Throughout the 19th century, the share of military personnel employed by the United States government was below 0.2 percent of the total population in most years. There were noticeable spikes in enlistments and conscriptions during the American Civil War (1861-65), the First World War (1917-18*), and Second World War (1941-45*), as well as smaller increases during the Mexican-American War (1946-48) and the Spanish-American War (1898), but figures were generally much lower than the post-WWII era.

Following the Second World War, the United States abandoned many of its isolationist positions as it sought to become the world's leading superpower. This involved stationing millions of troops in overseas bases during the Cold War, in strategically important locations such as West Germany, Japan, and Taiwan. Additionally, involvement in conflicts such as the Korean War (1950-1953) and Vietnam War (1964-1973*) kept military employment high, usually between 1-2 percent until the 1970s. Figures remained just below the one percent mark until the 1990s, when the end of the Cold War and the growing influence of technology in conventional warfare saw a decrease in demand for many traditional combat roles. Despite U.S. involvement in a number of overseas conflicts in the 21st century, military personnel represented less than 0.5 percent of the total population in most years between 2000 and 2016.

The graph illustrates the number of personnel in each branch of the U.S. Military for the year 2025. The x-axis lists the military branches: Army, Navy, Marine Corps, Air Force, Space Force, and Coast Guard. The y-axis represents the number of personnel, ranging from 41,477 to 449,265. Among the branches, the Army has the highest number of personnel with 449,265, followed by the Navy with 333,794 and the Air Force with 317,675. The Marine Corps and Coast Guard have 168,628 and 41,477 personnel, respectively. The data is displayed in a bar graph format, effectively highlighting the distribution of military personnel across the different branches.

In the past four centuries, the population of the United States has grown from a recorded 350 people around the Jamestown colony of Virginia in 1610, to an estimated 331 million people in 2020. The pre-colonization populations of the indigenous peoples of the Americas have proven difficult for historians to estimate, as their numbers decreased rapidly following the introduction of European diseases (namely smallpox, plague and influenza). Native Americans were also omitted from most censuses conducted before the twentieth century, therefore the actual population of what we now know as the United States would have been much higher than the official census data from before 1800, but it is unclear by how much. Population growth in the colonies throughout the eighteenth century has primarily been attributed to migration from the British Isles and the Transatlantic slave trade; however it is also difficult to assert the ethnic-makeup of the population in these years as accurate migration records were not kept until after the 1820s, at which point the importation of slaves had also been illegalized. Nineteenth century In the year 1800, it is estimated that the population across the present-day United States was around six million people, with the population in the 16 admitted states numbering at 5.3 million. Migration to the United States began to happen on a large scale in the mid-nineteenth century, with the first major waves coming from Ireland, Britain and Germany. In some aspects, this wave of mass migration balanced out the demographic impacts of the American Civil War, which was the deadliest war in U.S. history with approximately 620 thousand fatalities between 1861 and 1865. The civil war also resulted in the emancipation of around four million slaves across the south; many of whose ancestors would take part in the Great Northern Migration in the early 1900s, which saw around six million black Americans migrate away from the south in one of the largest demographic shifts in U.S. history. By the end of the nineteenth century, improvements in transport technology and increasing economic opportunities saw migration to the United States increase further, particularly from southern and Eastern Europe, and in the first decade of the 1900s the number of migrants to the U.S. exceeded one million people in some years. Twentieth and twenty-first century The U.S. population has grown steadily throughout the past 120 years, reaching one hundred million in the 1910s, two hundred million in the 1960s, and three hundred million in 2007. In the past century, the U.S. established itself as a global superpower, with the world's largest economy (by nominal GDP) and most powerful military. Involvement in foreign wars has resulted in over 620,000 further U.S. fatalities since the Civil War, and migration fell drastically during the World Wars and Great Depression; however the population continuously grew in these years as the total fertility rate remained above two births per woman, and life expectancy increased (except during the Spanish Flu pandemic of 1918).

Since the Second World War, Latin America has replaced Europe as the most common point of origin for migrants, with Hispanic populations growing rapidly across the south and border states. Because of this, the proportion of non-Hispanic whites, which has been the most dominant ethnicity in the U.S. since records began, has dropped more rapidly in recent decades. Ethnic minorities also have a much higher birth rate than non-Hispanic whites, further contributing to this decline, and the share of non-Hispanic whites is expected to fall below fifty percent of the U.S. population by the mid-2000s. In 2020, the United States has the third-largest population in the world (after China and India), and the population is expected to reach four hundred million in the 2050s.

In the fiscal year of 2019, 21.39 percent of active-duty enlisted women were of Hispanic origin. The total number of active duty military personnel in 2019 amounted to 1.3 million people.

Ethnicities in the United States The United States is known around the world for the diversity of its population. The Census recognizes six different racial and ethnic categories: White American, Native American and Alaska Native, Asian American, Black or African American, Native Hawaiian and Other Pacific Islander. People of Hispanic or Latino origin are classified as a racially diverse ethnicity.

The largest part of the population, about 61.3 percent, is composed of White Americans. The largest minority in the country are Hispanics with a share of 17.8 percent of the population, followed by Black or African Americans with 13.3 percent. Life in the U.S. and ethnicity However, life in the United States seems to be rather different depending on the race or ethnicity that you belong to. For instance: In 2019, native Hawaiians and other Pacific Islanders had the highest birth rate of 58 per 1,000 women, while the birth rae of white alone, non Hispanic women was 49 children per 1,000 women.

The Black population living in the United States has the highest poverty rate with of all Census races and ethnicities in the United States. About 19.5 percent of the Black population was living with an income lower than the 2020 poverty threshold. The Asian population has the smallest poverty rate in the United States, with about 8.1 percent living in poverty.

The median annual family income in the United States in 2020 earned by Black families was about 57,476 U.S. dollars, while the average family income earned by the Asian population was about 109,448 U.S. dollars. This is more than 25,000 U.S. dollars higher than the U.S. average family income, which was 84,008 U.S. dollars.

There were 449,344 active duty U.S. Army members in 2023. This amount represents a slight decrease in comparison to the number recorded in the previous year. Overall, there were 1.27 million active duty U.S. Department of Defense members, including officers and enlisted personnel in 2023.

This scatter chart displays military expenditure (% of GDP) against rural population (people) in the United States. The data is filtered where the date is 2023. The data is about countries per year.

The U.S. Army remains the largest branch of the American military, with 449,344 active duty personnel in 2023. While the Army leads in numbers, the newly established Space Force had just 8,879 active duty members, highlighting the evolving nature of modern warfare and the increasing importance of space-based capabilities. Confidence in military remains high Despite fluctuations in force size, public trust in the U.S. military remains strong. In 2024, 61 percent of Americans expressed a great deal or quite a lot of confidence in the armed forces, a slight increase from the previous year. While a slightly higher share of Republicans have shown more confidence in the military, trust in the institution remains high across party lines. Global commitments The United States continues to invest heavily in its military capabilities, with defense spending reaching 916.02 billion U.S. dollars in 2023. This substantial budget supports not only domestic defense needs but also enables the U.S. to respond to global crises, as evidenced by the over 40 billion euros in military aid provided to Ukraine following Russia's invasion. The high level of spending, which translates to about 2,220 U.S. dollars per capita.

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..Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, for 2010, the 2010 Census provides the official counts of the population and housing units for the nation, states, counties, cities and towns. For 2006 to 2009, the Population Estimates Program provides intercensal estimates of the population for the nation, 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 2000 data. Boundaries for urban areas have not been updated since Census 2000. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..While the 2006-2010 American Community Survey (ACS) data generally reflect the December 2009 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..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, 2006-2010 American Community Survey

SELECTED SOCIAL CHARACTERISTICS IN THE UNITED STATES VETERAN STATUS - DP02 Universe - Civilian population 18 Year and over Survey-Program - American Community Survey 5-year estimates Years - 2020, 2021, 2022 Veteran status is used to identify people with active duty military service and service in the military Reserves and the National Guard. Veterans are men and women who have served (even for a short time), but are not currently serving, on active duty in the U.S. Army, Navy, Air Force, Marine Corps, or the Coast Guard, or who served in the U.S. Merchant Marine during World War II. People who served in the National Guard or Reserves are classified as veterans only if they were ever called or ordered to active duty, not counting the 4-6 months for initial training or yearly summer camps.

This scatter chart displays military expenditure (% of GDP) against female population (people) in the United States. The data is filtered where the date is 2021. The data is about countries per year.

analyze the current population survey (cps) annual social and economic supplement (asec) with r the annual march cps-asec has been supplying the statistics for the census bureau's report on income, poverty, and health insurance coverage since 1948. wow. the us census bureau and the bureau of labor statistics ( bls) tag-team on this one. until the american community survey (acs) hit the scene in the early aughts (2000s), the current population survey had the largest sample size of all the annual general demographic data sets outside of the decennial census - about two hundred thousand respondents. this provides enough sample to conduct state- and a few large metro area-level analyses. your sample size will vanish if you start investigating subgroups b y state - consider pooling multiple years. county-level is a no-no. despite the american community survey's larger size, the cps-asec contains many more variables related to employment, sources of income, and insurance - and can be trended back to harry truman's presidency. aside from questions specifically asked about an annual experience (like income), many of the questions in this march data set should be t reated as point-in-time statistics. cps-asec generalizes to the united states non-institutional, non-active duty military population. the national bureau of economic research (nber) provides sas, spss, and stata importation scripts to create a rectangular file (rectangular data means only person-level records; household- and family-level information gets attached to each person). to import these files into r, the parse.SAScii function uses nber's sas code to determine how to import the fixed-width file, then RSQLite to put everything into a schnazzy database. you can try reading through the nber march 2012 sas importation code yourself, but it's a bit of a proc freak show. this new github repository contains three scripts: 2005-2012 asec - download all microdata.R down load the fixed-width file containing household, family, and person records import by separating this file into three tables, then merge 'em together at the person-level download the fixed-width file containing the person-level replicate weights merge the rectangular person-level file with the replicate weights, then store it in a sql database create a new variable - one - in the data table 2012 asec - analysis examples.R connect to the sql database created by the 'download all microdata' progr am create the complex sample survey object, using the replicate weights perform a boatload of analysis examples replicate census estimates - 2011.R connect to the sql database created by the 'download all microdata' program create the complex sample survey object, using the replicate weights match the sas output shown in the png file below 2011 asec replicate weight sas output.png statistic and standard error generated from the replicate-weighted example sas script contained in this census-provided person replicate weights usage instructions document. click here to view these three scripts for more detail about the current population survey - annual social and economic supplement (cps-asec), visit: the census bureau's current population survey page the bureau of labor statistics' current population survey page the current population survey's wikipedia article notes: interviews are conducted in march about experiences during the previous year. the file labeled 2012 includes information (income, work experience, health insurance) pertaining to 2011. when you use the current populat ion survey to talk about america, subract a year from the data file name. as of the 2010 file (the interview focusing on america during 2009), the cps-asec contains exciting new medical out-of-pocket spending variables most useful for supplemental (medical spending-adjusted) poverty research. confidential to sas, spss, stata, sudaan users: why are you still rubbing two sticks together after we've invented the butane lighter? time to transition to r. :D

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..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..Source: U.S. Census Bureau, 2021 American Community Survey 1-Year Estimates.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..The 2021 American Community Survey (ACS) data generally reflect the March 2020 Office of Management and Budget (OMB) delineations 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 delineations due to differences in the effective dates of the geographic entities..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..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.

In 2023, there were around 1.11 million active duty U.S. Armed Forces personnel stationed within the United States. In that year, there were 156,418 U.S. Armed Forces personnel stationed in California, the most of any state.

This scatter chart displays military expenditure (% of GDP) against urban population (people) in South America. The data is filtered where the date is 2023. The data is about countries per year.

These Public Use Microdata Sample (PUMS) files contain records representing a 5-percent sample of the occupied and vacant housing units in the United States and the people in the occupied units. People living in group quarters also are included. The files provide individual weights for persons and housing units, which when applied to the individual records, expand the sample to the relevant totals. Some of the items on the housing record are acreage, agricultural sales, allocation flags for housing items, bedrooms, condominium fee, contract rent, cost of utilities, family income in 1999, family, subfamily, and relationship recodes, farm residence, fire, hazard, and flood insurance, fuels used, gross rent, heating fuel, household income in 1999, household type, housing unit weight, kitchen facilities, linguistic isolation, meals included in rent, mobile home costs, mortgage payment, mortgage status, plumbing facilities, presence and age of own children, presence of subfamilies in household, real estate taxes, number of rooms, selected monthly owner costs, size of building (units in structure), state code, telephone service, tenure, vacancy status, value (of housing unit), vehicles available, year householder moved into unit, and year structure built. Some of the items on the person record are ability to speak English, age, allocation flags for population items, ancestry, citizenship, class of worker, disability status, earnings in 1999, educational attainment, grandparents as caregivers, Hispanic origin, hours worked, income in 1999 by type, industry, language spoken at home, marital status, means of transportation to work, migration Public Use Microdata Area (PUMA), migration state, mobility status, veteran period of service, years of military service, occupation, persons weight, personal care limitation, place of birth, place of work PUMA, place of work state, poverty status in 1999, race, relationship, school enrollment and type of school, time of departure for work, travel time to work, vehicle occupancy, weeks worked in 1999, work limitation status, work status in 1999, and year of entry. The Public Use Microdata Sample (PUMS) files contain geographic units known as Public Use Microdata Areas (PUMAs) and super-Public Use Microdata Areas (super-PUMAs). To maintain the confidentiality of the PUMS data, minimum population thresholds are set for PUMAs and super-PUMAs. For the 1-percent state-level files, the super-PUMAs contain a minimum population of 400,000 and are composed of a PUMA or a group of contiguous PUMAs delineated on the 5-percent state-level PUMS files. Super-PUMAs are a new geographic entity for Census 2000. The 5-percent state-level files contain PUMAs, each having a minimum population of 100,000, and corresponding super-PUMA codes. Each state is separately identified and may be comprised of one or more super-PUMAs or PUMAs. Large metropolitan areas may be subdivided into super-PUMAs and PUMAs. PUMAs and super-PUMAs do not cross state lines. Super-PUMAs and PUMAs also are defined for place of residence on April 1, 1995, and place of work.

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..Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, for 2010, the 2010 Census provides the official counts of the population and housing units for the nation, states, counties, cities and towns. For 2006 to 2009, the Population Estimates Program provides intercensal estimates of the population for the nation, 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 2000 data. Boundaries for urban areas have not been updated since Census 2000. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..While the 2006-2010 American Community Survey (ACS) data generally reflect the December 2009 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..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, 2006-2010 American Community Survey

This scatter chart displays male population (people) against military expenditure (% of GDP) in Central America. The data is filtered where the date is 2021. The data is about countries per year.

Annual Population Estimates for the United States; States; Metropolitan Statistical Areas, Micropolitan Statistical Areas, and Related Statistical Areas; Counties; and Subcounty Places; and for Puerto Rico and Its Municipios: April 1, 2010 to July 1, 2016 // Source: U.S. Census Bureau, Population Division // The contents of this file are released on a rolling basis from December through May. // Note: The estimates are based on the 2010 Census and reflect changes to the April 1, 2010 population due to the Count Question Resolution program and geographic program revisions. // The Office of Management and Budget's statistical area delineations for metropolitan, micropolitan, and combined statistical areas, as well as metropolitan divisions, are those issued by that agency in July 2015. // The 2010 Census did not ascertain the military status of the household population. Therefore, variables for the 2010 Census civilian, civilian noninstitutionalized, and resident population plus Armed Forces overseas populations cannot be derived and are not available on this file. // For detailed information about the methods used to create the population estimates, see https://www.census.gov/programs-surveys/popest/technical-documentation/methodology.html. // Each year, the Census Bureau's Population Estimates Program (PEP) utilizes current data on births, deaths, and migration to calculate population change since the most recent decennial census, and produces a time series of estimates of population. The annual time series of estimates begins with the most recent decennial census data and extends to the vintage year. The vintage year (e.g., Vintage 2016) refers to the final year of the time series. The reference date for all estimates is July 1, unless otherwise specified. With each new issue of estimates, the Census Bureau revises estimates for years back to the last census. As each vintage of estimates includes all years since the most recent decennial census, the latest vintage of data available supersedes all previously produced estimates for those dates. The Population Estimates Program provides additional information including historical and intercensal estimates, evaluation estimates, demographic analysis, and research papers on its website: https://www.census.gov/programs-surveys/popest.html.

The American Samoa Summary File contains data on population and housing subjects compiled from questions on the 2010 American Samoa Census questionnaire. Population subjects include age, sex, children ever born, citizenship status, foreign-born status, disability status, educational attainment, ethnic origin or race, family type, grandparents as caregivers, group quarters population, health insurance coverage status, household type and relationship, employment status and subsistence activity, work experience, class of worker, industry, occupation, place of work, journey to work, travel time to work, language spoken at home and frequency of language usage, marital status, nativity, year of entry, place of birth, parents' place of birth, earnings, income, remittances sent abroad, poverty status, residence in 2009, reason for moving, school enrollment, vocational training, military dependents and veteran status. Housing subjects include air conditioning, battery-operated radio ownership, computer ownership, gross rent, internet service, kitchen facilities, cooking facilities, mortgage status, number of rooms, number of bedrooms, occupancy status, occupants per room, plumbing facilities, condominium fee, selected monthly owner costs, sewage disposal, water supply, source of water, telephone service available, tenure, type of building materials, units in structure, vacancy status, value of home, vehicles available, year householder moved into unit and year structure built. The data are organized in 405 tables, one variable per table cell, which are presented at up to 19 levels of observation, including American Samoa as a whole, districts (including two separate atolls), counties, villages, census tracts, block groups, blocks and 5-digit ZIP Code Tabulation Areas. Fifty tables are presented at the block level and higher, 250 at the block group level and higher and 105 at the census tract level and higher. Additionally, the tables are iterated for the urban and rural geographic components of districts/atolls and 21 geographic components of American Samoa as a whole: 15 urban components (total urban, urbanized areas, urban clusters, and urbanized areas and urban clusters of various population sizes) and 6 rural components (total rural, rural areas outside places, rural areas inside places and inside places of various population sizes). Due to problems in the initial version, the Census Bureau ultimately issued the tables as three data products. The first or main release comprises 32 data files with all the tables except PBG7 (Nativity by Citizen Status by Year of Entry), PBG9 (Year of Entry for the Foreign-born Population) and ten tables on selected monthly owner costs, the tables HBG72, HBG73, HBG74, HBG75, HBG76, HBG77, HBG78, HCT17, HCT18, and HCT19. The second, called the American Samoa Year of Entry Summary File, consists of two data files with the tables PBG7 and PBG9. The third is a document file with the ten tables on selected monthly owner costs. This data collection comprises a codebook and three ZIP archives. The first archive contains the 32 data files in the main release, the second the two Year of Entry data files and the third contains the document file with the ten selected monthly owner costs tables and additional technical documentation.

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 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, 2018-2022 American Community Survey 5-Year Estimates.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..The 2018-2022 American Community Survey (ACS) data generally reflect the March 2020 Office of Management and Budget (OMB) delineations 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 delineation lists due to differences in the effective dates of the geographic entities..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.