Educational Attainment in the Reading Township, Perry County, Ohio (Township)

Educational Attainment#1

Highest level of education among people aged 25 years and older.
Scope: population of Perry County and the Reading Township
Reading Township
Perry County
0%20%40%60%CountHigher Degree1H.S. Diploma2No H.S. Diploma226.643267%21.889868%26.643267%26.6%83566.049777%62.020603%66.049777%66.0%2,0707.306956%16.089529%7.306956%7.3%229
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 Perry County at large.
Scope: population of Perry County and the Reading Township
-50%0%+50%%ref.Higher Degree1H.S. Diploma2No H.S. Diploma221.715066%21.715066%+21.7%26.643%26.6%21.890%21.9%6.496508%6.496508%+6.5%66.050%66.0%62.021%62.0%-54.585643%-54.585643%-54.6%7.307%7.31%16.090%16.1%
% percentage with given level in the Reading Township
ref. percentage with given level in Perry 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 Perry County and the Reading Township
Reading Township
Perry County
0%10%20%30%40%CountDoctorate1Professional1Master's1Bachelor's1Associate's1Some CollegeHigh School2Some H.S.3Less than H.S.3None0.000000%0.000000%0.0%0.215134%00.414805%0.450954%0.414805%0.4%133.063178%3.111166%3.063178%3.1%9613.720485%8.183360%13.720485%13.7%4309.444799%9.929254%9.444799%9.4%29621.920868%17.744404%21.920868%21.9%68744.128909%44.276199%44.128909%44.1%1,3834.594767%12.792189%4.594767%4.6%1441.467773%2.432667%1.467773%1.5%461.244416%0.864673%1.244416%1.2%39
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 Perry County at large.
Scope: population of Perry County and the Reading 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%0.215%0.22%-8.015960%-8.015960%-8.0%0.415%0.41%0.451%0.45%-1.542451%-1.542451%-1.5%3.063%3.06%3.111%3.11%67.663217%67.663217%+67.7%13.720%13.7%8.183%8.18%-4.879068%-4.879068%-4.9%9.445%9.44%9.929%9.93%23.536791%23.536791%+23.5%21.921%21.9%17.744%17.7%-0.332662%-0.332662%-0.3%44.129%44.1%44.276%44.3%-64.081463%-64.081463%-64.1%4.595%4.59%12.792%12.8%-39.664053%-39.664053%-39.7%1.468%1.47%2.433%2.43%43.917613%43.917613%+43.9%1.244%1.24%0.865%0.86%
% percentage with given level in the Reading Township
ref. percentage with given level in Perry 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 Perry County and the Reading Township
More Females More Males
Perry County
Reading Township
40%20%0%20%FMHigher Degree1H.S. Diploma2No H.S. Diploma2-6.209762%-49.077680%-6.209762%6%27.440%27.4%25.835%25.8%6.640365%5.395120%6.640365%7%63.942%63.9%68.188%68.2%-44.197773%-44.197773%44%39.778105%8.619%8.62%5.977%5.98%
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 Perry County and the Reading Township
More Females More Males
Perry County
Reading Township
500%0%500%1,000%FMProfessional1Master's1Bachelor's1Associate's1Some CollegeHigh School2Some H.S.3Less than H.S.3None1,000.000000%593.845106%1,000.000000%> 1000%0.000%0%0.835%0.84%-34.937434%173.037374%173.037374%173%1.648%1.65%4.499%4.50%-5.242761%-23.788721%-5.242761%5%14.068%14.1%13.368%13.4%-64.343050%-107.424791%-64.343050%64%11.724%11.7%7.134%7.13%26.270225%0.595548%26.270225%26%19.392%19.4%24.486%24.5%-1.941027%-1.941027%2%7.382989%44.550%44.6%43.702%43.7%-30.414162%-30.414162%30%28.018372%5.196%5.20%3.985%3.98%-557.372201%-557.372201%557%101.403204%2.535%2.53%0.386%0.39%81.096217%94.560660%81.096217%81%0.887%0.89%1.607%1.61%
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 Perry County and the Reading Township
Reading Township
Perry County
0%5%10%15%20%25%30%35%B.X.Total65+45-6435-4425-342.177068%6.934172%2.177068%2.2%1568914.303406%9.103367%14.303406%14.3%2311,61536.474164%8.346492%36.474164%36.5%12032912.774451%7.365095%12.774451%12.8%64501
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 Perry County at large.
Scope: population of Perry County and the Reading Township
0%100%200%300%%ref.65+45-6435-4425-34-68.603774%-68.603774%68.6%2.177%2.18%6.934%6.93%57.122141%57.122141%57.1%14.303%14.3%9.103%9.10%336.999918%336.999918%337.0%36.474%36.5%8.346%8.35%73.445848%73.445848%73.4%12.774%12.8%7.365%7.37%
% percentage in the Reading Township with a Bachelor's degree
ref percentage in Perry 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 Perry County and the Reading Township
More Females More Males
Perry County
Reading Township
0%500%1,000%FM65+45-6435-4425-341,000.000000%130.754317%1,000.000000%> 1000%0.000%0%4.286%4.29%-30.022029%72.957446%72.957446%73.0%10.673%10.7%18.459%18.5%-53.974781%-90.219644%-53.974781%54.0%42.708%42.7%27.737%27.7%-412.432432%-157.530726%-412.432432%412.4%25.946%25.9%5.063%5.06%
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 Perry County and the Reading Township
Reading Township
Perry County
$0k$20k$40kCount%Graduate Degree1Bachelor's DegreeSome CollegeH.S. Diploma2Total$53,676.000000$54,057.000000$53,676.000000$53.7k1093.478%3.48%$33,512.000000$47,321.000000$33,512.000000$33.5k43013.720%13.7%$42,523.000000$32,978.000000$42,523.000000$42.5k98331.366%31.4%$27,471.000000$27,143.000000$27,471.000000$27.5k1,38344.129%44.1%$37,955.000000$30,966.000000$37,955.000000$38.0k3,134100.000%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 Perry County and the Reading Township
Female Male
Perry County
Reading Township
Shaded bar tips show excess over facing bar.
$50k$0k$50kFMGraduate Degree1Some CollegeH.S. Diploma2Total$-53,603.000000$-16,553.000000$-51,522.000000$-70,156.000000$70.2k$53,603.000000$51,522.000000$8,579.000000$53,603.000000$53.6k2683$-33,125.000000$-26,021.000000$-33,125.000000$33.1k$33,125.000000$19,456.000000$26,021.000000$19,684.000000$52,581.000000$52.6k491492$-19,826.000000$-20,233.000000$-19,826.000000$19.8k$19,826.000000$22,485.000000$20,233.000000$15,927.000000$42,311.000000$42.3k703680$-27,262.000000$-23,925.000000$-27,262.000000$27.3k$27,262.000000$17,780.000000$23,925.000000$14,868.000000$45,042.000000$45.0k1,5781,556
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 Perry County and the Reading Township
Reading Township
Perry County
0%20%40%60%80%CountBachelor's Degree1Some College2H.S. Diploma3No H.S. Diploma379.330709%80.835796%79.330709%79.3%40370.523752%73.887446%70.523752%70.5%57972.463768%63.222990%72.463768%72.5%75020.987654%40.008432%20.987654%21.0%17
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 Perry County and the Reading Township
Female Male
Perry County
Reading Township
Shaded bar tips show excess over facing bar.
10%5%0%5%10%15%MFWhite1-6.046814%-2.571690%-13.078017%-8.618504%8.6%6.046814%13.078017%5.765044%6.046814%6.0%93136
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 Perry County and the Reading Township
Female Male
Perry County
Reading Township
Shaded bar tips show excess over facing bar.
15%10%5%0%5%10%15%MFWhite1-15.716096%-10.756461%-2.162680%-15.716096%15.7%15.716096%2.034229%10.756461%17.750325%17.8%273248
M number of males in category
F number of females in category
1non-Hispanic 2excluding black and Asian Hispanics

Map of Educational Attainment by Tract in the Reading Township

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

Percentage of the population 25 years and older with given highest level of educational attainment
25.2%26.0%26.7%27.4%28.1%28.9%

Coarse: High School Diploma Educational Attainment by Tract#16

Percentage of the population 25 years and older with given highest level of educational attainment
57.5%58.9%60.3%61.6%63.0%64.4%

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

Percentage of the population 25 years and older with given highest level of educational attainment
10.4%11.1%11.7%12.3%12.9%13.6%

Detailed: Doctorate Degree Educational Attainment by Tract#18

Percentage of the population 25 years and older with given highest level of educational attainment
0.00%0.11%0.22%0.33%0.44%0.56%

Detailed: Professional Degree Educational Attainment by Tract#19

Percentage of the population 25 years and older with given highest level of educational attainment
0.553%0.602%0.650%0.698%0.746%0.795%

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

Percentage of the population 25 years and older with given highest level of educational attainment
3.93%4.05%4.17%4.28%4.40%4.52%

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

Percentage of the population 25 years and older with given highest level of educational attainment
10.74%10.94%11.13%11.33%11.52%11.72%

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

Percentage of the population 25 years and older with given highest level of educational attainment
10.00%10.25%10.50%10.75%11.01%11.26%

Detailed: Some College Educational Attainment by Tract#23

Percentage of the population 25 years and older with given highest level of educational attainment
18.853%18.896%18.938%18.980%19.022%19.064%

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

Percentage of the population 25 years and older with given highest level of educational attainment
38.7%40.0%41.3%42.7%44.0%45.3%

Detailed: Some High School Educational Attainment by Tract#25

Percentage of the population 25 years and older with given highest level of educational attainment
8.36%8.82%9.27%9.72%10.18%10.63%

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

Percentage of the population 25 years and older with given highest level of educational attainment
1.25%1.54%1.83%2.12%2.41%2.70%

Detailed: None Educational Attainment by Tract#27

Percentage of the population 25 years and older with given highest level of educational attainment
0.24%0.36%0.48%0.59%0.71%0.83%
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Educational Attainment by County Subdivision in the Columbus Area

There are 181 county subdivisions in the Columbus Area. This section compares the Reading Township to the 50 most populous county subdivisions in the Columbus Area and to those entities that contain or substantially overlap with the Reading Township. The least populous of the compared county subdivisions has a population of 6,814.

No H.S. Diploma by County Subdivision#28

Percent of population 25 years of age and older without a high school diploma (or equivalent).
Scope: population of the Reading Township, selected other county subdivisions in the Columbus Area, and entities that contain the Reading Township
0%5%10%15%20%Count#Franklin TownshipFranklinPike TownshipScioto TownshipSciotoWhitehallPerry CountyPerryHamilton TownshipHamiltonCirclevilleLondonUnion TownshipUnionPrairie TownshipPrairieUnited States of AmericaUnited StatesPleasant TownshipPleasantNewarkFalls TownshipFallsLancaster City TownshipLancaster CityWalnut TownshipWalnutJefferson TownshipJeffersonColumbusEast North CentralHeathMonroe TownshipMonroeOhio965900Tract 965900Harrison TownshipHarrisonMidwestParis TownshipParisColumbus Metro AreaColumbus AreaBlendon TownshipBlendonMadison TownshipMadisonPataskalaReading TownshipReadingEtna TownshipTruro TownshipTruroColumbusJackson TownshipJacksonDelaware City TownshipDelaware CityLiberty TownshipLibertyMifflin TownshipMifflinHarrison TownshipHarrisonViolet TownshipVioletBloom TownshipBloomWestervilleNorwich TownshipNorwichJefferson TownshipJeffersonBerlin TownshipBerlinConcord TownshipConcordPlain TownshipPlainWesterville City TownshipWesterville CityBexleyJerome TownshipJeromeSharon TownshipSharonDublinLiberty TownshipLibertyOrange TownshipOrangeGranville TownshipGranvilleGenoa TownshipGenoaUpper ArlingtonGrandview HeightsGrandview Hts24.885541%24.885541%24.9%1,685119.520852%19.520852%19.5%880219.407227%19.407227%19.4%1,434319.347697%19.347697%19.3%2,272416.089529%16.089529%16.1%3,88915.953777%15.953777%16.0%925515.617892%15.617892%15.6%1,442613.879574%13.879574%13.9%952713.757596%13.757596%13.8%815813.417155%13.417155%13.4%1,558913.020590%13.020590%13.0%27,818,38027.8M13.017397%13.017397%13.0%6511012.943290%12.943290%12.9%4,1061112.793800%12.793800%12.8%1,0071212.375999%12.375999%12.4%3,3311311.694215%11.694215%11.7%5661411.543839%11.543839%11.5%5781511.376979%11.376979%11.4%60,83160.8k1610.719464%10.719464%10.7%3,363,7843.36M10.699701%10.699701%10.7%7861710.520898%10.520898%10.5%5111810.514146%10.514146%10.5%825,155825k10.446809%10.446809%10.4%49110.252270%10.252270%10.3%5081910.244520%10.244520%10.2%4,641,8354.64M10.236565%10.236565%10.2%1,640209.314501%9.314501%9.3%123,226123k8.397699%8.397699%8.4%511218.155569%8.155569%8.2%1,384227.536491%7.536491%7.5%759237.306956%7.306956%7.3%2297.242608%7.242608%7.2%752246.948891%6.948891%6.9%1,259256.732802%6.732802%6.7%414266.480864%6.480864%6.5%1,944276.430658%6.430658%6.4%1,475286.338438%6.338438%6.3%327295.595517%5.595517%5.6%1,408305.490989%5.490989%5.5%326313.979966%3.979966%4.0%1,041323.712336%3.712336%3.7%223333.672345%3.672345%3.7%733343.371215%3.371215%3.4%795352.958028%2.958028%3.0%222362.710914%2.710914%2.7%116372.662407%2.662407%2.7%175382.451334%2.451334%2.5%170392.242444%2.242444%2.2%138402.234276%2.234276%2.2%173412.157989%2.157989%2.2%109421.943537%1.943537%1.9%232431.754602%1.754602%1.8%428441.730449%1.730449%1.7%312451.713710%1.713710%1.7%306461.642439%1.642439%1.6%87471.387785%1.387785%1.4%227481.346130%1.346130%1.3%324490.707108%0.707108%0.7%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#29

Percent of population 25 years of age and older with a bachelor's degree or higher..
Scope: population of the Reading Township, selected other county subdivisions in the Columbus Area, and entities that contain the Reading Township
0%20%40%60%Count#DublinBexleyUpper ArlingtonPlain TownshipPlainGrandview HeightsGrandview HtsLiberty TownshipLibertySharon TownshipSharonGenoa TownshipGenoaOrange TownshipOrangeConcord TownshipConcordGranville TownshipGranvilleJerome TownshipJeromeWesterville City TownshipWesterville CityBerlin TownshipBerlinJefferson TownshipJeffersonNorwich TownshipNorwichWestervilleMifflin TownshipMifflinViolet TownshipVioletBlendon TownshipBlendonBloom TownshipBloomColumbus Metro AreaColumbus AreaColumbusDelaware City TownshipDelaware CityEtna TownshipHarrison TownshipHarrisonUnited States of AmericaUnited StatesColumbusJackson TownshipJacksonMidwestEast North CentralTruro TownshipTruroParis TownshipParisPataskalaOhioUnion TownshipUnionMonroe TownshipMonroeMadison TownshipMadisonPleasant TownshipPleasantLiberty TownshipLibertyPrairie TownshipPrairieHarrison TownshipHarrisonNewarkHeathReading TownshipReadingWalnut TownshipWalnutLancaster City TownshipLancaster CityFalls TownshipFallsCircleville965900Tract 965900LondonJefferson TownshipJeffersonWhitehallPerry CountyPerryScioto TownshipSciotoPike TownshipHamilton TownshipHamiltonFranklin TownshipFranklin75.246997%75.246997%75.2%18,35518.4k174.092729%74.092729%74.1%5,737274.003905%74.003905%74.0%17,81217.8k371.521269%71.521269%71.5%4,960471.027168%71.027168%71.0%3,817566.605657%66.605657%66.6%12,00912.0k666.390215%66.390215%66.4%7,925765.470441%65.470441%65.5%10,70910.7k862.964830%62.964830%63.0%11,24311.2k962.954511%62.954511%63.0%4,1381062.828016%62.828016%62.8%3,3281157.038210%57.038210%57.0%2,8811256.824829%56.824829%56.8%3,4971356.415050%56.415050%56.4%2,4141455.429714%55.429714%55.4%4,1601553.460266%53.460266%53.5%12,60712.6k1651.127255%51.127255%51.1%10,20510.2k1743.925605%43.925605%43.9%11,05311.1k1843.657287%43.657287%43.7%11,41911.4k1936.203780%36.203780%36.2%2,2032035.924754%35.924754%35.9%2,1582134.785494%34.785494%34.8%460,194460k34.685843%34.685843%34.7%185,460185k2234.119545%34.119545%34.1%7,8262332.129442%32.129442%32.1%3,3362430.907866%30.907866%30.9%1,8352530.315023%30.315023%30.3%64,767,78764.8M29.663360%29.663360%29.7%1,8242628.997200%28.997200%29.0%8,6982728.952816%28.952816%29.0%13,118,64213.1M28.462853%28.462853%28.5%8,931,6868.93M27.878353%27.878353%27.9%5,0512827.476437%27.476437%27.5%4,4022926.968523%26.968523%27.0%2,7163026.667466%26.667466%26.7%2,092,8752.09M23.109386%23.109386%23.1%1,3693122.894791%22.894791%22.9%1,1123221.373011%21.373011%21.4%3,6273321.075785%21.075785%21.1%1,0543420.469083%20.469083%20.5%1,0563518.790906%18.790906%18.8%2,1823618.668012%18.668012%18.7%9253718.053148%18.053148%18.1%5,7273817.438062%17.438062%17.4%1,2813917.198468%17.198468%17.2%53916.880165%16.880165%16.9%8174016.462939%16.462939%16.5%4,4314116.198704%16.198704%16.2%1,2754215.715369%15.715369%15.7%1,4514315.234043%15.234043%15.2%71613.952471%13.952471%14.0%9574413.620931%13.620931%13.6%6824512.671379%12.671379%12.7%1,4884611.960614%11.960614%12.0%2,89111.056977%11.056977%11.1%8174710.048802%10.048802%10.0%453489.796482%9.796482%9.8%568499.038547%9.038547%9.0%61250
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older with a bachelor's degree or higher..

Very Advanced Degrees by County Subdivision#30

Percent of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).
Scope: population of the Reading Township, selected other county subdivisions in the Columbus Area, and entities that contain the Reading Township
0%5%10%15%Count#Upper ArlingtonBexleyPlain TownshipPlainGrandview HeightsGrandview HtsGranville TownshipGranvilleSharon TownshipSharonDublinLiberty TownshipLibertyJerome TownshipJeromeJefferson TownshipJeffersonConcord TownshipConcordOrange TownshipOrangeNorwich TownshipNorwichGenoa TownshipGenoaWestervilleWesterville City TownshipWesterville CityEtna TownshipBlendon TownshipBlendonColumbus Metro AreaColumbus AreaMifflin TownshipMifflinColumbusUnited States of AmericaUnited StatesBerlin TownshipBerlinDelaware City TownshipDelaware CityViolet TownshipVioletMidwestEast North CentralOhioBloom TownshipBloomUnion TownshipUnionHarrison TownshipHarrisonParis TownshipParisTruro TownshipTruroJackson TownshipJacksonMadison TownshipMadisonMonroe TownshipMonroePataskalaWalnut TownshipWalnutColumbusLiberty TownshipLibertyNewarkHarrison TownshipHarrisonLancaster City TownshipLancaster CityHeathFalls TownshipFallsCirclevillePleasant TownshipPleasantPrairie TownshipPrairieLondonFranklin TownshipFranklinScioto TownshipSciotoPerry CountyPerryPike TownshipJefferson TownshipJefferson965900Tract 965900WhitehallReading TownshipReadingHamilton TownshipHamilton16.893099%16.893099%16.9%4,066114.748805%14.748805%14.7%1,142214.534968%14.534968%14.5%1,008313.658355%13.658355%13.7%734413.196149%13.196149%13.2%699510.404624%10.404624%10.4%1,242610.031566%10.031566%10.0%2,44778.879645%8.879645%8.9%1,60188.156801%8.156801%8.2%41297.834777%7.834777%7.8%588107.333029%7.333029%7.3%482117.073253%7.073253%7.1%1,263126.632177%6.632177%6.6%1,564135.422755%5.422755%5.4%887145.145291%5.145291%5.1%1,027154.956126%4.956126%5.0%305164.256958%4.256958%4.3%442173.944125%3.944125%3.9%240183.620928%3.620928%3.6%47,90347.9k3.389898%3.389898%3.4%853193.357865%3.357865%3.4%17,95418.0k203.336158%3.336158%3.3%7,127,6737.13M3.108203%3.108203%3.1%133212.982081%2.982081%3.0%684222.940052%2.940052%2.9%769232.893416%2.893416%2.9%1,311,0191.31M2.855432%2.855432%2.9%896,039896k2.683241%2.683241%2.7%210,582211k2.596970%2.596970%2.6%156242.329507%2.329507%2.3%138252.280525%2.280525%2.3%113262.159665%2.159665%2.2%346272.102881%2.102881%2.1%381282.063608%2.063608%2.1%619292.044785%2.044785%2.0%347302.038295%2.038295%2.0%99311.737663%1.737663%1.7%175321.611570%1.611570%1.6%78331.317287%1.317287%1.3%81341.221167%1.221167%1.2%63351.182108%1.182108%1.2%375361.162203%1.162203%1.2%69371.159205%1.159205%1.2%312381.157092%1.157092%1.2%85391.105323%1.105323%1.1%87401.093902%1.093902%1.1%101410.939812%0.939812%0.9%47420.878402%0.878402%0.9%102430.845604%0.845604%0.8%58440.827057%0.827057%0.8%56450.825551%0.825551%0.8%61460.666087%0.666087%0.7%1610.621118%0.621118%0.6%28470.599161%0.599161%0.6%30480.553191%0.553191%0.6%260.425786%0.425786%0.4%50490.414805%0.414805%0.4%130.120731%0.120731%0.1%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 professional or doctorate degree (e.g., MBA, PhD, or MD).

Under-Education Sex Ratio by County Subdivision#31

Percentage more likely men are than women to not have a high school diploma (or equivalent) among people aged 25 years and older.
Scope: population of the Reading Township, selected other county subdivisions in the Columbus Area, and entities that contain the Reading Township
Female
Male
6x4x2x0x2xFM#BerlinPlainSciotoGrandview HtsJeffersonHarrisonPike TownshipConcordJeffersonPerryFallsLibertyJeromeEtna TownshipFranklinUnionWhitehallDelaware CityHeathLondonPrairieLancaster CityMidwestEast North CentralMadisonHamiltonCirclevilleUnited StatesOhioColumbus AreaPataskalaColumbusTract 965900NewarkJacksonMifflinNorwichPleasantGenoaLibertyBexleyMonroeWestervilleBlendonUpper ArlingtonHarrisonBloomOrangeDublinTruroReadingColumbusSharonWalnutVioletParisWesterville CityGranville-1.000000x-1.000000x3.534140x3.534140x3.53x1.220%1.22%4.310%4.31%1-1.000000x-1.000000x2.629883x2.629883x2.63x1.352%1.35%3.556%3.56%2-1.000000x-1.000000x2.609615x2.609615x2.61x9.040%9.04%23.590%23.6%3-1.000000x-1.000000x2.304788x2.304788x2.30x0.433%0.43%0.998%1.00%4-1.000000x-1.000000x2.116996x2.116996x2.12x1.925%1.92%4.074%4.07%5-1.000000x-1.000000x1.786905x1.786905x1.79x7.497%7.50%13.397%13.4%6-1.000000x-1.000000x1.742201x1.742201x1.74x14.389%14.4%25.069%25.1%7-1.000000x-1.000000x1.714595x1.714595x1.71x1.965%1.96%3.369%3.37%8-1.000000x-1.000000x1.507670x1.507670x1.51x9.251%9.25%13.947%13.9%9-1.000000x-1.000000x1.397781x1.397781x1.40x13.445%13.4%18.793%18.8%-1.000000x-1.000000x1.390745x1.390745x1.39x10.820%10.8%15.048%15.0%10-1.000000x-1.000000x1.376228x1.376228x1.38x5.385%5.38%7.410%7.41%11-1.000000x-1.000000x1.340740x1.340740x1.34x1.846%1.85%2.475%2.48%12-1.000000x-1.000000x1.335507x1.335507x1.34x6.236%6.24%8.328%8.33%13-1.000000x-1.000000x1.325542x1.325542x1.33x21.302%21.3%28.237%28.2%14-1.000000x-1.000000x1.310877x1.310877x1.31x11.876%11.9%15.568%15.6%15-1.000000x-1.000000x1.273148x1.273148x1.27x17.097%17.1%21.767%21.8%16-1.000000x-1.000000x1.236558x1.236558x1.24x5.780%5.78%7.147%7.15%17-1.000000x-1.000000x1.215459x1.215459x1.22x9.732%9.73%11.829%11.8%18-1.000000x-1.000000x1.184141x1.184141x1.18x12.791%12.8%15.147%15.1%19-1.000000x-1.000000x1.155189x1.155189x1.16x12.502%12.5%14.442%14.4%20-1.000000x-1.000000x1.144160x1.144160x1.14x11.593%11.6%13.265%13.3%21-1.000000x-1.000000x1.127915x1.127915x1.13x9.647%9.65%10.881%10.9%-1.000000x-1.000000x1.125371x1.125371x1.13x10.108%10.1%11.375%11.4%-1.000000x-1.000000x1.121607x1.121607x1.12x7.715%7.72%8.654%8.65%22-1.000000x-1.000000x1.118404x1.118404x1.12x15.081%15.1%16.867%16.9%23-1.000000x-1.000000x1.114300x1.114300x1.11x14.797%14.8%16.488%16.5%24-1.000000x-1.000000x1.109070x1.109070x1.11x12.369%12.4%13.719%13.7%-1.000000x-1.000000x1.105363x1.105363x1.11x10.008%10.0%11.063%11.1%-1.000000x-1.000000x1.104385x1.104385x1.10x8.867%8.87%9.793%9.79%-1.000000x-1.000000x1.079320x1.079320x1.08x7.269%7.27%7.845%7.85%25-1.000000x-1.000000x1.052237x1.052237x1.05x11.098%11.1%11.678%11.7%26-1.000000x-1.000000x1.039865x1.039865x1.04x10.245%10.2%10.653%10.7%-1.000000x-1.000000x1.036562x1.036562x1.04x12.733%12.7%13.198%13.2%27-1.000000x-1.000000x1.025236x1.025236x1.03x6.405%6.41%6.567%6.57%28-1.053306x-1.053306x1.05x1.000000x1.000000x5.733%5.73%5.442%5.44%29-1.057578x-1.057578x1.06x1.000000x1.000000x3.463%3.46%3.274%3.27%30-1.063491x-1.063491x1.06x1.000000x1.000000x13.412%13.4%12.612%12.6%31-1.064171x-1.064171x1.06x1.000000x1.000000x1.430%1.43%1.344%1.34%32-1.069669x-1.069669x1.07x1.000000x1.000000x1.786%1.79%1.670%1.67%33-1.073251x-1.073251x1.07x1.000000x1.000000x2.308%2.31%2.151%2.15%34-1.086161x-1.086161x1.09x1.000000x1.000000x10.956%11.0%10.086%10.1%35-1.099069x-1.099069x1.10x1.000000x1.000000x3.830%3.83%3.485%3.48%36-1.159243x-1.159243x1.16x1.000000x1.000000x8.950%8.95%7.720%7.72%37-1.283067x-1.283067x1.28x1.000000x1.000000x1.500%1.50%1.169%1.17%38-1.294968x-1.294968x1.29x1.000000x1.000000x6.211%6.21%4.797%4.80%39-1.306893x-1.306893x1.31x1.000000x1.000000x4.213%4.21%3.224%3.22%40-1.310439x-1.310439x1.31x1.000000x1.000000x1.935%1.93%1.476%1.48%41-1.385029x-1.385029x1.39x1.000000x1.000000x2.028%2.03%1.464%1.46%42-1.414047x-1.414047x1.41x1.000000x1.000000x8.025%8.03%5.675%5.68%43-1.441978x-1.441978x1.44x1.000000x1.000000x8.619%8.62%5.977%5.98%-1.455501x-1.455501x1.46x1.000000x1.000000x7.866%7.87%5.404%5.40%44-1.481750x-1.481750x1.48x1.000000x1.000000x2.283%2.28%1.540%1.54%45-1.494722x-1.494722x1.49x1.000000x1.000000x13.851%13.9%9.267%9.27%46-1.798212x-1.798212x1.80x1.000000x1.000000x5.036%5.04%2.800%2.80%47-2.016419x-2.016419x2.02x1.000000x1.000000x12.927%12.9%6.411%6.41%48-2.172632x-2.172632x2.17x1.000000x1.000000x3.024%3.02%1.392%1.39%49-7.570273x-7.570273x7.57x1.000000x1.000000x2.883%2.88%0.381%0.38%50
F percentage of females in category
M percentage of males in category
# rank of county subdivision out of 50 by male-to-female sex ratio

Over-Education Sex Ratio by County Subdivision#32

Percentage more likely men are than women to have a professional or doctorate degree (e.g., MBA, PhD, or MD) among people aged 25 years and older.
Scope: population of the Reading Township, selected other county subdivisions in the Columbus Area, and entities that contain the Reading Township
Female
Male
0x5x10xFM#Tract 965900ReadingFallsLondonHamiltonJeffersonPike TownshipPleasantLibertyPerryCirclevilleColumbusDelaware CityLancaster CityWestervilleBloomSharonHarrisonHeathWalnutHarrisonLibertyMifflinNewarkJeromeConcordGranvillePlainDublinFranklinUpper ArlingtonNorwichTruroOhioBexleyJeffersonEast North CentralMidwestMadisonColumbus AreaUnited StatesEtna TownshipBlendonBerlinColumbusOrangeJacksonGrandview HtsVioletGenoaPrairieMonroeParisWesterville CityPataskalaUnionWhitehallScioto-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%1.117%1.12%-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%0.835%0.84%-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%2.367%2.37%1-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%1.830%1.83%2-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%0.247%0.25%3-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%1.227%1.23%4-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%1.293%1.29%5-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%1.906%1.91%6-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.220%0.22%2.347%2.35%7-1.000000x-1.000000x6.135051x6.135051x6.14x0.188%0.19%1.155%1.15%-1.000000x-1.000000x4.574814x4.574814x4.57x0.400%0.40%1.830%1.83%8-1.000000x-1.000000x3.824499x3.824499x3.82x0.573%0.57%2.190%2.19%9-1.000000x-1.000000x2.782910x2.782910x2.78x1.613%1.61%4.490%4.49%10-1.000000x-1.000000x2.442537x2.442537x2.44x0.692%0.69%1.690%1.69%11-1.000000x-1.000000x2.420464x2.420464x2.42x3.120%3.12%7.551%7.55%12-1.000000x-1.000000x2.407434x2.407434x2.41x1.517%1.52%3.651%3.65%13-1.000000x-1.000000x2.352477x2.352477x2.35x6.431%6.43%15.129%15.1%14-1.000000x-1.000000x2.344320x2.344320x2.34x1.401%1.40%3.284%3.28%15-1.000000x-1.000000x2.253443x2.253443x2.25x0.733%0.73%1.652%1.65%16-1.000000x-1.000000x2.251208x2.251208x2.25x1.014%1.01%2.284%2.28%17-1.000000x-1.000000x2.203299x2.203299x2.20x0.721%0.72%1.588%1.59%18-1.000000x-1.000000x2.163540x2.163540x2.16x5.691%5.69%12.313%12.3%19-1.000000x-1.000000x2.069018x2.069018x2.07x2.252%2.25%4.660%4.66%20-1.000000x-1.000000x1.967904x1.967904x1.97x0.822%0.82%1.618%1.62%21-1.000000x-1.000000x1.911908x1.911908x1.91x5.617%5.62%10.739%10.7%22-1.000000x-1.000000x1.876463x1.876463x1.88x5.109%5.11%9.587%9.59%23-1.000000x-1.000000x1.849712x1.849712x1.85x9.285%9.28%17.174%17.2%24-1.000000x-1.000000x1.848477x1.848477x1.85x10.213%10.2%18.878%18.9%25-1.000000x-1.000000x1.832511x1.832511x1.83x7.149%7.15%13.100%13.1%26-1.000000x-1.000000x1.821032x1.821032x1.82x0.581%0.58%1.057%1.06%27-1.000000x-1.000000x1.802942x1.802942x1.80x12.297%12.3%22.171%22.2%28-1.000000x-1.000000x1.734085x1.734085x1.73x4.889%4.89%8.478%8.48%29-1.000000x-1.000000x1.688068x1.688068x1.69x1.599%1.60%2.699%2.70%30-1.000000x-1.000000x1.669500x1.669500x1.67x2.031%2.03%3.391%3.39%-1.000000x-1.000000x1.622554x1.622554x1.62x11.419%11.4%18.528%18.5%31-1.000000x-1.000000x1.599641x1.599641x1.60x6.082%6.08%9.728%9.73%32-1.000000x-1.000000x1.597848x1.597848x1.60x2.216%2.22%3.541%3.54%-1.000000x-1.000000x1.589934x1.589934x1.59x2.251%2.25%3.579%3.58%-1.000000x-1.000000x1.576121x1.576121x1.58x1.610%1.61%2.537%2.54%33-1.000000x-1.000000x1.567060x1.567060x1.57x2.842%2.84%4.454%4.45%-1.000000x-1.000000x1.526215x1.526215x1.53x2.660%2.66%4.060%4.06%-1.000000x-1.000000x1.457364x1.457364x1.46x3.489%3.49%5.085%5.09%34-1.000000x-1.000000x1.449489x1.449489x1.45x3.282%3.28%4.757%4.76%35-1.000000x-1.000000x1.429540x1.429540x1.43x2.575%2.57%3.680%3.68%36-1.000000x-1.000000x1.413654x1.413654x1.41x2.801%2.80%3.959%3.96%37-1.000000x-1.000000x1.412405x1.412405x1.41x5.901%5.90%8.334%8.33%38-1.000000x-1.000000x1.297270x1.297270x1.30x1.812%1.81%2.351%2.35%39-1.000000x-1.000000x1.232696x1.232696x1.23x12.274%12.3%15.131%15.1%40-1.000000x-1.000000x1.149458x1.149458x1.15x2.746%2.75%3.157%3.16%41-1.000000x-1.000000x1.125108x1.125108x1.13x5.111%5.11%5.751%5.75%42-1.004340x-1.004340x1.00x1.000000x1.000000x0.880%0.88%0.876%0.88%43-1.020828x-1.020828x1.02x1.000000x1.000000x2.059%2.06%2.017%2.02%44-1.182723x-1.182723x1.18x1.000000x1.000000x2.307%2.31%1.950%1.95%45-1.269877x-1.269877x1.27x1.000000x1.000000x5.517%5.52%4.345%4.34%46-1.270588x-1.270588x1.27x1.000000x1.000000x1.928%1.93%1.518%1.52%47-1.311831x-1.311831x1.31x1.000000x1.000000x2.651%2.65%2.021%2.02%48-1.806191x-1.806191x1.81x1.000000x1.000000x0.542%0.54%0.300%0.30%49-2.735243x-2.735243x2.74x1.000000x1.000000x1.507%1.51%0.551%0.55%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 Ohio

There are 1,606 county subdivisions in Ohio. This section compares the Reading Township to the 50 most populous county subdivisions in Ohio and to those entities that contain or substantially overlap with the Reading Township. The least populous of the compared county subdivisions has a population of 36,945.

No H.S. Diploma by County Subdivision#33

Percent of population 25 years of age and older without a high school diploma (or equivalent).
Scope: population of the Reading Township, selected other county subdivisions in Ohio, and entities that contain the Reading Township
0%5%10%15%20%Count#ClevelandMiddletownLorainYoungstownSpringfieldDaytonMansfieldLimaPerry CountyPerryMarion TownshipMarionCantonHamiltonWarrenToledoCincinnatiAkronElyriaUnited States of AmericaUnited StatesNewarkBath TownshipLancaster City TownshipLancaster CityColumbusColerain TownshipColerainEast North CentralEuclidOhio965900Tract 965900MidwestParmaColumbus Metro AreaColumbus AreaFindlayFairfieldMiami TownshipMiamiUnion TownshipUnionReading TownshipReadingHuber HeightsJackson TownshipJacksonCleveland HeightsCleveland HtsCuyahoga FallsPlain TownshipPlainLakewoodKetteringGreen TownshipGrnBoardman TownshipBoardmanWest Chester TownshipW ChesterMiami TownshipMiamiMifflin TownshipMifflinMentorLiberty TownshipLibertySylvania TownshipSylvaniaStrongsvilleViolet TownshipVioletJackson TownshipJacksonWashington TownshipWashingtonAnderson TownshipAndersonDeerfield TownshipDeerfieldBeavercreek TownshipBeavercreekDublin21.582420%21.582420%21.6%54,98155.0k118.211726%18.211726%18.2%5,591217.551080%17.551080%17.6%7,207316.999061%16.999061%17.0%7,424416.947843%16.947843%16.9%6,580516.928359%16.928359%16.9%14,88914.9k616.499446%16.499446%16.5%5,361716.278163%16.278163%16.3%3,757816.089529%16.089529%16.1%3,88915.742056%15.742056%15.7%4,875915.631958%15.631958%15.6%7,3021015.293656%15.293656%15.3%6,2341115.055107%15.055107%15.1%4,0981214.332972%14.332972%14.3%26,34326.3k1313.761583%13.761583%13.8%26,28626.3k1413.591726%13.591726%13.6%17,95118.0k1513.343328%13.343328%13.3%4,8061613.020590%13.020590%13.0%27,818,38027.8M12.943290%12.943290%12.9%4,1061712.411362%12.411362%12.4%3,0631812.375999%12.375999%12.4%3,3311911.376979%11.376979%11.4%60,83160.8k2010.847918%10.847918%10.8%4,3142110.719464%10.719464%10.7%3,363,7843.36M10.656581%10.656581%10.7%3,5222210.514146%10.514146%10.5%825,155825k10.446809%10.446809%10.4%49110.244520%10.244520%10.2%4,641,8354.64M9.939137%9.939137%9.9%5,683239.314501%9.314501%9.3%123,226123k9.003845%9.003845%9.0%2,482248.712972%8.712972%8.7%2,559258.614662%8.614662%8.6%3,080268.597523%8.597523%8.6%2,777277.306956%7.306956%7.3%2297.261193%7.261193%7.3%1,797286.480864%6.480864%6.5%1,944296.307136%6.307136%6.3%1,918306.197364%6.197364%6.2%2,215316.171554%6.171554%6.2%2,311326.109570%6.109570%6.1%2,246335.953744%5.953744%6.0%2,340345.804316%5.804316%5.8%2,402355.764815%5.764815%5.8%1,682365.727981%5.727981%5.7%2,390375.628396%5.628396%5.6%1,554385.595517%5.595517%5.6%1,408395.268752%5.268752%5.3%1,834405.136204%5.136204%5.1%1,169414.322119%4.322119%4.3%1,462424.066023%4.066023%4.1%1,313433.979966%3.979966%4.0%1,041443.830735%3.830735%3.8%1,118453.637690%3.637690%3.6%1,496463.351036%3.351036%3.4%978473.293195%3.293195%3.3%815483.105178%3.105178%3.1%1,170491.754602%1.754602%1.8%42850
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older without a high school diploma (or equivalent).

Bachelor's Degrees by County Subdivision#34

Percent of population 25 years of age and older with a bachelor's degree or higher..
Scope: population of the Reading Township, selected other county subdivisions in Ohio, and entities that contain the Reading Township
0%20%40%60%Count#DublinDeerfield TownshipDeerfieldAnderson TownshipAndersonWashington TownshipWashingtonBeavercreek TownshipBeavercreekCleveland HeightsCleveland HtsLiberty TownshipLibertyWest Chester TownshipW ChesterSylvania TownshipSylvaniaStrongsvilleMifflin TownshipMifflinViolet TownshipVioletLakewoodMiami TownshipMiamiJackson TownshipJacksonColumbus Metro AreaColumbus AreaColumbusCincinnatiKetteringPlain TownshipPlainGreen TownshipGrnCuyahoga FallsMentorBoardman TownshipBoardmanUnited States of AmericaUnited StatesUnion TownshipUnionJackson TownshipJacksonMidwestEast North CentralFairfieldBath TownshipFindlayMiami TownshipMiamiOhioHuber HeightsColerain TownshipColerainEuclidAkronParmaNewarkToledoDaytonReading TownshipReadingMiddletownLancaster City TownshipLancaster CityClevelandElyria965900Tract 965900HamiltonSpringfieldCantonMansfieldWarrenYoungstownPerry CountyPerryLorainLimaMarion TownshipMarion75.246997%75.246997%75.2%18,35518.4k157.851139%57.851139%57.9%14,31714.3k256.039061%56.039061%56.0%16,35516.4k352.483891%52.483891%52.5%21,58421.6k451.261976%51.261976%51.3%19,31519.3k550.973364%50.973364%51.0%15,50115.5k650.549209%50.549209%50.5%11,50511.5k747.424805%47.424805%47.4%19,78819.8k846.115414%46.115414%46.1%15,59915.6k944.614765%44.614765%44.6%14,40714.4k1043.925605%43.925605%43.9%11,05311.1k1143.657287%43.657287%43.7%11,41911.4k1243.651053%43.651053%43.7%16,04716.0k1342.654835%42.654835%42.7%11,77711.8k1441.432243%41.432243%41.4%12,09212.1k1534.785494%34.785494%34.8%460,194460k34.685843%34.685843%34.7%185,460185k1633.783048%33.783048%33.8%64,52964.5k1733.391853%33.391853%33.4%13,12413.1k1833.138386%33.138386%33.1%12,40912.4k1932.914482%32.914482%32.9%13,62113.6k2032.380180%32.380180%32.4%11,57311.6k2132.238789%32.238789%32.2%11,22211.2k2231.219796%31.219796%31.2%9,1092330.315023%30.315023%30.3%64,767,78764.8M29.613003%29.613003%29.6%9,5652428.997200%28.997200%29.0%8,6982528.952816%28.952816%29.0%13,118,64213.1M28.462853%28.462853%28.5%8,931,6868.93M28.219271%28.219271%28.2%8,2882626.954091%26.954091%27.0%6,6522726.775738%26.775738%26.8%7,3812826.713842%26.713842%26.7%9,5512926.667466%26.667466%26.7%2,092,8752.09M22.834168%22.834168%22.8%5,6513021.665661%21.665661%21.7%8,6163120.614221%20.614221%20.6%6,8133220.213821%20.213821%20.2%26,69726.7k3319.988457%19.988457%20.0%11,42911.4k3418.053148%18.053148%18.1%5,7273518.048021%18.048021%18.0%33,17133.2k3617.635555%17.635555%17.6%15,51115.5k3717.198468%17.198468%17.2%53916.631922%16.631922%16.6%5,1063816.462939%16.462939%16.5%4,4313916.073076%16.073076%16.1%40,94640.9k4015.411739%15.411739%15.4%5,5514115.234043%15.234043%15.2%71615.075315%15.075315%15.1%6,1454214.851256%14.851256%14.9%5,7664314.608666%14.608666%14.6%6,8244413.812631%13.812631%13.8%4,4884512.832476%12.832476%12.8%3,4934612.044055%12.044055%12.0%5,2604711.960614%11.960614%12.0%2,89111.718579%11.718579%11.7%4,8124811.460139%11.460139%11.5%2,6454910.478559%10.478559%10.5%3,24550
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older with a bachelor's degree or higher..

Very Advanced Degrees by County Subdivision#35

Percent of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).
Scope: population of the Reading Township, selected other county subdivisions in Ohio, and entities that contain the Reading Township
0%2%4%6%8%10%Count#Cleveland HeightsCleveland HtsDublinAnderson TownshipAndersonSylvania TownshipSylvaniaWashington TownshipWashingtonBeavercreek TownshipBeavercreekJackson TownshipJacksonLakewoodCincinnatiStrongsvilleDeerfield TownshipDeerfieldWest Chester TownshipW ChesterKetteringColumbus Metro AreaColumbus AreaLiberty TownshipLibertyMifflin TownshipMifflinColumbusUnited States of AmericaUnited StatesPlain TownshipPlainBoardman TownshipBoardmanViolet TownshipVioletMiami TownshipMiamiMidwestEast North CentralOhioCuyahoga FallsGreen TownshipGrnBath TownshipAkronJackson TownshipJacksonClevelandMentorColerain TownshipColerainMiami TownshipMiamiFindlayToledoSpringfieldFairfieldEuclidHuber HeightsLimaDaytonCantonHamiltonUnion TownshipUnionParmaNewarkLancaster City TownshipLancaster CityMansfieldMiddletownLorainElyriaYoungstownWarrenMarion TownshipMarionPerry CountyPerry965900Tract 965900Reading TownshipReading10.753042%10.753042%10.8%3,270110.031566%10.031566%10.0%2,44727.476443%7.476443%7.5%2,18237.470585%7.470585%7.5%2,52746.820669%6.820669%6.8%2,80556.685422%6.685422%6.7%2,51965.297242%5.297242%5.3%1,54675.051412%5.051412%5.1%1,85784.729595%4.729595%4.7%9,03494.555308%4.555308%4.6%1,471104.149830%4.149830%4.1%1,027114.100659%4.100659%4.1%1,711123.778338%3.778338%3.8%1,485133.620928%3.620928%3.6%47,90347.9k3.514938%3.514938%3.5%800143.389898%3.389898%3.4%853153.357865%3.357865%3.4%17,95418.0k163.336158%3.336158%3.3%7,127,6737.13M3.036372%3.036372%3.0%1,137172.957809%2.957809%3.0%863182.940052%2.940052%2.9%769192.911988%2.911988%2.9%804202.893416%2.893416%2.9%1,311,0191.31M2.855432%2.855432%2.9%896,039896k2.683241%2.683241%2.7%210,582211k2.481744%2.481744%2.5%887212.476862%2.476862%2.5%1,025222.451477%2.451477%2.5%605232.163955%2.163955%2.2%2,858242.063608%2.063608%2.1%619251.927780%1.927780%1.9%4,911261.815622%1.815622%1.8%632271.815530%1.815530%1.8%722281.762090%1.762090%1.8%630291.675978%1.675978%1.7%462301.642065%1.642065%1.6%3,018311.545396%1.545396%1.5%600321.477698%1.477698%1.5%434331.388805%1.388805%1.4%459341.349604%1.349604%1.3%334351.304159%1.304159%1.3%301361.257490%1.257490%1.3%1,106371.245933%1.245933%1.2%582381.241352%1.241352%1.2%506391.238390%1.238390%1.2%400401.236490%1.236490%1.2%707411.182108%1.182108%1.2%375421.159205%1.159205%1.2%312431.104887%1.104887%1.1%359440.996743%0.996743%1.0%306450.964372%0.964372%1.0%396460.952302%0.952302%1.0%343470.794541%0.794541%0.8%347480.742101%0.742101%0.7%202490.720098%0.720098%0.7%223500.666087%0.666087%0.7%1610.553191%0.553191%0.6%260.414805%0.414805%0.4%13
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).

Under-Education Sex Ratio by County Subdivision#36

Percentage more likely men are than women to not have a high school diploma (or equivalent) among people aged 25 years and older.
Scope: population of the Reading Township, selected other county subdivisions in Ohio, and entities that contain the Reading Township
Female
Male
1x0x1xFM#AndersonMansfieldCleveland HtsPerryBeavercreekUnionToledoFindlayLorainMarionYoungstownColerainGrnFairfieldElyriaMiddletownLancaster CityMidwestEast North CentralSpringfieldWarrenDaytonCantonUnited StatesOhioColumbus AreaLimaParmaColumbusClevelandDeerfieldTract 965900MentorNewarkW ChesterPlainLibertyJacksonHuber HeightsHamiltonJacksonCincinnatiAkronMifflinSylvaniaMiamiEuclidMiamiCuyahoga FallsStrongsvilleLakewoodBath TownshipDublinReadingKetteringWashingtonBoardmanViolet-1.000000x-1.000000x1.766803x1.766803x1.77x2.468%2.47%4.360%4.36%1-1.000000x-1.000000x1.592708x1.592708x1.59x12.530%12.5%19.956%20.0%2-1.000000x-1.000000x1.485471x1.485471x1.49x5.146%5.15%7.645%7.64%3-1.000000x-1.000000x1.397781x1.397781x1.40x13.445%13.4%18.793%18.8%-1.000000x-1.000000x1.332397x1.332397x1.33x2.666%2.67%3.552%3.55%4-1.000000x-1.000000x1.242595x1.242595x1.24x7.704%7.70%9.573%9.57%5-1.000000x-1.000000x1.227011x1.227011x1.23x12.945%12.9%15.884%15.9%6-1.000000x-1.000000x1.222843x1.222843x1.22x8.133%8.13%9.946%9.95%7-1.000000x-1.000000x1.207850x1.207850x1.21x16.045%16.0%19.380%19.4%8-1.000000x-1.000000x1.204406x1.204406x1.20x14.131%14.1%17.020%17.0%9-1.000000x-1.000000x1.194114x1.194114x1.19x15.554%15.6%18.574%18.6%10-1.000000x-1.000000x1.175447x1.175447x1.18x10.032%10.0%11.792%11.8%11-1.000000x-1.000000x1.173903x1.173903x1.17x5.370%5.37%6.304%6.30%12-1.000000x-1.000000x1.173628x1.173628x1.17x8.033%8.03%9.428%9.43%13-1.000000x-1.000000x1.166450x1.166450x1.17x12.379%12.4%14.439%14.4%14-1.000000x-1.000000x1.147049x1.147049x1.15x17.010%17.0%19.512%19.5%15-1.000000x-1.000000x1.144160x1.144160x1.14x11.593%11.6%13.265%13.3%16-1.000000x-1.000000x1.127915x1.127915x1.13x9.647%9.65%10.881%10.9%-1.000000x-1.000000x1.125371x1.125371x1.13x10.108%10.1%11.375%11.4%-1.000000x-1.000000x1.124452x1.124452x1.12x16.027%16.0%18.022%18.0%17-1.000000x-1.000000x1.124390x1.124390x1.12x14.230%14.2%16.000%16.0%18-1.000000x-1.000000x1.114342x1.114342x1.11x16.070%16.1%17.907%17.9%19-1.000000x-1.000000x1.109752x1.109752x1.11x14.885%14.9%16.518%16.5%20-1.000000x-1.000000x1.109070x1.109070x1.11x12.369%12.4%13.719%13.7%-1.000000x-1.000000x1.105363x1.105363x1.11x10.008%10.0%11.063%11.1%-1.000000x-1.000000x1.104385x1.104385x1.10x8.867%8.87%9.793%9.79%-1.000000x-1.000000x1.087544x1.087544x1.09x15.592%15.6%16.957%17.0%21-1.000000x-1.000000x1.081824x1.081824x1.08x9.568%9.57%10.350%10.4%22-1.000000x-1.000000x1.052237x1.052237x1.05x11.098%11.1%11.678%11.7%23-1.000000x-1.000000x1.046686x1.046686x1.05x21.119%21.1%22.105%22.1%24-1.000000x-1.000000x1.045216x1.045216x1.05x3.224%3.22%3.370%3.37%25-1.000000x-1.000000x1.039865x1.039865x1.04x10.245%10.2%10.653%10.7%-1.000000x-1.000000x1.038813x1.038813x1.04x5.175%5.17%5.376%5.38%26-1.000000x-1.000000x1.036562x1.036562x1.04x12.733%12.7%13.198%13.2%27-1.000000x-1.000000x1.031821x1.031821x1.03x5.641%5.64%5.821%5.82%28-1.000000x-1.000000x1.027725x1.027725x1.03x6.093%6.09%6.262%6.26%29-1.000000x-1.000000x1.026192x1.026192x1.03x5.072%5.07%5.205%5.20%30-1.000000x-1.000000x1.025236x1.025236x1.03x6.405%6.41%6.567%6.57%31-1.000000x-1.000000x1.021443x1.021443x1.02x7.189%7.19%7.344%7.34%32-1.000000x-1.000000x1.015682x1.015682x1.02x15.182%15.2%15.420%15.4%33-1.000000x-1.000000x1.006889x1.006889x1.01x3.818%3.82%3.844%3.84%34-1.000000x-1.000000x1.001229x1.001229x1.00x13.754%13.8%13.771%13.8%35-1.001506x-1.001506x1.00x1.000000x1.000000x13.601%13.6%13.581%13.6%36-1.053306x-1.053306x1.05x1.000000x1.000000x5.733%5.73%5.442%5.44%37-1.068860x-1.068860x1.07x1.000000x1.000000x4.454%4.45%4.167%4.17%38-1.075183x-1.075183x1.08x1.000000x1.000000x5.828%5.83%5.420%5.42%39-1.084060x-1.084060x1.08x1.000000x1.000000x11.029%11.0%10.174%10.2%40-1.123601x-1.123601x1.12x1.000000x1.000000x9.091%9.09%8.091%8.09%41-1.132510x-1.132510x1.13x1.000000x1.000000x6.567%6.57%5.799%5.80%42-1.209810x-1.209810x1.21x1.000000x1.000000x4.433%4.43%3.664%3.66%43-1.275391x-1.275391x1.28x1.000000x1.000000x6.820%6.82%5.347%5.35%44-1.295653x-1.295653x1.30x1.000000x1.000000x13.964%14.0%10.778%10.8%45-1.385029x-1.385029x1.39x1.000000x1.000000x2.028%2.03%1.464%1.46%46-1.441978x-1.441978x1.44x1.000000x1.000000x8.619%8.62%5.977%5.98%-1.505212x-1.505212x1.51x1.000000x1.000000x7.040%7.04%4.677%4.68%47-1.641786x-1.641786x1.64x1.000000x1.000000x4.457%4.46%2.715%2.71%48-1.660386x-1.660386x1.66x1.000000x1.000000x7.066%7.07%4.256%4.26%49-1.798212x-1.798212x1.80x1.000000x1.000000x5.036%5.04%2.800%2.80%50
F percentage of females in category
M percentage of males in category
# rank of county subdivision out of 50 by male-to-female sex ratio

Over-Education Sex Ratio by County Subdivision#37

Percentage more likely men are than women to have a professional or doctorate degree (e.g., MBA, PhD, or MD) among people aged 25 years and older.
Scope: population of the Reading Township, selected other county subdivisions in Ohio, and entities that contain the Reading Township
Female
Male
0x5x10xFM#Tract 965900ReadingPerryElyriaSpringfieldWashingtonYoungstownBoardmanLorainMiddletownLancaster CityFindlayAndersonJacksonKetteringMifflinPlainBeavercreekDeerfieldDaytonNewarkEuclidMiamiAkronDublinSylvaniaStrongsvilleBath TownshipOhioFairfieldMansfieldW ChesterHuber HeightsLakewoodEast North CentralMidwestColumbus AreaWarrenUnited StatesLibertyParmaCleveland HtsColumbusUnionMentorGrnJacksonClevelandCincinnatiMiamiMarionVioletColerainToledoHamiltonCantonCuyahoga FallsLima-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%1.117%1.12%-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%0.835%0.84%-1.000000x-1.000000x6.135051x6.135051x6.14x0.188%0.19%1.155%1.15%-1.000000x-1.000000x3.557903x3.557903x3.56x0.433%0.43%1.542%1.54%1-1.000000x-1.000000x3.025650x3.025650x3.03x0.799%0.80%2.417%2.42%2-1.000000x-1.000000x2.977263x2.977263x2.98x3.534%3.53%10.523%10.5%3-1.000000x-1.000000x2.809581x2.809581x2.81x0.426%0.43%1.196%1.20%4-1.000000x-1.000000x2.780060x2.780060x2.78x1.621%1.62%4.507%4.51%5-1.000000x-1.000000x2.695011x2.695011x2.70x0.546%0.55%1.472%1.47%6-1.000000x-1.000000x2.596948x2.596948x2.60x0.564%0.56%1.465%1.46%7-1.000000x-1.000000x2.442537x2.442537x2.44x0.692%0.69%1.690%1.69%8-1.000000x-1.000000x2.437656x2.437656x2.44x0.991%0.99%2.417%2.42%9-1.000000x-1.000000x2.428350x2.428350x2.43x4.486%4.49%10.893%10.9%10-1.000000x-1.000000x2.183841x2.183841x2.18x3.386%3.39%7.394%7.39%11-1.000000x-1.000000x2.155653x2.155653x2.16x2.468%2.47%5.319%5.32%12-1.000000x-1.000000x2.069018x2.069018x2.07x2.252%2.25%4.660%4.66%13-1.000000x-1.000000x2.024516x2.024516x2.02x2.059%2.06%4.169%4.17%14-1.000000x-1.000000x2.007898x2.007898x2.01x4.457%4.46%8.948%8.95%15-1.000000x-1.000000x1.991550x1.991550x1.99x2.826%2.83%5.628%5.63%16-1.000000x-1.000000x1.989047x1.989047x1.99x0.860%0.86%1.711%1.71%17-1.000000x-1.000000x1.967904x1.967904x1.97x0.822%0.82%1.618%1.62%18-1.000000x-1.000000x1.903271x1.903271x1.90x0.997%1.00%1.897%1.90%19-1.000000x-1.000000x1.851159x1.851159x1.85x2.056%2.06%3.806%3.81%20-1.000000x-1.000000x1.846298x1.846298x1.85x1.550%1.55%2.862%2.86%21-1.000000x-1.000000x1.832511x1.832511x1.83x7.149%7.15%13.100%13.1%22-1.000000x-1.000000x1.805502x1.805502x1.81x5.447%5.45%9.835%9.84%23-1.000000x-1.000000x1.769961x1.769961x1.77x3.331%3.33%5.895%5.90%24-1.000000x-1.000000x1.691857x1.691857x1.69x1.833%1.83%3.102%3.10%25-1.000000x-1.000000x1.669500x1.669500x1.67x2.031%2.03%3.391%3.39%-1.000000x-1.000000x1.650680x1.650680x1.65x1.122%1.12%1.852%1.85%26-1.000000x-1.000000x1.650301x1.650301x1.65x0.820%0.82%1.353%1.35%27-1.000000x-1.000000x1.648570x1.648570x1.65x3.124%3.12%5.150%5.15%28-1.000000x-1.000000x1.627164x1.627164x1.63x1.044%1.04%1.699%1.70%29-1.000000x-1.000000x1.624128x1.624128x1.62x3.883%3.88%6.306%6.31%30-1.000000x-1.000000x1.597848x1.597848x1.60x2.216%2.22%3.541%3.54%-1.000000x-1.000000x1.589934x1.589934x1.59x2.251%2.25%3.579%3.58%-1.000000x-1.000000x1.567060x1.567060x1.57x2.842%2.84%4.454%4.45%-1.000000x-1.000000x1.543502x1.543502x1.54x0.592%0.59%0.914%0.91%31-1.000000x-1.000000x1.526215x1.526215x1.53x2.660%2.66%4.060%4.06%-1.000000x-1.000000x1.525512x1.525512x1.53x2.801%2.80%4.272%4.27%32-1.000000x-1.000000x1.433883x1.433883x1.43x1.025%1.03%1.470%1.47%33-1.000000x-1.000000x1.416609x1.416609x1.42x9.009%9.01%12.763%12.8%34-1.000000x-1.000000x1.413654x1.413654x1.41x2.801%2.80%3.959%3.96%35-1.000000x-1.000000x1.348352x1.348352x1.35x1.062%1.06%1.431%1.43%36-1.000000x-1.000000x1.325696x1.325696x1.33x1.576%1.58%2.089%2.09%37-1.000000x-1.000000x1.319751x1.319751x1.32x2.156%2.16%2.845%2.85%38-1.000000x-1.000000x1.297270x1.297270x1.30x1.812%1.81%2.351%2.35%39-1.000000x-1.000000x1.286599x1.286599x1.29x1.699%1.70%2.186%2.19%40-1.000000x-1.000000x1.280610x1.280610x1.28x4.179%4.18%5.351%5.35%41-1.000000x-1.000000x1.246667x1.246667x1.25x1.577%1.58%1.966%1.97%42-1.000000x-1.000000x1.217109x1.217109x1.22x0.642%0.64%0.782%0.78%43-1.000000x-1.000000x1.149458x1.149458x1.15x2.746%2.75%3.157%3.16%44-1.000000x-1.000000x1.145376x1.145376x1.15x1.701%1.70%1.948%1.95%45-1.000000x-1.000000x1.141406x1.141406x1.14x1.539%1.54%1.757%1.76%46-1.000000x-1.000000x1.036455x1.036455x1.04x1.220%1.22%1.265%1.26%47-1.103703x-1.103703x1.10x1.000000x1.000000x1.302%1.30%1.180%1.18%48-1.188945x-1.188945x1.19x1.000000x1.000000x2.687%2.69%2.260%2.26%49-1.404867x-1.404867x1.40x1.000000x1.000000x1.525%1.53%1.086%1.09%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 Reading Township to the 50 most populous county subdivisions in the Midwest and to those entities that contain or substantially overlap with the Reading Township. The least populous of the compared county subdivisions has a population of 112,821.

No H.S. Diploma by County Subdivision#38

Percent of population 25 years of age and older without a high school diploma (or equivalent).
Scope: population of the Reading Township, selected other county subdivisions in the Midwest, and entities that contain the Reading Township
0%10%20%30%Count#Aurora TownshipAuroraCenter TownshipCtrKansas CityClevelandWayne TownshipWayneDetroitMilwaukeeNorth TownshipNDaytonChicagoPerry CountyPerryProviso TownshipProvisoRockford TownshipRockfordSt. LouisWarrenGrand RapidsToledoBlue TownshipCincinnatiAkronSt. PaulSterling HeightsSterling HtsUnited States of AmericaUnited StatesThornton TownshipThorntonWichitaKaw TownshipOmahaBloomingdale TownshipBloomingdaleColumbusMaine TownshipMaineTopekaMinneapolisSpringfield TownshipSpringfieldEast North CentralWorth TownshipWorthOhio965900Tract 965900MidwestLawrence TownshipLawrenceSioux FallsColumbus Metro AreaColumbus AreaCapital TownshipCapitalWheeling TownshipWheelingPalatine TownshipPalatineSchaumburg TownshipSchaumburgReading TownshipReadingLincolnWashington TownshipWashingtonOlatheFargoCedar RapidsYork TownshipMilton TownshipMiltonMadisonDowners Grove TownshipDowners GrvLisle TownshipLisleOverland ParkAnn Arbor33.464284%33.464284%33.5%29,81429.8k123.165532%23.165532%23.2%22,92622.9k222.659362%22.659362%22.7%21,21821.2k321.582420%21.582420%21.6%54,98155.0k421.037720%21.037720%21.0%18,48918.5k521.003600%21.003600%21.0%90,67890.7k617.485105%17.485105%17.5%63,80063.8k717.062713%17.062713%17.1%17,39117.4k816.928359%16.928359%16.9%14,88914.9k916.905373%16.905373%16.9%309,770310k1016.089529%16.089529%16.1%3,88915.636222%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%11,14911.1k3110.719464%10.719464%10.7%3,363,7843.36M10.678962%10.678962%10.7%11,17511.2k3210.514146%10.514146%10.5%825,155825k10.446809%10.446809%10.4%49110.244520%10.244520%10.2%4,641,8354.64M10.179618%10.179618%10.2%8,161339.702326%9.702326%9.7%9,123349.314501%9.314501%9.3%123,226123k8.623103%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%7,226387.306956%7.306956%7.3%2297.092309%7.092309%7.1%11,88611.9k396.804680%6.804680%6.8%6,403406.424130%6.424130%6.4%5,331416.055621%6.055621%6.1%4,270425.981653%5.981653%6.0%5,099435.461095%5.461095%5.5%4,715445.266517%5.266517%5.3%4,126454.836248%4.836248%4.8%7,351464.020265%4.020265%4.0%4,166473.522812%3.522812%3.5%2,870483.377424%3.377424%3.4%4,282493.157717%3.157717%3.2%2,05750
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older without a high school diploma (or equivalent).

Bachelor's Degrees by County Subdivision#39

Percent of population 25 years of age and older with a bachelor's degree or higher..
Scope: population of the Reading Township, selected other county subdivisions in the Midwest, and entities that contain the Reading Township
0%20%40%60%Count#Ann ArborOverland ParkMilton TownshipMiltonLisle TownshipLisleMadisonDowners Grove TownshipDowners GrvWashington TownshipWashingtonPalatine TownshipPalatineYork TownshipMinneapolisOlatheWheeling TownshipWheelingSchaumburg TownshipSchaumburgKaw TownshipSt. PaulMaine TownshipMaineFargoLincolnLawrence TownshipLawrenceChicagoCapital TownshipCapitalColumbus Metro AreaColumbus AreaColumbusOmahaCincinnatiSt. LouisGrand RapidsBloomingdale TownshipBloomingdaleCedar RapidsUnited States of AmericaUnited StatesSioux FallsMidwestWichitaEast North CentralSterling HeightsSterling HtsTopekaSpringfield TownshipSpringfieldOhioProviso TownshipProvisoWorth TownshipWorthMilwaukeeRockford TownshipRockfordAkronCenter TownshipCtrNorth TownshipNThornton TownshipThorntonToledoDaytonWarrenReading TownshipReadingWayne TownshipWayneKansas CityClevelandAurora TownshipAuroraBlue Township965900Tract 965900DetroitPerry CountyPerry72.810169%72.810169%72.8%47,43047.4k158.823344%58.823344%58.8%74,57874.6k257.681507%57.681507%57.7%45,19045.2k356.900171%56.900171%56.9%46,35646.4k456.337583%56.337583%56.3%85,63285.6k553.762123%53.762123%53.8%55,71155.7k650.610540%50.610540%50.6%47,62347.6k749.860853%49.860853%49.9%39,77539.8k849.728972%49.728972%49.7%42,93542.9k947.670489%47.670489%47.7%127,663128k1046.512581%46.512581%46.5%38,59838.6k1146.409378%46.409378%46.4%51,46851.5k1241.792515%41.792515%41.8%39,02039.0k1341.581304%41.581304%41.6%50,61950.6k1439.969357%39.969357%40.0%74,08874.1k1539.511462%39.511462%39.5%38,91838.9k1638.241175%38.241175%38.2%26,96527.0k1737.146608%37.146608%37.1%62,25462.3k1836.577273%36.577273%36.6%29,32429.3k1936.546320%36.546320%36.5%669,666670k2036.298510%36.298510%36.3%28,78028.8k2134.785494%34.785494%34.8%460,194460k34.685843%34.685843%34.7%185,460185k2234.651487%34.651487%34.7%99,56199.6k2333.783048%33.783048%33.8%64,52964.5k2433.007421%33.007421%33.0%72,14372.1k2532.904381%32.904381%32.9%39,86339.9k2632.623147%32.623147%32.6%25,12725.1k2731.793440%31.793440%31.8%27,10227.1k2830.315023%30.315023%30.3%64,767,78764.8M30.259813%30.259813%30.3%28,45328.5k2928.952816%28.952816%29.0%13,118,64213.1M28.877567%28.877567%28.9%71,75771.8k3028.462853%28.462853%28.5%8,931,6868.93M27.532180%27.532180%27.5%25,60325.6k3127.007248%27.007248%27.0%22,95423.0k3226.964567%26.964567%27.0%27,92127.9k3326.667466%26.667466%26.7%2,092,8752.09M26.237989%26.237989%26.2%27,03327.0k3425.217641%25.217641%25.2%26,38926.4k3523.517740%23.517740%23.5%85,81285.8k3621.592552%21.592552%21.6%25,23525.2k3720.213821%20.213821%20.2%26,69726.7k3820.139240%20.139240%20.1%19,93119.9k3919.650916%19.650916%19.7%20,02920.0k4018.971090%18.971090%19.0%21,01221.0k4118.048021%18.048021%18.0%33,17133.2k4217.635555%17.635555%17.6%15,51115.5k4317.280259%17.280259%17.3%15,89315.9k4417.198468%17.198468%17.2%53916.826535%16.826535%16.8%14,78814.8k4516.167409%16.167409%16.2%15,13915.1k4616.073076%16.073076%16.1%40,94640.9k4715.929601%15.929601%15.9%14,19214.2k4815.821208%15.821208%15.8%16,95117.0k4915.234043%15.234043%15.2%71613.833543%13.833543%13.8%59,72359.7k5011.960614%11.960614%12.0%2,891
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older with a bachelor's degree or higher..

Very Advanced Degrees by County Subdivision#40

Percent of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).
Scope: population of the Reading Township, selected other county subdivisions in the Midwest, and entities that contain the Reading Township
0%5%10%15%Count#Ann ArborMadisonDowners Grove TownshipDowners GrvWashington TownshipWashingtonMinneapolisYork TownshipOverland ParkLisle TownshipLisleSt. PaulKaw TownshipMilton TownshipMiltonSt. LouisCincinnatiLincolnChicagoFargoCapital TownshipCapitalOmahaMaine TownshipMaineColumbus Metro AreaColumbus AreaPalatine TownshipPalatineWheeling TownshipWheelingColumbusUnited States of AmericaUnited StatesTopekaGrand RapidsLawrence TownshipLawrenceSpringfield TownshipSpringfieldCedar RapidsMidwestEast North CentralSioux FallsOlatheOhioCenter TownshipCtrSchaumburg TownshipSchaumburgWichitaProviso TownshipProvisoAkronBloomingdale TownshipBloomingdaleRockford TownshipRockfordMilwaukeeWorth TownshipWorthClevelandToledoNorth TownshipNSterling HeightsSterling HtsKansas CityDetroitDaytonWayne TownshipWayneWarrenBlue TownshipAurora TownshipAuroraThornton TownshipThorntonPerry CountyPerry965900Tract 965900Reading TownshipReading17.877867%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%3,970193.620928%3.620928%3.6%47,90347.9k3.487439%3.487439%3.5%2,782203.407574%3.407574%3.4%3,779213.357865%3.357865%3.4%17,95418.0k223.336158%3.336158%3.3%7,127,6737.13M3.233245%3.233245%3.2%2,748233.174629%3.174629%3.2%3,846243.083448%3.083448%3.1%2,472252.911721%2.911721%2.9%3,015262.905776%2.905776%2.9%2,477272.893416%2.893416%2.9%1,311,0191.31M2.855432%2.855432%2.9%896,039896k2.841677%2.841677%2.8%2,672282.830666%2.830666%2.8%2,349292.683241%2.683241%2.7%210,582211k2.602914%2.602914%2.6%2,576302.551250%2.551250%2.6%2,382312.519246%2.519246%2.5%6,260322.213918%2.213918%2.2%2,281332.163955%2.163955%2.2%2,858342.113682%2.113682%2.1%1,628352.067272%2.067272%2.1%2,416362.043126%2.043126%2.0%7,455371.958049%1.958049%2.0%2,049381.927780%1.927780%1.9%4,911391.642065%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%971500.666087%0.666087%0.7%1610.553191%0.553191%0.6%260.414805%0.414805%0.4%13
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).

Under-Education Sex Ratio by County Subdivision#41

Percentage more likely men are than women to not have a high school diploma (or equivalent) among people aged 25 years and older.
Scope: population of the Reading Township, selected other county subdivisions in the Midwest, and entities that contain the Reading Township
Female
Male
1x0x1xFM#PerryCedar RapidsLincolnDetroitOmahaToledoThorntonKansas CityMadisonLawrenceFargoProvisoRockfordBlue TownshipWayneMidwestTopekaEast North CentralMilwaukeeKaw TownshipDaytonSioux FallsUnited StatesOlatheOhioColumbus AreaWorthNOverland ParkAuroraWheelingGrand RapidsSchaumburgChicagoWichitaColumbusClevelandTract 965900PalatineCapitalWarrenSpringfieldYork TownshipSt. LouisWashingtonBloomingdaleCtrCincinnatiAkronAnn ArborSt. PaulLisleMinneapolisSterling HtsDowners GrvMiltonMaineReading-1.000000x-1.000000x1.397781x1.397781x1.40x13.445%13.4%18.793%18.8%-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-1.000000x1.132245x1.132245x1.13x19.779%19.8%22.395%22.4%14-1.000000x-1.000000x1.127915x1.127915x1.13x9.647%9.65%10.881%10.9%-1.000000x-1.000000x1.125507x1.125507x1.13x10.423%10.4%11.732%11.7%15-1.000000x-1.000000x1.125371x1.125371x1.13x10.108%10.1%11.375%11.4%-1.000000x-1.000000x1.123984x1.123984x1.12x16.526%16.5%18.574%18.6%16-1.000000x-1.000000x1.115695x1.115695x1.12x11.779%11.8%13.142%13.1%17-1.000000x-1.000000x1.114342x1.114342x1.11x16.070%16.1%17.907%17.9%18-1.000000x-1.000000x1.110589x1.110589x1.11x9.201%9.20%10.219%10.2%19-1.000000x-1.000000x1.109070x1.109070x1.11x12.369%12.4%13.719%13.7%-1.000000x-1.000000x1.107847x1.107847x1.11x6.105%6.11%6.764%6.76%20-1.000000x-1.000000x1.105363x1.105363x1.11x10.008%10.0%11.063%11.1%-1.000000x-1.000000x1.104385x1.104385x1.10x8.867%8.87%9.793%9.79%-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-1.000000x1.039865x1.039865x1.04x10.245%10.2%10.653%10.7%-1.000000x-1.000000x1.039581x1.039581x1.04x8.233%8.23%8.559%8.56%32-1.000000x-1.000000x1.039194x1.039194x1.04x8.470%8.47%8.802%8.80%33-1.000000x-1.000000x1.037373x1.037373x1.04x15.022%15.0%15.584%15.6%34-1.000000x-1.000000x1.028857x1.028857x1.03x10.622%10.6%10.928%10.9%35-1.000000x-1.000000x1.027464x1.027464x1.03x5.391%5.39%5.539%5.54%36-1.000000x-1.000000x1.018183x1.018183x1.02x15.334%15.3%15.613%15.6%37-1.000000x-1.000000x1.013146x1.013146x1.01x6.764%6.76%6.853%6.85%38-1.000000x-1.000000x1.007207x1.007207x1.01x12.130%12.1%12.217%12.2%39-1.000000x-1.000000x1.006204x1.006204x1.01x23.095%23.1%23.239%23.2%40-1.000000x-1.000000x1.001229x1.001229x1.00x13.754%13.8%13.771%13.8%41-1.001506x-1.001506x1.00x1.000000x1.000000x13.601%13.6%13.581%13.6%42-1.031649x-1.031649x1.03x1.000000x1.000000x3.205%3.21%3.107%3.11%43-1.060004x-1.060004x1.06x1.000000x1.000000x13.651%13.7%12.879%12.9%44-1.073696x-1.073696x1.07x1.000000x1.000000x3.642%3.64%3.392%3.39%45-1.092939x-1.092939x1.09x1.000000x1.000000x11.450%11.4%10.476%10.5%46-1.131063x-1.131063x1.13x1.000000x1.000000x13.912%13.9%12.300%12.3%47-1.140051x-1.140051x1.14x1.000000x1.000000x4.269%4.27%3.744%3.74%48-1.194783x-1.194783x1.19x1.000000x1.000000x5.710%5.71%4.779%4.78%49-1.208375x-1.208375x1.21x1.000000x1.000000x12.117%12.1%10.027%10.0%50-1.441978x-1.441978x1.44x1.000000x1.000000x8.619%8.62%5.977%5.98%
F percentage of females in category
M percentage of males in category
# rank of county subdivision out of 50 by male-to-female sex ratio

Over-Education Sex Ratio by County Subdivision#42

Percentage more likely men are than women to have a professional or doctorate degree (e.g., MBA, PhD, or MD) among people aged 25 years and older.
Scope: population of the Reading Township, selected other county subdivisions in the Midwest, and entities that contain the Reading Township
Female
Male
0x5x10xFM#Tract 965900ReadingPerryRockfordNDaytonSioux FallsCapitalLawrenceDowners GrvAkronLisleWichitaYork TownshipMaineWarrenWheelingBlue TownshipSpringfieldOverland ParkMiltonGrand RapidsOlatheOhioOmahaFargoWashingtonEast North CentralLincolnMidwestBloomingdaleKansas CityColumbus AreaAuroraUnited StatesAnn ArborTopekaSterling HtsPalatineSchaumburgColumbusMadisonKaw TownshipMilwaukeeCedar RapidsClevelandCincinnatiSt. PaulSt. LouisChicagoWayneCtrToledoMinneapolisWorthDetroitProvisoThornton-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%1.117%1.12%-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%0.835%0.84%-1.000000x-1.000000x6.135051x6.135051x6.14x0.188%0.19%1.155%1.15%-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-1.000000x1.669500x1.669500x1.67x2.031%2.03%3.391%3.39%-1.000000x-1.000000x1.669388x1.669388x1.67x3.061%3.06%5.110%5.11%21-1.000000x-1.000000x1.627456x1.627456x1.63x3.304%3.30%5.377%5.38%22-1.000000x-1.000000x1.610803x1.610803x1.61x5.701%5.70%9.183%9.18%23-1.000000x-1.000000x1.597848x1.597848x1.60x2.216%2.22%3.541%3.54%-1.000000x-1.000000x1.596978x1.596978x1.60x3.524%3.52%5.628%5.63%24-1.000000x-1.000000x1.589934x1.589934x1.59x2.251%2.25%3.579%3.58%-1.000000x-1.000000x1.586045x1.586045x1.59x1.649%1.65%2.616%2.62%25-1.000000x-1.000000x1.570028x1.570028x1.57x1.087%1.09%1.707%1.71%26-1.000000x-1.000000x1.567060x1.567060x1.57x2.842%2.84%4.454%4.45%-1.000000x-1.000000x1.550495x1.550495x1.55x0.737%0.74%1.143%1.14%27-1.000000x-1.000000x1.526215x1.526215x1.53x2.660%2.66%4.060%4.06%-1.000000x-1.000000x1.522839x1.522839x1.52x14.269%14.3%21.730%21.7%28-1.000000x-1.000000x1.481288x1.481288x1.48x2.641%2.64%3.912%3.91%29-1.000000x-1.000000x1.476996x1.476996x1.48x1.170%1.17%1.728%1.73%30-1.000000x-1.000000x1.457167x1.457167x1.46x2.851%2.85%4.154%4.15%31-1.000000x-1.000000x1.436165x1.436165x1.44x2.115%2.11%3.037%3.04%32-1.000000x-1.000000x1.413654x1.413654x1.41x2.801%2.80%3.959%3.96%33-1.000000x-1.000000x1.387878x1.387878x1.39x7.705%7.70%10.693%10.7%34-1.000000x-1.000000x1.373250x1.373250x1.37x4.975%4.97%6.832%6.83%35-1.000000x-1.000000x1.368590x1.368590x1.37x1.742%1.74%2.385%2.38%36-1.000000x-1.000000x1.346658x1.346658x1.35x2.491%2.49%3.354%3.35%37-1.000000x-1.000000x1.286599x1.286599x1.29x1.699%1.70%2.186%2.19%38-1.000000x-1.000000x1.280610x1.280610x1.28x4.179%4.18%5.351%5.35%39-1.000000x-1.000000x1.274509x1.274509x1.27x5.228%5.23%6.663%6.66%40-1.000000x-1.000000x1.273345x1.273345x1.27x4.319%4.32%5.500%5.50%41-1.000000x-1.000000x1.238186x1.238186x1.24x4.026%4.03%4.985%4.99%42-1.000000x-1.000000x1.223931x1.223931x1.22x1.068%1.07%1.307%1.31%43-1.000000x-1.000000x1.213574x1.213574x1.21x2.357%2.36%2.860%2.86%44-1.000000x-1.000000x1.141406x1.141406x1.14x1.539%1.54%1.757%1.76%45-1.000000x-1.000000x1.124528x1.124528x1.12x5.872%5.87%6.603%6.60%46-1.000000x-1.000000x1.084697x1.084697x1.08x1.883%1.88%2.042%2.04%47-1.000000x-1.000000x1.046557x1.046557x1.05x1.291%1.29%1.351%1.35%48-1.000000x-1.000000x1.042857x1.042857x1.04x2.171%2.17%2.264%2.26%49-1.706858x-1.706858x1.71x1.000000x1.000000x1.072%1.07%0.628%0.63%50
F percentage of females in category
M percentage of males in category
# rank of county subdivision out of 50 by male-to-female sex ratio

Educational Attainment by County Subdivision in the United States

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

No H.S. Diploma by County Subdivision#43

Percent of population 25 years of age and older without a high school diploma (or equivalent).
Scope: population of the Reading Township, selected other county subdivisions in the United States, and entities that contain the Reading 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 VlyMilwaukeePhiladelphiaOntarioChicagoBaltimorePerry CountyPerryOceanside-EscondidoOceanside-Escond…Las VegasPhoenixBostonSacramentoOrlandoAustinDenverUnited States of AmericaUnited StatesManhattanSan DiegoTampaSan JoseSan FranciscoTucsonAlbuquerqueTownship 1:Charlotte1, CharlotteColumbusTulsaEast North CentralOhio965900Tract 965900Salt Lake CitySalt Lk CityTown of HempsteadHempsteadMidwestNorthwest HarrisNW HarrisWashingtonAtlantaColumbus Metro AreaColumbus AreaSeattleNortheast TarrantNE TarrantReading TownshipReadingPlanoSeattle 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%69,83969.8k2316.089529%16.089529%16.1%3,88915.999398%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%43,65343.7k4110.719464%10.719464%10.7%3,363,7843.36M10.514146%10.514146%10.5%825,155825k10.446809%10.446809%10.4%49110.435356%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%37,37337.4k469.314501%9.314501%9.3%123,226123k8.833573%8.833573%8.8%66,22066.2k478.418271%8.418271%8.4%31,44331.4k487.306956%7.306956%7.3%2295.714681%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#44

Percent of population 25 years of age and older with a bachelor's degree or higher..
Scope: population of the Reading Township, selected other county subdivisions in the United States, and entities that contain the Reading Township
0%20%40%60%Count#ManhattanSeattle EastWashingtonSan FranciscoPlanoSan JoseAtlantaSeattleBostonDenverAustinTownship 1:Charlotte1, CharlotteTown of HempsteadHempsteadSan DiegoNortheast TarrantNE TarrantNorthwest HarrisNW HarrisChicagoColumbus Metro AreaColumbus AreaColumbusLos AngelesBrooklynSan Fernando ValleySan Fernando VlyNortheast DallasNE DallasSalt Lake CitySalt Lk CityAlbuquerqueTampaTucsonOceanside-EscondidoOceanside-Escond…TulsaQueensUnited States of AmericaUnited StatesHoustonBaltimoreLong Beach-LakewoodLong Bch-LakewoodMidwestPhoenixOrlandoEast North CentralAnaheim-Santa Ana-Garden GroveAnaheim-Santa An…SacramentoEast San Gabriel ValleyE San Gabriel VlyOntarioOhioPhiladelphiaMiamiFort WorthSouthwest DallasSW DallasMilwaukeeFresnoLas VegasEl PasoBronxReading TownshipReadingSan Bernardino965900Tract 965900San Antonio CentralSan Antonio CntrlDetroitPerry CountyPerry60.434640%60.434640%60.4%747,953748k157.691220%57.691220%57.7%238,638239k255.360186%55.360186%55.4%256,316256k354.793235%54.793235%54.8%366,564367k454.142756%54.142756%54.1%195,588196k549.985845%49.985845%50.0%600,334600k649.803731%49.803731%49.8%195,136195k749.626221%49.626221%49.6%372,018372k846.377869%46.377869%46.4%206,036206k945.718966%45.718966%45.7%214,085214k1044.843364%44.843364%44.8%256,674257k1141.989192%41.989192%42.0%223,068223k1238.767308%38.767308%38.8%202,458202k1338.701072%38.701072%38.7%616,296616k1438.547398%38.547398%38.5%143,978144k1536.877886%36.877886%36.9%173,478173k1636.546320%36.546320%36.5%669,666670k1734.785494%34.785494%34.8%460,194460k34.685843%34.685843%34.7%185,460185k1834.593243%34.593243%34.6%604,693605k1934.081468%34.081468%34.1%597,685598k2033.231104%33.231104%33.2%420,848421k2133.191099%33.191099%33.2%331,364331k2233.118385%33.118385%33.1%204,048204k2332.636312%32.636312%32.6%140,967141k2432.512191%32.512191%32.5%144,676145k2532.087814%32.087814%32.1%184,237184k2631.198303%31.198303%31.2%136,915137k2731.110082%31.110082%31.1%120,191120k2830.595789%30.595789%30.6%499,006499k2930.315023%30.315023%30.3%64,767,78764.8M30.080133%30.080133%30.1%627,520628k3029.719611%29.719611%29.7%125,423125k3129.113198%29.113198%29.1%109,693110k3228.952816%28.952816%29.0%13,118,64213.1M28.760152%28.760152%28.8%593,529594k3328.535877%28.535877%28.5%112,142112k3428.462853%28.462853%28.5%8,931,6868.93M28.412939%28.412939%28.4%312,038312k3528.231204%28.231204%28.2%209,283209k3627.276345%27.276345%27.3%170,682171k3726.758411%26.758411%26.8%111,532112k3826.667466%26.667466%26.7%2,092,8752.09M26.349720%26.349720%26.3%272,786273k3926.011156%26.011156%26.0%178,455178k4024.665414%24.665414%24.7%131,349131k4123.764821%23.764821%23.8%140,625141k4223.517740%23.517740%23.5%85,81285.8k4322.486319%22.486319%22.5%94,05694.1k4421.702666%21.702666%21.7%271,037271k4521.071885%21.071885%21.1%72,12072.1k4619.131504%19.131504%19.1%173,169173k4717.198468%17.198468%17.2%53916.375473%16.375473%16.4%80,59580.6k4815.234043%15.234043%15.2%71614.929012%14.929012%14.9%65,34165.3k4913.833543%13.833543%13.8%59,72359.7k5011.960614%11.960614%12.0%2,891
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#45

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 Reading Township, selected other county subdivisions in the United States, and entities that contain the Reading Township
0%5%10%Count#WashingtonManhattanSan FranciscoBostonAtlantaSeattleSan JoseSeattle EastDenverSan DiegoAustinBaltimoreLos AngelesAlbuquerquePlanoChicagoTucsonTown of HempsteadHempsteadTampaMiamiNortheast DallasNE DallasSalt Lake CitySalt Lk CityHoustonPhiladelphiaColumbus Metro AreaColumbus AreaSan Fernando ValleySan Fernando VlyTownship 1:Charlotte1, CharlotteOceanside-EscondidoOceanside-Escond…BrooklynSacramentoColumbusUnited States of AmericaUnited StatesTulsaPhoenixLong Beach-LakewoodLong Bch-LakewoodMidwestOrlandoEast North CentralFresnoAnaheim-Santa Ana-Garden GroveAnaheim-Santa An…QueensOhioNorthwest HarrisNW HarrisNortheast TarrantNE TarrantEast San Gabriel ValleyE San Gabriel VlyOntarioFort WorthLas VegasMilwaukeeSan BernardinoSan Antonio CentralSan Antonio CntrlEl PasoSouthwest DallasSW DallasBronxDetroitPerry CountyPerry965900Tract 965900Reading TownshipReading12.461852%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%38,51538.5k243.620928%3.620928%3.6%47,90347.9k3.601468%3.601468%3.6%45,61045.6k253.490252%3.490252%3.5%18,54218.5k263.466073%3.466073%3.5%15,21115.2k273.384967%3.384967%3.4%59,36259.4k283.380196%3.380196%3.4%25,05825.1k293.357865%3.357865%3.4%17,95418.0k303.336158%3.336158%3.3%7,127,6737.13M3.140490%3.140490%3.1%12,13312.1k313.010825%3.010825%3.0%62,13562.1k323.009440%3.009440%3.0%11,33911.3k332.893416%2.893416%2.9%1,311,0191.31M2.893233%2.893233%2.9%11,37011.4k342.855432%2.855432%2.9%896,039896k2.828959%2.828959%2.8%11,83311.8k352.763004%2.763004%2.8%30,34430.3k362.756960%2.756960%2.8%44,96545.0k372.683241%2.683241%2.7%210,582211k2.682967%2.682967%2.7%12,62112.6k382.630994%2.630994%2.6%9,827392.484535%2.484535%2.5%15,54715.5k402.324315%2.324315%2.3%9,688412.173239%2.173239%2.2%11,57311.6k422.155077%2.155077%2.2%26,91426.9k432.043126%2.043126%2.0%7,455441.807306%1.807306%1.8%8,895451.792414%1.792414%1.8%7,845461.745764%1.745764%1.7%5,975471.704476%1.704476%1.7%10,08610.1k481.664253%1.664253%1.7%15,06415.1k491.318660%1.318660%1.3%5,693500.666087%0.666087%0.7%1610.553191%0.553191%0.6%260.414805%0.414805%0.4%13
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#46

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 Reading Township, selected other county subdivisions in the United States, and entities that contain the Reading Township
Female
Male
1x0x1xFM#Perry1, CharlotteDetroitBaltimoreTulsaSW DallasMidwestFresnoEast North CentralMilwaukeeUnited StatesOhioColumbus AreaNE DallasHoustonHempsteadOrlandoPhiladelphiaOntarioSan BernardinoAustinAtlantaFort WorthPhoenixChicagoAlbuquerqueWashingtonSacramentoColumbusSalt Lk CityDenverNE TarrantTampaOceanside-EscondidoOceanside-Escond…Tract 965900NW HarrisBronxPlanoBrooklynSan Antonio CntrlSan Fernando VlyTucsonAnaheim-Santa Ana-Gdn GrvAnaheim-Santa An…Los AngelesLas VegasBostonE San Gabriel VlyQueensMiamiManhattanSeattleLong Bch-LakewoodSeattle EastSan JoseSan DiegoSan FranciscoEl PasoReading-1.000000x-1.000000x1.397781x1.397781x1.40x13.445%13.4%18.793%18.8%-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-1.000000x1.127915x1.127915x1.13x9.647%9.65%10.881%10.9%-1.000000x-1.000000x1.127206x1.127206x1.13x20.830%20.8%23.479%23.5%6-1.000000x-1.000000x1.125371x1.125371x1.13x10.108%10.1%11.375%11.4%-1.000000x-1.000000x1.123984x1.123984x1.12x16.526%16.5%18.574%18.6%7-1.000000x-1.000000x1.109070x1.109070x1.11x12.369%12.4%13.719%13.7%-1.000000x-1.000000x1.105363x1.105363x1.11x10.008%10.0%11.063%11.1%-1.000000x-1.000000x1.104385x1.104385x1.10x8.867%8.87%9.793%9.79%-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-1.000000x1.039865x1.039865x1.04x10.245%10.2%10.653%10.7%-1.000000x-1.000000x1.038394x1.038394x1.04x9.953%9.95%10.335%10.3%29-1.000000x-1.000000x1.030539x1.030539x1.03x28.448%28.4%29.316%29.3%30-1.000000x-1.000000x1.023151x1.023151x1.02x5.652%5.65%5.783%5.78%31-1.000000x-1.000000x1.018960x1.018960x1.02x19.845%19.8%20.221%20.2%32-1.000000x-1.000000x1.003929x1.003929x1.00x28.944%28.9%29.058%29.1%33-1.000000x-1.000000x1.003840x1.003840x1.00x19.308%19.3%19.383%19.4%34-1.006471x-1.006471x1.01x1.000000x1.000000x12.301%12.3%12.222%12.2%35-1.008020x-1.008020x1.01x1.000000x1.000000x22.734%22.7%22.553%22.6%36-1.013004x-1.013004x1.01x1.000000x1.000000x24.995%25.0%24.674%24.7%37-1.016645x-1.016645x1.02x1.000000x1.000000x16.036%16.0%15.774%15.8%38-1.022333x-1.022333x1.02x1.000000x1.000000x14.476%14.5%14.159%14.2%39-1.026902x-1.026902x1.03x1.000000x1.000000x20.723%20.7%20.180%20.2%40-1.027762x-1.027762x1.03x1.000000x1.000000x19.596%19.6%19.067%19.1%41-1.030897x-1.030897x1.03x1.000000x1.000000x22.136%22.1%21.473%21.5%42-1.044246x-1.044246x1.04x1.000000x1.000000x13.260%13.3%12.698%12.7%43-1.049689x-1.049689x1.05x1.000000x1.000000x9.047%9.05%8.619%8.62%44-1.056864x-1.056864x1.06x1.000000x1.000000x19.921%19.9%18.849%18.8%45-1.057675x-1.057675x1.06x1.000000x1.000000x5.050%5.05%4.774%4.77%46-1.127548x-1.127548x1.13x1.000000x1.000000x13.555%13.6%12.021%12.0%47-1.168454x-1.168454x1.17x1.000000x1.000000x13.975%14.0%11.960%12.0%48-1.228758x-1.228758x1.23x1.000000x1.000000x13.883%13.9%11.298%11.3%49-1.276282x-1.276282x1.28x1.000000x1.000000x26.394%26.4%20.680%20.7%50-1.441978x-1.441978x1.44x1.000000x1.000000x8.619%8.62%5.977%5.98%
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#47

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 Reading Township, selected other county subdivisions in the United States, and entities that contain the Reading Township
Female
Male
0x5x10xFM#Tract 965900ReadingPerryEl PasoSalt Lk CityPlanoTulsaAlbuquerqueNE DallasFort WorthOhioOrlandoPhoenixTucson1, CharlotteEast North CentralMidwestNW HarrisLas VegasColumbus AreaSeattle EastSan Antonio CntrlSan DiegoUnited StatesSan JoseHempsteadFresnoNE TarrantTampaSan Fernando VlyE San Gabriel VlyHoustonSan BernardinoColumbusMiamiAtlantaMilwaukeeAnaheim-Santa Ana-Gdn GrvAnaheim-Santa An…SacramentoPhiladelphiaOceanside-EscondidoOceanside-Escond…Los AngelesAustinBaltimoreWashingtonQueensSW DallasBrooklynManhattanChicagoSeattleBostonBronxOntarioLong Bch-LakewoodDenverSan FranciscoDetroit-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%1.117%1.12%-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%0.835%0.84%-1.000000x-1.000000x6.135051x6.135051x6.14x0.188%0.19%1.155%1.15%-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-1.000000x1.669500x1.669500x1.67x2.031%2.03%3.391%3.39%-1.000000x-1.000000x1.660799x1.660799x1.66x2.196%2.20%3.647%3.65%8-1.000000x-1.000000x1.659024x1.659024x1.66x2.280%2.28%3.783%3.78%9-1.000000x-1.000000x1.621815x1.621815x1.62x3.429%3.43%5.561%5.56%10-1.000000x-1.000000x1.611479x1.611479x1.61x2.711%2.71%4.369%4.37%11-1.000000x-1.000000x1.597848x1.597848x1.60x2.216%2.22%3.541%3.54%-1.000000x-1.000000x1.589934x1.589934x1.59x2.251%2.25%3.579%3.58%-1.000000x-1.000000x1.579303x1.579303x1.58x2.100%2.10%3.317%3.32%12-1.000000x-1.000000x1.576623x1.576623x1.58x1.677%1.68%2.643%2.64%13-1.000000x-1.000000x1.567060x1.567060x1.57x2.842%2.84%4.454%4.45%-1.000000x-1.000000x1.557664x1.557664x1.56x4.733%4.73%7.372%7.37%14-1.000000x-1.000000x1.540473x1.540473x1.54x1.423%1.42%2.192%2.19%15-1.000000x-1.000000x1.529565x1.529565x1.53x4.164%4.16%6.370%6.37%16-1.000000x-1.000000x1.526215x1.526215x1.53x2.660%2.66%4.060%4.06%-1.000000x-1.000000x1.514156x1.514156x1.51x4.979%4.98%7.539%7.54%17-1.000000x-1.000000x1.488724x1.488724x1.49x3.608%3.61%5.371%5.37%18-1.000000x-1.000000x1.484269x1.484269x1.48x2.293%2.29%3.404%3.40%19-1.000000x-1.000000x1.481801x1.481801x1.48x2.138%2.14%3.168%3.17%20-1.000000x-1.000000x1.476874x1.476874x1.48x3.518%3.52%5.196%5.20%21-1.000000x-1.000000x1.460302x1.460302x1.46x2.944%2.94%4.299%4.30%22-1.000000x-1.000000x1.451775x1.451775x1.45x2.041%2.04%2.963%2.96%23-1.000000x-1.000000x1.424636x1.424636x1.42x3.092%3.09%4.404%4.40%24-1.000000x-1.000000x1.423621x1.423621x1.42x1.501%1.50%2.137%2.14%25-1.000000x-1.000000x1.413654x1.413654x1.41x2.801%2.80%3.959%3.96%26-1.000000x-1.000000x1.395174x1.395174x1.40x3.384%3.38%4.722%4.72%27-1.000000x-1.000000x1.391590x1.391590x1.39x5.799%5.80%8.070%8.07%28-1.000000x-1.000000x1.368590x1.368590x1.37x1.742%1.74%2.385%2.38%29-1.000000x-1.000000x1.362600x1.362600x1.36x2.347%2.35%3.199%3.20%30-1.000000x-1.000000x1.359928x1.359928x1.36x2.888%2.89%3.927%3.93%31-1.000000x-1.000000x1.341930x1.341930x1.34x3.216%3.22%4.316%4.32%32-1.000000x-1.000000x1.310218x1.310218x1.31x3.011%3.01%3.945%3.95%33-1.000000x-1.000000x1.308108x1.308108x1.31x4.045%4.05%5.292%5.29%34-1.000000x-1.000000x1.303834x1.303834x1.30x4.384%4.38%5.716%5.72%35-1.000000x-1.000000x1.303196x1.303196x1.30x4.332%4.33%5.645%5.65%36-1.000000x-1.000000x1.300117x1.300117x1.30x10.922%10.9%14.199%14.2%37-1.000000x-1.000000x1.285200x1.285200x1.29x2.428%2.43%3.121%3.12%38-1.000000x-1.000000x1.265486x1.265486x1.27x1.515%1.51%1.917%1.92%39-1.000000x-1.000000x1.262281x1.262281x1.26x3.021%3.02%3.814%3.81%40-1.000000x-1.000000x1.245683x1.245683x1.25x9.673%9.67%12.050%12.1%41-1.000000x-1.000000x1.238186x1.238186x1.24x4.026%4.03%4.985%4.99%42-1.000000x-1.000000x1.228890x1.228890x1.23x5.961%5.96%7.326%7.33%43-1.000000x-1.000000x1.221037x1.221037x1.22x6.643%6.64%8.112%8.11%44-1.000000x-1.000000x1.202385x1.202385x1.20x1.526%1.53%1.834%1.83%45-1.000000x-1.000000x1.198236x1.198236x1.20x2.119%2.12%2.539%2.54%46-1.000000x-1.000000x1.181998x1.181998x1.18x2.766%2.77%3.269%3.27%47-1.000000x-1.000000x1.129665x1.129665x1.13x5.378%5.38%6.075%6.08%48-1.000000x-1.000000x1.098720x1.098720x1.10x7.194%7.19%7.905%7.90%49-1.000000x-1.000000x1.046557x1.046557x1.05x1.291%1.29%1.351%1.35%50
F percentage of females in category
M percentage of males in category
# rank of county subdivision out of 50 by male-to-female sex ratio

Definitions

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

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

The coarse levels of educational attainment are as follows:

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

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

More Topics to Explore

Demographics

Income

Education

More Maps to Explore

State:
Ohio
County:
Perry
Metro Area:
Columbus Area
Village:
Somerset
ZIP Codes:
43076, 43150, 43748, 43764, 43783
Unified School Districts:
Fairfield Union, New Lexington, Northern
Congressional District:
OH-15
State Senate District:
OH-31
State House District:
OH-72
Neighboring Townships:
Clayton, Hopewell, Jackson, Madison, Pike, Richland, Rush Creek, Thorn
Nearby Townships:
Bowling Green, Franklin, Harrison, Marion, Monday Creek, Newton, Pleasant, Pleasant, Salt Lick, Walnut