Educational Attainment in the Brown Township, Miami County, Ohio (Township)

Educational Attainment#1

Highest level of education among people aged 25 years and older.
Scope: population of Miami County and the Brown Township
Brown Township
Miami County
0%20%40%60%CountHigher Degree1H.S. Diploma2No H.S. Diploma219.932811%30.692682%19.932811%19.9%17870.324748%58.394395%70.324748%70.3%6289.742441%10.912923%9.742441%9.7%87
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 Miami County at large.
Scope: population of Miami County and the Brown Township
-20%0%+20%%ref.Higher Degree1H.S. Diploma2No H.S. Diploma2-35.056798%-35.056798%-35.1%19.933%19.9%30.693%30.7%20.430648%20.430648%+20.4%70.325%70.3%58.394%58.4%-10.725646%-10.725646%-10.7%9.742%9.74%10.913%10.9%
% percentage with given level in the Brown Township
ref. percentage with given level in Miami 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 Miami County and the Brown Township
Brown Township
Miami County
0%10%20%30%40%CountDoctorate1Professional1Master's1Bachelor's1Associate's1Some CollegeHigh School2Some H.S.3Less than H.S.3None0.000000%0.000000%0.0%0.351715%00.783875%0.827646%0.783875%0.8%73.135498%6.291784%3.135498%3.1%286.270997%13.592653%6.270997%6.3%569.742441%9.628885%9.742441%9.7%8723.740202%22.356209%23.740202%23.7%21246.584546%36.038186%46.584546%46.6%4167.390817%8.639339%7.390817%7.4%662.239642%1.459895%2.239642%2.2%200.111982%0.813689%0.111982%0.1%1
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 Miami County at large.
Scope: population of Miami County and the Brown 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%0.352%0.35%-5.288651%-5.288651%-5.3%0.784%0.78%0.828%0.83%-50.165191%-50.165191%-50.2%3.135%3.14%6.292%6.29%-53.864808%-53.864808%-53.9%6.271%6.27%13.593%13.6%1.179326%1.179326%+1.2%9.742%9.74%9.629%9.63%6.190642%6.190642%+6.2%23.740%23.7%22.356%22.4%29.264404%29.264404%+29.3%46.585%46.6%36.038%36.0%-14.451586%-14.451586%-14.5%7.391%7.39%8.639%8.64%53.411171%53.411171%+53.4%2.240%2.24%1.460%1.46%-86.237729%-86.237729%-86.2%0.112%0.11%0.814%0.81%
% percentage with given level in the Brown Township
ref. percentage with given level in Miami 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 Miami County and the Brown Township
More Females More Males
Miami County
Brown Township
100%0%100%FMHigher Degree1H.S. Diploma2No H.S. Diploma2-165.040128%-6.047062%-165.040128%165%28.989%29.0%10.938%10.9%14.297945%5.518232%14.297945%14%65.618%65.6%75.000%75.0%-13.101499%160.742188%160.742188%161%5.393%5.39%14.063%14.1%
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 Miami County and the Brown Township
More Females More Males
Miami County
Brown Township
500%0%500%1,000%FMProfessional1Master's1Bachelor's1Associate's1Some CollegeHigh School2Some H.S.3Less than H.S.3None1,000.000000%173.328433%1,000.000000%> 1000%0.000%0%1.563%1.56%-112.534332%-16.507743%-112.534332%113%4.270%4.27%2.009%2.01%-738.951311%-738.951311%739%6.426189%11.236%11.2%1.339%1.34%-123.720350%-37.531324%-123.720350%124%13.483%13.5%6.027%6.03%-17.110754%-17.110754%17%1.243365%25.618%25.6%21.875%21.9%32.812500%8.259419%32.812500%33%40.000%40.0%53.125%53.1%-24.753370%73.828125%73.828125%74%5.393%5.39%9.375%9.38%1,000.000000%89.354812%1,000.000000%> 1000%0.000%0%4.464%4.46%-56.258873%1,000.000000%1,000.000000%> 1000%0.000%0%0.223%0.22%
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 Miami County and the Brown Township
Brown Township
Miami County
0%5%10%15%B.X.Total65+45-6435-4425-348.426966%10.718473%8.426966%8.4%151786.868132%11.962642%6.868132%6.9%253644.972376%15.567880%4.972376%5.0%91814.117647%19.830652%4.117647%4.1%7170
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 Miami County at large.
Scope: population of Miami County and the Brown Township
60%40%20%0%%ref.65+45-6435-4425-34-21.379038%-21.379038%21.4%8.427%8.43%10.718%10.7%-42.586833%-42.586833%42.6%6.868%6.87%11.963%12.0%-68.060033%-68.060033%68.1%4.972%4.97%15.568%15.6%-79.235947%-79.235947%79.2%4.118%4.12%19.831%19.8%
% percentage in the Brown Township with a Bachelor's degree
ref percentage in Miami 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 Miami County and the Brown Township
More Females More Males
Miami County
Brown Township
1,000%500%0%FM65+45-6435-4425-34-92.307692%-92.307692%92.3%27.651717%11.538%11.5%6.000%6.00%-1,000.000000%-1,000.000000%> 1000%1.195764%14.124%14.1%0.000%0%-1,000.000000%-4.858874%-1,000.000000%> 1000%8.571%8.57%0.000%0%-1,000.000000%-1,000.000000%> 1000%2.557397%8.235%8.24%0.000%0%
F female degree holders as a percentage of all females
M male degree holders as a percentage of all males

Median Earnings by Educational Attainment#10

Among population 25 years old and over with earnings.
Scope: population of Miami County and the Brown Township
Brown Township
Miami County
$0k$20k$40k$60kCount%Graduate Degree1Bachelor's DegreeSome CollegeH.S. Diploma2No H.S. Diploma2Total$56,417.000000$68,559.000000$56,417.000000$56.4k353.919%3.92%$50,125.000000$51,302.000000$50,125.000000$50.1k566.271%6.27%$37,813.000000$32,129.000000$37,813.000000$37.8k29933.483%33.5%$34,412.000000$30,504.000000$34,412.000000$34.4k41646.585%46.6%$23,125.000000$21,980.000000$23,125.000000$23.1k879.742%9.74%$37,059.000000$35,556.000000$37,059.000000$37.1k893100.000%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 Miami County and the Brown Township
Female Male
Miami County
Brown Township
Shaded bar tips show excess over facing bar.
$20k$0k$20k$40kFMH.S. Diploma2Total$-26,833.000000$-23,077.000000$-26,833.000000$26.8k$26,833.000000$13,405.000000$23,077.000000$13,931.000000$40,238.000000$40.2k178238$-30,550.000000$-27,133.000000$-30,550.000000$30.6k$30,550.000000$9,770.000000$27,133.000000$15,182.000000$40,320.000000$40.3k445448
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 Miami County and the Brown Township
Brown Township
Miami County
0%20%40%60%80%100%CountBachelor's Degree1Some College2H.S. Diploma3No H.S. Diploma3100.000000%85.490658%100.000000%100.0%7576.190476%78.360394%76.190476%76.2%20885.932722%73.917249%85.932722%85.9%28157.500000%53.532182%57.500000%57.5%23
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 Miami County and the Brown Township
Female Male
Miami County
Brown Township
Shaded bar tips show excess over facing bar.
10%5%0%5%10%MFWhite1-5.393258%-10.314835%-0.971366%-5.393258%5.4%5.393258%8.860135%10.314835%14.253394%14.3%6324
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 Miami County and the Brown Township
Female Male
Miami County
Brown Township
Shaded bar tips show excess over facing bar.
20%10%0%10%20%MFWhite1-4.977376%-10.528242%-20.408859%-15.505618%15.5%4.977376%20.408859%1.127341%4.977376%5.0%2269
M number of males in category
F number of females in category
1non-Hispanic 2excluding black and Asian Hispanics

Educational Attainment by County Subdivision in the Dayton Area

There are 52 county subdivisions in the Dayton Area. This section compares the Brown Township to the 50 most populous county subdivisions in the Dayton Area and to those entities that contain or substantially overlap with the Brown Township. The least populous of the compared county subdivisions has a population of 538.

No H.S. Diploma by County Subdivision#15

Percent of population 25 years of age and older without a high school diploma (or equivalent).
Scope: population of the Brown Township, selected other county subdivisions in the Dayton Area, and entities that contain the Brown Township
0%5%10%15%Count#Harrison TownshipHarrisonDaytonJefferson TownshipJeffersonRoss TownshipBethel TownshipBethelPiquaMoraineTrotwoodUnion TownshipUnionRiversideUnited States of AmericaUnited StatesNewton TownshipNewtonBath TownshipXeniaStaunton TownshipStauntonNewberry TownshipNewberryJefferson TownshipJeffersonSilvercreek TownshipSilvercreekMiami CountyMiamiEast North CentralPerry TownshipPerryOhioJackson TownshipJacksonWest CarrolltonW CarrolltonConcord TownshipConcordMidwestDayton Metro AreaDayton AreaBrown TownshipBrownVandaliaMiami East Local School DistrictMiami EastNew Jasper TownshipNew JasperXenia TownshipXeniaMiami TownshipMiamiElizabeth TownshipElizabethGerman TownshipGermanHuber HeightsClay TownshipCaesarscreek TownshipCaesarscreek390100Tract 390100Monroe TownshipMonroeEnglewoodWashington TownshipWashingtonSpringcreek TownshipSpringcreekKetteringButler TownshipButlerSpring Valley TownshipSpg VlyClaytonUnion City TownshipUnion CityMiami TownshipMiamiCedarville TownshipCedarvilleLostcreek TownshipLostcreekWashington TownshipWashingtonBellbrookBeavercreek TownshipBeavercreekHuber HeightsSugarcreek TownshipSugarcreekOakwoodKettering16.956522%16.956522%17.0%2,574116.928359%16.928359%16.9%14,88914.9k216.831479%16.831479%16.8%817315.966387%15.966387%16.0%95414.705090%14.705090%14.7%546514.360238%14.360238%14.4%1,982614.342166%14.342166%14.3%617713.774203%13.774203%13.8%2,312813.145604%13.145604%13.1%957913.107180%13.107180%13.1%2,1561013.020590%13.020590%13.0%27,818,38027.8M12.416667%12.416667%12.4%2981112.411362%12.411362%12.4%3,0631212.138892%12.138892%12.1%2,1431312.080057%12.080057%12.1%1691412.033860%12.033860%12.0%5261511.711712%11.711712%11.7%1041611.407860%11.407860%11.4%2991710.912923%10.912923%10.9%7,81910.719464%10.719464%10.7%3,363,7843.36M10.566948%10.566948%10.6%4381810.514146%10.514146%10.5%825,155825k10.428894%10.428894%10.4%4621910.412768%10.412768%10.4%9462010.356923%10.356923%10.4%2,1852110.244520%10.244520%10.2%4,641,8354.64M9.844056%9.844056%9.8%53,48053.5k9.742441%9.742441%9.7%87229.616815%9.616815%9.6%1,034239.451796%9.451796%9.5%4509.394572%9.394572%9.4%180248.650218%8.650218%8.7%298258.614662%8.614662%8.6%3,080268.289242%8.289242%8.3%94277.443946%7.443946%7.4%415287.261193%7.261193%7.3%1,797297.101582%7.101582%7.1%467307.073171%7.073171%7.1%58317.048040%7.048040%7.0%2236.896868%6.896868%6.9%751326.503982%6.503982%6.5%637336.329114%6.329114%6.3%60346.016598%6.016598%6.0%87355.953744%5.953744%6.0%2,340365.715722%5.715722%5.7%341375.451866%5.451866%5.5%111384.952094%4.952094%5.0%460394.832460%4.832460%4.8%212404.173312%4.173312%4.2%157413.947368%3.947368%3.9%84423.693931%3.693931%3.7%42433.637690%3.637690%3.6%1,496443.147892%3.147892%3.1%159453.105178%3.105178%3.1%1,170463.070175%3.070175%3.1%35472.652763%2.652763%2.7%145481.721876%1.721876%1.7%105490.000000%0.000000%0.0%050
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older without a high school diploma (or equivalent).

Bachelor's Degrees by County Subdivision#16

Percent of population 25 years of age and older with a bachelor's degree or higher..
Scope: population of the Brown Township, selected other county subdivisions in the Dayton Area, and entities that contain the Brown Township
0%20%40%60%Count#OakwoodKetteringSugarcreek TownshipSugarcreekMiami TownshipMiamiWashington TownshipWashingtonBeavercreek TownshipBeavercreekBellbrookCedarville TownshipCedarvilleHuber HeightsClaytonButler TownshipButlerKetteringStaunton TownshipStauntonUnited States of AmericaUnited StatesXenia TownshipXeniaMonroe TownshipMonroeSpring Valley TownshipSpg VlyMidwestEnglewoodEast North CentralWashington TownshipWashingtonDayton Metro AreaDayton AreaBath TownshipMiami TownshipMiamiOhioConcord TownshipConcordElizabeth TownshipElizabethNew Jasper TownshipNew JasperVandaliaGerman TownshipGermanHuber HeightsMiami East Local School DistrictMiami EastMiami CountyMiamiCaesarscreek TownshipCaesarscreekClay TownshipBethel TownshipBethelXenia390100Tract 390100Springcreek TownshipSpringcreekLostcreek TownshipLostcreekRiversideDaytonUnion City TownshipUnion CityUnion TownshipUnionRoss TownshipTrotwoodSilvercreek TownshipSilvercreekJefferson TownshipJeffersonWest CarrolltonW CarrolltonMoraineHarrison TownshipHarrisonJackson TownshipJacksonPerry TownshipPerryJefferson TownshipJeffersonNewton TownshipNewtonPiquaBrown TownshipBrownNewberry TownshipNewberry70.580518%70.580518%70.6%4,304161.676647%61.676647%61.7%206260.336626%60.336626%60.3%3,298356.831473%56.831473%56.8%2,138452.483891%52.483891%52.5%21,58421.6k551.261976%51.261976%51.3%19,31519.3k644.525836%44.525836%44.5%2,249742.763158%42.763158%42.8%910839.736842%39.736842%39.7%453934.298633%34.298633%34.3%3,1861034.059671%34.059671%34.1%2,0321133.391853%33.391853%33.4%13,12413.1k1232.952109%32.952109%33.0%4611330.315023%30.315023%30.3%64,767,78764.8M30.217707%30.217707%30.2%1,0411430.213977%30.213977%30.2%3,2901529.764244%29.764244%29.8%6061628.952816%28.952816%29.0%13,118,64213.1M28.599142%28.599142%28.6%2,8011728.462853%28.462853%28.5%8,931,6868.93M28.270042%28.270042%28.3%2681827.783136%27.783136%27.8%150,938151k26.954091%26.954091%27.0%6,6521926.713842%26.713842%26.7%9,5512026.667466%26.667466%26.7%2,092,8752.09M26.548798%26.548798%26.5%5,6012126.455026%26.455026%26.5%3002224.686848%24.686848%24.7%4732323.818824%23.818824%23.8%2,5612423.426009%23.426009%23.4%1,3062522.834168%22.834168%22.8%5,6512622.369250%22.369250%22.4%1,06521.063797%21.063797%21.1%15,09215.1k20.487805%20.487805%20.5%1682719.784063%19.784063%19.8%1,3012819.714517%19.714517%19.7%7322919.468676%19.468676%19.5%3,4373019.089760%19.089760%19.1%60418.741355%18.741355%18.7%2713118.733509%18.733509%18.7%2133218.043650%18.043650%18.0%2,9683317.635555%17.635555%17.6%15,51115.5k3415.933440%15.933440%15.9%6993515.728022%15.728022%15.7%1,1453615.126050%15.126050%15.1%903715.102770%15.102770%15.1%2,5353814.307516%14.307516%14.3%3753914.153276%14.153276%14.2%6874013.780958%13.780958%13.8%1,2524113.598326%13.598326%13.6%5854213.570487%13.570487%13.6%2,0604312.731377%12.731377%12.7%5644412.545235%12.545235%12.5%5204511.936937%11.936937%11.9%1064611.750000%11.750000%11.8%2824711.404144%11.404144%11.4%1,5744810.190370%10.190370%10.2%91499.402883%9.402883%9.4%41150
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older with a bachelor's degree or higher..

Very Advanced Degrees by County Subdivision#17

Percent of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).
Scope: population of the Brown Township, selected other county subdivisions in the Dayton Area, and entities that contain the Brown Township
0%5%10%15%Count#OakwoodMiami TownshipMiamiKetteringSugarcreek TownshipSugarcreekWashington TownshipWashingtonBeavercreek TownshipBeavercreekXenia TownshipXeniaKetteringCedarville TownshipCedarvilleBellbrookUnited States of AmericaUnited StatesWashington TownshipWashingtonButler TownshipButlerMidwestClaytonEast North CentralGerman TownshipGermanOhioDayton Metro AreaDayton AreaSpring Valley TownshipSpg VlyBath TownshipNew Jasper TownshipNew JasperJefferson TownshipJeffersonLostcreek TownshipLostcreekStaunton TownshipStauntonMiami TownshipMiamiMonroe TownshipMonroeConcord TownshipConcordSpringcreek TownshipSpringcreekRoss TownshipXeniaVandaliaJackson TownshipJacksonHuber HeightsDaytonMiami CountyMiamiMiami East Local School DistrictMiami EastNewton TownshipNewtonEnglewoodRiversideUnion TownshipUnionBethel TownshipBethelPerry TownshipPerryCaesarscreek TownshipCaesarscreek390100Tract 390100Clay TownshipMoraineBrown TownshipBrownHarrison TownshipHarrisonJefferson TownshipJeffersonTrotwoodUnion City TownshipUnion CityPiquaSilvercreek TownshipSilvercreekWest CarrolltonW CarrolltonNewberry TownshipNewberryHuber HeightsElizabeth TownshipElizabeth15.759265%15.759265%15.8%961111.642743%11.642743%11.6%43829.880240%9.880240%9.9%3338.562020%8.562020%8.6%46846.820669%6.820669%6.8%2,80556.685422%6.685422%6.7%2,51963.976778%3.976778%4.0%13773.778338%3.778338%3.8%1,48583.712406%3.712406%3.7%7993.563651%3.563651%3.6%180103.336158%3.336158%3.3%7,127,6737.13M3.270042%3.270042%3.3%31113.050620%3.050620%3.1%182122.893416%2.893416%2.9%1,311,0191.31M2.885133%2.885133%2.9%268132.855432%2.855432%2.9%896,039896k2.798206%2.798206%2.8%156142.683241%2.683241%2.7%210,582211k2.681530%2.681530%2.7%14,56814.6k2.603143%2.603143%2.6%53152.451477%2.451477%2.5%605162.087683%2.087683%2.1%40172.027027%2.027027%2.0%18182.022867%2.022867%2.0%23191.858470%1.858470%1.9%26201.762090%1.762090%1.8%630211.689779%1.689779%1.7%184221.625824%1.625824%1.6%343231.590595%1.590595%1.6%23241.512605%1.512605%1.5%9251.484083%1.484083%1.5%262261.432292%1.432292%1.4%154271.422122%1.422122%1.4%63281.349604%1.349604%1.3%334291.257490%1.257490%1.3%1,106301.179360%1.179360%1.2%8451.176223%1.176223%1.2%561.166667%1.166667%1.2%28311.163978%1.163978%1.2%114321.161165%1.161165%1.2%191331.098901%1.098901%1.1%80341.077296%1.077296%1.1%40351.013269%1.013269%1.0%42360.975610%0.975610%1.0%8370.948167%0.948167%0.9%300.821168%0.821168%0.8%54380.790330%0.790330%0.8%34390.783875%0.783875%0.8%7400.665349%0.665349%0.7%101410.618047%0.618047%0.6%30420.613643%0.613643%0.6%103430.410303%0.410303%0.4%18440.391248%0.391248%0.4%54450.381534%0.381534%0.4%10460.363236%0.363236%0.4%33470.137268%0.137268%0.1%6480.000000%0.000000%0.0%0490.000000%0.000000%0.0%050
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).

Under-Education Sex Ratio by County Subdivision#18

Percentage more likely men are than women to not have a high school diploma (or equivalent) among people aged 25 years and older.
Scope: population of the Brown Township, selected other county subdivisions in the Dayton Area, and entities that contain the Brown Township
Female
Male
0x2x4xFM#LostcreekWashingtonBrownUnion CityJeffersonMiamiEnglewoodTract 390100SpringcreekBellbrookBeavercreekHarrisonTrotwoodClay TownshipClaytonXeniaPerryMidwestEast North CentralDaytonUnited StatesOhioNew JasperPiquaRiversideMiami EastOakwoodVandaliaSilvercreekButlerHuber HeightsNewberryDayton AreaStauntonGermanXeniaMonroeBethelCedarvilleMiamiJacksonMiamiHuber HeightsNewtonJeffersonSpg VlyCaesarscreekBath TownshipUnionW CarrolltonSugarcreekMoraineConcordKetteringRoss TownshipElizabethWashington-1.000000x-1.000000x5.393053x5.393053x5.39x1.186%1.19%6.399%6.40%1-1.000000x-1.000000x4.530368x4.530368x4.53x2.301%2.30%10.426%10.4%2-1.000000x-1.000000x2.607422x2.607422x2.61x5.393%5.39%14.063%14.1%3-1.000000x-1.000000x2.074399x2.074399x2.07x3.156%3.16%6.547%6.55%4-1.000000x-1.000000x1.824560x1.824560x1.82x12.037%12.0%21.962%22.0%5-1.000000x-1.000000x1.693635x1.693635x1.69x3.194%3.19%5.409%5.41%6-1.000000x-1.000000x1.662684x1.662684x1.66x4.982%4.98%8.283%8.28%7-1.000000x-1.000000x1.585131x1.585131x1.59x5.426%5.43%8.601%8.60%-1.000000x-1.000000x1.393347x1.393347x1.39x5.021%5.02%6.996%7.00%8-1.000000x-1.000000x1.392132x1.392132x1.39x2.663%2.66%3.707%3.71%9-1.000000x-1.000000x1.332397x1.332397x1.33x2.666%2.67%3.552%3.55%10-1.000000x-1.000000x1.228308x1.228308x1.23x15.280%15.3%18.769%18.8%11-1.000000x-1.000000x1.202006x1.202006x1.20x12.700%12.7%15.265%15.3%12-1.000000x-1.000000x1.169610x1.169610x1.17x6.579%6.58%7.695%7.69%13-1.000000x-1.000000x1.168343x1.168343x1.17x4.575%4.58%5.345%5.35%14-1.000000x-1.000000x1.164301x1.164301x1.16x11.282%11.3%13.136%13.1%15-1.000000x-1.000000x1.158773x1.158773x1.16x9.787%9.79%11.341%11.3%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-1.000000x1.114342x1.114342x1.11x16.070%16.1%17.907%17.9%17-1.000000x-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-1.000000x1.078091x1.078091x1.08x9.054%9.05%9.761%9.76%18-1.000000x-1.000000x1.067081x1.067081x1.07x13.933%13.9%14.868%14.9%19-1.000000x-1.000000x1.063703x1.063703x1.06x12.715%12.7%13.525%13.5%20-1.000000x-1.000000x1.061437x1.061437x1.06x9.165%9.16%9.728%9.73%-1.000000x-1.000000x1.053352x1.053352x1.05x1.681%1.68%1.771%1.77%21-1.000000x-1.000000x1.041405x1.041405x1.04x9.427%9.43%9.818%9.82%22-1.000000x-1.000000x1.039463x1.039463x1.04x11.205%11.2%11.647%11.6%23-1.000000x-1.000000x1.038221x1.038221x1.04x5.615%5.62%5.830%5.83%24-1.000000x-1.000000x1.021443x1.021443x1.02x7.189%7.19%7.344%7.34%25-1.000000x-1.000000x1.003493x1.003493x1.00x12.013%12.0%12.055%12.1%26-1.000000x-1.000000x1.000795x1.000795x1.00x9.840%9.84%9.848%9.85%-1.009360x-1.009360x1.01x1.000000x1.000000x12.140%12.1%12.027%12.0%27-1.036785x-1.036785x1.04x1.000000x1.000000x7.569%7.57%7.300%7.30%28-1.098304x-1.098304x1.10x1.000000x1.000000x9.064%9.06%8.253%8.25%29-1.107040x-1.107040x1.11x1.000000x1.000000x7.229%7.23%6.530%6.53%30-1.112699x-1.112699x1.11x1.000000x1.000000x15.512%15.5%13.941%13.9%31-1.114383x-1.114383x1.11x1.000000x1.000000x4.152%4.15%3.725%3.73%32-1.123601x-1.123601x1.12x1.000000x1.000000x9.091%9.09%8.091%8.09%33-1.128565x-1.128565x1.13x1.000000x1.000000x11.021%11.0%9.765%9.77%34-1.131015x-1.131015x1.13x1.000000x1.000000x11.559%11.6%10.220%10.2%-1.167707x-1.167707x1.17x1.000000x1.000000x3.276%3.28%2.806%2.81%35-1.174356x-1.174356x1.17x1.000000x1.000000x13.448%13.4%11.452%11.5%36-1.218241x-1.218241x1.22x1.000000x1.000000x12.867%12.9%10.562%10.6%37-1.239072x-1.239072x1.24x1.000000x1.000000x6.004%6.00%4.845%4.85%38-1.273525x-1.273525x1.27x1.000000x1.000000x7.940%7.94%6.235%6.24%39-1.295653x-1.295653x1.30x1.000000x1.000000x13.964%14.0%10.778%10.8%40-1.322963x-1.322963x1.32x1.000000x1.000000x14.938%14.9%11.291%11.3%41-1.326146x-1.326146x1.33x1.000000x1.000000x11.777%11.8%8.881%8.88%42-1.329514x-1.329514x1.33x1.000000x1.000000x3.020%3.02%2.272%2.27%43-1.430388x-1.430388x1.43x1.000000x1.000000x16.703%16.7%11.677%11.7%44-1.476972x-1.476972x1.48x1.000000x1.000000x12.258%12.3%8.300%8.30%45-1.505212x-1.505212x1.51x1.000000x1.000000x7.040%7.04%4.677%4.68%46-1.535714x-1.535714x1.54x1.000000x1.000000x19.388%19.4%12.625%12.6%47-1.564827x-1.564827x1.56x1.000000x1.000000x10.331%10.3%6.602%6.60%48-1.641786x-1.641786x1.64x1.000000x1.000000x4.457%4.46%2.715%2.71%49
F percentage of females in category
M percentage of males in category
# rank of county subdivision out of 49 by male-to-female sex ratio

Over-Education Sex Ratio by County Subdivision#19

Percentage more likely men are than women to have a professional or doctorate degree (e.g., MBA, PhD, or MD) among people aged 25 years and older.
Scope: population of the Brown Township, selected other county subdivisions in the Dayton Area, and entities that contain the Brown Township
Female
Male
10x5x0x5x10xFM#PiquaNewberryBethelSpringcreekBrownKetteringUnionXeniaButlerHarrisonMiamiSugarcreekConcordJacksonWashingtonNewtonSilvercreekGermanStauntonClaytonMonroeDayton AreaKetteringXeniaOakwoodBeavercreekJeffersonDaytonW CarrolltonEnglewoodMiamiMiami EastBath TownshipSpg VlyOhioHuber HeightsUnion CityEast North CentralMidwestTrotwoodUnited StatesRiversideVandaliaCedarvilleTract 390100MiamiWashingtonLostcreekBellbrookNew JasperCaesarscreekClay TownshipPerryJeffersonMoraineRoss Township-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%0.856%0.86%1-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%0.274%0.27%2-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%2.096%2.10%3-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%3.155%3.16%4-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%1.563%1.56%5-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%22.148%22.1%6-1.000000x-1.000000x7.242594x7.242594x7.24x0.270%0.27%1.956%1.96%7-1.000000x-1.000000x6.351483x6.351483x6.35x1.066%1.07%6.773%6.77%8-1.000000x-1.000000x5.744397x5.744397x5.74x0.946%0.95%5.436%5.44%9-1.000000x-1.000000x4.666070x4.666070x4.67x0.241%0.24%1.124%1.12%10-1.000000x-1.000000x3.501312x3.501312x3.50x0.534%0.53%1.871%1.87%-1.000000x-1.000000x3.370909x3.370909x3.37x3.955%3.96%13.333%13.3%11-1.000000x-1.000000x3.284216x3.284216x3.28x0.775%0.78%2.546%2.55%12-1.000000x-1.000000x3.032298x3.032298x3.03x0.726%0.73%2.202%2.20%13-1.000000x-1.000000x2.977263x2.977263x2.98x3.534%3.53%10.523%10.5%14-1.000000x-1.000000x2.806452x2.806452x2.81x0.603%0.60%1.694%1.69%15-1.000000x-1.000000x2.754576x2.754576x2.75x0.211%0.21%0.582%0.58%16-1.000000x-1.000000x2.595017x2.595017x2.60x1.608%1.61%4.171%4.17%17-1.000000x-1.000000x2.417181x2.417181x2.42x1.062%1.06%2.568%2.57%18-1.000000x-1.000000x2.408687x2.408687x2.41x1.708%1.71%4.114%4.11%19-1.000000x-1.000000x2.225590x2.225590x2.23x1.068%1.07%2.376%2.38%20-1.000000x-1.000000x2.159743x2.159743x2.16x1.731%1.73%3.739%3.74%-1.000000x-1.000000x2.155653x2.155653x2.16x2.468%2.47%5.319%5.32%21-1.000000x-1.000000x2.113800x2.113800x2.11x0.980%0.98%2.071%2.07%22-1.000000x-1.000000x2.018680x2.018680x2.02x10.778%10.8%21.756%21.8%23-1.000000x-1.000000x2.007898x2.007898x2.01x4.457%4.46%8.948%8.95%24-1.000000x-1.000000x1.991011x1.991011x1.99x1.354%1.35%2.697%2.70%25-1.000000x-1.000000x1.989047x1.989047x1.99x0.860%0.86%1.711%1.71%26-1.000000x-1.000000x1.965529x1.965529x1.97x0.250%0.25%0.491%0.49%27-1.000000x-1.000000x1.930562x1.930562x1.93x0.815%0.81%1.573%1.57%28-1.000000x-1.000000x1.807171x1.807171x1.81x8.580%8.58%15.505%15.5%29-1.000000x-1.000000x1.732481x1.732481x1.73x0.857%0.86%1.484%1.48%-1.000000x-1.000000x1.691857x1.691857x1.69x1.833%1.83%3.102%3.10%30-1.000000x-1.000000x1.674620x1.674620x1.67x1.970%1.97%3.299%3.30%31-1.000000x-1.000000x1.669500x1.669500x1.67x2.031%2.03%3.391%3.39%-1.000000x-1.000000x1.627164x1.627164x1.63x1.044%1.04%1.699%1.70%32-1.000000x-1.000000x1.606929x1.606929x1.61x0.316%0.32%0.507%0.51%33-1.000000x-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-1.000000x1.529593x1.529593x1.53x0.502%0.50%0.768%0.77%34-1.000000x-1.000000x1.526215x1.526215x1.53x2.660%2.66%4.060%4.06%-1.000000x-1.000000x1.510836x1.510836x1.51x0.931%0.93%1.407%1.41%35-1.000000x-1.000000x1.378684x1.378684x1.38x1.210%1.21%1.668%1.67%36-1.000000x-1.000000x1.365602x1.365602x1.37x3.159%3.16%4.314%4.31%37-1.000000x-1.000000x1.252666x1.252666x1.25x0.840%0.84%1.052%1.05%-1.000000x-1.000000x1.246667x1.246667x1.25x1.577%1.58%1.966%1.97%38-1.000000x-1.000000x1.084823x1.084823x1.08x3.138%3.14%3.404%3.40%39-1.205254x-1.205254x1.21x1.000000x1.000000x2.203%2.20%1.828%1.83%40-1.215163x-1.215163x1.22x1.000000x1.000000x3.883%3.88%3.196%3.20%41-1.722621x-1.722621x1.72x1.000000x1.000000x2.616%2.62%1.518%1.52%42-1.724566x-1.724566x1.72x1.000000x1.000000x1.241%1.24%0.719%0.72%43-1.762014x-1.762014x1.76x1.000000x1.000000x1.030%1.03%0.584%0.58%44-2.016473x-2.016473x2.02x1.000000x1.000000x1.357%1.36%0.673%0.67%45-6.075130x-6.075130x6.08x1.000000x1.000000x1.036%1.04%0.171%0.17%46-10.000000x-10.000000x> 10.0x1.000000x1.000000x1.491%1.49%0.000%0%47-10.000000x-10.000000x> 10.0x1.000000x1.000000x3.061%3.06%0.000%0%48
F percentage of females in category
M percentage of males in category
# rank of county subdivision out of 48 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 Brown Township to the 50 most populous county subdivisions in Ohio and to those entities that contain or substantially overlap with the Brown Township. The least populous of the compared county subdivisions has a population of 36,945.

No H.S. Diploma by County Subdivision#20

Percent of population 25 years of age and older without a high school diploma (or equivalent).
Scope: population of the Brown Township, selected other county subdivisions in Ohio, and entities that contain the Brown Township
0%5%10%15%20%Count#ClevelandMiddletownLorainYoungstownSpringfieldDaytonMansfieldLimaMarion TownshipMarionCantonHamiltonWarrenToledoCincinnatiAkronElyriaUnited States of AmericaUnited StatesNewarkBath TownshipLancaster City TownshipLancaster CityColumbusMiami CountyMiamiColerain TownshipColerainEast North CentralEuclidOhioMidwestParmaDayton Metro AreaDayton AreaBrown TownshipBrownMiami East Local School DistrictMiami EastFindlayFairfieldMiami TownshipMiamiUnion TownshipUnionHuber Heights390100Tract 390100Jackson 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%3,757815.742056%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%60,83160.8k2010.912923%10.912923%10.9%7,81910.847918%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%825,155825k10.244520%10.244520%10.2%4,641,8354.64M9.939137%9.939137%9.9%5,683239.844056%9.844056%9.8%53,48053.5k9.742441%9.742441%9.7%879.451796%9.451796%9.5%4509.003845%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%2,777277.261193%7.261193%7.3%1,797287.048040%7.048040%7.0%2236.480864%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#21

Percent of population 25 years of age and older with a bachelor's degree or higher..
Scope: population of the Brown Township, selected other county subdivisions in Ohio, and entities that contain the Brown Township
0%20%40%60%Count#DublinDeerfield TownshipDeerfieldAnderson TownshipAndersonWashington TownshipWashingtonBeavercreek TownshipBeavercreekCleveland HeightsCleveland HtsLiberty TownshipLibertyWest Chester TownshipW ChesterSylvania TownshipSylvaniaStrongsvilleMifflin TownshipMifflinViolet TownshipVioletLakewoodMiami TownshipMiamiJackson TownshipJacksonColumbusCincinnatiKetteringPlain TownshipPlainGreen TownshipGrnCuyahoga FallsMentorBoardman TownshipBoardmanUnited States of AmericaUnited StatesUnion TownshipUnionJackson TownshipJacksonMidwestEast North CentralFairfieldDayton Metro AreaDayton AreaBath TownshipFindlayMiami TownshipMiamiOhioHuber HeightsMiami East Local School DistrictMiami EastColerain TownshipColerainMiami CountyMiamiEuclidAkronParma390100Tract 390100NewarkToledoDaytonMiddletownLancaster City TownshipLancaster CityClevelandElyriaHamiltonSpringfieldCantonMansfieldWarrenYoungstownLorainLimaMarion TownshipMarionBrown TownshipBrown75.246997%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%12,09212.1k1534.685843%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%8,2882627.783136%27.783136%27.8%150,938151k26.954091%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%5,6513022.369250%22.369250%22.4%1,06521.665661%21.665661%21.7%8,6163121.063797%21.063797%21.1%15,09215.1k20.614221%20.614221%20.6%6,8133220.213821%20.213821%20.2%26,69726.7k3319.988457%19.988457%20.0%11,42911.4k3419.089760%19.089760%19.1%60418.053148%18.053148%18.1%5,7273518.048021%18.048021%18.0%33,17133.2k3617.635555%17.635555%17.6%15,51115.5k3716.631922%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%5,5514115.075315%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%5,2604711.718579%11.718579%11.7%4,8124811.460139%11.460139%11.5%2,6454910.478559%10.478559%10.5%3,2455010.190370%10.190370%10.2%91
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older with a bachelor's degree or higher..

Very Advanced Degrees by County Subdivision#22

Percent of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).
Scope: population of the Brown Township, selected other county subdivisions in Ohio, and entities that contain the Brown Township
0%2%4%6%8%10%Count#Cleveland HeightsCleveland HtsDublinAnderson TownshipAndersonSylvania TownshipSylvaniaWashington TownshipWashingtonBeavercreek TownshipBeavercreekJackson TownshipJacksonLakewoodCincinnatiStrongsvilleDeerfield TownshipDeerfieldWest Chester TownshipW ChesterKetteringLiberty TownshipLibertyMifflin TownshipMifflinColumbusUnited States of AmericaUnited StatesPlain TownshipPlainBoardman TownshipBoardmanViolet TownshipVioletMiami TownshipMiamiMidwestEast North CentralOhioDayton Metro AreaDayton AreaCuyahoga FallsGreen TownshipGrnBath TownshipAkronJackson TownshipJacksonClevelandMentorColerain TownshipColerainMiami TownshipMiamiFindlayToledoSpringfieldFairfieldEuclidHuber HeightsLimaDaytonCantonHamiltonUnion TownshipUnionParmaNewarkMiami CountyMiamiMiami East Local School DistrictMiami EastLancaster City TownshipLancaster CityMansfieldMiddletownLorainElyria390100Tract 390100YoungstownBrown TownshipBrownWarrenMarion TownshipMarion10.753042%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%1,485133.514938%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%210,582211k2.681530%2.681530%2.7%14,56814.6k2.481744%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%375421.179360%1.179360%1.2%8451.176223%1.176223%1.2%561.159205%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%343470.948167%0.948167%0.9%300.794541%0.794541%0.8%347480.783875%0.783875%0.8%70.742101%0.742101%0.7%202490.720098%0.720098%0.7%22350
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).

Under-Education Sex Ratio by County Subdivision#23

Percentage more likely men are than women to not have a high school diploma (or equivalent) among people aged 25 years and older.
Scope: population of the Brown Township, selected other county subdivisions in Ohio, and entities that contain the Brown Township
Female
Male
1x0x1x2xFM#BrownAndersonMansfieldTract 390100Cleveland HtsBeavercreekUnionToledoFindlayLorainMarionYoungstownColerainGrnFairfieldElyriaMiddletownLancaster CityMidwestEast North CentralSpringfieldWarrenDaytonCantonUnited StatesOhioLimaParmaMiami EastColumbusClevelandDeerfieldMentorNewarkW ChesterPlainLibertyJacksonHuber HeightsHamiltonJacksonCincinnatiDayton AreaAkronMifflinSylvaniaMiamiEuclidMiamiMiamiCuyahoga FallsStrongsvilleLakewoodBath TownshipDublinKetteringWashingtonBoardmanViolet-1.000000x-1.000000x2.607422x2.607422x2.61x5.393%5.39%14.063%14.1%-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-1.000000x1.585131x1.585131x1.59x5.426%5.43%8.601%8.60%-1.000000x-1.000000x1.485471x1.485471x1.49x5.146%5.15%7.645%7.64%3-1.000000x-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-1.000000x1.087544x1.087544x1.09x15.592%15.6%16.957%17.0%21-1.000000x-1.000000x1.081824x1.081824x1.08x9.568%9.57%10.350%10.4%22-1.000000x-1.000000x1.061437x1.061437x1.06x9.165%9.16%9.728%9.73%-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-1.000000x1.038813x1.038813x1.04x5.175%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%35-1.000000x-1.000000x1.000795x1.000795x1.00x9.840%9.84%9.848%9.85%-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%41-1.131015x-1.131015x1.13x1.000000x1.000000x11.559%11.6%10.220%10.2%-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%46-1.505212x-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#24

Percentage more likely men are than women to have a professional or doctorate degree (e.g., MBA, PhD, or MD) among people aged 25 years and older.
Scope: population of the Brown Township, selected other county subdivisions in Ohio, and entities that contain the Brown Township
Female
Male
0x5x10xFM#BrownElyriaMiamiSpringfieldWashingtonYoungstownBoardmanLorainMiddletownLancaster CityFindlayAndersonJacksonDayton AreaKetteringMifflinPlainBeavercreekDeerfieldDaytonNewarkEuclidMiamiAkronDublinSylvaniaStrongsvilleMiami EastBath TownshipOhioFairfieldMansfieldW ChesterHuber HeightsLakewoodEast North CentralMidwestWarrenUnited StatesLibertyParmaCleveland HtsColumbusUnionMentorGrnJacksonClevelandCincinnatiTract 390100MiamiMarionVioletColerainToledoHamiltonCantonCuyahoga FallsLima-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%1.563%1.56%-1.000000x-1.000000x3.557903x3.557903x3.56x0.433%0.43%1.542%1.54%1-1.000000x-1.000000x3.501312x3.501312x3.50x0.534%0.53%1.871%1.87%-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-1.000000x2.159743x2.159743x2.16x1.731%1.73%3.739%3.74%-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-1.000000x1.732481x1.732481x1.73x0.857%0.86%1.484%1.48%-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-1.000000x1.543502x1.543502x1.54x0.592%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-1.000000x1.252666x1.252666x1.25x0.840%0.84%1.052%1.05%-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 Brown Township to the 50 most populous county subdivisions in the Midwest and to those entities that contain or substantially overlap with the Brown Township. The least populous of the compared county subdivisions has a population of 112,821.

No H.S. Diploma by County Subdivision#25

Percent of population 25 years of age and older without a high school diploma (or equivalent).
Scope: population of the Brown Township, selected other county subdivisions in the Midwest, and entities that contain the Brown Township
0%10%20%30%Count#Aurora TownshipAuroraCenter TownshipCtrKansas CityClevelandWayne TownshipWayneDetroitMilwaukeeNorth TownshipNDaytonChicagoProviso TownshipProvisoRockford TownshipRockfordSt. LouisWarrenGrand RapidsToledoBlue TownshipCincinnatiAkronSt. PaulSterling HeightsSterling HtsUnited States of AmericaUnited StatesThornton TownshipThorntonWichitaKaw TownshipOmahaBloomingdale TownshipBloomingdaleColumbusMaine TownshipMaineTopekaMinneapolisMiami CountyMiamiSpringfield TownshipSpringfieldEast North CentralWorth TownshipWorthOhioMidwestLawrence TownshipLawrenceDayton Metro AreaDayton AreaBrown TownshipBrownSioux FallsMiami East Local School DistrictMiami EastCapital TownshipCapitalWheeling TownshipWheelingPalatine TownshipPalatineSchaumburg TownshipSchaumburgLincoln390100Tract 390100Washington TownshipWashingtonOlatheFargoCedar RapidsYork TownshipMilton TownshipMiltonMadisonDowners Grove TownshipDowners GrvLisle TownshipLisleOverland ParkAnn Arbor33.464284%33.464284%33.5%29,81429.8k123.165532%23.165532%23.2%22,92622.9k222.659362%22.659362%22.7%21,21821.2k321.582420%21.582420%21.6%54,98155.0k421.037720%21.037720%21.0%18,48918.5k521.003600%21.003600%21.0%90,67890.7k617.485105%17.485105%17.5%63,80063.8k717.062713%17.062713%17.1%17,39117.4k816.928359%16.928359%16.9%14,88914.9k916.905373%16.905373%16.9%309,770310k1015.636222%15.636222%15.6%16,11016.1k1115.608074%15.608074%15.6%18,24118.2k1215.466266%15.466266%15.5%33,80433.8k1315.286174%15.286174%15.3%14,05914.1k1414.563179%14.563179%14.6%17,64317.6k1514.332972%14.332972%14.3%26,34326.3k1614.241047%14.241047%14.2%15,25815.3k1713.761583%13.761583%13.8%26,28626.3k1813.591726%13.591726%13.6%17,95118.0k1913.278342%13.278342%13.3%24,61324.6k2013.132171%13.132171%13.1%12,21212.2k2113.020590%13.020590%13.0%27,818,38027.8M12.974232%12.974232%13.0%14,37014.4k2212.568464%12.568464%12.6%31,23131.2k2312.455744%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%29,34729.3k3010.912923%10.912923%10.9%7,81910.767091%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%825,155825k10.244520%10.244520%10.2%4,641,8354.64M10.179618%10.179618%10.2%8,161339.844056%9.844056%9.8%53,48053.5k9.742441%9.742441%9.7%879.702326%9.702326%9.7%9,123349.451796%9.451796%9.5%4508.623103%8.623103%8.6%6,837358.424707%8.424707%8.4%9,343368.392669%8.392669%8.4%6,695377.739434%7.739434%7.7%7,226387.092309%7.092309%7.1%11,88611.9k397.048040%7.048040%7.0%2236.804680%6.804680%6.8%6,403406.424130%6.424130%6.4%5,331416.055621%6.055621%6.1%4,270425.981653%5.981653%6.0%5,099435.461095%5.461095%5.5%4,715445.266517%5.266517%5.3%4,126454.836248%4.836248%4.8%7,351464.020265%4.020265%4.0%4,166473.522812%3.522812%3.5%2,870483.377424%3.377424%3.4%4,282493.157717%3.157717%3.2%2,05750
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older without a high school diploma (or equivalent).

Bachelor's Degrees by County Subdivision#26

Percent of population 25 years of age and older with a bachelor's degree or higher..
Scope: population of the Brown Township, selected other county subdivisions in the Midwest, and entities that contain the Brown Township
0%20%40%60%Count#Ann ArborOverland ParkMilton TownshipMiltonLisle TownshipLisleMadisonDowners Grove TownshipDowners GrvWashington TownshipWashingtonPalatine TownshipPalatineYork TownshipMinneapolisOlatheWheeling TownshipWheelingSchaumburg TownshipSchaumburgKaw TownshipSt. PaulMaine TownshipMaineFargoLincolnLawrence TownshipLawrenceChicagoCapital TownshipCapitalColumbusOmahaCincinnatiSt. LouisGrand RapidsBloomingdale TownshipBloomingdaleCedar RapidsUnited States of AmericaUnited StatesSioux FallsMidwestWichitaEast North CentralDayton Metro AreaDayton AreaSterling HeightsSterling HtsTopekaSpringfield TownshipSpringfieldOhioProviso TownshipProvisoWorth TownshipWorthMilwaukeeMiami East Local School DistrictMiami EastRockford TownshipRockfordMiami CountyMiamiAkronCenter TownshipCtrNorth TownshipN390100Tract 390100Thornton TownshipThorntonToledoDaytonWarrenWayne TownshipWayneKansas CityClevelandAurora TownshipAuroraBlue TownshipDetroitBrown TownshipBrown72.810169%72.810169%72.8%47,43047.4k158.823344%58.823344%58.8%74,57874.6k257.681507%57.681507%57.7%45,19045.2k356.900171%56.900171%56.9%46,35646.4k456.337583%56.337583%56.3%85,63285.6k553.762123%53.762123%53.8%55,71155.7k650.610540%50.610540%50.6%47,62347.6k749.860853%49.860853%49.9%39,77539.8k849.728972%49.728972%49.7%42,93542.9k947.670489%47.670489%47.7%127,663128k1046.512581%46.512581%46.5%38,59838.6k1146.409378%46.409378%46.4%51,46851.5k1241.792515%41.792515%41.8%39,02039.0k1341.581304%41.581304%41.6%50,61950.6k1439.969357%39.969357%40.0%74,08874.1k1539.511462%39.511462%39.5%38,91838.9k1638.241175%38.241175%38.2%26,96527.0k1737.146608%37.146608%37.1%62,25462.3k1836.577273%36.577273%36.6%29,32429.3k1936.546320%36.546320%36.5%669,666670k2036.298510%36.298510%36.3%28,78028.8k2134.685843%34.685843%34.7%185,460185k2234.651487%34.651487%34.7%99,56199.6k2333.783048%33.783048%33.8%64,52964.5k2433.007421%33.007421%33.0%72,14372.1k2532.904381%32.904381%32.9%39,86339.9k2632.623147%32.623147%32.6%25,12725.1k2731.793440%31.793440%31.8%27,10227.1k2830.315023%30.315023%30.3%64,767,78764.8M30.259813%30.259813%30.3%28,45328.5k2928.952816%28.952816%29.0%13,118,64213.1M28.877567%28.877567%28.9%71,75771.8k3028.462853%28.462853%28.5%8,931,6868.93M27.783136%27.783136%27.8%150,938151k27.532180%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%85,81285.8k3622.369250%22.369250%22.4%1,06521.592552%21.592552%21.6%25,23525.2k3721.063797%21.063797%21.1%15,09215.1k20.213821%20.213821%20.2%26,69726.7k3820.139240%20.139240%20.1%19,93119.9k3919.650916%19.650916%19.7%20,02920.0k4019.089760%19.089760%19.1%60418.971090%18.971090%19.0%21,01221.0k4118.048021%18.048021%18.0%33,17133.2k4217.635555%17.635555%17.6%15,51115.5k4317.280259%17.280259%17.3%15,89315.9k4416.826535%16.826535%16.8%14,78814.8k4516.167409%16.167409%16.2%15,13915.1k4616.073076%16.073076%16.1%40,94640.9k4715.929601%15.929601%15.9%14,19214.2k4815.821208%15.821208%15.8%16,95117.0k4913.833543%13.833543%13.8%59,72359.7k5010.190370%10.190370%10.2%91
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older with a bachelor's degree or higher..

Very Advanced Degrees by County Subdivision#27

Percent of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).
Scope: population of the Brown Township, selected other county subdivisions in the Midwest, and entities that contain the Brown Township
0%5%10%15%Count#Ann ArborMadisonDowners Grove TownshipDowners GrvWashington TownshipWashingtonMinneapolisYork TownshipOverland ParkLisle TownshipLisleSt. PaulKaw TownshipMilton TownshipMiltonSt. LouisCincinnatiLincolnChicagoFargoCapital TownshipCapitalOmahaMaine TownshipMainePalatine TownshipPalatineWheeling TownshipWheelingColumbusUnited States of AmericaUnited StatesTopekaGrand RapidsLawrence TownshipLawrenceSpringfield TownshipSpringfieldCedar RapidsMidwestEast North CentralSioux FallsOlatheOhioDayton Metro AreaDayton AreaCenter TownshipCtrSchaumburg TownshipSchaumburgWichitaProviso TownshipProvisoAkronBloomingdale TownshipBloomingdaleRockford TownshipRockfordMilwaukeeWorth TownshipWorthClevelandToledoNorth TownshipNSterling HeightsSterling HtsKansas CityDetroitDaytonWayne TownshipWayneMiami CountyMiamiMiami East Local School DistrictMiami EastWarrenBlue Township390100Tract 390100Aurora TownshipAuroraThornton TownshipThorntonBrown TownshipBrown17.877867%17.877867%17.9%11,64611.6k19.171173%9.171173%9.2%13,94013.9k27.658384%7.658384%7.7%7,93637.306290%7.306290%7.3%6,87546.241155%6.241155%6.2%16,71416.7k56.197734%6.197734%6.2%5,35165.940071%5.940071%5.9%7,53175.933545%5.933545%5.9%4,83485.920847%5.920847%5.9%10,97511.0k95.896414%5.896414%5.9%7,178105.800061%5.800061%5.8%4,544114.880448%4.880448%4.9%10,66710.7k124.729595%4.729595%4.7%9,034134.568292%4.568292%4.6%7,656144.485379%4.485379%4.5%82,18982.2k154.336789%4.336789%4.3%3,058164.233985%4.233985%4.2%3,357174.059919%4.059919%4.1%11,66511.7k184.030539%4.030539%4.0%3,970193.487439%3.487439%3.5%2,782203.407574%3.407574%3.4%3,779213.357865%3.357865%3.4%17,95418.0k223.336158%3.336158%3.3%7,127,6737.13M3.233245%3.233245%3.2%2,748233.174629%3.174629%3.2%3,846243.083448%3.083448%3.1%2,472252.911721%2.911721%2.9%3,015262.905776%2.905776%2.9%2,477272.893416%2.893416%2.9%1,311,0191.31M2.855432%2.855432%2.9%896,039896k2.841677%2.841677%2.8%2,672282.830666%2.830666%2.8%2,349292.683241%2.683241%2.7%210,582211k2.681530%2.681530%2.7%14,56814.6k2.602914%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%1,040461.179360%1.179360%1.2%8451.176223%1.176223%1.2%561.047058%1.047058%1.0%963470.997751%0.997751%1.0%1,069480.948167%0.948167%0.9%300.936111%0.936111%0.9%834490.876686%0.876686%0.9%971500.783875%0.783875%0.8%7
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).

Under-Education Sex Ratio by County Subdivision#28

Percentage more likely men are than women to not have a high school diploma (or equivalent) among people aged 25 years and older.
Scope: population of the Brown Township, selected other county subdivisions in the Midwest, and entities that contain the Brown Township
Female
Male
1x0x1x2xFM#BrownTract 390100Cedar RapidsLincolnDetroitOmahaToledoThorntonKansas CityMadisonLawrenceFargoProvisoRockfordBlue TownshipWayneMidwestTopekaEast North CentralMilwaukeeKaw TownshipDaytonSioux FallsUnited StatesOlatheOhioWorthNOverland ParkAuroraWheelingGrand RapidsSchaumburgChicagoMiami EastWichitaColumbusClevelandPalatineCapitalWarrenSpringfieldYork TownshipSt. LouisWashingtonBloomingdaleCtrCincinnatiDayton AreaAkronAnn ArborSt. PaulLisleMinneapolisMiamiSterling HtsDowners GrvMiltonMaine-1.000000x-1.000000x2.607422x2.607422x2.61x5.393%5.39%14.063%14.1%-1.000000x-1.000000x1.585131x1.585131x1.59x5.426%5.43%8.601%8.60%-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-1.000000x1.099747x1.099747x1.10x10.199%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-1.000000x1.061437x1.061437x1.06x9.165%9.16%9.728%9.73%-1.000000x-1.000000x1.059528x1.059528x1.06x12.215%12.2%12.942%12.9%29-1.000000x-1.000000x1.052237x1.052237x1.05x11.098%11.1%11.678%11.7%30-1.000000x-1.000000x1.046686x1.046686x1.05x21.119%21.1%22.105%22.1%31-1.000000x-1.000000x1.039581x1.039581x1.04x8.233%8.23%8.559%8.56%32-1.000000x-1.000000x1.039194x1.039194x1.04x8.470%8.47%8.802%8.80%33-1.000000x-1.000000x1.037373x1.037373x1.04x15.022%15.0%15.584%15.6%34-1.000000x-1.000000x1.028857x1.028857x1.03x10.622%10.6%10.928%10.9%35-1.000000x-1.000000x1.027464x1.027464x1.03x5.391%5.39%5.539%5.54%36-1.000000x-1.000000x1.018183x1.018183x1.02x15.334%15.3%15.613%15.6%37-1.000000x-1.000000x1.013146x1.013146x1.01x6.764%6.76%6.853%6.85%38-1.000000x-1.000000x1.007207x1.007207x1.01x12.130%12.1%12.217%12.2%39-1.000000x-1.000000x1.006204x1.006204x1.01x23.095%23.1%23.239%23.2%40-1.000000x-1.000000x1.001229x1.001229x1.00x13.754%13.8%13.771%13.8%41-1.000000x-1.000000x1.000795x1.000795x1.00x9.840%9.84%9.848%9.85%-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%46-1.131015x-1.131015x1.13x1.000000x1.000000x11.559%11.6%10.220%10.2%-1.131063x-1.131063x1.13x1.000000x1.000000x13.912%13.9%12.300%12.3%47-1.140051x-1.140051x1.14x1.000000x1.000000x4.269%4.27%3.744%3.74%48-1.194783x-1.194783x1.19x1.000000x1.000000x5.710%5.71%4.779%4.78%49-1.208375x-1.208375x1.21x1.000000x1.000000x12.117%12.1%10.027%10.0%50
F percentage of females in category
M percentage of males in category
# rank of county subdivision out of 50 by male-to-female sex ratio

Over-Education Sex Ratio by County Subdivision#29

Percentage more likely men are than women to have a professional or doctorate degree (e.g., MBA, PhD, or MD) among people aged 25 years and older.
Scope: population of the Brown Township, selected other county subdivisions in the Midwest, and entities that contain the Brown Township
Female
Male
0x5x10xFM#BrownMiamiDayton AreaRockfordNDaytonSioux FallsCapitalLawrenceDowners GrvAkronLisleWichitaYork TownshipMaineWarrenWheelingBlue TownshipSpringfieldMiami EastOverland ParkMiltonGrand RapidsOlatheOhioOmahaFargoWashingtonEast North CentralLincolnMidwestBloomingdaleKansas CityAuroraUnited StatesAnn ArborTopekaSterling HtsPalatineSchaumburgColumbusMadisonKaw TownshipMilwaukeeCedar RapidsClevelandCincinnatiSt. PaulSt. LouisTract 390100ChicagoWayneCtrToledoMinneapolisWorthDetroitProvisoThornton-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%1.563%1.56%-1.000000x-1.000000x3.501312x3.501312x3.50x0.534%0.53%1.871%1.87%-1.000000x-1.000000x2.159743x2.159743x2.16x1.731%1.73%3.739%3.74%-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-1.000000x1.732481x1.732481x1.73x0.857%0.86%1.484%1.48%-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-1.000000x1.550495x1.550495x1.55x0.737%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-1.000000x1.252666x1.252666x1.25x0.840%0.84%1.052%1.05%-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 Brown Township to the 50 most populous county subdivisions in the United States and to those entities that contain or substantially overlap with the Brown Township. The least populous of the compared county subdivisions has a population of 547,300.

No H.S. Diploma by County Subdivision#30

Percent of population 25 years of age and older without a high school diploma (or equivalent).
Scope: population of the Brown Township, selected other county subdivisions in the United States, and entities that contain the Brown Township
0%10%20%Count#San Antonio CentralSan Antonio CntrlBronxSan BernardinoLos AngelesSouthwest DallasSW DallasEl PasoAnaheim-Santa Ana-Garden GroveAnaheim-Santa An…FresnoHoustonMiamiDetroitNortheast DallasNE DallasEast San Gabriel ValleyE San Gabriel VlyFort WorthBrooklynLong Beach-LakewoodLong Bch-LakewoodQueensSan Fernando ValleySan Fernando VlyMilwaukeePhiladelphiaOntarioChicagoBaltimoreOceanside-EscondidoOceanside-Escond…Las VegasPhoenixBostonSacramentoOrlandoAustinDenverUnited States of AmericaUnited StatesManhattanSan DiegoTampaSan JoseSan FranciscoTucsonAlbuquerqueTownship 1:Charlotte1, CharlotteColumbusTulsaMiami CountyMiamiEast North CentralOhioSalt Lake CitySalt Lk CityTown of HempsteadHempsteadMidwestNorthwest HarrisNW HarrisWashingtonDayton Metro AreaDayton AreaBrown TownshipBrownAtlantaMiami East Local School DistrictMiami EastSeattleNortheast TarrantNE Tarrant390100Tract 390100PlanoSeattle East28.998944%28.998944%29.0%126,922127k128.837398%28.837398%28.8%261,022261k227.582802%27.582802%27.6%135,754136k324.837401%24.837401%24.8%434,160434k423.987048%23.987048%24.0%141,940142k523.756417%23.756417%23.8%81,30881.3k622.645542%22.645542%22.6%248,699249k722.107626%22.107626%22.1%92,47292.5k821.922900%21.922900%21.9%457,347457k921.818150%21.818150%21.8%149,688150k1021.003600%21.003600%21.0%90,67890.7k1120.783651%20.783651%20.8%207,494207k1220.461493%20.461493%20.5%128,038128k1320.041576%20.041576%20.0%106,726107k1420.017506%20.017506%20.0%351,046351k1519.402518%19.402518%19.4%73,10573.1k1619.344706%19.344706%19.3%315,505316k1719.344408%19.344408%19.3%244,983245k1817.485105%17.485105%17.5%63,80063.8k1917.390838%17.390838%17.4%180,039180k2017.129346%17.129346%17.1%71,39771.4k2116.905373%16.905373%16.9%309,770310k2216.548703%16.548703%16.5%69,83969.8k2315.999398%15.999398%16.0%70,21470.2k2415.906523%15.906523%15.9%198,651199k2514.952077%14.952077%15.0%308,569309k2614.325556%14.325556%14.3%63,64263.6k2713.900512%13.900512%13.9%103,047103k2813.679368%13.679368%13.7%53,75853.8k2913.668915%13.668915%13.7%78,23878.2k3013.638703%13.638703%13.6%63,86563.9k3113.020590%13.020590%13.0%27,818,38027.8M12.996284%12.996284%13.0%160,845161k3212.985760%12.985760%13.0%206,792207k3312.979618%12.979618%13.0%57,75857.8k3412.789590%12.789590%12.8%153,604154k3512.559735%12.559735%12.6%84,02484.0k3612.262851%12.262851%12.3%70,40970.4k3712.089143%12.089143%12.1%52,21752.2k3811.553484%11.553484%11.6%61,37861.4k3911.376979%11.376979%11.4%60,83160.8k4011.299086%11.299086%11.3%43,65343.7k4110.912923%10.912923%10.9%7,81910.719464%10.719464%10.7%3,363,7843.36M10.514146%10.514146%10.5%825,155825k10.435356%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%46,51046.5k459.844056%9.844056%9.8%53,48053.5k9.742441%9.742441%9.7%879.538552%9.538552%9.5%37,37337.4k469.451796%9.451796%9.5%4508.833573%8.833573%8.8%66,22066.2k478.418271%8.418271%8.4%31,44331.4k487.048040%7.048040%7.0%2235.714681%5.714681%5.7%20,64420.6k494.913852%4.913852%4.9%20,32620.3k50
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older without a high school diploma (or equivalent).

Bachelor's Degrees by County Subdivision#31

Percent of population 25 years of age and older with a bachelor's degree or higher..
Scope: population of the Brown Township, selected other county subdivisions in the United States, and entities that contain the Brown Township
0%20%40%60%Count#ManhattanSeattle EastWashingtonSan FranciscoPlanoSan JoseAtlantaSeattleBostonDenverAustinTownship 1:Charlotte1, CharlotteTown of HempsteadHempsteadSan DiegoNortheast TarrantNE TarrantNorthwest HarrisNW HarrisChicagoColumbusLos AngelesBrooklynSan Fernando ValleySan Fernando VlyNortheast DallasNE DallasSalt Lake CitySalt Lk CityAlbuquerqueTampaTucsonOceanside-EscondidoOceanside-Escond…TulsaQueensUnited States of AmericaUnited StatesHoustonBaltimoreLong Beach-LakewoodLong Bch-LakewoodMidwestPhoenixOrlandoEast North CentralAnaheim-Santa Ana-Garden GroveAnaheim-Santa An…SacramentoDayton Metro AreaDayton AreaEast San Gabriel ValleyE San Gabriel VlyOntarioOhioPhiladelphiaMiamiFort WorthSouthwest DallasSW DallasMilwaukeeFresnoMiami East Local School DistrictMiami EastLas VegasEl PasoMiami CountyMiamiBronx390100Tract 390100San BernardinoSan Antonio CentralSan Antonio CntrlDetroitBrown TownshipBrown60.434640%60.434640%60.4%747,953748k157.691220%57.691220%57.7%238,638239k255.360186%55.360186%55.4%256,316256k354.793235%54.793235%54.8%366,564367k454.142756%54.142756%54.1%195,588196k549.985845%49.985845%50.0%600,334600k649.803731%49.803731%49.8%195,136195k749.626221%49.626221%49.6%372,018372k846.377869%46.377869%46.4%206,036206k945.718966%45.718966%45.7%214,085214k1044.843364%44.843364%44.8%256,674257k1141.989192%41.989192%42.0%223,068223k1238.767308%38.767308%38.8%202,458202k1338.701072%38.701072%38.7%616,296616k1438.547398%38.547398%38.5%143,978144k1536.877886%36.877886%36.9%173,478173k1636.546320%36.546320%36.5%669,666670k1734.685843%34.685843%34.7%185,460185k1834.593243%34.593243%34.6%604,693605k1934.081468%34.081468%34.1%597,685598k2033.231104%33.231104%33.2%420,848421k2133.191099%33.191099%33.2%331,364331k2233.118385%33.118385%33.1%204,048204k2332.636312%32.636312%32.6%140,967141k2432.512191%32.512191%32.5%144,676145k2532.087814%32.087814%32.1%184,237184k2631.198303%31.198303%31.2%136,915137k2731.110082%31.110082%31.1%120,191120k2830.595789%30.595789%30.6%499,006499k2930.315023%30.315023%30.3%64,767,78764.8M30.080133%30.080133%30.1%627,520628k3029.719611%29.719611%29.7%125,423125k3129.113198%29.113198%29.1%109,693110k3228.952816%28.952816%29.0%13,118,64213.1M28.760152%28.760152%28.8%593,529594k3328.535877%28.535877%28.5%112,142112k3428.462853%28.462853%28.5%8,931,6868.93M28.412939%28.412939%28.4%312,038312k3528.231204%28.231204%28.2%209,283209k3627.783136%27.783136%27.8%150,938151k27.276345%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%94,05694.1k4422.369250%22.369250%22.4%1,06521.702666%21.702666%21.7%271,037271k4521.071885%21.071885%21.1%72,12072.1k4621.063797%21.063797%21.1%15,09215.1k19.131504%19.131504%19.1%173,169173k4719.089760%19.089760%19.1%60416.375473%16.375473%16.4%80,59580.6k4814.929012%14.929012%14.9%65,34165.3k4913.833543%13.833543%13.8%59,72359.7k5010.190370%10.190370%10.2%91
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older with a bachelor's degree or higher..

Very Advanced Degrees by County Subdivision#32

Percent of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).
Scope: population of the Brown Township, selected other county subdivisions in the United States, and entities that contain the Brown Township
0%5%10%Count#WashingtonManhattanSan FranciscoBostonAtlantaSeattleSan JoseSeattle EastDenverSan DiegoAustinBaltimoreLos AngelesAlbuquerquePlanoChicagoTucsonTown of HempsteadHempsteadTampaMiamiNortheast DallasNE DallasSalt Lake CitySalt Lk CityHoustonPhiladelphiaSan Fernando ValleySan Fernando VlyTownship 1:Charlotte1, CharlotteOceanside-EscondidoOceanside-Escond…BrooklynSacramentoColumbusUnited States of AmericaUnited StatesTulsaPhoenixLong Beach-LakewoodLong Bch-LakewoodMidwestOrlandoEast North CentralFresnoAnaheim-Santa Ana-Garden GroveAnaheim-Santa An…QueensOhioNorthwest HarrisNW HarrisDayton Metro AreaDayton AreaNortheast TarrantNE TarrantEast San Gabriel ValleyE San Gabriel VlyOntarioFort WorthLas VegasMilwaukeeSan BernardinoSan Antonio CentralSan Antonio CntrlEl PasoSouthwest DallasSW DallasBronxDetroitMiami CountyMiamiMiami East Local School DistrictMiami East390100Tract 390100Brown TownshipBrown12.461852%12.461852%12.5%57,69857.7k110.788423%10.788423%10.8%133,520134k27.558053%7.558053%7.6%50,56350.6k37.340604%7.340604%7.3%32,61132.6k46.889819%6.889819%6.9%26,99527.0k56.641855%6.641855%6.6%49,79049.8k66.255912%6.255912%6.3%75,13475.1k76.036065%6.036065%6.0%24,96825.0k85.725842%5.725842%5.7%26,81226.8k95.247128%5.247128%5.2%83,55883.6k105.058711%5.058711%5.1%28,95529.0k114.934352%4.934352%4.9%20,82420.8k124.659072%4.659072%4.7%81,44181.4k134.631274%4.631274%4.6%20,00420.0k144.617088%4.617088%4.6%16,67916.7k154.485379%4.485379%4.5%82,18982.2k164.461087%4.461087%4.5%25,61425.6k174.441262%4.441262%4.4%23,19423.2k184.325266%4.325266%4.3%19,24719.2k194.025531%4.025531%4.0%27,61827.6k203.827408%3.827408%3.8%38,21138.2k213.792624%3.792624%3.8%23,36723.4k223.737871%3.737871%3.7%77,97878.0k233.720350%3.720350%3.7%38,51538.5k243.601468%3.601468%3.6%45,61045.6k253.490252%3.490252%3.5%18,54218.5k263.466073%3.466073%3.5%15,21115.2k273.384967%3.384967%3.4%59,36259.4k283.380196%3.380196%3.4%25,05825.1k293.357865%3.357865%3.4%17,95418.0k303.336158%3.336158%3.3%7,127,6737.13M3.140490%3.140490%3.1%12,13312.1k313.010825%3.010825%3.0%62,13562.1k323.009440%3.009440%3.0%11,33911.3k332.893416%2.893416%2.9%1,311,0191.31M2.893233%2.893233%2.9%11,37011.4k342.855432%2.855432%2.9%896,039896k2.828959%2.828959%2.8%11,83311.8k352.763004%2.763004%2.8%30,34430.3k362.756960%2.756960%2.8%44,96545.0k372.683241%2.683241%2.7%210,582211k2.682967%2.682967%2.7%12,62112.6k382.681530%2.681530%2.7%14,56814.6k2.630994%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%5,693501.179360%1.179360%1.2%8451.176223%1.176223%1.2%560.948167%0.948167%0.9%300.783875%0.783875%0.8%7
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).

Under-Education Sex Ratio by County Subdivision#33

Percentage more likely men are than women to not have a high school diploma (or equivalent) among people aged 25 years and older.
Scope: population of the Brown Township, selected other county subdivisions in the United States, and entities that contain the Brown Township
Female
Male
1x0x1x2xFM#BrownTract 3901001, CharlotteDetroitBaltimoreTulsaSW DallasMidwestFresnoEast North CentralMilwaukeeUnited StatesOhioNE DallasHoustonHempsteadOrlandoPhiladelphiaOntarioSan BernardinoAustinAtlantaFort WorthPhoenixChicagoAlbuquerqueWashingtonMiami EastSacramentoColumbusSalt Lk CityDenverNE TarrantTampaOceanside-EscondidoOceanside-Escond…NW HarrisBronxPlanoBrooklynSan Antonio CntrlSan Fernando VlyDayton AreaTucsonAnaheim-Santa Ana-Gdn GrvAnaheim-Santa An…Los AngelesLas VegasBostonE San Gabriel VlyQueensMiamiManhattanSeattleLong Bch-LakewoodSeattle EastSan JoseMiamiSan DiegoSan FranciscoEl Paso-1.000000x-1.000000x2.607422x2.607422x2.61x5.393%5.39%14.063%14.1%-1.000000x-1.000000x1.585131x1.585131x1.59x5.426%5.43%8.601%8.60%-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-1.000000x1.099797x1.099797x1.10x19.814%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-1.000000x1.061437x1.061437x1.06x9.165%9.16%9.728%9.73%-1.000000x-1.000000x1.053268x1.053268x1.05x13.558%13.6%14.280%14.3%22-1.000000x-1.000000x1.052237x1.052237x1.05x11.098%11.1%11.678%11.7%23-1.000000x-1.000000x1.051272x1.051272x1.05x10.176%10.2%10.697%10.7%24-1.000000x-1.000000x1.049933x1.049933x1.05x13.307%13.3%13.971%14.0%25-1.000000x-1.000000x1.040742x1.040742x1.04x8.257%8.26%8.594%8.59%26-1.000000x-1.000000x1.040003x1.040003x1.04x12.734%12.7%13.244%13.2%27-1.000000x-1.000000x1.039910x1.039910x1.04x15.694%15.7%16.321%16.3%28-1.000000x-1.000000x1.038394x1.038394x1.04x9.953%9.95%10.335%10.3%29-1.000000x-1.000000x1.030539x1.030539x1.03x28.448%28.4%29.316%29.3%30-1.000000x-1.000000x1.023151x1.023151x1.02x5.652%5.65%5.783%5.78%31-1.000000x-1.000000x1.018960x1.018960x1.02x19.845%19.8%20.221%20.2%32-1.000000x-1.000000x1.003929x1.003929x1.00x28.944%28.9%29.058%29.1%33-1.000000x-1.000000x1.003840x1.003840x1.00x19.308%19.3%19.383%19.4%34-1.000000x-1.000000x1.000795x1.000795x1.00x9.840%9.84%9.848%9.85%-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%47-1.131015x-1.131015x1.13x1.000000x1.000000x11.559%11.6%10.220%10.2%-1.168454x-1.168454x1.17x1.000000x1.000000x13.975%14.0%11.960%12.0%48-1.228758x-1.228758x1.23x1.000000x1.000000x13.883%13.9%11.298%11.3%49-1.276282x-1.276282x1.28x1.000000x1.000000x26.394%26.4%20.680%20.7%50
F percentage of females in category
M percentage of males in category
# rank of county subdivision out of 50 by male-to-female sex ratio

Over-Education Sex Ratio by County Subdivision#34

Percentage more likely men are than women to have a professional or doctorate degree (e.g., MBA, PhD, or MD) among people aged 25 years and older.
Scope: population of the Brown Township, selected other county subdivisions in the United States, and entities that contain the Brown Township
Female
Male
0x5x10xFM#BrownMiamiDayton AreaEl PasoSalt Lk CityPlanoMiami EastTulsaAlbuquerqueNE DallasFort WorthOhioOrlandoPhoenixTucson1, CharlotteEast North CentralMidwestNW HarrisLas VegasSeattle EastSan Antonio CntrlSan DiegoUnited StatesSan JoseHempsteadFresnoNE TarrantTampaSan Fernando VlyE San Gabriel VlyHoustonSan BernardinoColumbusMiamiAtlantaMilwaukeeAnaheim-Santa Ana-Gdn GrvAnaheim-Santa An…SacramentoPhiladelphiaOceanside-EscondidoOceanside-Escond…Los AngelesAustinBaltimoreWashingtonQueensSW DallasBrooklynTract 390100ManhattanChicagoSeattleBostonBronxOntarioLong Bch-LakewoodDenverSan FranciscoDetroit-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%1.563%1.56%-1.000000x-1.000000x3.501312x3.501312x3.50x0.534%0.53%1.871%1.87%-1.000000x-1.000000x2.159743x2.159743x2.16x1.731%1.73%3.739%3.74%-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-1.000000x1.732481x1.732481x1.73x0.857%0.86%1.484%1.48%-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-1.000000x1.557664x1.557664x1.56x4.733%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-1.000000x1.252666x1.252666x1.25x0.840%0.84%1.052%1.05%-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:
Miami
Metro Area:
Dayton Area
Village:
Fletcher
ZIP Codes:
45317, 45326, 45356
Unified School District:
Miami East
Congressional District:
OH-8
State Senate District:
OH-5
State House District:
OH-80
Neighboring Townships:
Green, Jackson, Johnson, Lostcreek, Orange, Springcreek, Staunton
Nearby Townships:
Adams, Clinton, Concord, Concord, Elizabeth, Perry, Pike, Washington, Washington