Abstract

The census date was midnight, the 23rd of July 2018.

The Census is the official count of population, household and dwellings in Wallis & Futuna and it gives a general overview of the country at one specific point in time: 23rd of July 2018. Since 1969 until 2003, Census has been taken once in every 7 or 6 years and every 5 years from 2003.

The census can be the source of information for allocation of public funding, more particularly in areas such as health, education and social policy. The main users of the information provided by the Census are the government, education facilities (such as schools and tertiary organizations), local authorities, businesses, community organizations and the public in general.

The objectives of Census changed over time shifting from earlier years where they were essentially household registrations and counts, to now where a national population census stands supreme as the most valuable single source of statistical data for Wallis & Futuna. This Census allowed to determine the legal population of Wallis and Futuna in all geographical aspects: Wallis island, Futuna island, the 3 "circonsriptions" (Alo, Sigave, Uvea) and 5 districts (Alo, Sigave, Hahake, Hihifo, Mua).

Census data is now widely used to evaluate: - The availability of basic household needs in key sectors, to identify disadvantaged areas and help set priorities for action plans; - Benefits of development programmes in particular areas, such as literacy, employment and family planning;

In addition, census data is useful to asses manpower resources, identify areas of social concern and for the improvement in the social and economic status of women by giving more information about this part of the population and formulating housing policies and programmes and investment of development funds.

Geographic coverage

National coverage.

Analysis unit

Households and Individuals.

Universe

The Census is covering all people alive on the reference date (23rd of July 2018), that are usually living in Wallis and Futuna - whichever nationality they are, for at least 12 months. The Census covered all household and communitiy members. Communities are considered to be: boarding schools, gendarmerie, retirement homes, religious communities, but also people living in mobile dwelling (e.g. boats) and homeless people.

Kind of data

Census/enumeration data [cen]

Sampling procedure

Not applicable as it is a full coverage.

Mode of data collection

Face-to-face [f2f]

Research instrument

There are two types of questionnaire for this Census:

Individual sheet (Feuille de Logement or "FL"): describing the dwelling characteristics and enlisting all the individuals living in it; Individual form (Bulletin Individuel or "BI"): information on each individual that are usually living in the household.

The questionnaires were distributed in French and are available in the "External Resources" section.

Cleaning operations

Data editing was done by SPC in collaboration with Wallis and Futuna NSO.

Sampling error estimates

Not applicable.

About this dataset

Context

The dataset tabulates the Day town population distribution across 18 age groups. It lists the population in each age group along with the percentage population relative of the total population for Day town. The dataset can be utilized to understand the population distribution of Day town by age. For example, using this dataset, we can identify the largest age group in Day town.

Key observations

The largest age group in Day, New York was for the group of age 60 to 64 years years with a population of 154 (18.16%), according to the ACS 2019-2023 5-Year Estimates. At the same time, the smallest age group in Day, New York was the 5 to 9 years years with a population of 3 (0.35%). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 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

Variables / Data Columns

• Age Group: This column displays the age group in consideration
• Population: The population for the specific age group in the Day town is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of Day town total population. Please note that the sum of all percentages may not equal one due to rounding of values.

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

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

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 Day town Population by Age. You can refer the same here

The Department of Health requires nursing homes to complete electronic filing of each facility's licensed nursing home beds and availability by bed category on a weekly basis. All nursing homes are requested to submit their Weekly Bed Census between Wednesday and Friday of each week, based on the census at 12:00 AM on Wednesday night.

The Nursing Home Census- Historic data is the most comprehensive nursing home data available and is suitable for trending.

Available Bed and Occupancy information is self-reported, and is not audited by the NYSDOH.

For more information, check out http://nursinghomes.nyhealth.gov/, or go to the "About" tab.

Census 2021 data of the industry of people’s last main job who were not employed on census day. This dataset is at the division level of the Standard Industrial Classification.

As included in this EnviroAtlas dataset, the community-level domestic water use is calculated using locally available water use data per capita in gallons of water per day (GPD), distributed dasymetrically, and summarized by census block group. Domestic water use, as defined in this case, is intended to represent residential indoor and outdoor water use (e.g., cooking, hygiene, landscaping, pools, etc.) for primary residences (i.e., excluding second homes and tourism rentals). Water use estimates within the EnviroAtlas-defined Cleveland study area range from 42 to 109 GPD. They were derived through a normalized, weighted average of estimates of publicly-supplied and self-supplied water use by county from the U.S. Geological Survey (USGS). This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

Census 2021 data outlining the employment history of those not in employment on census day, including estimates by personal characteristics and reason for not being employed.

See other items

Census 2021 data outlining the occupation of the last main job of those who were not employed on census day. This data is at the four-digit level of the Standard Occupational Classification.

About this dataset

Context

The dataset tabulates the John Day population distribution across 18 age groups. It lists the population in each age group along with the percentage population relative of the total population for John Day. The dataset can be utilized to understand the population distribution of John Day by age. For example, using this dataset, we can identify the largest age group in John Day.

Key observations

The largest age group in John Day, OR was for the group of age 5 to 9 years years with a population of 138 (8.94%), according to the ACS 2019-2023 5-Year Estimates. At the same time, the smallest age group in John Day, OR was the Under 5 years years with a population of 11 (0.71%). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 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

Variables / Data Columns

• Age Group: This column displays the age group in consideration
• Population: The population for the specific age group in the John Day is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of John Day total population. Please note that the sum of all percentages may not equal one due to rounding of values.

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

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

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 John Day Population by Age. You can refer the same here

As included in this EnviroAtlas dataset, the community domestic water use was calculated using locally available water use data per capita in gallons of water per day (GPD), distributed dasymetrically, and summarized by census block group. Domestic water use, as defined in this case, is intended to represent residential indoor and outdoor water use (e.g., cooking, hygiene, landscaping, pools, etc.) for primary residences (i.e., excluding second homes and tourism rentals). For the purposes of this metric, these publicly-supplied estimates are also considered representative of local self-supplied water use. Specific to Durham, NC, the Division of Water Resources (DWR), part of the North Carolina Department of Natural Resources (NCDENR), has made local water supply plans centrally available online. All local governments are required to provide public water service. Community water systems with 1,000+ service connections or 3,000+ residents are required to prepare a local water supply plan. These plans include residential, also known as domestic, water usage. To account for variations due to weather, a ten-year average was calculated for Durham, Hillsborough, and the Orange Water and Sewer Authority (OWASA), which supplies southeast Orange County, including Chapel Hill and Carrboro. The ten-year average included available data between 2000 and 2010. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

Graph and download economic data for Total Expenses for Child Day Care Services, Establishments Exempt from Federal Income Tax (EXP6244TAXEPT144QNSA) from Q1 2009 to Q1 2025 about tax exempt, day care, establishments, tax, expenditures, federal, child, income, and USA.

As included in this EnviroAtlas dataset, the community level domestic water use is calculated using locally available water use data per capita in gallons of water per day (GPD), distributed dasymetrically, and summarized by census block group. Domestic water use, as defined in this case, is intended to represent residential indoor and outdoor water use (e.g., cooking hygiene, landscaping, pools, etc.) for primary residences (i.e., excluding second homes and tourism rentals). For the purposes of this metric, these publicly-supplied estimates are also applied and considered representative of local self-supplied water use. Water utility service reporting in the EnviroAtlas-defined study area is available through the Public Service Commission of Wisconsin (http://psc.wi.gov/). Within the Green Bay boundary, there are seven service providers with 2008-2013 estimates ranging from 36 to 48 GPD. This dataset was produced by the U.S. EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets ).

As included in this EnviroAtlas dataset, the community level domestic water use is calculated using locally available water use data per capita in gallons of water per day (GPD), distributed dasymetrically, and summarized by census block group. Domestic water use, as defined in this case, is intended to represent residential indoor and outdoor water use (e.g., cooking hygiene, landscaping, pools, etc.) for primary residences (i.e., excluding second homes and tourism rentals). For the purposes of this metric, these publicly-supplied estimates are also applied and considered representative of local self-supplied water use. Residential Gallons per Capita per Day (RGPCD) in the EnviroAtlas-defined study area is available through the Commonwealth of Massachusetts' (mass.gov). Within the New Bedford boundary, there are five service providers with 2008-2013 estimates ranging from 45 to 76 GPD.This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

As included in this EnviroAtlas dataset, the community level domestic water use is calculated using locally available water use data per capita in gallons of water per day (GPD), distributed dasymetrically, and summarized by census block group. Domestic water use, as defined in this case, is intended to represent residential indoor and outdoor water use (e.g., cooking, hygiene, landscaping, pools, etc.) for primary residences (i.e., excluding second homes and tourism rentals). Two reports were used with city- or water supply authority- level domestic water demand data, in addition to county level data. The 2013 Jefferson County Data Book provides detailed publicly, privately, and self supplied water use and population served for 2013 and covers the Jefferson County, MO portion of the EnviroAtlas study area. The 2019 Census of Missouri Public Water Systems provides detailed publicly supplied water use and population served for 2019 and covers all of Missouri. The 2010 USGS Estimated Use of Water in the United States in 2010 report covers the missing areas, including counties in Illinois within the study area. Data from these reports were weighted across publicly, privately, and self-supplied sources by population served, resulting in a single water use estimate between 25 and 427 GPD for each of the subregions in the study area. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

Office for National Statistics' national and subnational Census 2021. Schoolchildren and full-time studentsThis dataset provides Census 2021 estimates that classify all usual residents aged 5 years and over in England and Wales. The estimates are as at Census Day, 21 March 2021. Schoolchild or full-time student indicator definition: Indicates whether a person aged 5 years and over was in full-time education on Census Day, 21 March 2021. This includes schoolchildren and adults in full-time education.Schoolchildren and students in full-time education studying away from home are treated as usually resident at their term-time address.Comparability with 2011: Broadly comparable.We have removed the category Schoolchild or full-time student for Census 2021 and replaced it with Student. In the 2011 Census people aged 4 years and over were asked to answer the question, in Census 2021 people aged 5 years and over were asked to answer the question. This data is issued at (BGC) Generalised (20m) boundary type for:Country - England and WalesRegion - EnglandUTLA - England and WalesLTLA - England and WalesWard - England and WalesMSOA - England and WalesLSOA - England and WalesOA - England and WalesIf you require the data at full resolution boundaries, or if you are interested in the range of statistical data that Esri UK make available in ArcGIS Online please enquire at content@esriuk.com.The data services available from this page are derived from the National Data Service. The NDS delivers thousands of open national statistical indicators for the UK as data-as-a-service. Data are sourced from major providers such as the Office for National Statistics, Public Health England and Police UK and made available for your area at standard geographies such as counties, districts and wards and census output areas. This premium service can be consumed as online web services or on-premise for use throughout the ArcGIS system.Read more about the NDS.

As included in this EnviroAtlas dataset, the community domestic water use was calculated using local domestic water use per capita in gallons of water per day (GPD), distributed dasymetrically, and summarized by census block group. Domestic water use, as defined in this case, is intended to represent residential indoor and outdoor water use (e.g., cooking, hygiene, landscaping, pools, etc) for primary residences (i.e., excluding second homes and tourism rentals). For the purposes of this metric, these provider-supplied estimates are also considered representative of local self-supplied water use. Specific to Portland, ME, the Portland Water District (PWD) is the main provider for the study area. Within the study area, PWD supports Portland, South Portland, Westbrook, Scarborough, and Cape Elizabeth. PWD estimates current residential water use to be ~52 GPD. The southern portion of the study area is supported by the Biddeford and Saco Water Company (BSWC). Within the study area, their service area includes Biddeford, Saco, Old Orchard Beach, and Pine Point. BSWC estimates current residential water usage to be ~50 GPD. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets ).

Abstract

IPUMS-International is an effort to inventory, preserve, harmonize, and disseminate census microdata from around the world. The project has collected the world's largest archive of publicly available census samples. The data are coded and documented consistently across countries and over time to facillitate comparative research. IPUMS-International makes these data available to qualified researchers free of charge through a web dissemination system.

The IPUMS project is a collaboration of the Minnesota Population Center, National Statistical Offices, and international data archives. Major funding is provided by the U.S. National Science Foundation and the Demographic and Behavioral Sciences Branch of the National Institute of Child Health and Human Development. Additional support is provided by the University of Minnesota Office of the Vice President for Research, the Minnesota Population Center, and Sun Microsystems.

Geographic coverage

National coverage

Analysis unit

Household

UNITS IDENTIFIED: - Dwellings: No - Households: Yes - Group quarters: Included in microdata without identification

UNIT DESCRIPTIONS: - Group quarters: Group quarters consist of schools/colleges, barracks, prisons, hospitals and other institutions.

Universe

All persons present in Kenya on the reference date.

Kind of data

Census/enumeration data [cen]

Sampling procedure

MICRODATA SOURCE: Constructed by census agency. Microdata files dated September 9, 2001.

SAMPLE DESIGN: Systematic sample of every twentieth household.

SAMPLE FRACTION: 5%

SAMPLE UNIVERSE: The current version of the microdata sample excludes travelers and vagrants.

SAMPLE SIZE (person records): 1,407,547

Mode of data collection

Face-to-face [f2f]

Research instrument

A long form was used to enumerate individuals in private households and in institutions such as schools, colleges, barracks, prisons, and hospitals. The long form includes both individual and housing characteristics. A greatly abbreviated form was used for persons in transit or who slept outdoors, in hotels or boarding houses.

Response rate

UNDERCOUNT: No official estimate

Abstract

IPUMS-International is an effort to inventory, preserve, harmonize, and disseminate census microdata from around the world. The project has collected the world's largest archive of publicly available census samples. The data are coded and documented consistently across countries and over time to facillitate comparative research. IPUMS-International makes these data available to qualified researchers free of charge through a web dissemination system.

The IPUMS project is a collaboration of the Minnesota Population Center, National Statistical Offices, and international data archives. Major funding is provided by the U.S. National Science Foundation and the Demographic and Behavioral Sciences Branch of the National Institute of Child Health and Human Development. Additional support is provided by the University of Minnesota Office of the Vice President for Research, the Minnesota Population Center, and Sun Microsystems.

Geographic coverage

National coverage

Analysis unit

Dwelling

UNITS IDENTIFIED: - Dwellings: No - Vacant units: No - Households: Yes - Individuals: Yes - Group quarters: Yes

UNIT DESCRIPTIONS: - Dwellings: Place where people reside. - Households: That collectivity composed of one or several people, whether bound by kinship or not, living in the same house or in a portion of the same house, sharing in the provision of service or in the management of the household, who do not separate their income and expenses among themselves. People lacking a kinship bond among themselves, but who live together on a continuous basis for various reasons and make no distinction among themselves in terms of their expenses and earnings, are considered to be households. - Group quarters: Military barracks, jails, hospitals, clinics, boarding schools, prisons, transit stations, factories, embassies.

Universe

The total population within the boundaries of the country on the day of enumeration at localities where they were physically present on the census day.

Kind of data

Census/enumeration data [cen]

Sampling procedure

MICRODATA SOURCE: State Institute of Statistics of Turkey

SAMPLE DESIGN: Systematic random sampling by province

SAMPLE UNIT: Households, otherwise individuals if enumerated in non-household places on census day.

SAMPLE FRACTION: 5%

SAMPLE SIZE (person records): 2,817,455

Mode of data collection

Face-to-face [f2f]

Research instrument

Single form with 4 sections: address information, dwelling type information, household questions, and personal characteristics.

See other items

Abstract

The 2000 Republic of Palau Census of Population and Housing was the second census collected and processed entirely by the republic itself. This monograph provides analyses of data from the most recent census of Palau for decision makers in the United States and Palau to understand current socioeconomic conditions. The 2005 Census of Population and Housing collected a wide range of information on the characteristics of the population including demographics, educational attainments, employment status, fertility, housing characteristics, housing characteristics and many others.

Geographic coverage

National

Analysis unit

• Household;
• Individual.

Universe

The 1990, 1995 and 2000 censuses were all modified de jure censuses, counting people and recording selected characteristics of each individual according to his or her usual place of residence as of census day. Data were collected for each enumeration district - the households and population in each enumerator assignment - and these enumeration districts were then collected into hamlets in Koror, and the 16 States of Palau.

Kind of data

Census/enumeration data [cen]

Sampling procedure

No sampling - whole universe covered

Mode of data collection

Face-to-face [f2f]

Research instrument

The 2000 censuses of Palau employed a modified list-enumerate procedure, also known as door-to-door enumeration. Beginning in mid-April 2000, enumerators began visiting each housing unit and conducted personal interviews, recording the information collected on the single questionnaire that contained all census questions. Follow-up enumerators visited all addresses for which questionnaires were missing to obtain the information required for the census.

Cleaning operations

The completed questionnaires were checked for completeness and consistency of responses, and then brought to OPS for processing. After checking in the questionnaires, OPS staff coded write-in responses (e.g., ethnicity or race, relationship, language). Then data entry clerks keyed all the questionnaire responses. The OPS brought the keyed data to the U.S. Census Bureau headquarters near Washington, DC, where OPS and Bureau staff edited the data using the Consistency and Correction (CONCOR) software package prior to generating tabulations using the Census Tabulation System (CENTS) package. Both packages were developed at the Census Bureau's International Programs Center (IPC) as part of the Integrated Microcomputer Processing System (IMPS).

The goal of census data processing is to produce a set of data that described the population as clearly and accurately as possible. To meet this objective, crew leaders reviewed and edited questionnaires during field data collection to ensure consistency, completeness, and acceptability. Census clerks also reviewed questionnaires for omissions, certain inconsistencies, and population coverage. Census personnel conducted a telephone or personal visit follow-up to obtain missing information. The follow-ups considered potential coverage errors as well as questionnaires with omissions or inconsistencies beyond the completeness and quality tolerances specified in the review procedures.

Following field operations, census staff assigned remaining incomplete information and corrected inconsistent information on the questionnaires using imputation procedures during the final automated edit of the data. The use of allocations, or computer assignments of acceptable data, occurred most often when an entry for a given item was lacking or when the information reported for a person or housing unit on an item was inconsistent with other information for that same person or housing unit. In all of Palau’s censuses, the general procedure for changing unacceptable entries was to assign an entry for a person or housing unit that was consistent with entries for persons or housing units with similar characteristics. The assignment of acceptable data in place of blanks or unacceptable entries enhanced the usefulness of the data.

Sampling error estimates

Human and machine-related errors occur in any large-scale statistical operation. Researchers generally refer to these problems as non-sampling errors. These errors include the failure to enumerate every household or every person in a population, failure to obtain all required information from residents, collection of incorrect or inconsistent information, and incorrect recording of information. In addition, errors can occur during the field review of the enumerators' work, during clerical handling of the census questionnaires, or during the electronic processing of the questionnaires. To reduce various types of non-sampling errors, Census office personnel used several techniques during planning, data collection, and data processing activities. Quality assurance methods were used throughout the data collection and processing phases of the census to improve the quality of the data.

Census staff implemented several coverage improvement programs during the development of census enumeration and processing strategies to minimize under-coverage of the population and housing units. A quality assurance program improved coverage in each census. Telephone and personal visit follow-ups also helped improve coverage. Computer and clerical edits emphasized improving the quality and consistency of the data. Local officials participated in post-census local reviews. Census enumerators conducted additional re-canvassing where appropriate.