This dataset contains model-based census tract level estimates for the PLACES 2022 release in GIS-friendly format. PLACES covers the entire United States—50 states and the District of Columbia (DC)—at county, place, census tract, and ZIP Code Tabulation Area levels. It provides information uniformly on this large scale for local areas at 4 geographic levels. Estimates were provided by the Centers for Disease Control and Prevention (CDC), Division of Population Health, Epidemiology and Surveillance Branch. PLACES was funded by the Robert Wood Johnson Foundation in conjunction with the CDC Foundation. Data sources used to generate these model-based estimates include Behavioral Risk Factor Surveillance System (BRFSS) 2020 or 2019 data, Census Bureau 2010 population estimates, and American Community Survey (ACS) 2015–2019 estimates. The 2022 release uses 2020 BRFSS data for 25 measures and 2019 BRFSS data for 4 measures (high blood pressure, taking high blood pressure medication, high cholesterol, and cholesterol screening) that the survey collects data on every other year. These data can be joined with the census tract 2015 boundary file in a GIS system to produce maps for 29 measures at the census tract level. An ArcGIS Online feature service is also available for users to make maps online or to add data to desktop GIS software. https://cdcarcgis.maps.arcgis.com/home/item.html?id=3b7221d4e47740cab9235b839fa55cd7
California is home to 12 percent of the nation's population yet accounts for more than 20 percent of the people living in the nation’s hardest-to-count areas, according to the United States Census Bureau (U.S. Census Bureau). California's unique diversity, large population distributed across both urban and rural areas, and sheer geographic size present significant barriers to achieving a complete and accurate count. The state’s population is more racially and ethnically diverse than ever before, with about 18 percent of Californians speaking English “less than very well,” according to U.S. Census Bureau estimates. Because the 2020 Census online form was offered in only twelve non-English languages, which did not correspond with the top spoken language in California, and a paper questionnaire only in English and Spanish, many Californians may not have been able to access a census questionnaire or written guidance in a language they could understand. In order to earn the confidence of California’s most vulnerable populations, it was critical during the 2020 Census that media and trusted messengers communicate with them in their primary language and in accessible formats. An accurate count of the California population in each decennial census is essential to receive its equitable share of federal funds and political representation, through reapportionment and redistricting. It plays a vital role in many areas of public life, including important investments in health, education, housing, social services, highways, and schools. Without a complete count in the 2020 Census, the State faced a potential loss of congressional seats and billions of dollars in muchneeded federal funding. An undercount of California in 1990 cost an estimated $2 billion in federal funding. The potential loss of representation and critically needed funding could have long-term impacts; only with a complete count does California receive the share of funding the State deserves with appropriate representation at the federal, state, and local government levels. The high stakes and formidable challenges made this California Complete Count Census 2020 Campaign (Campaign) the most important to date. The 2020 Census brought an unprecedented level of new challenges to all states, beyond the California-specific hurdles discussed above. For the first time, the U.S. Census Bureau sought to collect data from households through an online form. While the implementation of digital forms sought to reduce costs and increase participation, its immediate impact is still unknown as of this writing, and it may have substantially changed how many households responded to the census. In addition, conditions such as the novel Coronavirus (COVID-19) pandemic, a contentious political climate, ongoing mistrust and distrust of government, and rising concerns about privacy may have discouraged people to open their doors, or use computers, to participate. Federal immigration policy, as well as the months-long controversy over adding a citizenship question to the census, may have deterred households with mixed documentation status, recent immigrants, and undocumented immigrants from participating. In 2017, to prepare for the unique challenges of the 2020 Census, California leaders and advocates reflected on lessons learned from previous statewide census efforts and launched the development of a high-impact strategy to efficiently raise public awareness about the 2020 Census. Subsequently, the State established the California Complete Count – Census 2020 Office (Census Office) and invested a significant sum for the Campaign. The Campaign was designed to educate, motivate, and activate Californians to respond to the 2020 Census. It relied heavily on grassroots messaging and outreach to those least likely to fill out the census form. One element of the Campaign was the Language and Communication Access Plan (LACAP), which the Census Office developed to ensure that language and communication access was linguistically and culturally relevant and sensitive and provided equal and meaningful access for California’s vulnerable populations. The Census Office contracted with outreach partners, including community leaders and organizations, local government, and ethnic media, who all served as trusted messengers in their communities to deliver impactful words and offer safe places to share information and trusted messages. The State integrated consideration of hardest-to-count communities’ needs throughout the Campaign’s strategy at both the statewide and regional levels. The Campaign first educated, then motivated, and during the census response period, activated Californians to fill out their census form. The Census Office’s mission was to ensure that Californians get their fair share of resources and representation by encouraging the full participation of all Californians in the 2020 Census. This report focuses on the experience of the Census Office and partner organizations who worked to achieve the most complete count possible, presenting an evaluation of four outreach and communications strategies.
The American Community Survey (ACS) is a nationwide, continuous survey designed to provide communities with reliable and timely demographic, housing, social and economic data. The ACS replaces the decennial census long form in 2010 and every year thereafter. The annual ACS sample is smaller than that of previous long form surveys resulting in a larger sampling error. Coefficients of Variation (CVs), which are statistical measures that show the relative amount of sampling error associated with an estimate, are presented here as a measure of reliability and usability of the data. The unit of geography used for the 2010 - 2014 data is the census tract - a small statistical area within a county, which is delineated every 10 years prior to the decennial census.Last Updated: UnknownThis is a MD iMAP hosted service. Find more information at https://imap.maryland.gov.Feature Service Link:https://mdgeodata.md.gov/imap/rest/services/Demographics/MD_AmericanCommunitySurvey/FeatureServer/0
This dataset contains model-based census tract level estimates for the PLACES 2021 release in GIS-friendly format. PLACES is the expansion of the original 500 Cities project and covers the entire United States—50 states and the District of Columbia (DC)—at county, place, census tract, and ZIP Code Tabulation Area (ZCTA) levels. It represents a first-of-its kind effort to release information uniformly on this large scale for local areas at 4 geographic levels. Estimates were provided by the Centers for Disease Control and Prevention (CDC), Division of Population Health, Epidemiology and Surveillance Branch. PLACES was funded by the Robert Wood Johnson Foundation (RWJF) in conjunction with the CDC Foundation. Data sources used to generate these model-based estimates include Behavioral Risk Factor Surveillance System (BRFSS) 2019 or 2018 data, Census Bureau 2010 population estimates, and American Community Survey (ACS) 2015–2019 or 2014–2018 estimates. The 2021 release uses 2019 BRFSS data for 22 measures and 2018 BRFSS data for 7 measures (all teeth lost, dental visits, mammograms, cervical cancer screening, colorectal cancer screening, core preventive services among older adults, and sleeping less than 7 hours a night). Seven measures are based on the 2018 BRFSS data because the relevant questions are only asked every other year in the BRFSS. These data can be joined with the census tract 2015 boundary file in a GIS system to produce maps for 29 measures at the census tract level. An ArcGIS Online feature service is also available for users to make maps online or to add data to desktop GIS software. https://cdcarcgis.maps.arcgis.com/home/item.html?id=024cf3f6f59e49fe8c70e0e5410fe3cf
The 2010 Population and Housing Census was Conducted between 11-17 November 2010. Over 750,000 household forms were completed by over 12,000 enumerators. More than 30,000 persons were directly involved in census conducting. The Population and Housing Census is the biggest event organized by the National Statistical Office. The unique feature of the Census is that it covers a wide range of entities starting from the primary unit of the local government up to the highest levels of the government as well as all citizens and conducted with the highest levels of organization. For the 2010 Population and Housing Census, the management team to coordinate the preparatory work was established, a detailed work plan was prepared and the plan was successfully implemented. The preliminary condition for the successful conduct of the Census was the development of a detailed plan. The well thought-out, step by step plan and carefully evidenced estimation of the expenditure and expected results were crucial for the successful Census. Every stage of the Census including preparation, training, enumeration, data processing, analysis, evaluation and dissemination of the results to users should be reflected in the Census Plan.
National
Census/enumeration data [cen]
Face-to-face [f2f]
Data Processing System
The introduction of internet technology and GIS in the 2010 Population and Housing Census has made the census more technically advanced than the previous ones. Compared to the data processing of the 2000 Population and Housing Census the techniques and technological abilities of the NSO have advanced. The central office - National Statistical Office has used an internal network with 1000 Mbps speed, an independent internet line with 2048 Kbps speed and server computers with special equipments to ensure the reliable function of internal and external networks and confidentiality. The Law on Statistics, the Law on Population and Housing Census, the guidelines of the safety of statistical information systems and policies, the provisional guidelines on the use of census and survey raw data by the users, the guidelines on receiving, entering and validating census data have created a legal basis for census data processing.
The data-entry network was set up separately from the network of the organization in order to ensure the safety and confidentiality of the data. The network was organized by using the windows platform and managed by a separate domain controller. Computers where the census data will be entered were linked to this server computer and a safety devise was set up to protect data loss and fixing. Data backup was done twice daily at 15:10 hour and 22:10 hour by auto archive and the full day archive was stored in tape at 23:00 hour everyday.
The essential resources of important equipments and tools were prepared in order to provide continuous function of all equipment, to be able to carry out urgent repairs when needed, and to return the equipment to normal function. The computer where the census data would be entered and other necessary equipment were purchased by the state budget. For the data processing, the latest packages of software programs (CSPro, SPSS) were used. Also, software programs for the computer assisted coding and checking were developed on NET within the network framework.
INTERNET CENSUS DATA PROCESSING
One of the specific features of the 2010 Population and Housing Census was e-enumeration of Mongolian citizens living abroad for longer period. The development of a web based software and a website, and other specific measures were taken in line with the coordination of the General Authority for State Registration, the National Data Centre, and the Central Intelligence Agency in relation to ensuring the confidentiality of data. Some difficulties were encountered in sharing information between government agencies and ensuring the safety and confidentiality of census data due to limited professional and organizational experience, also because it was the first attempt to enumerate its citizens online.
The main software to be used for online registration, getting permission to get login and filling in the census questionnaire online as well as receiving a reply was developed by the NSO using a symphony framework and the web service was provided by the National Data Centre. Due to the different technological conditions for citizens living and working abroad and the lack of certain levels of technological knowledge for some people the diplomatic representative offices from Mongolia in different countries printed out the online-census questionnaire and asked citizens to fill in and deliver them to the NSO in Mongolia. During the data processing stage these filled in questionnaires were key-entered into the system and checked against the main census database to avoid duplication.
CODING OF DATA, DATA-ENTRY AND VALIDATION
Additional 136 workers were contracted temporarily to complete the census data processing and disseminate the results to the users within a short period of time. Due to limited work spaces all of them were divided into six groups and worked in two shifts with equipments set up in three rooms and connected to the network. A total of six team leaders and 130 operators worked on data processing. The census questionnaires were checked by the ad hoc bureau staff at the respective levels and submitted to the NSO according to the intended schedule.
These organizational measures were taken to ensure continuity of the census data processing that included stages of receiving the census documents, coding the questionnaire, key-entering into the system and validating the data. Coding was started on December 13, 2010 and the data-entry on January 7, 2011. Data entering of the post-enumeration survey and verification were completed by April 16, 2011. Data checking and validation started on April 18, 2011 and was completed on May 5, 2011. The automatic editing and imputation based on scripts written by the PHCB staff was completed on May 10, 2011 and the results tabulation was started.
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This is a MD iMAP hosted service. Find more information on http://imap.maryland.gov. The American Community Survey (ACS) is a nationwide - continuous survey designed to provide communities with reliable and timely demographic - housing - social and economic data. The ACS replaces the decennial census long form in 2010 and every year thereafter. The annual ACS sample is smaller than that of previous long form surveys resulting in a larger sampling error. Coefficients of Variation (CVs) - which are statistical measures that show the relative amount of sampling error associated with an estimate - are presented here as a measure of reliability and usability of the data. The unit of geography used for the 2009 - 2013 data is the census tract - a small statistical area within a county - which is delineated every 10 years prior to the decennial census. Map Service Link: http://archive.geodata.md.gov/imap/rest/services/ Demographics/MD_ArchivedAmericanCommunitySurvey/MapServer/2 ADDITIONAL LICENSE TERMS: The Spatial Data and the information therein (collectively "the Data") is provided "as is" without warranty of any kind either expressed implied or statutory. The user assumes the entire risk as to quality and performance of the Data. No guarantee of accuracy is granted nor is any responsibility for reliance thereon assumed. In no event shall the State of Maryland be liable for direct indirect incidental consequential or special damages of any kind. The State of Maryland does not accept liability for any damages or misrepresentation caused by inaccuracies in the Data or as a result to changes to the Data nor is there responsibility assumed to maintain the Data in any manner or form. The Data can be freely distributed as long as the metadata entry is not modified or deleted. Any data derived from the Data must acknowledge the State of Maryland in the metadata.
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Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, the decennial census is the official source of population totals for April 1st of each decennial year. In between censuses, the Census Bureau's Population Estimates Program produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units and the group quarters population for states and counties..Information about the American Community Survey (ACS) can be found on the ACS website. Supporting documentation including code lists, subject definitions, data accuracy, and statistical testing, and a full list of ACS tables and table shells (without estimates) can be found on the Technical Documentation section of the ACS website.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2023 American Community Survey 1-Year Estimates.ACS data generally reflect the geographic boundaries of legal and statistical areas as of January 1 of the estimate year. For more information, see Geography Boundaries by Year..Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..Users must consider potential differences in geographic boundaries, questionnaire content or coding, or other methodological issues when comparing ACS data from different years. Statistically significant differences shown in ACS Comparison Profiles, or in data users' own analysis, may be the result of these differences and thus might not necessarily reflect changes to the social, economic, housing, or demographic characteristics being compared. For more information, see Comparing ACS Data..One person in each household is designated as the householder. In most cases, this is the person or one of the people in whose name the home is owned, being bought, or rented and who is listed on line one of the survey questionnaire. If there is no such person in the household, any adult household member 15 years old and over could be designated as the householder.Households are classified by type according to the presence of relatives. Two types of householders are distinguished: a family householder and a nonfamily householder. A family householder is a householder living with one or more individuals related to him or her by birth, marriage, or adoption. The householder and all people in the household related to him or her are family members. A nonfamily householder is a householder living alone or with non-relatives only.To determine poverty status of a householder in family households, one compares the total income in the past 12 months of all family members with the poverty threshold appropriate for that family size and composition. If the total family income is less than the threshold, then the householder together with every member of his or her family are considered as having income below the poverty level.In determining poverty status of a nonfamily householder, only the householder's own personal income is compared with the appropriate threshold for a single person. The poverty status of a nonfamily householder does not affect the poverty status of the other unrelated individuals living in the household and the incomes of people living in the household who are not related to the householder are not considered when determining the poverty status of a householder. The income of each unrelated individual is compared to the appropriate threshold for a single person..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on 2020 Census data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution. For a 5-year median estimate, the margin of error associated with a median was larger than the median itself.N The estimate or margin of error can...
The Bureau of the Census has released Census 2000 Summary File 1 (SF1) 100-Percent data. The file includes the following population items: sex, age, race, Hispanic or Latino origin, household relationship, and household and family characteristics. Housing items include occupancy status and tenure (whether the unit is owner or renter occupied). SF1 does not include information on incomes, poverty status, overcrowded housing or age of housing. These topics will be covered in Summary File 3. Data are available for states, counties, county subdivisions, places, census tracts, block groups, and, where applicable, American Indian and Alaskan Native Areas and Hawaiian Home Lands. The SF1 data are available on the Bureau's web site and may be retrieved from American FactFinder as tables, lists, or maps. Users may also download a set of compressed ASCII files for each state via the Bureau's FTP server. There are over 8000 data items available for each geographic area. The full listing of these data items is available here as a downloadable compressed data base file named TABLES.ZIP. The uncompressed is in FoxPro data base file (dbf) format and may be imported to ACCESS, EXCEL, and other software formats. While all of this information is useful, the Office of Community Planning and Development has downloaded selected information for all states and areas and is making this information available on the CPD web pages. The tables and data items selected are those items used in the CDBG and HOME allocation formulas plus topics most pertinent to the Comprehensive Housing Affordability Strategy (CHAS), the Consolidated Plan, and similar overall economic and community development plans. The information is contained in five compressed (zipped) dbf tables for each state. When uncompressed the tables are ready for use with FoxPro and they can be imported into ACCESS, EXCEL, and other spreadsheet, GIS and database software. The data are at the block group summary level. The first two characters of the file name are the state abbreviation. The next two letters are BG for block group. Each record is labeled with the code and name of the city and county in which it is located so that the data can be summarized to higher-level geography. The last part of the file name describes the contents . The GEO file contains standard Census Bureau geographic identifiers for each block group, such as the metropolitan area code and congressional district code. The only data included in this table is total population and total housing units. POP1 and POP2 contain selected population variables and selected housing items are in the HU file. The MA05 table data is only for use by State CDBG grantees for the reporting of the racial composition of beneficiaries of Area Benefit activities. The complete package for a state consists of the dictionary file named TABLES, and the five data files for the state. The logical record number (LOGRECNO) links the records across tables.
https://hub.arcgis.com/api/v2/datasets/337f7661a706410f8994d76b9fde8e8c_1/licensehttps://hub.arcgis.com/api/v2/datasets/337f7661a706410f8994d76b9fde8e8c_1/license
Estimates of persons with disabilities or other support needs by Census tract in Washington State. DSHS prepared estimates of persons with disabilities or other support needs in Washington Census tracts using data from the US Census Bureau’s 2012 American Community Survey. The estimates were prepared for DSHS and the Washington Department of Health to assist in emergency preparedness planning for Washington jurisdictions.
Estimated counts, percentages, margins of error (MOEs) of counts and percentages by Census tract have been calculated for the following characteristics: Persons with Disabilities, Hearing Difficulty, Vision Difficulty, Cognitive Difficulty, Ambulatory Difficulty, Self-Care Difficulty, Independent Living Difficulty, Persons with Two or More Disabilities, Persons with Disabilities and in Poverty, Persons in Groups Quarters, Households Without Vehicles, Persons Speaking English less than "Very Well," Persons in Poverty.
The American Community Survey (ACS) is a nationwide, continuous survey designed to provide communities with reliable and timely demographic, housing, social and economic data. The ACS replaces the decennial census long form in 2010 and every year thereafter. The annual ACS sample is smaller than that of previous long form surveys resulting in a larger sampling error. Coefficients of Variation (CVs), which are statistical measures that show the relative amount of sampling error associated with an estimate, are presented here as a measure of reliability and usability of the data. The unit of geography used for the 2009 - 2013 data is the census tract - a small statistical area within a county, which is delineated every 10 years prior to the decennial census.This is a MD iMAP hosted service. Find more information on https://imap.maryland.gov.Feature Service Link: https://archive.geodata.md.gov/imap/rest/services/Demographics/MD_ArchivedAmericanCommunitySurvey/FeatureServer/2
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This is a MD iMAP hosted service. Find more information at http://imap.maryland.gov. The units of geography used for the 2010 Census maps displayed here are the Census tracts. Census tracts generally have a population size between 1 - 200 and 8 - 000 people - with an optimum size of 4 - 000 people. When first delineated - census tracts were designed to be homogeneous with respect to population characteristics - economic status - and living conditions. Census tract boundaries generally follow visible and identifiable features. State and county boundaries always are census tract boundaries in the standard census geographic hierarchy. In a few rare instances - a census tract may consist of noncontiguous areas. The data collected on the short form survey are general demographic characteristics such as age - race - ethnicity - household relationship - housing vacancy and tenure (owner/renter).Feature Service Link:https://mdgeodata.md.gov/imap/rest/services/Demographics/MD_CensusData/FeatureServer ADDITIONAL LICENSE TERMS: The Spatial Data and the information therein (collectively "the Data") is provided "as is" without warranty of any kind either expressed implied or statutory. The user assumes the entire risk as to quality and performance of the Data. No guarantee of accuracy is granted nor is any responsibility for reliance thereon assumed. In no event shall the State of Maryland be liable for direct indirect incidental consequential or special damages of any kind. The State of Maryland does not accept liability for any damages or misrepresentation caused by inaccuracies in the Data or as a result to changes to the Data nor is there responsibility assumed to maintain the Data in any manner or form. The Data can be freely distributed as long as the metadata entry is not modified or deleted. Any data derived from the Data must acknowledge the State of Maryland in the metadata.
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Analysis of ‘PLACES: Census Tract Data (GIS Friendly Format), 2020 release’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/36454ff3-3bd6-4626-8607-ed62ff3f4619 on 12 February 2022.
--- Dataset description provided by original source is as follows ---
This dataset contains model-based census tract level estimates for the PLACES project 2020 release in GIS-friendly format. The PLACES project is the expansion of the original 500 Cities project and covers the entire United States—50 states and the District of Columbia (DC)—at county, place, census tract, and ZIP Code tabulation Areas (ZCTA) levels. It represents a first-of-its kind effort to release information uniformly on this large scale for local areas at 4 geographic levels. Estimates were provided by the Centers for Disease Control and Prevention (CDC), Division of Population Health, Epidemiology and Surveillance Branch. The project was funded by the Robert Wood Johnson Foundation (RWJF) in conjunction with the CDC Foundation. Data sources used to generate these model-based estimates include Behavioral Risk Factor Surveillance System (BRFSS) 2018 or 2017 data, Census Bureau 2010 population estimates, and American Community Survey (ACS) 2014-2018 or 2013-2017 estimates. The 2020 release uses 2018 BRFSS data for 23 measures and 2017 BRFSS data for 4 measures (high blood pressure, taking high blood pressure medication, high cholesterol, and cholesterol screening). Four measures are based on the 2017 BRFSS data because the relevant questions are only asked every other year in the BRFSS. These data can be joined with the census tract 2015 boundary file in a GIS system to produce maps for 27 measures at the census tract level. An ArcGIS Online feature service is also available at https://www.arcgis.com/home/item.html?id=8eca985039464f4d83467b8f6aeb1320 for users to make maps online or to add data to desktop GIS software.
--- Original source retains full ownership of the source dataset ---
https://datafinder.stats.govt.nz/license/attribution-4-0-international/https://datafinder.stats.govt.nz/license/attribution-4-0-international/
Dataset contains life-cycle age group census usually resident population counts from the 2013, 2018, and 2023 Censuses, as well as the percentage change in the age group population counts between the 2013 and 2018 Censuses, and between the 2018 and 2023 Censuses. Data is available by regional council.
The life-cycle age groups are:
Map shows the percentage change in the census usually resident population count for life-cycle age groups between the 2018 and 2023 Censuses.
Download lookup file 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.
Footnotes
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.
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.
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).
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.
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.
Quality rating of a variable
The quality rating of a variable provides an overall evaluation of data quality for that variable, usually at the highest levels of classification. The quality ratings shown are for the 2023 Census unless stated. There is variability in the quality of data at smaller geographies. Data quality may also vary between censuses, for subpopulations, or when cross tabulated with other variables or at lower levels of the classification. Data quality ratings for 2023 Census variables has more information on quality ratings by variable.
Age concept quality rating
Age is rated as very high quality.
Age – 2023 Census: Information by concept has more information, for example, definitions and data quality.
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”.
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.
The American Community Survey (ACS) is a nationwide, continuous survey designed to provide communities with reliable and timely demographic, housing, social and economic data. The ACS replaces the decennial census long form in 2010 and every year thereafter. The annual ACS sample is smaller than that of previous long form surveys resulting in a larger sampling error. Coefficients of Variation (CVs), which are statistical measures that show the relative amount of sampling error associated with an estimate, are presented here as a measure of reliability and usability of the data. The unit of geography used for the 2010 - 2014 data is the ZIP Code Tabulation Area (ZCTA). ZCTAs are statistical geographic areas produced by the Census Bureau by aggregating census blocks to create generalized areas closely resembling the U.S. Postal Service's postal ZIP codes.Last Updated: UnknownThis is a MD iMAP hosted service. Find more information at https://imap.maryland.gov.Feature Service Link:https://mdgeodata.md.gov/imap/rest/services/Demographics/MD_AmericanCommunitySurvey/FeatureServer/1
Geolytics Census 2000 Long Form dataset. The Geolytics Census 2000 Long Form is a comprehensive source of detailed information about the people, housing, and economy of the United States. The Census 2000 Long Form offers the entire US Census Bureau's SF3 dataset. This dataset contains variables such as income, housing, employment, language spoken, ancestry, education, poverty, rent, mortgage, commute to work, etc. There are 5,500 variables at the Block Group level. A select portion of the Geolytics Census data was joined to GDT spatial data by block group and some census attributes were aggregated. See the attached txt file for a description of the attributes. 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.
https://search.gesis.org/research_data/datasearch-httpwww-da-ra-deoaip--oaioai-da-ra-de465399https://search.gesis.org/research_data/datasearch-httpwww-da-ra-deoaip--oaioai-da-ra-de465399
Abstract (en): To reduce respondent burden for the 2013 collection, the Census of Jails was combined with the Deaths in Custody Reporting Program (DCRP). The census provides the sampling frame for the nationwide Survey of Inmates in Local Jails (SILJ) and the Annual Survey of Jails (ASJ). Previous jail enumerations were conducted in 1970 (ICPSR 7641), 1972 (ICPSR 7638), 1978 (ICPSR 7737), 1983 (ICPSR 8203), 1988 (ICPSR 9256), 1993 (ICPSR 6648), 1999 (ICPSR 3318), 2005 (ICPSR 20367), and 2006 (ICPSR 26602). The RTI International collected the data for the Bureau of Justice Statistics in 2013. The United States Census Bureau was the collection agent from 1970-2006. The 2013 Census of Jails gathered data from all jail detention facilities holding inmates beyond arraignment, a period normally exceeding 72 hours. Jail facilities were operated by cities and counties, by private entities under contract to correctional authorities, and by the Federal Bureau of Prisons (BOP). Excluded from the census were physically separate temporary holding facilities such as drunk tanks and police lockups that do not hold persons after being formally charged in court. Also excluded were state-operated facilities in Connecticut, Delaware, Hawaii, Rhode Island, Vermont, and Alaska, which have combined jail-prison systems. Fifteen independently operated jails in Alaska were included in the Census. The 2013 census collected facility-level information on the number of confined and nonconfined inmates, number of inmates participating in weekend programs, number of confined non-U.S. citizens, number of confined inmates by sex and adult or juvenile status, number of juveniles held as adults, conviction and sentencing status, offense type, number of inmates held by race or Hispanic origin, number of inmates held for other jurisdictions or authorities, average daily population, rated capacity, number of admissions and releases, program participation for nonconfined inmates, operating expenditures, and staff by occupational category. 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.; Standardized missing values.; Performed recodes and/or calculated derived variables.; Checked for undocumented or out-of-range codes.. Datasets:DS1: Census of Jails, 2013 All locally, regionally, and federally administered jails in the United States. The respondent universe was derived from a facility list maintained by the Census Bureau for BJS, from correctional association directories, and from other secondary sources. Census forms were sent to each jail jurisdiction. In addition to a paper form, BJS offered respondents an electronic version via the internet, allowing them to complete and submit their completed questionnaires on-line. 2018-04-25 The dataset and the codebook have been updated2016-03-25 Two records needed to be updated. Funding insitution(s): United States Department of Justice. Office of Justice Programs. Bureau of Justice Statistics. mail questionnaire web-based survey
The Community Life Survey is a nationally representative annual survey of adults (16+) in England that tracks the latest trends and developments across areas that are key to encouraging social action and empowering communities. Data collection on the Community Life Survey commenced in 2012/13 using a face-to-face format. During the survey years from 2013/14 to 2015/16 a push-to-web format was tested, which included collecting online/paper data alongside the face-to-face data, before moving fully to a push-to-web format in 2016/17. The results included in this release are based on online/paper completes only, covering the ten survey years from 2013/14, when this method was first tested, to 2023/24.
In 2023/24, DCMS partnered with the Ministry of Housing, Communities and Local Government (MHCLG) to boost the Community Life Survey to be able to produce meaningful estimates at the local authority level. This has enabled us to have the most granular data we have ever had. The questionnaire for 2023/24 has been developed collaboratively to adapt to the needs and interests of both DCMS and MHCLG, and there were some new questions and changes to existing questions, response options and definitions in the 23/24 survey.
In 2023/24 we collected data on the respondent’s sex and gender identity. Please note that patterns were identified in Census 2021 data that suggest that some respondents may not have interpreted the gender identity question as intended, notably those with lower levels of English language proficiency. https://www.scotlandscensus.gov.uk/2022-results/scotland-s-census-2022-quality-assurance-reports/quality-assurance-report-sexual-orientation-and-trans-status-or-history/" class="govuk-link">Analysis of Scotland’s census, where the gender identity question was different, has added weight to this observation. More information can be found in the ONS https://www.ons.gov.uk/peoplepopulationandcommunity/culturalidentity/sexuality/methodologies/sexualorientationandgenderidentityqualityinformationforcensus2021" class="govuk-link">sexual orientation and gender identity quality information report, and in the National Statistical https://blog.ons.gov.uk/2024/09/12/better-understanding-the-strengths-and-limitations-of-gender-identity-statistics/" class="govuk-link">blog about the strengths and limitations of gender identity statistics.
Fieldwork for 2023/24 was delivered over two quarters (October to December 2023 and January to March 2024) due to an extended period earlier in 2023/24 to develop and implement the boosted design. As such there are two quarterly publications in 2023/24, in addition to the annual publication.
This release is the second and final quarterly publication from the 2023/24 Community Life Survey, providing estimates reported during the period of January to March 2024. The quarterly releases contain headline findings only and do not contain geographical or demographic breakdowns – this detail is published through the 2023/24 annual publication.
Released: 4 December 2024
Period covered: January to March 2024
Geographic coverage: National level data for England
Next release date: Spring 2025
The pre-release access list above contains the ministers and officials who have received privileged early access to this release of Community Life Survey data. In line with best-practice, the list has been kept to a minimum and those given access for briefing purposes had a maximum of 24 hours. Details on the pre-release access arrangements for this dataset are available in the accompanying material.
Our statistical practice is regulated by the Office for Statistics Regulation (OSR). OSR sets the standards of trustworthiness, quality and value in the https://code.statisticsauthority.gov.uk/the-code/" class="govuk-link">Code of Practice for Statistics that all producers of official statistics should adhere to.
You are welcome to contact us directly with any comments about how we meet these standards by emailing evidence@dcms.gov.uk. Alternatively, you can contact OSR by emailing regulation@statistics.gov.uk or via the <a rel="external" href="https://osr.statisticsauthority.gov.uk/
Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
License information was derived automatically
This dataset provides Census 2021 estimates that classify usual residents aged three and over in Northern Ireland by their main language. The estimates are as at census day, 21 March 2021. The main language classification used is a 19-category classification corresponding to the tick box options and write-in responses on the census questionnaire with at least 1,000 responses.
The census collected information on the usually resident population of Northern Ireland on census day (21 March 2021). Initial contact letters or questionnaire packs were delivered to every household and communal establishment, and residents were asked to complete online or return the questionnaire with information as correct on census day. Special arrangements were made to enumerate special groups such as students, members of the Travellers Community, HM Forces personnel etc. The Census Coverage Survey (an independent doorstep survey) followed between 12 May and 29 June 2021 and was used to adjust the census counts for under-enumeration.
U.S. Government Workshttps://www.usa.gov/government-works
License information was derived automatically
This is a MD iMAP hosted service. Find more information at http://imap.maryland.gov. The American Community Survey (ACS) is a nationwide - continuous survey designed to provide communities with reliable and timely demographic - housing - social and economic data. The ACS replaces the decennial census long form in 2010 and every year thereafter. The annual ACS sample is smaller than that of previous long form surveys resulting in a larger sampling error. Coefficients of Variation (CVs) - which are statistical measures that show the relative amount of sampling error associated with an estimate - are presented here as a measure of reliability and usability of the data. The unit of geography used for the 2010 - 2014 data is the ZIP Code Tabulation Area (ZCTA). ZCTAs are statistical geographic areas produced by the Census Bureau by aggregating census blocks to create generalized areas closely resembling the U.S. Postal Service's postal ZIP codes.Feature Service Link:https://mdgeodata.md.gov/imap/rest/services/Demographics/MD_AmericanCommunitySurvey/FeatureServer ADDITIONAL LICENSE TERMS: The Spatial Data and the information therein (collectively "the Data") is provided "as is" without warranty of any kind either expressed implied or statutory. The user assumes the entire risk as to quality and performance of the Data. No guarantee of accuracy is granted nor is any responsibility for reliance thereon assumed. In no event shall the State of Maryland be liable for direct indirect incidental consequential or special damages of any kind. The State of Maryland does not accept liability for any damages or misrepresentation caused by inaccuracies in the Data or as a result to changes to the Data nor is there responsibility assumed to maintain the Data in any manner or form. The Data can be freely distributed as long as the metadata entry is not modified or deleted. Any data derived from the Data must acknowledge the State of Maryland in the metadata.