In 2021, the District of Columbia had the most highly educated population in the United States, with 61.4 percent of residents over the age of 25 having a Bachelor's degree or higher. Massachusetts followed closely behind, with 45.2 percent of residents having completed a Bachelor's degree or higher. For the United States as a whole, this figure stood at 33.7 percent of the population.

This layer shows Educational Attainment. This is shown by state and county boundaries. This service contains the 2018-2022 release of data from the 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 Population 25 years and over - Bachelor's Degree or higher (%). 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: 2018-2022ACS Table(s): DP02Data downloaded from: Census Bureau's API for American Community Survey Date of API call: January 18, 2022National 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. 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:Boundaries come from the Cartographic Boundaries via US Census TIGER geodatabases. Boundaries are updated at the same time as the data updates, and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines clipped for cartographic purposes. For state and county boundaries, the water and coastlines are derived from the coastlines of the 500k TIGER Cartographic Boundary Shapefiles. 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 Rico. The Counties (and equivalent) layer contains 3221 records - all counties and equivalent, Washington D.C., and Puerto Rico municipios. See Areas Published. 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.Margin of error (MOE) values of -555555555 in the API (or "*****" (five asterisks) on data.census.gov) are displayed as 0 in this dataset. The estimates associated with these MOEs have been controlled to independent counts in the ACS weighting and have zero sampling error. So, the MOEs are effectively zeroes, and are treated as zeroes in MOE calculations. Other negative values on the API, such as -222222222, -666666666, -888888888, and -999999999, all represent estimates or MOEs that can't be calculated or can't be published, usually due to small sample sizes. All of these are rendered in this dataset as null (blank) values.

In 2021, 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.

This layer shows education level for adults 25+. Counts broken down 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 by 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: 2015-2019ACS Table(s): B15002Data downloaded from: Census Bureau's API for American Community Survey Date of API call: July 27, 2021National 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. 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 clipped for cartographic purposes. For census tracts, the water cutouts are derived from a subset of the 2010 AWATER (Area Water) boundaries offered by TIGER. For state and county boundaries, the water and coastlines are derived from the coastlines of the 500k TIGER Cartographic Boundary Shapefiles. 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: 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; ;

This layer shows Educational Attainment. This is shown by state and county boundaries. This service contains 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 Population 25 years and over - Bachelor's Degree or higher (%). 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: 2017-2021ACS Table(s): DP02Data downloaded from: Census Bureau's API for American Community Survey Date of API call: February 16, 2023National 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. 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:Boundaries come from the Cartographic Boundaries via US Census TIGER geodatabases. Boundaries are updated at the same time as the data updates, and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines clipped for cartographic purposes. For state and county boundaries, the water and coastlines are derived from the coastlines of the 500k TIGER Cartographic Boundary Shapefiles. 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 Rico. The Counties (and equivalent) layer contains 3221 records - all counties and equivalent, Washington D.C., and Puerto Rico municipios. See Areas Published. 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.Margin of error (MOE) values of -555555555 in the API (or "*****" (five asterisks) on data.census.gov) are displayed as 0 in this dataset. The estimates associated with these MOEs have been controlled to independent counts in the ACS weighting and have zero sampling error. So, the MOEs are effectively zeroes, and are treated as zeroes in MOE calculations. Other negative values on the API, such as -222222222, -666666666, -888888888, and -999999999, all represent estimates or MOEs that can't be calculated or can't be published, usually due to small sample sizes. All of these are rendered in this dataset as null (blank) values.

Graph and download economic data for Bachelor's Degree or Higher for Maine (GCT1502ME) from 2006 to 2023 about ME, 25 years +, tertiary schooling, educational attainment, education, and USA.

United States US: Educational Attainment: At Least Master's or Equivalent: Population 25+ Years: Total: % Cumulative data was reported at 11.995 % in 2015. This records an increase from the previous number of 11.765 % for 2014. United States US: Educational Attainment: At Least Master's or Equivalent: Population 25+ Years: Total: % Cumulative data is updated yearly, averaging 11.765 % from Dec 2013 (Median) to 2015, with 3 observations. The data reached an all-time high of 11.995 % in 2015 and a record low of 11.566 % in 2013. United States US: Educational Attainment: At Least Master's or Equivalent: 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 Master's or equivalent.; ; UNESCO Institute for Statistics; ;

This table contains data on the percent of population age 25 and up with a four-year college degree or higher for California, its regions, counties, county subdivisions, cities, towns, and census tracts. Greater educational attainment has been associated with health-promoting behaviors including consumption of fruits and vegetables and other aspects of healthy eating, engaging in regular physical activity, and refraining from excessive consumption of alcohol and from smoking. Completion of formal education (e.g., high school) is a key pathway to employment and access to healthier and higher paying jobs that can provide food, housing, transportation, health insurance, and other basic necessities for a healthy life. Education is linked with social and psychological factors, including sense of control, social standing and social support. These factors can improve health through reducing stress, influencing health-related behaviors and providing practical and emotional support. More information on the data table and a data dictionary can be found in the Data and Resources section. The educational attainment table is part of a series of indicators in the Healthy Communities Data and Indicators Project (HCI) of the Office of Health Equity. The goal of HCI is to enhance public health by providing data, a standardized set of statistical measures, and tools that a broad array of sectors can use for planning healthy communities and evaluating the impact of plans, projects, policy, and environmental changes on community health. The creation of healthy social, economic, and physical environments that promote healthy behaviors and healthy outcomes requires coordination and collaboration across multiple sectors, including transportation, housing, education, agriculture and others. Statistical metrics, or indicators, are needed to help local, regional, and state public health and partner agencies assess community environments and plan for healthy communities that optimize public health. More information on HCI can be found here: https://www.cdph.ca.gov/Programs/OHE/CDPH%20Document%20Library/Accessible%202%20CDPH_Healthy_Community_Indicators1pager5-16-12.pdf

The format of the educational attainment table is based on the standardized data format for all HCI indicators. As a result, this data table contains certain variables used in the HCI project (e.g., indicator ID, and indicator definition). Some of these variables may contain the same value for all observations.

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.

As of 2022, there were approximately 4.86 million people in the United States who had completed their doctorate degree. Furthermore, there were 74.53 million people in the U.S. whose highest educational attainment was a high school degree.

Graph and download economic data for Bachelor's Degree or Higher for Utah (GCT1502UT) from 2006 to 2023 about UT, 25 years +, tertiary schooling, educational attainment, education, and USA.

United States US: Educational Attainment, At Least Completed Upper Secondary: Population 25+ Years: Total: % Cumulative data was reported at 88.412 % in 2015. This records an increase from the previous number of 88.314 % for 2014. United States US: Educational Attainment, At Least Completed Upper Secondary: Population 25+ Years: Total: % Cumulative data is updated yearly, averaging 86.709 % from Dec 1970 (Median) to 2015, with 13 observations. The data reached an all-time high of 88.412 % in 2015 and a record low of 65.700 % in 1970. United States US: Educational Attainment, At Least Completed Upper Secondary: 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 upper secondary education.; ; UNESCO Institute for Statistics; ;

Graph and download economic data for High School Graduate or Higher for Kansas (GCT1501KS) from 2006 to 2023 about secondary schooling, KS, secondary, 25 years +, educational attainment, education, and USA.

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.

Educational attainment rates for Washington State counties with populations greater than 65,000 according to US Census Bureau’s Data Profile. All values are the percent estimates of individuals 25 years of age or higher from the ACS 1 Year Survey. DP02_0063PE - Percent Associate's Degree DP02_0066PE - Percent High School Graduate or Higher DP02_0067PE - Percent Bachelor's Degree or Higher DP02_0065PE - Percent Graduate/Professional Degree

This dataset provides population 25 years and over estimates by sex and educational attainment for State of Iowa, individual Iowa counties, Iowa places and census tracts within Iowa. Data is from the American Community Survey, Five Year Estimates, Table B15002.

Sex includes Male, Female and Both.

Educational Attainment includes the following: No School; PK to 4th Grade; 5th to 6th Grade; 7th to 8th Grade; 9th Grade; 10th Grade; 11th Grade; 12th Grade, No Diploma; High School Diploma or Equivalent; Some College, Less than Year; Some College, One Year or More; Associates Degree; Bachelors Degree; Masters Degree; Professional Degree; and Doctorate Degree.

Each have been placed in the following educational categories: Less than High School, High School Graduate; Some College or Associates Degree; and Bachelors Degree or Higher.

This dataset provides population 25 years and over estimates by educational attainment for State of Iowa, individual Iowa counties, Iowa places and census tracts within Iowa. Data is from the American Community Survey, Five Year Estimates, Table B15003. Levels of educational attainment include the following: No schooling completed; Nursery school; Kindergarten; 1st grade; 2nd grade; 3rd grade; 4th grade; 5th grade; 6th grade; 7th grade; 8th grade; 9th grade; 10th grade; 11th grade; 12th grade, no diploma; Regular high school diploma; GED or alternative credential; Some college, less than 1 year; Some college, 1 or more years, no degree; Associate's degree; Bachelor's degree; Master's degree; Professional school degree; and Doctorate degree.

This dataset was developed by the Research & Analytics Group at the Atlanta Regional Commission using data from the U.S. Census Bureau.For a deep dive into the data model including every specific metric, see the Infrastructure Manifest. The manifest details ARC-defined naming conventions, field names/descriptions and topics, summary levels; source tables; notes and so forth for all metrics.Naming conventions:Prefixes: None Countp Percentr Ratem Mediana Mean (average)t Aggregate (total)ch Change in absolute terms (value in t2 - value in t1)pch Percent change ((value in t2 - value in t1) / value in t1)chp Change in percent (percent in t2 - percent in t1)s Significance flag for change: 1 = statistically significant with a 90% CI, 0 = not statistically significant, blank = cannot be computed Suffixes: _e19 Estimate from 2014-19 ACS_m19 Margin of Error from 2014-19 ACS_00_v19 Decennial 2000, re-estimated to 2019 geography_00_19 Change, 2000-19_e10_v19 2006-10 ACS, re-estimated to 2019 geography_m10_v19 Margin of Error from 2006-10 ACS, re-estimated to 2019 geography_e10_19 Change, 2010-19The 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 2015-2019). 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.Source: U.S. Census Bureau, Atlanta Regional CommissionDate: 2015-2019Data License: Creative Commons Attribution 4.0 International (CC by 4.0)Link to the manifest: https://www.arcgis.com/sharing/rest/content/items/3d489c725bb24f52a987b302147c46ee/data

Educational attainment, at least completed upper secondary, population 25+, total (%) (cumulative) in United States was reported at 95.29 % in 2023, according to the World Bank collection of development indicators, compiled from officially recognized sources. United States - Educational attainment, at least completed upper secondary, population 25+, total (cumulative) - actual values, historical data, forecasts and projections were sourced from the World Bank on March of 2025.