Educational Attainment in Brown County, Ohio (County)

Educational Attainment#1

Highest level of education among people aged 25 years and older.
Scope: population of Ohio and Brown County
Brown County
Ohio
0%20%40%60%CountHigher Degree1H.S. Diploma2No H.S. Diploma219.797973%35.063314%19.797973%19.8%6,01765.464596%54.422540%65.464596%65.5%19,89619.9k14.737431%10.514146%14.737431%14.7%4,479
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 Ohio at large.
Scope: population of Ohio and Brown County
0%%ref.Higher Degree1H.S. Diploma2No H.S. Diploma2-43.536503%-43.536503%-43.5%19.798%19.8%35.063%35.1%20.289490%20.289490%+20.3%65.465%65.5%54.423%54.4%40.167648%40.167648%+40.2%14.737%14.7%10.514%10.5%
% percentage with given level in Brown County
ref. percentage with given level in Ohio
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 Ohio and Brown County
Brown County
Ohio
0%10%20%30%40%CountDoctorate1Professional1Master's1Bachelor's1Associate's1Some CollegeHigh School2Some H.S.3Less than H.S.3None0.332324%1.076166%0.332324%0.3%1010.315873%1.607075%0.315873%0.3%963.211371%7.279494%3.211371%3.2%9768.577915%16.704731%8.577915%8.6%2,6077.360490%8.395848%7.360490%7.4%2,23717.715188%20.603422%17.715188%17.7%5,38447.749408%33.819119%47.749408%47.7%14,51214.5k10.904185%7.545636%10.904185%10.9%3,3143.066596%2.095069%3.066596%3.1%9320.766649%0.873440%0.766649%0.8%233
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 Ohio at large.
Scope: population of Ohio and Brown County
-50%0%+50%%ref.Doctorate1Professional1Master's1Bachelor's1Associate's1Some CollegeHigh School2Some H.S.3Less than H.S.3None-69.119605%-69.119605%-69.1%0.332%0.33%1.076%1.08%-80.344877%-80.344877%-80.3%0.316%0.32%1.607%1.61%-55.884686%-55.884686%-55.9%3.211%3.21%7.279%7.28%-48.649786%-48.649786%-48.6%8.578%8.58%16.705%16.7%-12.331789%-12.331789%-12.3%7.360%7.36%8.396%8.40%-14.018222%-14.018222%-14.0%17.715%17.7%20.603%20.6%41.190573%41.190573%+41.2%47.749%47.7%33.819%33.8%44.509820%44.509820%+44.5%10.904%10.9%7.546%7.55%46.372080%46.372080%+46.4%3.067%3.07%2.095%2.10%-12.226505%-12.226505%-12.2%0.767%0.77%0.873%0.87%
% percentage with given level in Brown County
ref. percentage with given level in Ohio
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 Ohio and Brown County
More Females More Males
Ohio
Brown County
20%0%20%FMHigher Degree1H.S. Diploma2No H.S. Diploma2-23.831010%-7.885240%-23.831010%24%21.866%21.9%17.658%17.7%-0.090192%-0.090192%0%2.984493%65.494%65.5%65.435%65.4%33.756218%10.536340%33.756218%34%12.641%12.6%16.908%16.9%
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 Ohio and Brown County
More Females More Males
Ohio
Brown County
0%50%FMDoctorate1Professional1Master's1Bachelor's1Associate's1Some CollegeHigh School2Some H.S.3Less than H.S.3None-2.525078%-2.525078%3%65.373714%0.336%0.34%0.328%0.33%88.751290%68.015763%88.751290%89%0.220%0.22%0.415%0.42%-37.363839%-21.244079%-37.363839%37%3.707%3.71%2.699%2.70%-29.073264%-29.073264%29%0.726598%9.645%9.65%7.473%7.47%-18.004477%-39.383112%-18.004477%18%7.957%7.96%6.743%6.74%-36.431566%-0.103999%-36.431566%36%20.391%20.4%14.946%14.9%11.941500%4.911287%11.941500%12%45.103%45.1%50.489%50.5%43.274012%10.693269%43.274012%43%8.992%8.99%12.883%12.9%1.746920%11.385964%1.746920%2%3.040%3.04%3.094%3.09%53.060844%7.203042%53.060844%53%0.608%0.61%0.931%0.93%
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 Ohio and Brown County
Brown County
Ohio
0%5%10%15%20%B.X.Total65+45-6435-4425-343.885591%11.168673%3.885591%3.9%2887,4128.146672%15.925332%8.146672%8.1%1,02212,54512.5k13.145118%19.733657%13.145118%13.1%7315,56111.612638%22.259142%11.612638%11.6%5664,874
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 Ohio at large.
Scope: population of Ohio and Brown County
60%50%40%30%20%10%0%%ref.65+45-6435-4425-34-65.209913%-65.209913%65.2%3.886%3.89%11.169%11.2%-48.844569%-48.844569%48.8%8.147%8.15%15.925%15.9%-33.387320%-33.387320%33.4%13.145%13.1%19.734%19.7%-47.829802%-47.829802%47.8%11.613%11.6%22.259%22.3%
% percentage in Brown County with a Bachelor's degree
ref percentage in Ohio 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 Ohio and Brown County
More Females More Males
Ohio
Brown County
100%50%0%FM65+45-6435-4425-3420.117627%36.828803%20.117627%20.1%3.553%3.55%4.268%4.27%-28.591486%-0.054549%-28.591486%28.6%9.154%9.15%7.119%7.12%-17.040710%-14.012939%-17.040710%17.0%14.212%14.2%12.142%12.1%-112.332533%-14.499975%-112.332533%112.3%15.738%15.7%7.412%7.41%
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 Ohio and Brown County
Brown County
Ohio
$0k$20k$40k$60kCount%Graduate Degree1Bachelor's DegreeSome CollegeH.S. Diploma2No H.S. Diploma2Total$57,105.000000$63,821.000000$57,105.000000$57.1k1,1733.860%3.86%$52,066.000000$50,107.000000$52,066.000000$52.1k2,6078.578%8.58%$35,235.000000$32,706.000000$35,235.000000$35.2k7,62125.076%25.1%$30,335.000000$28,919.000000$30,335.000000$30.3k14,51214.5k47.749%47.7%$24,662.000000$20,344.000000$24,662.000000$24.7k4,47914.737%14.7%$34,281.000000$35,841.000000$34,281.000000$34.3k30,39230.4k100.000%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 Ohio and Brown County
Female Male
Ohio
Brown County
Shaded bar tips show excess over facing bar.
$50k$0k$50kFMGraduate Degree1Bachelor's DegreeSome CollegeH.S. Diploma2No H.S. Diploma2Total$-52,924.000000$-55,571.000000$-52,924.000000$52.9k$52,924.000000$20,431.000000$55,571.000000$22,109.000000$73,355.000000$73.4k659514$-38,955.000000$-40,856.000000$-38,955.000000$39.0k$38,955.000000$27,295.000000$40,856.000000$20,405.000000$66,250.000000$66.3k1,4911,116$-27,193.000000$-27,361.000000$-27,193.000000$27.2k$27,193.000000$14,008.000000$27,361.000000$13,780.000000$41,201.000000$41.2k4,3823,239$-21,895.000000$-22,081.000000$-21,895.000000$21.9k$21,895.000000$15,703.000000$22,081.000000$13,410.000000$37,598.000000$37.6k6,9727,540$-17,083.000000$-15,062.000000$-17,083.000000$17.1k$17,083.000000$19,935.000000$15,062.000000$9,409.000000$37,018.000000$37.0k1,9542,525$-26,274.000000$-29,749.000000$-26,274.000000$26.3k$26,274.000000$14,719.000000$29,749.000000$12,566.000000$40,993.000000$41.0k15,45815.5k14,93414.9k
F females with given highest level of educational attainment
M males with given highest level of educational attainment
1or professional degree 2H.S. = High School

Employment by Educational Attainment#12

Percentage of population that is employed by highest level of educational attainment among the population aged 25 to 64 years old.
Scope: population of Ohio and Brown County
Brown County
Ohio
0%20%40%60%80%CountBachelor's Degree1Some College2H.S. Diploma3No H.S. Diploma383.912363%84.712194%83.912363%83.9%2,68172.216114%75.098475%72.216114%72.2%4,59866.847623%67.335954%66.847623%66.8%7,14242.318947%44.096181%42.318947%42.3%1,157
Count employed people with given educational attainment aged 25 to 64 years old
1or higher 2two or four year institution 3H.S. = High School

Lacking High School Diploma By Race#13

Percent of racial or ethnic group lacking a high school diploma (or equivalent).
Scope: population of Ohio and Brown County
Female Male
Ohio
Brown County
Shaded bar tips show excess over facing bar.
20%10%0%10%20%MFWhite1BlackAsianHispanic2Other1-12.579830%-8.849949%-12.579830%12.6%12.579830%4.355153%8.849949%0.838407%16.934982%16.9%2,4511,891-8.045977%-14.710486%-8.045977%8.0%8.045977%18.225209%14.710486%2.396424%26.271186%26.3%3114-0.000000%-20.000000%-10.995328%-3.238870%-20.000000%20.0%0.000000%10.995328%0.000000%0.0%08-23.863636%-4.341492%-23.269744%-28.205128%28.2%23.863636%23.269744%5.740390%23.863636%23.9%2122-10.830325%-2.364120%-16.869350%-13.194444%13.2%10.830325%16.869350%3.904344%10.830325%10.8%3019
M number of males in category
F number of females in category
1non-Hispanic 2excluding black and Asian Hispanics

College Graduates By Race#14

Percent of racial or ethnic group with a bachelor's degree or higher.
Scope: population of Ohio and Brown County
Female Male
Ohio
Brown County
Shaded bar tips show excess over facing bar.
50%0%50%MFWhite1BlackAsianHispanic2Other1-10.944517%-3.098857%-27.409880%-14.043374%14.0%10.944517%27.409880%0.383981%10.944517%10.9%1,5842,111-0.000000%-14.337282%-3.326272%0.000000%0.0%0.000000%5.084746%14.337282%5.084746%5.1%60-42.500000%-55.571247%-42.500000%42.5%42.500000%37.500000%55.571247%11.025101%80.000000%80.0%817-10.227273%-6.439394%-15.825016%-4.164425%-16.666667%16.7%10.227273%15.825016%10.227273%10.2%913-6.250000%-18.226192%-3.481943%-6.250000%6.3%6.250000%5.302347%18.226192%11.552347%11.6%329
M number of males in category
F number of females in category
1non-Hispanic 2excluding black and Asian Hispanics

Map of Educational Attainment by County Subdivision in Brown County

Coarse: Post-Secondary Degree Educational Attainment by County Subdivision#15

Percentage of the population 25 years and older with given highest level of educational attainment
13.1%17.3%21.6%25.8%30.0%34.3%

Coarse: High School Diploma Educational Attainment by County Subdivision#16

Percentage of the population 25 years and older with given highest level of educational attainment
57.8%60.8%63.8%66.7%69.7%72.7%

Coarse: No High School Diploma Educational Attainment by County Subdivision#17

Percentage of the population 25 years and older with given highest level of educational attainment
4.0%7.2%10.4%13.6%16.8%20.1%

Detailed: Doctorate Degree Educational Attainment by County Subdivision#18

Percentage of the population 25 years and older with given highest level of educational attainment
0.00%0.38%0.76%1.15%1.53%1.91%

Detailed: Professional Degree Educational Attainment by County Subdivision#19

Percentage of the population 25 years and older with given highest level of educational attainment
0.00%0.43%0.87%1.30%1.73%2.17%

Detailed: Master's Degree Educational Attainment by County Subdivision#20

Percentage of the population 25 years and older with given highest level of educational attainment
0.0%1.6%3.2%4.8%6.4%8.0%

Detailed: Bachelor's Degree Educational Attainment by County Subdivision#21

Percentage of the population 25 years and older with given highest level of educational attainment
3.1%5.8%8.4%10.9%13.5%16.2%

Detailed: Associate's Degree Educational Attainment by County Subdivision#22

Percentage of the population 25 years and older with given highest level of educational attainment
1.0%4.0%6.8%9.7%12.6%15.5%

Detailed: Some College Educational Attainment by County Subdivision#23

Percentage of the population 25 years and older with given highest level of educational attainment
10.8%13.2%15.6%18.1%20.5%22.9%

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

Percentage of the population 25 years and older with given highest level of educational attainment
37.9%42.6%47.2%51.9%56.5%61.2%

Detailed: Some High School Educational Attainment by County Subdivision#25

Percentage of the population 25 years and older with given highest level of educational attainment
4.0%6.8%9.5%12.2%14.9%17.7%

Detailed: Less than High School Educational Attainment by County Subdivision#26

Percentage of the population 25 years and older with given highest level of educational attainment
0.0%1.5%3.0%4.5%6.1%7.6%

Detailed: None Educational Attainment by County Subdivision#27

Percentage of the population 25 years and older with given highest level of educational attainment
0.00%0.46%0.92%1.38%1.84%2.31%
Road Data ©OpenStreetMap

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Map of Educational Attainment by Tract in Brown County

Coarse: Post-Secondary Degree Educational Attainment by Tract#28

Percentage of the population 25 years and older with given highest level of educational attainment
14.7%17.0%19.2%21.3%23.5%25.8%

Coarse: High School Diploma Educational Attainment by Tract#29

Percentage of the population 25 years and older with given highest level of educational attainment
60.6%62.2%63.9%65.5%67.1%68.8%

Coarse: No High School Diploma Educational Attainment by Tract#30

Percentage of the population 25 years and older with given highest level of educational attainment
10.5%12.2%13.9%15.6%17.3%19.0%

Detailed: Doctorate Degree Educational Attainment by Tract#31

Percentage of the population 25 years and older with given highest level of educational attainment
0.00%0.23%0.46%0.69%0.91%1.15%

Detailed: Professional Degree Educational Attainment by Tract#32

Percentage of the population 25 years and older with given highest level of educational attainment
0.00%0.20%0.39%0.59%0.79%0.99%

Detailed: Master's Degree Educational Attainment by Tract#33

Percentage of the population 25 years and older with given highest level of educational attainment
1.4%2.2%2.9%3.6%4.4%5.2%

Detailed: Bachelor's Degree Educational Attainment by Tract#34

Percentage of the population 25 years and older with given highest level of educational attainment
5.4%6.8%8.3%9.7%11.1%12.6%

Detailed: Associate's Degree Educational Attainment by Tract#35

Percentage of the population 25 years and older with given highest level of educational attainment
5.5%6.2%6.8%7.5%8.1%8.8%

Detailed: Some College Educational Attainment by Tract#36

Percentage of the population 25 years and older with given highest level of educational attainment
14.0%15.9%17.8%19.6%21.5%23.4%

Detailed: High School Diploma or Equivalent Educational Attainment by Tract#37

Percentage of the population 25 years and older with given highest level of educational attainment
42.1%44.4%46.7%49.0%51.3%53.7%

Detailed: Some High School Educational Attainment by Tract#38

Percentage of the population 25 years and older with given highest level of educational attainment
8.6%9.7%10.8%11.9%13.0%14.2%

Detailed: Less than High School Educational Attainment by Tract#39

Percentage of the population 25 years and older with given highest level of educational attainment
1.3%2.2%3.0%3.8%4.6%5.4%

Detailed: None Educational Attainment by Tract#40

Percentage of the population 25 years and older with given highest level of educational attainment
0.07%0.40%0.72%1.05%1.37%1.70%
Road Data ©OpenStreetMap

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Educational Attainment by Place in Brown County

There are 12 places that are fully or partially contained within Brown County (11 fully and 1 partially). This section compares all 12 of those to each other, Brown County, and other entities that contain or substantially overlap with Brown County.

No H.S. Diploma by Place#41

Percent of population 25 years of age and older without a high school diploma (or equivalent).
Scope: population of Brown County, selected places in Brown County, and entities that contain Brown County
0%5%10%15%20%Count#HigginsportRipleyRussellvilleMount OrabAberdeenSardiniaBrown CountyBrownGeorgetownUnited States of AmericaUnited StatesEast North CentralOhioHamersvilleMidwestCincinnati Metro AreaCincinnatiFayettevilleLake LoreleiSt. MartinLake Waynoka24.752475%24.752475%24.8%50122.058824%22.058824%22.1%285221.634615%21.634615%21.6%90318.759630%18.759630%18.8%487418.648649%18.648649%18.6%207518.356868%18.356868%18.4%143614.737431%14.737431%14.7%4,47914.660012%14.660012%14.7%470713.020590%13.020590%13.0%27,818,38027.8M10.719464%10.719464%10.7%3,363,7843.36M10.514146%10.514146%10.5%825,155825k10.404624%10.404624%10.4%54810.244520%10.244520%10.2%4,641,8354.64M9.940523%9.940523%9.9%141,727142k8.810573%8.810573%8.8%2094.086538%4.086538%4.1%34100.851064%0.851064%0.9%2110.000000%0.000000%0.0%012
Count number of people in category
# rank of place out of 12 by percentage of population 25 years of age and older without a high school diploma (or equivalent).

Bachelor's Degrees by Place#42

Percent of population 25 years of age and older with a bachelor's degree or higher..
Scope: population of Brown County, selected places in Brown County, and entities that contain Brown County
0%10%20%30%Count#Cincinnati Metro AreaCincinnatiUnited States of AmericaUnited StatesMidwestEast North CentralOhioLake WaynokaSt. MartinLake LoreleiFayettevilleHamersvilleBrown CountyBrownRipleyGeorgetownMount OrabAberdeenHigginsportSardiniaRussellville31.723093%31.723093%31.7%452,292452k30.315023%30.315023%30.3%64,767,78764.8M28.952816%28.952816%29.0%13,118,64213.1M28.462853%28.462853%28.5%8,931,6868.93M26.667466%26.667466%26.7%2,092,8752.09M26.054591%26.054591%26.1%210122.127660%22.127660%22.1%52218.149038%18.149038%18.1%151313.656388%13.656388%13.7%31412.909441%12.909441%12.9%67512.437484%12.437484%12.4%3,78011.996904%11.996904%12.0%155611.759201%11.759201%11.8%377711.093991%11.093991%11.1%288811.081081%11.081081%11.1%12398.415842%8.415842%8.4%17107.830552%7.830552%7.8%61116.730769%6.730769%6.7%2812
Count number of people in category
# rank of place out of 12 by percentage of population 25 years of age and older with a bachelor's degree or higher..

Very Advanced Degrees by Place#43

Percent of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).
Scope: population of Brown County, selected places in Brown County, and entities that contain Brown County
0%1%2%3%4%Count#Lake WaynokaUnited States of AmericaUnited StatesCincinnati Metro AreaCincinnatiMidwestEast North CentralOhioRussellvilleLake LoreleiBrown CountyBrownHamersvilleRipleySt. MartinSardiniaGeorgetownMount OrabAberdeenFayettevilleHigginsport4.962779%4.962779%5.0%4013.336158%3.336158%3.3%7,127,6737.13M3.129371%3.129371%3.1%44,61744.6k2.893416%2.893416%2.9%1,311,0191.31M2.855432%2.855432%2.9%896,039896k2.683241%2.683241%2.7%210,582211k2.403846%2.403846%2.4%1022.043269%2.043269%2.0%1730.648197%0.648197%0.6%1970.578035%0.578035%0.6%340.464396%0.464396%0.5%650.425532%0.425532%0.4%160.385109%0.385109%0.4%370.000000%0.000000%0.0%080.000000%0.000000%0.0%090.000000%0.000000%0.0%0100.000000%0.000000%0.0%0110.000000%0.000000%0.0%012
Count number of people in category
# rank of place out of 12 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 Place#44

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 Brown County, selected places in Brown County, and entities that contain Brown County
Female
Male
10x5x0xFM#Lake LoreleiGeorgetownMount OrabHigginsportRipleyHamersvilleBrownSardiniaMidwestEast North CentralCincinnatiUnited StatesOhioRussellvilleAberdeenFayettevilleSt. Martin-1.000000x-1.000000x3.297215x3.297215x3.30x1.909%1.91%6.295%6.30%1-1.000000x-1.000000x1.866187x1.866187x1.87x10.288%10.3%19.199%19.2%2-1.000000x-1.000000x1.610246x1.610246x1.61x14.643%14.6%23.579%23.6%3-1.000000x-1.000000x1.516820x1.516820x1.52x19.355%19.4%29.358%29.4%4-1.000000x-1.000000x1.479886x1.479886x1.48x18.143%18.1%26.850%26.9%5-1.000000x-1.000000x1.471459x1.471459x1.47x8.429%8.43%12.403%12.4%6-1.000000x-1.000000x1.337562x1.337562x1.34x12.641%12.6%16.908%16.9%-1.000000x-1.000000x1.188972x1.188972x1.19x16.867%16.9%20.055%20.1%7-1.000000x-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-1.000000x1.120901x1.120901x1.12x9.396%9.40%10.532%10.5%-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%-1.106594x-1.106594x1.11x1.000000x1.000000x22.685%22.7%20.500%20.5%8-1.168168x-1.168168x1.17x1.000000x1.000000x19.967%20.0%17.092%17.1%9-2.820513x-2.820513x2.82x1.000000x1.000000x12.821%12.8%4.545%4.55%10-10.000000x-10.000000x> 10.0x1.000000x1.000000x1.869%1.87%0.000%0%11
F percentage of females in category
M percentage of males in category
# rank of place out of 11 by male-to-female sex ratio

Over-Education Sex Ratio by Place#45

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 Brown County, selected places in Brown County, and entities that contain Brown County
Female
Male
10x5x0x5x10xFM#Lake LoreleiLake WaynokaOhioEast North CentralMidwestCincinnatiUnited StatesBrownRussellvilleRipleySardiniaHamersvilleSt. Martin-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%4.116%4.12%1-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%12.012%12.0%2-1.000000x-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-1.000000x1.582232x1.582232x1.58x2.447%2.45%3.871%3.87%-1.000000x-1.000000x1.526215x1.526215x1.53x2.660%2.66%4.060%4.06%-1.000000x-1.000000x1.335985x1.335985x1.34x0.556%0.56%0.743%0.74%-2.160494x-2.160494x2.16x1.000000x1.000000x3.241%3.24%1.500%1.50%3-10.000000x-10.000000x> 10.0x1.000000x1.000000x0.844%0.84%0.000%0%4-10.000000x-10.000000x> 10.0x1.000000x1.000000x0.723%0.72%0.000%0%5-10.000000x-10.000000x> 10.0x1.000000x1.000000x1.149%1.15%0.000%0%6-10.000000x-10.000000x> 10.0x1.000000x1.000000x0.935%0.93%0.000%0%7
F percentage of females in category
M percentage of males in category
# rank of place out of 7 by male-to-female sex ratio

Educational Attainment by County Subdivision in Brown County

There are 16 county subdivisions in Brown County. This section compares all 16 of those to each other, Brown County, and other entities that contain or substantially overlap with Brown County.

No H.S. Diploma by County Subdivision#46

Percent of population 25 years of age and older without a high school diploma (or equivalent).
Scope: population of Brown County, selected county subdivisions in Brown County, and entities that contain Brown County
0%5%10%15%20%Count#Green TownshipGrnHuntington TownshipHuntingtonWashington TownshipWashingtonEagle TownshipEagleUnion TownshipUnionClark TownshipClarkPike TownshipBrown CountyBrownPleasant TownshipPleasantByrd TownshipLewis TownshipLewisScott TownshipScottUnited States of AmericaUnited StatesJefferson TownshipJeffersonEast North CentralOhioPerry TownshipPerrySterling TownshipSterlingMidwestFranklin TownshipFranklinCincinnati Metro AreaCincinnatiJackson TownshipJackson20.025952%20.025952%20.0%463119.850187%19.850187%19.9%371218.745918%18.745918%18.7%287318.718802%18.718802%18.7%225417.953403%17.953403%18.0%393516.401205%16.401205%16.4%381616.308864%16.308864%16.3%471714.737431%14.737431%14.7%4,47914.489743%14.489743%14.5%558814.197531%14.197531%14.2%92913.994638%13.994638%14.0%2611013.043478%13.043478%13.0%961113.020590%13.020590%13.0%27,818,38027.8M12.211669%12.211669%12.2%901210.719464%10.719464%10.7%3,363,7843.36M10.514146%10.514146%10.5%825,155825k10.451306%10.451306%10.5%3521310.270270%10.270270%10.3%2851410.244520%10.244520%10.2%4,641,8354.64M10.043290%10.043290%10.0%116159.940523%9.940523%9.9%141,727142k4.029692%4.029692%4.0%3816
Count number of people in category
# rank of county subdivision out of 16 by percentage of population 25 years of age and older without a high school diploma (or equivalent).

Bachelor's Degrees by County Subdivision#47

Percent of population 25 years of age and older with a bachelor's degree or higher..
Scope: population of Brown County, selected county subdivisions in Brown County, and entities that contain Brown County
0%10%20%30%Count#Cincinnati Metro AreaCincinnatiUnited States of AmericaUnited StatesMidwestEast North CentralOhioLewis TownshipLewisJackson TownshipJacksonScott TownshipScottEagle TownshipEagleFranklin TownshipFranklinPerry TownshipPerryClark TownshipClarkSterling TownshipSterlingBrown CountyBrownUnion TownshipUnionByrd TownshipJefferson TownshipJeffersonPleasant TownshipPleasantPike TownshipWashington TownshipWashingtonHuntington TownshipHuntingtonGreen TownshipGrn31.723093%31.723093%31.7%452,292452k30.315023%30.315023%30.3%64,767,78764.8M28.952816%28.952816%29.0%13,118,64213.1M28.462853%28.462853%28.5%8,931,6868.93M26.667466%26.667466%26.7%2,092,8752.09M18.927614%18.927614%18.9%353118.769883%18.769883%18.8%177217.798913%17.798913%17.8%131317.054908%17.054908%17.1%205414.632035%14.632035%14.6%169514.340855%14.340855%14.3%483614.291864%14.291864%14.3%332713.549550%13.549550%13.5%376812.437484%12.437484%12.4%3,78012.380082%12.380082%12.4%271912.037037%12.037037%12.0%781011.804613%11.804613%11.8%871110.906258%10.906258%10.9%420129.383657%9.383657%9.4%271138.360549%8.360549%8.4%128148.239700%8.239700%8.2%154156.271626%6.271626%6.3%14516
Count number of people in category
# rank of county subdivision out of 16 by percentage of population 25 years of age and older with a bachelor's degree or higher..

Very Advanced Degrees by County Subdivision#48

Percent of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).
Scope: population of Brown County, selected county subdivisions in Brown County, and entities that contain Brown County
0%1%2%3%Count#Franklin TownshipFranklinUnited States of AmericaUnited StatesCincinnati Metro AreaCincinnatiJefferson TownshipJeffersonMidwestEast North CentralOhioScott TownshipScottJackson TownshipJacksonByrd TownshipClark TownshipClarkPerry TownshipPerryWashington TownshipWashingtonLewis TownshipLewisBrown CountyBrownUnion TownshipUnionPleasant TownshipPleasantSterling TownshipSterlingPike TownshipGreen TownshipGrnHuntington TownshipHuntingtonEagle TownshipEagle3.463203%3.463203%3.5%4013.336158%3.336158%3.3%7,127,6737.13M3.129371%3.129371%3.1%44,61744.6k2.985075%2.985075%3.0%2222.893416%2.893416%2.9%1,311,0191.31M2.855432%2.855432%2.9%896,039896k2.683241%2.683241%2.7%210,582211k2.581522%2.581522%2.6%1931.908802%1.908802%1.9%1841.234568%1.234568%1.2%851.033147%1.033147%1.0%2460.920428%0.920428%0.9%3170.914435%0.914435%0.9%1480.804290%0.804290%0.8%1590.648197%0.648197%0.6%1970.274098%0.274098%0.3%6100.000000%0.000000%0.0%0110.000000%0.000000%0.0%0120.000000%0.000000%0.0%0130.000000%0.000000%0.0%0140.000000%0.000000%0.0%0150.000000%0.000000%0.0%016
Count number of people in category
# rank of county subdivision out of 16 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#49

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 Brown County, selected county subdivisions in Brown County, and entities that contain Brown County
Female
Male
2x0x2x4xFM#JacksonLewisPleasantPike TownshipUnionGrnPerryClarkBrownHuntingtonMidwestEast North CentralCincinnatiUnited StatesOhioSterlingWashingtonByrd TownshipEagleFranklinJeffersonScott-1.000000x-1.000000x4.649644x4.649644x4.65x1.533%1.53%7.126%7.13%1-1.000000x-1.000000x2.285356x2.285356x2.29x8.295%8.29%18.957%19.0%2-1.000000x-1.000000x1.798437x1.798437x1.80x10.386%10.4%18.678%18.7%3-1.000000x-1.000000x1.714004x1.714004x1.71x12.025%12.0%20.611%20.6%4-1.000000x-1.000000x1.680790x1.680790x1.68x13.753%13.8%23.116%23.1%5-1.000000x-1.000000x1.516449x1.516449x1.52x15.990%16.0%24.248%24.2%6-1.000000x-1.000000x1.391931x1.391931x1.39x8.696%8.70%12.104%12.1%7-1.000000x-1.000000x1.350150x1.350150x1.35x13.967%14.0%18.858%18.9%8-1.000000x-1.000000x1.337562x1.337562x1.34x12.641%12.6%16.908%16.9%-1.000000x-1.000000x1.162748x1.162748x1.16x18.382%18.4%21.374%21.4%9-1.000000x-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-1.000000x1.120901x1.120901x1.12x9.396%9.40%10.532%10.5%-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-1.000000x1.016331x1.016331x1.02x10.192%10.2%10.358%10.4%10-1.000000x-1.000000x1.000403x1.000403x1.00x18.742%18.7%18.750%18.8%11-1.012158x-1.012158x1.01x1.000000x1.000000x14.286%14.3%14.114%14.1%12-1.289202x-1.289202x1.29x1.000000x1.000000x21.053%21.1%16.330%16.3%13-1.333333x-1.333333x1.33x1.000000x1.000000x11.429%11.4%8.571%8.57%14-1.335927x-1.335927x1.34x1.000000x1.000000x14.080%14.1%10.540%10.5%15-2.394152x-2.394152x2.39x1.000000x1.000000x18.158%18.2%7.584%7.58%16
F percentage of females in category
M percentage of males in category
# rank of county subdivision out of 16 by male-to-female sex ratio

Over-Education Sex Ratio by County Subdivision#50

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 Brown County, selected county subdivisions in Brown County, and entities that contain Brown County
Female
Male
10x5x0x5x10xFM#FranklinByrd TownshipClarkJeffersonOhioEast North CentralMidwestCincinnatiUnited StatesBrownScottPerryUnionLewisWashingtonJackson-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%7.143%7.14%1-1.000000x-1.000000x10.000000x10.000000x> 10.0x0.000%0%2.402%2.40%2-1.000000x-1.000000x7.066609x7.066609x7.07x0.257%0.26%1.817%1.82%3-1.000000x-1.000000x1.917003x1.917003x1.92x2.011%2.01%3.856%3.86%4-1.000000x-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-1.000000x1.582232x1.582232x1.58x2.447%2.45%3.871%3.87%-1.000000x-1.000000x1.526215x1.526215x1.53x2.660%2.66%4.060%4.06%-1.000000x-1.000000x1.335985x1.335985x1.34x0.556%0.56%0.743%0.74%-1.000000x-1.000000x1.186017x1.186017x1.19x2.368%2.37%2.809%2.81%5-1.000000x-1.000000x1.142898x1.142898x1.14x0.857%0.86%0.980%0.98%6-10.000000x-10.000000x> 10.0x1.000000x1.000000x0.497%0.50%0.000%0%7-10.000000x-10.000000x> 10.0x1.000000x1.000000x1.728%1.73%0.000%0%8-10.000000x-10.000000x> 10.0x1.000000x1.000000x1.693%1.69%0.000%0%9-10.000000x-10.000000x> 10.0x1.000000x1.000000x3.448%3.45%0.000%0%10
F percentage of females in category
M percentage of males in category
# rank of county subdivision out of 10 by male-to-female sex ratio

Educational Attainment by County in the Cincinnati Area

There are 15 counties in the Cincinnati Area. This section compares Brown County to all of the counties in the Cincinnati Area and to those entities that contain or substantially overlap with Brown County.

No H.S. Diploma by County#51

Percent of population 25 years of age and older without a high school diploma (or equivalent).
Scope: population of Brown County, selected other counties in the Cincinnati Area, and entities that contain Brown County
0%5%10%15%Count#Gallatin CountyGallatinGrant CountyGrantBracken CountyBrackenPendleton CountyPendletonBrown CountyBrownUnited States of AmericaUnited StatesUnion CountyUnionOhio CountyOhioEast North CentralKenton CountyKentonOhioClermont CountyClermontButler CountyButlerMidwestCincinnati Metro AreaCincinnatiCampbell CountyCampbellHamilton CountyHamiltonDearborn CountyDearbornBoone CountyBooneWarren CountyWarren19.668921%19.668921%19.7%1,105117.528517%17.528517%17.5%2,766216.830467%16.830467%16.8%959315.282659%15.282659%15.3%1,522414.737431%14.737431%14.7%4,479513.020590%13.020590%13.0%27,818,38027.8M11.841576%11.841576%11.8%589611.405109%11.405109%11.4%500710.719464%10.719464%10.7%3,363,7843.36M10.686537%10.686537%10.7%11,76011.8k810.514146%10.514146%10.5%825,155825k10.407526%10.407526%10.4%14,16114.2k910.314030%10.314030%10.3%24,52824.5k1010.244520%10.244520%10.2%4,641,8354.64M9.940523%9.940523%9.9%141,727142k9.937858%9.937858%9.9%6,141119.873275%9.873275%9.9%53,29153.3k129.365994%9.365994%9.4%3,185137.614095%7.614095%7.6%6,208147.119778%7.119778%7.1%10,53310.5k15
Count number of people in category
# rank of county out of 15 by percentage of population 25 years of age and older without a high school diploma (or equivalent).

Bachelor's Degrees by County#52

Percent of population 25 years of age and older with a bachelor's degree or higher..
Scope: population of Brown County, selected other counties in the Cincinnati Area, and entities that contain Brown County
0%10%20%30%40%Count#Warren CountyWarrenHamilton CountyHamiltonCincinnati Metro AreaCincinnatiBoone CountyBooneCampbell CountyCampbellUnited States of AmericaUnited StatesButler CountyButlerKenton CountyKentonMidwestEast North CentralClermont CountyClermontOhioDearborn CountyDearbornUnion CountyUnionBracken CountyBrackenOhio CountyOhioBrown CountyBrownGrant CountyGrantPendleton CountyPendletonGallatin CountyGallatin40.956469%40.956469%41.0%60,59160.6k135.595553%35.595553%35.6%192,127192k231.723093%31.723093%31.7%452,292452k31.061043%31.061043%31.1%25,32525.3k330.588730%30.588730%30.6%18,90218.9k430.315023%30.315023%30.3%64,767,78764.8M29.134358%29.134358%29.1%69,28569.3k529.093553%29.093553%29.1%32,01632.0k628.952816%28.952816%29.0%13,118,64213.1M28.462853%28.462853%28.5%8,931,6868.93M27.618418%27.618418%27.6%37,57937.6k726.667466%26.667466%26.7%2,092,8752.09M19.964124%19.964124%20.0%6,789818.556494%18.556494%18.6%923914.636715%14.636715%14.6%8341013.845803%13.845803%13.8%6071112.437484%12.437484%12.4%3,7801212.351077%12.351077%12.4%1,9491310.292198%10.292198%10.3%1,025149.967960%9.967960%10.0%56015
Count number of people in category
# rank of county out of 15 by percentage of population 25 years of age and older with a bachelor's degree or higher..

Very Advanced Degrees by County#53

Percent of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).
Scope: population of Brown County, selected other counties in the Cincinnati Area, and entities that contain Brown County
0%1%2%3%4%Count#Hamilton CountyHamiltonWarren CountyWarrenUnited States of AmericaUnited StatesCampbell CountyCampbellCincinnati Metro AreaCincinnatiMidwestEast North CentralKenton CountyKentonOhioBoone CountyBooneButler CountyButlerUnion CountyUnionClermont CountyClermontOhio CountyOhioGrant CountyGrantDearborn CountyDearbornBracken CountyBrackenPendleton CountyPendletonGallatin CountyGallatinBrown CountyBrown4.198425%4.198425%4.2%22,66122.7k13.623766%3.623766%3.6%5,36123.336158%3.336158%3.3%7,127,6737.13M3.325566%3.325566%3.3%2,05533.129371%3.129371%3.1%44,61744.6k2.893416%2.893416%2.9%1,311,0191.31M2.855432%2.855432%2.9%896,039896k2.761598%2.761598%2.8%3,03942.683241%2.683241%2.7%210,582211k2.514319%2.514319%2.5%2,05052.445209%2.445209%2.4%5,81561.950141%1.950141%2.0%9771.832213%1.832213%1.8%2,49381.459854%1.459854%1.5%6491.356147%1.356147%1.4%214101.211551%1.211551%1.2%412110.930151%0.930151%0.9%53120.692841%0.692841%0.7%69130.658597%0.658597%0.7%37140.648197%0.648197%0.6%19715
Count number of people in category
# rank of county out of 15 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#54

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 Brown County, selected other counties in the Cincinnati Area, and entities that contain Brown County
Female
Male
1x0x1xFM#BrackenUnionWarrenGrantBrownDearbornPendletonGallatinClermontKentonMidwestEast North CentralCincinnatiCampbellUnited StatesOhioBooneButlerHamiltonOhio-1.000000x-1.000000x1.532994x1.532994x1.53x13.340%13.3%20.450%20.5%1-1.000000x-1.000000x1.520984x1.520984x1.52x9.500%9.50%14.450%14.4%2-1.000000x-1.000000x1.457031x1.457031x1.46x5.811%5.81%8.466%8.47%3-1.000000x-1.000000x1.389288x1.389288x1.39x14.737%14.7%20.474%20.5%4-1.000000x-1.000000x1.337562x1.337562x1.34x12.641%12.6%16.908%16.9%5-1.000000x-1.000000x1.327840x1.327840x1.33x8.066%8.07%10.711%10.7%6-1.000000x-1.000000x1.254194x1.254194x1.25x13.571%13.6%17.021%17.0%7-1.000000x-1.000000x1.254076x1.254076x1.25x17.455%17.5%21.889%21.9%8-1.000000x-1.000000x1.219059x1.219059x1.22x9.410%9.41%11.471%11.5%9-1.000000x-1.000000x1.218252x1.218252x1.22x9.663%9.66%11.772%11.8%10-1.000000x-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-1.000000x1.120901x1.120901x1.12x9.396%9.40%10.532%10.5%-1.000000x-1.000000x1.110176x1.110176x1.11x9.440%9.44%10.480%10.5%11-1.000000x-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-1.000000x1.088050x1.088050x1.09x7.302%7.30%7.945%7.95%12-1.000000x-1.000000x1.042157x1.042157x1.04x10.109%10.1%10.535%10.5%13-1.000000x-1.000000x1.012905x1.012905x1.01x9.814%9.81%9.941%9.94%14-1.117624x-1.117624x1.12x1.000000x1.000000x12.038%12.0%10.771%10.8%15
F percentage of females in category
M percentage of males in category
# rank of county out of 15 by male-to-female sex ratio

Over-Education Sex Ratio by County#55

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 Brown County, selected other counties in the Cincinnati Area, and entities that contain Brown County
Female
Male
0x2x4x6xFM#OhioUnionBrackenCampbellButlerClermontBooneOhioHamiltonEast North CentralMidwestCincinnatiUnited StatesWarrenBrownKentonDearbornGallatinPendletonGrant-1.000000x-1.000000x6.116689x6.116689x6.12x0.410%0.41%2.510%2.51%1-1.000000x-1.000000x3.388104x3.388104x3.39x0.916%0.92%3.102%3.10%2-1.000000x-1.000000x1.856011x1.856011x1.86x0.655%0.65%1.216%1.22%3-1.000000x-1.000000x1.832612x1.832612x1.83x2.378%2.38%4.358%4.36%4-1.000000x-1.000000x1.799448x1.799448x1.80x1.767%1.77%3.179%3.18%5-1.000000x-1.000000x1.797099x1.797099x1.80x1.322%1.32%2.376%2.38%6-1.000000x-1.000000x1.702800x1.702800x1.70x1.875%1.87%3.193%3.19%7-1.000000x-1.000000x1.669500x1.669500x1.67x2.031%2.03%3.391%3.39%-1.000000x-1.000000x1.601589x1.601589x1.60x3.275%3.27%5.245%5.24%8-1.000000x-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-1.000000x1.582232x1.582232x1.58x2.447%2.45%3.871%3.87%-1.000000x-1.000000x1.526215x1.526215x1.53x2.660%2.66%4.060%4.06%-1.000000x-1.000000x1.471795x1.471795x1.47x2.940%2.94%4.327%4.33%9-1.000000x-1.000000x1.335985x1.335985x1.34x0.556%0.56%0.743%0.74%10-1.000000x-1.000000x1.288989x1.288989x1.29x2.422%2.42%3.122%3.12%11-1.000000x-1.000000x1.129378x1.129378x1.13x1.139%1.14%1.287%1.29%12-1.173125x-1.173125x1.17x1.000000x1.000000x0.711%0.71%0.606%0.61%13-1.846229x-1.846229x1.85x1.000000x1.000000x0.897%0.90%0.486%0.49%14-1.908682x-1.908682x1.91x1.000000x1.000000x1.765%1.76%0.925%0.92%15
F percentage of females in category
M percentage of males in category
# rank of county out of 15 by male-to-female sex ratio

Educational Attainment by County in Ohio

There are 88 counties in Ohio. This section compares Brown County to the 50 most populous counties in Ohio and to those entities that contain or substantially overlap with Brown County. The least populous of the compared counties has a population of 48,949.

No H.S. Diploma by County#56

Percent of population 25 years of age and older without a high school diploma (or equivalent).
Scope: population of Brown County, selected other counties in Ohio, and entities that contain Brown County
0%5%10%15%Count#Scioto CountySciotoBrown CountyBrownWayne CountyWayneAshtabula CountyAshtabulaLawrence CountyLawrenceRoss CountyRossTuscarawas CountyTuscarawasMuskingum CountyMuskingumMarion CountyMarionUnited States of AmericaUnited StatesPickaway CountyPickawayRichland CountyRichlandClark CountyClarkAshland CountyAshlandColumbiana CountyColumbianaHuron CountyHuronCuyahoga CountyCuyahogaLucas CountyLucasTrumbull CountyTrumbullDarke CountyDarkeMiami CountyMiamiLorain CountyLorainEast North CentralAllen CountyAllenSandusky CountySanduskyOhioKnox CountyKnoxClermont CountyClermontMontgomery CountyMontgomeryAthens CountyAthensButler CountyButlerMidwestBelmont CountyBelmontJefferson CountyJeffersonCincinnati Metro AreaCincinnatiMahoning CountyMahoningHamilton CountyHamiltonWashington CountyWashingtonFranklin CountyFranklinLicking CountyLickingStark CountyStarkErie CountyErieShelby CountyShelbySeneca CountySenecaSummit CountySummitGeauga CountyGeaugaFairfield CountyFairfieldPortage CountyPortageUnion CountyUnionLake CountyLakeHancock CountyHancockGreene CountyGreeneWarren CountyWarrenMedina CountyMedinaWood CountyWoodDelaware CountyDelaware15.880426%15.880426%15.9%8,436114.737431%14.737431%14.7%4,47914.573422%14.573422%14.6%11,02811.0k214.566860%14.566860%14.6%10,02210.0k314.348435%14.348435%14.3%6,144414.253056%14.253056%14.3%7,731514.068037%14.068037%14.1%9,011613.498115%13.498115%13.5%7,842713.413630%13.413630%13.4%6,192813.020590%13.020590%13.0%27,818,38027.8M12.917789%12.917789%12.9%5,036912.809922%12.809922%12.8%10,88610.9k1012.792826%12.792826%12.8%11,88311.9k1112.567763%12.567763%12.6%4,4281212.374124%12.374124%12.4%9,3021312.286515%12.286515%12.3%4,8201411.473065%11.473065%11.5%100,034100k1511.204220%11.204220%11.2%32,51732.5k1611.138115%11.138115%11.1%16,17816.2k1711.073863%11.073863%11.1%3,9311810.912923%10.912923%10.9%7,8191910.838036%10.838036%10.8%22,53022.5k2010.719464%10.719464%10.7%3,363,7843.36M10.716657%10.716657%10.7%7,4262110.672042%10.672042%10.7%4,3942210.514146%10.514146%10.5%825,155825k10.433639%10.433639%10.4%4,1242310.407526%10.407526%10.4%14,16114.2k2410.369633%10.369633%10.4%37,59537.6k2510.342892%10.342892%10.3%3,6862610.314030%10.314030%10.3%24,52824.5k2710.244520%10.244520%10.2%4,641,8354.64M10.147068%10.147068%10.1%5,1542810.108764%10.108764%10.1%4,833299.940523%9.940523%9.9%141,727142k9.896656%9.896656%9.9%16,29916.3k309.873275%9.873275%9.9%53,29153.3k319.795325%9.795325%9.8%4,245329.640656%9.640656%9.6%78,29978.3k339.609394%9.609394%9.6%10,95011.0k349.565083%9.565083%9.6%24,75324.8k359.415905%9.415905%9.4%5,057369.300022%9.300022%9.3%3,004379.244310%9.244310%9.2%3,424389.016560%9.016560%9.0%33,82433.8k398.928599%8.928599%8.9%5,691408.257364%8.257364%8.3%8,306418.081706%8.081706%8.1%8,364428.064021%8.064021%8.1%2,892438.051408%8.051408%8.1%13,15613.2k447.505079%7.505079%7.5%3,842457.394980%7.394980%7.4%8,066467.119778%7.119778%7.1%10,53310.5k476.360906%6.360906%6.4%7,689485.919879%5.919879%5.9%4,714493.378461%3.378461%3.4%4,15050
Count number of people in category
# rank of county 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#57

Percent of population 25 years of age and older with a bachelor's degree or higher..
Scope: population of Brown County, selected other counties in Ohio, and entities that contain Brown County
0%10%20%30%40%50%Count#Delaware CountyDelawareWarren CountyWarrenFranklin CountyFranklinGreene CountyGreeneGeauga CountyGeaugaHamilton CountyHamiltonCincinnati Metro AreaCincinnatiWood CountyWoodMedina CountyMedinaCuyahoga CountyCuyahogaSummit CountySummitUnited States of AmericaUnited StatesButler CountyButlerAthens CountyAthensUnion CountyUnionMidwestEast North CentralClermont CountyClermontPortage CountyPortageLake CountyLakeOhioFairfield CountyFairfieldMontgomery CountyMontgomeryHancock CountyHancockLucas CountyLucasLorain CountyLorainLicking CountyLickingMahoning CountyMahoningStark CountyStarkKnox CountyKnoxErie CountyErieWayne CountyWayneMiami CountyMiamiAshland CountyAshlandWashington CountyWashingtonClark CountyClarkTrumbull CountyTrumbullAllen CountyAllenPickaway CountyPickawayShelby CountyShelbyBelmont CountyBelmontRichland CountyRichlandJefferson CountyJeffersonRoss CountyRossMuskingum CountyMuskingumScioto CountySciotoTuscarawas CountyTuscarawasSandusky CountySanduskySeneca CountySenecaLawrence CountyLawrenceColumbiana CountyColumbianaHuron CountyHuronAshtabula CountyAshtabulaDarke CountyDarkeBrown CountyBrownMarion CountyMarion52.455693%52.455693%52.5%64,43564.4k140.956469%40.956469%41.0%60,59160.6k238.352941%38.352941%38.4%311,493311k337.647835%37.647835%37.6%41,06441.1k437.269176%37.269176%37.3%23,75523.8k535.595553%35.595553%35.6%192,127192k631.723093%31.723093%31.7%452,292452k31.682783%31.682783%31.7%25,22925.2k731.455422%31.455422%31.5%38,02338.0k830.891280%30.891280%30.9%269,342269k930.713722%30.713722%30.7%115,217115k1030.315023%30.315023%30.3%64,767,78764.8M29.134358%29.134358%29.1%69,28569.3k1129.126214%29.126214%29.1%10,38010.4k1229.091264%29.091264%29.1%10,43310.4k1328.952816%28.952816%29.0%13,118,64213.1M28.462853%28.462853%28.5%8,931,6868.93M27.618418%27.618418%27.6%37,57937.6k1427.280106%27.280106%27.3%28,23328.2k1527.039780%27.039780%27.0%44,18344.2k1626.667466%26.667466%26.7%2,092,8752.09M26.410442%26.410442%26.4%26,56626.6k1726.143225%26.143225%26.1%94,78294.8k1825.838022%25.838022%25.8%13,22713.2k1925.090190%25.090190%25.1%72,81772.8k2023.488664%23.488664%23.5%48,82848.8k2123.329326%23.329326%23.3%26,58426.6k2222.789814%22.789814%22.8%37,53337.5k2322.631528%22.631528%22.6%58,56758.6k2421.891919%21.891919%21.9%8,6532521.593088%21.593088%21.6%11,59711.6k2621.467650%21.467650%21.5%16,24516.2k2721.063797%21.063797%21.1%15,09215.1k2819.637840%19.637840%19.6%6,9192918.409212%18.409212%18.4%7,9783017.966799%17.966799%18.0%16,68916.7k3117.959504%17.959504%18.0%26,08626.1k3217.386787%17.386787%17.4%12,04812.0k3317.306656%17.306656%17.3%6,7473417.089254%17.089254%17.1%5,5203516.407773%16.407773%16.4%8,3343616.395430%16.395430%16.4%13,93313.9k3715.429826%15.429826%15.4%7,3773815.303921%15.303921%15.3%8,3013915.066182%15.066182%15.1%8,7534014.993788%14.993788%15.0%7,9654114.979782%14.979782%15.0%9,5954214.815534%14.815534%14.8%6,1004314.711520%14.711520%14.7%5,4494414.142924%14.142924%14.1%6,0564513.935855%13.935855%13.9%10,47610.5k4613.479480%13.479480%13.5%5,2884713.119186%13.119186%13.1%9,0264813.093695%13.093695%13.1%4,6484912.437484%12.437484%12.4%3,78012.295828%12.295828%12.3%5,67650
Count number of people in category
# rank of county 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#58

Percent of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).
Scope: population of Brown County, selected other counties in Ohio, and entities that contain Brown County
0%1%2%3%4%5%Count#Athens CountyAthensDelaware CountyDelawareGreene CountyGreeneFranklin CountyFranklinHamilton CountyHamiltonCuyahoga CountyCuyahogaWarren CountyWarrenWood CountyWoodUnited States of AmericaUnited StatesGeauga CountyGeaugaSummit CountySummitCincinnati Metro AreaCincinnatiLucas CountyLucasMidwestEast North CentralOhioUnion CountyUnionPortage CountyPortageKnox CountyKnoxButler CountyButlerMontgomery CountyMontgomeryLicking CountyLickingErie CountyErieMedina CountyMedinaWayne CountyWayneMahoning CountyMahoningLake CountyLakeAllen CountyAllenLorain CountyLorainStark CountyStarkHancock CountyHancockAshland CountyAshlandClermont CountyClermontFairfield CountyFairfieldJefferson CountyJeffersonWashington CountyWashingtonClark CountyClarkTrumbull CountyTrumbullRoss CountyRossScioto CountySciotoLawrence CountyLawrenceMiami CountyMiamiRichland CountyRichlandShelby CountyShelbyPickaway CountyPickawayBelmont CountyBelmontMuskingum CountyMuskingumAshtabula CountyAshtabulaColumbiana CountyColumbianaSandusky CountySanduskySeneca CountySenecaMarion CountyMarionHuron CountyHuronTuscarawas CountyTuscarawasBrown CountyBrownDarke CountyDarke5.390314%5.390314%5.4%1,92115.031057%5.031057%5.0%6,18024.454774%4.454774%4.5%4,85934.335519%4.335519%4.3%35,21235.2k44.198425%4.198425%4.2%22,66122.7k54.184410%4.184410%4.2%36,48436.5k63.623766%3.623766%3.6%5,36173.600402%3.600402%3.6%2,86783.336158%3.336158%3.3%7,127,6737.13M3.260170%3.260170%3.3%2,07893.147959%3.147959%3.1%11,80911.8k103.129371%3.129371%3.1%44,61744.6k2.925012%2.925012%2.9%8,489112.893416%2.893416%2.9%1,311,0191.31M2.855432%2.855432%2.9%896,039896k2.683241%2.683241%2.7%210,582211k2.506762%2.506762%2.5%899122.505483%2.505483%2.5%2,593132.474321%2.474321%2.5%978142.445209%2.445209%2.4%5,815152.444911%2.444911%2.4%8,864162.283438%2.283438%2.3%2,602172.256689%2.256689%2.3%1,212182.239430%2.239430%2.2%2,707192.226715%2.226715%2.2%1,685202.131251%2.131251%2.1%3,510212.086903%2.086903%2.1%3,410222.046353%2.046353%2.0%1,418232.027141%2.027141%2.0%4,214241.963406%1.963406%2.0%5,081251.906548%1.906548%1.9%976261.867567%1.867567%1.9%658271.832213%1.832213%1.8%2,493281.755659%1.755659%1.8%1,766291.604267%1.604267%1.6%767301.589865%1.589865%1.6%689311.506115%1.506115%1.5%1,399321.396223%1.396223%1.4%2,028331.281319%1.281319%1.3%695341.278190%1.278190%1.3%679351.268099%1.268099%1.3%543361.179360%1.179360%1.2%845371.166143%1.166143%1.2%991381.111421%1.111421%1.1%359391.095293%1.095293%1.1%427401.025732%1.025732%1.0%521410.984560%0.984560%1.0%572420.899709%0.899709%0.9%619430.895268%0.895268%0.9%673440.871931%0.871931%0.9%359450.861254%0.861254%0.9%319460.847017%0.847017%0.8%391470.830997%0.830997%0.8%326480.771236%0.771236%0.8%494490.648197%0.648197%0.6%1970.546510%0.546510%0.5%19450
Count number of people in category
# rank of county 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#59

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 Brown County, selected other counties in Ohio, and entities that contain Brown County
Female
Male
1x0x1xFM#PickawayWarrenRichlandShelbyBrownAthensHancockMarionClermontLorainTuscarawasDelawareHuronKnoxAshlandMuskingumLucasMahoningTrumbullWayneGeaugaClarkLawrenceDarkeLakeMidwestEast North CentralBelmontAshtabulaCincinnatiWashingtonUnited StatesOhioMedinaRossSanduskyErieCuyahogaAllenFranklinFairfieldButlerLickingMontgomeryPortageSciotoStarkSenecaHamiltonJeffersonColumbianaGreeneSummitWoodMiamiUnion-1.000000x-1.000000x1.597241x1.597241x1.60x9.831%9.83%15.703%15.7%1-1.000000x-1.000000x1.457031x1.457031x1.46x5.811%5.81%8.466%8.47%2-1.000000x-1.000000x1.428027x1.428027x1.43x10.554%10.6%15.071%15.1%3-1.000000x-1.000000x1.355020x1.355020x1.36x7.910%7.91%10.718%10.7%4-1.000000x-1.000000x1.337562x1.337562x1.34x12.641%12.6%16.908%16.9%-1.000000x-1.000000x1.239662x1.239662x1.24x9.239%9.24%11.453%11.5%5-1.000000x-1.000000x1.228711x1.228711x1.23x6.756%6.76%8.301%8.30%6-1.000000x-1.000000x1.222802x1.222802x1.22x11.988%12.0%14.658%14.7%7-1.000000x-1.000000x1.219059x1.219059x1.22x9.410%9.41%11.471%11.5%8-1.000000x-1.000000x1.216863x1.216863x1.22x9.813%9.81%11.941%11.9%9-1.000000x-1.000000x1.212065x1.212065x1.21x12.766%12.8%15.474%15.5%10-1.000000x-1.000000x1.204437x1.204437x1.20x3.074%3.07%3.703%3.70%11-1.000000x-1.000000x1.201209x1.201209x1.20x11.198%11.2%13.451%13.5%12-1.000000x-1.000000x1.196265x1.196265x1.20x9.533%9.53%11.404%11.4%13-1.000000x-1.000000x1.194357x1.194357x1.19x11.488%11.5%13.721%13.7%14-1.000000x-1.000000x1.190045x1.190045x1.19x12.386%12.4%14.740%14.7%15-1.000000x-1.000000x1.169306x1.169306x1.17x10.373%10.4%12.129%12.1%16-1.000000x-1.000000x1.158437x1.158437x1.16x9.203%9.20%10.662%10.7%17-1.000000x-1.000000x1.157733x1.157733x1.16x10.358%10.4%11.992%12.0%18-1.000000x-1.000000x1.151379x1.151379x1.15x13.576%13.6%15.631%15.6%19-1.000000x-1.000000x1.151241x1.151241x1.15x8.319%8.32%9.577%9.58%20-1.000000x-1.000000x1.150715x1.150715x1.15x11.939%11.9%13.739%13.7%21-1.000000x-1.000000x1.140157x1.140157x1.14x13.451%13.5%15.336%15.3%22-1.000000x-1.000000x1.139879x1.139879x1.14x10.372%10.4%11.823%11.8%23-1.000000x-1.000000x1.134887x1.134887x1.13x7.564%7.56%8.584%8.58%24-1.000000x-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-1.000000x1.122752x1.122752x1.12x9.558%9.56%10.731%10.7%25-1.000000x-1.000000x1.121822x1.121822x1.12x13.739%13.7%15.412%15.4%26-1.000000x-1.000000x1.120901x1.120901x1.12x9.396%9.40%10.532%10.5%-1.000000x-1.000000x1.116980x1.116980x1.12x9.270%9.27%10.354%10.4%27-1.000000x-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-1.000000x1.104033x1.104033x1.10x6.055%6.06%6.685%6.69%28-1.000000x-1.000000x1.090568x1.090568x1.09x13.607%13.6%14.839%14.8%29-1.000000x-1.000000x1.079648x1.079648x1.08x10.276%10.3%11.095%11.1%30-1.000000x-1.000000x1.070676x1.070676x1.07x9.106%9.11%9.749%9.75%31-1.000000x-1.000000x1.068330x1.068330x1.07x11.121%11.1%11.881%11.9%32-1.000000x-1.000000x1.067772x1.067772x1.07x10.371%10.4%11.074%11.1%33-1.000000x-1.000000x1.059046x1.059046x1.06x9.376%9.38%9.930%9.93%34-1.000000x-1.000000x1.047665x1.047665x1.05x8.071%8.07%8.455%8.46%35-1.000000x-1.000000x1.042157x1.042157x1.04x10.109%10.1%10.535%10.5%36-1.000000x-1.000000x1.041562x1.041562x1.04x9.421%9.42%9.813%9.81%37-1.000000x-1.000000x1.037009x1.037009x1.04x10.193%10.2%10.570%10.6%38-1.000000x-1.000000x1.036905x1.036905x1.04x7.939%7.94%8.232%8.23%39-1.000000x-1.000000x1.033630x1.033630x1.03x15.627%15.6%16.153%16.2%40-1.000000x-1.000000x1.031161x1.031161x1.03x9.426%9.43%9.720%9.72%41-1.000000x-1.000000x1.020140x1.020140x1.02x9.155%9.15%9.339%9.34%42-1.000000x-1.000000x1.012905x1.012905x1.01x9.814%9.81%9.941%9.94%43-1.000000x-1.000000x1.004137x1.004137x1.00x10.089%10.1%10.131%10.1%44-1.022047x-1.022047x1.02x1.000000x1.000000x12.509%12.5%12.239%12.2%45-1.030592x-1.030592x1.03x1.000000x1.000000x7.503%7.50%7.280%7.28%46-1.057764x-1.057764x1.06x1.000000x1.000000x9.256%9.26%8.751%8.75%47-1.088790x-1.088790x1.09x1.000000x1.000000x6.164%6.16%5.661%5.66%48-1.131015x-1.131015x1.13x1.000000x1.000000x11.559%11.6%10.220%10.2%49-1.420116x-1.420116x1.42x1.000000x1.000000x9.358%9.36%6.590%6.59%50
F percentage of females in category
M percentage of males in category
# rank of county out of 50 by male-to-female sex ratio

Over-Education Sex Ratio by County#60

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 Brown County, selected other counties in Ohio, and entities that contain Brown County
Female
Male
1x0x1x2x3xFM#MiamiColumbianaClarkJeffersonLawrenceAshtabulaMahoningWashingtonMontgomeryErieLorainBelmontAthensGreeneHancockGeaugaSciotoRichlandPortageDarkeButlerClermontTrumbullAllenCuyahogaOhioStarkWayneWoodAshlandSenecaTuscarawasDelawareFairfieldSummitHamiltonEast North CentralMuskingumMidwestCincinnatiFranklinHuronUnited StatesShelbyUnionRossKnoxWarrenLickingLakeLucasMedinaBrownPickawaySanduskyMarion-1.000000x-1.000000x3.501312x3.501312x3.50x0.534%0.53%1.871%1.87%1-1.000000x-1.000000x3.345227x3.345227x3.35x0.412%0.41%1.379%1.38%2-1.000000x-1.000000x2.838033x2.838033x2.84x0.805%0.80%2.284%2.28%3-1.000000x-1.000000x2.291361x2.291361x2.29x0.992%0.99%2.274%2.27%4-1.000000x-1.000000x2.274678x2.274678x2.27x0.789%0.79%1.795%1.79%5-1.000000x-1.000000x2.235629x2.235629x2.24x0.558%0.56%1.248%1.25%6-1.000000x-1.000000x2.218047x2.218047x2.22x1.350%1.35%2.994%2.99%7-1.000000x-1.000000x2.165620x2.165620x2.17x1.016%1.02%2.200%2.20%8-1.000000x-1.000000x2.146385x2.146385x2.15x1.591%1.59%3.414%3.41%9-1.000000x-1.000000x2.105141x2.105141x2.11x1.473%1.47%3.100%3.10%10-1.000000x-1.000000x2.086342x2.086342x2.09x1.331%1.33%2.776%2.78%11-1.000000x-1.000000x2.063493x2.063493x2.06x0.669%0.67%1.380%1.38%12-1.000000x-1.000000x2.046436x2.046436x2.05x3.542%3.54%7.249%7.25%13-1.000000x-1.000000x2.003204x2.003204x2.00x2.999%3.00%6.008%6.01%14-1.000000x-1.000000x1.977220x1.977220x1.98x1.293%1.29%2.557%2.56%15-1.000000x-1.000000x1.957255x1.957255x1.96x2.227%2.23%4.360%4.36%16-1.000000x-1.000000x1.939604x1.939604x1.94x0.880%0.88%1.706%1.71%17-1.000000x-1.000000x1.868071x1.868071x1.87x0.813%0.81%1.520%1.52%18-1.000000x-1.000000x1.859489x1.859489x1.86x1.765%1.77%3.283%3.28%19-1.000000x-1.000000x1.849233x1.849233x1.85x0.387%0.39%0.716%0.72%20-1.000000x-1.000000x1.799448x1.799448x1.80x1.767%1.77%3.179%3.18%21-1.000000x-1.000000x1.797099x1.797099x1.80x1.322%1.32%2.376%2.38%22-1.000000x-1.000000x1.771358x1.771358x1.77x1.021%1.02%1.808%1.81%23-1.000000x-1.000000x1.732122x1.732122x1.73x1.505%1.50%2.606%2.61%24-1.000000x-1.000000x1.683297x1.683297x1.68x3.179%3.18%5.351%5.35%25-1.000000x-1.000000x1.669500x1.669500x1.67x2.031%2.03%3.391%3.39%-1.000000x-1.000000x1.666317x1.666317x1.67x1.492%1.49%2.486%2.49%26-1.000000x-1.000000x1.658480x1.658480x1.66x1.687%1.69%2.798%2.80%27-1.000000x-1.000000x1.654546x1.654546x1.65x2.731%2.73%4.519%4.52%28-1.000000x-1.000000x1.646276x1.646276x1.65x1.423%1.42%2.343%2.34%29-1.000000x-1.000000x1.645493x1.645493x1.65x0.656%0.66%1.079%1.08%30-1.000000x-1.000000x1.642114x1.642114x1.64x0.589%0.59%0.968%0.97%31-1.000000x-1.000000x1.634773x1.634773x1.63x3.849%3.85%6.292%6.29%32-1.000000x-1.000000x1.623998x1.623998x1.62x1.348%1.35%2.189%2.19%33-1.000000x-1.000000x1.609994x1.609994x1.61x2.442%2.44%3.932%3.93%34-1.000000x-1.000000x1.601589x1.601589x1.60x3.275%3.27%5.245%5.24%35-1.000000x-1.000000x1.597848x1.597848x1.60x2.216%2.22%3.541%3.54%-1.000000x-1.000000x1.590424x1.590424x1.59x0.770%0.77%1.224%1.22%36-1.000000x-1.000000x1.589934x1.589934x1.59x2.251%2.25%3.579%3.58%-1.000000x-1.000000x1.582232x1.582232x1.58x2.447%2.45%3.871%3.87%-1.000000x-1.000000x1.567965x1.567965x1.57x3.409%3.41%5.346%5.35%37-1.000000x-1.000000x1.532147x1.532147x1.53x0.661%0.66%1.013%1.01%38-1.000000x-1.000000x1.526215x1.526215x1.53x2.660%2.66%4.060%4.06%-1.000000x-1.000000x1.522652x1.522652x1.52x0.883%0.88%1.344%1.34%39-1.000000x-1.000000x1.506598x1.506598x1.51x2.027%2.03%3.053%3.05%40-1.000000x-1.000000x1.490387x1.490387x1.49x1.019%1.02%1.519%1.52%41-1.000000x-1.000000x1.481268x1.481268x1.48x2.009%2.01%2.976%2.98%42-1.000000x-1.000000x1.471795x1.471795x1.47x2.940%2.94%4.327%4.33%43-1.000000x-1.000000x1.469621x1.469621x1.47x1.863%1.86%2.738%2.74%44-1.000000x-1.000000x1.461851x1.461851x1.46x1.709%1.71%2.499%2.50%45-1.000000x-1.000000x1.435534x1.435534x1.44x2.425%2.43%3.481%3.48%46-1.000000x-1.000000x1.406400x1.406400x1.41x1.871%1.87%2.631%2.63%47-1.000000x-1.000000x1.335985x1.335985x1.34x0.556%0.56%0.743%0.74%-1.000000x-1.000000x1.250193x1.250193x1.25x0.968%0.97%1.210%1.21%48-1.000000x-1.000000x1.242747x1.242747x1.24x0.780%0.78%0.970%0.97%49-1.000000x-1.000000x1.220919x1.220919x1.22x0.758%0.76%0.925%0.93%50
F percentage of females in category
M percentage of males in category
# rank of county out of 50 by male-to-female sex ratio

Educational Attainment by County in the United States

There are 3,142 counties in the United States. This section compares Brown County to the 50 most populous counties in the United States and to those entities that contain or substantially overlap with Brown County. The least populous of the compared counties has a population of 941,618.

No H.S. Diploma by County#61

Percent of population 25 years of age and older without a high school diploma (or equivalent).
Scope: population of Brown County, selected other counties in the United States, and entities that contain Brown County
0%10%20%Count#Bronx CountyBronxFresno CountyFresnoLos Angeles CountyLos AngelesDallas CountyDallasSan Bernardino CountySan BernardinoKings CountyKingsHarris CountyHarrisRiverside CountyRiversideMiami-Dade CountyMiami-DadeQueens CountyQueensPhiladelphia CountyPhiladelphiaBexar CountyBexarOrange CountyOrangeClark CountyClarkWayne CountyWayneTarrant CountyTarrantBrown CountyBrownCook CountyCookSan Diego CountySan DiegoSacramento CountySacramentoMilwaukee CountyMilwaukeeMaricopa CountyMaricopaUnited States of AmericaUnited StatesNew York CountyNew YorkSanta Clara CountySanta ClaraAlameda CountyAlamedaWestchester CountyWestchesterOrange CountyOrangePima CountyPimaHillsborough CountyHillsboroughPalm Beach CountyPalm BeachTravis CountyTravisBroward CountyBrowardCuyahoga CountyCuyahogaContra Costa CountyContra CostaEast North CentralOhioMecklenburg CountyMecklenburgMidwestSalt Lake CountySalt LakeFairfield CountyFairfieldSuffolk CountySuffolkCincinnati Metro AreaCincinnatiFranklin CountyFranklinNassau CountyNassauHonolulu CountyHonoluluMontgomery CountyMontgomeryFulton CountyFultonFairfax CountyFairfaxWake CountyWakeKing CountyKingMiddlesex CountyMiddlesexHennepin CountyHennepinSt. Louis CountySt. LouisOakland CountyOaklandAllegheny CountyAllegheny28.837398%28.837398%28.8%261,022261k126.224410%26.224410%26.2%151,875152k222.282470%22.282470%22.3%1,495,6171.50M321.975765%21.975765%22.0%349,434349k421.207718%21.207718%21.2%274,381274k520.017506%20.017506%20.0%351,046351k619.839074%19.839074%19.8%554,024554k719.521191%19.521191%19.5%286,746287k819.375775%19.375775%19.4%362,252362k919.344706%19.344706%19.3%315,505316k1017.390838%17.390838%17.4%180,039180k1116.576437%16.576437%16.6%194,124194k1215.490423%15.490423%15.5%325,372325k1315.108430%15.108430%15.1%210,261210k1414.881687%14.881687%14.9%173,869174k1514.774230%14.774230%14.8%182,543183k1614.737431%14.737431%14.7%4,47914.189351%14.189351%14.2%503,252503k1713.598133%13.598133%13.6%293,959294k1813.220947%13.220947%13.2%129,386129k1913.092854%13.092854%13.1%81,52281.5k2013.051927%13.051927%13.1%348,801349k2113.020590%13.020590%13.0%27,818,38027.8M12.996284%12.996284%13.0%160,845161k2212.928824%12.928824%12.9%166,105166k2312.700590%12.700590%12.7%141,393141k2412.397264%12.397264%12.4%81,98182.0k2512.319191%12.319191%12.3%101,664102k2612.252238%12.252238%12.3%81,21881.2k2712.196236%12.196236%12.2%108,416108k2812.054893%12.054893%12.1%122,162122k2911.841956%11.841956%11.8%90,92190.9k3011.688725%11.688725%11.7%152,462152k3111.473065%11.473065%11.5%100,034100k3210.940787%10.940787%10.9%82,37182.4k3310.719464%10.719464%10.7%3,363,7843.36M10.514146%10.514146%10.5%825,155825k10.377895%10.377895%10.4%69,51069.5k3410.244520%10.244520%10.2%4,641,8354.64M10.238253%10.238253%10.2%69,21169.2k3510.103521%10.103521%10.1%64,29864.3k369.992975%9.992975%10.0%102,414102k379.940523%9.940523%9.9%141,727142k9.640656%9.640656%9.6%78,29978.3k389.121758%9.121758%9.1%85,26785.3k398.945780%8.945780%8.9%60,28460.3k408.836226%8.836226%8.8%62,20562.2k418.677323%8.677323%8.7%57,57157.6k428.282040%8.282040%8.3%63,67163.7k437.696387%7.696387%7.7%50,50850.5k447.543133%7.543133%7.5%110,490110k457.360151%7.360151%7.4%80,37880.4k467.173605%7.173605%7.2%59,66059.7k477.049887%7.049887%7.0%48,46648.5k486.540987%6.540987%6.5%56,30256.3k496.132273%6.132273%6.1%53,97454.0k50
Count number of people in category
# rank of county 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#62

Percent of population 25 years of age and older with a bachelor's degree or higher..
Scope: population of Brown County, selected other counties in the United States, and entities that contain Brown County
0%20%40%60%Count#New York CountyNew YorkFairfax CountyFairfaxMontgomery CountyMontgomeryMiddlesex CountyMiddlesexWake CountyWakeFulton CountyFultonSanta Clara CountySanta ClaraKing CountyKingHennepin CountyHennepinWestchester CountyWestchesterTravis CountyTravisFairfield CountyFairfieldOakland CountyOaklandAlameda CountyAlamedaNassau CountyNassauMecklenburg CountyMecklenburgSt. Louis CountySt. LouisContra Costa CountyContra CostaAllegheny CountyAlleghenyOrange CountyOrangeFranklin CountyFranklinSan Diego CountySan DiegoCook CountyCookSuffolk CountySuffolkPalm Beach CountyPalm BeachKings CountyKingsHonolulu CountyHonoluluSalt Lake CountySalt LakeOrange CountyOrangeCincinnati Metro AreaCincinnatiHillsborough CountyHillsboroughBroward CountyBrowardMaricopa CountyMaricopaCuyahoga CountyCuyahogaPima CountyPimaLos Angeles CountyLos AngelesTarrant CountyTarrantQueens CountyQueensUnited States of AmericaUnited StatesHarris CountyHarrisMilwaukee CountyMilwaukeeDallas CountyDallasSacramento CountySacramentoMidwestEast North CentralMiami-Dade CountyMiami-DadeBexar CountyBexarOhioPhiladelphia CountyPhiladelphiaClark CountyClarkWayne CountyWayneRiverside CountyRiversideFresno CountyFresnoSan Bernardino CountySan BernardinoBronx CountyBronxBrown CountyBrown60.434640%60.434640%60.4%747,953748k160.260099%60.260099%60.3%463,270463k258.105449%58.105449%58.1%409,049409k353.004569%53.004569%53.0%578,847579k450.070856%50.070856%50.1%328,593329k549.806094%49.806094%49.8%330,446330k649.103299%49.103299%49.1%630,862631k749.055555%49.055555%49.1%718,554719k847.581343%47.581343%47.6%395,715396k947.303651%47.303651%47.3%312,811313k1046.446606%46.446606%46.4%356,611357k1146.362462%46.362462%46.4%295,047295k1245.020952%45.020952%45.0%387,521388k1343.887830%43.887830%43.9%488,594489k1443.543885%43.543885%43.5%407,033407k1543.097901%43.097901%43.1%288,665289k1642.382090%42.382090%42.4%291,365291k1740.269631%40.269631%40.3%303,182303k1839.069581%39.069581%39.1%343,876344k1938.447168%38.447168%38.4%807,572808k2038.352941%38.352941%38.4%311,493311k2136.494430%36.494430%36.5%788,922789k2236.471153%36.471153%36.5%1,293,5181.29M2334.384794%34.384794%34.4%352,396352k2434.188819%34.188819%34.2%346,463346k2534.081468%34.081468%34.1%597,685598k2633.350646%33.350646%33.4%224,744225k2732.800693%32.800693%32.8%221,734222k2831.922850%31.922850%31.9%263,443263k2931.723093%31.723093%31.7%452,292452k31.433296%31.433296%31.4%279,420279k3031.015731%31.015731%31.0%404,554405k3130.968863%30.968863%31.0%827,615828k3230.891280%30.891280%30.9%269,342269k3330.800609%30.800609%30.8%204,172204k3430.764105%30.764105%30.8%2,064,9112.06M3530.734653%30.734653%30.7%379,742380k3630.595789%30.595789%30.6%499,006499k3730.315023%30.315023%30.3%64,767,78764.8M30.076273%30.076273%30.1%839,907840k3829.748251%29.748251%29.7%185,226185k3929.683200%29.683200%29.7%471,989472k4029.283682%29.283682%29.3%286,583287k4128.952816%28.952816%29.0%13,118,64213.1M28.462853%28.462853%28.5%8,931,6868.93M27.281635%27.281635%27.3%510,061510k4226.926164%26.926164%26.9%315,328315k4326.667466%26.667466%26.7%2,092,8752.09M26.349720%26.349720%26.3%272,786273k4422.823853%22.823853%22.8%317,635318k4522.338065%22.338065%22.3%260,985261k4621.189043%21.189043%21.2%311,245311k4719.731980%19.731980%19.7%114,275114k4819.317210%19.317210%19.3%249,922250k4919.131504%19.131504%19.1%173,169173k5012.437484%12.437484%12.4%3,780
Count number of people in category
# rank of county 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#63

Percent of population 25 years of age and older with a professional or doctorate degree (e.g., MBA, PhD, or MD).
Scope: population of Brown County, selected other counties in the United States, and entities that contain Brown County
0%5%10%Count#Montgomery CountyMontgomeryNew York CountyNew YorkMiddlesex CountyMiddlesexFairfax CountyFairfaxWestchester CountyWestchesterSanta Clara CountySanta ClaraNassau CountyNassauAlameda CountyAlamedaFulton CountyFultonKing CountyKingFairfield CountyFairfieldSt. Louis CountySt. LouisOakland CountyOaklandHennepin CountyHennepinTravis CountyTravisAllegheny CountyAlleghenyContra Costa CountyContra CostaWake CountyWakeSan Diego CountySan DiegoPalm Beach CountyPalm BeachOrange CountyOrangeFranklin CountyFranklinCook CountyCookCuyahoga CountyCuyahogaPima CountyPimaHonolulu CountyHonoluluSuffolk CountySuffolkMiami-Dade CountyMiami-DadeSalt Lake CountySalt LakePhiladelphia CountyPhiladelphiaLos Angeles CountyLos AngelesMecklenburg CountyMecklenburgBroward CountyBrowardHillsborough CountyHillsboroughKings CountyKingsHarris CountyHarrisUnited States of AmericaUnited StatesSacramento CountySacramentoCincinnati Metro AreaCincinnatiMaricopa CountyMaricopaDallas CountyDallasOrange CountyOrangeMilwaukee CountyMilwaukeeMidwestEast North CentralBexar CountyBexarQueens CountyQueensOhioFresno CountyFresnoTarrant CountyTarrantClark CountyClarkRiverside CountyRiversideWayne CountyWayneSan Bernardino CountySan BernardinoBronx CountyBronxBrown CountyBrown12.399695%12.399695%12.4%87,29187.3k110.788423%10.788423%10.8%133,520134k28.541485%8.541485%8.5%93,27993.3k37.784891%7.784891%7.8%59,84959.8k47.604460%7.604460%7.6%50,28750.3k56.177550%6.177550%6.2%79,36779.4k65.833659%5.833659%5.8%54,53154.5k75.762347%5.762347%5.8%64,15164.2k85.719518%5.719518%5.7%37,94737.9k95.673632%5.673632%5.7%83,10683.1k105.463614%5.463614%5.5%34,77034.8k115.244723%5.244723%5.2%36,05636.1k125.214131%5.214131%5.2%44,88144.9k135.193709%5.193709%5.2%43,19443.2k145.061951%5.061951%5.1%38,86538.9k155.039180%5.039180%5.0%44,35344.4k164.956168%4.956168%5.0%37,31437.3k174.892146%4.892146%4.9%32,10532.1k184.749001%4.749001%4.7%102,662103k194.475020%4.475020%4.5%45,34945.3k204.348784%4.348784%4.3%91,34591.3k214.335519%4.335519%4.3%35,21235.2k224.239617%4.239617%4.2%150,366150k234.184410%4.184410%4.2%36,48436.5k244.139192%4.139192%4.1%27,43827.4k253.970725%3.970725%4.0%26,75826.8k263.962200%3.962200%4.0%40,60740.6k273.784527%3.784527%3.8%70,75670.8k283.768025%3.768025%3.8%25,47225.5k293.720350%3.720350%3.7%38,51538.5k303.604427%3.604427%3.6%241,932242k313.598297%3.598297%3.6%24,10124.1k323.517075%3.517075%3.5%45,87545.9k333.474402%3.474402%3.5%30,88530.9k343.384967%3.384967%3.4%59,36259.4k353.344637%3.344637%3.3%93,40293.4k363.336158%3.336158%3.3%7,127,6737.13M3.266254%3.266254%3.3%31,96532.0k373.129371%3.129371%3.1%44,61744.6k3.113482%3.113482%3.1%83,20583.2k383.037379%3.037379%3.0%48,29748.3k392.990491%2.990491%3.0%24,67924.7k402.985811%2.985811%3.0%18,59118.6k412.893416%2.893416%2.9%1,311,0191.31M2.855432%2.855432%2.9%896,039896k2.818073%2.818073%2.8%33,00233.0k422.756960%2.756960%2.8%44,96545.0k432.683241%2.683241%2.7%210,582211k2.392530%2.392530%2.4%13,85613.9k442.368743%2.368743%2.4%29,26729.3k452.315475%2.315475%2.3%32,22432.2k462.260473%2.260473%2.3%33,20433.2k472.178386%2.178386%2.2%25,45125.5k481.852789%1.852789%1.9%23,97124.0k491.664253%1.664253%1.7%15,06415.1k500.648197%0.648197%0.6%197
Count number of people in category
# rank of county 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#64

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 Brown County, selected other counties in the United States, and entities that contain Brown County
Female
Male
1x0x1xFM#BrownMecklenburgPalm BeachWakeWestchesterFairfieldContra CostaHillsboroughFresnoMidwestEast North CentralDallasCincinnatiSuffolkMilwaukeeWayneUnited StatesOhioOrangeHarrisFultonPhiladelphiaSan BernardinoTarrantCookMaricopaCuyahogaTravisBrowardRiversideOaklandNassauSalt LakeFranklinSacramentoMontgomeryBronxMiddlesexKingsFairfaxBexarPimaKingLos AngelesClarkOrangeSt. LouisHennepinMiami-DadeQueensAlamedaAlleghenyNew YorkSan DiegoSanta ClaraHonolulu-1.000000x-1.000000x1.337562x1.337562x1.34x12.641%12.6%16.908%16.9%-1.000000x-1.000000x1.282326x1.282326x1.28x9.163%9.16%11.750%11.7%1-1.000000x-1.000000x1.244689x1.244689x1.24x10.804%10.8%13.447%13.4%2-1.000000x-1.000000x1.180227x1.180227x1.18x7.089%7.09%8.367%8.37%3-1.000000x-1.000000x1.161379x1.161379x1.16x11.523%11.5%13.383%13.4%4-1.000000x-1.000000x1.158198x1.158198x1.16x9.397%9.40%10.884%10.9%5-1.000000x-1.000000x1.145263x1.145263x1.15x10.231%10.2%11.718%11.7%6-1.000000x-1.000000x1.132218x1.132218x1.13x11.472%11.5%12.989%13.0%7-1.000000x-1.000000x1.130389x1.130389x1.13x24.647%24.6%27.860%27.9%8-1.000000x-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-1.000000x1.120951x1.120951x1.12x20.762%20.8%23.273%23.3%9-1.000000x-1.000000x1.120901x1.120901x1.12x9.396%9.40%10.532%10.5%-1.000000x-1.000000x1.117209x1.117209x1.12x9.458%9.46%10.567%10.6%10-1.000000x-1.000000x1.111013x1.111013x1.11x12.441%12.4%13.822%13.8%11-1.000000x-1.000000x1.109962x1.109962x1.11x14.154%14.2%15.710%15.7%12-1.000000x-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-1.000000x1.101852x1.101852x1.10x11.740%11.7%12.936%12.9%13-1.000000x-1.000000x1.098530x1.098530x1.10x18.925%18.9%20.790%20.8%14-1.000000x-1.000000x1.090368x1.090368x1.09x8.321%8.32%9.073%9.07%15-1.000000x-1.000000x1.090163x1.090163x1.09x16.700%16.7%18.206%18.2%16-1.000000x-1.000000x1.084622x1.084622x1.08x20.369%20.4%22.092%22.1%17-1.000000x-1.000000x1.079174x1.079174x1.08x14.234%14.2%15.361%15.4%18-1.000000x-1.000000x1.079067x1.079067x1.08x13.676%13.7%14.757%14.8%19-1.000000x-1.000000x1.072566x1.072566x1.07x12.608%12.6%13.523%13.5%20-1.000000x-1.000000x1.068330x1.068330x1.07x11.121%11.1%11.881%11.9%21-1.000000x-1.000000x1.066137x1.066137x1.07x11.462%11.5%12.220%12.2%22-1.000000x-1.000000x1.065180x1.065180x1.07x11.337%11.3%12.076%12.1%23-1.000000x-1.000000x1.064463x1.064463x1.06x18.923%18.9%20.143%20.1%24-1.000000x-1.000000x1.062700x1.062700x1.06x6.352%6.35%6.750%6.75%25-1.000000x-1.000000x1.061865x1.061865x1.06x8.863%8.86%9.411%9.41%26-1.000000x-1.000000x1.061606x1.061606x1.06x9.934%9.93%10.546%10.5%27-1.000000x-1.000000x1.059046x1.059046x1.06x9.376%9.38%9.930%9.93%28-1.000000x-1.000000x1.056584x1.056584x1.06x12.873%12.9%13.601%13.6%29-1.000000x-1.000000x1.048432x1.048432x1.05x8.640%8.64%9.059%9.06%30-1.000000x-1.000000x1.030539x1.030539x1.03x28.448%28.4%29.316%29.3%31-1.000000x-1.000000x1.025105x1.025105x1.03x7.273%7.27%7.455%7.46%32-1.000000x-1.000000x1.018960x1.018960x1.02x19.845%19.8%20.221%20.2%33-1.000000x-1.000000x1.016052x1.016052x1.02x8.218%8.22%8.350%8.35%34-1.000000x-1.000000x1.009187x1.009187x1.01x16.504%16.5%16.655%16.7%35-1.000000x-1.000000x1.001235x1.001235x1.00x12.245%12.2%12.260%12.3%36-1.004399x-1.004399x1.00x1.000000x1.000000x7.560%7.56%7.526%7.53%37-1.004399x-1.004399x1.00x1.000000x1.000000x22.330%22.3%22.232%22.2%38-1.008231x-1.008231x1.01x1.000000x1.000000x15.170%15.2%15.046%15.0%39-1.015422x-1.015422x1.02x1.000000x1.000000x15.605%15.6%15.368%15.4%40-1.015859x-1.015859x1.02x1.000000x1.000000x7.101%7.10%6.990%6.99%41-1.016401x-1.016401x1.02x1.000000x1.000000x7.230%7.23%7.114%7.11%42-1.022059x-1.022059x1.02x1.000000x1.000000x19.576%19.6%19.154%19.2%43-1.027762x-1.027762x1.03x1.000000x1.000000x19.596%19.6%19.067%19.1%44-1.029280x-1.029280x1.03x1.000000x1.000000x12.877%12.9%12.511%12.5%45-1.033862x-1.033862x1.03x1.000000x1.000000x6.229%6.23%6.025%6.02%46-1.044246x-1.044246x1.04x1.000000x1.000000x13.260%13.3%12.698%12.7%47-1.097207x-1.097207x1.10x1.000000x1.000000x14.217%14.2%12.958%13.0%48-1.110312x-1.110312x1.11x1.000000x1.000000x13.602%13.6%12.250%12.3%49-1.156494x-1.156494x1.16x1.000000x1.000000x9.584%9.58%8.287%8.29%50
F percentage of females in category
M percentage of males in category
# rank of county out of 50 by male-to-female sex ratio

Over-Education Sex Ratio by County#65

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 Brown County, selected other counties in the United States, and entities that contain Brown County
Female
Male
1x0x1x2xFM#Palm BeachSalt LakeSt. LouisOaklandMaricopaCuyahogaOrangeOhioBexarMontgomeryPimaSuffolkRiversideDallasWestchesterTarrantFairfieldEast North CentralAlleghenyMidwestCincinnatiNassauBrowardClarkFranklinMecklenburgFairfaxWayneUnited StatesSanta ClaraFultonContra CostaMilwaukeeSan DiegoOrangeFresnoHillsboroughHarrisMiami-DadeHennepinTravisLos AngelesCookWakeAlamedaMiddlesexKingPhiladelphiaBrownSan BernardinoHonoluluQueensSacramentoKingsNew YorkBronx-1.000000x-1.000000x2.101230x2.101230x2.10x2.942%2.94%6.181%6.18%1-1.000000x-1.000000x2.085261x2.085261x2.09x2.448%2.45%5.105%5.11%2-1.000000x-1.000000x1.898944x1.898944x1.90x3.714%3.71%7.052%7.05%3-1.000000x-1.000000x1.827444x1.827444x1.83x3.743%3.74%6.840%6.84%4-1.000000x-1.000000x1.685640x1.685640x1.69x2.336%2.34%3.937%3.94%5-1.000000x-1.000000x1.683297x1.683297x1.68x3.179%3.18%5.351%5.35%6-1.000000x-1.000000x1.678378x1.678378x1.68x2.251%2.25%3.778%3.78%7-1.000000x-1.000000x1.669500x1.669500x1.67x2.031%2.03%3.391%3.39%-1.000000x-1.000000x1.660749x1.660749x1.66x2.139%2.14%3.552%3.55%8-1.000000x-1.000000x1.654377x1.654377x1.65x9.490%9.49%15.700%15.7%9-1.000000x-1.000000x1.652714x1.652714x1.65x3.148%3.15%5.202%5.20%10-1.000000x-1.000000x1.626700x1.626700x1.63x3.043%3.04%4.950%4.95%11-1.000000x-1.000000x1.619416x1.619416x1.62x1.734%1.73%2.808%2.81%12-1.000000x-1.000000x1.609547x1.609547x1.61x2.346%2.35%3.776%3.78%13-1.000000x-1.000000x1.607280x1.607280x1.61x5.915%5.92%9.508%9.51%14-1.000000x-1.000000x1.602206x1.602206x1.60x1.838%1.84%2.945%2.95%15-1.000000x-1.000000x1.600562x1.600562x1.60x4.251%4.25%6.804%6.80%16-1.000000x-1.000000x1.597848x1.597848x1.60x2.216%2.22%3.541%3.54%-1.000000x-1.000000x1.596070x1.596070x1.60x3.932%3.93%6.276%6.28%17-1.000000x-1.000000x1.589934x1.589934x1.59x2.251%2.25%3.579%3.58%-1.000000x-1.000000x1.582232x1.582232x1.58x2.447%2.45%3.871%3.87%-1.000000x-1.000000x1.577713x1.577713x1.58x4.582%4.58%7.229%7.23%18-1.000000x-1.000000x1.575810x1.575810x1.58x2.760%2.76%4.350%4.35%19-1.000000x-1.000000x1.574188x1.574188x1.57x1.803%1.80%2.838%2.84%20-1.000000x-1.000000x1.567965x1.567965x1.57x3.409%3.41%5.346%5.35%21-1.000000x-1.000000x1.566566x1.566566x1.57x2.842%2.84%4.452%4.45%22-1.000000x-1.000000x1.562801x1.562801x1.56x6.111%6.11%9.551%9.55%23-1.000000x-1.000000x1.545600x1.545600x1.55x1.736%1.74%2.683%2.68%24-1.000000x-1.000000x1.526215x1.526215x1.53x2.660%2.66%4.060%4.06%-1.000000x-1.000000x1.513974x1.513974x1.51x4.919%4.92%7.447%7.45%25-1.000000x-1.000000x1.510882x1.510882x1.51x4.604%4.60%6.956%6.96%26-1.000000x-1.000000x1.494007x1.494007x1.49x4.011%4.01%5.992%5.99%27-1.000000x-1.000000x1.492516x1.492516x1.49x2.423%2.42%3.616%3.62%28-1.000000x-1.000000x1.488172x1.488172x1.49x3.830%3.83%5.700%5.70%29-1.000000x-1.000000x1.475755x1.475755x1.48x3.533%3.53%5.214%5.21%30-1.000000x-1.000000x1.471877x1.471877x1.47x1.943%1.94%2.859%2.86%31-1.000000x-1.000000x1.467166x1.467166x1.47x2.841%2.84%4.168%4.17%32-1.000000x-1.000000x1.442161x1.442161x1.44x2.749%2.75%3.965%3.96%33-1.000000x-1.000000x1.414670x1.414670x1.41x3.162%3.16%4.473%4.47%34-1.000000x-1.000000x1.413446x1.413446x1.41x4.324%4.32%6.112%6.11%35-1.000000x-1.000000x1.407975x1.407975x1.41x4.203%4.20%5.918%5.92%36-1.000000x-1.000000x1.390984x1.390984x1.39x3.031%3.03%4.216%4.22%37-1.000000x-1.000000x1.383306x1.383306x1.38x3.586%3.59%4.961%4.96%38-1.000000x-1.000000x1.367936x1.367936x1.37x4.164%4.16%5.696%5.70%39-1.000000x-1.000000x1.362517x1.362517x1.36x4.905%4.91%6.683%6.68%40-1.000000x-1.000000x1.361790x1.361790x1.36x7.280%7.28%9.914%9.91%41-1.000000x-1.000000x1.345994x1.345994x1.35x4.845%4.84%6.521%6.52%42-1.000000x-1.000000x1.341930x1.341930x1.34x3.216%3.22%4.316%4.32%43-1.000000x-1.000000x1.335985x1.335985x1.34x0.556%0.56%0.743%0.74%-1.000000x-1.000000x1.317072x1.317072x1.32x1.605%1.61%2.114%2.11%44-1.000000x-1.000000x1.300801x1.300801x1.30x3.459%3.46%4.499%4.50%45-1.000000x-1.000000x1.285200x1.285200x1.29x2.428%2.43%3.121%3.12%46-1.000000x-1.000000x1.281324x1.281324x1.28x2.879%2.88%3.689%3.69%47-1.000000x-1.000000x1.262281x1.262281x1.26x3.021%3.02%3.814%3.81%48-1.000000x-1.000000x1.245683x1.245683x1.25x9.673%9.67%12.050%12.1%49-1.000000x-1.000000x1.202385x1.202385x1.20x1.526%1.53%1.834%1.83%50
F percentage of females in category
M percentage of males in category
# rank of county 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

Townships:
Byrd, Clark, Eagle, Franklin, Green, Huntington, Jackson, Jefferson, Lewis, Perry, Pike, Pleasant, Scott, Sterling, Union, Washington
Unincorporated Places:
Lake Lorelei, Lake Waynoka, St. Martin
Villages:
Aberdeen, Fayetteville, Georgetown, Hamersville, Higginsport, Mount Orab, Ripley, Russellville, Sardinia
ZIP Codes:
45101, 45106, 45107, 45115, 45118, 45120, 45121, 45130, 45131, 45133, 45142, 45144, 45148, 45154, 45167, 45168, 45171, 45176, 45697
Unified School Districts:
Bethel-Tate, Blanchester, Clermont Northeastern, Eastern, Fayetteville-Perry, Georgetown, Lynchburg-Clay, Ripley-Union-Lewis-Huntington, Western Brown, Williamsburg
Congressional District:
OH-2
State Senate District:
OH-14
State House District:
OH-66
Neighboring Counties:
Adams, Bracken, Clermont, Clinton, Highland, Mason
Nearby Counties:
Campbell, Fleming, Hamilton, Harrison, Kenton, Lewis, Nicholas, Pendleton, Robertson, Warren