Educational Attainment in Oakwood, Montgomery County, Ohio (City)

Educational Attainment#1

Highest level of education among people aged 25 years and older.
Scope: population of Montgomery County and Oakwood
Oakwood
Montgomery County
0%20%40%60%CountHigher Degree1H.S. Diploma2No H.S. Diploma275.926533%35.923972%75.926533%75.9%4,63022.351591%53.706396%22.351591%22.4%1,3631.721876%10.369633%1.721876%1.7%105
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 Montgomery County at large.
Scope: population of Montgomery County and Oakwood
-100%0%+100%%ref.Higher Degree1H.S. Diploma2No H.S. Diploma2111.353394%111.353394%+111.4%75.927%75.9%35.924%35.9%-58.381883%-58.381883%-58.4%22.352%22.4%53.706%53.7%-83.395014%-83.395014%-83.4%1.722%1.72%10.370%10.4%
% percentage with given level in Oakwood
ref. percentage with given level in Montgomery 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 Montgomery County and Oakwood
Oakwood
Montgomery County
0%5%10%15%20%25%30%CountDoctorate1Professional1Master's1Bachelor's1Associate's1Some CollegeHigh School2Some H.S.3Less than H.S.3None5.149229%0.994624%5.149229%5.1%31410.610036%1.450287%10.610036%10.6%64721.515251%8.013813%21.515251%21.5%1,31233.306002%15.684501%33.306002%33.3%2,0315.346015%9.780747%5.346015%5.3%32615.300098%25.334782%15.300098%15.3%9337.051492%28.371613%7.051492%7.1%4301.082322%7.580217%1.082322%1.1%660.639554%1.992007%0.639554%0.6%390.000000%0.000000%0.0%0.797409%0
Count number of people in category
1Degree 2Diploma or equivialent 3H.S. = High School

Detailed Relative Educational Attainment#4

Highest level of education among people aged 25 years and older, as percentage more or less than Montgomery County at large.
Scope: population of Montgomery County and Oakwood
-500%0%+500%%ref.Doctorate1Professional1Master's1Bachelor's1Associate's1Some CollegeHigh School2Some H.S.3Less than H.S.3None417.706023%417.706023%+417.7%5.149%5.15%0.995%0.99%631.581965%631.581965%+631.6%10.610%10.6%1.450%1.45%168.477067%168.477067%+168.5%21.515%21.5%8.014%8.01%112.349777%112.349777%+112.3%33.306%33.3%15.685%15.7%-45.341443%-45.341443%-45.3%5.346%5.35%9.781%9.78%-39.608329%-39.608329%-39.6%15.300%15.3%25.335%25.3%-75.145959%-75.145959%-75.1%7.051%7.05%28.372%28.4%-85.721753%-85.721753%-85.7%1.082%1.08%7.580%7.58%-67.893984%-67.893984%-67.9%0.640%0.64%1.992%1.99%-100.000000%-100.000000%-100.0%0.000%0%0.797%0.80%
% percentage with given level in Oakwood
ref. percentage with given level in Montgomery 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 Montgomery County and Oakwood
More Females More Males
Montgomery County
Oakwood
40%20%0%FMHigher Degree1H.S. Diploma2No H.S. Diploma2-2.101518%13.610906%13.610906%14%71.510%71.5%81.243%81.2%-57.829481%-57.829481%58%0.689994%26.809%26.8%16.986%17.0%5.335201%3.700935%5.335201%5%1.681%1.68%1.771%1.77%
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 Montgomery County and Oakwood
More Females More Males
Montgomery County
Oakwood
200%0%200%FMDoctorate1Professional1Master's1Bachelor's1Associate's1Some CollegeHigh School2Some H.S.3Less than H.S.3270.529759%154.434915%270.529759%271%2.312%2.31%8.565%8.57%55.814988%91.979239%55.814988%56%8.466%8.47%13.191%13.2%-10.707514%27.175862%27.175862%27%19.153%19.2%24.359%24.4%-27.033232%-27.033232%27%4.698319%36.866%36.9%29.021%29.0%-29.294695%29.584341%29.584341%30%4.713%4.71%6.108%6.11%-7.824911%-2.789340%-7.824911%8%15.821%15.8%14.673%14.7%-375.045970%-375.045970%375%3.823603%10.988%11.0%2.313%2.31%-78.003174%-78.003174%78%3.815935%1.351%1.35%0.759%0.76%206.429674%5.912297%206.429674%206%0.330%0.33%1.012%1.01%
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 Montgomery County and Oakwood
Oakwood
Montgomery County
0%10%20%30%B.X.Total65+45-6435-4425-3439.792899%12.214499%39.792899%39.8%5381,35232.940743%15.478148%32.940743%32.9%8952,71734.419382%17.523909%34.419382%34.4%4121,19722.355769%18.903429%22.355769%22.4%186832
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 Montgomery County at large.
Scope: population of Montgomery County and Oakwood
0%50%100%150%200%%ref.65+45-6435-4425-34225.784144%225.784144%225.8%39.793%39.8%12.214%12.2%112.820966%112.820966%112.8%32.941%32.9%15.478%15.5%96.413837%96.413837%96.4%34.419%34.4%17.524%17.5%18.263038%18.263038%18.3%22.356%22.4%18.903%18.9%
% percentage in Oakwood with a Bachelor's degree
ref percentage in Montgomery 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 Montgomery County and Oakwood
More Females More Males
Montgomery County
Oakwood
40%20%0%20%40%FM65+45-6435-4425-342.497205%48.018831%2.497205%2.5%39.335%39.3%40.317%40.3%-43.478261%-43.478261%43.5%2.133245%38.462%38.5%26.807%26.8%-39.119751%-19.093409%-39.119751%39.1%38.897%38.9%27.959%28.0%-35.466734%-8.640759%-35.466734%35.5%25.212%25.2%18.611%18.6%
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 Montgomery County and Oakwood
Oakwood
Montgomery County
$0k$20k$40k$60k$80kCount%Graduate Degree1Bachelor's DegreeSome CollegeH.S. Diploma2Total$88,910.000000$64,295.000000$88,910.000000$88.9k2,27337.275%37.3%$64,155.000000$46,659.000000$64,155.000000$64.2k2,03133.306%33.3%$34,055.000000$31,290.000000$34,055.000000$34.1k1,25920.646%20.6%$25,521.000000$26,078.000000$25,521.000000$25.5k4307.051%7.05%$66,000.000000$33,622.000000$66,000.000000$66.0k6,098100.000%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 Montgomery County and Oakwood
Female Male
Montgomery County
Oakwood
Shaded bar tips show excess over facing bar.
$50k$0k$50k$100kFMGraduate Degree1Bachelor's DegreeSome CollegeTotal$-76,982.000000$-56,381.000000$-76,982.000000$77.0k$76,982.000000$31,576.000000$56,381.000000$20,933.000000$108,558.000000$108.6k9971,276$-33,986.000000$-40,185.000000$-33,986.000000$34.0k$33,986.000000$57,108.000000$40,185.000000$14,888.000000$91,094.000000$91.1k1,228803$-33,583.000000$-26,764.000000$-33,583.000000$33.6k$33,583.000000$1,605.000000$26,764.000000$10,727.000000$35,188.000000$35.2k684575$-50,110.000000$-28,928.000000$-50,110.000000$50.1k$50,110.000000$32,871.000000$28,928.000000$11,556.000000$82,981.000000$83.0k3,3312,767
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

Composition of the Armed Forces by Educational Attainment#12

Percentage of the armed forces aged 25 to 64 years old with various highest levels of educational attainment.
Scope: population of Montgomery County and Oakwood
Oakwood
Montgomery County
0%20%40%60%80%100%CountBachelor's Degree1Some College2H.S. Diploma3No H.S. Diploma3100.000000%54.139194%100.000000%100.0%1100.000000%0.000000%0.0%41.831502%00.000000%0.000000%0.0%2.344322%00.000000%0.000000%0.0%1.684982%0
Count members of the armed forces with the given level of educational attainment
1or higher 2two or four year institution 3H.S. = High School

Employment by Educational Attainment#13

Percentage of population that is employed by highest level of educational attainment among the population aged 25 to 64 years old.
Scope: population of Montgomery County and Oakwood
Oakwood
Montgomery County
0%20%40%60%80%CountBachelor's Degree1Some College2H.S. Diploma3No H.S. Diploma385.163205%84.147917%85.163205%85.2%2,87073.459245%73.184747%73.459245%73.5%73966.431095%64.520690%66.431095%66.4%18817.241379%40.774995%17.241379%17.2%15
Count employed people with given educational attainment aged 25 to 64 years old
1or higher 2two or four year institution 3H.S. = High School

Lacking High School Diploma By Race#14

Percent of racial or ethnic group lacking a high school diploma (or equivalent).
Scope: population of Montgomery County and Oakwood
Female Male
Montgomery County
Oakwood
Shaded bar tips show excess over facing bar.
10%0%10%20%30%40%MFWhite1AsianHispanic2Other1-1.244344%-0.363475%-8.957880%-1.607818%1.6%1.244344%8.957880%0.144171%1.244344%1.2%3351-0.000000%-11.156123%-6.490935%0.000000%0.0%0.000000%0.000000%11.156123%0.000000%0.0%00-0.000000%-9.803922%-19.697834%-9.803922%9.8%0.000000%19.697834%6.828186%0.000000%0.0%05-0.000000%-9.596879%0.000000%0.0%0.000000%44.444444%9.596879%5.938404%44.444444%44.4%160
M number of males in category
F number of females in category
1non-Hispanic 2excluding black and Asian Hispanics

College Graduates By Race#15

Percent of racial or ethnic group with a bachelor's degree or higher.
Scope: population of Montgomery County and Oakwood
Female Male
Montgomery County
Oakwood
Shaded bar tips show excess over facing bar.
100%50%0%50%100%MFWhite1AsianHispanic2Other1-65.636822%-26.972031%-65.636822%65.6%65.636822%9.212348%26.972031%1.706094%74.849170%74.8%1,9852,082-94.117647%-45.328720%-94.117647%94.1%94.117647%5.882353%45.328720%21.047098%100.000000%100.0%1464-76.470588%-18.272520%-76.470588%76.5%76.470588%15.837104%18.272520%4.596678%92.307692%92.3%6039-55.555556%-44.444444%-23.302991%-100.000000%100.0%55.555556%23.302991%0.120674%55.555556%55.6%2040
M number of males in category
F number of females in category
1non-Hispanic 2excluding black and Asian Hispanics

Educational Attainment by Neighborhood in Oakwood

There is 1 neighborhood that are fully or partially contained within Oakwood (0 fully and 1 partially). This section compares all 1 of those to each other, Oakwood, and other entities that contain or substantially overlap with Oakwood.

No H.S. Diploma by Neighborhood#16

Percent of population 25 years of age and older without a high school diploma (or equivalent).
Scope: population of Oakwood, selected neighborhoods in Oakwood, and entities that contain Oakwood
0%5%10%15%Count#University Park NeighborhoodUniv PkUnited States of AmericaUnited StatesEast North CentralOhioMontgomery CountyMontgomeryMidwestDayton Metro AreaDayton AreaOakwoodOakwood15.267523%15.267523%15.3%7273113.020590%13.020590%13.0%27,818,38027.8M10.719464%10.719464%10.7%3,363,7843.36M10.514146%10.514146%10.5%825,155825k10.369633%10.369633%10.4%37,59537.6k10.244520%10.244520%10.2%4,641,8354.64M9.844056%9.844056%9.8%53,48053.5k1.721876%1.721876%1.7%1051.721876%1.721876%1.7%105
Count number of people in category
# rank of neighborhood out of 1 by percentage of population 25 years of age and older without a high school diploma (or equivalent).

Bachelor's Degrees by Neighborhood#17

Percent of population 25 years of age and older with a bachelor's degree or higher..
Scope: population of Oakwood, selected neighborhoods in Oakwood, and entities that contain Oakwood
0%20%40%60%Count#OakwoodOakwoodUniversity Park NeighborhoodUniv PkUnited States of AmericaUnited StatesMidwestEast North CentralDayton Metro AreaDayton AreaOhioMontgomery CountyMontgomery70.580518%70.580518%70.6%4,30470.580518%70.580518%70.6%4,30434.072146%34.072146%34.1%162130.315023%30.315023%30.3%64,767,78764.8M28.952816%28.952816%29.0%13,118,64213.1M28.462853%28.462853%28.5%8,931,6868.93M27.783136%27.783136%27.8%150,938151k26.667466%26.667466%26.7%2,092,8752.09M26.143225%26.143225%26.1%94,78294.8k
Count number of people in category
# rank of neighborhood out of 1 by percentage of population 25 years of age and older with a bachelor's degree or higher..

Very Advanced Degrees by Neighborhood#18

Percent of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).
Scope: population of Oakwood, selected neighborhoods in Oakwood, and entities that contain Oakwood
0%5%10%15%Count#OakwoodOakwoodUniversity Park NeighborhoodUniv PkUnited States of AmericaUnited StatesMidwestEast North CentralOhioDayton Metro AreaDayton AreaMontgomery CountyMontgomery15.759265%15.759265%15.8%96115.759265%15.759265%15.8%9614.831839%4.831839%4.8%222313.336158%3.336158%3.3%7,127,6737.13M2.893416%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%14,56814.6k2.444911%2.444911%2.4%8,864
Count number of people in category
# rank of neighborhood out of 1 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 Neighborhood#19

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 Oakwood, selected neighborhoods in Oakwood, and entities that contain Oakwood
Female
Male
1.0x0.5x0.0x0.5x1.0xFM#MidwestEast North CentralUnited StatesOhioUniv PkOakwoodOakwoodMontgomeryDayton Area-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-1.000000x1.109070x1.109070x1.11x12.369%12.4%13.719%13.7%-1.000000x-1.000000x1.105363x1.105363x1.11x10.008%10.0%11.063%11.1%-1.000000x-1.000000x1.092836x1.092836x1.09x14.413%14.4%15.751%15.8%1-1.000000x-1.000000x1.053352x1.053352x1.05x1.681%1.68%1.771%1.77%-1.000000x-1.000000x1.053352x1.053352x1.05x1.681%1.68%1.771%1.77%-1.000000x-1.000000x1.037009x1.037009x1.04x10.193%10.2%10.570%10.6%-1.000000x-1.000000x1.000795x1.000795x1.00x9.840%9.84%9.848%9.85%
F percentage of females in category
M percentage of males in category
# rank of neighborhood out of 1 by male-to-female sex ratio

Over-Education Sex Ratio by Neighborhood#20

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 Oakwood, selected neighborhoods in Oakwood, and entities that contain Oakwood
Female
Male
1x0x1x2xFM#Dayton AreaMontgomeryOakwoodOakwoodOhioEast North CentralMidwestUnited StatesUniv Pk-1.000000x-1.000000x2.159743x2.159743x2.16x1.731%1.73%3.739%3.74%-1.000000x-1.000000x2.146385x2.146385x2.15x1.591%1.59%3.414%3.41%-1.000000x-1.000000x2.018680x2.018680x2.02x10.778%10.8%21.756%21.8%-1.000000x-1.000000x2.018680x2.018680x2.02x10.778%10.8%21.756%21.8%-1.000000x-1.000000x1.669500x1.669500x1.67x2.031%2.03%3.391%3.39%-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-1.000000x1.526215x1.526215x1.53x2.660%2.66%4.060%4.06%-1.201638x-1.201638x1.20x1.000000x1.000000x5.412%5.41%4.503%4.50%1
F percentage of females in category
M percentage of males in category
# rank of neighborhood out of 1 by male-to-female sex ratio

Educational Attainment by County Subdivision in the Dayton Area

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

No H.S. Diploma by County Subdivision#21

Percent of population 25 years of age and older without a high school diploma (or equivalent).
Scope: population of Oakwood, selected other county subdivisions in the Dayton Area, and entities that contain Oakwood
0%5%10%15%Count#Harrison TownshipHarrisonDaytonJefferson TownshipJeffersonRoss TownshipBethel TownshipBethelPiquaMoraineTrotwoodUnion TownshipUnionRiversideUnited States of AmericaUnited StatesNewton TownshipNewtonBath TownshipXeniaStaunton TownshipStauntonNewberry TownshipNewberryJefferson TownshipJeffersonSilvercreek TownshipSilvercreekEast North CentralPerry TownshipPerryOhioJackson TownshipJacksonWest CarrolltonW CarrolltonMontgomery CountyMontgomeryConcord TownshipConcordMidwestDayton Metro AreaDayton AreaBrown TownshipBrownVandaliaNew Jasper TownshipNew JasperXenia TownshipXeniaMiami TownshipMiamiElizabeth TownshipElizabethGerman TownshipGermanHuber HeightsClay TownshipCaesarscreek TownshipCaesarscreekMonroe TownshipMonroeEnglewoodWashington TownshipWashingtonSpringcreek TownshipSpringcreekKetteringButler TownshipButlerSpring Valley TownshipSpg VlyClaytonUnion City TownshipUnion CityMiami TownshipMiamiCedarville TownshipCedarvilleLostcreek TownshipLostcreekWashington TownshipWashingtonBellbrookBeavercreek TownshipBeavercreekHuber HeightsSugarcreek TownshipSugarcreekOakwoodOakwoodKettering16.956522%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%2991710.719464%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%9462010.369633%10.369633%10.4%37,59537.6k10.356923%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%1,034239.394572%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%58316.896868%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%1051.721876%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#22

Percent of population 25 years of age and older with a bachelor's degree or higher..
Scope: population of Oakwood, selected other county subdivisions in the Dayton Area, and entities that contain Oakwood
0%20%40%60%Count#OakwoodOakwoodKetteringSugarcreek 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 TownshipElizabethMontgomery CountyMontgomeryNew Jasper TownshipNew JasperVandaliaGerman TownshipGermanHuber HeightsCaesarscreek TownshipCaesarscreekClay TownshipBethel TownshipBethelXeniaSpringcreek TownshipSpringcreekLostcreek TownshipLostcreekRiversideDaytonUnion City TownshipUnion CityUnion TownshipUnionRoss TownshipTrotwoodSilvercreek TownshipSilvercreekJefferson TownshipJeffersonWest CarrolltonW CarrolltonMoraineHarrison TownshipHarrisonJackson TownshipJacksonPerry TownshipPerryJefferson TownshipJeffersonNewton TownshipNewtonPiquaBrown TownshipBrownNewberry TownshipNewberry70.580518%70.580518%70.6%4,30470.580518%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%3002226.143225%26.143225%26.1%94,78294.8k24.686848%24.686848%24.7%4732323.818824%23.818824%23.8%2,5612423.426009%23.426009%23.4%1,3062522.834168%22.834168%22.8%5,6512620.487805%20.487805%20.5%1682719.784063%19.784063%19.8%1,3012819.714517%19.714517%19.7%7322919.468676%19.468676%19.5%3,4373018.741355%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#23

Percent of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).
Scope: population of Oakwood, selected other county subdivisions in the Dayton Area, and entities that contain Oakwood
0%5%10%15%Count#OakwoodOakwoodMiami TownshipMiamiKetteringSugarcreek TownshipSugarcreekWashington TownshipWashingtonBeavercreek TownshipBeavercreekXenia TownshipXeniaKetteringCedarville TownshipCedarvilleBellbrookUnited States of AmericaUnited StatesWashington TownshipWashingtonButler TownshipButlerMidwestClaytonEast North CentralGerman TownshipGermanOhioDayton Metro AreaDayton AreaSpring Valley TownshipSpg VlyBath TownshipMontgomery CountyMontgomeryNew Jasper TownshipNew JasperJefferson TownshipJeffersonLostcreek TownshipLostcreekStaunton TownshipStauntonMiami TownshipMiamiMonroe TownshipMonroeConcord TownshipConcordSpringcreek TownshipSpringcreekRoss TownshipXeniaVandaliaJackson TownshipJacksonHuber HeightsDaytonNewton TownshipNewtonEnglewoodRiversideUnion TownshipUnionBethel TownshipBethelPerry TownshipPerryCaesarscreek TownshipCaesarscreekClay TownshipMoraineBrown TownshipBrownHarrison TownshipHarrisonJefferson TownshipJeffersonTrotwoodUnion City TownshipUnion CityPiquaSilvercreek TownshipSilvercreekWest CarrolltonW CarrolltonNewberry TownshipNewberryHuber HeightsElizabeth TownshipElizabeth15.759265%15.759265%15.8%96115.759265%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%605162.444911%2.444911%2.4%8,8642.087683%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%1,106301.166667%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%8370.821168%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#24

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 Oakwood, selected other county subdivisions in the Dayton Area, and entities that contain Oakwood
Female
Male
0x2x4xFM#LostcreekWashingtonBrownUnion CityJeffersonMiamiEnglewoodSpringcreekBellbrookBeavercreekHarrisonTrotwoodClay TownshipClaytonXeniaPerryMidwestEast North CentralDaytonUnited StatesOhioNew JasperPiquaRiversideOakwoodOakwoodVandaliaSilvercreekButlerMontgomeryHuber HeightsNewberryDayton AreaStauntonGermanXeniaMonroeBethelCedarvilleMiamiJacksonHuber 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-1.000000x1.393347x1.393347x1.39x5.021%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-1.000000x1.053352x1.053352x1.05x1.681%1.68%1.771%1.77%-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-1.000000x1.037009x1.037009x1.04x10.193%10.2%10.570%10.6%-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%34-1.167707x-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#25

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 Oakwood, selected other county subdivisions in the Dayton Area, and entities that contain Oakwood
Female
Male
10x5x0x5x10xFM#PiquaNewberryBethelSpringcreekBrownKetteringUnionXeniaButlerHarrisonSugarcreekConcordJacksonWashingtonNewtonSilvercreekGermanStauntonClaytonMonroeDayton AreaKetteringMontgomeryXeniaOakwoodOakwoodBeavercreekJeffersonDaytonW CarrolltonEnglewoodMiamiBath TownshipSpg VlyOhioHuber HeightsUnion CityEast North CentralMidwestTrotwoodUnited StatesRiversideVandaliaCedarvilleMiamiWashingtonLostcreekBellbrookNew 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-1.000000x3.370909x3.370909x3.37x3.955%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-1.000000x2.146385x2.146385x2.15x1.591%1.59%3.414%3.41%-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%-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-1.000000x1.691857x1.691857x1.69x1.833%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-1.000000x1.246667x1.246667x1.25x1.577%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 Oakwood to the 50 most populous county subdivisions in Ohio and to those entities that contain or substantially overlap with Oakwood. The least populous of the compared county subdivisions has a population of 36,945.

No H.S. Diploma by County Subdivision#26

Percent of population 25 years of age and older without a high school diploma (or equivalent).
Scope: population of Oakwood, selected other county subdivisions in Ohio, and entities that contain Oakwood
0%5%10%15%20%Count#ClevelandMiddletownLorainYoungstownSpringfieldDaytonMansfieldLimaMarion TownshipMarionCantonHamiltonWarrenToledoCincinnatiAkronElyriaUnited States of AmericaUnited StatesNewarkBath TownshipLancaster City TownshipLancaster CityColumbusColerain TownshipColerainEast North CentralEuclidOhioMontgomery CountyMontgomeryMidwestParmaDayton Metro AreaDayton AreaFindlayFairfieldMiami TownshipMiamiUnion TownshipUnionHuber HeightsJackson TownshipJacksonCleveland HeightsCleveland HtsCuyahoga FallsPlain TownshipPlainLakewoodKetteringGreen TownshipGrnBoardman TownshipBoardmanWest Chester TownshipW ChesterMiami TownshipMiamiMifflin TownshipMifflinMentorLiberty TownshipLibertySylvania TownshipSylvaniaStrongsvilleViolet TownshipVioletJackson TownshipJacksonWashington TownshipWashingtonAnderson TownshipAndersonDeerfield TownshipDeerfieldBeavercreek TownshipBeavercreekDublinOakwoodOakwood21.582420%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%60,83160.8k2010.847918%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%825,155825k10.369633%10.369633%10.4%37,59537.6k10.244520%10.244520%10.2%4,641,8354.64M9.939137%9.939137%9.9%5,683239.844056%9.844056%9.8%53,48053.5k9.003845%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%1,797286.480864%6.480864%6.5%1,944296.307136%6.307136%6.3%1,918306.197364%6.197364%6.2%2,215316.171554%6.171554%6.2%2,311326.109570%6.109570%6.1%2,246335.953744%5.953744%6.0%2,340345.804316%5.804316%5.8%2,402355.764815%5.764815%5.8%1,682365.727981%5.727981%5.7%2,390375.628396%5.628396%5.6%1,554385.595517%5.595517%5.6%1,408395.268752%5.268752%5.3%1,834405.136204%5.136204%5.1%1,169414.322119%4.322119%4.3%1,462424.066023%4.066023%4.1%1,313433.979966%3.979966%4.0%1,041443.830735%3.830735%3.8%1,118453.637690%3.637690%3.6%1,496463.351036%3.351036%3.4%978473.293195%3.293195%3.3%815483.105178%3.105178%3.1%1,170491.754602%1.754602%1.8%428501.721876%1.721876%1.7%1051.721876%1.721876%1.7%105
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#27

Percent of population 25 years of age and older with a bachelor's degree or higher..
Scope: population of Oakwood, selected other county subdivisions in Ohio, and entities that contain Oakwood
0%20%40%60%Count#DublinOakwoodOakwoodDeerfield 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 TownshipMiamiOhioMontgomery CountyMontgomeryHuber HeightsColerain TownshipColerainEuclidAkronParmaNewarkToledoDaytonMiddletownLancaster City TownshipLancaster CityClevelandElyriaHamiltonSpringfieldCantonMansfieldWarrenYoungstownLorainLimaMarion TownshipMarion75.246997%75.246997%75.2%18,35518.4k170.580518%70.580518%70.6%4,30470.580518%70.580518%70.6%4,30457.851139%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%2,092,8752.09M26.143225%26.143225%26.1%94,78294.8k22.834168%22.834168%22.8%5,6513021.665661%21.665661%21.7%8,6163120.614221%20.614221%20.6%6,8133220.213821%20.213821%20.2%26,69726.7k3319.988457%19.988457%20.0%11,42911.4k3418.053148%18.053148%18.1%5,7273518.048021%18.048021%18.0%33,17133.2k3617.635555%17.635555%17.6%15,51115.5k3716.631922%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%3,24550
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older with a bachelor's degree or higher..

Very Advanced Degrees by County Subdivision#28

Percent of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).
Scope: population of Oakwood, selected other county subdivisions in Ohio, and entities that contain Oakwood
0%5%10%15%Count#OakwoodOakwoodCleveland 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 TownshipMontgomery CountyMontgomeryAkronJackson TownshipJacksonClevelandMentorColerain TownshipColerainMiami TownshipMiamiFindlayToledoSpringfieldFairfieldEuclidHuber HeightsLimaDaytonCantonHamiltonUnion TownshipUnionParmaNewarkLancaster City TownshipLancaster CityMansfieldMiddletownLorainElyriaYoungstownWarrenMarion TownshipMarion15.759265%15.759265%15.8%96115.759265%15.759265%15.8%96110.753042%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%605232.444911%2.444911%2.4%8,8642.163955%2.163955%2.2%2,858242.063608%2.063608%2.1%619251.927780%1.927780%1.9%4,911261.815622%1.815622%1.8%632271.815530%1.815530%1.8%722281.762090%1.762090%1.8%630291.675978%1.675978%1.7%462301.642065%1.642065%1.6%3,018311.545396%1.545396%1.5%600321.477698%1.477698%1.5%434331.388805%1.388805%1.4%459341.349604%1.349604%1.3%334351.304159%1.304159%1.3%301361.257490%1.257490%1.3%1,106371.245933%1.245933%1.2%582381.241352%1.241352%1.2%506391.238390%1.238390%1.2%400401.236490%1.236490%1.2%707411.182108%1.182108%1.2%375421.159205%1.159205%1.2%312431.104887%1.104887%1.1%359440.996743%0.996743%1.0%306450.964372%0.964372%1.0%396460.952302%0.952302%1.0%343470.794541%0.794541%0.8%347480.742101%0.742101%0.7%202490.720098%0.720098%0.7%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#29

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 Oakwood, selected other county subdivisions in Ohio, and entities that contain Oakwood
Female
Male
1x0x1xFM#AndersonMansfieldCleveland HtsBeavercreekUnionToledoFindlayLorainMarionYoungstownColerainGrnFairfieldElyriaMiddletownLancaster CityMidwestEast North CentralSpringfieldWarrenDaytonCantonUnited StatesOhioLimaParmaOakwoodOakwoodColumbusClevelandDeerfieldMentorMontgomeryNewarkW ChesterPlainLibertyJacksonHuber HeightsHamiltonJacksonCincinnatiDayton AreaAkronMifflinSylvaniaMiamiEuclidMiamiCuyahoga FallsStrongsvilleLakewoodBath TownshipDublinKetteringWashingtonBoardmanViolet-1.000000x-1.000000x1.766803x1.766803x1.77x2.468%2.47%4.360%4.36%1-1.000000x-1.000000x1.592708x1.592708x1.59x12.530%12.5%19.956%20.0%2-1.000000x-1.000000x1.485471x1.485471x1.49x5.146%5.15%7.645%7.64%3-1.000000x-1.000000x1.332397x1.332397x1.33x2.666%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-1.000000x1.053352x1.053352x1.05x1.681%1.68%1.771%1.77%-1.000000x-1.000000x1.053352x1.053352x1.05x1.681%1.68%1.771%1.77%-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-1.000000x1.037009x1.037009x1.04x10.193%10.2%10.570%10.6%-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%41-1.132510x-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#30

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 Oakwood, selected other county subdivisions in Ohio, and entities that contain Oakwood
Female
Male
1x0x1x2x3xFM#ElyriaSpringfieldWashingtonYoungstownBoardmanLorainMiddletownLancaster CityFindlayAndersonJacksonDayton AreaKetteringMontgomeryMifflinPlainOakwoodOakwoodBeavercreekDeerfieldDaytonNewarkEuclidMiamiAkronDublinSylvaniaStrongsvilleBath TownshipOhioFairfieldMansfieldW ChesterHuber HeightsLakewoodEast North CentralMidwestWarrenUnited StatesLibertyParmaCleveland HtsColumbusUnionMentorGrnJacksonClevelandCincinnatiMiamiMarionVioletColerainToledoHamiltonCantonCuyahoga FallsLima-1.000000x-1.000000x3.557903x3.557903x3.56x0.433%0.43%1.542%1.54%1-1.000000x-1.000000x3.025650x3.025650x3.03x0.799%0.80%2.417%2.42%2-1.000000x-1.000000x2.977263x2.977263x2.98x3.534%3.53%10.523%10.5%3-1.000000x-1.000000x2.809581x2.809581x2.81x0.426%0.43%1.196%1.20%4-1.000000x-1.000000x2.780060x2.780060x2.78x1.621%1.62%4.507%4.51%5-1.000000x-1.000000x2.695011x2.695011x2.70x0.546%0.55%1.472%1.47%6-1.000000x-1.000000x2.596948x2.596948x2.60x0.564%0.56%1.465%1.46%7-1.000000x-1.000000x2.442537x2.442537x2.44x0.692%0.69%1.690%1.69%8-1.000000x-1.000000x2.437656x2.437656x2.44x0.991%0.99%2.417%2.42%9-1.000000x-1.000000x2.428350x2.428350x2.43x4.486%4.49%10.893%10.9%10-1.000000x-1.000000x2.183841x2.183841x2.18x3.386%3.39%7.394%7.39%11-1.000000x-1.000000x2.159743x2.159743x2.16x1.731%1.73%3.739%3.74%-1.000000x-1.000000x2.155653x2.155653x2.16x2.468%2.47%5.319%5.32%12-1.000000x-1.000000x2.146385x2.146385x2.15x1.591%1.59%3.414%3.41%-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-1.000000x2.018680x2.018680x2.02x10.778%10.8%21.756%21.8%-1.000000x-1.000000x2.018680x2.018680x2.02x10.778%10.8%21.756%21.8%-1.000000x-1.000000x2.007898x2.007898x2.01x4.457%4.46%8.948%8.95%15-1.000000x-1.000000x1.991550x1.991550x1.99x2.826%2.83%5.628%5.63%16-1.000000x-1.000000x1.989047x1.989047x1.99x0.860%0.86%1.711%1.71%17-1.000000x-1.000000x1.967904x1.967904x1.97x0.822%0.82%1.618%1.62%18-1.000000x-1.000000x1.903271x1.903271x1.90x0.997%1.00%1.897%1.90%19-1.000000x-1.000000x1.851159x1.851159x1.85x2.056%2.06%3.806%3.81%20-1.000000x-1.000000x1.846298x1.846298x1.85x1.550%1.55%2.862%2.86%21-1.000000x-1.000000x1.832511x1.832511x1.83x7.149%7.15%13.100%13.1%22-1.000000x-1.000000x1.805502x1.805502x1.81x5.447%5.45%9.835%9.84%23-1.000000x-1.000000x1.769961x1.769961x1.77x3.331%3.33%5.895%5.90%24-1.000000x-1.000000x1.691857x1.691857x1.69x1.833%1.83%3.102%3.10%25-1.000000x-1.000000x1.669500x1.669500x1.67x2.031%2.03%3.391%3.39%-1.000000x-1.000000x1.650680x1.650680x1.65x1.122%1.12%1.852%1.85%26-1.000000x-1.000000x1.650301x1.650301x1.65x0.820%0.82%1.353%1.35%27-1.000000x-1.000000x1.648570x1.648570x1.65x3.124%3.12%5.150%5.15%28-1.000000x-1.000000x1.627164x1.627164x1.63x1.044%1.04%1.699%1.70%29-1.000000x-1.000000x1.624128x1.624128x1.62x3.883%3.88%6.306%6.31%30-1.000000x-1.000000x1.597848x1.597848x1.60x2.216%2.22%3.541%3.54%-1.000000x-1.000000x1.589934x1.589934x1.59x2.251%2.25%3.579%3.58%-1.000000x-1.000000x1.543502x1.543502x1.54x0.592%0.59%0.914%0.91%31-1.000000x-1.000000x1.526215x1.526215x1.53x2.660%2.66%4.060%4.06%-1.000000x-1.000000x1.525512x1.525512x1.53x2.801%2.80%4.272%4.27%32-1.000000x-1.000000x1.433883x1.433883x1.43x1.025%1.03%1.470%1.47%33-1.000000x-1.000000x1.416609x1.416609x1.42x9.009%9.01%12.763%12.8%34-1.000000x-1.000000x1.413654x1.413654x1.41x2.801%2.80%3.959%3.96%35-1.000000x-1.000000x1.348352x1.348352x1.35x1.062%1.06%1.431%1.43%36-1.000000x-1.000000x1.325696x1.325696x1.33x1.576%1.58%2.089%2.09%37-1.000000x-1.000000x1.319751x1.319751x1.32x2.156%2.16%2.845%2.85%38-1.000000x-1.000000x1.297270x1.297270x1.30x1.812%1.81%2.351%2.35%39-1.000000x-1.000000x1.286599x1.286599x1.29x1.699%1.70%2.186%2.19%40-1.000000x-1.000000x1.280610x1.280610x1.28x4.179%4.18%5.351%5.35%41-1.000000x-1.000000x1.246667x1.246667x1.25x1.577%1.58%1.966%1.97%42-1.000000x-1.000000x1.217109x1.217109x1.22x0.642%0.64%0.782%0.78%43-1.000000x-1.000000x1.149458x1.149458x1.15x2.746%2.75%3.157%3.16%44-1.000000x-1.000000x1.145376x1.145376x1.15x1.701%1.70%1.948%1.95%45-1.000000x-1.000000x1.141406x1.141406x1.14x1.539%1.54%1.757%1.76%46-1.000000x-1.000000x1.036455x1.036455x1.04x1.220%1.22%1.265%1.26%47-1.103703x-1.103703x1.10x1.000000x1.000000x1.302%1.30%1.180%1.18%48-1.188945x-1.188945x1.19x1.000000x1.000000x2.687%2.69%2.260%2.26%49-1.404867x-1.404867x1.40x1.000000x1.000000x1.525%1.53%1.086%1.09%50
F percentage of females in category
M percentage of males in category
# rank of county subdivision out of 50 by male-to-female sex ratio

Educational Attainment by County Subdivision in the Midwest

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

No H.S. Diploma by County Subdivision#31

Percent of population 25 years of age and older without a high school diploma (or equivalent).
Scope: population of Oakwood, selected other county subdivisions in the Midwest, and entities that contain Oakwood
0%10%20%30%Count#Aurora TownshipAuroraCenter TownshipCtrKansas CityClevelandWayne TownshipWayneDetroitMilwaukeeNorth TownshipNDaytonChicagoProviso TownshipProvisoRockford TownshipRockfordSt. LouisWarrenGrand RapidsToledoBlue TownshipCincinnatiAkronSt. PaulSterling HeightsSterling HtsUnited States of AmericaUnited StatesThornton TownshipThorntonWichitaKaw TownshipOmahaBloomingdale TownshipBloomingdaleColumbusMaine TownshipMaineTopekaMinneapolisSpringfield TownshipSpringfieldEast North CentralWorth TownshipWorthOhioMontgomery CountyMontgomeryMidwestLawrence TownshipLawrenceDayton Metro AreaDayton AreaSioux FallsCapital TownshipCapitalWheeling TownshipWheelingPalatine TownshipPalatineSchaumburg TownshipSchaumburgLincolnWashington TownshipWashingtonOlatheFargoCedar RapidsYork TownshipMilton TownshipMiltonMadisonDowners Grove TownshipDowners GrvLisle TownshipLisleOverland ParkAnn ArborOakwoodOakwood33.464284%33.464284%33.5%29,81429.8k123.165532%23.165532%23.2%22,92622.9k222.659362%22.659362%22.7%21,21821.2k321.582420%21.582420%21.6%54,98155.0k421.037720%21.037720%21.0%18,48918.5k521.003600%21.003600%21.0%90,67890.7k617.485105%17.485105%17.5%63,80063.8k717.062713%17.062713%17.1%17,39117.4k816.928359%16.928359%16.9%14,88914.9k916.905373%16.905373%16.9%309,770310k1015.636222%15.636222%15.6%16,11016.1k1115.608074%15.608074%15.6%18,24118.2k1215.466266%15.466266%15.5%33,80433.8k1315.286174%15.286174%15.3%14,05914.1k1414.563179%14.563179%14.6%17,64317.6k1514.332972%14.332972%14.3%26,34326.3k1614.241047%14.241047%14.2%15,25815.3k1713.761583%13.761583%13.8%26,28626.3k1813.591726%13.591726%13.6%17,95118.0k1913.278342%13.278342%13.3%24,61324.6k2013.132171%13.132171%13.1%12,21212.2k2113.020590%13.020590%13.0%27,818,38027.8M12.974232%12.974232%13.0%14,37014.4k2212.568464%12.568464%12.6%31,23131.2k2312.455744%12.455744%12.5%15,16315.2k2412.198899%12.198899%12.2%35,05035.1k2512.171847%12.171847%12.2%9,3752611.376979%11.376979%11.4%60,83160.8k2711.132206%11.132206%11.1%10,96511.0k2811.032803%11.032803%11.0%9,3772910.958428%10.958428%11.0%29,34729.3k3010.767091%10.767091%10.8%11,14911.1k3110.719464%10.719464%10.7%3,363,7843.36M10.678962%10.678962%10.7%11,17511.2k3210.514146%10.514146%10.5%825,155825k10.369633%10.369633%10.4%37,59537.6k10.244520%10.244520%10.2%4,641,8354.64M10.179618%10.179618%10.2%8,161339.844056%9.844056%9.8%53,48053.5k9.702326%9.702326%9.7%9,123348.623103%8.623103%8.6%6,837358.424707%8.424707%8.4%9,343368.392669%8.392669%8.4%6,695377.739434%7.739434%7.7%7,226387.092309%7.092309%7.1%11,88611.9k396.804680%6.804680%6.8%6,403406.424130%6.424130%6.4%5,331416.055621%6.055621%6.1%4,270425.981653%5.981653%6.0%5,099435.461095%5.461095%5.5%4,715445.266517%5.266517%5.3%4,126454.836248%4.836248%4.8%7,351464.020265%4.020265%4.0%4,166473.522812%3.522812%3.5%2,870483.377424%3.377424%3.4%4,282493.157717%3.157717%3.2%2,057501.721876%1.721876%1.7%1051.721876%1.721876%1.7%105
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#32

Percent of population 25 years of age and older with a bachelor's degree or higher..
Scope: population of Oakwood, selected other county subdivisions in the Midwest, and entities that contain Oakwood
0%20%40%60%Count#Ann ArborOakwoodOakwoodOverland 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 TownshipProvisoMontgomery CountyMontgomeryWorth TownshipWorthMilwaukeeRockford TownshipRockfordAkronCenter TownshipCtrNorth TownshipNThornton TownshipThorntonToledoDaytonWarrenWayne TownshipWayneKansas CityClevelandAurora TownshipAuroraBlue TownshipDetroit72.810169%72.810169%72.8%47,43047.4k170.580518%70.580518%70.6%4,30470.580518%70.580518%70.6%4,30458.823344%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%27,03327.0k3426.143225%26.143225%26.1%94,78294.8k25.217641%25.217641%25.2%26,38926.4k3523.517740%23.517740%23.5%85,81285.8k3621.592552%21.592552%21.6%25,23525.2k3720.213821%20.213821%20.2%26,69726.7k3820.139240%20.139240%20.1%19,93119.9k3919.650916%19.650916%19.7%20,02920.0k4018.971090%18.971090%19.0%21,01221.0k4118.048021%18.048021%18.0%33,17133.2k4217.635555%17.635555%17.6%15,51115.5k4317.280259%17.280259%17.3%15,89315.9k4416.826535%16.826535%16.8%14,78814.8k4516.167409%16.167409%16.2%15,13915.1k4616.073076%16.073076%16.1%40,94640.9k4715.929601%15.929601%15.9%14,19214.2k4815.821208%15.821208%15.8%16,95117.0k4913.833543%13.833543%13.8%59,72359.7k50
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older with a bachelor's degree or higher..

Very Advanced Degrees by County Subdivision#33

Percent of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).
Scope: population of Oakwood, selected other county subdivisions in the Midwest, and entities that contain Oakwood
0%5%10%15%Count#Ann ArborOakwoodOakwoodMadisonDowners 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 TownshipSchaumburgWichitaMontgomery CountyMontgomeryProviso TownshipProvisoAkronBloomingdale TownshipBloomingdaleRockford TownshipRockfordMilwaukeeWorth TownshipWorthClevelandToledoNorth TownshipNSterling HeightsSterling HtsKansas CityDetroitDaytonWayne TownshipWayneWarrenBlue TownshipAurora TownshipAuroraThornton TownshipThornton17.877867%17.877867%17.9%11,64611.6k115.759265%15.759265%15.8%96115.759265%15.759265%15.8%9619.171173%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%6,260322.444911%2.444911%2.4%8,8642.213918%2.213918%2.2%2,281332.163955%2.163955%2.2%2,858342.113682%2.113682%2.1%1,628352.067272%2.067272%2.1%2,416362.043126%2.043126%2.0%7,455371.958049%1.958049%2.0%2,049381.927780%1.927780%1.9%4,911391.642065%1.642065%1.6%3,018401.575684%1.575684%1.6%1,606411.439893%1.439893%1.4%1,339421.388310%1.388310%1.4%1,300431.318660%1.318660%1.3%5,693441.257490%1.257490%1.3%1,106451.183365%1.183365%1.2%1,040461.047058%1.047058%1.0%963470.997751%0.997751%1.0%1,069480.936111%0.936111%0.9%834490.876686%0.876686%0.9%97150
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).

Under-Education Sex Ratio by County Subdivision#34

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 Oakwood, selected other county subdivisions in the Midwest, and entities that contain Oakwood
Female
Male
1x0x1xFM#Cedar RapidsLincolnDetroitOmahaToledoThorntonKansas CityMadisonLawrenceFargoProvisoRockfordBlue TownshipWayneMidwestTopekaEast North CentralMilwaukeeKaw TownshipDaytonSioux FallsUnited StatesOlatheOhioWorthNOverland ParkAuroraWheelingGrand RapidsSchaumburgChicagoWichitaOakwoodOakwoodColumbusClevelandPalatineCapitalWarrenMontgomerySpringfieldYork TownshipSt. LouisWashingtonBloomingdaleCtrCincinnatiDayton AreaAkronAnn ArborSt. PaulLisleMinneapolisSterling HtsDowners GrvMiltonMaine-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-1.000000x1.059528x1.059528x1.06x12.215%12.2%12.942%12.9%29-1.000000x-1.000000x1.053352x1.053352x1.05x1.681%1.68%1.771%1.77%-1.000000x-1.000000x1.053352x1.053352x1.05x1.681%1.68%1.771%1.77%-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-1.000000x1.037009x1.037009x1.04x10.193%10.2%10.570%10.6%-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%46-1.131063x-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#35

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 Oakwood, selected other county subdivisions in the Midwest, and entities that contain Oakwood
Female
Male
1x0x1x2xFM#Dayton AreaMontgomeryRockfordNOakwoodOakwoodDaytonSioux FallsCapitalLawrenceDowners GrvAkronLisleWichitaYork TownshipMaineWarrenWheelingBlue TownshipSpringfieldOverland ParkMiltonGrand RapidsOlatheOhioOmahaFargoWashingtonEast North CentralLincolnMidwestBloomingdaleKansas CityAuroraUnited StatesAnn ArborTopekaSterling HtsPalatineSchaumburgColumbusMadisonKaw TownshipMilwaukeeCedar RapidsClevelandCincinnatiSt. PaulSt. LouisChicagoWayneCtrToledoMinneapolisWorthDetroitProvisoThornton-1.000000x-1.000000x2.159743x2.159743x2.16x1.731%1.73%3.739%3.74%-1.000000x-1.000000x2.146385x2.146385x2.15x1.591%1.59%3.414%3.41%-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-1.000000x2.018680x2.018680x2.02x10.778%10.8%21.756%21.8%-1.000000x-1.000000x2.018680x2.018680x2.02x10.778%10.8%21.756%21.8%-1.000000x-1.000000x1.989047x1.989047x1.99x0.860%0.86%1.711%1.71%3-1.000000x-1.000000x1.962539x1.962539x1.96x1.928%1.93%3.783%3.78%4-1.000000x-1.000000x1.901348x1.901348x1.90x2.990%2.99%5.686%5.69%5-1.000000x-1.000000x1.879271x1.879271x1.88x2.206%2.21%4.146%4.15%6-1.000000x-1.000000x1.852471x1.852471x1.85x5.456%5.46%10.107%10.1%7-1.000000x-1.000000x1.846298x1.846298x1.85x1.550%1.55%2.862%2.86%8-1.000000x-1.000000x1.815266x1.815266x1.82x4.271%4.27%7.754%7.75%9-1.000000x-1.000000x1.792728x1.792728x1.79x1.819%1.82%3.261%3.26%10-1.000000x-1.000000x1.792314x1.792314x1.79x4.498%4.50%8.062%8.06%11-1.000000x-1.000000x1.788417x1.788417x1.79x2.939%2.94%5.256%5.26%12-1.000000x-1.000000x1.768853x1.768853x1.77x0.769%0.77%1.361%1.36%13-1.000000x-1.000000x1.766097x1.766097x1.77x2.485%2.48%4.389%4.39%14-1.000000x-1.000000x1.761699x1.761699x1.76x0.737%0.74%1.298%1.30%15-1.000000x-1.000000x1.751445x1.751445x1.75x2.146%2.15%3.759%3.76%16-1.000000x-1.000000x1.732234x1.732234x1.73x4.415%4.41%7.647%7.65%17-1.000000x-1.000000x1.695067x1.695067x1.70x4.357%4.36%7.385%7.38%18-1.000000x-1.000000x1.689013x1.689013x1.69x2.382%2.38%4.023%4.02%19-1.000000x-1.000000x1.678153x1.678153x1.68x2.131%2.13%3.576%3.58%20-1.000000x-1.000000x1.669500x1.669500x1.67x2.031%2.03%3.391%3.39%-1.000000x-1.000000x1.669388x1.669388x1.67x3.061%3.06%5.110%5.11%21-1.000000x-1.000000x1.627456x1.627456x1.63x3.304%3.30%5.377%5.38%22-1.000000x-1.000000x1.610803x1.610803x1.61x5.701%5.70%9.183%9.18%23-1.000000x-1.000000x1.597848x1.597848x1.60x2.216%2.22%3.541%3.54%-1.000000x-1.000000x1.596978x1.596978x1.60x3.524%3.52%5.628%5.63%24-1.000000x-1.000000x1.589934x1.589934x1.59x2.251%2.25%3.579%3.58%-1.000000x-1.000000x1.586045x1.586045x1.59x1.649%1.65%2.616%2.62%25-1.000000x-1.000000x1.570028x1.570028x1.57x1.087%1.09%1.707%1.71%26-1.000000x-1.000000x1.550495x1.550495x1.55x0.737%0.74%1.143%1.14%27-1.000000x-1.000000x1.526215x1.526215x1.53x2.660%2.66%4.060%4.06%-1.000000x-1.000000x1.522839x1.522839x1.52x14.269%14.3%21.730%21.7%28-1.000000x-1.000000x1.481288x1.481288x1.48x2.641%2.64%3.912%3.91%29-1.000000x-1.000000x1.476996x1.476996x1.48x1.170%1.17%1.728%1.73%30-1.000000x-1.000000x1.457167x1.457167x1.46x2.851%2.85%4.154%4.15%31-1.000000x-1.000000x1.436165x1.436165x1.44x2.115%2.11%3.037%3.04%32-1.000000x-1.000000x1.413654x1.413654x1.41x2.801%2.80%3.959%3.96%33-1.000000x-1.000000x1.387878x1.387878x1.39x7.705%7.70%10.693%10.7%34-1.000000x-1.000000x1.373250x1.373250x1.37x4.975%4.97%6.832%6.83%35-1.000000x-1.000000x1.368590x1.368590x1.37x1.742%1.74%2.385%2.38%36-1.000000x-1.000000x1.346658x1.346658x1.35x2.491%2.49%3.354%3.35%37-1.000000x-1.000000x1.286599x1.286599x1.29x1.699%1.70%2.186%2.19%38-1.000000x-1.000000x1.280610x1.280610x1.28x4.179%4.18%5.351%5.35%39-1.000000x-1.000000x1.274509x1.274509x1.27x5.228%5.23%6.663%6.66%40-1.000000x-1.000000x1.273345x1.273345x1.27x4.319%4.32%5.500%5.50%41-1.000000x-1.000000x1.238186x1.238186x1.24x4.026%4.03%4.985%4.99%42-1.000000x-1.000000x1.223931x1.223931x1.22x1.068%1.07%1.307%1.31%43-1.000000x-1.000000x1.213574x1.213574x1.21x2.357%2.36%2.860%2.86%44-1.000000x-1.000000x1.141406x1.141406x1.14x1.539%1.54%1.757%1.76%45-1.000000x-1.000000x1.124528x1.124528x1.12x5.872%5.87%6.603%6.60%46-1.000000x-1.000000x1.084697x1.084697x1.08x1.883%1.88%2.042%2.04%47-1.000000x-1.000000x1.046557x1.046557x1.05x1.291%1.29%1.351%1.35%48-1.000000x-1.000000x1.042857x1.042857x1.04x2.171%2.17%2.264%2.26%49-1.706858x-1.706858x1.71x1.000000x1.000000x1.072%1.07%0.628%0.63%50
F percentage of females in category
M percentage of males in category
# rank of county subdivision out of 50 by male-to-female sex ratio

Educational Attainment by County Subdivision in the United States

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

No H.S. Diploma by County Subdivision#36

Percent of population 25 years of age and older without a high school diploma (or equivalent).
Scope: population of Oakwood, selected other county subdivisions in the United States, and entities that contain Oakwood
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, CharlotteColumbusTulsaEast North CentralOhioSalt Lake CitySalt Lk CityTown of HempsteadHempsteadMontgomery CountyMontgomeryMidwestNorthwest HarrisNW HarrisWashingtonDayton Metro AreaDayton AreaAtlantaSeattleNortheast TarrantNE TarrantPlanoSeattle EastOakwoodOakwood28.998944%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%43,65343.7k4110.719464%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%54,23054.2k4310.369633%10.369633%10.4%37,59537.6k10.244520%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%53,48053.5k9.538552%9.538552%9.5%37,37337.4k468.833573%8.833573%8.8%66,22066.2k478.418271%8.418271%8.4%31,44331.4k485.714681%5.714681%5.7%20,64420.6k494.913852%4.913852%4.9%20,32620.3k501.721876%1.721876%1.7%1051.721876%1.721876%1.7%105
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#37

Percent of population 25 years of age and older with a bachelor's degree or higher..
Scope: population of Oakwood, selected other county subdivisions in the United States, and entities that contain Oakwood
0%20%40%60%Count#OakwoodOakwoodManhattanSeattle 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 VlyOntarioOhioPhiladelphiaMontgomery CountyMontgomeryMiamiFort WorthSouthwest DallasSW DallasMilwaukeeFresnoLas VegasEl PasoBronxSan BernardinoSan Antonio CentralSan Antonio CntrlDetroit70.580518%70.580518%70.6%4,30470.580518%70.580518%70.6%4,30460.434640%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%272,786273k3926.143225%26.143225%26.1%94,78294.8k26.011156%26.011156%26.0%178,455178k4024.665414%24.665414%24.7%131,349131k4123.764821%23.764821%23.8%140,625141k4223.517740%23.517740%23.5%85,81285.8k4322.486319%22.486319%22.5%94,05694.1k4421.702666%21.702666%21.7%271,037271k4521.071885%21.071885%21.1%72,12072.1k4619.131504%19.131504%19.1%173,169173k4716.375473%16.375473%16.4%80,59580.6k4814.929012%14.929012%14.9%65,34165.3k4913.833543%13.833543%13.8%59,72359.7k50
Count number of people in category
# rank of county subdivision out of 50 by percentage of population 25 years of age and older with a bachelor's degree or higher..

Very Advanced Degrees by County Subdivision#38

Percent of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).
Scope: population of Oakwood, selected other county subdivisions in the United States, and entities that contain Oakwood
0%5%10%15%Count#OakwoodOakwoodWashingtonManhattanSan 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 VlyMontgomery CountyMontgomeryOntarioFort WorthLas VegasMilwaukeeSan BernardinoSan Antonio CentralSan Antonio CntrlEl PasoSouthwest DallasSW DallasBronxDetroit15.759265%15.759265%15.8%96115.759265%15.759265%15.8%96112.461852%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%15,54715.5k402.444911%2.444911%2.4%8,8642.324315%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%5,69350
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#39

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 Oakwood, selected other county subdivisions in the United States, and entities that contain Oakwood
Female
Male
1x0x1xFM#1, CharlotteDetroitBaltimoreTulsaSW DallasMidwestFresnoEast North CentralMilwaukeeUnited StatesOhioNE DallasHoustonHempsteadOrlandoPhiladelphiaOntarioSan BernardinoAustinAtlantaFort WorthPhoenixChicagoAlbuquerqueWashingtonOakwoodOakwoodSacramentoColumbusSalt Lk CityDenverNE TarrantTampaOceanside-EscondidoOceanside-Escond…NW HarrisMontgomeryBronxPlanoBrooklynSan Antonio CntrlSan Fernando VlyDayton AreaTucsonAnaheim-Santa Ana-Gdn GrvAnaheim-Santa An…Los AngelesLas VegasBostonE San Gabriel VlyQueensMiamiManhattanSeattleLong Bch-LakewoodSeattle EastSan JoseSan DiegoSan FranciscoEl Paso-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-1.000000x1.053352x1.053352x1.05x1.681%1.68%1.771%1.77%-1.000000x-1.000000x1.053352x1.053352x1.05x1.681%1.68%1.771%1.77%-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-1.000000x1.037009x1.037009x1.04x10.193%10.2%10.570%10.6%-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%47-1.168454x-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#40

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 Oakwood, selected other county subdivisions in the United States, and entities that contain Oakwood
Female
Male
1x0x1x2xFM#Dayton AreaMontgomeryEl PasoSalt Lk CityOakwoodOakwoodPlanoTulsaAlbuquerqueNE 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 DallasBrooklynManhattanChicagoSeattleBostonBronxOntarioLong Bch-LakewoodDenverSan FranciscoDetroit-1.000000x-1.000000x2.159743x2.159743x2.16x1.731%1.73%3.739%3.74%-1.000000x-1.000000x2.146385x2.146385x2.15x1.591%1.59%3.414%3.41%-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-1.000000x2.018680x2.018680x2.02x10.778%10.8%21.756%21.8%-1.000000x-1.000000x2.018680x2.018680x2.02x10.778%10.8%21.756%21.8%-1.000000x-1.000000x1.782054x1.782054x1.78x3.355%3.35%5.978%5.98%3-1.000000x-1.000000x1.720683x1.720683x1.72x2.338%2.34%4.022%4.02%4-1.000000x-1.000000x1.707718x1.707718x1.71x3.458%3.46%5.905%5.91%5-1.000000x-1.000000x1.692229x1.692229x1.69x2.857%2.86%4.836%4.84%6-1.000000x-1.000000x1.684272x1.684272x1.68x1.637%1.64%2.757%2.76%7-1.000000x-1.000000x1.669500x1.669500x1.67x2.031%2.03%3.391%3.39%-1.000000x-1.000000x1.660799x1.660799x1.66x2.196%2.20%3.647%3.65%8-1.000000x-1.000000x1.659024x1.659024x1.66x2.280%2.28%3.783%3.78%9-1.000000x-1.000000x1.621815x1.621815x1.62x3.429%3.43%5.561%5.56%10-1.000000x-1.000000x1.611479x1.611479x1.61x2.711%2.71%4.369%4.37%11-1.000000x-1.000000x1.597848x1.597848x1.60x2.216%2.22%3.541%3.54%-1.000000x-1.000000x1.589934x1.589934x1.59x2.251%2.25%3.579%3.58%-1.000000x-1.000000x1.579303x1.579303x1.58x2.100%2.10%3.317%3.32%12-1.000000x-1.000000x1.576623x1.576623x1.58x1.677%1.68%2.643%2.64%13-1.000000x-1.000000x1.557664x1.557664x1.56x4.733%4.73%7.372%7.37%14-1.000000x-1.000000x1.540473x1.540473x1.54x1.423%1.42%2.192%2.19%15-1.000000x-1.000000x1.529565x1.529565x1.53x4.164%4.16%6.370%6.37%16-1.000000x-1.000000x1.526215x1.526215x1.53x2.660%2.66%4.060%4.06%-1.000000x-1.000000x1.514156x1.514156x1.51x4.979%4.98%7.539%7.54%17-1.000000x-1.000000x1.488724x1.488724x1.49x3.608%3.61%5.371%5.37%18-1.000000x-1.000000x1.484269x1.484269x1.48x2.293%2.29%3.404%3.40%19-1.000000x-1.000000x1.481801x1.481801x1.48x2.138%2.14%3.168%3.17%20-1.000000x-1.000000x1.476874x1.476874x1.48x3.518%3.52%5.196%5.20%21-1.000000x-1.000000x1.460302x1.460302x1.46x2.944%2.94%4.299%4.30%22-1.000000x-1.000000x1.451775x1.451775x1.45x2.041%2.04%2.963%2.96%23-1.000000x-1.000000x1.424636x1.424636x1.42x3.092%3.09%4.404%4.40%24-1.000000x-1.000000x1.423621x1.423621x1.42x1.501%1.50%2.137%2.14%25-1.000000x-1.000000x1.413654x1.413654x1.41x2.801%2.80%3.959%3.96%26-1.000000x-1.000000x1.395174x1.395174x1.40x3.384%3.38%4.722%4.72%27-1.000000x-1.000000x1.391590x1.391590x1.39x5.799%5.80%8.070%8.07%28-1.000000x-1.000000x1.368590x1.368590x1.37x1.742%1.74%2.385%2.38%29-1.000000x-1.000000x1.362600x1.362600x1.36x2.347%2.35%3.199%3.20%30-1.000000x-1.000000x1.359928x1.359928x1.36x2.888%2.89%3.927%3.93%31-1.000000x-1.000000x1.341930x1.341930x1.34x3.216%3.22%4.316%4.32%32-1.000000x-1.000000x1.310218x1.310218x1.31x3.011%3.01%3.945%3.95%33-1.000000x-1.000000x1.308108x1.308108x1.31x4.045%4.05%5.292%5.29%34-1.000000x-1.000000x1.303834x1.303834x1.30x4.384%4.38%5.716%5.72%35-1.000000x-1.000000x1.303196x1.303196x1.30x4.332%4.33%5.645%5.65%36-1.000000x-1.000000x1.300117x1.300117x1.30x10.922%10.9%14.199%14.2%37-1.000000x-1.000000x1.285200x1.285200x1.29x2.428%2.43%3.121%3.12%38-1.000000x-1.000000x1.265486x1.265486x1.27x1.515%1.51%1.917%1.92%39-1.000000x-1.000000x1.262281x1.262281x1.26x3.021%3.02%3.814%3.81%40-1.000000x-1.000000x1.245683x1.245683x1.25x9.673%9.67%12.050%12.1%41-1.000000x-1.000000x1.238186x1.238186x1.24x4.026%4.03%4.985%4.99%42-1.000000x-1.000000x1.228890x1.228890x1.23x5.961%5.96%7.326%7.33%43-1.000000x-1.000000x1.221037x1.221037x1.22x6.643%6.64%8.112%8.11%44-1.000000x-1.000000x1.202385x1.202385x1.20x1.526%1.53%1.834%1.83%45-1.000000x-1.000000x1.198236x1.198236x1.20x2.119%2.12%2.539%2.54%46-1.000000x-1.000000x1.181998x1.181998x1.18x2.766%2.77%3.269%3.27%47-1.000000x-1.000000x1.129665x1.129665x1.13x5.378%5.38%6.075%6.08%48-1.000000x-1.000000x1.098720x1.098720x1.10x7.194%7.19%7.905%7.90%49-1.000000x-1.000000x1.046557x1.046557x1.05x1.291%1.29%1.351%1.35%50
F percentage of females in category
M percentage of males in category
# rank of county subdivision out of 50 by male-to-female sex ratio

Definitions

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

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

The coarse levels of educational attainment are as follows:

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

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

More Topics to Explore

Demographics

Income

Education

More Maps to Explore

State:
Ohio
County:
Montgomery
Metro Area:
Dayton Area
City:
Oakwood
ZIP Codes:
45409, 45419
Unified School Districts:
Dayton, Oakwood
Neighborhood:
University Park
Congressional District:
OH-10
State Senate Districts:
OH-5, OH-6
State House Districts:
OH-39, OH-41
Nearby Townships:
Beavercreek, Harrison, Jefferson, Miami, Washington