In 2022, about 37.7 percent of the U.S. population who were aged 25 and above had graduated from college or another higher education institution, a slight decline from 37.9 the previous year. However, this is a significant increase from 1960, when only 7.7 percent of the U.S. population had graduated from college. Demographics Educational attainment varies by gender, location, race, and age throughout the United States. Asian-American and Pacific Islanders had the highest level of education, on average, while Massachusetts and the District of Colombia are areas home to the highest rates of residents with a bachelor’s degree or higher. However, education levels are correlated with wealth. While public education is free up until the 12th grade, the cost of university is out of reach for many Americans, making social mobility increasingly difficult. Earnings White Americans with a professional degree earned the most money on average, compared to other educational levels and races. However, regardless of educational attainment, males typically earned far more on average compared to females. Despite the decreasing wage gap over the years in the country, it remains an issue to this day. Not only is there a large wage gap between males and females, but there is also a large income gap linked to race as well.

In 2021, about ** percent of the United States population aged 25 to 34 years had attained a bachelor's degree or higher. In comparison, only ** percent of the U.S. population aged 65 years or older had a bachelor's degree.

United States US: Educational Attainment: At Least Completed Primary: Population 25+ Years: Total: % Cumulative data was reported at 98.774 % in 2015. This records a decrease from the previous number of 98.793 % for 2014. United States US: Educational Attainment: At Least Completed Primary: Population 25+ Years: Total: % Cumulative data is updated yearly, averaging 98.677 % from Dec 1970 (Median) to 2015, with 13 observations. The data reached an all-time high of 98.867 % in 2013 and a record low of 94.500 % in 1970. United States US: Educational Attainment: At Least Completed Primary: Population 25+ Years: Total: % Cumulative data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s USA – Table US.World Bank: Education Statistics. The percentage of population ages 25 and over that attained or completed primary education.; ; UNESCO Institute for Statistics; ;

US: Educational Attainment: Doctoral or Equivalent: Population 25+ Years: Female: % Cumulative data was reported at 1.364 % in 2015. This records an increase from the previous number of 1.264 % for 2014. US: Educational Attainment: Doctoral or Equivalent: Population 25+ Years: Female: % Cumulative data is updated yearly, averaging 1.264 % from Dec 2013 (Median) to 2015, with 3 observations. The data reached an all-time high of 1.364 % in 2015 and a record low of 1.188 % in 2013. US: Educational Attainment: Doctoral or Equivalent: Population 25+ Years: Female: % Cumulative data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s USA – Table US.World Bank: Education Statistics. The percentage of population ages 25 and over that attained or completed Doctoral or equivalent.; ; UNESCO Institute for Statistics; ;

US: Educational Attainment: At Least Completed Lower Secondary: Population 25+ Years: Female: % Cumulative data was reported at 95.478 % in 2015. This records an increase from the previous number of 95.430 % for 2014. US: Educational Attainment: At Least Completed Lower Secondary: Population 25+ Years: Female: % Cumulative data is updated yearly, averaging 94.823 % from Dec 1980 (Median) to 2015, with 12 observations. The data reached an all-time high of 95.478 % in 2015 and a record low of 93.014 % in 1980. US: Educational Attainment: At Least Completed Lower Secondary: Population 25+ Years: Female: % Cumulative data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s USA – Table US.World Bank: Education Statistics. The percentage of population ages 25 and over that attained or completed lower secondary education.; ; UNESCO Institute for Statistics; ;

Graph and download economic data for Bachelor's Degree or Higher for California (GCT1502CA) from 2006 to 2023 about 25 years +, tertiary schooling, educational attainment, education, CA, and USA.

In 2023, about 19.9 percent of the population of Michigan aged 25 years and over held a Bachelor's degree as their highest level of education. Furthermore, about 27.7 percent of people in the state had a high school diploma or equivalency as their highest level of education.

This layer shows education level for adults (25+) by race by sex. This is shown by tract, county, and state boundaries. This service is updated annually to contain the most currently released American Community Survey (ACS) 5-year data, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. This layer is symbolized to show the percent of adults age 25+ who have a bachelor's degree or higher as their highest education level. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. Current Vintage: 2019-2023ACS Table(s): B15002, C15002B, C15002C, C15002D, C15002E, C15002F, C15002G, C15002H, C15002I (Not all lines of these ACS tables are available in this layer.)Data downloaded from: Census Bureau's API for American Community Survey Date of API call: December 12, 2024National Figures: data.census.govThe United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. For more information about ACS layers, visit the FAQ. Please cite the Census and ACS when using this data.Data Note from the Census:Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables.Data Processing Notes:This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Click here to learn more about ACS data releases.Boundaries come from the US Census TIGER geodatabases, specifically, the National Sub-State Geography Database (named tlgdb_(year)_a_us_substategeo.gdb). Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For census tracts, the water cutouts are derived from a subset of the 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract level boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2020 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters). The States layer contains 52 records - all US states, Washington D.C., and Puerto RicoCensus tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. These negative values exist in the raw API data to indicate the following situations:The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.Either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.The estimate is controlled. A statistical test for sampling variability is not appropriate.The data for this geographic area cannot be displayed because the number of sample cases is too small.

This layer was developed by the Research & Analytics Group of the Atlanta Regional Commission, using data from the U.S. Census Bureau’s American Community Survey 5-year estimates for 2013-2017, to show levels of educational attainment by State of Georgia in the Atlanta region. The user should note that American Community Survey data represent estimates derived from a surveyed sample of the population, which creates some level of uncertainty, as opposed to an exact measure of the entire population (the full census count is only conducted once every 10 years and does not cover as many detailed characteristics of the population). Therefore, any measure reported by ACS should not be taken as an exact number – this is why a corresponding margin of error (MOE) is also given for ACS measures. The size of the MOE relative to its corresponding estimate value provides an indication of confidence in the accuracy of each estimate. Each MOE is expressed in the same units as its corresponding measure; for example, if the estimate value is expressed as a number, then its MOE will also be a number; if the estimate value is expressed as a percent, then its MOE will also be a percent. The user should also note that for relatively small geographic areas, such as census tracts shown here, ACS only releases combined 5-year estimates, meaning these estimates represent rolling averages of survey results that were collected over a 5-year span (in this case 2013-2017). Therefore, these data do not represent any one specific point in time or even one specific year. For geographic areas with larger populations, 3-year and 1-year estimates are also available. For further explanation of ACS estimates and margin of error, visit Census ACS website. Naming conventions: Prefixes:NoneCountpPercentrRatemMedianaMean (average)tAggregate (total)chChange in absolute terms (value in t2 - value in t1)pchPercent change ((value in t2 - value in t1) / value in t1)chpChange in percent (percent in t2 - percent in t1)Suffixes:NoneChange over two periods_eEstimate from most recent ACS_mMargin of Error from most recent ACS_00Decennial 2000 Attributes: SumLevelSummary level of geographic unit (e.g., County, Tract, NSA, NPU, DSNI, SuperDistrict, etc)GEOIDCensus tract Federal Information Processing Series (FIPS) code NAMEName of geographic unitPlanning_RegionPlanning region designation for ARC purposesAcresTotal area within the tract (in acres)SqMiTotal area within the tract (in square miles)CountyCounty identifier (combination of Federal Information Processing Series (FIPS) codes for state and county)CountyNameCounty NamePop25P_e# Population 25 years and over, 2017Pop25P_m# Population 25 years and over, 2017 (MOE)NoHS_e# Population 25 years and over, less than 9th grade education, 2017NoHS_m# Population 25 years and over, less than 9th grade education, 2017 (MOE)pNoHS_e% Population 25 years and over, less than 9th grade education, 2017pNoHS_m% Population 25 years and over, less than 9th grade education, 2017 (MOE)SomeHS_e# Population 25 years and over, 9th-12th grade, no diploma, 2017SomeHS_m# Population 25 years and over, 9th-12th grade, no diploma, 2017 (MOE)pSomeHS_e% Population 25 years and over, 9th-12th grade, no diploma, 2017pSomeHS_m% Population 25 years and over, 9th-12th grade, no diploma, 2017 (MOE)HSGrad_e# Population 25 years and over, high school graduate (includes GED), 2017HSGrad_m# Population 25 years and over, high school graduate (includes GED), 2017 (MOE)pHSGrad_e% Population 25 years and over, high school graduate (includes GED), 2017pHSGrad_m% Population 25 years and over, high school graduate (includes GED), 2017 (MOE)SomeColl_e# Population 25 years and over, some college, no degree, 2017SomeColl_m# Population 25 years and over, some college, no degree, 2017 (MOE)pSomeColl_e% Population 25 years and over, some college, no degree, 2017pSomeColl_m% Population 25 years and over, some college, no degree, 2017 (MOE)Associates_e# Population 25 years and over, associate's degree, 2017Associates_m# Population 25 years and over, associate's degree, 2017 (MOE)pAssociates_e% Population 25 years and over, associate's degree, 2017pAssociates_m% Population 25 years and over, associate's degree, 2017 (MOE)BA_e# Population 25 years and over, bachelor's degree, 2017BA_m# Population 25 years and over, bachelor's degree, 2017 (MOE)pBA_e% Population 25 years and over, bachelor's degree, 2017pBA_m% Population 25 years and over, bachelor's degree, 2017 (MOE)GradProf_e# Population 25 years and over, graduate or professional degree, 2017GradProf_m# Population 25 years and over, graduate or professional degree, 2017 (MOE)pGradProf_e% Population 25 years and over, graduate or professional degree, 2017pGradProf_m% Population 25 years and over, graduate or professional degree, 2017 (MOE)LtHS_e# Population 25 years and over, Less than high school graduate, 2017LtHS_m# Population 25 years and over, Less than high school graduate, 2017 (MOE)pLtHS_e% Population 25 years and over, Less than high school graduate, 2017pLtHS_m% Population 25 years and over, Less than high school graduate, 2017 (MOE)HSPlus_e# Population 25 years and over, high school graduate or higher, 2017HSPlus_m# Population 25 years and over, high school graduate or higher, 2017 (MOE)pHSPlus_e% Population 25 years and over, high school graduate or higher, 2017pHSPlus_m% Population 25 years and over, high school graduate or higher, 2017 (MOE)BAPlus_e# Population 25 years and over, bachelor's degree or higher, 2017BAPlus_m# Population 25 years and over, bachelor's degree or higher, 2017 (MOE)pBAPlus_e% Population 25 years and over, bachelor's degree or higher, 2017pBAPlus_m% Population 25 years and over, bachelor's degree or higher, 2017 (MOE)last_edited_dateLast date the feature was edited by ARC Source: U.S. Census Bureau, Atlanta Regional CommissionDate: 2013-2017 For additional information, please visit the Census ACS website.

Graph and download economic data for Bachelor's Degree or Higher for Kentucky (GCT1502KY) from 2006 to 2023 about 25 years +, tertiary schooling, educational attainment, KY, education, and USA.

U.S. citizens with a professional degree had the highest median household income in 2023, at 172,100 U.S. dollars. In comparison, those with less than a 9th grade education made significantly less money, at 35,690 U.S. dollars. Household income The median household income in the United States has fluctuated since 1990, but rose to around 70,000 U.S. dollars in 2021. Maryland had the highest median household income in the United States in 2021. Maryland’s high levels of wealth is due to several reasons, and includes the state's proximity to the nation's capital. Household income and ethnicity The median income of white non-Hispanic households in the United States had been on the rise since 1990, but declining since 2019. While income has also been on the rise, the median income of Hispanic households was much lower than those of white, non-Hispanic private households. However, the median income of Black households is even lower than Hispanic households. Income inequality is a problem without an easy solution in the United States, especially since ethnicity is a contributing factor. Systemic racism contributes to the non-White population suffering from income inequality, which causes the opportunity for growth to stagnate.

US: School Enrollment: Preprimary: % Gross data was reported at 69.492 % in 2015. This records a decrease from the previous number of 69.917 % for 2014. US: School Enrollment: Preprimary: % Gross data is updated yearly, averaging 60.389 % from Dec 1971 (Median) to 2015, with 27 observations. The data reached an all-time high of 70.965 % in 1996 and a record low of 37.734 % in 1972. US: School Enrollment: Preprimary: % Gross data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s USA – Table US.World Bank: Education Statistics. Gross enrollment ratio is the ratio of total enrollment, regardless of age, to the population of the age group that officially corresponds to the level of education shown. Preprimary education refers to programs at the initial stage of organized instruction, designed primarily to introduce very young children to a school-type environment and to provide a bridge between home and school.; ; UNESCO Institute for Statistics; Weighted average; Each economy is classified based on the classification of World Bank Group's fiscal year 2018 (July 1, 2017-June 30, 2018).

US: School Enrollment: Preprimary: Female: % Gross data was reported at 68.891 % in 2015. This records a decrease from the previous number of 70.205 % for 2014. US: School Enrollment: Preprimary: Female: % Gross data is updated yearly, averaging 63.943 % from Dec 1981 (Median) to 2015, with 17 observations. The data reached an all-time high of 70.447 % in 1996 and a record low of 51.131 % in 1981. US: School Enrollment: Preprimary: Female: % Gross data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s USA – Table US.World Bank: Education Statistics. Gross enrollment ratio is the ratio of total enrollment, regardless of age, to the population of the age group that officially corresponds to the level of education shown. Preprimary education refers to programs at the initial stage of organized instruction, designed primarily to introduce very young children to a school-type environment and to provide a bridge between home and school.; ; UNESCO Institute for Statistics; Weighted average; Each economy is classified based on the classification of World Bank Group's fiscal year 2018 (July 1, 2017-June 30, 2018).

This layer shows education level for adults 25+. Counts broken down by sex. This is shown by tract, county, and state centroids. This service is updated annually to contain the most currently released American Community Survey (ACS) 5-year data, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. This layer is symbolized by the count of total adults (25+) and the percentage of adults (25+) who were not high school graduates. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. Current Vintage: 2019-2023ACS Table(s): B15002Data downloaded from: Census Bureau's API for American Community Survey Date of API call: December 12, 2024National Figures: data.census.govThe United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. For more information about ACS layers, visit the FAQ. Please cite the Census and ACS when using this data.Data Note from the Census:Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables.Data Processing Notes:This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Click here to learn more about ACS data releases.Boundaries come from the US Census TIGER geodatabases, specifically, the National Sub-State Geography Database (named tlgdb_(year)_a_us_substategeo.gdb). Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For census tracts, the water cutouts are derived from a subset of the 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract level boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2023 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters).The States layer contains 52 records - all US states, Washington D.C., and Puerto RicoCensus tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. These negative values exist in the raw API data to indicate the following situations:The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.Either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.The estimate is controlled. A statistical test for sampling variability is not appropriate.The data for this geographic area cannot be displayed because the number of sample cases is too small.

United States US: Secondary Education: Pupils: % Female data was reported at 49.172 % in 2015. This records an increase from the previous number of 49.145 % for 2014. United States US: Secondary Education: Pupils: % Female data is updated yearly, averaging 48.936 % from Dec 1972 (Median) to 2015, with 32 observations. The data reached an all-time high of 49.713 % in 1998 and a record low of 34.965 % in 1972. United States US: Secondary Education: Pupils: % Female data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s USA – Table US.World Bank: Education Statistics. Female pupils as a percentage of total pupils at secondary level includes enrollments in public and private schools.; ; UNESCO Institute for Statistics; Weighted average; Each economy is classified based on the classification of World Bank Group's fiscal year 2018 (July 1, 2017-June 30, 2018).

In an impressive increase from years past, 39 percent of women in the United States had completed four years or more of college in 2022. This figure is up from 3.8 percent of women in 1940. A significant increase can also be seen in males, with 36.2 percent of the U.S. male population having completed four years or more of college in 2022, up from 5.5 percent in 1940.

4- and 2-year colleges

In the United States, college students are able to choose between attending a 2-year postsecondary program and a 4-year postsecondary program. Generally, attending a 2-year program results in an Associate’s Degree, and 4-year programs result in a Bachelor’s Degree.

Many 2-year programs are designed so that attendees can transfer to a college or university offering a 4-year program upon completing their Associate’s. Completion of a 4-year program is the generally accepted standard for entry-level positions when looking for a job.

Earnings after college

Factors such as gender, degree achieved, and the level of postsecondary education can have an impact on employment and earnings later in life. Some Bachelor’s degrees continue to attract more male students than female, particularly in STEM fields, while liberal arts degrees such as education, languages and literatures, and communication tend to see higher female attendance.

All of these factors have an impact on earnings after college, and despite nearly the same rate of attendance within the American population between males and females, men with a Bachelor’s Degree continue to have higher weekly earnings on average than their female counterparts.

In 2023, about 24.3 percent of the population of Washington aged 25 and above held a Bachelor's degree as their highest level of education. Furthermore, about 20.5 percent of people in the state had some college, but no degree as their highest level of education.

Graph and download economic data for Expenditures: Total Average Annual Expenditures by Highest Education: Less Than College Graduate: Total (CXUTOTALEXPLB1402M) from 2012 to 2023 about no college, secondary schooling, secondary, average, expenditures, education, and USA.

This dataset tracks annual distribution of students across grade levels in State College Area School District and average distribution per school district in Pennsylvania

United States US: School Enrollment: Secondary: Male: % Net data was reported at 89.513 % in 2015. This records an increase from the previous number of 87.832 % for 2014. United States US: School Enrollment: Secondary: Male: % Net data is updated yearly, averaging 87.442 % from Dec 1987 (Median) to 2015, with 21 observations. The data reached an all-time high of 89.513 % in 2015 and a record low of 85.450 % in 2002. United States US: School Enrollment: Secondary: Male: % Net data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s USA – Table US.World Bank: Education Statistics. Net enrollment rate is the ratio of children of official school age who are enrolled in school to the population of the corresponding official school age. Secondary education completes the provision of basic education that began at the primary level, and aims at laying the foundations for lifelong learning and human development, by offering more subject- or skill-oriented instruction using more specialized teachers.; ; UNESCO Institute for Statistics; Weighted average; Each economy is classified based on the classification of World Bank Group's fiscal year 2018 (July 1, 2017-June 30, 2018).