Key Table Information.Table Title.Household Type (Including Living Alone) (Asian Alone).Table ID.ACSDT1Y2024.B11001D.Survey/Program.American Community Survey.Year.2024.Dataset.ACS 1-Year Estimates Detailed Tables.Source.U.S. Census Bureau, 2024 American Community Survey, 1-Year Estimates.Dataset Universe.The dataset universe of the American Community Survey (ACS) is the U.S. resident population and housing. For more information about ACS residence rules, see the ACS Design and Methodology Report. Note that each table describes the specific universe of interest for that set of estimates..Methodology.Unit(s) of Observation.American Community Survey (ACS) data are collected from individuals living in housing units and group quarters, and about housing units whether occupied or vacant. For more information about ACS sampling and data collection, see the ACS Design and Methodology Report..Geography Coverage.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.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..Sampling.The ACS consists of two separate samples: housing unit addresses and group quarters facilities. Independent housing unit address samples are selected for each county or county-equivalent in the U.S. and Puerto Rico, with sampling rates depending on a measure of size for the area. For more information on sampling in the ACS, see the Accuracy of the Data document..Confidentiality.The Census Bureau has modified or suppressed some estimates in ACS data products to protect respondents' confidentiality. Title 13 United States Code, Section 9, prohibits the Census Bureau from publishing results in which an individual's data can be identified. For more information on confidentiality protection in the ACS, see the Accuracy of the Data document..Technical Documentation/Methodology.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.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..Weights.ACS estimates are obtained from a raking ratio estimation procedure that results in the assignment of two sets of weights: a weight to each sample person record and a weight to each sample housing unit record. Estimates of person characteristics are based on the person weight. Estimates of family, household, and housing unit characteristics are based on the housing unit weight. For any given geographic area, a characteristic total is estimated by summing the weights assigned to the persons, households, families or housing units possessing the characteristic in the geographic area. For more information on weighting and estimation in the ACS, see the Accuracy of the Data document.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, a...

Use this application to view the pattern of concentrations of people by race and Hispanic or Latino ethnicity. Data are provided at the U.S. Census block group level, one of the smallest Census geographies, to provide a detailed picture of these patterns. The data is sourced from the U.S Census Bureau, 2020 Census Redistricting Data (Public Law 94-171) Summary File. Definitions: Definitions of the Census Bureau’s categories are provided below. This interactive map shows patterns for all categories except American Indian or Alaska Native and Native Hawaiian or Other Pacific Islander. The total population countywide for these two categories is small (1,582 and 263 respectively). The Census Bureau uses the following race categories:Population by RaceWhite – A person having origins in any of the original peoples of Europe, the Middle East, or North Africa.Black or African American – A person having origins in any of the Black racial groups of Africa.American Indian or Alaska Native – A person having origins in any of the original peoples of North and South America (including Central America) and who maintains tribal affiliation or community attachment.Asian – 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.Native Hawaiian or Other Pacific Islander – A person having origins in any of the original peoples of Hawaii, Guam, Samoa, or other Pacific Islands.Some Other Race - this category is chosen by people who do not identify with any of the categories listed above. People can identify with more than one race. These people are included in the Two or More Races Hispanic or Latino PopulationThe Hispanic/Latino population is an ethnic group. Hispanic/Latino people may be of any race.Other layers provided in this tool included the Loudoun County Census block groups, towns and Dulles airport, and the Loudoun County 2021 aerial imagery.

Decennial Census Summary File 3 (SF 3) Description Census 2000 Summary File 3 (SF3) Summary File 3 presents in-depth population and housing data collected on a sample basis from the Census 2000 long form questionnaire, as well as the topics from the short form 100-percent data (age, race, sex, Hispanic or Latino origin, tenure [whether a housing unit is owner- or renter-occupied], and vacancy status). Summary File 3 consists of 813 detailed tables of Census 2000 social, economic and housing characteristics compiled from a sample of approximately 19 million housing units (about 1 in 6 households) that received the Census 2000 long-form questionnaire. Fifty-one tables are repeated for nine major race and Hispanic or Latino groups: White alone; Black or African American alone; American Indian and Alaska Native alone; Asian alone; Native Hawaiian and Other Pacific Islander alone; Some other race alone; Two or more races; Hispanic or Latino; and White alone, not Hispanic or Latino. For information on confidentiality protection, sampling error, nonsampling error, and definitions, see http://www.census.gov/prod/cen2000/doc/sf3.pdf. See Chapter 8 for computation of margins of error.

Key Table Information.Table Title.Annual Business Survey: Statistics for Employer Firms by Race for the U.S.: 2023.Table ID.ABSCS2023.AB00MYCSA01C.Survey/Program.Economic Surveys.Year.2023.Dataset.ECNSVY Annual Business Survey Company Summary.Source.U.S. Census Bureau, 2023 Economic Surveys, Annual Business Survey.Release Date.2025-11-20.Release Schedule.The Annual Business Survey (ABS) occurs every year, beginning in reference year 2017.For more information about ABS planned data product releases, see Tentative ABS Schedule..Dataset Universe.The dataset universe consists of employer firms that are in operation for at least some part of the reference year, are located in one of the 50 U.S. states, associated offshore areas, or the District of Columbia, have paid employees and annual receipts of $1,000 or more, and are classified in one of nineteen in-scope sectors defined by the 2022 North American Industry Classification System (NAICS), except for NAICS 111, 112, 482, 491, 521, 525, 813, 814, and 92 which are not covered..Sponsor.National Center for Science and Engineering Statistics, U.S. National Science Foundation.Methodology.Data Items and Other Identifying Records.Number of employer firms (firms with paid employees)Sales and receipts of employer firms (reported in $1,000s of dollars)Number of employees (during the March 12 pay period)Annual payroll (reported in $1,000s of dollars)These data are aggregated by the following demographic classifications of firm for:All firms Classifiable (firms classifiable by sex, ethnicity, race, and veteran status) Race White Black or African American American Indian and Alaska Native Asian Native Hawaiian and Other Pacific Islander Minority (Firms classified as any race and ethnicity combination other than non-Hispanic and White) Equally minority/nonminority Nonminority (Firms classified as non-Hispanic and White) Unclassifiable (firms not classifiable by sex, ethnicity, race, and veteran status) Definitions can be found by clicking on the column header in the table or by accessing the Economic Census Glossary..Unit(s) of Observation.The reporting units for the ABS are employer companies or firms rather than establishments. A company or firm is comprised of one or more in-scope establishments that operate under the ownership or control of a single organization..Geography Coverage.The data are shown for the U.S. only.For information about geographies, see Geographies..Industry Coverage.The data are shown for the total of all sectors ("00") NAICS code. Sector "00" is not an official NAICS sector but is rather a way to indicate a total for multiple sectors. Note: Other programs outside of ABS may use sector 00 to indicate when multiple NAICS sectors are being displayed within the same table and/or dataset.The following are excluded from the total of all sectors:Crop and Animal Production (NAICS 111 and 112)Rail Transportation (NAICS 482)Postal Service (NAICS 491)Monetary Authorities-Central Bank (NAICS 521)Funds, Trusts, and Other Financial Vehicles (NAICS 525)Office of Notaries (NAICS 541120)Religious, Grantmaking, Civic, Professional, and Similar Organizations (NAICS 813)Private Households (NAICS 814)Public Administration (NAICS 92)For information about NAICS, see North American Industry Classification System..Sampling.The ABS sample includes firms that are selected with certainty if they have known research and development activities, were included in the 2023 BERD sample, or have high receipts, payroll, or employment. Total sample size is 330,000 firms. The universe is stratified by state, industry group, and expected demographic group. Firms selected to the sample receive a questionnaire. For all data on this table, firms not selected into the sample are represented with administrative, 2022 Economic Census, or other economic surveys records.For more information about the sample design, see Annual Business Survey Methodology..Confidentiality.The Census Bureau has reviewed this data product to ensure appropriate access, use, and disclosure avoidance protection of the confidential source data (Project No. P-7504866, Disclosure Review Board (DRB) approval numbers: CBDRB-FY25-0115 and CBDRB-FY25-0410).To protect confidentiality, the U.S. Census Bureau suppresses cell values to minimize the risk of identifying a particular business' data or identity.To comply with data quality standards, data rows with high relative standard errors (RSE) are not presented. Additionally, firm counts are suppressed when other select statistics in the same row are suppressed. More information on disclosure avoidance is available in the Annual Business Survey Methodology..Technical Documentation/Methodology.For detailed information about the methods used to collect data and produce statistics, survey questionnaires, Primary Business Activity/NAICS codes, and more, see Technical Documentation..Weights.For more information about weighting, see Annual Business Survey Methodology..Table Inf...

Key Table Information.Table Title.Sex by Age by Nativity and Citizenship Status (Asian Alone).Table ID.ACSDT1Y2024.B05003D.Survey/Program.American Community Survey.Year.2024.Dataset.ACS 1-Year Estimates Detailed Tables.Source.U.S. Census Bureau, 2024 American Community Survey, 1-Year Estimates.Dataset Universe.The dataset universe of the American Community Survey (ACS) is the U.S. resident population and housing. For more information about ACS residence rules, see the ACS Design and Methodology Report. Note that each table describes the specific universe of interest for that set of estimates..Methodology.Unit(s) of Observation.American Community Survey (ACS) data are collected from individuals living in housing units and group quarters, and about housing units whether occupied or vacant. For more information about ACS sampling and data collection, see the ACS Design and Methodology Report..Geography Coverage.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.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..Sampling.The ACS consists of two separate samples: housing unit addresses and group quarters facilities. Independent housing unit address samples are selected for each county or county-equivalent in the U.S. and Puerto Rico, with sampling rates depending on a measure of size for the area. For more information on sampling in the ACS, see the Accuracy of the Data document..Confidentiality.The Census Bureau has modified or suppressed some estimates in ACS data products to protect respondents' confidentiality. Title 13 United States Code, Section 9, prohibits the Census Bureau from publishing results in which an individual's data can be identified. For more information on confidentiality protection in the ACS, see the Accuracy of the Data document..Technical Documentation/Methodology.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.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..Weights.ACS estimates are obtained from a raking ratio estimation procedure that results in the assignment of two sets of weights: a weight to each sample person record and a weight to each sample housing unit record. Estimates of person characteristics are based on the person weight. Estimates of family, household, and housing unit characteristics are based on the housing unit weight. For any given geographic area, a characteristic total is estimated by summing the weights assigned to the persons, households, families or housing units possessing the characteristic in the geographic area. For more information on weighting and estimation in the ACS, see the Accuracy of the Data document.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, cit...

Key Table Information.Table Title.Sex by Age by Veteran Status for the Civilian Population 18 Years and Over (Asian Alone).Table ID.ACSDT1Y2024.B21001D.Survey/Program.American Community Survey.Year.2024.Dataset.ACS 1-Year Estimates Detailed Tables.Source.U.S. Census Bureau, 2024 American Community Survey, 1-Year Estimates.Dataset Universe.The dataset universe of the American Community Survey (ACS) is the U.S. resident population and housing. For more information about ACS residence rules, see the ACS Design and Methodology Report. Note that each table describes the specific universe of interest for that set of estimates..Methodology.Unit(s) of Observation.American Community Survey (ACS) data are collected from individuals living in housing units and group quarters, and about housing units whether occupied or vacant. For more information about ACS sampling and data collection, see the ACS Design and Methodology Report..Geography Coverage.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.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..Sampling.The ACS consists of two separate samples: housing unit addresses and group quarters facilities. Independent housing unit address samples are selected for each county or county-equivalent in the U.S. and Puerto Rico, with sampling rates depending on a measure of size for the area. For more information on sampling in the ACS, see the Accuracy of the Data document..Confidentiality.The Census Bureau has modified or suppressed some estimates in ACS data products to protect respondents' confidentiality. Title 13 United States Code, Section 9, prohibits the Census Bureau from publishing results in which an individual's data can be identified. For more information on confidentiality protection in the ACS, see the Accuracy of the Data document..Technical Documentation/Methodology.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.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..Weights.ACS estimates are obtained from a raking ratio estimation procedure that results in the assignment of two sets of weights: a weight to each sample person record and a weight to each sample housing unit record. Estimates of person characteristics are based on the person weight. Estimates of family, household, and housing unit characteristics are based on the housing unit weight. For any given geographic area, a characteristic total is estimated by summing the weights assigned to the persons, households, families or housing units possessing the characteristic in the geographic area. For more information on weighting and estimation in the ACS, see the Accuracy of the Data document.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 ...

Key Table Information.Table Title.Nonemployer Statistics by Demographics series (NES-D): Statistics for Employer and Nonemployer Firms by Industry and Race for the U.S., States, Metro Areas, Counties, and Places: 2023.Table ID.ABSNESD2023.AB00MYNESD01C.Survey/Program.Economic Surveys.Year.2023.Dataset.ECNSVY Nonemployer Statistics by Demographics Company Summary.Source.U.S. Census Bureau, 2023 Economic Surveys, Nonemployer Statistics by Demographics.Release Date.2025-11-20.Release Schedule.The Nonemployer Statistics by Demographics (NES-D) is released yearly, beginning in 2017..Sponsor.National Center for Science and Engineering Statistics, U.S. National Science Foundation.Table Universe.Data in this table combines estimates from the Annual Business Survey (employer firms) and the Nonemployer Statistics by Demographics (nonemployer firms).Includes U.S. firms with no paid employment or payroll, annual receipts of $1,000 or more ($1 or more in the construction industries) and filing Internal Revenue Service (IRS) tax forms for sole proprietorships (Form 1040, Schedule C), partnerships (Form 1065), or corporations (the Form 1120 series).Includes U.S. employer firms estimates of business ownership by sex, ethnicity, race, and veteran status from the 2024 Annual Business Survey (ABS) collection. The employer business dataset universe consists of employer firms that are in operation for at least some part of the reference year, are located in one of the 50 U.S. states, associated offshore areas, or the District of Columbia, have paid employees and annual receipts of $1,000 or more, and are classified in one of nineteen in-scope sectors defined by the 2022 North American Industry Classification System (NAICS), except for NAICS 111, 112, 482, 491, 521, 525, 813, 814, and 92 which are not covered.Data are also obtained from administrative records, the 2022 Economic Census, and other economic surveys. Note: For employer data only, the collection year is the year in which the data are collected. A reference year is the year that is referenced in the questions on the survey and in which the statistics are tabulated. For example, the 2024 ABS collection year produces statistics for the 2023 reference year. The "Year" column in the table is the reference year..Methodology.Data Items and Other Identifying Records.Total number of employer and nonemployer firmsTotal sales, value of shipments, or revenue of employer and nonemployer firms ($1,000)Number of nonemployer firmsSales, value of shipments, or revenue of nonemployer firms ($1,000)Number of employer firmsSales, value of shipments, or revenue of employer firms ($1,000)Number of employeesAnnual payroll ($1,000)These data are aggregated by the following demographic classifications of firm for:All firms Classifiable (firms classifiable by sex, ethnicity, race, and veteran status) Race White Black or African American American Indian and Alaska Native Asian Native Hawaiian and Other Pacific Islander Minority (Firms classified as any race and ethnicity combination other than non-Hispanic and White) Equally minority/nonminority Nonminority (Firms classified as non-Hispanic and White) Unclassifiable (firms not classifiable by sex, ethnicity, race, and veteran status) Definitions can be found by clicking on the column header in the table or by accessing the Economic Census Glossary..Unit(s) of Observation.The reporting units for the NES-D and the ABS are companies or firms rather than establishments. A company or firm is comprised of one or more in-scope establishments that operate under the ownership or control of a single organization..Geography Coverage.The 2023 data are shown for the total of all sectors (00) and the 2- to 6-digit NAICS code levels for:United StatesStates and the District of ColumbiaIn addition, the total of all sectors (00) NAICS and the 2-digit NAICS code levels for:Metropolitan Statistical AreasMicropolitan Statistical AreasMetropolitan DivisionsCombined Statistical AreasCountiesEconomic PlacesFor information about geographies, see Geographies..Industry Coverage.The data are shown for the total of all sectors ("00"), and at the 2- through 6-digit NAICS code levels depending on geography. Sector "00" is not an official NAICS sector but is rather a way to indicate a total for multiple sectors. Note: Other programs outside of ABS may use sector 00 to indicate when multiple NAICS sectors are being displayed within the same table and/or dataset.The following are excluded from the total of all sectors:Crop and Animal Production (NAICS 111 and 112)Rail Transportation (NAICS 482)Postal Service (NAICS 491)Monetary Authorities-Central Bank (NAICS 521)Funds, Trusts, and Other Financial Vehicles (NAICS 525)Office of Notaries (NAICS 541120)Religious, Grantmaking, Civic, Professional, and Similar Organizations (NAICS 813)Private Households (NAICS 814)Public Administration (NAICS 92)For information about NAICS, see North American Industry Classification System..Sa...

Release Date: 2017-07-13.[NOTE: Includes firms with payroll at any time during 2015. Employment reflects the number of paid employees during the March 12 pay period. Data are based on Census administrative records, and the estimates of business ownership by gender, ethnicity, race, and veteran status are from the 2015 Annual Survey of Entrepreneurs. Detail may not add to total due to rounding or because a Hispanic firm may be of any race. Moreover, each owner had the option of selecting more than one race and therefore is included in each race selected. Respondent firms include all firms that responded to the characteristic(s) tabulated in this dataset and reported gender, ethnicity, race, or veteran status or that were publicly held or not classifiable by gender, ethnicity, race, or veteran status. Percentages are for respondent firms only and are not recalculated when the dataset is resorted. Percentages are always based on total reporting (defined above) within a gender, ethnicity, race, veteran status, and/or industry group for the characteristics tabulated in this dataset. Firms with more than one domestic establishment are counted in each geographic area and industry in which they operate, but only once in the U.S. and state totals for all sectors. For information on confidentiality protection, sampling error, nonsampling error, and definitions, see Survey Methodology.]..Table Name. . Statistics for U.S. Employer Firms by Owner('s) Business Aspirations by Sector, Gender, Ethnicity, Race, Veteran Status, and Years in Business for the U.S., States, and Top 50 MSAs: 2015. ..Release Schedule. . This file was released in July 2017.. ..Key Table Information. . These data are related to all other 2015 ASE files.. Refer to the Methodology section of the Annual Survey of Entrepreneurs website for additional information.. ..Universe. . The universe for the 2015 Annual Survey of Entrepreneurs (ASE) includes all U.S. firms with paid employees operating during 2015 with receipts of $1,000 or more which are classified in the North American Industry Classification System (NAICS) sectors 11 through 99, except for NAICS 111, 112, 482, 491, 521, 525, 813, 814, and 92 which are not covered. Firms with more than one domestic establishment are counted in each geographic area and industry in which they operate, but only once in the U.S. total.. In this file, "respondent firms" refers to all firms that reported gender, ethnicity, race, or veteran status for at least one owner or returned a survey form with at least one item completed and were publicly held or not classifiable by gender, ethnicity, race, and veteran status.. ..Geographic Coverage. . The data are shown for:. . United States. States and the District of Columbia. The fifty most populous metropolitan areas. . ..Industry Coverage. . The data are shown for the total of all sectors (00) and the 2-digit NAICS code level.. ..Data Items and Other Identifying Records. . Statistics for U.S. Employer Firms by Owner('s) Business Aspirations by Sector, Gender, Ethnicity, Race, Veteran Status, and Years in Business for the U.S., States, and Top 50 MSAs: 2015 contains data on:. . Number of firms with paid employees. Sales and receipts for firms with paid employees. Number of employees for firms with paid employees. Annual payroll for firms with paid employees. Percent of respondent firms with paid employees. Percent of sales and receipts of respondent firms with paid employees. Percent of number of employees of respondent firms with paid employees. Percent of annual payroll of respondent firms with paid employees. . The data are shown for:. . Gender, ethnicity, race and veteran status of respondent firms. . All firms. Female-owned. Male-owned. Equally male-/female-owned. Hispanic. Equally Hispanic/non-Hispanic. Non-Hispanic. White. Black or African American. American Indian and Alaska Native. Asian. Native Hawaiian and Other Pacific Islander. Some other race. Minority. Equally minority/nonminority. Nonminority. Veteran-owned. Equally veteran-/nonveteran-owned. Nonveteran-owned. All firms classifiable by gender, ethnicity, race, and veteran status. Publicly held and other firms not classifiable by gender, ethnicity, race, and veteran status. . . Years in business. . All firms. Firms less than 2 years in business. Firms with 2 to 3 years in business. Firms with 4 to 5 years in business. Firms with 6 to 10 years in business. Firms with 11 to 15 years in business. Firms with...

Urban Institute racial and economic inclusion indexes for 2016; extracted from source: https://apps.urban.org/features/inclusion/?topic=map.

The racial inclusion index is made up of five measures: racial segregation (white/person of color dissimilarity index), homeownership gap, educational attainment gap, poverty rate gap, and share of people of color. All racial gap measures calculate the disparity between white non-Hispanic residents and residents of color. For this analysis, we define people of color as any person identifying in US Census Bureau records as Black or African American, American Indian or Alaska Native, Asian, Native Hawaiian or other Pacific Islander, other race, two or more races, or Hispanic or Latino white. We recognize the issues that arise with placing all these groups under one umbrella—both in defining identity in comparison with whiteness and in papering over differences in how different groups experience state-sanctioned, institutionalized, systemic, and individual forms of racism. This broad racial disparity measure allows us to compare cities with differing demographic patterns while limiting the size of sampling error for groups within cities that have small populations.

The economic inclusion index is made up of four measures: income segregation (rank-order information theory index), rent burden, share of 16- to 19-year-olds who are not in school and have not graduated, and working poor. The overall inclusion index is the composite of the racial and economic inclusion indices. The economic health index is made up of four indicators: percentage change in employed people period over period, median family income, unemployment rate, and housing vacancy rate.

DESCRIPTION This table contains data on the percent of residents aged 16 years and older mode of transportation to work for ...

SUMMARY This table contains data on the percent of residents aged 16 years and older mode of transportation to work for California, its regions, counties, cities/towns, and census tracts. Data is from the U.S. Census Bureau, Decennial Census and American Community Survey. The table is part of a series of indicators in the Healthy Communities Data and Indicators Project of the Office of Health Equity. Commute trips to work represent 19% of travel miles in the United States. The predominant mode – the automobile - offers extraordinary personal mobility and independence, but it is also associated with health hazards, such as air pollution, motor vehicle crashes, pedestrian injuries and fatalities, and sedentary lifestyles. Automobile commuting has been linked to stress-related health problems. Active modes of transport – bicycling and walking alone and in combination with public transit – offer opportunities for physical activity, which is associated with lowering rates of heart disease and stroke, diabetes, colon and breast cancer, dementia and depression. Risk of injury and death in collisions are higher in urban areas with more concentrated vehicle and pedestrian activity. Bus and rail passengers have a lower risk of injury in collisions than motorcyclists, pedestrians, and bicyclists. Minority communities bear a disproportionate share of pedestrian-car fatalities; Native American male pedestrians experience four times the death rate Whites or Asian pedestrians, and African-Americans and Latinos experience twice the rate as Whites or Asians. More information about the data table and a data dictionary can be found in the About/Attachments section.

ind_id - Indicator ID ind_definition - Definition of indicator in plain language reportyear - Year that the indicator was reported race_eth_code - numeric code for a race/ethnicity group race_eth_name - Name of race/ethnic group geotype - Type of geographic unit geotypevalue - Value of geographic unit geoname - Name of a geographic unit county_name - Name of county that geotype is in county_fips - FIPS code of the county that geotype is in region_name - MPO-based region name; see MPO_County list tab region_code - MPO-based region code; see MPO_County list tab mode - Mode of transportation short name mode_name - Mode of transportation long name pop_total - denominator pop_mode - numerator percent - Percent of Residents Mode of Transportation to Work,
Population Aged 16 Years and Older LL_95CI_percent - The lower limit of 95% confidence interval UL_95CI_percent - The lower limit of 95% confidence interval percent_se - Standard error of the percent mode of transportation percent_rse - Relative standard error (se/value) expressed as a percent CA_decile - California decile CA_RR - Rate ratio to California rate version - Date/time stamp of a version of data

Release Date: 2017-07-13.[NOTE: Includes firms with payroll at any time during 2015. Employment reflects the number of paid employees during the March 12 pay period. Data are based on Census administrative records, and the estimates of business ownership by gender, ethnicity, race, and veteran status are from the 2015 Annual Survey of Entrepreneurs. Detail may not add to total due to rounding or because a Hispanic firm may be of any race. Moreover, each owner had the option of selecting more than one race and therefore is included in each race selected. Respondent firms include all firms that responded to the characteristic(s) tabulated in this dataset and reported gender, ethnicity, race, or veteran status or that were publicly held or not classifiable by gender, ethnicity, race, or veteran status. Percentages are for respondent firms only and are not recalculated when the dataset is resorted. Percentages are always based on total reporting (defined above) within a gender, ethnicity, race, veteran status, and/or industry group for the characteristics tabulated in this dataset. Firms with more than one domestic establishment are counted in each geographic area and industry in which they operate, but only once in the U.S. and state totals for all sectors. For information on confidentiality protection, sampling error, nonsampling error, and definitions, see Survey Methodology.]..Table Name. . Statistics for U.S. Employer Firms That Outsourced or Transferred a Function/Service Outside the United States by Sector, Gender, Ethnicity, Race, Veteran Status, and Years in Business for the U.S., States, and Top 50 MSAs: 2015. ..Release Schedule. . This file was released in July 2017.. ..Key Table Information. . These data are related to all other 2015 ASE files.. Refer to the Methodology section of the Annual Survey of Entrepreneurs website for additional information.. ..Universe. . The universe for the 2015 Annual Survey of Entrepreneurs (ASE) includes all U.S. firms with paid employees operating during 2015 with receipts of $1,000 or more which are classified in the North American Industry Classification System (NAICS) sectors 11 through 99, except for NAICS 111, 112, 482, 491, 521, 525, 813, 814, and 92 which are not covered. Firms with more than one domestic establishment are counted in each geographic area and industry in which they operate, but only once in the U.S. total.. In this file, "respondent firms" refers to all firms that reported gender, ethnicity, race, or veteran status for at least one owner or returned a survey form with at least one item completed and were publicly held or not classifiable by gender, ethnicity, race, and veteran status.. ..Geographic Coverage. . The data are shown for:. . United States. States and the District of Columbia. The fifty most populous metropolitan areas. . ..Industry Coverage. . The data are shown for the total of all sectors (00) and the 2-digit NAICS code level.. ..Data Items and Other Identifying Records. . Statistics for U.S. Employer Firms That Outsourced or Transferred a Function/Service Outside the United States by Sector, Gender, Ethnicity, Race, Veteran Status, and Years in Business for the U.S., States, and Top 50 MSAs: 2015 contains data on:. . Number of firms with paid employees. Sales and receipts for firms with paid employees. Number of employees for firms with paid employees. Annual payroll for firms with paid employees. Percent of respondent firms with paid employees. Percent of sales and receipts of respondent firms with paid employees. Percent of number of employees of respondent firms with paid employees. Percent of annual payroll of respondent firms with paid employees. . The data are shown for:. . Gender, ethnicity, race and veteran status of respondent firms. . All firms. Female-owned. Male-owned. Equally male-/female-owned. Hispanic. Equally Hispanic/non-Hispanic. Non-Hispanic. White. Black or African American. American Indian and Alaska Native. Asian. Native Hawaiian and Other Pacific Islander. Some other race. Minority. Equally minority/nonminority. Nonminority. Veteran-owned. Equally veteran-/nonveteran-owned. Nonveteran-owned. All firms classifiable by gender, ethnicity, race, and veteran status. Publicly held and other firms not classifiable by gender, ethnicity, race, and veteran status. . . Years in business. . All firms. Firms less than 2 years in business. Firms with 2 to 3 years in business. Firms with 4 to 5 years in business. Firms with 6 to 10 years ...

Attribute Description NY 2010-2019

County: Location where the crime was reported.

Year: Year the crime incident was reported.

Crime Type: Category of crime defined by the FBI, including Crimes Against Persons (crimes targeting individuals or groups of individuals), and Property Crimes.

Anti-Male: Count of incidents with a reported Anti-Male bias. Male: An individual that produces small usually motile gametes (as spermatozoa or spermatozoids) which fertilize the egg of a female. (Merriam-Webster Dictionary)

Anti-Female: Count of incidents with a reported Anti-Female bias. Female: An individual of the sex that bears young or produces eggs. (Merriam-Webster Dictionary)

Anti-Transgender: Count of incidents with a reported Anti-Transgender bias. Transgender: Of or relating to a person who identifies as a different gender from their gender as determined at birth. The person may also identify himself or herself as “transsexual.” A transgender person may outwardly express his or her gender identity all of the time, part of the time, or none of the time; a transgender person may decide to change his or her body to medically conform to his or her gender identity.

Anti-Gender: Identity Expression Count of incidents with a reported Anti-Gender Identity Expression bias. Gender Nonconforming: Describes a person who does not conform to the gender-based expectations of society, e.g., a woman dressed in traditionally male clothing or a man wearing makeup. Note: A gender nonconforming person may or may not be a lesbian, gay, bisexual, or transgender person but may be perceived as such.

Anti-Age*: Count of incidents with a reported Anti-Age bias (60 years old or more). Age (60 years old or more): A preformed negative opinion or attitude toward a person or group of persons based on their actual or perceived age of 60 years old or more. The two bias types included under New York State’s Hate Crime Law (Penal Law Article 485) that are not included in the list of federally-defined bias types are noted with an asterisk(*).

Anti-White: Count of incidents with a reported Anti-White bias. White: A person having origins in any of the original peoples of Europe, the Middle East, or North Africa. This category includes persons from the following nationalities: Irish, German, Italian, Lebanese, Arab, Moroccan, or Caucasian. (Census)

Anti-Black: Count of incidents with a reported Anti-Black of African American bias. Black or African American: A person having origins in any of the Black racial groups of Africa. This category includes persons from the following nationalities or groups: African American, Kenyan, Nigerian, or Haitian. (Census)

Anti-American Indian/Alaskan Native: Count of incidents with a reported Anti-American Indian or Alaskan Native bias. American Indian or Alaska Native: A person having origins in any of the original peoples of North and South America (including Central America) and who maintains tribal affiliation or community attachment. This category includes persons from the following tribal affiliations: Navajo, Blackfeet, Inupiat, Yup’ik, or Central American Indian groups or South American Indian groups. (Census)

Anti-Asian: Count of incidents with a reported Anti-Asian bias. Asian: 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. This category includes persons from the following nationalities: Asian Indian, Bangledeshi, Bhutanese, Bermese, Cambodian, Chinese Filipino, Hmong, Indonesian, Japanese, Korean, Laotian, Malaysian, Nepalese, Pakistani, Sri Lankan, Taiwanese, Thai, Vietnamese, Other Asian, specified; Other Asian, not specified. (Census)

Anti-Native Hawaiian/Pacific Islander: Count of incidents with a reported Anti-Native Hawaiian/Pacific Islander bias. Native Hawaiian or Other Pacific Islander: A person having origins in any of the original peoples of Hawaii, Guam, Samoa, or other Pacific Islands. This category includes persons from the following nationalities: Fijian, Guamanian or Chamorro, Marshallese, Native Hawaiian, Other Micronesian, Other Pacific Islander, not specified; Other Polynesian, Samoan, Tongan. (Census)

Anti-Multi-Racial Groups: Count of incidents with a reported Anti-Multi-Racial Groups bias. Multiple Races, Group: A group of persons having origins from multiple racial categories.

Anti-Other Race: Count of incidents with a reported Anti-Other Race bias. Other Race/Ethnicity/Ancestry: A person of a different race/ethnicity/ancestry than is otherwise included in this combined category.

Anti-Jewish: Count of incident...

This dataset contains information on:

· Estimated resident population (ERP) at 30 June 1996, 2001, 2006, 2013, and 2018 for total population

· ERP at 30 June 2018 by ethnic groups (European or Other (including New Zealander), Māori, Pacific, Asian, and Middle Eastern/Latin American/African) – estimates and percentage

· Sex ratio – number of males per 100 females

· ERP at 30 June 2018 by broad age groups and median age

· Geographies available are regional council areas, territorial authority and Auckland local board areas, Statistical Area 2, and urban rural.

Note: The geography corresponds to 2020 boundaries

Note: -999 indicates data are not available.

​

About the estimated resident population

The estimated resident population at 30 June in the census year is based on the census usually resident population count, with updates for:

· net census undercount (as measured by a post-enumeration survey)

· residents temporarily overseas on census night

· births, deaths and net migration between census night and 30 June

· reconciliation with demographic estimates at the youngest ages.

The estimated resident population is not directly comparable with the census usually resident population count because of these adjustments.

For more detailed information about the methods used to calculate each base population, see DataInfo+ Demographic estimates.

​

Ethnic groups

It is important to note that these ethnic groups are not mutually exclusive because people can and do identify with more than one ethnicity. People who identify with more than one ethnicity have been included in each ethnic group.

The 'Māori', 'Pacific', 'Asian' and 'Middle Eastern/Latin American/African' ethnic groups are defined in level 1 of the Ethnicity New Zealand Standard Classification 2005. The estimates for the 'European or Other (including New Zealander)' group include people who belong to the 'European' or 'Other ethnicity' groups defined in level 1 of the standard classification. If a person belongs to both the 'European' and 'Other ethnicity' groups they have only been counted once. Almost all people in the 'Other ethnicity' group belong to the 'New Zealander' sub-group.

​

Time series

This time series is irregular. Because the 2011 Census was cancelled after the Canterbury earthquake on 22 February 2011, the gap between the 2006-base and 2013-base estimated resident population is seven years. The change in data between 2006 and 2013 may be greater than in the usual five-year gap between censuses. Be careful when comparing trends.

​

Rounding

Individual figures may not sum to stated totals due to rounding.

​

More information

See Estimated resident population (2018-base): At 30 June 2018 for commentary about the 2018 ERP.

Subnational population estimates concepts – DataInfo+ provides definitions of terms used in the map.

Access more population estimates data in NZ.Stat:

Theme: Population estimates.

Key Table Information.Table Title.Nonemployer Statistics by Demographics series (NES-D): Statistics for Employer and Nonemployer Firms by Industry and Race for the U.S., States, Metro Areas, Counties, and Places: 2022.Table ID.ABSNESD2022.AB00MYNESD01C.Survey/Program.Economic Surveys.Year.2022.Dataset.ECNSVY Nonemployer Statistics by Demographics Company Summary.Source.U.S. Census Bureau, 2022 Economic Surveys, Nonemployer Statistics by Demographics.Release Date.2025-05-08.Release Schedule.The Nonemployer Statistics by Demographics (NES-D) is released yearly, beginning in 2017..Sponsor.National Center for Science and Engineering Statistics, U.S. National Science Foundation.Table Universe.Data in this table combines estimates from the Annual Business Survey (employer firms) and the Nonemployer Statistics by Demographics (nonemployer firms).Includes U.S. firms with no paid employment or payroll, annual receipts of $1,000 or more ($1 or more in the construction industries) and filing Internal Revenue Service (IRS) tax forms for sole proprietorships (Form 1040, Schedule C), partnerships (Form 1065), or corporations (the Form 1120 series).Includes U.S. employer firms estimates of business ownership by sex, ethnicity, race, and veteran status from the 2023 Annual Business Survey (ABS) collection. The employer business dataset universe consists of employer firms that are in operation for at least some part of the reference year, are located in one of the 50 U.S. states, associated offshore areas, or the District of Columbia, have paid employees and annual receipts of $1,000 or more, and are classified in one of nineteen in-scope sectors defined by the 2022 North American Industry Classification System (NAICS), except for NAICS 111, 112, 482, 491, 521, 525, 813, 814, and 92 which are not covered.Data are also obtained from administrative records, the 2022 Economic Census, and other economic surveys. Note: For employer data only, the collection year is the year in which the data are collected. A reference year is the year that is referenced in the questions on the survey and in which the statistics are tabulated. For example, the 2023 ABS collection year produces statistics for the 2022 reference year. The "Year" column in the table is the reference year..Methodology.Data Items and Other Identifying Records.Total number of employer and nonemployer firmsTotal sales, value of shipments, or revenue of employer and nonemployer firms ($1,000)Number of nonemployer firmsSales, value of shipments, or revenue of nonemployer firms ($1,000)Number of employer firmsSales, value of shipments, or revenue of employer firms ($1,000)Number of employeesAnnual payroll ($1,000)These data are aggregated by the following demographic classifications of firm for:All firms Classifiable (firms classifiable by sex, ethnicity, race, and veteran status) Race White Black or African American American Indian and Alaska Native Asian Native Hawaiian and Other Pacific Islander Minority (Firms classified as any race and ethnicity combination other than non-Hispanic and White) Equally minority/nonminority Nonminority (Firms classified as non-Hispanic and White) Unclassifiable (firms not classifiable by sex, ethnicity, race, and veteran status) Definitions can be found by clicking on the column header in the table or by accessing the Economic Census Glossary..Unit(s) of Observation.The reporting units for the NES-D and the ABS are companies or firms rather than establishments. A company or firm is comprised of one or more in-scope establishments that operate under the ownership or control of a single organization..Geography Coverage.The 2022 data are shown for the total of all sectors (00) and the 2- to 6-digit NAICS code levels for:United StatesStates and the District of ColumbiaIn addition, the total of all sectors (00) NAICS and the 2-digit NAICS code levels for:Metropolitan Statistical AreasMicropolitan Statistical AreasMetropolitan DivisionsCombined Statistical AreasCountiesEconomic PlacesFor information about geographies, see Geographies..Industry Coverage.The data are shown for the total of all sectors ("00"), and at the 2- through 6-digit NAICS code levels depending on geography. Sector "00" is not an official NAICS sector but is rather a way to indicate a total for multiple sectors. Note: Other programs outside of ABS may use sector 00 to indicate when multiple NAICS sectors are being displayed within the same table and/or dataset.The following are excluded from the total of all sectors:Crop and Animal Production (NAICS 111 and 112)Rail Transportation (NAICS 482)Postal Service (NAICS 491)Monetary Authorities-Central Bank (NAICS 521)Funds, Trusts, and Other Financial Vehicles (NAICS 525)Office of Notaries (NAICS 541120)Religious, Grantmaking, Civic, Professional, and Similar Organizations (NAICS 813)Private Households (NAICS 814)Public Administration (NAICS 92)For information about NAICS, see North American Industry Classification System..Sa...

Key Table Information.Table Title.Annual Business Survey: Statistics for Employer Firms by Race for the U.S.: 2017.Table ID.ABSCS2017.AB00MYCSA01C.Survey/Program.Economic Surveys.Year.2017.Dataset.ECNSVY Annual Business Survey Company Summary.Release Date.2020-05-19.Release Schedule.The Annual Business Survey (ABS) occurs every year, beginning in reference year 2017.For more information about ABS planned data product releases, see Tentative ABS Schedule..Dataset Universe.The dataset universe consists of employer firms that are in operation for at least some part of the reference year, are located in one of the 50 U.S. states, associated offshore areas, or the District of Columbia, have paid employees and annual receipts of $1,000 or more, and are classified in one of nineteen in-scope sectors defined by the 2017 North American Industry Classification System (NAICS), except for NAICS 111, 112, 482, 491, 521, 525, 813, 814, and 92 which are not covered..Sponsor.National Center for Science and Engineering Statistics, U.S. National Science Foundation.Methodology.Data Items and Other Identifying Records.Number of employer firms (firms with paid employees)Sales and receipts of employer firms (reported in $1,000s of dollars)Number of employees (during the March 12 pay period)Annual payroll (reported in $1,000s of dollars)These data are aggregated by the following demographic classifications of firm for:All firms Classifiable (firms classifiable by sex, ethnicity, race, and veteran status) Race White Black or African American American Indian and Alaska Native Asian Asian Indian Chinese Filipino Japanese Korean Vietnamese Other Asian Native Hawaiian and Other Pacific Islander Native Hawaiian Guamanian or Chamorro Samoan Other Pacific Islander Minority (Firms classified as any race and ethnicity combination other than non-Hispanic and White) Equally minority/nonminority Nonminority (Firms classified as non-Hispanic and White) Unclassifiable (firms not classifiable by sex, ethnicity, race, and veteran status) Definitions can be found by clicking on the column header in the table or by accessing the Economic Census Glossary..Unit(s) of Observation.The reporting units for the ABS are employer companies or firms rather than establishments. A company or firm is comprised of one or more in-scope establishments that operate under the ownership or control of a single organization..Geography Coverage.The data are shown for the U.S. only.For information about geographies, see Geographies..Industry Coverage.The data are shown for the total of all sectors ("00") NAICS code. Sector "00" is not an official NAICS sector but is rather a way to indicate a total for multiple sectors. Note: Other programs outside of ABS may use sector 00 to indicate when multiple NAICS sectors are being displayed within the same table and/or dataset.The following are excluded from the total of all sectors:Crop and Animal Production (NAICS 111 and 112)Rail Transportation (NAICS 482)Postal Service (NAICS 491)Monetary Authorities-Central Bank (NAICS 521)Funds, Trusts, and Other Financial Vehicles (NAICS 525)Religious, Grantmaking, Civic, Professional, and Similar Organizations (NAICS 813)Private Households (NAICS 814)Public Administration (NAICS 92)For information about NAICS, see North American Industry Classification System..Sampling.The ABS sample includes firms that are selected with certainty if they have known research and development activities, were included in the 2017 BERD sample, or have high receipts, payroll, or employment. Total sample size is 850,000 firms. The universe is stratified by state, industry group, and expected demographic group. Firms selected to the sample receive a questionnaire. For all data on this table, firms not selected into the sample are represented with administrative, 2017 Economic Census, or other economic surveys records.For more information about the sample design, see Annual Business Survey Methodology..Confidentiality.The Census Bureau has reviewed this data product to ensure appropriate access, use, and disclosure avoidance protection of the confidential source data (Project No. P-7504866, Disclosure Review Board (DRB) approval number: CBDRB-FY20-008).To protect confidentiality, the U.S. Census Bureau suppresses cell values to minimize the risk of identifying a particular business' data or identity.To comply with data quality standards, data rows with high relative standard errors (RSE) are not presented. Additionally, firm counts are suppressed when other select statistics in the same row are suppressed. More information on disclosure avoidance is available in the Annual Business Survey Methodology..Technical Documentation/Methodology.For detailed information about the methods used to collect data and produce statistics, survey questionnaires, Primary Business Activity/NAICS codes, and more, see Technical Documentation..Weights.For more information about weighting, see Annual Business Survey Methodology.....

Key Table Information.Table Title.Annual Business Survey: Statistics for Employer Firms by Race for the U.S.: 2022.Table ID.ABSCS2022.AB00MYCSA01C.Survey/Program.Economic Surveys.Year.2022.Dataset.ECNSVY Annual Business Survey Company Summary.Release Date.2024-12-19.Release Schedule.The Annual Business Survey (ABS) occurs every year, beginning in reference year 2017.For more information about ABS planned data product releases, see Tentative ABS Schedule..Dataset Universe.The dataset universe consists of employer firms that are in operation for at least some part of the reference year, are located in one of the 50 U.S. states, associated offshore areas, or the District of Columbia, have paid employees and annual receipts of $1,000 or more, and are classified in one of nineteen in-scope sectors defined by the 2022 North American Industry Classification System (NAICS), except for NAICS 111, 112, 482, 491, 521, 525, 813, 814, and 92 which are not covered..Sponsor.National Center for Science and Engineering Statistics, U.S. National Science Foundation.Methodology.Data Items and Other Identifying Records.Number of employer firms (firms with paid employees)Sales and receipts of employer firms (reported in $1,000s of dollars)Number of employees (during the March 12 pay period)Annual payroll (reported in $1,000s of dollars)These data are aggregated by the following demographic classifications of firm for:All firms Classifiable (firms classifiable by sex, ethnicity, race, and veteran status) Race White Black or African American American Indian and Alaska Native Asian Asian Indian Chinese Filipino Japanese Korean Vietnamese Other Asian Native Hawaiian and Other Pacific Islander Native Hawaiian Guamanian or Chamorro Samoan Other Pacific Islander Minority (Firms classified as any race and ethnicity combination other than non-Hispanic and White) Equally minority/nonminority Nonminority (Firms classified as non-Hispanic and White) Unclassifiable (firms not classifiable by sex, ethnicity, race, and veteran status) Definitions can be found by clicking on the column header in the table or by accessing the Economic Census Glossary..Unit(s) of Observation.The reporting units for the ABS are employer companies or firms rather than establishments. A company or firm is comprised of one or more in-scope establishments that operate under the ownership or control of a single organization..Geography Coverage.The data are shown for the U.S. only.For information about geographies, see Geographies..Industry Coverage.The data are shown for the total of all sectors ("00") NAICS code. Sector "00" is not an official NAICS sector but is rather a way to indicate a total for multiple sectors. Note: Other programs outside of ABS may use sector 00 to indicate when multiple NAICS sectors are being displayed within the same table and/or dataset.The following are excluded from the total of all sectors:Crop and Animal Production (NAICS 111 and 112)Rail Transportation (NAICS 482)Postal Service (NAICS 491)Monetary Authorities-Central Bank (NAICS 521)Funds, Trusts, and Other Financial Vehicles (NAICS 525)Office of Notaries (NAICS 541120)Religious, Grantmaking, Civic, Professional, and Similar Organizations (NAICS 813)Private Households (NAICS 814)Public Administration (NAICS 92)For information about NAICS, see North American Industry Classification System..Sampling.The ABS sample includes firms that are selected with certainty if they have known research and development activities, were included in the 2022 BERD sample, or have high receipts, payroll, or employment. Total sample size is 850,000 firms. The universe is stratified by state, industry group, and expected demographic group. Firms selected to the sample receive a questionnaire. For all data on this table, firms not selected into the sample are represented with administrative, 2022 Economic Census, or other economic surveys records.For more information about the sample design, see Annual Business Survey Methodology..Confidentiality.The Census Bureau has reviewed this data product to ensure appropriate access, use, and disclosure avoidance protection of the confidential source data (Project No. P-7504866, Disclosure Review Board (DRB) approval number: CBDRB-FY24-0351).To protect confidentiality, the U.S. Census Bureau suppresses cell values to minimize the risk of identifying a particular business' data or identity.To comply with data quality standards, data rows with high relative standard errors (RSE) are not presented. Additionally, firm counts are suppressed when other select statistics in the same row are suppressed. More information on disclosure avoidance is available in the Annual Business Survey Methodology..Technical Documentation/Methodology.For detailed information about the methods used to collect data and produce statistics, survey questionnaires, Primary Business Activity/NAICS codes, and more, see Technical Documentation..Weights.For more information about weighting, see An...

This dataset contains information on:

· Estimated resident population (ERP) at 30 June 1996, 2001, 2006, 2013, and 2018 for total population

· ERP at 30 June 2018 by ethnic groups (European or Other (including New Zealander), Māori, Pacific, Asian, and Middle Eastern/Latin American/African) – estimates and percentage

· Sex ratio – number of males per 100 females

· ERP at 30 June 2018 by broad age groups and median age

· Geographies available are regional council areas, territorial authority and Auckland local board areas, Statistical Area 2, and urban rural.

Note: The geography corresponds to 2020 boundaries

Note: -999 indicates data are not available.

​

About the estimated resident population

The estimated resident population at 30 June in the census year is based on the census usually resident population count, with updates for:

· net census undercount (as measured by a post-enumeration survey)

· residents temporarily overseas on census night

· births, deaths and net migration between census night and 30 June

· reconciliation with demographic estimates at the youngest ages.

The estimated resident population is not directly comparable with the census usually resident population count because of these adjustments.

For more detailed information about the methods used to calculate each base population, see DataInfo+ Demographic estimates.

​

Ethnic groups

It is important to note that these ethnic groups are not mutually exclusive because people can and do identify with more than one ethnicity. People who identify with more than one ethnicity have been included in each ethnic group.

The 'Māori', 'Pacific', 'Asian' and 'Middle Eastern/Latin American/African' ethnic groups are defined in level 1 of the Ethnicity New Zealand Standard Classification 2005. The estimates for the 'European or Other (including New Zealander)' group include people who belong to the 'European' or 'Other ethnicity' groups defined in level 1 of the standard classification. If a person belongs to both the 'European' and 'Other ethnicity' groups they have only been counted once. Almost all people in the 'Other ethnicity' group belong to the 'New Zealander' sub-group.

​

Time series

This time series is irregular. Because the 2011 Census was cancelled after the Canterbury earthquake on 22 February 2011, the gap between the 2006-base and 2013-base estimated resident population is seven years. The change in data between 2006 and 2013 may be greater than in the usual five-year gap between censuses. Be careful when comparing trends.

​

Rounding

Individual figures may not sum to stated totals due to rounding.

​

More information

See Estimated resident population (2018-base): At 30 June 2018 for commentary about the 2018 ERP.

Subnational population estimates concepts – DataInfo+ provides definitions of terms used in the map.

Access more population estimates data in NZ.Stat:

Theme: Population estimates.

Release Date: 2018-08-10.[NOTE: Includes firms with payroll at any time during 2016. Employment reflects the number of paid employees during the March 12 pay period. Data are based on Census administrative records, and the estimates of business ownership by gender, ethnicity, race, and veteran status are from the 2016 Annual Survey of Entrepreneurs. Detail may not add to total due to rounding or because a Hispanic firm may be of any race. Moreover, each owner had the option of selecting more than one race and therefore is included in each race selected. Respondent firms include all firms that responded to the characteristic(s) tabulated in this dataset and reported gender, ethnicity, race, or veteran status for at least one owner and were not publicly held or not classifiable by gender, ethnicity, race, and veteran status. The 2016 Annual Survey of Entrepreneurs asked for information for up to four persons owning the largest percentage(s) of the business. Percentages are for owners of respondent firms only and are not recalculated when the dataset is resorted. Percentages are always based on total reporting (defined above) within a gender, ethnicity, race, veteran status, and/or industry group for the characteristics tabulated in this dataset. Firms with more than one domestic establishment are counted in each geographic area and industry in which they operate, but only once in the U.S. and state totals for all sectors. For information on confidentiality protection, sampling error, nonsampling error, and definitions, see Survey Methodology.]..Table Name. . Statistics for Owners of Respondent Employer Firms by Whether the Business Provided the Owner's Primary Source of Personal Income by Sector, Gender, Ethnicity, Race, Veteran Status, and Years in Business for the U.S., States, and Top 50 MSAs: 2016. ..Release Schedule. . This file was released in August 2018.. ..Key Table Information. . These data are related to all other 2016 ASE files.. Refer to the Methodology section of the Annual Survey of Entrepreneurs website for additional information.. ..Universe. . The universe for the 2016 Annual Survey of Entrepreneurs (ASE) includes all U.S. firms with paid employees operating during 2016 with receipts of $1,000 or more which are classified in the North American Industry Classification System (NAICS) sectors 11 through 99, except for NAICS 111, 112, 482, 491, 521, 525, 813, 814, and 92 which are not covered. Firms with more than one domestic establishment are counted in each geographic area and industry in which they operate, but only once in the U.S. total.. For Characteristics of Business Owners (CBO) data, all estimates are of owners of firms responding to the ASE. That is, estimates are based only on firms providing gender, ethnicity, race, or veteran status; or firms not classifiable by gender, ethnicity, race, and veteran status that returned an ASE online questionnaire with at least one question answered. The ASE online questionnaire provided space for up to four owners to report their characteristics.. CBO data are not representative of all owners of all firms operating in the United States. The data do not represent all business owners in the United States.. ..Geographic Coverage. . The data are shown for:. . United States. States and the District of Columbia. The fifty most populous metropolitan areas. . ..Industry Coverage. . The data are shown for the total of all sectors (00) and the 2-digit NAICS code level.. ..Data Items and Other Identifying Records. . Statistics for Owners of Respondent Employer Firms by Whether the Business Provided the Owner's Primary Source of Personal Income by Sector, Gender, Ethnicity, Race, Veteran Status, and Years in Business for the U.S., States, and Top 50 MSAs: 2016 contains data on:. . Number of owners of respondent firms with paid employees. Percent of number of owners of respondent firms with paid employees. . The data are shown for:. . Gender, ethnicity, race and veteran status of owners of respondent firms. . All owners of respondent firms. Female. Male. Hispanic. Non-Hispanic. White. Black or African American. American Indian and Alaska Native. Asian. Native Hawaiian and Other Pacific Islander. Some other race. Minority. Nonminority. Veteran. Nonveteran. . . Years in business. . All firms. Firms less than 2 years in business. Firms with 2 to 3 years in business. Firms with 4 to 5 years in business. Firms with 6 to 10 years in business. Firms with 11 to 15 years in business. Firms with 16 or more years in business. . . Whether the busines...

This dataset is published by the Research & Analytics Group at the Atlanta Regional Commission to show population change by utilizing the 2020 redistricting data and comparable data for 2010, 2000, and 1990 across multiple geographies for the State of Georgia. For a deep dive into the data model including every specific metric, see the Data Manifest. The manifest details ARC-defined naming conventions, names/descriptions and topics where applicable, summary levels; source tables; notes and so forth for all metrics.

It should be noted:The 2020 redistricting release is not as detailed in terms of data compared to ACS estimates; data include total population, population by race and ethnicity, and "voting age" population (i.e., adults) by race and ethnicity, adults are subtracted from the total population to show children (ages 0-17); total number of housing units, occupied housing units, and vacant housing units. Percent and change measures are calculated over four different Censuses.These data are expressed in terms of 2020 geographies such as the new 2020 Census tracts. This means that that historical data for geographies like cities have been estimated to the 2020 boundaries. For example, the city of Atlanta, which has made multiple annexations since 1990, has a higher estimated 1990 population of 400,452 (2020 boundaries) than the 394,017 reported in the 1990 Census (1990 boundaries).Due to changes in block geographies and annexations, 2010 population totals for custom geographies such as City of Atlanta NSAs may differ slightly from the numbers we have published in the past.The procedure to re-estimate historical data to 2020 blocks often results in fractional population (e.g., 1.25 instead of 1 or 2). Counts have been rounded to the nearest whole, but to be more precise, all aggregation, percent, and change measures were performed pre-rounding. Some change measures may appear curious as a result. For example, 100.4 - 20.8 = 79.6 which rounds to 80. But if rounded first, 100.4 rounds down to 100, 20.8 rounds up to 21; 100 - 21 = 79.Asian and Pacific Islander categories are combined to maximize compatibility with the 1990 release, which reported the two groups as a single category. Caution should be exercised with 1990 race data because the Census Bureau changed to the current system (which allows people to identify as biracial or multiracial) starting only in 2000.The "other" race category includes American Indian and Alaska Natives, people identifying with "some other race" and (for 2000 forward), people who identify as biracial or multiracial.For more information regarding Decennial Census source data, visit 2020 Census website

Social vulnerability is defined as the disproportionate susceptibility of some social groups to the impacts of hazards, including death, injury, loss, or disruption of livelihood. In this dataset from Climate Ready Boston, groups identified as being more vulnerable are older adults, children, people of color, people with limited English proficiency, people with low or no incomes, people with disabilities, and people with medical illnesses. Source:The analysis and definitions used in Climate Ready Boston (2016) are based on "A framework to understand the relationship between social factors that reduce resilience in cities: Application to the City of Boston." Published 2015 in the International Journal of Disaster Risk Reduction by Atyia Martin, Northeastern University.Population Definitions:Older Adults:Older adults (those over age 65) have physical vulnerabilities in a climate event; they suffer from higher rates of medical illness than the rest of the population and can have some functional limitations in an evacuation scenario, as well as when preparing for and recovering from a disaster. Furthermore, older adults are physically more vulnerable to the impacts of extreme heat. Beyond the physical risk, older adults are more likely to be socially isolated. Without an appropriate support network, an initially small risk could be exacerbated if an older adult is not able to get help.Data source: 2008-2012 American Community Survey 5-year Estimates (ACS) data by census tract for population over 65 years of age.Attribute label: OlderAdultChildren: Families with children require additional resources in a climate event. When school is cancelled, parents need alternative childcare options, which can mean missing work. Children are especially vulnerable to extreme heat and stress following a natural disaster.Data source: 2010 American Community Survey 5-year Estimates (ACS) data by census tract for population under 5 years of age.Attribute label: TotChildPeople of Color: People of color make up a majority (53 percent) of Boston’s population. People of color are more likely to fall into multiple vulnerable groups aswell. People of color statistically have lower levels of income and higher levels of poverty than the population at large. People of color, many of whom also have limited English proficiency, may not have ready access in their primary language to information about the dangers of extreme heat or about cooling center resources. This risk to extreme heat can be compounded by the fact that people of color often live in more densely populated urban areas that are at higher risk for heat exposure due to the urban heat island effect.Data source: 2008-2012 American Community Survey 5-year Estimates (ACS) data by census tract: Black, Native American, Asian, Island, Other, Multi, Non-white Hispanics.Attribute label: POC2Limited English Proficiency: Without adequate English skills, residents can miss crucial information on how to preparefor hazards. Cultural practices for information sharing, for example, may focus on word-of-mouth communication. In a flood event, residents can also face challenges communicating with emergency response personnel. If residents are more sociallyisolated, they may be less likely to hear about upcoming events. Finally, immigrants, especially ones who are undocumented, may be reluctant to use government services out of fear of deportation or general distrust of the government or emergency personnel.Data Source: 2008-2012 American Community Survey 5-year Estimates (ACS) data by census tract, defined as speaks English only or speaks English “very well”.Attribute label: LEPLow to no Income: A lack of financial resources impacts a household’s ability to prepare for a disaster event and to support friends and neighborhoods. For example, residents without televisions, computers, or data-driven mobile phones may face challenges getting news about hazards or recovery resources. Renters may have trouble finding and paying deposits for replacement housing if their residence is impacted by flooding. Homeowners may be less able to afford insurance that will cover flood damage. Having low or no income can create difficulty evacuating in a disaster event because of a higher reliance on public transportation. If unable to evacuate, residents may be more at risk without supplies to stay in their homes for an extended period of time. Low- and no-income residents can also be more vulnerable to hot weather if running air conditioning or fans puts utility costs out of reach.Data source: 2008-2012 American Community Survey 5-year Estimates (ACS) data by census tract for low-to- no income populations. The data represents a calculated field that combines people who were 100% below the poverty level and those who were 100–149% of the poverty level.Attribute label: Low_to_NoPeople with Disabilities: People with disabilities are among the most vulnerable in an emergency; they sustain disproportionate rates of illness, injury, and death in disaster events.46 People with disabilities can find it difficult to adequately prepare for a disaster event, including moving to a safer place. They are more likely to be left behind or abandoned during evacuations. Rescue and relief resources—like emergency transportation or shelters, for example— may not be universally accessible. Research has revealed a historic pattern of discrimination against people with disabilities in times of resource scarcity, like after a major storm and flood.Data source: 2008-2012 American Community Survey 5-year Estimates (ACS) data by census tract for total civilian non-institutionalized population, including: hearing difficulty, vision difficulty, cognitive difficulty, ambulatory difficulty, self-care difficulty, and independent living difficulty. Attribute label: TotDisMedical Illness: Symptoms of existing medical illnesses are often exacerbated by hot temperatures. For example, heat can trigger asthma attacks or increase already high blood pressure due to the stress of high temperatures put on the body. Climate events can interrupt access to normal sources of healthcare and even life-sustaining medication. Special planning is required for people experiencing medical illness. For example, people dependent on dialysis will have different evacuation and care needs than other Boston residents in a climate event.Data source: Medical illness is a proxy measure which is based on EASI data accessed through Simply Map. Health data at the local level in Massachusetts is not available beyond zip codes. EASI modeled the health statistics for the U.S. population based upon age, sex, and race probabilities using U.S. Census Bureau data. The probabilities are modeled against the census and current year and five year forecasts. Medical illness is the sum of asthma in children, asthma in adults, heart disease, emphysema, bronchitis, cancer, diabetes, kidney disease, and liver disease. A limitation is that these numbers may be over-counted as the result of people potentially having more than one medical illness. Therefore, the analysis may have greater numbers of people with medical illness within census tracts than actually present. Overall, the analysis was based on the relationship between social factors.Attribute label: MedIllnesOther attribute definitions:GEOID10: Geographic identifier: State Code (25), Country Code (025), 2010 Census TractAREA_SQFT: Tract area (in square feet)AREA_ACRES: Tract area (in acres)POP100_RE: Tract population countHU100_RE: Tract housing unit countName: Boston Neighborhood