SSTF 1 contains sample data weighted to represent the total population. In addition, the file contains 100-percent counts and unweighted sample counts for total persons and total housing units in the 1990 Census. Population variables include citizenship, ability to speak English, age, number of children ever born, class of worker, disability status, earnings in 1989, educational attainment, employment status, household size, industry, labor force status, language spoken at home, occupation, poverty status in 1989, school enrollment, and year of entry into the United States. Housing variables include gross rent, housing units, kitchen facilities, mortgage status, plumbing facilities, tenure, units in structure, and year householder moved into unit. The data are also crosstabulated and presented in a variety of tables. Crosstabulations include citizenship and year of entry by all other variables, age (groups) by sex by school enrollment or college enrollment or educational attainment and employment status, age by poverty status by sex, relationship by family type by subfamily type, and employment status by hours worked last week and year last worked. The dataset includes both "A" and "B" records. "A" records have three population (PA) and three housing (HA) tables. The "B" records present more detail in 66 population (PB) and 10 housing (HB) tables, and are divided into 22 segments of 8,142 characters each.

This layer contains 2010-2014 American Community Survey (ACS) 5-year data, and contains estimates and margins of error. The layer shows children by nativity of parents by age group. This is shown by tract, county, and state boundaries. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. This layer is symbolized to show the percentage of children who are in immigrant families (children who are foreign born or live with at least one parent who is foreign born). To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. Vintage: 2010-2014ACS Table(s): B05009 Data downloaded from: Census Bureau's API for American Community Survey Date of API call: November 11, 2020National Figures: data.census.govThe United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. For more information about ACS layers, visit the FAQ. Please cite the Census and ACS when using this data.Data Note from the Census: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 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.Data Processing Notes:This layer has associated layers containing the most recent ACS data available by the U.S. Census Bureau. Click here to learn more about ACS data releases and click here for the associated boundaries layer. The reason this data is 5+ years different from the most recent vintage is due to the overlapping of survey years. It is recommended by the U.S. Census Bureau to compare non-overlapping datasets.Boundaries come from the US Census TIGER geodatabases. Boundary vintage (2014) appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines clipped for cartographic purposes. For census tracts, the water cutouts are derived from a subset of the 2010 AWATER (Area Water) boundaries offered by TIGER. For state and county boundaries, the water and coastlines are derived from the coastlines of the 500k TIGER Cartographic Boundary Shapefiles. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters). The States layer contains 52 records - all US states, Washington D.C., and Puerto RicoCensus tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. These negative values exist in the raw API data to indicate the following situations: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.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.The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.The estimate is controlled. A statistical test for sampling variability is not appropriate.The data for this geographic area cannot be displayed because the number of sample cases is too small.

Abstract (en): The Urban Household Sample of the 1860 United States Census was designed to supplement the Bateman-Foust rural sample with observations from urban areas. The sample covers both northern and southern towns and cities and permits examination of female occupations and labor force participation rates. Information on individuals includes occupation, city of residence, age, sex, race, dollar value of real and personal property owned, whether American or foreign born, and literacy. The second release of this collection adds nine constructed variables, including several weight variables, collapsed occupation, ICPSR state code, region, and unique internal family and household identifier numbers. ICPSR data undergo a confidentiality review and are altered when necessary to limit the risk of disclosure. ICPSR also routinely creates ready-to-go data files along with setups in the major statistical software formats as well as standard codebooks to accompany the data. In addition to these procedures, ICPSR performed the following processing steps for this data collection: Created variable labels and/or value labels.. All individuals living in towns with populations of 3,000 or more who were enumerated in the 1860 Census of Population Manuscript Schedules. Stratified random sample. 2009-07-24 SAS, SPSS, and Stata setups have been added to this data collection. Funding insitution(s): University of Chicago. Booth School of Business. Center for Population Economics. Nathanial T. Wilcox of the University of Chicago collaborated with Jon Moen for the second release of the data collection.

This layer shows place of birth by citizenship status. This is shown by tract, county, and state centroids. This service is updated annually to contain the most currently released American Community Survey (ACS) 5-year data, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. This layer is symbolized to show the predominant area of birth among those who are foreign born as well as the count of the foreign-born population. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. Current Vintage: 2019-2023ACS Table(s): B05002 (Not all lines of this ACS table are available in this feature layer.)Data downloaded from: Census Bureau's API for American Community Survey Date of API call: December 12, 2024National Figures: data.census.govThe United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. For more information about ACS layers, visit the FAQ. Please cite the Census and ACS when using this data.Data Note from the Census: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 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.Data Processing Notes:This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Click here to learn more about ACS data releases.Boundaries come from the US Census TIGER geodatabases, specifically, the National Sub-State Geography Database (named tlgdb_(year)_a_us_substategeo.gdb). Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For census tracts, the water cutouts are derived from a subset of the 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract level boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2023 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters).The States layer contains 52 records - all US states, Washington D.C., and Puerto RicoCensus tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. These negative values exist in the raw API data to indicate the following situations: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.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.The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.The estimate is controlled. A statistical test for sampling variability is not appropriate.The data for this geographic area cannot be displayed because the number of sample cases is too small.

A computerized data set of demographic, economic and social data for 227 countries of the world. Information presented includes population, health, nutrition, mortality, fertility, family planning and contraceptive use, literacy, housing, and economic activity data. Tabular data are broken down by such variables as age, sex, and urban/rural residence. Data are organized as a series of statistical tables identified by country and table number. Each record consists of the data values associated with a single row of a given table. There are 105 tables with data for 208 countries. The second file is a note file, containing text of notes associated with various tables. These notes provide information such as definitions of categories (i.e. urban/rural) and how various values were calculated. The IDB was created in the U.S. Census Bureau''s International Programs Center (IPC) to help IPC staff meet the needs of organizations that sponsor IPC research. The IDB provides quick access to specialized information, with emphasis on demographic measures, for individual countries or groups of countries. The IDB combines data from country sources (typically censuses and surveys) with IPC estimates and projections to provide information dating back as far as 1950 and as far ahead as 2050. Because the IDB is maintained as a research tool for IPC sponsor requirements, the amount of information available may vary by country. As funding and research activity permit, the IPC updates and expands the data base content. Types of data include: * Population by age and sex * Vital rates, infant mortality, and life tables * Fertility and child survivorship * Migration * Marital status * Family planning Data characteristics: * Temporal: Selected years, 1950present, projected demographic data to 2050. * Spatial: 227 countries and areas. * Resolution: National population, selected data by urban/rural * residence, selected data by age and sex. Sources of data include: * U.S. Census Bureau * International projects (e.g., the Demographic and Health Survey) * United Nations agencies Links: * ICPSR: http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/08490

The American Community Survey (ACS) is a part of the Decennial Census Program, and is designed to produce critical information about the characteristics of local communities. The ACS publishes social, housing, and economic characteristics for demographic groups covering a broad spectrum of geographic areas in the United States and Puerto Rico. Every year the ACS supports the release of single-year estimates for geographic areas with populations of 65,000 or more. Demographic variables include sex, age, relationship, households by type, race, and Hispanic origin. Social characteristics variables include school enrollment, educational attainment, marital status, fertility, grandparents caring for children, veteran status, disability status, residence one year ago, place of birth, United States citizenship status, year of entry, world region of birth of foreign born, language spoken at home, and ancestry. Variables focusing on economic characteristics include employment status, commuting to work, occupation, industry, class of worker, income and benefits, and poverty status. Variables focusing on housing characteristics include occupancy, units in structure, year structure was built, number of rooms, number of bedrooms, housing tenure, year householder moved into unit, vehicles available, house heating fuel, utility costs, occupants per room, housing value, and mortgage status. The American Community Survey is conducted under the authority of Title 13, United States Code, Sections 141 and 193, and response is mandatory. (Source: ICPSR, retrieved 06/29/2011)

The Virgin Islands of the United States Demographic Profile Summary File contains data on population and housing subjects derived from questions on the 2010 United States Virgin Islands Census questionnaire. Population subjects include age, sex, children ever born, citizenship status, disability status, educational attainment, race, Hispanic or Latino origin, family type, grandparents as caregivers, group quarters population, health insurance coverage status, household type and relationship, employment status, work experience, class of worker, industry, occupation, place of work, journey to work, travel time to work, language spoken at home and ability to speak English, marital status, foreign born status, nativity, year of entry, place of birth, parents' place of birth, earnings, income, poverty status, residence in 2009, school enrollment, vocational training and veteran status. Housing subjects include computer ownership, cooking fuel, gross rent, internet service, kitchen facilities, mortgage status, number of rooms, number of bedrooms, occupancy status, occupants per room, plumbing facilities, purchase of water from water vendor, selected monthly owner costs, sewage disposal, source of water, telephone service available, tenure, units in structure, vacancy status, value of home, vehicles available, year householder moved into unit and year structure built. The population and housing data are organized in 115 tables which are presented at five levels of observation: the United States Virgin Islands as a whole, island, census subdistrict, estate and place (town or census designated place). Every table cell is represented by a separate variable. The data are segmented into four data files. One data file contains geographic identification variables and the other three the population and housing variables. Together with the data files, the Census Bureau prepared a codebook and additional documentation, a Microsoft Access database shell, and a HTML-based application for displaying the tables called the Interactive Summary Level Access and Navigation Database (ISLAND). ICPSR provides all of these components, except the codebook, in three ZIP archives. The first archive contains the data files, the second the database shell and additional documentation and the third contains ISLAND. The codebook is provided as a separate file.

The American Community Survey (ACS) is an ongoing survey that provides vital information on a yearly basis about our nation and its people. Information from the survey generates data that help determine how more than $400 billion in federal and state funds are distributed each year. Demographic variables include sex, age, relationship, households by type, race, and Hispanic origin. Social characteristics variables include school enrollment, educational attainment, marital status, fertility, grandparents caring for children, veteran status, disability status, residence one year ago, place of birth, United States citizenship status, year of entry, world region of birth of foreign born, language spoken at home, and ancestry. Variables focusing on economic characteristics include employment status, commuting to work, occupation, industry, class of worker, income and benefits, and poverty status. Variables focusing on housing characteristics include occupancy, units in structure, year structure was built, number of rooms, number of bedrooms, housing tenure, year householder moved into unit, vehicles available, house heating fuel, utility costs, occupants per room, housing value, and mortgage status. The American Community Survey is conducted under the authority of Title 13, United States Code, Sections 141 and 193, and response is mandatory

The Guam Demographic Profile Summary File contains data on population and housing subjects derived from questions on the 2010 Guam Census questionnaire. Population subjects include age, sex, children ever born, citizenship status, disability status, educational attainment, ethnic origin or race, family type, grandparents as caregivers, group quarters population, health insurance coverage status, household type and relationship, employment status and subsistence activity, work experience, class of worker, industry, occupation, place of work, journey to work, travel time to work, language spoken at home and frequency of language usage, marital status, nativity, foreign-born status, year of entry, place of birth, parents' place of birth, earnings, income, remittances sent abroad, poverty status, residence in 2009, reason for moving, school enrollment, vocational training and veteran status. Housing subjects include air conditioning, battery-operated radio ownership, computer ownership, gross rent, internet service, kitchen facilities, mortgage status, number of rooms, number of bedrooms, occupancy status, occupants per room, plumbing facilities, selected monthly owner costs, sewage disposal, source of water, telephone service available, tenure, type of building materials, units in structure, vacancy status, value of home, vehicles available, year householder moved into unit and year structure built. The population and housing data are organized in 121 tables which are presented at three levels of observation: Guam as a whole, municipalities and census designated places. Every table cell is represented by a separate variable. The data are segmented into four data files. One data file contains geographic identification variables and the other three the population and housing variables. Together with the data files, the Census Bureau prepared a codebook and additional documentation, a Microsoft Access database shell, and a HTML-based application for displaying the tables called the Interactive Summary Level Access and Navigation Database (ISLAND). ICPSR provides all of these components, except the codebook, in three ZIP archives. The first archive contains the data files, the second the database shell and additional documentation and the third contains ISLAND. The codebook is provided as a separate file.

Abstract

This dataset includes all individuals from the 1870 US census.

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Documentation

This dataset was developed through a collaboration between the Minnesota Population Center and the Church of Jesus Christ of Latter-Day Saints. The data contain demographic variables, economic variables, migration variables and race variables. Unlike more recent census datasets, pre-1900 census datasets only contain individual level characteristics and no household or family characteristics, but household and family identifiers do exist.

The official enumeration day of the 1870 census was 1 June 1870. The main goal of an early census like the 1870 U.S. census was to allow Congress to determine the collection of taxes and the appropriation of seats in the House of Representatives. Each district was assigned a U.S. Marshall who organized other marshals to administer the census. These enumerators visited households and recorder names of every person, along with their age, sex, color, profession, occupation, value of real estate, place of birth, parental foreign birth, marriage, literacy, and whether deaf, dumb, blind, insane or “idiotic”.

Sources: Szucs, L.D. and Hargreaves Luebking, S. (1997). Research in Census Records, The Source: A Guidebook of American Genealogy. Ancestry Incorporated, Salt Lake City, UT Dollarhide, W.(2000). The Census Book: A Genealogist’s Guide to Federal Census Facts, Schedules and Indexes. Heritage Quest, Bountiful, UT

Dataset contains counts and measures for individuals from the 2013, 2018, and 2023 Censuses. Data is available by statistical area 1.

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The variables included in this dataset are for the census usually resident population count (unless otherwise stated). All data is for level 1 of the classification.

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The variables for part 2 of the dataset are:

• Individual home ownership for the census usually resident population count aged 15 years and over
• Usual residence 1 year ago indicator
• Usual residence 5 years ago indicator
• Years at usual residence
• Average years at usual residence
• Years since arrival in New Zealand for the overseas-born census usually resident population count
• Average years since arrival in New Zealand for the overseas-born census usually resident population count
• Study participation
• Main means of travel to education, by usual residence address for the census usually resident population who are studying
• Main means of travel to education, by education address for the census usually resident population who are studying
• Highest qualification for the census usually resident population count aged 15 years and over
• Post-school qualification in New Zealand indicator for the census usually resident population count aged 15 years and over
• Highest secondary school qualification for the census usually resident population count aged 15 years and over
• Post-school qualification level of attainment for the census usually resident population count aged 15 years and over
• Sources of personal income (total responses) for the census usually resident population count aged 15 years and over
• Total personal income for the census usually resident population count aged 15 years and over
• Median ($) total personal income for the census usually resident population count aged 15 years and over
• Work and labour force status for the census usually resident population count aged 15 years and over
• Job search methods (total responses) for the unemployed census usually resident population count aged 15 years and over
• Status in employment for the employed census usually resident population count aged 15 years and over
• Unpaid activities (total responses) for the census usually resident population count aged 15 years and over
• Hours worked in employment per week for the employed census usually resident population count aged 15 years and over
• Average hours worked in employment per week for the employed census usually resident population count aged 15 years and over
• Industry, by usual residence address for the employed census usually resident population count aged 15 years and over
• Industry, by workplace address for the employed census usually resident population count aged 15 years and over
• Occupation, by usual residence address for the employed census usually resident population count aged 15 years and over
• Occupation, by workplace address for the employed census usually resident population count aged 15 years and over
• Main means of travel to work, by usual residence address for the employed census usually resident population count aged 15 years and over
• Main means of travel to work, by workplace address for the employed census usually resident population count aged 15 years and over
• Sector of ownership for the employed census usually resident population count aged 15 years and over
• Individual unit data source.

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Download lookup file for part 2 from Stats NZ ArcGIS Online or embedded attachment in Stats NZ geographic data service. Download data table (excluding the geometry column for CSV files) using the instructions in the Koordinates help guide.

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Footnotes

Te Whata

Under the Mana Ōrite Relationship Agreement, Te Kāhui Raraunga (TKR) will be publishing Māori descent and iwi affiliation data from the 2023 Census in partnership with Stats NZ. This will be available on Te Whata, a TKR platform.

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Geographical boundaries

Statistical standard for geographic areas 2023 (updated December 2023) has information about geographic boundaries as of 1 January 2023. Address data from 2013 and 2018 Censuses was updated to be consistent with the 2023 areas. Due to the changes in area boundaries and coding methodologies, 2013 and 2018 counts published in 2023 may be slightly different to those published in 2013 or 2018.

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Subnational census usually resident population

The census usually resident population count of an area (subnational count) is a count of all people who usually live in that area and were present in New Zealand on census night. It excludes visitors from overseas, visitors from elsewhere in New Zealand, and residents temporarily overseas on census night. For example, a person who usually lives in Christchurch city and is visiting Wellington city on census night will be included in the census usually resident population count of Christchurch city.

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Population counts

Stats NZ publishes a number of different population counts, each using a different definition and methodology. Population statistics – user guide has more information about different counts.

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Caution using time series

Time series data should be interpreted with care due to changes in census methodology and differences in response rates between censuses. The 2023 and 2018 Censuses used a combined census methodology (using census responses and administrative data), while the 2013 Census used a full-field enumeration methodology (with no use of administrative data).

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Study participation time series

In the 2013 Census study participation was only collected for the census usually resident population count aged 15 years and over.

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About the 2023 Census dataset

For information on the 2023 dataset see Using a combined census model for the 2023 Census. We combined data from the census forms with administrative data to create the 2023 Census dataset, which meets Stats NZ's quality criteria for population structure information. We added real data about real people to the dataset where we were confident the people who hadn’t completed a census form (which is known as admin enumeration) will be counted. We also used data from the 2018 and 2013 Censuses, administrative data sources, and statistical imputation methods to fill in some missing characteristics of people and dwellings.

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Data quality

The quality of data in the 2023 Census is assessed using the quality rating scale and the quality assurance framework to determine whether data is fit for purpose and suitable for release. Data quality assurance in the 2023 Census has more information.

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Concept descriptions and quality ratings

Data quality ratings for 2023 Census variables has additional details about variables found within totals by topic, for example, definitions and data quality.

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Disability indicator

This data should not be used as an official measure of disability prevalence. Disability prevalence estimates are only available from the 2023 Household Disability Survey. Household Disability Survey 2023: Final content has more information about the survey.

Activity limitations are measured using the Washington Group Short Set (WGSS). The WGSS asks about six basic activities that a person might have difficulty with: seeing, hearing, walking or climbing stairs, remembering or concentrating, washing all over or dressing, and communicating. A person was classified as disabled in the 2023 Census if there was at least one of these activities that they had a lot of difficulty with or could not do at all.

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Using data for good

Stats NZ expects that, when working with census data, it is done so with a positive purpose, as outlined in the Māori Data Governance Model (Data Iwi Leaders Group, 2023). This model states that "data should support transformative outcomes and should uplift and strengthen our relationships with each other and with our environments. The avoidance of harm is the minimum expectation for data use. Māori data should also contribute to iwi and hapū tino rangatiratanga”.

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Confidentiality

The 2023 Census confidentiality rules have been applied to 2013, 2018, and 2023 data. These rules protect the confidentiality of individuals, families, households, dwellings, and undertakings in 2023 Census data. Counts are calculated using fixed random rounding to base 3 (FRR3) and suppression of ‘sensitive’ counts less than six, where tables report multiple geographic variables and/or small populations. Individual figures may not always sum to stated totals. Applying confidentiality rules to 2023 Census data and summary of changes since 2018 and 2013 Censuses has more information about 2023 Census confidentiality rules.

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Measures

Measures like averages, medians, and other quantiles are calculated from unrounded counts, with input noise added to or subtracted from each contributing value

The American Community Survey (ACS) is a part of the Decennial Census Program, and is designed to produce critical information about the characteristics of local communities. The ACS publishes social, housing, and economic characteristics for demographic groups covering a broad spectrum of geographic areas in the United States and Puerto Rico. Every year the ACS supports the release of single-year estimates for geographic areas with populations of 65,000 or more. Demographic variables include sex, age, relationship, households by type, race, and Hispanic origin. Social characteristics variables include school enrollment, educational attainment, marital status, fertility, grandparents caring for children, veteran status, disability status, residence one year ago, place of birth, United States citizenship status, year of entry, world region of birth of foreign born, language spoken at home, and ancestry. Variables focusing on economic characteristics include employment status, commuting to work, occupation, industry, class of worker, income and benefits, and poverty status. Variables focusing on housing characteristics include occupancy, units in structure, year structure was built, number of rooms, number of bedrooms, housing tenure, year householder moved into unit, vehicles available, house heating fuel, utility costs, occupants per room, housing value, and mortgage status. The American Community Survey is conducted under the authority of Title 13, United States Code, Sections 141 and 193, and response is mandatory. (Source: ICPSR, retrieved 06/29/2011)

Summary File 3 Data Profile 2 (SF3 Table DP-2) for Census Tracts in Minneapolis-St. Paul 7 County metropolitan area is a subset of the profile of selected social characteristics for 2000 prepared by the U.S. Census Bureau.

This table (DP-2) includes: School Enrollment, Educational Attainment, Marital Status, Grandparents as Caregivers, Veteran Status, Disability Status of the Civilian Noninstitutionalized Population, Residence in 1995, Nativity and Place of Birth, Region of Birth of Foreign Born, Language Spoken At Home, Ancestry

US Census 2000 Demographic Profiles: 100-percent and Sample Data

The profile includes four tables (DP-1 thru DP-4) that provide various demographic, social, economic, and housing characteristics for the United States, states, counties, minor civil divisions in selected states, places, metropolitan areas, American Indian and Alaska Native areas, Hawaiian home lands and congressional districts (106th Congress). It includes 100-percent and sample data from Census 2000. The DP-1 table is available as part of the Summary File 1 (SF 1) dataset, and the other three tables are available as part of the Summary File 3 (SF 3) dataset.

The US Census provides DP-1 thru DP-4 data at the Census tract level through their DataFinder search engine. However, since the Metropolitan Council and MetroGIS participants are interested in all Census tracts within the seven county metropolitan area, it was quicker to take the raw Census SF-1 and SF-3 data at tract levels and recreate the DP1-4 variables using the appropriate formula for each DP variable. This file lists the formulas used to create the DP variables.

This data collection contains selected variables at the tract level from the 1960 Census of Population and Housing. Census tracts are statistical subdivisions, most of which are within Standard Metropolitan Statistical Areas (SMSAs). Tracts were originally designed to be relatively homogenous with respect to population characteristics, economic status, and living conditions. This tables includes some of the census data for Maryland, including the housing occupants' family structure, ages, basic racial categories, origins if foreign-born, child custody information, and education levels. Coverage includes the following counties: Anne Arundel, Baltimore, Baltimore City, Caroll, Howard, Prince George's. Data were extracted from 1960 Census Tract-Level Data from the Inter-university Consortium for Political and Social Science Research site. This is part of a collection of 221 Baltimore Ecosystem Study metadata records that point to a geodatabase. The geodatabase is available online and is considerably large. Upon request, and under certain arrangements, it can be shipped on media, such as a usb hard drive. The geodatabase is roughly 51.4 Gb in size, consisting of 4,914 files in 160 folders. Although this metadata record and the others like it are not rich with attributes, it is nonetheless made available because the data that it represents could be indeed useful.

About this dataset

Context

The dataset tabulates the population of International Falls by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for International Falls. The dataset can be utilized to understand the population distribution of International Falls by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in International Falls. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for International Falls.

Key observations

Largest age group (population): Male # 60-64 years (229) | Female # 55-59 years (344). Source: U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis.

Variables / Data Columns

• Age Group: This column displays the age group for the International Falls population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the International Falls is shown in the following column.
• Population (Female): The female population in the International Falls is shown in the following column.
• Gender Ratio: Also known as the sex ratio, this column displays the number of males per 100 females in International Falls for each age group.

Good to know

Margin of Error

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

Custom data

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

Recommended for further research

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

There is a requirement, as per Commission Implementing Regulation (EU) 2018/1799, to deliver Census data for the reference year 2021 to Eurostat. In September 2020, the Irish Government decided to postpone the scheduled April 2021 Census to April 2022 following a recommendation from CSO related to the impact of the Covid-19 pandemic. The CSO however has agreed that the office will still meet its legal requirement. It will base the Eurostat requirements on Census 2022 data, using administrative and other sources to appropriately adjust the data to reference year 2021. A (preliminary) headcount of usual residents at the 1 km² grid level (there are approximately 73,000 such square kilometres in Ireland) is required by Eurostat by 31^st December 2022. The data was produced in the following manner:

Initial preliminary Census estimate for April 2022 As part of the field operation for the 2022 Census, the CSO introduced a new smartphone-based application that allowed field staff to capture information about every dwelling in the country. This application facilitated the production of a preliminary population publication less than 12 weeks (June 23^rd) after census night (April 3^rd). The information includes data on the number of de facto occupants. This information is provisional, and the final file will not be completed until all collected paper forms are fully processed, which is expected to be around the end of January 2023. The provisional data should however be a very strong indicator of the final results.

The preliminary Census de facto population estimate was 5,123,536 persons, available at the 1 km² grid level. As we need the population on a usual resident basis, it was decided to adjust this estimated de facto population at the 1 km² grid level by applying the arithmetic differences between the 2016 usual resident and de facto population counts at that level to the de facto population for 2022. A ratio model, where rates of change of de facto to usual resident counts are applied instead of differences, was also considered but this led to more extreme adjustments, mainly where there was a large change in the population count of a cell between 2016 and 2022. This reduced the usual resident population to 5,101,268 for April 2022, a fall of 22,268 persons.

Temporary Absent Dwellings Census also provided data on the temporarily absent dwellings dataset (at 1 km² grid level), containing a count of persons usually resident in the State but whose entire household were abroad on census night and therefore not included in the de facto population count. This covers 33,365 temporarily absent dwellings with 50,749 temporarily absent persons across 9,138 grid cells. This category was not present in the 2016 figures so it was decided to include these absent persons as they meet the definition of usual residents and will be present in the final transmission, due March 2024. The resulting usually resident population count for 3^rd April 2022 was estimated as 5,152,671 persons.

Note that in a small number cases (80 grid cells), adjustments resulted in a negative cell value, but these were set to zero.

Final preliminary estimate

The CSO then adjusted this figure of estimated usual residents for 3^rd April 2022 back to the 3^rd December 2021 reference point by performing a reverse cohort-survival model.

Firstly, there are an estimated 21,528 births, some 12,405 deaths and approximately 63,595 inward and 25,730 outward migrants for the four-month period December 2021 to March 2022. This affects a total of approximately 123,000 persons, or about 2.4% in a total population of around 5.15 million persons. These population changes were ‘reversed’, as indicated below. Secondly, we also ‘reversed’ those persons who moved from their address within Ireland after December 3^rd 2021 to their Census April 3^rd 2022 address. Based on the selection method approximately 85,000 persons were moved to their previous address, representing about 1.7% of the population.

The steps in the process were:

Births We took the actual November 2015 to April 2016 births from Census 2016 with the variables grid reference, gender and NUTS3 as the sampling frame for the selection of births. Then, using data from table 19 in the Q1 2022 Vital Stats quarterly release (Table VSQ19 on Statbank), we derived the number of Q1 2022 births at NUTS3 by gender level. We also included a proportion of Q4 2021 births, taking one-third to represent December 2021. There are 21,528 births in total for the four-month period we are interested in (16,121 for Q1 2022 plus a third of the value of Q4 2021 which is 5,407), see table 2. Then, using the SAS procedure surveyselect, we selected, at random, the required number of births per strata from the frame and totalled up per grid reference. The resulting figure is the number of people removed from the Census 2021 grid totals, as these figures represent those born during December 2021 to March 2022.

We took the entire Census 2016 data with the variables grid reference, gender, NUTS3 and broad age group (0-14, 15-29, 30-49, 50-64, 65-84 and 85+) as the sampling frame for the selection of people to add back in who died between December 2020 and March 2022. This stratification results in 96 cells. This frame serves as a proxy for the distribution of deaths across the 1km grid square strata. Next, we obtained the Q4 2021 and Q1 2022 mortality data stratified by gender, NUTS3 and age group, provided by the Vital Stats statistician. The total number is 12,405 deaths for the four-month period of interest (9,535 for Q1 2022 plus one third of the value for Q4 2021 which is 8,626), see tables 3 and 4.

Then using the SAS procedure surveyselect, we selected, at random, the required number of deaths per strata from the frame and total up per grid reference. The resulting figure is simply the number of people added to the Census 2021 grid figures as summarised at the grid level, as they represent those who died during December 2021 to March 2022.

Inward and outward migrants

The processing of the inward and outward migrants essentially follows the same methodology in that we used Census 2016 as a sampling frame for the inclusion of those who emigrated in December 2021 and March 2022 and the exclusion of those who immigrated in the same period.

We took the Census 2016 with the variables grid reference, gender, NUTS3, broad nationality (Irish, UK, EU14 excl. IE, EU15 to 27 and Rest of the World) and broad age group (0-14, 15-29, 30-49, 50-64, 65-84 and 85+) as the sampling frame for the selection of migrants. Using the Q4 2021 and Q1 2022 migration data, we got the required inward and outward movers. The Population and Migration statistician provided the data at an individual level for our purposes. There are 63,780 inward migrators (53,403 in Q1 2022 and 10,377 taking one-third of the Q4 2021 values) and 25,730 outward migrators (19,779 in Q1 2022 and 5,951 taking one-third of the Q4 2021 values), see tables 5 to 7.

Then, using SAS procedure surveyselect, we selected, at random, the required number of inward and outward migrants per strata from the frame and sum over grid reference. Given that there will be more inward than outward migrants, the resulting figures will generally be negative i.e., the population will fall.

Ukrainian refugees There are no official statistics, but it was estimated that there were more than 23,000 Ukrainian refugees present in the State in April 3 2022. It is difficult to know the exact numbers captured by the Census until the full final dataset is available. Ukrainian refugees were to be counted as immigrants and usual residents (UR) on the census form unless an individual classed themselves as a visitor, in which case they were de facto (DF) residents. From the point of view of the procedure being described here, Ukrainians who are classified

This layer shows children by nativity of parents by age group. This is shown by tract, county, and state boundaries. This service is updated annually to contain the most currently released American Community Survey (ACS) 5-year data, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. This layer is symbolized to show the percentage of children who are in immigrant families (children who are foreign born or live with at least one parent who is foreign born). To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. Current Vintage: 2019-2023ACS Table(s): B05009Data downloaded from: Census Bureau's API for American Community Survey Date of API call: December 12, 2024National Figures: data.census.govThe United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. For more information about ACS layers, visit the FAQ. Please cite the Census and ACS when using this data.Data Note from the Census: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 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.Data Processing Notes:This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Click here to learn more about ACS data releases.Boundaries come from the US Census TIGER geodatabases, specifically, the National Sub-State Geography Database (named tlgdb_(year)_a_us_substategeo.gdb). Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For census tracts, the water cutouts are derived from a subset of the 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract level boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2023 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters). The States layer contains 52 records - all US states, Washington D.C., and Puerto RicoCensus tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. These negative values exist in the raw API data to indicate the following situations: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.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.The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.The estimate is controlled. A statistical test for sampling variability is not appropriate.The data for this geographic area cannot be displayed because the number of sample cases is too small.

The American Community Survey (ACS) is an ongoing survey that provides vital information on a yearly basis about our nation and its people. Information from the survey generates data that help determine how more than $400 billion in federal and state funds are distributed each year. Demographic variables include sex, age, relationship, households by type, race, and Hispanic origin. Social characteristics variables include school enrollment, educational attainment, marital status, fertility, grandparents caring for children, veteran status, disability status, residence one year ago, place of birth, United States citizenship status, year of entry, world region of birth of foreign born, language spoken at home, and ancestry. Variables focusing on economic characteristics include employment status, commuting to work, occupation, industry, class of worker, income and benefits, and poverty status. Variables focusing on housing characteristics include occupancy, units in structure, year structure was built, number of rooms, number of bedrooms, housing tenure, year householder moved into unit, vehicles available, house heating fuel, utility costs, occupants per room, housing value, and mortgage status. The American Community Survey is conducted under the authority of Title 13, United States Code, Sections 141 and 193, and response is mandatory

This layer shows place of birth by citizenship status. This is shown by tract, county, and state boundaries. This service is updated annually to contain the most currently released American Community Survey (ACS) 5-year data, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. This layer is symbolized to show the predominant area of birth among those who are foreign born. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. Current Vintage: 2019-2023ACS Table(s): B05002 (Not all lines of this ACS table are available in this feature layer.)Data downloaded from: Census Bureau's API for American Community Survey Date of API call: December 12, 2024National Figures: data.census.govThe United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. For more information about ACS layers, visit the FAQ. Please cite the Census and ACS when using this data.Data Note from the Census: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 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.Data Processing Notes:This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Click here to learn more about ACS data releases.Boundaries come from the US Census TIGER geodatabases, specifically, the National Sub-State Geography Database (named tlgdb_(year)_a_us_substategeo.gdb). Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For census tracts, the water cutouts are derived from a subset of the 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract level boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2023 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters).The States layer contains 52 records - all US states, Washington D.C., and Puerto RicoCensus tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. These negative values exist in the raw API data to indicate the following situations: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.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.The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.The estimate is controlled. A statistical test for sampling variability is not appropriate.The data for this geographic area cannot be displayed because the number of sample cases is too small.

Abstract The article compares income differentials of Bolivian and Northeastern workers in the State of São Paulo based on data from the 2010 Demographic Census. The strategy of comparing internal and international migrants is a way of trying to understand how mechanisms of selectivity, adaptation and discrimination by origin operate. Statistical models were used to control the analyses and to know if Bolivians and Northeastern people with characteristics as similar as possible in terms of census variables, would present a salary differential, leaving the place of birth as the only discriminant variable. From the decomposition of wage differentials, we verify that the productive attributes of these immigrants are valued differently. The analysis shows that Bolivians "do better" when compared to Northeasterners, who find themselves in a worse situation, given the lower valuation of their individual attributes.