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: Male: % Cumulative data was reported at 98.780 % in 2015. This records a decrease from the previous number of 98.823 % for 2014. United States US: Educational Attainment: At Least Completed Primary: Population 25+ Years: Male: % Cumulative data is updated yearly, averaging 98.617 % from Dec 1970 (Median) to 2015, with 13 observations. The data reached an all-time high of 98.865 % in 2013 and a record low of 93.941 % in 1970. United States US: Educational Attainment: At Least Completed Primary: Population 25+ Years: Male: % 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 map shows the percentage of people age 25+ whose highest education level is some college. This is shown by state, county, and census tracts throughout the US. Zoom to any city to see the pattern there, or use one of the bookmarks to explore different areas.Some college education means that the individual has some college credits, but no degree. For more information from the Census Bureau, click here.The pop-up is configured to show the overall breakdown of educational attainment for the population 25+. The data shown is current-year American Community Survey (ACS) data from the US Census Bureau. The data is updated each year when the ACS releases its new 5-year estimates. For more information about the data, visit this page.To learn more about when the ACS releases data updates, click here.

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.

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.

Graph and download economic data for High School Graduate or Higher for Massachusetts (GCT1501MA) from 2006 to 2023 about secondary schooling, secondary, 25 years +, MA, educational attainment, education, and USA.

This layer shows education level for adults (25+) by race 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 to show the count and 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.

In 2021, about 41 percent of the United States population aged 25 to 34 years had attained a bachelor's degree or higher. In comparison, only 33 percent of the U.S. population aged 65 years or older had a bachelor's degree.

This map shows the predominant highest level of education for the population age 25+ in the United States. This is shown by state, county, and census tracts throughout the US. Click on a feature to learn more about the breakdown of population by their highest level of education.The categories are grouped as:Less than High SchoolHigh SchoolAssociate's DegreeSome CollegeBachelor's Degree or HigherThe data shown is current-year American Community Survey (ACS) data from the US Census. The data is updated each year when the ACS releases its new 5-year estimates. For more information about the data layer used in this map, visit this page.To learn more about when the ACS releases data updates, click here.

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.

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.

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.

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.

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.

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

Graph and download economic data for Bachelor's Degree or Higher for Kansas (GCT1502KS) from 2006 to 2023 about KS, 25 years +, tertiary schooling, educational attainment, education, and USA.

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.

According to a 2020 survey, 40 percent of Indian American respondents in the United States had obtained a postgraduate degree. Only one percent of survey participants did not have any high school education.

This collection comprises unaltered data files downloaded from https://eddataexpress.ed.gov/download/data-library on February 6, 2025. The original access page consisted of a table with category filters, which provided links to data ZIP files containing the specified data fields. This table has been saved into tabular data formats here in the Index folder, with the original web links replaced with the matching ZIP filename only, which essentially replicates the functionality of the original web page in a downloadable format.In the website's underlying file structure, the original ZIP files were nested within folders named according to the format EID_####, apparently to avoid conflicts between files with the same name. These seeming duplications might have been due to updates or revisions that had to be made to a data file. To preserve this original order, the ZIP files were renamed by appending the EID number to their original file name. The files were not otherwise unzipped or altered in any way from their original state.At the time of download, the page at https://eddataexpress.ed.gov/download/data-library displayed the following two notices in red:"The COVID-19 pandemic disrupted the collection and reporting of data on EDE, beginning in SY 2019-20. The Department urges abundant caution when using the data and recommends reviewing the relevant data notes prior to use or interpretation. This includes data on state assessments, graduation rates, and chronic absenteeism.""WARNING: The data library functionality has stopped working temporarily for many SY2122 school files. Please go to the download tool page to download your data of interest. We apologize for the inconvenience."--------------------The "About Us" page from the ED Data Express website had this to say about its resources:Purpose of ED Data ExpressED Data Express is a website designed to improve the public's ability to access and explore high-value state- and district-level education data collected by the U.S. Department of Education. The site is designed to be interactive and to present the data in a clear, easy-to-use manner, with options to download information into Excel or to explore the data within the site's grant program dashboards. The site currently includes data from EDFacts, Consolidated State Performance Reports (CSPR), and the Department's Budget Service office. For more information about these topics, please visit the following web pages:https://www2.ed.gov/about/inits/ed/edfacts/index.html [see below for the text of the linked page]https://www2.ed.gov/about/offices/list/om/fs_po/ofo/budget-service.html [this URL was dead at the time of download]Using the SiteED Data Express includes two sections that allow users to access and view the data: (1) grant program data dashboards and (2) download functionality. The grant program data dashboards provide a snapshot of information on the funding, participation and performance of some of the grant programs administered by the U.S. Department of Education's Office of Elementary and Secondary Education. The dashboards are interactive and update depending on the program, state and school year selected. Additional information is provided through data notes as well as through the small "i" icon. The download functionality allows users to build customized tables of data and contain more data than what is available via the dashboards. The download functionality also allows users to download data notes which provide important caveats and contextual information to consider when using the data. Data Included and Frequency of UpdatesThe site currently includes funding, participation and performance data from school years 2010-11 to 2016-17 on formula grant programs administered in the Office of Elementary and Secondary Education. Additional data and data notes will be added to the site over time. Quality Control and Personally Identifiable InformationAll CSPR and EDFacts data are self-reported by each state. The U.S. Department of Education conducts a review of the data and provides feedback to states, but it is ultimately states’ responsibility to verify and certify that their data are correct. Please note that during the reporting years represented on this site, the Office of Elementary and Secondary Education in collaboration with EDFacts and SEAs have wor