As of 2022, South Africa's population increased and counted approximately 60.6 million inhabitants in total, of which the majority (roughly 49.1 million) were Black Africans. Individuals with an Indian or Asian background formed the smallest population group, counting approximately 1.56 million people overall. Looking at the population from a regional perspective, Gauteng (includes Johannesburg) is the smallest province of South Africa, though highly urbanized with a population of nearly 16 million people.

Increase in number of households

The total number of households increased annually between 2002 and 2022. Between this period, the number of households in South Africa grew by approximately 65 percent. Furthermore, households comprising two to three members were more common in urban areas (39.2 percent) than they were in rural areas (30.6 percent). Households with six or more people, on the other hand, amounted to 19.3 percent in rural areas, being roughly twice as common as those in urban areas.

Main sources of income

The majority of the households in South Africa had salaries or grants as a main source of income in 2019. Roughly 10.7 million drew their income from regular wages, whereas 7.9 million households received social grants paid by the government for citizens in need of state support.

This statistic shows the age structure in South Africa from 2013 to 2023. In 2023, about 26.08 percent of South Africa's total population were aged 0 to 14 years.

Abstract

The 1980 South African Population Census was a count of all persons present on Republic of South African territory during census night (i.e. at midnight between 6 and 7 May 1980). The purpose of the population census was to collect, process and disseminate detailed statistics on population size, composition and distribution at small area level. The 1980 South African Population Census contains data collected on HOUSEHOLDS: household goods and dwelling characteristics as well as employment of domestic workers; INDIVIDUALS: population group, citizenship/nationality, marital status, fertility and infant mortality, education, employment, religion, language and disabilities, as well as mode of transport used and participation in sport and other recreational activities

Geographic coverage

The 1980 census covered the so-called white areas of South Africa, i.e. the areas in the former four provinces of the Cape, the Orange Free State, Transvaal, and Natal. It also covered areas in the following so-called National States of Ciskei, KwaZulu, Gazankulu, Lebowa, Qwaqwa, Kangwane, and Kwandebele. The 1980 South African census excluded the areas of the Transkei and Bophuthatswana. A census data file for Bophuthatswana was released with the final South African Census 1980 dataset.

Analysis unit

The units of analysis of the 1980 census includes households, individuals and institutions

Universe

The 1980 South African census covered all household members (usual residents).

The 1980 South African Population Census was enumerated on a de facto basis, that is, according to the place where persons were located during the census. All persons who were present on Republic of South African territory during census night (i.e. at midnight between 6 and 7 May 1980) were enumerated and included in the data. Visitors from abroad who were present in the RSA on holiday or business on the night of the census, as well as foreigners (and their families) who were studying or economically active, were not enumerated and included in the figures. Likewise, members of the Diplomatic and Consular Corps of foreign countries were not included. However, the South African personnel linked to the foreign missions including domestic workers were enumerated. Crews and passengers of ships were also not enumerated, unless they were normally resident in the Republic of South Africa. Residents of the RSA who were absent from the night were as far as possible enumerated on their return and included in the region where they normally resided. Personnel of the South African Government stationed abroad and their families were, however enumerated. Such persons were included in the Transvaal (Pretoria).

Kind of data

Census/enumeration data [cen]

Mode of data collection

Face-to-face [f2f]

Research instrument

The 1980 Population Census questionnaire was administered to all household members and covered household goods and dwelling characteristics, and employment of domestic workers. Questions concerning individuals included those on citizenship/nationality, marital status, fertility and infant mortality, education, employment, religion, language and disabilities, as well as mode of transport used and participation in sport and other recreational activities.

The following questions appear in the questionnaire but the corresponding data has not been included in the data set: PART C: PARTICULARS OF DWELLING: 2. How many separate families (i) Number of families (ii) Number of non-family persons (iii) total number of occupants [i.e. persons in families shown against (i) plus persons shown against 3. Persons employed by household Full-time, Part-time (a) How many persons are employed as domestics by you? (Include garden workers) (b) Total cash wages paid to above –mentioned persons for April 1980 4. Ownership – Do not answer this question if your dwelling is on a farm. (i) Own dwelling – (Including hire-purchase, sectional title property or property of wife): (a) Is the dwelling Fully paid Partly paid-off (b) If partly paid-off, state monthly repayment (include housing subsidy, but exclude insurance. (ii) Rented or occupied free dwelling : (a) Is the dwelling occupied free, rented furnished, rented unfurnished (b) If rented, state monthly rent (c) Is the dwelling owned by the employer? (d) Does it belong to the state, SA Railways, a provincial administration, a divisional council, or a municipality or other local authority? PART D: PARTICULARS OF THE FAMILY 1. Number of members in the family 2. Occupation. (Nature of work done) (a) Head of family (b) Wife 3. Annual income of head of family and wife. Annual income of: Head, Wife (if applicable)

As of 2024, South Africa's population increased, counting approximately 63 million inhabitants. Of these, roughly 27.5 million were aged 0-24, while 654,000 people were 80 years or older. Gauteng and Cape Town are the most populated South Africa’s yearly population growth has been fluctuating since 2013, with the growth rate dropping below the world average in 2024. The majority of people lived in the borders of Gauteng, the smallest of the nine provinces in terms of land area. The number of people residing there amounted to 16.6 million in 2023. Although the Western Cape was the third-largest province, the city of Cape Town had the highest number of inhabitants in the country, at 3.4 million. An underemployed younger population South Africa has a large population under 14, who will be looking for job opportunities in the future. However, the country's labor market has had difficulty integrating these youngsters. Specifically, as of the fourth quarter of 2024, the unemployment rate reached close to 60 percent and 384 percent among people aged 15-24 and 25–34 years, respectively. In the same period, some 27 percent of the individuals between 15 and 24 years were economically active, while the labor force participation rate was higher among people aged 25 to 34, at 74.3 percent.

Abstract

Every person, household and institution present in South Africa on Census Night, 9-10 October 1996, should have been enumerated in Census '96. The intent was to provide a count of all persons present within the territory of the Republic of South Africa at that time. More specifically, the purpose of this census was to collect, process and disseminate detailed statistics on population size, composition and distribution at a small area level. The 1996 South African population Census contains data collected on HOUSEHOLDS and INSTITUTIONS: dwellling type, home ownership, household assets, access to services and energy sources; INDIVIDUALS: age, population group, language, religion, citizenship, migration, fertility, mortality and disability; and economic characteristics of individuals, including employment activities and unemployment.

Geographic coverage

The South African Census 1996 has national coverage.

Analysis unit

The units of analysis for the South Africa Census 1996 were households, individuals and institutions

Universe

The South African Census 1996 covered every person present in South Africa on Census Night, 9-10 October 1996 (except foreign diplomats and their families).

Kind of data

Census/enumeration data [cen]

Sampling procedure

The data in the South African Census 1996 data file is a 10% unit level sample drawn from Census 1996 as follows:

1) Households: • A 10% sample of all households (excluding special institutions and hostels)

2) Persons: • A 10% sample of all persons as enumerated in the 1996 Population Census in South Africa

The census household records were explicitly stratified according to province and district council. Within each district council the records were further implicitly stratified by local authority. Within each implicit stratum the household records were ordered according to the unique seven-digit census enumerator area number, of which the first three digits are the (old) magisterial district number.

Mode of data collection

Face-to-face [f2f]

Research instrument

Different methods of enumeration were used to accommodate different situations and a variety of questionnaires were used. The information collected with each questionnaire differed slightly. The questionnaires used were as follows:

Questionnaire 1: (Household and personal questionnaire) This questionnaire was used in private households and within hostels which provided family accommodation. It contained 50 questions for each person and 15 for each household. Every household living in a private dwelling should have been enumerated on a household questionnaire. This questionnaire obtained information about the household and about each person who was present in the household on census night.

Questionnaire 2: (Summary book for hostels) This questionnaire was used to list all persons/households in the hostel and included 9 questions about the hostel. A summary book for hostels should have been completed for each hostel (that is, a compound for workers provided by mines, other employers, municipalities or local authorities). This questionnaire obtained information about the hostel and also listed all household and/or persons enumerated in the hostel. Some hostels contain people living in family groups. Where people were living as a household in a hostel, they were enumerated as such on a household questionnaire (which obtained information about the household and about each person who was present in the household on Census Night). On the final census file, they will be listed as for any other household and not as part of a hostel. Generally, hostels accommodate mostly individual workers. In these situations, persons were enumerated on separate personal questionnaires. These questionnaires obtained the same information on each person as would have been obtained on the household questionnaire. The persons will appear on the census file as part of a hostel. Some hostels were enumerated as special institutions and not on the questionnaires designed specifically for hostels.

Questionnaire 3: (Enumerator's book for special enumeration) This questionnaire was used to obtain very basic information for individuals within institutions such as hotels, prisons, hospitals etc. as well as for homeless persons. Only 6 questions were asked of these people. The questionnaire also included 9 questions about the institution. An enumerator's book for special enumeration should have been completed for each institution such as prisons and hospitals. This questionnaire obtained information on the institution and listed all persons present. Each person was asked a brief sub-set of questions - just 7 compared to around 50 on the household and personal questionnaires. People in institutions could not be enumerated as households. Homeless persons were enumerated during a sweep on census night using a special questionnaire. The results were later transcribed to standard enumerator's books for special enumeration to facilitate coding and data entry.

Response rate

The final calculation of the undercount of persons, based on analysis of a post-enumeration survey (PES) conducted shortly after the original census, was performed by Statistics South Africa. The estimated reponse rates are detailed below, both according to stratum and for the country as a whole. An estimated 10,7% of the people in South Africa, through the course of the census process, were not enumerated. For more information on the undercount and PES, see the publication, "Calculating the Undercount in Census '96", Statistics South Africa Report No. 03-01-18 (1996) which is included in the external documents section.

Undercount of persons by province (stratum, in %):

Western Cape 8,69
Eastern Cape 10,57
Northern Cape 15,59
Free State 8,75
KwaZulu-Natal 12,81
North West 9,37
Gauteng 9,99
Mpumalanga 10,09
Northern Province 11,28

South Africa 10,69

In 2023, there were around 211 million children aged 0-4 years in Africa. In total, the population aged 17 years and younger amounted to approximately 680 million. In contrast, only approximately 52 million individuals were aged 65 years and older as of the same year. The youngest continent in the world Africa is the continent with the youngest population worldwide. As of 2024, around 40 percent of the population in Sub-Saharan Africa was aged 15 years and younger, compared to a global average of 25 percent. Although the median age on the continent has been increasing annually, it remains low at around 20 years. There are several reasons behind the low median age. One factor is the low life expectancy at birth: On average, the male and female populations in Africa live between 61 and 65 years, respectively. In addition, poor healthcare on the continent leads to high mortality, also among children and newborns, while the high fertility rate contributes to lowering the median age. Cross-country demographic differences Africa’s demographic characteristics are not uniform across the continent. The age structure of the population differs significantly from one country to another. For instance, Niger and Uganda have the lowest median age in Africa, at 15.1 and 16.1 years, respectively. Not surprisingly, these countries also register a high crude birth rate. On the other hand, North Africa is the region recording the highest life expectancy at birth, with Tunisia and Algeria leading the ranking in 2025.

As of 2023, South Africa's population increased and counted approximately 62.3 million inhabitants in total, of which the majority inhabited Gauteng, KwaZulu-Natal, and the Western-Eastern Cape. Gauteng (includes Johannesburg) is the smallest province in South Africa, though highly urbanized with a population of over 16 million people according to the estimates. Cape Town, on the other hand, is the largest city in South Africa with nearly 3.43 million inhabitants in the same year, whereas Durban counted 3.12 million citizens. However, looking at cities including municipalities, Johannesburg ranks first. High rate of young population South Africa has a substantial population of young people. In 2024, approximately 34.3 percent of the people were aged 19 years or younger. Those aged 60 or older, on the other hand, made-up over 10 percent of the total population. Distributing South African citizens by marital status, approximately half of the males and females were classified as single in 2021. Furthermore, 29.1 percent of the men were registered as married, whereas nearly 27 percent of the women walked down the aisle. Youth unemployment Youth unemployment fluctuated heavily between 2003 and 2022. In 2003, the unemployment rate stood at 36 percent, followed by a significant increase to 45.5 percent in 2010. However, it fluctuated again and as of 2022, over 51 percent of the youth were registered as unemployed. Furthermore, based on a survey conducted on the worries of South Africans, some 64 percent reported being worried about employment and the job market situation.

This statistic shows the total population of South Africa from 2013 to 2023 by gender. In 2023, South Africa's female population amounted to approximately 32.46 million, while the male population amounted to approximately 30.75 million inhabitants.

Analysis unit

Persons, households, and dwellings

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

UNIT DESCRIPTIONS: - Dwellings: Any structure intended or used for human habitation - Households: A household is a group of persons who live together and provide themselves jointly with food or other essentials for living, or a single person who lives alone. - Group quarters: Living quarters where certain facilities are shared by groups of individuals or households. They can be divided into: (a) hotels, motels, guesthouses, etc.; (b) workers' hostels and students' residences; and (c) institutions.

Universe

All persons present in the country on the night of 9-10 October, 2011

Kind of data

Population and Housing Census [hh/popcen]

Sampling procedure

MICRODATA SOURCE: Statistics South Africa

SAMPLE SIZE (person records): 4418594.

SAMPLE DESIGN: Systematic stratified sample. 1 in 10 sample of household records classified as housing units or converted households, and an independent 1 in 10 sample of persons who resided in other living quarters. Local municipalities were the primary strata and demographic characteristics of persons within the household were used a secondary strata.

Mode of data collection

Face-to-face [f2f]

Research instrument

Three separate questionnaires were used to enumerate the household population (form A), transient individuals and individuals staying in hotels on census night (form B), and the institutional population (form C).

According to the 2021 Census, 81.7% of the population of England and Wales was white, 9.3% Asian, 4.0% black, 2.9% mixed and 2.1% from other ethnic groups.

Abstract

The Project for Statistics on Living standards and Development was a coutrywide World Bank Living Standards Measurement Survey. It covered approximately 9000 households, drawn from a representative sample of South African households. The fieldwork was undertaken during the nine months leading up to the country's first democratic elections at the end of April 1994. The purpose of the survey was to collect statistical information about the conditions under which South Africans live in order to provide policymakers with the data necessary for planning strategies. This data would aid the implementation of goals such as those outlined in the Government of National Unity's Reconstruction and Development Programme.

Geographic coverage

National coverage

Analysis unit

• Households
• Individuals
• Community

Kind of data

Sample survey data [ssd]

Sampling procedure

Sample size is 9,000 households

The sample design adopted for the study was a two-stage self-weightingdesign in which the first stage units were Census Enumerator Subdistricts (ESDs, or their equivalent) and the second stage were households.

The advantage of using such a design is that it provides a representative sample that need not be based on accurate census population distribution.in the case of South Africa, the sample will automatically include many poor people, without the need to go beyond this and oversample the poor. Proportionate sampling as in such a self-weighting sample design offers the simplest possible data files for further analysis, as weights do not have to be added. However, in the end this advantage could not be retained and weights had to be added.

The sampling frame was drawn up on the basis of small, clearly demarcated area units, each with a population estimate. The nature of the self-weighting procedure adopted ensured that this population estimate was not important for determining the final sample, however. For most of the country, census ESDs were used. Where some ESDs comprised relatively large populations as for instance in some black townships such as Soweto, aerial photographs were used to divide the areas into blocks of approximately equal population size. In other instances, particularly in some of the former homelands, the area units were not ESDs but villages or village groups.

In the sample design chosen, the area stage units (generally ESDs) were selected with probability proportional to size, based on the census population. Systematic sampling was used throughout that is, sampling at fixed interval in a list of ESDs, starting at a randomly selected starting point. Given that sampling was self-weighting, the impact of stratification was expected to be modest. The main objective was to ensure that the racial and geographic breakdown approximated the national population distribution. This was done by listing the area stage units (ESDs) by statistical region and then within the statistical region by urban or rural. Within these sub-statistical regions, the ESDs were then listed in order of percentage African. The sampling interval for the selection of the ESDs was obtained by dividing the 1991 census population of 38,120,853 by the 300 clusters to be selected. This yielded 105,800. Starting at a randomly selected point, every 105,800th person down the cluster list was selected. This ensured both geographic and racial diversity (ESDs were ordered by statistical sub-region and proportion of the population African). In three or four instances, the ESD chosen was judged inaccessible and replaced with a similar one.

In the second sampling stage the unit of analysis was the household. In each selected ESD a listing or enumeration of households was carried out by means of a field operation. From the households listed in an ESD a sample of households was selected by systematic sampling. Even though the ultimate enumeration unit was the household, in most cases "stands" were used as enumeration units. However, when a stand was chosen as the enumeration unit all households on that stand had to be interviewed.

Census population data, however, was available only for 1991. An assumption on population growth was thus made to obtain an approximation of the population size for 1993, the year of the survey. The sampling interval at the level of the household was determined in the following way: Based on the decision to have a take of 125 individuals on average per cluster (i.e. assuming 5 members per household to give an average cluster size of 25 households), the interval of households to be selected was determined as the census population divided by 118.1, i.e. allowing for population growth since the census. It was subsequently discovered that population growth was slightly over-estimated but this had little effect on the findings of the survey.

Individuals in hospitals, old age homes, hotels and hostels of educational institutions were not included in the sample. Migrant labour hostels were included. In addition to those that turned up in the selected ESDs, a sample of three hostels was chosen from a national list provided by the Human Sciences Research Council and within each of these hostels a representative sample was drawn on a similar basis as described abovefor the households in ESDs.

Mode of data collection

Face-to-face [f2f]

Research instrument

The main instrument used in the survey was a comprehensive household questionnaire. This questionnaire covered a wide range of topics but was not intended to provide exhaustive coverage of any single subject. In other words, it was an integrated questionnaire aimed at capturing different aspects of living standards. The topics covered included demography, household services, household expenditure, educational status and expenditure, remittances and marital maintenance, land access and use, employment and income, health status and expenditure and anthropometry (children under the age of six were weighed and their heights measured). This questionnaire was available to households in two languages, namely English and Afrikaans. In addition, interviewers had in their possession a translation in the dominant African language/s of the region.

In addition to the detailed household questionnaire referred to above, a community questionnaire was administered in each cluster of the sample. The purpose of this questionnaire was to elicit information on the facilities available to the community in each cluster. Questions related primarily to the provision of education, health and recreational facilities. Furthermore there was a detailed section for the prices of a range of commodities from two retail sources in or near the cluster: a formal source such as a supermarket and a less formal one such as the "corner cafe" or a "spaza". The purpose of this latter section was to obtain a measure of regional price variation both by region and by retail source. These prices were obtained by the interviewer. For the questions relating to the provision of facilities, respondents were "prominent" members of the community such as school principals, priests and chiefs.

Cleaning operations

All the questionnaires were checked when received. Where information was incomplete or appeared contradictory, the questionnaire was sent back to the relevant survey organization. As soon as the data was available, it was captured using local development platform ADE. This was completed in February 1994. Following this, a series of exploratory programs were written to highlight inconsistencies and outlier. For example, all person level files were linked together to ensure that the same person code reported in different sections of the questionnaire corresponded to the same person. The error reports from these programs were compared to the questionnaires and the necessary alterations made. This was a lengthy process, as several files were checked more than once, and completed at the beginning of August 1994. In some cases questionnaires would contain missing values, or comments that the respondent did not know, or refused to answer a question.

These responses are coded in the data files with the following values: VALUE MEANING -1 : The data was not available on the questionnaire or form -2 : The field is not applicable -3 : Respondent refused to answer -4 : Respondent did not know answer to question

Data appraisal

The data collected in clusters 217 and 218 should be viewed as highly unreliable and therefore removed from the data set. The data currently available on the web site has been revised to remove the data from these clusters. Researchers who have downloaded the data in the past should revise their data sets. For information on the data in those clusters, contact SALDRU http://www.saldru.uct.ac.za/.

No description is available. Visit https://dataone.org/datasets/judithk.514.7 for complete metadata about this dataset.

Abstract

Every person, household and institution present in South Africa on Census Night, 9-10 October 1996, should have been enumerated in Census 1996. The purpose of the census was to provide a count of all persons present within the territory of the Republic of South Africa at that time. More specifically, the purpose of this census was to collect, process and disseminate detailed statistics on population size, composition and distribution at a small area level.

Geographic coverage

The South African Census 1996 has national coverage.

Analysis unit

Households and individuals

Universe

The South African census 1996 covered every person present in South Africa on Census Night, 9-10 October 1996 (except foreign diplomats and their families).

Kind of data

Census enumeration data

Sampling procedure

The data in the South African Census 1996 data file is a 10% unit level sample drawn from Census 1996 as follows:

1) Households: • A 10% sample of all households (excluding special institutions and hostels)

2) Persons: • A 10% sample of all persons as enumerated in the 1996 Population Census in South Africa

The census household records were explicitly stratified according to province and district council. Within each district council the records were further implicitly stratified by local authority. Within each implicit stratum the household records were ordered according to the unique seven-digit census enumerator area number, of which the first three digits are the (old) magisterial district number.

Mode of data collection

Face-to-face [f2f]

Research instrument

Different methods of enumeration were used to accommodate different situations and a variety of questionnaires were used. The information collected with each questionnaire differed slightly. The questionnaires used were as follows:

Questionnaire 1: (Household and personal questionnaire) This questionnaire was used in private households and within hostels which provided family accommodation. It contained 50 questions for each person and 15 for each household. Every household living in a private dwelling should have been enumerated on a household questionnaire. This questionnaire obtained information about the household and about each person who was present in the household on census night.

Questionnaire 2: (Summary book for hostels) This questionnaire was used to list all persons/households in the hostel and included 9 questions about the hostel. A summary book for hostels should have been completed for each hostel (that is, a compound for workers provided by mines, other employers, municipalities or local authorities). This questionnaire obtained information about the hostel and also listed all household and/or persons enumerated in the hostel. Some hostels contain people living in family groups. Where people were living as a household in a hostel, they were enumerated as such on a household questionnaire (which obtained information about the household and about each person who was present in the household on Census Night). On the final census file, they will be listed as for any other household and not as part of a hostel. Generally, hostels accommodate mostly individual workers. In these situations, persons were enumerated on separate personal questionnaires. These questionnaires obtained the same information on each person as would have been obtained on the household questionnaire. The persons will appear on the census file as part of a hostel. Some hostels were enumerated as special institutions and not on the questionnaires designed specifically for hostels.

Questionnaire 3: (Enumerator's book for special enumeration) This questionnaire was used to obtain very basic information for individuals within institutions such as hotels, prisons, hospitals etc. as well as for homeless persons. Only 6 questions were asked of these people. The questionnaire also included 9 questions about the institution. An enumerator's book for special enumeration should have been completed for each institution such as prisons and hospitals. This questionnaire obtained information on the institution and listed all persons present. Each person was asked a brief sub-set of questions - just 7 compared to around 50 on the household and personal questionnaires. People in institutions could not be enumerated as households. Homeless persons were enumerated during a sweep on census night using a special questionnaire. The results were later transcribed to standard enumerator's books for special enumeration to facilitate coding and data entry.

Response rate

The final calculation of the undercount of persons, based on analysis of a post-enumeration survey (PES) conducted shortly after the original census, was performed by Statistics South Africa. The estimated reponse rates are detailed below, both according to stratum and for the country as a whole. An estimated 10,7% of the people in South Africa, through the course of the census process, were not enumerated. For more information on the undercount and PES, see the publication, "Calculating the Undercount in Census '96", Statistics South Africa Report No. 03-01-18 (1996) which is included in the external documents section.

Undercount of persons by province (stratum, in %):

Western Cape 8,69
Eastern Cape 10,57
Northern Cape 15,59
Free State 8,75
KwaZulu-Natal 12,81
North West 9,37
Gauteng 9,99
Mpumalanga 10,09
Northern Province 11,28

South Africa 10,69

Details of final model, component-rate submodels, and model simulations.

White rhinocerus (Ceratotherium simum) population in Southern sub-section of Welgevonden Game Reserve, South Africa—Ivlev’s selectivity index with Jacob’s correction (J) for terrain composition.

A table of estimates of genetic diversity of the microsatellite markers per population. The table describes the genetic diversity of the markers. Significant Hardy-Weinberg equilibrium (P < 0.05) tests are in BOLD. The expected gene diversity (He) varied from (0.2–0.94) while the observed heterozygosity (Ho) ranged from (0.125–1.0). Putative null alleles were identified at some loci in some populations using Microchecker. The null alleles were not locus specific. Ho- Observed heterozygosity; He- Expected heterozygosity; PHWE- Probability of Hardy-Weinberg equilibrium; FIS- Inbreeding coefficient; Nallele- Null allele; n- number of Samples (XLS 29 kb)

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

Nigeria has the largest population in Africa. As of 2025, the country counted over 237.5 million individuals, whereas Ethiopia, which ranked second, has around 135.5 million inhabitants. Egypt registered the largest population in North Africa, reaching nearly 118.4 million people. In terms of inhabitants per square kilometer, Nigeria only ranked seventh, while Mauritius had the highest population density on the whole African continent in 2023. The fastest-growing world region Africa is the second most populous continent in the world, after Asia. Nevertheless, Africa records the highest growth rate worldwide, with figures rising by over two percent every year. In some countries, such as Chad, South Sudan, Somalia, and the Central African Republic, the population increase peaks at over 3.4 percent. With so many births, Africa is also the youngest continent in the world. However, this coincides with a low life expectancy. African cities on the rise The last decades have seen high urbanization rates in Asia, mainly in China and India. African cities are also growing at large rates. Indeed, the continent has three megacities and is expected to add four more by 2050. Furthermore, Africa's fastest-growing cities are forecast to be Bujumbura, in Burundi, and Zinder, Nigeria, by 2035.

Details of model formulation and assessment.

angora_plosGenotyping data of 104 angora goats (30 from Argentina, 26 from France and 48 from South Africa) genotyped with the standardized 50k Goat SNP Chip. Date file is made of 5 colums: 1st Column -> country code (AR -> Argentina, FR -> France, ZA -> South Africa); 2nd column -> Individual ID; 3rd column -> snp name; 4th column ->: allel 1 ; 5th column -> allel 2.