This statistic shows the change in the United States' Korean population from 1980 to 2010. In 1980, there were 363,000 Korean-Americans (Korean immigrants and people with Korean heritage) living in the United States.

In 2024, about 170,251 U.S. citizens resided in South Korea, up from about 161,895 in the previous year. The number of U.S. citizens residing in South Korea has increased over the last few years.

In 1800, it is estimated that approximately 9.4 million people lived in the region of modern-day South Korea (and 13.8 million on the entire peninsula). The population of this region would remain fairly constant through much of the 19th century, but would begin to grow gradually starting in the mid-1800s, as the fall of the Joseon dynasty and pressure from the U.S. and Japan would end centuries of Korean isolationism. Following the opening of the country to foreign trade, the Korean peninsula would begin to modernize, and by the start of the 20th century, it would have a population of just over ten million. The Korean peninsula was then annexed by Japan in 1910, whose regime implemented industrialization and modernization policies that saw the population of South Korea rising from just under ten million in 1900, to over fifteen million by the start of the Second World War in 1939.

The Korean War Like most regions, the end of the Second World War coincided with a baby boom, that helped see South Korea's population grow by almost two million between 1945 and 1950. However, this boom would stop suddenly in the early 1950s, due to disruption caused by the Korean War. After WWII, the peninsula was split along the 38th parallel, with governments on both sides claiming to be the legitimate rulers of all Korea. Five years of tensions then culminated in North Korea's invasion of the South in June 1950, in the first major conflict of the Cold War. In September, the UN-backed South then repelled the Soviet- and Chinese-backed Northern army, and the frontlines would then fluctuate on either side of the 38th parallel throughout the next three years. The war came to an end in July, 1953, and had an estimated death toll of three million fatalities. The majority of fatalities were civilians on both sides, although the North suffered a disproportionate amount due to extensive bombing campaigns of the U.S. Unlike North Korea, the South's total population did not fall during the war.

Post-war South Korea Between the war's end and the late 1980s, the South's total population more than doubled. In these decades, South Korea was generally viewed as a nominal democracy under authoritarian and military leadership; it was not until 1988 when South Korea transitioned into a stable democracy, and grew its international presence. Much of South Korea's rapid socio-economic growth in the late 20th century was based on the West German model, and was greatly assisted by Japanese and U.S. investment. Today, South Korea is considered one of the world's wealthiest and most developed nations, ranking highly in terms of GDP, human development and life expectancy; it is home to some of the most valuable brands in the world, such as Samsung and Hyundai; and has a growing international cultural presence in music and cinema. In the past decades, South Korea's population growth has somewhat slowed, however it remains one of the most densely populated countries in the world, with total population of more than 51 million people.

Graph and download economic data for Population Level - Veterans, Vietnam-Era and Earlier Wartime Periods, 18 Years and over (LNU00077884) from Sep 2008 to Jun 2025 about korean war, Vietnam Era, World War, 18 years +, veterans, civilian, population, and USA.

Graph and download economic data for Unemployment Rate - Veterans, Vietnam-Era and Earlier Wartime Periods, 18 Years and over (LNU04077884) from Sep 2008 to Jun 2025 about korean war, Vietnam Era, World War, 18 years +, veterans, household survey, unemployment, rate, and USA.

Korea Population Projection: Mid Year data was reported at 47,731,321.000 Person in 2050. This records a decrease from the previous number of 48,162,628.000 Person for 2049. Korea Population Projection: Mid Year data is updated yearly, averaging 46,840,607.000 Person from Jun 1950 (Median) to 2050, with 101 observations. The data reached an all-time high of 52,796,081.000 Person in 2029 and a record low of 20,845,771.000 Person in 1950. Korea Population Projection: Mid Year data remains active status in CEIC and is reported by US Census Bureau. The data is categorized under Global Database’s Korea – Table KR.US Census Bureau: Demographic Projection.

This statistic shows the share of U.S. Americans who would support sending U.S. troops to South Korea to defend the country if North Korea invaded from 1990 to 2017. In 2017, 62 percent of Americans would support the United States sending troops to South Korea's aid if such an invasion took place.

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..The numbers by detailed Asian groups do not add to the total population. This is because the detailed Asian groups are tallies of the number of Asian responses rather than the number of Asian respondents. Responses that include more than one race and/or Asian group are counted several times. For example, a respondent reporting "Korean, Filipino, and Black or African American" would be included in the Korean as well as the Filipino numbers. "Specified" includes the remaining Other Asian write-in responses that were not tallied into separate groups in the table. "Not specified" includes respondents who checked the Other Asian response category on the ACS questionnaire and did not write in a specific group or wrote in a generic term such as "Asian" or "Asiatic.".The Hispanic origin and race codes were updated in 2020. For more information on the Hispanic origin and race code changes, please visit the American Community Survey Technical Documentation website..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 sa...

BackgroundAddressing contemporary anti-Asian racism and its impacts on health requires understanding its historical roots, including discriminatory restrictions on immigration, citizenship, and land ownership. Archival secondary data such as historical census records provide opportunities to quantitatively analyze structural dynamics that affect the health of Asian immigrants and Asian Americans. Census data overcome weaknesses of other data sources, such as small sample size and aggregation of Asian subgroups. This article explores the strengths and limitations of early twentieth-century census data for understanding Asian Americans and structural racism.MethodsWe used California census data from three decennial census spanning 1920–1940 to compare two criteria for identifying Asian Americans: census racial categories and Asian surname lists (Chinese, Indian, Japanese, Korean, and Filipino) that have been validated in contemporary population data. This paper examines the sensitivity and specificity of surname classification compared to census-designated “color or race” at the population level.ResultsSurname criteria were found to be highly specific, with each of the five surname lists having a specificity of over 99% for all three census years. The Chinese surname list had the highest sensitivity (ranging from 0.60–0.67 across census years), followed by the Indian (0.54–0.61) and Japanese (0.51–0.62) surname lists. Sensitivity was much lower for Korean (0.40–0.45) and Filipino (0.10–0.21) surnames. With the exception of Indian surnames, the sensitivity values of surname criteria were lower for the 1920–1940 census data than those reported for the 1990 census. The extent of the difference in sensitivity and trends across census years vary by subgroup.DiscussionSurname criteria may have lower sensitivity in detecting Asian subgroups in historical data as opposed to contemporary data as enumeration procedures for Asians have changed across time. We examine how the conflation of race, ethnicity, and nationality in the census could contribute to low sensitivity of surname classification compared to census-designated “color or race.” These results can guide decisions when operationalizing race in the context of specific research questions, thus promoting historical quantitative study of Asian American experiences. Furthermore, these results stress the need to situate measures of race and racism in their specific historical context.

This scatter chart displays GDP (current US$) against population (people) in Korea. The data is about countries per year.

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, for 2020, the 2020 Census provides the official counts of the population and housing units for the nation, states, counties, cities, and towns. For 2016 to 2019, the Population Estimates Program provides estimates of the population for the nation, states, counties, cities, and towns and intercensal housing unit estimates for the nation, 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, 2016-2020 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 numbers by detailed Asian groups do not add to the total population. This is because the detailed Asian groups are tallies of the number of Asian responses rather than the number of Asian respondents. Responses that include more than one race and/or Asian group are counted several times. For example, a respondent reporting "Korean, Filipino, and Black or African American" would be included in the Korean as well as the Filipino numbers. "Specified" includes the remaining Other Asian write-in responses that were not tallied into separate groups in the table. "Not specified" includes respondents who checked the Other Asian response category on the ACS questionnaire and did not write in a specific group or wrote in a generic term such as "Asian" or "Asiatic.".The Hispanic origin and race codes were updated in 2020. For more information on the Hispanic origin and race code changes, please visit the American Community Survey Technical Documentation website..The 2016-2020 American Community Survey (ACS) data generally reflect the September 2018 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 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.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.

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, 2023 American Community Survey 1-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..The numbers by detailed Asian groups do not add to the total population. This is because the detailed Asian groups are tallies of the number of Asian responses rather than the number of Asian respondents. Responses that include more than one race and/or Asian group are counted several times. For example, a respondent reporting "Korean, Filipino, and Black or African American" would be included in the Korean as well as the Filipino numbers. "Specified" includes the remaining Other Asian write-in responses that were not tallied into separate groups in the table. "Not specified" includes respondents who checked the Other Asian response category on the ACS questionnaire and did not write in a specific group or wrote in a generic term such as "Asian" or "Asiatic.".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.

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, 2022 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 numbers by detailed Asian groups do not add to the total population. This is because the detailed Asian groups are tallies of the number of Asian responses rather than the number of Asian respondents. Responses that include more than one race and/or Asian group are counted several times. For example, a respondent reporting "Korean, Filipino, and Black or African American" would be included in the Korean as well as the Filipino numbers. "Specified" includes the remaining Other Asian write-in responses that were not tallied into separate groups in the table. "Not specified" includes respondents who checked the Other Asian response category on the ACS questionnaire and did not write in a specific group or wrote in a generic term such as "Asian" or "Asiatic.".The Hispanic origin and race codes were updated in 2020. For more information on the Hispanic origin and race code changes, please visit the American Community Survey Technical Documentation website..The 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 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 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.

This Pew Research Center survey asked a nationally representative sample of 7,006 Asian American adults about their experiences living in, and views of, the United States. It covers topics such as racial and ethnic identity, religious identities and practices, policy priorities, discrimination and racism in America, affirmative action, global affairs, living with economic hardship and immigrant experiences.The survey sampled U.S. adults who self-identify as Asian, either alone or in combination with other races or Hispanic ethnicity. It included oversamples of the Chinese, Filipino, Indian, Korean and Vietnamese populations. Respondents were drawn from a national sample of residential mailing addresses, which included addresses from all 50 states and the District of Columbia. Specialized surname list frames were used to supplement the sample. The survey was conducted on paper and web in six languages: Chinese (Simplified and Traditional), English, Hindi, Korean, Tagalog and Vietnamese. Responses were collected from July 5, 2022, to Jan. 27, 2023.

In 2022, the total health expenditure in South Korea accounted for approximately 9.7 percent of South Korea's Gross Domestic Product (GDP). This was a slight increase from the previous year's share, making it the highest share in the past decade. Overall, this share indicates that as the GDP grew, health spending grew at an even faster rate. Korea's GDP per capita was estimated to have dropped to around 32.3 thousand U.S. dollars in 2022, an increase from around 19 thousand dollars in 2009. Meanwhile, overall medical expenditure in 2021 increased by around 7.5 percent compared to the previous year, up to around 93.5 trillion South Korean won. Nearly 60 percent of the costs were covered by the government or the public health insurance system.

Higher health spending is still insufficient

Even though the country has been an OECD member since 1996, health spending as a share of the GDP stayed below the OECD average of 8.8 percent until 2021. Similarly, the government’s health expenses lay at around 60 percent, showing a slight increase from the previous year, but this was still lower than the OECD average of almost 74 percent. The increased expenditure was largely attributed to the introduction of what is dubbed “Moon Jae-In Care”, named after the former Korean president, much like the American Affordable Care Act is colloquially known as “Obamacare”. In short, the government will provide greatly expanded coverage for medical treatments and care, increasing the reimbursement rate of the public health insurance, along with other measures. In addition, the Korean population as a whole is rapidly aging, and more people than before are being hospitalized and receiving examinations. Koreans already see doctors far more frequently than any other OECD nationals.

Strains on health spending and insurance

The Korean national public health insurance system enjoyed seven years of surplus revenue since 2011 but fell into the red in 2018. As noted above, Moon Jae-In Care and the aging population are largely responsible. The years’ worth of revenue is projected to run out in the coming years. Foreigners who come to Korea as medical tourists make things worse, with an all-time high of over 497 thousand medical tourists visiting Korea in 2019, though this has dropped off since the coronavirus (COVID-19) pandemic began.

727,986 (number) in 2019. According to U.S. Office of Management and Budget (OMB), “Asian” refers to a person having origins in any of the original peoples of the Far East, Southeast Asia, or the Indian subcontinent, including, for example, Cambodia, China, India, Japan, Korea, Malaysia, Pakistan, the Philippine Islands, Thailand, and Vietnam. The Asian population includes people who indicated their race(s) as “Asian” or reported entries such as “Asian Indian,” “Chinese,” “Filipino,” “Korean,” “Japanes"".

In 2024, approximately 958,959 Chinese (including those of Korean descent) resided in South Korea, the largest group of foreign nationals. This was followed by citizens from Vietnam, with around 305,936 people.

ACS DEMOGRAPHIC AND HOUSING ESTIMATES RACE - DP05 Universe - Total population Survey-Program - American Community Survey 5-year estimates Years - 2020, 2021, 2022 The concept “race alone” includes people who reported a single entry (e.g., Korean) and no other race, as well as people who reported two or more entries within the same major race group (e.g., Asian). For example, respondents who reported Korean and Vietnamese are part of the larger “Asian alone” race group.

US Language Learner Market size was estimated at USD 74.06 Billion in 2024 and is projected to reach USD 234.55 Billion by 2031, growing at a CAGR of 15.50% from 2024 to 2031.

Key Market Drivers • Increase in Globalized Communication: Heightened demand for multilingual communication skills is observed due to the growing interconnectedness of the world, fostered by international trade and travel. This demand is particularly true in the US, where businesses are increasingly operated on a global scale. As a result, the need to learn new languages to effectively collaborate with international partners is driven by globalization. • Evolving Educational Landscape: A shift towards incorporating language learning at a younger age is being observed in the educational system in the US. This shift is driven by a recognition of the cognitive benefits of multilingualism and the growing importance of foreign languages in the job market. As a result, language learning at a foundational level is exposed to a larger segment of the US population, creating a more fertile ground for continued language acquisition later in life. • Technological Advancements in Learning Methods: The rise of mobile technology and online learning platforms has significantly impacted the US language learner market. Language learning has been made more accessible and convenient than ever before by these advancements. A vast array of interactive and personalized language courses can now be accessed by learners on their own time and schedule. This surge in language learning participation within the US is fueled by this ease of access. • Growing Hispanic Population: A significant and rapidly growing Hispanic population is observed in the US. This demographic shift has led to a heightened demand for Spanish language learning within the country. Spanish language skills are increasingly seen as valuable not only for personal communication but also for professional opportunities in a diverse workforce. The growth of the Spanish language learning segment within the US market is propelled by this demand.

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, 2019 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 numbers by detailed Asian groups do not add to the total population. This is because the detailed Asian groups are tallies of the number of Asian responses rather than the number of Asian respondents. Responses that include more than one race and/or Asian group are counted several times. For example, a respondent reporting "Korean, Filipino, and Black or African American" would be included in the Korean as well as the Filipino numbers. "Specified" includes the remaining Other Asian write-in responses that were not tallied into separate groups in the table. "Not specified" includes respondents who checked the Other Asian response category on the ACS questionnaire and did not write in a specific group or wrote in a generic term such as "Asian" or "Asiatic.".The 2019 American Community Survey (ACS) data generally reflect the September 2018 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: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, or the margin of error associated with a median was larger than the median itself.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.