5%15,54715.5k402.324315%2.324315%2.3%9,688412.173239%2.173239%2.2%11,57311.6k422.155077%2.155077%2.2%26,91426.9k432.043126%2.043126%2.0%7,455441.807306%1.807306%1.8%8,895451.792414%1.792414%1.8%7,845461.745764%1.745764%1.7%5,975471.704476%1.704476%1.7%10,08610.1k481.664253%1.664253%1.7%15,06415.1k491.318660%1.318660%1.3%5,693501.317957%1.317957%1.3%161.221996%1.221996%1.2%6
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 United States, and entities that contain the Chester Township
Female
Male
1x0x1x2xFM#ChesterLakeTract 9603001, CharlotteSouth DakotaDetroitBaltimoreTulsaSW DallasChester 39-1West North CentralMidwestFresnoMilwaukeeUnited 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-1.000000x2.351613x2.351613x2.35x4.115%4.12%9.677%9.68%-1.000000x-1.000000x1.719013x1.719013x1.72x4.396%4.40%7.557%7.56%-1.000000x-1.000000x1.327602x1.327602x1.33x4.343%4.34%5.765%5.77%-1.000000x-1.000000x1.285784x1.285784x1.29x10.185%10.2%13.096%13.1%1-1.000000x-1.000000x1.244888x1.244888x1.24x7.858%7.86%9.783%9.78%-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-1.000000x1.143280x1.143280x1.14x5.137%5.14%5.873%5.87%-1.000000x-1.000000x1.137506x1.137506x1.14x8.598%8.60%9.780%9.78%-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-1.000000x1.123984x1.123984x1.12x16.526%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#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 United States, and entities that contain the Chester Township
Female
Male
0x5x10xFM#Tract 960300El PasoSalt Lk CityPlanoTulsaAlbuquerqueNE DallasFort WorthOrlandoPhoenixSouth DakotaTucson1, CharlotteMidwestNW HarrisLas VegasWest North CentralSeattle EastSan Antonio CntrlSan DiegoUnited StatesSan JoseHempsteadFresnoNE TarrantTampaSan Fernando VlyE San Gabriel VlyHoustonSan BernardinoColumbusMiamiAtlantaMilwaukeeAnaheim-Santa Ana-Gdn GrvAnaheim-Santa An…SacramentoPhiladelphiaLakeOceanside-EscondidoOceanside-Escond…Los AngelesAustinBaltimoreWashingtonQueensSW DallasBrooklynManhattanChicagoSeattleBostonBronxOntarioLong Bch-LakewoodDenverSan FranciscoDetroitChesterChester 39-1-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.352%0.35%4.573%4.57%-1.000000x-1.000000x2.132933x2.132933x2.13x1.146%1.15%2.445%2.44%1-1.000000x-1.000000x2.053360x2.053360x2.05x2.488%2.49%5.109%5.11%2-1.000000x-1.000000x1.782054x1.782054x1.78x3.355%3.35%5.978%5.98%3-1.000000x-1.000000x1.720683x1.720683x1.72x2.338%2.34%4.022%4.02%4-1.000000x-1.000000x1.707718x1.707718x1.71x3.458%3.46%5.905%5.91%5-1.000000x-1.000000x1.692229x1.692229x1.69x2.857%2.86%4.836%4.84%6-1.000000x-1.000000x1.684272x1.684272x1.68x1.637%1.64%2.757%2.76%7-1.000000x-1.000000x1.660799x1.660799x1.66x2.196%2.20%3.647%3.65%8-1.000000x-1.000000x1.659024x1.659024x1.66x2.280%2.28%3.783%3.78%9-1.000000x-1.000000x1.656908x1.656908x1.66x1.896%1.90%3.141%3.14%-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-1.000000x1.476874x1.476874x1.48x3.518%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-1.000000x1.318591x1.318591x1.32x2.667%2.67%3.517%3.52%-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%50-1.020576x-1.020576x1.02x1.000000x1.000000x1.235%1.23%1.210%1.21%-1.386986x-1.386986x1.39x1.000000x1.000000x1.541%1.54%1.111%1.11%
F percentage of females in category
M percentage of males in category
# rank of county subdivision out of 50 by male-to-female sex ratio

Definitions

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

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

The coarse levels of educational attainment are as follows:

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

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

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State:
South Dakota
County:
Lake
Unincorporated Places:
Brant Lake, Chester, Lake Madison
ZIP Codes:
57016, 57022, 57075
Unified School District:
Chester 39-1
Congressional District:
SD-At Large
State Senate District:
SD-8
State House District:
SD-8
Neighboring Townships:
Buffalo, Burk, Colman, Franklin, Lake View, Lynn, Taopi, Wentworth
Nearby Townships:
Dell Rapids, Enterprise, Grand Meadow, Orland, Rutland