The 1940 Census population schedules were created by the Bureau of the Census in an attempt to enumerate every person living in the United States on April 1, 1940, although some persons were missed. The 1940 census population schedules were digitized by the National Archives and Records Administration (NARA) and released publicly on April 2, 2012. The 1940 Census enumeration district maps contain maps of counties, cities, and other minor civil divisions that show enumeration districts, census tracts, and related boundaries and numbers used for each census. The coverage is nation wide and includes territorial areas. The 1940 Census enumeration district descriptions contain written descriptions of census districts, subdivisions, and enumeration districts.

Post-Enumeration Survey estimates of net coverage error and components of census coverage for the 2020 Census.

Prewar Neighborhoods Dataset - historical census data from St. Louis 1920. Uploaded from https://www.allisonshertzer.com/data/

This data collection contains the MEDList file, the geographic reference file for the 1970 Census containing records for states, counties, minor civil divisions (MCD) or census county divisions (CCD)s, place segments, enumeration districts, and block groups. Items include state code, county code, MCD/CCD code, place code, place type, standard consolidated area code, standard metropolitan statistical area (SMSA) code, urbanized area code, tracted area code, state economic area code, economic subregion code, central business district code, area name, tract code, block group code, enumeration district code, urban/rural classification, ward code, congressional district code, housing count, and population count.

X Not applicable.Z Represents or rounds to zero.DSE: Dual-system estimate.A negative (positive) estimate of net coverage error indicates an undercount (overcount)..Standard errors are in parentheses below the estimate..Source: U.S. Census Bureau, Decennial Statistical Studies Division, 2020 Post-Enumeration Survey (March 2022 Release).Post-Enumeration Survey estimates are subject to sampling and nonsampling errors. For information regarding data collection, definitions, sampling error, nonsampling error, and estimation methodology, see: Post-Enumeration Surveys.

Analysis unit

Persons Persons not organized into households

UNITS IDENTIFIED: - Dwellings: no - Vacant Units: no - Households: no - Individuals: yes - Group quarters: no

UNIT DESCRIPTIONS: - Dwellings: Separated space with independent access that serves as a human lodging - Households: Individuals living in the same dwelling and sharing at least one meal. If a household is identified within a group quarters unit, it is enumerated separately as a private household - Group quarters: Group of persons who share a common roof and food because of work, health, religion, etc.

Universe

Population census included people in territories, sailors, diplomats and their families. The indigenous population residing in remote areas was not enumerated. People in transit included in microdata sample

Kind of data

Population and Housing Census [hh/popcen]

Sampling procedure

MICRODATA SOURCE: Departmento Administrativo Nacional de Estadística (DANE)

SAMPLE SIZE (person records): 349652.

SAMPLE DESIGN: Systematic sample of every 50th individual after a random start. Drawn by DANE from the original census enumeration forms. People in transit included in microdata sample

Mode of data collection

Face-to-face [f2f]

Research instrument

A single form was used for the entire country. It requested information about buildings, dwellings, households and individuals.

This dataset contains enumeration area level data for the following topics: census families, dwellings, education, ethnic origin, households, immigration, income, language, mother tongue, population, and religion.

A negative (positive) estimate of net coverage error indicates an undercount (overcount)..Source: U.S. Census Bureau, Decennial Statistical Studies Division, 2020 Post-Enumeration Survey (March 2022 Release).Post-Enumeration Survey estimates are subject to sampling and nonsampling errors. For information regarding data collection, definitions, sampling error, nonsampling error, and estimation methodology, see: Post-Enumeration Surveys.

A negative (positive) estimate of net coverage error indicates an undercount (overcount)..Source: U.S. Census Bureau, Decennial Statistical Studies Division, 2020 Post-Enumeration Survey (August 2022 Release).Post-Enumeration Survey estimates are subject to sampling and nonsampling errors. For information regarding data collection, definitions, sampling error, nonsampling error, and estimation methodology, see: Post-Enumeration Surveys.

Abstract

The main aim and objectives of the census is to provide benchmark statistics and a comprehensive profile of the population and households of Niue at a given time. This information obtained from the census is very crucial and useful in providing evidence to decision making and policy formulation for the Government, Business Community, Local Communities or Village Councils, Non Government Organisations of Niue and The International Communities who have an interest in Niue and its people.

Geographic coverage

National Coverage

Analysis unit

A Population and Household Census have the following units of analysis: - Households - Individuals/Persons - Members Overseas

Universe

All households in Niue and all persons in the household including those temporarily overseas and those absent for not more than 12 months.

Kind of data

Census/enumeration data [cen]

Sampling procedure

Not Applicable to a complete Enumeration Census.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionaire was published in English, a translated questionnaire was on hand when on demand by the respondent.

The questionnaire design differed slightly from the design of previous census questionnaires. As usual, government departments were asked to submit a list of questions on any specific topic they would like to add. Responses were not forthcoming in this census, although a few new questions were included.

There were two types of questionaires used in the census: the household questionaire and the individual questionnaire. An enumerator manual was prepared to assist the enumerators in their duties.

The questionnaire was pre-tested by the enumerators before they were to go out for field enumeration.

Cleaning operations

Census processing began as soon as questionaires were checked and coded. Forms were checked, edited and coded before being entered into the computer database.

Data processing was assisted by the Secretariat of the Pacific Community (SPC) using the computer software program CSPro for data entry and for generating tables. Tables were then exported to Excel for analysis.

Occupation and Industry were coded using the United Nations International Standard Classification of Occupation and International Standard Industrial Classification.

It is standard practice that as each area was completed the forms were first checked by the field supervisors for missing information and obvious inconsistencies. Omissions and errors identified at this stage were corrected by the enumerators.

The next stage was for the field supervisors to go through the completed forms again in the office to check in more detail for omissions and logical inconsistencies. Where they were found, the supervisors were responsible to take the necessary action.

Once the questionnaires had been thoroughly checked and edited, they were then coded in preparation for data processing.

Checking, editing and coding of the questionnaires in office were done after normal working hours as to ensure that the confidentiality of the survey is well observed.

Response rate

Complete enumeration of all households

Sampling error estimates

Not Applicable

Analysis unit

Persons and households

UNITS IDENTIFIED: - Dwellings: no - Vacant Units: Yes - Households: yes - Individuals: yes - Group quarters: no

UNIT DESCRIPTIONS: - Dwellings: Separated space with independent access that serves as a human lodging - Households: Individuals living in the same dwelling. For indigenous population definition of household requires sharing at least one meal. - Group quarters: Group of persons who share a common roof and food because of work, health, religion, etc.

Universe

Population census included people in territories, sailors, diplomats and their families. The indigenous population was enumerated. Due to guerrilla activity, approximately 3,000 dwellings (out of 6 million) could not be enumerated. The microdata sample consists of the 10% survey. It excludes population in group quarters and indigenous population.

Kind of data

Population and Housing Census [hh/popcen]

Sampling procedure

MICRODATA SOURCE: Departmento Administrativo Nacional de Estadística (DANE)

SAMPLE SIZE (person records): 2643125.

SAMPLE DESIGN: Systematic sample of dwellings pre-selected before fieldwork based on pre-census enumeration. In rural areas selection was determined in the field by the enumerator.

Mode of data collection

Face-to-face [f2f]

Research instrument

5 enumeration forms applied to 5 different target populations: (f1) short form for private dwellings (90%) of the population, requested information on age, sex, and relationship to householder; (f2) long form for private dwellings (10%); (f3) group quarters, 0.17% of dwellings; (f4) indigenous private dwellings (100%), representing 0.95% of dwellings; and (f5) indigenous group-quarters, 0.01% of dwellings.

Abstract

The 2005 Republic of Palau Census of Population and Housing will be used to give a snapshot of Republic of Palau's population and housing at the mid-point of the decade. This Census is also important because it measures the population at the beginning of the implementation of the Compact of Free Association. The information collected in the census is needed to plan for the needs of the population. The government uses the census figures to allocate funds for public services in a wide variety of areas, such as education, housing, and job training. The figures also are used by private businesses, academic institutions, local organizations, and the public in general to understand who we are and what our situation is, in order to prepare better for our future needs.

The fundamental purpose of a census is to provide information on the size, distribution and characteristics of a country's population. The census data are used for policymaking, planning and administration, as well as in management and evaluation of programmes in education, labour force, family planning, housing, health, transportation and rural development. A basic administrative use is in the demarcation of constituencies and allocation of representation to governing bodies. The census is also an invaluable resource for research, providing data for scientific analysis of the composition and distribution of the population and for statistical models to forecast its future growth. The census provides business and industry with the basic data they need to appraise the demand for housing, schools, furnishings, food, clothing, recreational facilities, medical supplies and other goods and services.

Geographic coverage

A hierarchical geographic presentation shows the geographic entities in a superior/subordinate structure in census products. This structure is derived from the legal, administrative, or areal relationships of the entities. The hierarchical structure is depicted in report tables by means of indentation. The following structure is used for the 2005 Census of the Republic of Palau:

Republic of Palau State Hamlet/Village Enumeration District Block

Analysis unit

Individuals Families Households General Population

Universe

The Census covered all the households and respective residents in the entire country.

Kind of data

Census/enumeration data [cen]

Sampling procedure

Not applicable to a full enumeration census.

Mode of data collection

Face-to-face [f2f]

Research instrument

The 2005 Palau Census of Population and Housing comprises three parts: 1. Housing - one form for each household 2. Population - one for for each member of the household 3. People who have left home - one form for each household.

Cleaning operations

Full scale processing and editing activiities comprised eight separate sessions either with or separately but with remote guidance of the U.S. Census Bureau experts to finalize all datasets for publishing stage.

Processing operation was handled with care to produce a set of data that describes the population as clearly and accurately as possible. To meet this objective, questionnaires were reviewed and edited during field data collection operations by crew leaders for consistency, completeness, and acceptability. Questionnaires were also reviewed by census clerks in the census office for omissions, certain inconsistencies, and population coverage. For example, write-in entries such as "Don't know" or "NA" were considered unacceptable in certain quantities and/or in conjunction with other data omissions.

As a result of this review operation, a telephone or personal visit follow-up was made to obtain missing information. Potential coverage errors were included in the follow-up, as well as questionnaires with omissions or inconsistencies beyond the completeness and quality tolerances specified in the review procedures.

Subsequent to field operations, remaining incomplete or inconsistent information on the questionnaires was assigned using imputation procedures during the final automated edit of the collected data. Allocations, or computer assignments of acceptable data in place of unacceptable entries or blanks, were needed most often when an entry for a given item was lacking or when the information reported for a person or housing unit on that item was inconsistent with other information for that same person or housing unit. As in previous 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 lace of blanks or unacceptable entries enhanced the usefulness of the data.

Another way to make corrections during the computer editing process is substitution. Substitution is the assignment of a full set of characteristics for a person or housing unit. Because of the detailed field operations, substitution was not needed for the 2005 Census.

Sampling error estimates

Sampling Error is not applicable to full enumeration censuses.

Data appraisal

In any large-scale statistical operation, such as the 2005 Census of the Republic of Palau, human- and machine-related errors were anticipated. These errors are commonly referred to as nonsampling errors. Such errors include not enumerating every household or every person in the population, not obtaining all required information form the respondents, obtaining incorrect or inconsistent information, and recording information incorrectly. 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 nonsampling errors, a number of techniques were implemented during the 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.

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.

Abstract

The 2001 census enumerated both de-facto and de-jure populations. It was intended that all information would be collected during an enumeration period of one week, the week from 11th October 2001. Census night for individual households was the night of 11 October 2001. Given the transport difficulties between Apia and Tokelau, and within Tokelau, and in order to restrict the enumeration period to less than one week, 9 interviewers were involved.

It is also obvious that in the conduct of a statistical operation as large and complex as a national census (even for Tokelau), it is inevitable that errors will occur due to questions being misunderstood, replies being incorrect or misinterpreted, etc. In fact, errors could have been introduced at all stages of the census, from planning, field operation stage, non-responses, non-call back to check on households that were missed during the actual enumeration and the training of enumerators (i.e. misunderstanding on the part of enumerators). Also errors could have been introduced at the data processing stage (editing, coding and data entry). In designing and carrying out the field procedures, including training procedures, efforts were made to reduce the effects of such errors on the results. However, it is clear that several errors still occurred.

Geographic coverage

National coverage: 3 atolls covered.

Analysis unit

Households and Individuals.

Universe

The 2001 census enumerated both de-facto and de-jure populations.

Kind of data

Census/enumeration data [cen]

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaire from the Tokelau 2001 census, which was published in English, remained mainly similar to the previous census questionnaire of 1996. An important difference was the inclusion of Tokelau Public Servants (and their families/relatives) living and working in Apia, Samoa. This was reflected in the questionnaire.

The questionnaire is divided into 2 main sections: - Dwelling: collects information on household characteristics, sanitation, water access, energy, waste disposal, household durables, remittances. - Individual: collects information on individual characteristics, religion, ethnicity, education, economic activities, fertility.

Cleaning operations

Data processing was done using census and survey processing software called CSPro.

Corrections were made by visual control of the questionnaire.

Z Represents or rounds to zero.Percent is out of the total census count excluding people in group quarters..Source: U.S. Census Bureau, Decennial Statistical Studies Division, 2020 Post-Enumeration Survey (August 2022 Release).Post-Enumeration Survey estimates are subject to sampling and nonsampling errors. For information regarding data collection, definitions, sampling error, nonsampling error, and estimation methodology, see: Post-Enumeration Surveys.

Analysis unit

Persons, households, and dwellings

UNITS IDENTIFIED: - Dwellings: yes - Vacant Units: no - Households: yes - Individuals: yes - Group quarters: yes

UNIT DESCRIPTIONS: - Dwellings: A place in which, at the time of the census, one or more persons regularly sleep. It may be a room in a factory, store or office building, a loft over a stable, a canal boat, tent, or a wigwam. A building like a tenement or apartment house, if it has only one front door, counts as only one dwelling house, no matter how many persons or families live in it. But one building with a partition wall through it and a front door for each of the two parts, counts as two dwelling houses. So in a block of houses there are as many dwelling-houses as front doors. - Households: A group of persons living together in the same dwelling place. The persons constituting this group may or may not be related by ties of kinship, but if they live together forming one household they should be considered as one family. Thus a servant who sleeps in the house or on the premises should be included with the members of the family for which he or she works. A boarder or lodger should be included with the members of the family with which he lodges, but a persons who boards in one place and lodges or rooms at another should be returned as a member of the family at the place where he lodges or rooms. - Group quarters: Yes

Universe

All persons living in the United States. Native Americans living on reservations or under tribal rule were enumerated using a separate schedule.

Kind of data

Population and Housing Census [hh/popcen]

Sampling procedure

MICRODATA SOURCE: Department of Commerce and Labor, Bureau of the Census

SAMPLE SIZE (person records): 923153.

SAMPLE DESIGN: 1-in-100 national random sample of the population, including Alaskans, Hawaiians, and persons enumerated on the American Indians schedules.

Mode of data collection

Face-to-face [f2f]

Research instrument

The census operation involved six schedules. Schdule 1 was used to enumerate the population and collected information on individual characteristics. Other schedules were used to enumerate the Native American population, and record information on agriculture and livestock.

Abstract (en): This data collection provides a preliminary subsample of the 1880 Public Use Sample drawn from census enumeration forms. The file contains two types of records: family and person. Each household record is followed by a record for each person in the family. This collection contains information about size of family, number of persons and families in dwelling, and geographic location of each household. Information on individuals includes demographic characteristics, civil condition, occupation, health, education, and nativity. Manuscript census records from 1880 for the 38 United States, the District of Columbia, and the Dakota Territory. This collection is a nationally representative--although clustered--1 in 1000 preliminary subsample of the United States population in 1880. The subsample is based on every tenth microfilm reel of enumeration forms (there are a total of 1,454 reels) and, within each reel, on the census page itself. In terms of the Public Use Sample as a whole, a sample density of 1 person per 100 was chosen so that a single sample point was randomly generated for every two census pages. Sample points were chosen for inclusion in the collection only if the individual selected was the first person listed in the dwelling. Under this procedure each dwelling, family, and individual in the population had a 1 in 100 probability of inclusion in the Public Use Sample. The complete sample, which will be released by the principal investigators in December 1993, will contain approximately 500,000 individuals living in 100,000 families, or 1 percent of the United States population in 1880. Funding insitution(s): United States Department of Health and Human Services. National Institutes of Health (HD25839). (1) This dataset has two levels. The first level ("F" Record Type) contains 29 variables for each of 10,126 families. The second level ("P" Record Type) contains 45 variables for each of 48,786 individuals residing in those families. (2) The data contain blanks and alphabetic characters. (3) Users will note some differences in code frequencies between certain variables in this collection and the totals listed in the documentation. (4) This collection is superseded by CENSUS OF POPULATION, 1880 [UNITED STATES]: PUBLIC USE SAMPLE (ICPSR 6460).

X Not applicable.DSE: Dual-system estimate.Census counts are rounded. As a result, counts may not sum to totals shown..A negative (positive) estimate of net coverage error indicates an undercount (overcount)..Standard errors are in parentheses below the estimate..Source: U.S. Census Bureau, Decennial Statistical Studies Division, 2020 Post-Enumeration Survey (August 2022 Release).Post-Enumeration Survey estimates are subject to sampling and nonsampling errors. For information regarding data collection, definitions, sampling error, nonsampling error, and estimation methodology, see: Post-Enumeration Surveys.

The life-cycle age groups are:

• under 15 years
• 15 to 29 years
• 30 to 64 years
• 65 years and over.

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 Stats NZ geographic data service.

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.

Abstract

Censuses are principal means of collecting basic population and housing statistics required for social and economic development, policy interventions, their implementation and evaluation.The census plays an essential role in public administration. The results are used to ensure: • equity in distribution of government services • distributing and allocating government funds among various regions and districts for education and health services • delineating electoral districts at national and local levels, and • measuring the impact of industrial development, to name a few The census also provides the benchmark for all surveys conducted by the national statistical office. Without the sampling frame derived from the census, the national statistical system would face difficulties in providing reliable official statistics for use by government and the public. Census also provides information on small areas and population groups with minimum sampling errors. This is important, for example, in planning the location of a school or clinic. Census information is also invaluable for use in the private sector for activities such as business planning and market analyses. The information is used as a benchmark in research and analysis.

Census 2011 was the third democratic census to be conducted in South Africa. Census 2011 specific objectives included: - To provide statistics on population, demographic, social, economic and housing characteristics; - To provide a base for the selection of a new sampling frame; - To provide data at lowest geographical level; and - To provide a primary base for the mid-year projections.

Geographic coverage

National

Analysis unit

Households, Individuals

Kind of data

Census/enumeration data [cen]

Mode of data collection

Face-to-face [f2f]

Research instrument

About the Questionnaire : Much emphasis has been placed on the need for a population census to help government direct its development programmes, but less has been written about how the census questionnaire is compiled. The main focus of a population and housing census is to take stock and produce a total count of the population without omission or duplication. Another major focus is to be able to provide accurate demographic and socio-economic characteristics pertaining to each individual enumerated. Apart from individuals, the focus is on collecting accurate data on housing characteristics and services.A population and housing census provides data needed to facilitate informed decision-making as far as policy formulation and implementation are concerned, as well as to monitor and evaluate their programmes at the smallest area level possible. It is therefore important that Statistics South Africa collects statistical data that comply with the United Nations recommendations and other relevant stakeholder needs.

The United Nations underscores the following factors in determining the selection of topics to be investigated in population censuses: a) The needs of a broad range of data users in the country; b) Achievement of the maximum degree of international comparability, both within regions and on a worldwide basis; c) The probable willingness and ability of the public to give adequate information on the topics; and d) The total national resources available for conducting a census.

In addition, the UN stipulates that census-takers should avoid collecting information that is no longer required simply because it was traditionally collected in the past, but rather focus on key demographic, social and socio-economic variables.It becomes necessary, therefore, in consultation with a broad range of users of census data, to review periodically the topics traditionally investigated and to re-evaluate the need for the series to which they contribute, particularly in the light of new data needs and alternative data sources that may have become available for investigating topics formerly covered in the population census. It was against this background that Statistics South Africa conducted user consultations in 2008 after the release of some of the Community Survey products. However, some groundwork in relation to core questions recommended by all countries in Africa has been done. In line with users' meetings, the crucial demands of the Millennium Development Goals (MDGs) should also be met. It is also imperative that Stats SA meet the demands of the users that require small area data.

Accuracy of data depends on a well-designed questionnaire that is short and to the point. The interview to complete the questionnaire should not take longer than 18 minutes per household. Accuracy also depends on the diligence of the enumerator and honesty of the respondent.On the other hand, disadvantaged populations, owing to their small numbers, are best covered in the census and not in household sample surveys.Variables such as employment/unemployment, religion, income, and language are more accurately covered in household surveys than in censuses.Users'/stakeholders' input in terms of providing information in the planning phase of the census is crucial in making it a success. However, the information provided should be within the scope of the census.

1. The Household Questionnaire is divided into the following sections:
2. Household identification particulars

3. Individual particulars Section A: Demographics Section B: Migration Section C: General Health and Functioning Section D: Parental Survival and Income Section E: Education Section F: Employment Section G: Fertility (Women 12-50 Years Listed) Section H: Housing, Household Goods and Services and Agricultural Activities Section I: Mortality in the Last 12 Months The Household Questionnaire is available in Afrikaans; English; isiZulu; IsiNdebele; Sepedi; SeSotho; SiSwati;Tshivenda;Xitsonga

4. The Transient and Tourist Hotel Questionnaire (English) is divided into the following sections:

5. Name, Age, Gender, Date of Birth, Marital Status, Population Group, Country of birth, Citizenship, Province.

6. The Questionnaire for Institutions (English) is divided into the following sections:

7. Particulars of the institution

8. Availability of piped water for the institution

9. Main source of water for domestic use

10. Main type of toilet facility

11. Type of energy/fuel used for cooking, heating and lighting at the institution

12. Disposal of refuse or rubbish

13. Asset ownership (TV, Radio, Landline telephone, Refrigerator, Internet facilities)

14. List of persons in the institution on census night (name, date of birth, sex, population group, marital status, barcode number)

15. The Post Enumeration Survey Questionnaire (English)

These questionnaires are provided as external resources.

Cleaning operations

Data editing and validation system The execution of each phase of Census operations introduces some form of errors in Census data. Despite quality assurance methodologies embedded in all the phases; data collection, data capturing (both manual and automated), coding, and editing, a number of errors creep in and distort the collected information. To promote consistency and improve on data quality, editing is a paramount phase in identifying and minimising errors such as invalid values, inconsistent entries or unknown/missing values. The editing process for Census 2011 was based on defined rules (specifications).

The editing of Census 2011 data involved a number of sequential processes: selection of members of the editing team, review of Census 2001 and 2007 Community Survey editing specifications, development of editing specifications for the Census 2011 pre-tests (2009 pilot and 2010 Dress Rehearsal), development of firewall editing specifications and finalisation of specifications for the main Census.

Editing team The Census 2011 editing team was drawn from various divisions of the organisation based on skills and experience in data editing. The team thus composed of subject matter specialists (demographers and programmers), managers as well as data processors. Census 2011 editing team was drawn from various divisions of the organization based on skills and experience in data editing. The team thus composed of subject matter specialists (demographers and programmers), managers as well as data processors.

The Census 2011 questionnaire was very complex, characterised by many sections, interlinked questions and skipping instructions. Editing of such complex, interlinked data items required application of a combination of editing techniques. Errors relating to structure were resolved using structural query language (SQL) in Oracle dataset. CSPro software was used to resolve content related errors. The strategy used for Census 2011 data editing was implementation of automated error detection and correction with minimal changes. Combinations of logical and dynamic imputation/editing were used. Logical imputations were preferred, and in many cases substantial effort was undertaken to deduce a consistent value based on the rest of the household’s information. To profile the extent of changes in the dataset and assess the effects of imputation, a set of imputation flags are included in the edited dataset. Imputation flags values include the following: 0 no imputation was performed; raw data were preserved 1 Logical editing was performed, raw data were blank 2 logical editing was performed, raw data were not blank 3 hot-deck imputation was performed, raw data were blank 4 hot-deck imputation was performed, raw data were not blank

Data appraisal

Independent monitoring and evaluation of Census field activities Independent monitoring of the Census 2011 field activities was carried out by a team of 31 professionals and 381 Monitoring