This statistic displays the number of people speaking Indian languages in the United States as of July 2017, by language. As of this date, there were around *** thousand Hindi speakers in the United States.

In 2023, around 43.37 million people in the United States spoke Spanish at home. In comparison, approximately 998,179 people were speaking Russian at home during the same year. The distribution of the U.S. population by ethnicity can be accessed here. A ranking of the most spoken languages across the world can be accessed here.

This dataset includes the year, state, and the total number of speakers for each language (including indian and foreign languages) in each state in the USA.

Note: Indian languages refer to those listed in Schedule 8 of the Constitution of India.

This data was made as part of the Alaska Experimental Program to Stimulate Competitive Research (EPSCoR) Northern Test Case. The data can be used to look at language skills and retention over time. This data is the percent of the American and Alaska Native population that speaks only Other. Other languages include: Navajo, Other Native American languages, Hungarian, Arabic, Hebrew, African languages, All other languages. We chose only Natives because our interest is Alaska Natives. However, data for places like Anchorage might have a large other Native presence which should be examined. Source: American Community Survey (ACS) Extent: Data is for all communities in Alaska. Notes: We chose only Natives because our interest is Alaska Natives. However, data for places like Anchorage might have a large other Native presence which should be examined.

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 2011-2015 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..When information is missing or inconsistent, the Census Bureau uses a method called imputation to assign values. Responses assigned using the Census Bureau's imputation method are called imputed values. The "Percent Imputed" section is the percent of respondents who received an imputed value for a particular subject. ..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, 2011-2015 American Community Survey 5-Year Estimates

The American Community Survey (ACS) replaced the United States (US) Census Long Form Survey after 2000 as the only systematic source of community-level information on the American Indian and Alaska Native (AIAN) population living in rural Alaska communities. We define rural Alaska as the region corresponding to Census Public Use Microdata Area (PUMA) 400, known also as the Subsistence Alaska PUMA. The ACS is an annual survey. However, due to small sample sizes, the ACS publishes estimates for places and census areas/boroughs only as five-year moving averages. Even with the averaging over five years, estimates of educational attainment and language use vary substantially over time in many communities, and high margins of error make it difficult to distinguish communities from each other. Using individual Census and ACS records accessed through the Census Research Data Center program, we generated annual synthetic estimates of language use at home and two measures of educational attainment -- high school graduation and college degree -- based on logistic regressions estimated with data on individuals indicating AIAN identity, either alone or in combination with other races. The equations were estimated under the assumption that language and education change gradually at the community level, and that variations from year to year are associated with sample variation in basic characteristics of the population such as age and gender that can be benchmarked with precision to the 2000 and 2010 census counts. The synthetic estimates remove the variation associated with interannual survey age and gender variation, resulting in a smaller margin of error for the smoothed estimates than in the original sample means. They also include interpolated values for years 2001 through 2004 when no survey data were collected.

The Survey of American Indians and Alaska Natives (SAIAN) is one of three major components of the 1987 National Medical Expenditure Survey (NMES). (The other two components are the Household Survey and the Institutional Population Component.) The SAIAN was designed in collaboration with the Indian Health Service (IHS), and used the same data collection instruments, interview procedures, and time frame as the Household Survey component. However, the SAIAN differed from the Household Survey in several respects. The SAIAN sample was interviewed only three times and was not given the supplements on long-term care, caregiving, and care-receiving. Also, SAIAN respondents were asked additional questions on topics such as use of IHS facilities and traditional medicine, and were given a modified self-administered questionnaire with separate versions for adults and children. Interviewers for the SAIAN were mainly American Indians or Alaska Natives, and about 40 percent of the interviews were conducted entirely in the native language of the respondent. Public Use Tape 11 contains person-level data from Round 1 only, focusing on demographics, household composition, employment, and health insurance.

Race and Ethnicity:Percent American Indian/Native Alaskan Alone: Basic demographics by census tracts in King County based on current American Community Survey 5 Year Average (ACS). Included demographics are: total population; foreign born; median household income; English language proficiency; languages spoken; race and ethnicity; sex; and age. Numbers and derived percentages are estimates based on the current year's ACS. GEO_ID_TRT is the key field and may be used to join to other demographic Census data tables.

This graph shows the population of the U.S. by race and ethnic group from 2000 to 2023. In 2023, there were around 21.39 million people of Asian origin living in the United States. A ranking of the most spoken languages across the world can be accessed here. U.S. populationCurrently, the white population makes up the vast majority of the United States’ population, accounting for some 252.07 million people in 2023. This ethnicity group contributes to the highest share of the population in every region, but is especially noticeable in the Midwestern region. The Black or African American resident population totaled 45.76 million people in the same year. The overall population in the United States is expected to increase annually from 2022, with the 320.92 million people in 2015 expected to rise to 341.69 million people by 2027. Thus, population densities have also increased, totaling 36.3 inhabitants per square kilometer as of 2021. Despite being one of the most populous countries in the world, following China and India, the United States is not even among the top 150 most densely populated countries due to its large land mass. Monaco is the most densely populated country in the world and has a population density of 24,621.5 inhabitants per square kilometer as of 2021. As population numbers in the U.S. continues to grow, the Hispanic population has also seen a similar trend from 35.7 million inhabitants in the country in 2000 to some 62.65 million inhabitants in 2021. This growing population group is a significant source of population growth in the country due to both high immigration and birth rates. The United States is one of the most racially diverse countries in the world.

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, 2017-2021 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..Methodological changes to citizenship edits may have affected citizenship data for those born in American Samoa. Users should be aware of these changes when using 2018 data or multi-year data containing data from 2018. For more information, see: American Samoa Citizenship User Note..The 2017-2021 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 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. 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 2025, there were around 1.53 billion people worldwide who spoke English either natively or as a second language, slightly more than the 1.18 billion Mandarin Chinese speakers at the time of survey. Hindi and Spanish accounted for the third and fourth most widespread languages that year. Languages in the United States The United States does not have an official language, but the country uses English, specifically American English, for legislation, regulation, and other official pronouncements. The United States is a land of immigration, and the languages spoken in the United States vary as a result of the multicultural population. The second most common language spoken in the United States is Spanish or Spanish Creole, which over than 43 million people spoke at home in 2023. There were also 3.5 million Chinese speakers (including both Mandarin and Cantonese),1.8 million Tagalog speakers, and 1.57 million Vietnamese speakers counted in the United States that year. Different languages at home The percentage of people in the United States speaking a language other than English at home varies from state to state. The state with the highest percentage of population speaking a language other than English is California. About 45 percent of its population was speaking a language other than English at home in 2023.

The statistic shows the total population of India from 2019 to 2029. In 2023, the estimated total population in India amounted to approximately 1.43 billion people.

Total population in India

India currently has the second-largest population in the world and is projected to overtake top-ranking China within forty years. Its residents comprise more than one-seventh of the entire world’s population, and despite a slowly decreasing fertility rate (which still exceeds the replacement rate and keeps the median age of the population relatively low), an increasing life expectancy adds to an expanding population. In comparison with other countries whose populations are decreasing, such as Japan, India has a relatively small share of aged population, which indicates the probability of lower death rates and higher retention of the existing population.

With a land mass of less than half that of the United States and a population almost four times greater, India has recognized potential problems of its growing population. Government attempts to implement family planning programs have achieved varying degrees of success. Initiatives such as sterilization programs in the 1970s have been blamed for creating general antipathy to family planning, but the combined efforts of various family planning and contraception programs have helped halve fertility rates since the 1960s. The population growth rate has correspondingly shrunk as well, but has not yet reached less than one percent growth per year.

As home to thousands of ethnic groups, hundreds of languages, and numerous religions, a cohesive and broadly-supported effort to reduce population growth is difficult to create. Despite that, India is one country to watch in coming years. It is also a growing economic power; among other measures, its GDP per capita was expected to triple between 2003 and 2013 and was listed as the third-ranked country for its share of the global gross domestic product.

BackgroundThe mainland of the Americas is home to a remarkable diversity of languages, and the relationships between genes and languages have attracted considerable attention in the past. Here we investigate to which extent geography and languages can predict the genetic structure of Native American populations. Methodology/Principal FindingsOur approach is based on a Bayesian latent cluster regression model in which cluster membership is explained by geographic and linguistic covariates. After correcting for geographic effects, we find that the inclusion of linguistic information improves the prediction of individual membership to genetic clusters. We further compare the predictive power of Greenberg's and The Ethnologue classifications of Amerindian languages. We report that The Ethnologue classification provides a better genetic proxy than Greenberg's classification at the stock and at the group levels. Although high predictive values can be achieved from The Ethnologue classification, we nevertheless emphasize that Choco, Chibchan and Tupi linguistic families do not exhibit a univocal correspondence with genetic clusters. Conclusions/SignificanceThe Bayesian latent class regression model described here is efficient at predicting population genetic structure using geographic and linguistic information in Native American populations.

The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line File is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Census tracts are small, relatively permanent statistical subdivisions of a county or equivalent entity, and were defined by local participants as part of the 2010 Census Participant Statistical Areas Program. The Census Bureau delineated the census tracts in situations where no local participant existed or where all the potential participants declined to participate. The primary purpose of census tracts is to provide a stable set of geographic units for the presentation of census data and comparison back to previous decennial censuses. Census tracts generally have a population size between 1,200 and 8,000 people, with an optimum size of 4,000 people. When first delineated, census tracts were designed to be homogeneous with respect to population characteristics, economic status, and living conditions. The spatial size of census tracts varies widely depending on the density of settlement. Physical changes in street patterns caused by highway construction, new development, and so forth, may require boundary revisions. In addition, census tracts occasionally are split due to population growth, or combined as a result of substantial population decline. Census tract boundaries generally follow visible and identifiable features. They may follow legal boundaries such as minor civil division (MCD) or incorporated place boundaries in some States and situations to allow for census tract-to-governmental unit relationships where the governmental boundaries tend to remain unchanged between censuses. State and county boundaries always are census tract boundaries in the standard census geographic hierarchy. In a few rare instances, a census tract may consist of noncontiguous areas. These noncontiguous areas may occur where the census tracts are coextensive with all or parts of legal entities that are themselves noncontiguous. For the 2010 Census, the census tract code range of 9400 through 9499 was enforced for census tracts that include a majority American Indian population according to Census 2000 data and/or their area was primarily covered by federally recognized American Indian reservations and/or off-reservation trust lands; the code range 9800 through 9899 was enforced for those census tracts that contained little or no population and represented a relatively large special land use area such as a National Park, military installation, or a business/industrial park; and the code range 9900 through 9998 was enforced for those census tracts that contained only water area, no land area.

This table contains data on individual languages spoken from the American Community Survey 2006-2010 database for tracts. The American Community Survey (ACS) is a household survey conducted by the U.S. Census Bureau that currently has an annual sample size of about 3.5 million addresses. ACS estimates provides communities with the current information they need to plan investments and services. Information from the survey generates estimates that help determine how more than $400 billion in federal and state funds are distributed annually. Each year the survey produces data that cover the periods of 1-year, 3-year, and 5-year estimates for geographic areas in the United States and Puerto Rico, ranging from neighborhoods to Congressional districts to the entire nation. This table also has a companion table (Same table name with MOE Suffix) with the margin of error (MOE) values for each estimated element. MOE is expressed as a measure value for each estimated element. So a value of 25 and an MOE of 5 means 25 +/- 5 (or statistical certainty between 20 and 30). There are also special cases of MOE. An MOE of -1 means the associated estimates do not have a measured error. An MOE of 0 means that error calculation is not appropriate for the associated value. An MOE of 109 is set whenever an estimate value is 0. The MOEs of aggregated elements and percentages must be calculated. This process means using standard error calculations as described in "American Community Survey Multiyear Accuracy of the Data (3-year 2008-2010 and 5-year 2006-2010)". Also, following Census guidelines, aggregated MOEs do not use more than 1 0-element MOE (109) to prevent over estimation of the error. Due to the complexity of the calculations, some percentage MOEs cannot be calculated (these are set to null in the summary-level MOE tables).

The name for table 'ACS10LSPTRMOE' was added as a prefix to all field names imported from that table. Be sure to turn off 'Show Field Aliases' to see complete field names in the Attribute Table of this feature layer. This can be done in the 'Table Options' drop-down menu in the Attribute Table or with key sequence '[CTRL]+[SHIFT]+N'. Due to database restrictions, the prefix may have been abbreviated if the field name exceded the maximum allowed characters.

Baseline characteristics and missing data for American Indian patients with diabetes admitted to GIMC between 2009 and 2016.

Geologically, Panama belongs to the Central American land-bridge between North and South America crossed by Homo sapiens >14 ka ago. Archaeologically, it belongs to a wider Isthmo-Colombian Area. Today, seven indigenous ethnic groups account for 12.3% of Panama’s population. Five speak Chibchan languages and are characterized by low genetic diversity and a high level of differentiation. In addition, no evidence of differential structuring between maternally and paternally inherited genes has been reported in isthmian Chibchan cultural groups. Recent data have shown that 83% of the Panamanian general population harbour mitochondrial DNAs (mtDNAs) of Native American ancestry. Considering differential male/female mortality at European contact and multiple degrees of geographical and genetic isolation over the subsequent five centuries, the Y-chromosome Native American component is expected to vary across different geographic regions and communities in Panama. To address this issue, we investigated Y-chromosome variation in 408 modern males from the nine provinces of Panama and one indigenous territory (the comarca of Kuna Yala). In contrast to mtDNA data, the Y-chromosome Native American component (haplogroup Q) exceeds 50% only in three populations facing the Caribbean Sea: the comarca of Kuna Yala and Bocas del Toro province where Chibchan languages are spoken by the majority, and the province of Colón where many Kuna and people of mixed indigenous-African-and-European descent live. Elsewhere the Old World component is dominant and mostly represented by western Eurasian haplogroups, which signal the strong male genetic impact of invaders. Sub-Saharan African input accounts for 5.9% of male haplotypes. This reflects the consequences of the colonial Atlantic slave trade and more recent influxes of West Indians of African heritage. Overall, our findings reveal a local evolution of the male Native American ancestral gene pool, and a strong but geographically differentiated unidirectional sex bias in the formation of local modern Panamanian populations.

This dataset tracks annual reading and language arts proficiency from 2010 to 2022 for Native American Community Academy vs. New Mexico and Albuquerque School District

A recent survey estimated that 7.5 percent of the population in Latin America spoke a native or indigenous language as their mother tongue. Among the countries included in the study, the highest share was found in Paraguay, where 49 percent of respondents said their first language was either native or indigenous. Bolivia followed second, with 31.9 percent of the people interviewed having an indigenous language as their mother tongue.

The proposed project aims to determine how social conditions for Alaska Natives living in small arctic communities have changed since 2000, and differ among communities and small regions. The Census Long Form Survey historically provided much of the data for measuring social and economic conditions in the United States. Its replacement with the American Community Survey (ACS) after the 2000 Census has raised serious concerns about whether Census data continue to provide accurate measures of well-being in rural Alaska communities, at a time when the region faces unprecedented environmental and socio-economic change. The project addresses the uncertainty with ACS data by developing a new set of social, economic, and cultural indicators with increased capability to detect differences at local scales. Specific objectives include: (1) systematically examine the reliability of ACS data for rural Alaska by disaggregating published margins of error into components expressing dispersion across communities, years, and individuals; (2) construct socio-economic indicators for rural Alaska communities and regions with substantially smaller margins of error than published results; (3) estimate key indicators for communities where observations are sparse or missing entirely; and (4) test whether communities and regions have changed or differ significantly with respect to one or more indicators. The project pursues these objectives through modeling and statistical analyses of multiple primary data sources, including individual interview data from the ACS and the previous censuses in cooperation with the United States Census Bureau. Project outputs include a set of socio-economic indicators with improved reliability over published ACS figures that can help state and local governments and non-governmental organizations allocate funds, plan, and evaluate social service and economic development programs. A pioneering application of data assimilation with a social system model aids arctic social observing system design by revealing highest priority targets for new data collection for observing and understanding social change in arctic communities.

Mexico is the country with the largest number of native Spanish speakers in the world. As of 2024, 132.5 million people in Mexico spoke Spanish with a native command of the language. Colombia was the nation with the second-highest number of native Spanish speakers, at around 52.7 million. Spain came in third, with 48 million, and Argentina fourth, with 46 million. Spanish, a world language As of 2023, Spanish ranked as the fourth most spoken language in the world, only behind English, Chinese, and Hindi, with over half a billion speakers. Spanish is the official language of over 20 countries, the majority on the American continent, nonetheless, it's also one of the official languages of Equatorial Guinea in Africa. Other countries have a strong influence, like the United States, Morocco, or Brazil, countries included in the list of non-Hispanic countries with the highest number of Spanish speakers. The second most spoken language in the U.S. In the most recent data, Spanish ranked as the language, other than English, with the highest number of speakers, with 12 times more speakers as the second place. Which comes to no surprise following the long history of migrations from Latin American countries to the Northern country. Moreover, only during the fiscal year 2022. 5 out of the top 10 countries of origin of naturalized people in the U.S. came from Spanish-speaking countries.