In 2022, around 91.8 percent of women had graduated high school or had obtained a higher educational degree in the United States. This is an increase from 1960, when 42.5 percent of women in the U.S. had graduated from high school or above.

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.

Metric scores are not reported for n-sizes under 10. Per OSSE's policy, secondary suppression is applied to all student groups when a complementary group has an n-size under 10 or is top/bottom suppressed to prevent the calculation of suppressed data.

Data Source: DC Office of the State Superintendent of Education

Why This Matters

Graduating from high school is a critical step in advancing along educational and professional paths. Many careers and almost all colleges require a high school diploma or GED.

Educational attainment is strongly linked with socioeconomic and health outcomes. Americans who graduate high school tend to have higher incomes than those who do not. High school graduates also tend to live longer, healthier, and happier lives.

Black, Hispanic, and Native American students in the U.S. have lower graduation rates, on average, than white students. Segregation and historical disinvestment in communities of color play a significant role in these disparities. Poverty and limited educational resources act as barriers to graduation.

The District Response

The Office of the State Superintendent of Education (OSSE)’s Reimagining High School Graduation Requirements initiative aims to identify and implement new high school graduation requirements that incorporate outcome measures and support innovative approaches to preparing young people for life after graduation.

The District of Columbia Public Schools offers a number of supports to both proactively aid students in graduating and assist those at risk of not graduating.

Since 2014, those who pass the GED receive a State High School Diploma instead of a GED credential. This more accurately represents the dedication, hard work, and demonstration of skill it takes for residents to successfully complete this alternative path to a high school diploma.

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 the United States, the rate of obesity is lower among college graduates compared to those who did not graduate from college. For example, in 2023, around 27 percent of college graduates were obese, while 36 percent of those with some college or technical school were obese. At that time, rates of obesity were highest among those with less than a high school education, at around 37 percent. Income and obesity As with education level, there are also differences in rates of obesity in the United States based on income. Adults in the U.S. with an annual income of 75,000 U.S. dollars or more have the lowest rates of obesity, with around 29 percent of this population obese in 2023. On the other hand, those earning less than 15,000 U.S. dollars per year had the highest rates of obesity at that time, at 37 percent. One reason for this disparity may be a lack of access to fresh food among those earning less, as cheap food in the United States tends to be unhealthier. What is the most obese state? As of 2023, the states with the highest rates of obesity were West Virginia, Mississippi, and Arkansas. At that time, around 41 percent of adults in West Virginia were obese. The states with the lowest rates of obesity were Colorado, Hawaii, and Massachusetts. Still, around a quarter of adults in Colorado were obese in 2023. West Virginia and Mississippi are also the states with the highest rates of obesity among high school students. Children with obesity are more likely to be obese as adults and are at increased risk of health conditions such as asthma, type 2 diabetes, and sleep apnea.

The research goals of the Baseline survey were to establish a panel of sophomore and senior high school students in the state of Texas that can be followed to examine the decision-making, knowledge and attitudes of students regarding post-high school life course decisions in light of the existence of the Top 10 legislation in Texas. The baseline survey was intended to establish benchmark measures. Follow-up surveys with a subsample of the students will be used to track the evolution of student decision-making about college attendance among those who attend college (full time or part time) immediately after high school graduation as well as those who decide to attend college one or more years after graduation. The Baseline survey objectives called for the collection of 33,000 to 35,000 completed interviews with sophomores and seniors in Texas public high schools using a sample survey design. A probability sample of 100 high schools was desired. Interviews were to be conducted in class using self-administered surveys. This would require district and high school cooperation with the survey effort. Analysis was desired at multiple levels of the education system -- students, schools and districts. Because of the multilevel nature of the analytic goals of the study, a census of sophomores and seniors was desired within the schools that were selected into the survey (to facilitate multilevel analyses). At the student level, analyses were desired separately by racial/ethnic subgroup: non-Hispanic Whites; African Americans; Asians and Hispanics. Moreover, analyses of likely college goers and non-college goers were desired. The Wave 2 Senior Study is the first follow-up with a subsample of baseline seniors. This phase tracks the evolution of student decision-making about college attendance among those who decide to attend college (full or part time) immediately after high school graduation, as well as those who decide to attend college one or more years after graduation. The survey also covers post high school activities including military enlistment, employment, civic activities, high school experiences, life events, self-esteem, and current living status. The following demographic subgroups will be used for comparative analyses: Non-Hispanic Whites, African Americans, Hispanics, and Asians. Additionally, separate analyses are desired for students attending college or technical school and students not attending college one year after attending high school. The Sophomore Wave 2 "Stayer Leaver" Survey is the first follow-up with a subsample of baseline sophomores. Most of the respondents were in their senior year of high school at the time of the interview. The focus of the survey is on the student's activities during the senior year and their plans after high school. An important component of this study was to partition the sophomore cohort into Stayers and Leavers. Stayers represent those students who have attended the same high school from the baseline survey in 2002 to the Wave 2 survey in 2004. Analysis of students who stayed at the same high school will determine whether students' knowledge of the Top 10 Percent law increased and whether they changed their college aspirations as they progressed through school. Leavers are those students that have changed schools or dropped out (and did not return to the same high school) between the baseline survey and the Wave 2 survey. Analysis of the leaver students will determine whether, how many, and which students deliberately changed schools in order to qualify for the benefits of the Top 10 Percent law. Students that had dropped out of school, regardless of whether they returned to school or not, were asked a series of questions that explored reasons for dropping out and activities during their time away from school. Students that dropped out, but then returned to the same high school are defined as Stayers. Those that dropped out and did not return to school, or attended a different school, are defined as Leavers. The Senior Wave 3 survey is the second follow-up interview with the subsample of 8,345 baseline seniors. The Wave 3 survey sought to determine students' educational pursuits and levels of attainment, and other life choices, four years after high school graduation. For students following a four-year path through college or university, graduation would occur in 2006, but a

Graph and download economic data for Consumer Unit Characteristics: Adults 65 and Older by Education: Less Than High School Graduate (CXU980060LB1303M) from 1995 to 2009 about no college, 65-years +, adult, consumer unit, secondary schooling, secondary, education, and USA.

Community colleges in the US are undergoing a significant transformation, shaped by shifting student demand, economic pressures and volatile public policy in the wake of COVID. Between 2020 and 2025, community colleges have transitioned from pandemic emergency response to a phase of strategic recovery and adaptation. Following a dramatic enrollment decline during COVID-19, when students paused their education because of public health concerns, economic instability and the rapid transition to online learning, the industry is now experiencing a significant rebound. In spring 2025, two-year colleges saw a 5.4% surge in attendance, the strongest growth among all undergraduate settings. Several factors drove this growth: inflation and rising living costs made community colleges’ lower tuition more attractive, while skepticism about the value of a four-year degree prompted more students to seek affordable, flexible programs that quickly build in-demand skills. Despite rising enrollment, revenue has increased at a CAGR of 0.9%, reaching an estimated $75.2 billion in 2025, because most new students pay low tuition, state funding growth remains modest and operating challenges strain resources. As a result, colleges benefit from stronger demand without a corresponding boost in revenue or profit. Community colleges' policy and regulatory landscape is evolving rapidly at the federal and state levels. Recent federal actions, including the Trump administration’s elimination of race-based admissions practices and equity action plans, signal a move from earlier diversity and accountability requirements tied to federal funding. Persistent FAFSA processing delays and confusing changes have disrupted access to financial aid and uncertainty around Pell Grant structure and funding complicates efforts to support low-income students. State policy directions vary widely: while states like Ohio are imposing new restrictions on DEI initiatives and faculty rights, and New Jersey is contemplating a $20.0 billion funding cut, others like Illinois are expanding community colleges’ authority to offer bachelor’s degrees in high-demand fields. While ongoing policy reforms, demographic shifts and affordability concerns will continue to shape the industry, community colleges are poised to play a crucial role in broadening access to higher education and supporting targeted workforce growth. Colleges face strong tailwinds from increased demand for affordable, career-focused programs, growing interest in upskilling and new private-sector partnerships. However, uncertain funding, regulatory volatility and persistent financial aid challenges remain significant headwinds. Converting higher enrollment into stronger financial health will require stable resources, policy agility and ongoing innovation to serve a diverse student population. Overall, revenue is forecast to rise slowly at CAGR of 0.1%, reaching $75.5 billion in 2030.

Seeking a comprehensive database that encompasses high school students, college attendees, young professionals, or individuals interested in continuing education opportunities?

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Book publishers Colleges Universities Religious Organizations Education Supply Companies Office Supply Companies Fundraising Product Companies

This dataset is imported from the US Department of Commerce, National Telecommunications and Information Administration (NTIA) and its "Data Explorer" site. The underlying data comes from the US Census

1. dataset: Specifies the month and year of the survey as a string, in "Mon YYYY" format. The CPS is a monthly survey, and NTIA periodically sponsors Supplements to that survey.

2. variable: Contains the standardized name of the variable being measured. NTIA identified the availability of similar data across Supplements, and assigned variable names to ease time-series comparisons.

3. description: Provides a concise description of the variable.

4. universe: Specifies the variable representing the universe of persons or households included in the variable's statistics. The specified variable is always included in the file. The only variables lacking universes are isPerson and isHouseholder, as they are themselves the broadest universes measured in the CPS.

5. A large number of *Prop, *PropSE, *Count, and *CountSE columns comprise the remainder of the columns. For each demographic being measured (see below), four statistics are produced, including the estimated proportion of the group for which the variable is true (*Prop), the standard error of that proportion (*PropSE), the estimated number of persons or households in that group for which the variable is true (*Count), and the standard error of that count (*CountSE).

DEMOGRAPHIC CATEGORIES

1. us: The usProp, usPropSE, usCount, and usCountSE columns contain statistics about all persons and households in the universe (which represents the population of the fifty states and the District and Columbia). For example, to see how the prevelance of Internet use by Americans has changed over time, look at the usProp column for each survey's internetUser variable.

2. age: The age category is divided into five ranges: ages 3-14, 15-24, 25-44, 45-64, and 65+. The CPS only includes data on Americans ages 3 and older. Also note that household reference persons must be at least 15 years old, so the age314* columns are blank for household-based variables. Those columns are also blank for person-based variables where the universe is "isAdult" (or a sub-universe of "isAdult"), as the CPS defines adults as persons ages 15 or older. Finally, note that some variables where children are technically in the univese will show zero values for the age314* columns. This occurs in cases where a variable simply cannot be true of a child (e.g. the workInternetUser variable, as the CPS presumes children under 15 are not eligible to work), but the topic of interest is relevant to children (e.g. locations of Internet use).

3. work: Employment status is divided into "Employed," "Unemployed," and "NILF" (Not in the Labor Force). These three categories reflect the official BLS definitions used in official labor force statistics. Note that employment status is only recorded in the CPS for individuals ages 15 and older. As a result, children are excluded from the universe when calculating statistics by work status, even if they are otherwise considered part of the universe for the variable of interest.

4. income: The income category represents annual family income, rather than just an individual person's income. It is divided into five ranges: below $25K, $25K-49,999, $50K-74,999, $75K-99,999, and $100K or more. Statistics by income group are only available in this file for Supplements beginning in 2010; prior to 2010, family income range is available in public use datasets, but is not directly comparable to newer datasets due to the 2010 introduction of the practice of allocating "don't know," "refused," and other responses that result in missing data. Prior to 2010, family income is unkown for approximately 20 percent of persons, while in 2010 the Census Bureau began imputing likely income ranges to replace missing data.

5. education: Educational attainment is divided into "No Diploma," "High School Grad,

From 2020 to 2022, 5.2 percent of those with less than a high school diploma in the U.S. reported that they had a stroke during this period, compared to only 1.7 percent of those with a Bachelor's degree or higher. This statistic displays the percentage of adults in the U.S. who were told by a doctor they had a stroke from 2020 to 2022, by education.

BackgroundLife expectancy at birth in the United States will likely surpass 80 years in the coming decade. Yet recent studies suggest that longevity gains are unevenly shared across age and socioeconomic groups. First, mortality in midlife has risen among non-Hispanic whites. Second, low-educated whites have suffered stalls (men) or declines (women) in adult life expectancy, which is significantly lower than among their college-educated counterparts. Estimating the number of life years lost or gained by age and cause of death, broken down by educational attainment, is crucial in identifying vulnerable populations.Methods and FindingsUsing U.S. vital statistics data from 1990 to 2010, this study decomposes the change in life expectancy at age 25 by age and cause of death across educational attainment groups, broken down by race and gender. The findings reveal that mortality in midlife increased for white women (and to a lesser extent men) with 12 or fewer years of schooling, accounting for most of the stalls or declines in adult life expectancy observed in those groups. Among blacks, mortality declined in nearly all age and educational attainment groups. Although an educational gradient was found across multiple causes of death, between 60 and 80 percent of the gap in adult life expectancy was explained by cardiovascular diseases, smoking-related diseases, and external causes of death. Furthermore, the number of life years lost to smoking-related, external, and other causes of death increased among low- and high school-educated whites, explaining recent stalls or declines in longevity.ConclusionsLarge segments of the American population—particularly low- and high school-educated whites under age 55—are diverging from their college-educated counterparts and losing additional years of life to smoking-related diseases and external causes of death. If this trend continues, old-age mortality may also increase for these birth cohorts in the coming decades.

Context & Content

This dataset consists of the unemployment rate and education level of adults in the USA by county. That is, for each county in the USA, this dataset provides the count and percentage of unemployed adults as well as the count and percentage of adults of various educational backgrounds. Each county was been assigned one of four locale categories (City, Suburb, Town, Rural) according to its 2013 Urban Influence Code and their descriptions provided in UIC_codes.csv. From the descriptions of each of the codes and the descriptions of the locales "City", "Suburb", "Town", and "Rural" provided on page 2 of the locale user manual (locale_user_manual.pdf), each county was assigned one of four locales.

The unemployment rate data includes the count and percentage of unemployed adults for each county in the USA for each year from 2000-2020. The median household income for 2019 is also included. The education level data includes the count and percentage of adults with less than a high school diploma, a high school diploma only, some college, and a bachelor's degree/four years of college or more for the years 1970, 1980, 1990, 2000, and 2019. The Urban Influence Code data includes the UIC and locale description of each county in the USA and the locale user manual has been included as a PDF as strictly a reference file, to understand how each county was assigned a locale within the unemployment.csv and education.csv files.

Data Sources

Source for the unemployment rate and education level data by county: "County-level Data Sets." USDA Economic Research Service, US Department of Agriculture. Access date: Sept 8, 2021. URL: https://www.ers.usda.gov/data-products/county-level-data-sets/

Source for Urban Influence Codes by county: "Urban Influence Codes." USDA Economic Research Service, US Department of Agriculture. Access date: Sept 8, 2021. URL: https://www.ers.usda.gov/data-products/urban-influence-codes/#:~:text=The%202013%20Urban%20Influence%20Codes,to%20metro%20and%20micropolitan%20areas.&text=An%20update%20of%20the%20Urban,is%20planned%20for%20mid%2D2023.

Inspiration

This dataset was created to be used as an additional data source for the LearnPlatform COVID-19 Impact on Digital Learning Kaggle competition, but is suitable for other analyses related to unemployment rate and education level in the USA.

Snapshot img

US Community College Market Size 2025-2029

The US community college market size is forecast to increase by USD -7825.8 million, at a CAGR of -2.7% between 2024 and 2029.

The Community College market in the US is experiencing significant shifts driven by the growing emphasis on non-traditional learning and the evolving education marketing process. This trend is fueled by the increasing number of adults returning to education and the need for flexible learning options. However, community colleges face challenges in securing adequate funding, which may hinder their ability to meet the demands of an expanding student population. The education landscape is transforming, with community colleges playing a pivotal role in catering to the needs of non-traditional learners. The marketing process has become increasingly important as institutions compete for students in a crowded market.
Yet, reduced funding poses a significant challenge. Community colleges must navigate this financial obstacle by exploring innovative funding models and cost-effective solutions to maintain their competitiveness and continue providing accessible, affordable education. Adapting to these market dynamics and addressing funding constraints will be crucial for community colleges seeking to capitalize on opportunities and thrive in the evolving educational landscape.

What will be the size of the US Community College Market during the forecast period?

Explore in-depth regional segment analysis with market size data - historical 2019-2023 and forecasts 2025-2029 - in the full report.
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The community college market in the US is characterized by a shift towards hybrid learning and competency-based education, as resource management and curriculum mapping gain prominence. Student recruitment strategies are increasingly data-driven, with mobile learning and learning analytics playing crucial roles. Institutional advancement efforts include compliance regulations, capital campaigns, and board of trustees engagement. Budget allocation and information technology investments are key areas of focus for administrators, with technology infrastructure and program review shaping the future of education. Faculty governance, endowment management, and professional development are essential components of institutional success.
Skills gap analysis and blended learning are critical in addressing workforce needs, while accreditation standards ensure academic rigor. Personalized learning and alumni relations strengthen student engagement, and faculty recruitment and shared governance foster a collaborative learning environment.

How is this market segmented?

The market research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

Revenue Stream

  Government funds
  Tuition and fees
  Grants and contracts
  Others


Courses

  Associate degree
  TVET certification
  Continuing education
  Bachelors degree


Student Type

  Traditional
  Non-Traditional
  Online
  Recent High School Graduates
  Adult Learners
  Career Changers


Delivery Mode

  On-Campus
  Online
  Hybrid


Subject Area

  STEM
  Healthcare
  Business
  Liberal Arts


Geography

  North America

    US

By Revenue Stream Insights

The government funds segment is estimated to witness significant growth during the forecast period.

Community colleges in the US receive the majority of their revenue from government funds, primarily from state, local, and central sources. These funds support various aspects of college operations, including instructor salaries, staff compensation, and infrastructure improvements. Thirty-two out of the fifty states in the US employ funding formulas to distribute resources to their respective colleges. Some states, such as Washington and Ohio, have adopted performance-based funding models to incentivize enrollment growth and expedite graduation rates. Educational technology plays a significant role in community colleges, with online learning platforms and classroom technology enhancing the learning experience. Dual enrollment programs enable high school students to earn college credits, while GED preparation courses help adults attain their diplomas.

Faculty development and program assessment ensure academic rigor and continuous improvement. International students contribute to campus diversity, with career services and student affairs providing support. Campus safety and accessibility compliance are essential considerations, as are technical skills training, workforce development, certificate programs, and continuing education. Transfer agreements facilitate seamless transitions to four-year institutions, while ESL programs cater to non-native English speakers. Associate degrees and bachelor's

Graph and download economic data for Employment Level - High School Graduates, No College, 25 Yrs. & over (LNS12027660) from Jan 1992 to Jun 2025 about secondary schooling, secondary, 25 years +, tertiary schooling, education, household survey, employment, and USA.

Dataset contains information on Tempeans receiving post-secondary education, licenses, certificates. Data supports City's Achieve65Tempe goal that 65 percent of Tempe’s adult population access post-secondary education, resulting in a certification to an advanced degree by 2030.This page provides data for the Post-Secondary School Achievement Rate performance measure. Information on Tempe resident post-secondary attainment including 2-year degrees, 4-year degrees, and graduate degrees. Data supports City's Achieve65 Tempe goal that 65 percent of Tempe’s adult population access post-secondary education, resulting in a certification to an advanced degree by 2030. Data shows breakdown of post-secondary attainment by degree, by gender, for individuals 25 years and older.The performance measure dashboard is available at 3.09 Post-Secondary Achievement Rate.Additional InformationSource: US Census 1-year ACSContact: Marie RaymondContact E-Mail: Marie_Raymond@tempe.govData Source Type: ExcelPreparation Method: Numbers retrieved from US Census and entered into a detailed spreadsheet.Publish Frequency: AnnuallyPublish Method: ManualData Dictionary

The Longitudinal Study of American Youth (LSAY) was designed to examine the development of: (1) student attitudes toward and achievement in science, (2) student attitudes toward and achievement in mathematics, and (3) student interest in and plans for a career in science, mathematics, or engineering, during middle school, high school, and the first four years post-high school, and to estimate the relative influence of parents, home, teachers, school, peers, media, and selected informal learning experiences on these developmental patterns. At the time of the original award, it was not known if support would be available beyond the initial four-year period of support and the first years were designed to create a synthetic cohort that would extend from grade seven through the first year after high school. To allow the construction of this synthetic cohort, a two-cohort design was developed. The older LSAY cohort, Cohort One, consisted of a national sample of 2,829 tenth-grade students in public high schools throughout the United States. These students were followed for an initial period of seven years, ending four years after high school in 1994. Cohort Two, consisted of a national sample of 3,116 seventh-grade students in public schools that served as feeder schools to the same high schools in which the older cohort was enrolled. These students were followed for an initial period of seven years, concluding with a telephone interview approximately one year after the end of high school in 1994. Beginning in the fall of 1987, the LSAY collected a wide array of information from each student, including: (1) a science achievement test and a mathematics achievement test each fall, (2) an attitudinal and experience questionnaire at the beginning and end of each school year, (3) reports about education and experience from all science and math teachers in each school, (4) reports on classroom practice by each science and math teacher serving an LSAY student, (5) an annual 25-minute telephone interview with one parent of each student, and (6) extensive school-level information from the principal of each study school. In 2006, the NSF funded a proposal to re-contact the original LSAY students (now in their mid-30’s) to resume data collection to determine their educational and occupational outcomes. Through an extensive tracking activity (described in Kimmel and Miller, 2008), more than 95 percent of the original sample of 5,945 LSAY students were located or accounted for. A new eligible sample of approximately 5,000 students was defined and these young adults were asked to complete a survey in 2007. The public release data files include the information collected from the national probability sample students, their parents, and the science and mathematics teachers in their schools during the initial seven years, beginning in the fall of 1987, as well as the data collected in the 2007 questionnaire. The original two-cohort, two-file data structure reflected the initial period of data collection, but it was awkward for users that wanted to compare the two cohorts or to combine them for various analyses. The merged data file includes a variable to indicate the original cohort, allowing a user to repeat or extend any analysis conducted with the previous LSAY release file, but the naming of the variables in the merged file has been revised to correct dual or conflicting variable names and indicators. Equally important, the new merged file structure will facilitate the annual release of new cycles of data collection through the addition of variables to the base system. Analysts are encouraged to read the LSAY user guide before doing any data analysis. (Source: ICPSR, retrieved 07/19/2011)

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.

The Longitudinal Study of American Youth (LSAY) is a project that was funded by the National Science Foundation in 1985 and was designed to examine the development of: (1) student attitudes toward and achievement in science, (2) student attitudes toward and achievement in mathematics, and (3) student interest in and plans for a career in science, mathematics, or engineering, during middle school, high school, and the first four years post-high school. The relative influence parents, home, teachers, school, peers, media, and selected informal learning experiences had on these developmental patterns was considered as well. The older LSAY cohort, Cohort One, consisted of a national sample of 2,829 tenth-grade students in public high schools throughout the United States. These students were followed for an initial period of seven years, ending four years after high school in 1994. Cohort Two, consisted of a national sample of 3,116 seventh-grade students in public schools that served as feeder schools to the same high schools in which the older cohort was enrolled. These students were followed for an initial period of seven years, concluding with a telephone interview approximately one year after the end of high school in 1994. Beginning in the fall of 1987, the LSAY collected a wide array of information including: (1) a science achievement test and a mathematics achievement test each fall, (2) an attitudinal and experience questionnaire at the beginning and end of each school year, (3) reports about education and experience from all science and math teachers in each school, (4) reports on classroom practice by each science and math teacher serving a LSAY student, (5) an annual 25-minute telephone interview with one parent of each student, and (6) extensive school-level information from the principal of each study school. In 2006, the NSF funded a proposal to re-contact the original LSAY students (then in their mid-30's) to resume data collection to determine their educational and occupational outcomes. Through an extensive tracking activity which involved: (1) online tracking, (2) newsletter mailing, (3) calls to parents and other relatives, (4) use of alternative online search methods, and (5) questionnaire mailing, more than 95 percent of the original sample of 5,945 LSAY students were located or accounted for. In addition to re-contacting the students, the proposal defined a new eligible sample of approximately 5,000 students and these young adults were asked to complete a survey in 2007. A second survey was conducted in the fall of 2008 that sought to gather updated information about occupational and education outcomes and to measure the civic scientific literacy of these young adults, in which to date more than 3,200 participants have responded. A third survey was conducted in the fall of 2009 that sought to gather updated information about occupational and education outcomes and to measure the participants' use of selected informal science education resources, in which to date more than 3,200 participants have responded. A fourth survey was conducted in the fall of 2010 that sought to gather updated information about occupational and education outcomes, as well as provided questions about the participants' interactions with their children, in which to date more than 3,200 participants have responded. Finally, a fifth survey was conducted in the fall of 2011 that sought to gather updated information about education outcomes and included an expanded occupation battery for all participants, as well as an expanded spousal information battery for all participants. The 2011 questionnaire also included items about the 2011 Fukushima incident in Japan along with attitudinal items about nuclear power and global climate change. To date approximately 3,200 participants responded to the 2011 survey. There were no surveys conducted in 2012 or 2013. Beginning in 2014 the LSAY was funded by the National Institute on Aging for five years. This data release adds the 2017 data to the previous data release that included data through 2016. The public release data files include information collected from the national probability sample students, their parents, and the science and mathematics teachers in the students' schools. The data covers the initial seven years, beginning in the fall of 1987, as well as the data collected in the

Analysis of ‘Broadband Adoption and Computer Use by year, state, demographic characteristics’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/720f8c4b-7a1c-415c-9297-55904ba24840 on 26 January 2022.

--- Dataset description provided by original source is as follows ---

This dataset is imported from the US Department of Commerce, National Telecommunications and Information Administration (NTIA) and its "Data Explorer" site. The underlying data comes from the US Census

1. dataset: Specifies the month and year of the survey as a string, in "Mon YYYY" format. The CPS is a monthly survey, and NTIA periodically sponsors Supplements to that survey.

2. variable: Contains the standardized name of the variable being measured. NTIA identified the availability of similar data across Supplements, and assigned variable names to ease time-series comparisons.

3. description: Provides a concise description of the variable.

4. universe: Specifies the variable representing the universe of persons or households included in the variable's statistics. The specified variable is always included in the file. The only variables lacking universes are isPerson and isHouseholder, as they are themselves the broadest universes measured in the CPS.

5. A large number of *Prop, *PropSE, *Count, and *CountSE columns comprise the remainder of the columns. For each demographic being measured (see below), four statistics are produced, including the estimated proportion of the group for which the variable is true (*Prop), the standard error of that proportion (*PropSE), the estimated number of persons or households in that group for which the variable is true (*Count), and the standard error of that count (*CountSE).

DEMOGRAPHIC CATEGORIES

1. us: The usProp, usPropSE, usCount, and usCountSE columns contain statistics about all persons and households in the universe (which represents the population of the fifty states and the District and Columbia). For example, to see how the prevelance of Internet use by Americans has changed over time, look at the usProp column for each survey's internetUser variable.

2. age: The age category is divided into five ranges: ages 3-14, 15-24, 25-44, 45-64, and 65+. The CPS only includes data on Americans ages 3 and older. Also note that household reference persons must be at least 15 years old, so the age314* columns are blank for household-based variables. Those columns are also blank for person-based variables where the universe is "isAdult" (or a sub-universe of "isAdult"), as the CPS defines adults as persons ages 15 or older. Finally, note that some variables where children are technically in the univese will show zero values for the age314* columns. This occurs in cases where a variable simply cannot be true of a child (e.g. the workInternetUser variable, as the CPS presumes children under 15 are not eligible to work), but the topic of interest is relevant to children (e.g. locations of Internet use).

3. work: Employment status is divided into "Employed," "Unemployed," and "NILF" (Not in the Labor Force). These three categories reflect the official BLS definitions used in official labor force statistics. Note that employment status is only recorded in the CPS for individuals ages 15 and older. As a result, children are excluded from the universe when calculating statistics by work status, even if they are otherwise considered part of the universe for the variable of interest.

4. income: The income category represents annual family income, rather than just an individual person's income. It is divided into five ranges: below $25K, $25K-49,999, $50K-74,999, $75K-99,999, and $100K or more. Statistics by income group are only available in this file for Supplements beginning in 2010; prior to 2010, family income range is available in public use datasets, but is not directly comparable to newer datasets due to the 2010 introduction of the practice of allocating "don't know," "refused," and other responses that result in missing data. Prior to 2010, family income is unkown for approximately 20 percent of persons, while in 2010 the Census Bureau began imputing likely income ranges to replace missing data.

5. education: Educational attainment is divided into "No Diploma," "High School Grad,

--- Original source retains full ownership of the source dataset ---