There were 347,602 international students studying at the undergraduate level in the United States in the 2022/23 academic year. In that same year, there were 467,027 international graduate students studying in the country, and a further 43,766 non-degree seeking international students.

Colleges and universities in the United States are still a popular study destination for Chinese students, with around 277 thousand choosing to take courses there in the 2023/24 academic year. Although numbers were heavily affected by the coronavirus pandemic, China is still the leading source of international students in the U.S. education market, accounting for 24.6 percent of all incoming students. The education exodus Mathematics and computer science courses led the field in terms of what Chinese students were studying in the United States, followed by engineering and business & management programs. The vast majority of Chinese students were self-funded, wth the remainder receiving state-funding to complete their overseas studies. Tuition fees can run into the tens of thousands of U.S. dollars, as foreign students usually pay out-of-state tuition fees. What about the local situation? Although studying abroad attracts many Chinese students, the country itself boasts the largest state-run education system in the world. With modernization of the national tertiary education system being a top priority for the Chinese government, the country has seen a significant increase in the number of local universities over the last decade. Enrolments in these universities exceeded 37 million in 2023, and a record of more than ten million students graduated in the same year, indicating that China's education market is still expanding.

The CPC-ONS-UUK Survey of Graduating International Students (SoGIS) is a collaborative project between the ESRC Centre for Population Change (CPC) at the University of Southampton, the Office for National Statistics (ONS) and Universities UK (UUK). SoGIS wave 1 collected detailed information from international students in UK Higher Education in their final year of study. SoGIS wave 2 is a follow-up survey administered to a subsample of students who participated in wave 1. The survey sampled both undergraduate and postgraduate, EU and non-EU finalist students. SoGIS Wave 1 contains 3560 responses from a sample of 101,049 (response rate 3.5%). SoGIS Wave 2 contains 563 responses from a sample of 1,517 (37% response rate). SoGIS provides valuable information about the post-study intentions, certainty of these intentions, travel patterns, use of public services, and working patterns whilst studying of international students approaching course completion. The survey increases our understanding of students migratory and employment intentions after studying.

Funded by the Economic and Social Research Council, the ESRC Centre for Population Change (CPC) is investigating how and why our population is changing and what this means for people, communities and governments. The Centre is a joint partnership between the Universities of Southampton, St. Andrews, and Stirling. Our research agenda is planned in collaboration with the Office for National Statistics and the National Records of Scotland. CPC is a founding partner of Population Europe, the network of Europe's leading research centres in the field of policy-relevant population studies.

The pattern of our lives is continuously changing; many of us now remain in education for longer than in the past, we delay becoming parents and we are living longer than ever before. The households we live in are more complex with more step- and half-kin but also more of us live alone at some point in our lives. Many of us move around locally, nationally and internationally for work and family. Our behaviours interact to create the society in which we live. CPC research aims to understand the causes and consequences of changes in births, deaths, relationships and migration to enable policy makers and planners to know how, when and where to respond. By finding out how our population is changing we can improve the world in which we live.

CPC research is organised around five thematic areas: 1. Fertility and family change 2. Increasing longevity and the changing life course 3. New mobilities and migration 4. Understanding intergenerational relations and exchange 5. Integrated demographic estimation and forecasting

These thematic areas explicitly recognise the dynamic interaction of the individual components of population change both with each other and with economic and social processes.

Midyear population estimates and projections for all countries and areas of the world with a population of 5,000 or more // Source: U.S. Census Bureau, Population Division, International Programs Center// Note: Total population available from 1950 to 2100 for 227 countries and areas. Other demographic variables available from base year to 2100. Base year varies by country and therefore data are not available for all years for all countries. For the United States, total population available from 1950-2060, and other demographic variables available from 1980-2060. See methodology at https://www.census.gov/programs-surveys/international-programs/about/idb.html

United States US: Adjusted Net Enrollment Rate: Primary: Male: % of Primary School Age Children data was reported at 93.137 % in 2015. This records an increase from the previous number of 92.551 % for 2014. United States US: Adjusted Net Enrollment Rate: Primary: Male: % of Primary School Age Children data is updated yearly, averaging 94.128 % from Dec 1986 (Median) to 2015, with 25 observations. The data reached an all-time high of 98.628 % in 1991 and a record low of 91.823 % in 2004. United States US: Adjusted Net Enrollment Rate: Primary: Male: % of Primary School Age Children data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United States – Table US.World Bank.WDI: Education Statistics. Adjusted net enrollment is the number of pupils of the school-age group for primary education, enrolled either in primary or secondary education, expressed as a percentage of the total population in that age group.; ; UNESCO Institute for Statistics; Weighted average; Each economy is classified based on the classification of World Bank Group's fiscal year 2018 (July 1, 2017-June 30, 2018).

About this dataset

Context

The dataset tabulates the Non-Hispanic population of International Falls by race. It includes the distribution of the Non-Hispanic population of International Falls across various race categories as identified by the Census Bureau. The dataset can be utilized to understand the Non-Hispanic population distribution of International Falls across relevant racial categories.

Key observations

Of the Non-Hispanic population in International Falls, the largest racial group is White alone with a population of 5,198 (92.71% of the total Non-Hispanic population).

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race: This column displays the racial categories (for Non-Hispanic) for the International Falls
• Population: The population of the racial category (for Non-Hispanic) in the International Falls is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of International Falls total Non-Hispanic population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for International Falls Population by Race & Ethnicity. You can refer the same here

Content

The United States Census Bureau’s International Dataset provides estimates of country populations since 1950 and projections through 2050. Specifically, the data set includes midyear population figures broken down by age and gender assignment at birth. Additionally, they provide time-series data for attributes including fertility rates, birth rates, death rates, and migration rates.

The full documentation is available here. For basic field details, please see the data dictionary.

Note: The U.S. Census Bureau provides estimates and projections for countries and areas that are recognized by the U.S. Department of State that have a population of at least 5,000.

Acknowledgements

This dataset was created by the United States Census Bureau.

Inspiration

Which countries have made the largest improvements in life expectancy? Based on current trends, how long will it take each country to catch up to today’s best performers?

Use this dataset with BigQuery

You can use Kernels to analyze, share, and discuss this data on Kaggle, but if you’re looking for real-time updates and bigger data, check out the data on BigQuery, too: https://cloud.google.com/bigquery/public-data/international-census.

United States US: Population: as % of Total: Female: Aged 65 and Above data was reported at 16.925 % in 2017. This records an increase from the previous number of 16.550 % for 2016. United States US: Population: as % of Total: Female: Aged 65 and Above data is updated yearly, averaging 14.035 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 16.925 % in 2017 and a record low of 10.023 % in 1960. United States US: Population: as % of Total: Female: Aged 65 and Above 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: Population and Urbanization Statistics. Female population 65 years of age or older as a percentage of the total female population. Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship.; ; World Bank staff estimates based on age/sex distributions of United Nations Population Division's World Population Prospects: 2017 Revision.; Weighted average; Relevance to gender indicator: Knowing how many girls, adolescents and women there are in a population helps a country in determining its provision of services.

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, the decennial census is the official source of population totals for April 1st of each decennial year. In between censuses, the Census Bureau's Population Estimates Program produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units and the group quarters population for states and counties..Information about the American Community Survey (ACS) can be found on the ACS website. Supporting documentation including code lists, subject definitions, data accuracy, and statistical testing, and a full list of ACS tables and table shells (without estimates) can be found on the Technical Documentation section of the ACS website.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2019-2023 American Community Survey 5-Year Estimates.ACS data generally reflect the geographic boundaries of legal and statistical areas as of January 1 of the estimate year. For more information, see Geography Boundaries by Year..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 roughly 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 ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..Users must consider potential differences in geographic boundaries, questionnaire content or coding, or other methodological issues when comparing ACS data from different years. Statistically significant differences shown in ACS Comparison Profiles, or in data users' own analysis, may be the result of these differences and thus might not necessarily reflect changes to the social, economic, housing, or demographic characteristics being compared. For more information, see Comparing ACS Data..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on 2020 Census data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution. For a 5-year median estimate, the margin of error associated with a median was larger than the median itself.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (X) The estimate or margin of error is not applicable or not available.median- The median falls in the lowest interval of an open-ended distribution (for example "2,500-")median+ The median falls in the highest interval of an open-ended distribution (for example "250,000+").** The margin of error could not be computed because there were an insufficient number of sample observations.*** The margin of error could not be computed because the median falls in the lowest interval or highest interval of an open-ended distribution.***** A margin of error is not appropriate because the corresponding estimate is controlled to an independent population or housing estimate. Effectively, the corresponding estimate has no sampling error and the margin of error may be treated as zero.

United States Unemployment Rate: Foreign Born: Male data was reported at 4.600 % in Feb 2025. This stayed constant from the previous number of 4.600 % for Jan 2025. United States Unemployment Rate: Foreign Born: Male data is updated monthly, averaging 4.550 % from Jan 2007 (Median) to Feb 2025, with 218 observations. The data reached an all-time high of 15.300 % in Apr 2020 and a record low of 2.100 % in Jun 2019. United States Unemployment Rate: Foreign Born: Male data remains active status in CEIC and is reported by U.S. Bureau of Labor Statistics. The data is categorized under Global Database’s United States – Table US.G037: Current Population Survey: Unemployment Rate.

For the original data source: https://data.census.gov/table/ACSDP5Y2023.DP02. Layer published for the Equity Explorer, a web experience developed by the LA County CEO Anti-Racism, Diversity, and Inclusion (ARDI) initiative in collaboration with eGIS and ISD. Visit the Equity Explorer to explore foreign born population and other equity related datasets and indices, including the COVID Vulnerability and Recovery Index. Foreign born population for census tracts in LA County from the US Census American Communities Survey (ACS), 2023. Estimates are based on 2020 census tract boundaries, and tracts are joined to 2021 Supervisorial Districts, Service Planning Areas (SPA), and Countywide Statistical Areas (CSA). For more information about this dataset, please contact egis@isd.lacounty.gov.

Graph and download economic data for Labor Force Participation Rate - Foreign Born (LNU01373395) from Jan 2007 to Feb 2025 about foreign, participation, civilian, 16 years +, labor force, labor, household survey, rate, and USA.

The layer was derived and compiled from the U.S. Census Bureau’s 2013 – 2017 American Community Survey (ACS) 5-Year Estimates in order to assist 2020 Census planning purposes.

Source: U.S. Census Bureau, Table B05002 PLACE OF BIRTH BY NATIVITY AND CITIZENSHIP STATUS, 2013 – 2017 ACS 5-Year Estimates

Effective Date: December 2018

Last Update: December 2019

Update Cycle: ACS 5-Year Estimates update annually each December. Vintage used for 2020 Census planning purposes by Broward County.

United States US: Pupil-Teacher Ratio: Primary data was reported at 14.457 % in 2015. This records a decrease from the previous number of 14.537 % for 2014. United States US: Pupil-Teacher Ratio: Primary data is updated yearly, averaging 14.454 % from Dec 1984 (Median) to 2015, with 25 observations. The data reached an all-time high of 16.173 % in 1995 and a record low of 13.591 % in 2010. United States US: Pupil-Teacher Ratio: Primary 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. Primary school pupil-teacher ratio is the average number of pupils per teacher in primary school.; ; UNESCO Institute for Statistics; Weighted average; Each economy is classified based on the classification of World Bank Group's fiscal year 2018 (July 1, 2017-June 30, 2018).

Graph and download economic data for Population Level - Foreign Born, Women (LNU00073397) from Jan 2007 to Feb 2025 about foreign, females, civilian, population, and USA.

Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Data and Documentation section...Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Tell us what you think. Provide feedback to help make American Community Survey data more useful for you..Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, it is the Census Bureau''s Population Estimates Program that produces and disseminates the official estimates of the population for the nation, states, counties, cities and towns and estimates of housing units for states and counties..Explanation of Symbols:An ''**'' entry in 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..An ''-'' entry in the estimate column indicates that 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..An ''-'' following a median estimate means the median falls in the lowest interval of an open-ended distribution..An ''+'' following a median estimate means the median falls in the upper interval of an open-ended distribution..An ''***'' entry in the margin of error column indicates that the median falls in the lowest interval or upper interval of an open-ended distribution. A statistical test is not appropriate..An ''*****'' entry in the margin of error column indicates that the estimate is controlled. A statistical test for sampling variability is not appropriate. .An ''N'' entry in the estimate and margin of error columns indicates that data for this geographic area cannot be displayed because the number of sample cases is too small..An ''(X)'' means that the estimate is not applicable or not available..Estimates of urban and rural population, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2010 data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..While the 2016 American Community Survey (ACS) data generally reflect the February 2013 Office of Management and Budget (OMB) definitions of metropolitan and micropolitan statistical areas; in certain instances the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB definitions due to differences in the effective dates of the geographic entities..Telephone service data are not available for certain geographic areas due to problems with data collection of this question that occurred in 2015 and 2016. Both ACS 1-year and ACS 5-year files were affected. It may take several years in the ACS 5-year files until the estimates are available for the geographic areas affected...Occupation codes are 4-digit codes and are based on Standard Occupational Classification 2010..Industry codes are 4-digit codes and are based on the North American Industry Classification System 2012. The Industry categories adhere to the guidelines issued in Clarification Memorandum No. 2, "NAICS Alternate Aggregation Structure for Use By U.S. Statistical Agencies," issued by the Office of Management and Budget..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 roughly 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..Source: U.S. Census Bureau, 2016 American Community Survey 1-Year Estimates

Abstract

IPUMS-International is an effort to inventory, preserve, harmonize, and disseminate census microdata from around the world. The project has collected the world's largest archive of publicly available census samples. The data are coded and documented consistently across countries and over time to facillitate comparative research. IPUMS-International makes these data available to qualified researchers free of charge through a web dissemination system.

The IPUMS project is a collaboration of the Minnesota Population Center, National Statistical Offices, and international data archives. Major funding is provided by the U.S. National Science Foundation and the Demographic and Behavioral Sciences Branch of the National Institute of Child Health and Human Development. Additional support is provided by the University of Minnesota Office of the Vice President for Research, the Minnesota Population Center, and Sun Microsystems.

Geographic coverage

National coverage

Analysis unit

Households and Group Quarters

UNITS IDENTIFIED: - Dwellings: No - Vacant units: Yes - Households: Yes - Individuals: Yes - Group quarters: Yes

UNIT DESCRIPTIONS: - Households: Dwelling places with fewer than five persons unrelated to a household head, excluding institutions and transient quarters. - Group quarters: Institutions, transient quarters, and dwelling places with five or more persons unrelated to a household head.

Universe

Residents of the 50 states (not the outlying areas).

Kind of data

Census/enumeration data [cen]

Sampling procedure

MICRODATA SOURCE: U.S. Census Bureau

SAMPLE UNIT: Household

SAMPLE FRACTION: 1%

SAMPLE SIZE (person records): 2,029,666

Mode of data collection

Face-to-face [f2f]

Research instrument

One in five housing units in 1970 received a long form containing supplemental sample questions. There were two versions of the long form, with different inquiries on both housing and population items; 15 percent of households received one version, and 5 percent received the other. Six independent 1 percent public use samples were produced for 1970, three from the 15 percent questionnaire and three from the 5 percent questionnaire. IPUMS-International uses the "Form 2 Metro" sample.

Response rate

UNDERCOUNT: No official estimates

Snapshot img

US Compliance Training Market Size 2024-2028

The US Compliance Training Market size is forecast to increase by USD 1.57 billion, at a CAGR of 15.2% between 2023 and 2028. The market is experiencing significant growth due to the increase in demand for customized courses and personalized learning, which drives institutions to tailor their offerings to individual student needs. Simultaneously, there is a continuous need for compliance with federal regulations, ensuring that institutions adhere to evolving standards and maintain accreditation. Additionally, the rise in the international student population further fuels market expansion as schools and universities strive to attract and support a diverse student base. Together, these factors contribute to a dynamic educational landscape where institutions must adapt and innovate to meet both regulatory requirements and the growing expectations of a global student community.

What will be the Size of the Market During the Forecast Period?

For More Highlights About this Report, Request Free Sample

Market Dynamic and Customer Landscape

The market has gained significant traction due to the increasing demand for ensuring food safety and maintaining the quality of perishable items, particularly raw fish. Companies like Allwin Roto Plast cater to this need by providing insulated tubs, fish boxes, and fish containers made of high-density polyethylene, fiberglass, and stainless steel. These containers prioritize integrity, durability, and longevity to ensure fresh fish during transportation and handling. Size and capacity, hygiene, and cleaning are crucial factors in the selection of these containers. Monsoons and other environmental factors necessitate the use of containers that can withstand harsh conditions. Plastic pallets, fabric-lined containers, and fish boxes with stackability features facilitate efficient storage and ease of handling. Raw fish processors rely on these compliance training and adherence to regulations to maintain their business operations and customer trust. The market is expected to grow due to the increasing focus on food safety and the need for sustainable and eco-friendly packaging solutions.

Key Market Driver

Increase in demand for customized courses and personalized learning is notably driving market growth. The compliance training market is experiencing significant growth due to the increasing demand for customized courses in various sectors, particularly in higher education. In this context, institutions in the US have unique regulatory requirements based on factors such as size, employee count, student enrollments, and types of courses offered. These differences necessitate customized compliance training programs, as off-the-shelf courses may not effectively address the specific needs of each institution.

Consequently, vendors like Skillsoft and Campus Answers are providing tailored solutions to cater to the diverse requirements of educational institutions. This trend is driven by the shift towards circular economy projects, which prioritize the reduction and management of ocean plastic waste, including that derived from polystyrene. Customized compliance training plays a crucial role in ensuring adherence to the regulations and codes of conduct associated with these projects. Thus, such factors are driving the growth of the market during the forecast period.

Significant Market Trends

Increasing emphasis on microlearning is the key trend in the market. Compliance training is evolving with the adoption of microlearning, a platform that delivers training content in short, easily digestible modules. This approach is particularly effective for ocean plastic and polystyrene compliance training, as it allows learners to absorb complex information through short videos, animations, infographics, and other multimedia formats. The flexibility of microlearning caters to diverse learning styles and schedules, enhancing retention rates without compromising learner motivation.

Further, organizations can leverage this method to deliver accurate and timely information, aligning with their circular economy projects and sustainability initiatives. Microlearning's adaptability and convenience make it an indispensable tool for effective and efficient compliance training. Thus, such trends will shape the growth of the market during the forecast period.

Major Market Challenge

Lack of adequate funding and infrastructure is the major challenge that affects the growth of the market. The compliance training market has seen varying growth trends due to numerous factors. One significant challenge is the financial constraints faced by educational institutions, particularly in the United States. In 2017, weak state tax revenue growth led to budget deficits for many states. Reduced grant funding for colleges and universities, coupled with increasing student debt, has affected the market's growth. These cir

Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the .Technical Documentation.. section......Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the .Methodology.. section..Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, it is the Census Bureau's Population Estimates Program that produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units for states and counties..Explanation of Symbols:..An "**" entry in 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..An "-" entry in the estimate column indicates that 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..An "-" following a median estimate means the median falls in the lowest interval of an open-ended distribution..An "+" following a median estimate means the median falls in the upper interval of an open-ended distribution..An "***" entry in the margin of error column indicates that the median falls in the lowest interval or upper interval of an open-ended distribution. A statistical test is not appropriate..An "*****" entry in the margin of error column indicates that the estimate is controlled. A statistical test for sampling variability is not appropriate. .An "N" entry in the estimate and margin of error columns indicates that data for this geographic area cannot be displayed because the number of sample cases is too small..An "(X)" means that the estimate is not applicable or not available...Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2010 data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..While the 2013-2017 American Community Survey (ACS) data generally reflect the February 2013 Office of Management and Budget (OMB) definitions of metropolitan and micropolitan statistical areas; in certain instances the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB definitions due to differences in the effective dates of the geographic entities..Occupation codes are 4-digit codes and are based on Standard Occupational Classification 2010..Industry codes are 4-digit codes and are based on the North American Industry Classification System 2012. The Industry categories adhere to the guidelines issued in Clarification Memorandum No. 2, "NAICS Alternate Aggregation Structure for Use By U.S. Statistical Agencies," issued by the Office of Management and Budget..Methodological changes to data collection in 2013 may have affected language data for 2013. Users should be aware of these changes when using 2013 data or multi-year data containing data from 2013. For more information, see: .Language User Note..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 roughly 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..Source: U.S. Census Bureau, 2013-2017 American Community Survey 5-Year Estimates

United States Labour Force Parti Rate: sa: Age 25 & Over: SomeCollege ButNumber Degree data was reported at 65.300 % in Oct 2018. This stayed constant from the previous number of 65.300 % for Sep 2018. United States Labour Force Parti Rate: sa: Age 25 & Over: SomeCollege ButNumber Degree data is updated monthly, averaging 72.400 % from Jan 1992 (Median) to Oct 2018, with 322 observations. The data reached an all-time high of 76.100 % in May 1994 and a record low of 65.300 % in Oct 2018. United States Labour Force Parti Rate: sa: Age 25 & Over: SomeCollege ButNumber Degree data remains active status in CEIC and is reported by Bureau of Labor Statistics. The data is categorized under Global Database’s United States – Table US.G011: Current Population Survey: Labour Force: Seasonally Adjusted.