South Africa ZA: Educational Attainment: At Least Master's or Equivalent: Population 25+ Years: Male: % Cumulative data was reported at 1.282 % in 2015. South Africa ZA: Educational Attainment: At Least Master's or Equivalent: Population 25+ Years: Male: % Cumulative data is updated yearly, averaging 1.282 % from Dec 2015 (Median) to 2015, with 1 observations. South Africa ZA: Educational Attainment: At Least Master's or Equivalent: Population 25+ Years: Male: % Cumulative data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s South Africa – Table ZA.World Bank: Education Statistics. The percentage of population ages 25 and over that attained or completed Master's or equivalent.; ; UNESCO Institute for Statistics; ;

Abstract

The GHS is an annual household survey which measures the living circumstances of South African households. The GHS collects data on education, health, and social development, housing, access to services and facilities, food security, and agriculture.

Geographic coverage

National coverage

Analysis unit

Households and individuals

Universe

The survey covers all de jure household members (usual residents) of households in the nine provinces of South Africa, and residents in workers' hostels. The survey does not cover collective living quarters such as student hostels, old age homes, hospitals, prisons, and military barracks.

Kind of data

Sample survey data [ssd]

Sampling procedure

From 2015 the General Household Survey (GHS) uses a Master Sample (MS) frame developed in 2013 as a general-purpose sampling frame to be used for all Stats SA household-based surveys. This MS has design requirements that are reasonably compatible with the GHS. The 2013 Master Sample is based on information collected during the 2011 Census conducted by Stats SA. In preparation for Census 2011, the country was divided into 103576 enumeration areas (EAs). The census EAs, together with the auxiliary information for the EAs, were used as the frame units or building blocks for the formation of primary sampling units (PSUs) for the Master Sample, since they covered the entire country, and had other information that is crucial for stratification and creation of PSUs. There are 3324 primary sampling units (PSUs) in the Master Sample, with an expected sample of approximately 33000 dwelling units (DUs). The number of PSUs in the current Master Sample (3324) reflect an 8,0% increase in the size of the Master Sample compared to the previous (2008) Master Sample (which had 3080 PSUs). The larger Master Sample of PSUs was selected to improve the precision (smaller coefficients of variation, known as CVs) of the GHS estimates. The Master Sample is designed to be representative at provincial level and within provinces at metro/non-metro levels. Within the metros, the sample is further distributed by geographical type. The three geography types are Urban, Tribal and Farms. This implies, for example, that within a metropolitan area, the sample is representative of the different geography types that may exist within that metro.

The sample for the GHS is based on a stratified two-stage design with probability proportional to size (PPS) sampling of PSUs in the first stage, and sampling of dwelling units (DUs) with systematic sampling in the second stage. After allocating the sample to the provinces, the sample was further stratified by geography (primary stratification), and by population attributes using Census 2011 data (secondary stratification).

Mode of data collection

Computer Assisted Telephone Interview [cati]

Research instrument

Data was collected with a household questionnaire and a questionnaire administered to a household member to elicit information on household members.

Data appraisal

Since 2019, the questionnaire for the GHS series changed and the variables were also renamed. For correspondence between old names (GHS pre-2019) and new name (GHS post-2019), see the document ghs-2019-variables-renamed.

Abstract

The Victims of Crime Survey (VCS) is a countrywide household-based survey which collects data on the prevalence of particular kinds of crime within South Africa. The survey includes information on victimisation experienced by individuals and households and their perspectives on community responses to crime. Therefore, VCS data can be used for research in the development of policies and strategies for crime prevention and public safety and education programmes. Statistics South Africa (StatsSA) conducted its first VCS in 1998. Following the VCS 1998, victims surveys were conducted by the Institute for Security Studies (ISS). Since 2011, StatsSA began conducting an annual collection of the VCS as a source of information on crime in South Africa. The main objectives of the survey are to:

• Provide information about the dynamics of crime from the perspective of households and the victims of crime.

• Explore public perceptions of the activities of the police, prosecutors, courts and correctional services in the prevention of crime and victimisation.

• Provide complimentary data on the level of crime within South Africa in addition to the statistics published annually by the South African Police Service.

The VCS 2011 is the second release in the collection and is comparable to the VCS 1998 and all subsequent releases. However, the VCS 2011 is not comparable to new Governance, Public Safety and Justice Survey (GPSJS). StatsSA launched the GPSJS in April 2018 in response to the need for standardised international reporting standards on governance and access to justice that are recommended by the SDGs, ShaSA and Agenda 2063.

Geographic coverage

The survey has national coverage

Analysis unit

Households and individuals

Universe

The target population of the survey consists of all private households in all nine provinces of South Africa, as well as residents in workers’ hostels. The survey does not cover other collective living quarters such as students’ hostels, old-age homes, hospitals, prisons and military barracks. It is only representative of non-institutionalised and non-military persons or households in South Africa.

Kind of data

Sample survey data

Sampling procedure

The VCS 2011 used a master sample (MS) originally designed for the Quarterly Labour Force Survey (QLFS) as a sampling frame. The MS is based on information collected during the 2001 Population Census conducted by Stats SA. The MS has been developed as a general-purpose household survey frame that can be used by all household-based surveys irrespective of the sample size requirement of the survey. The VCS 2012 uses an MS of primary sampling units (PSUs) which comprise census enumeration areas (EAs) that are drawn from across the country.

The sample used a stratified two-stage design with probability-proportional-to-size (PPS) sampling of PSUs in the first stage, and sampling of dwelling units (DUs) with systematic sampling in the second stage. The sample was designed to be representative at provincial level. A self-weighting design at provincial level was used and MS stratification was divided into two levels. Primary stratification was defined by metropolitan and non-metropolitan geographic area type. During secondary stratification, the Census 2001 data were summarised at PSU level. The following variables were used for secondary stratification: household size, education, occupancy status, gender, industry and income.

A randomised probability proportional to size (RPPS) systematic sample of PSUs was drawn in each stratum, with the measure of size being the number of households in the PSU. The sample size of 3 080 PSUs was selected. In each selected PSU a systematic sample of dwelling units was drawn. The number of DUs selected per PSU varies from PSU to PSU and depends on the inverse sampling ratios (ISR) of each PSU. The sample size for the VCS 2011 is 29 754 dwelling units.

Mode of data collection

Face-to-face [f2f]

Research instrument

The VOCS 2011 questionnaire was based on the questionnaires used in the International Crime Victim Survey (ICVS) and previous VOCSs conducted by the Institute for Security Studies (ISS) and Statistics SA.

Sections 10 to 20 of the questionnaire relate to household crimes. A proxy respondent (preferably head of the household or acting head of household) answered on behalf of the household. Section 21 to 27 of the questionnaire about crimes on individuals were asked of a household member who was selected using the birthday section method. This methodology selects an individual who is 16 years or older, whose birthday is soonest after the survey date.

Cleaning operations

Capture was undertaken on Epi-Info. A process of double capture was undertaken in order to eliminate capture error.

Data appraisal

Comparability:

The VCS 2011 is comparable to the previous VCSs in that several questions have remained unchanged over time. Where possible, it was generally indicated in the report. However, it is important to note that the sample size for the VCS 2011 is much bigger than any of the preceding surveys, and the data should be considered more reliable than the earlier surveys especially at lower levels of disaggregation. The current survey can thus provide more accurate estimates than the previous surveys, for example at provincial level and for domain variables, such as gender and race. Caution should be exercised when running cross tabulation of different crimes by province and other variables as in most cases the reported cases were too few for this type of analysis.

Abstract

The GHS is an annual household survey which measures the living circumstances of South African households. The GHS collects data on education, health, and social development, housing, access to services and facilities, food security, and agriculture.

Geographic coverage

The General Household Survey has national coverage.

Analysis unit

Households and individuals

Universe

The survey covers all de jure household members (usual residents) of households in the nine provinces of South Africa, and residents in workers' hostels. The survey does not cover collective living quarters such as student hostels, old age homes, hospitals, prisons, and military barracks.

Kind of data

Sample survey data

Sampling procedure

From 2015 the General Household Survey (GHS) uses a Master Sample (MS) frame developed in 2013 as a general-purpose sampling frame to be used for all Stats SA household-based surveys. This MS has design requirements that are reasonably compatible with the GHS. The 2013 Master Sample is based on information collected during the 2011 Census conducted by Stats SA. In preparation for Census 2011, the country was divided into 103 576 enumeration areas (EAs). The census EAs, together with the auxiliary information for the EAs, were used as the frame units or building blocks for the formation of primary sampling units (PSUs) for the Master Sample, since they covered the entire country, and had other information that is crucial for stratification and creation of PSUs. There are 3 324 primary sampling units (PSUs) in the Master Sample, with an expected sample of approximately 33 000 dwelling units (DUs). The number of PSUs in the current Master Sample (3 324) reflect an 8,0% increase in the size of the Master Sample compared to the previous (2008) Master Sample (which had 3 080 PSUs). The larger Master Sample of PSUs was selected to improve the precision (smaller coefficients of variation, known as CVs) of the GHS estimates. The Master Sample is designed to be representative at provincial level and within provinces at metro/non-metro levels. Within the metros, the sample is further distributed by geographical type. The three geography types are Urban, Tribal and Farms. This implies, for example, that within a metropolitan area, the sample is representative of the different geography types that may exist within that metro.

The sample for the GHS is based on a stratified two-stage design with probability proportional to size (PPS) sampling of PSUs in the first stage, and sampling of dwelling units (DUs) with systematic sampling in the second stage.After allocating the sample to the provinces, the sample was further stratified by geography (primary stratification), and by population attributes using Census 2011 data (secondary stratification).

Mode of data collection

Computer Assisted Telephone Interview [cati]

Research instrument

Data was collected with a household questionnaire and a questionnaire administered to a household member to elicit information on household members.

Data appraisal

Since 2019, the questionnaire for the GHS series changed and the variables were also renamed. For correspondence between old names (GHS pre-2019) and new name (GHS post-2019), see the document ghs-2019-variables-renamed.

This bar chart displays graduate students (people) by country using the aggregation sum in South Africa. The data is about universities.

Abstract

The General Household Survey (GHS) has been used as an instrument to track the progress of development since 2002 when it was first introduced . It is an annual household survey specifically designed to measure the living circumstances of South African households. The GHS collects data on education, health and social development, housing, household access to services and facilities, food security, and agriculture.

Geographic coverage

National

Analysis unit

Households

Universe

The survey covers all de jure household members (usual residents) of households in the nine provinces of South Africa and residents in workers' hostels. The survey does not cover collective living quarters such as student hostels, old age homes, hospitals, prisons and military barracks.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample design for the GHS 2013 was based on a master sample (MS) that was originally designed for the Quarterly Labour Force Survey (QLFS) and was used for the first time for the GHS in 2008. This master sample is shared by the QLFS, GHS, Living Conditions Survey (LCS), Domestic Tourism Survey (DTS) and the Income and Expenditure Survey (IES). The master sample used a two-stage, stratified design with probability-proportional-to-size (PPS) sampling of primary sampling units (PSUs) from within strata, and systematic sampling of dwelling units (DUs) from the sampled PSUs. A self-weighting design at provincial level was used and MS stratification was divided into two levels. Primary stratification was defined by metropolitan and non-metropolitan geographic area type. During secondary stratification, the Census 2001 data were summarised at PSU level. The following variables were used for secondary stratification: household size, education, occupancy status, gender, industry and income. Census enumeration areas (EAs) as delineated for Census 2001 formed the basis of the PSUs. The following additional rules were used:

• Where possible, PSU sizes were kept between 100 and 500 DUs • EAs with fewer than 25 DUs were excluded • EAs with between 26 and 99 DUs were pooled to form larger PSUs and the criteria used was same settlement type • Virtual splits were applied to large PSUs: 500 to 999 splits into two; 1 000 to 1 499 split into three; and 1 500 plus split into four PSUs; and • Informal PSUs were segmented

A randomised-probability-proportional-to-size (RPPS) systematic sample of PSUs was drawn in each stratum, with the measure of size being the number of households in the PSU. Altogether approximately 3 080 PSUs were selected. In each selected PSU a systematic sample of dwelling units was drawn. The number of DUs selected per PSU varies from PSU to PSU and depends on the Inverse Sampling Ratios (ISR) of each PSU.

Mode of data collection

Face-to-face [f2f]

Data appraisal

Please note that DataFirst provides versioning at dataset and file level. Revised files have new version numbers. Files that are not revised retain their original version numbers. Changes to any of the data files will result in the dataset having a new version number. Thus, version numbers of files within a dataset may not match.

Abstract

The primary aim of the Victims of Crime Survey is to establish the prevalence of particular kinds of crime within a certain population. This may be victimisation experienced by individuals or households. Data from victimisation surveys can be used to supplement official crime statistics. The objectives of the survey are to:

• Provide information about the dynamics of crime from the perspective of households and the victims of crime. • Explore public perceptions of the activities of the police, prosecutors, courts and correctional services in the prevention of crime and victimisation. • Provide complimentary data on the level of crime within South Africa in addition to the statistics published annually by the South African Police Service.

Geographic coverage

The survey had national coverage. The lowest level of geographic aggregation of the data is Province.

Analysis unit

The units of analysis in the study were individuals and households

Universe

The target population of the survey consists of all private households in all nine provinces of South Africa, as well as residents in workers’ hostels. The survey does not cover other collective living quarters such as students’ hostels, old-age homes, hospitals, prisons and military barracks. It is only representative of non-institutionalised and non-military persons or households in South Africa.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample design for the VOCS 2013-2014 used a master sample (MS) originally designed for the Quarterly Labour Force Survey (QLFS) as a sampling frame. The MS is based on information collected during the 2001 Population Census conducted by Stats SA. The MS has been developed as a general-purpose household survey frame that can be used by all household-based surveys irrespective of the sample size requirement of the survey. The VOCS 2013/14, like all other household-based surveys, uses an MS of primary sampling units (PSUs) which comprise census enumeration areas (EAs) that are drawn from across the country.

The sample for the VOCS 2013/14 used a stratified two-stage design with probability-proportional-to-size (PPS) sampling of PSUs in the first stage, and sampling of dwelling units (DUs) with systematic sampling in the second stage. The sample was designed to be representative at provincial level. A self-weighting design at provincial level was used and MS stratification was divided into two levels. Primary stratification was defined by metropolitan and non-metropolitan geographic area type. During secondary stratification, the Census 2001 data were summarised at PSU level. The following variables were used for secondary stratification: household size, education, occupancy status, gender, industry and income. The Master Sample is based on 3 080 PSUs.

A Probability Proportional to Size (PPS) systematic sample of PSUs was drawn in each stratum, with the measure of size being the number of households in the PSU. The sample size for the VOCS 2013/14 had 31 390 dwelling units from 3 052 PSUs. In each selected PSU, a systematic sample of dwelling units was drawn. The number of DUs selected per PSU varies from PSU to PSU and depends on the Inverse Sampling Ratios (ISR) of each PSU and the number of dwelling units in that PSU.

Mode of data collection

Face-to-face [f2f]

Research instrument

The VOCS 2013/14 questionnaire was based on the questionnaires used in the International Crime Victim Survey (ICVS) and previous VOCSs conducted by the Institute for Security Studies (ISS) and Statistics SA.

Sections 10 to 20 of the questionnaire relate to household crimes. A proxy respondent (preferably head of the household or acting head of household) answered on behalf of the household. Section 21 to 28 of the questionnaire about crimes on individuals were asked of a household member who was selected using the birthday section method. This methodology selects an individual who is 16 years or older, whose birthday is soonest after the survey date.

Data appraisal

Comparability:

The VOCS 2013-2014 is comparable to the previous VOC surveys because several questions have remained unchanged over time. Where comparisons were possible, thi is indicated in the report provided with the data. The current survey can provide for more accurate estimates at provincial level. Caution should be exercised when running cross tabulations of different crimes by provinces with other variables, however. For several crimes the reported experienced cases were too few to allow for extensive analysis.

Because VOCS 2013-2014 is the first in a new continuous data collection series it covers estimates of crimes as from April 2012 to February 2014, which is more years than covered by previous VOC surveys conducted by Statistics SA.

Abstract

The Income and Expenditure Survey is conducted every five years in South Africa.The main purpose of the survey is to determine the average expenditure patterns of households in different areas of the country. This survey forms the basis for the determination of the "basket" of consumer goods and services used for the calculation of the Consumer Price Index.

Geographic coverage

The survey had national coverage.

Analysis unit

Households

Universe

The survey covered private dwellings, workers' hostels, residential hotels, and nurses' and doctors' quarters, but excluded hospitals and clinics, hotels and guest houses, prisons, schools and student hostels and old-age homes.

Kind of data

Sample survey data

Sampling procedure

The sampling frame for the IES 2010/2011 was obtained from Statistics South Africa’s Master Sample (MS) based on the 2001 Population Census enumeration areas (EAs). The scope of the Master Sample (MS) is national coverage of all households in South Africa and the target population consists of all qualifying persons and households in the country. In summary, it has been designed to cover all households living in private dwelling units and workers living in workers’ quarters in the country. The IES 2010/2011 sample is based on an extended sample of 3 254 PSUs, which consists of the 3 080 PSUs in the Master Sample and a supplement of 174 urban PSUs selected from the PSU frame. The IES sample file contained 31 419 sampled dwelling units (DUs). The 31 419 sampled DUs consist of 31 007 DUs sampled from the 3 080 design PSUs in the Master Sample and 412 DUs from the supplemented 174 urban PSUs. In the case of multiple households at a sampled DU, all households in the DU were included.

Mode of data collection

Face-to-face [f2f]

Research instrument

There were four modules in the household questionnaire with eighteen subsections. The first module collected general household data and data on household members. Modules 2 to 4 collected data on consumption expenditure, household finances and income. The diary was a booklet in which the respondent recorded weekly expenditure data. A household completed a different diary for each week of the survey period.

Response rate

From the 31 419 dwelling units sampled across South Africa, 33 420 households were identified. Out of these, there was a sample realisation of 27 665 (82,8%) households, with the remaining 5 755 (17,2%) households being classified as out of scope.

Data appraisal

All continous household income and expenditure data collected during the Income and Expenditure Survey 2010-2011 are contained in the Total IES data file. The household data file contains only categorical variables. For example, expenditure data on electricity collected with the questions in sub-section 5.7 of the questionnaire will be found in the "Total_IES" data file under the COICOP codes 04511010, 04511110, 04404500. This is explained under "Data Organisation" on page 6 of the metadata record for the IES 2010 2011, which documents how the data files are organised and the variables in each data file.

Abstract

The GHS is a household survey that has been executed annually by Stats SA since 2002. The survey in its present form was instituted as a result of the need identified by the Government of South Africa to determine the level of development in the country and the performance of programmes and projects on a regular basis. The survey was specifically designed to measure multiple facets of the living conditions of South African households, as well as the quality of service delivery in a number of key service sectors. The GHS covers six broad areas, namely: education, health, social development, housing, household access to services and facilities, food security and agriculture.

Geographic coverage

The nine provinces of South Africa

Analysis unit

Households Individuals

Universe

The target population of the survey consists of all private households in all nine provinces of South Africa and residents in workers' hostels. The survey does not cover other collective living quarters such as students' hostels, old-age homes, hospitals, prisons and military barracks, and is therefore only representative of non-institutionalised and non-military persons or households in South Africa.

Kind of data

Données échantillonées [ssd]

Sampling procedure

The sample design for the GHS 2011 was based on a master sample (MS) that was originally designed for the QLFS and was used for the first time for the GHS in 2008. This master sample is shared by the Quarterly Labour Force Surveys (QLFS), General Household Survey (GHS), Living Conditions Survey (LCS), Domestic Tourism Survey and the Income and Expenditure Surveys (IES).

The master sample used a two-stage, stratified design with probability-proportional-to-size (PPS) sampling of PSUs from within strata, and systematic sampling of dwelling units (DUs) from the sampled primary sampling units (PSUs). A self-weighting design at provincial level was used and MS stratification was divided into two levels. Primary stratification was defined by metropolitan and non-metropolitan geographic area type. During secondary stratification, the Census 2001 data were summarised at PSU level. The following variables were used for secondary stratification; household size, education, occupancy status, gender, industry and income.

Census enumeration areas (EAs) as delineated for Census 2001 formed the basis of the PSUs. The following additional rules were used: · Where possible, PSU sizes were kept between 100 and 500 dwelling units (DUs); · EAs with fewer than 25 DUs were excluded; · EAs with between 26 and 99 DUs were pooled to form larger PSUs and the criteria used was same settlement type; · Virtual splits were applied to large PSUs: 500 to 999 split into two; 1 000 to 1 499 split into three; and 1 500 plus split into four PSUs; and · Informal PSUs were segmented.

A Randomised Probability Proportional to Size (RPPS) systematic sample of PSUs was drawn in each stratum, with the measure of size being the number of households in the PSU. Altogether approximately 3 080 PSUs were selected. In each selected PSU a systematic sample of dwelling units was drawn. The number of DUs selected per PSU varies from PSU to PSU and depends on the Inverse Sampling Ratios (ISR) of each PSU.

For more Information on sampling please view technical notes in the statistical release

Mode of data collection

Interview face à face [f2f]

Research instrument

The questionnaire covers five core areas of importance with sections on education, health, non-remunerated trips undertaken by the household, housing, and household access to services and facilities. These are covered in four sections, each focusing on a particular aspect. Depending on the need for additional information, the questionnaire is adapted on an annual basis. New sections may be introduced on a specific topic for which information is needed or additional questions may be added to existing sections. Likewise, questions that are no longer necessary may be removed.

Contents of the GHS questionnaire - Cover page: Household information, response details, field staff information, result codes, etc. - Flap: Demographic information (name, sex, age, population group, etc.) - Section 1: Biographical information (education, health, disability, welfare) - Section 2: Economic activities - Section 3:Household information (type of dwelling, ownership of dwelling, electricity, water and sanitation,environmental issues, services, transport, etc.) - Section 4: Food security, income and expenditure (food supply, agriculture, expenditure, etc.)

Response rate

The national response rate for the survey was 94,2%.

Subscribers can find out export and import data of 23 countries by HS code or product’s name. This demo is helpful for market analysis.

Abstract

The concept of victimisation surveys (also known as International Crime Victim Survey (ICVS)) is well established in South Africa (SA) and internationally. Until recently the United Nations Interregional Crime and Justice Research Institute (UNICRI) coordinated and sometimes conducted the ICVS in developing countries. During the past two decades a number of surveys related to crime, crime victims and users of services provided by the safety and security cluster departments have been conducted by various service providers in South Africa. Besides these surveys, three national VOCS have been conducted. The first of these was the Victims of Crime Survey conducted in 1998 by Statistics South Africa. This survey was based on the ICVS questionnaire developed by UNICRI, with adjustments made for local conditions. The Institute for Security Studies (ISS) was responsible for conducting subsequent versions of the VOCS, the National Victimes of Crime Survey 2003 and the Victim Survey 2007.

Starting with the Victims of Crime Survey 2011, Statistics SA plans to conduct the VOCS annually. The ‘new’ Victims of Crime Survey (VOCS) series is a countrywide household-based survey and examines three aspects of crime:

• The nature, extent and patterns of crime in South Africa, from the victim’s perspective; • Victim risk and victim proneness, so as to inform the development of crime prevention and public education programmes; • People’s perceptions of services provided by the police and the courts as components of the criminal justice system.

The VOCS 2011 is comparable to the VOCS 1998, VOCS 2003 and VOCS 2007 in cases where the questions remained largely unchanged. However, it is important to note that the sample size for the VOCS 2011 is much bigger than any of the preceding surveys, and the data should be considered more reliable than the earlier surveys especially at lower levels of disaggregation.

Geographic coverage

The survey had national coverage

Analysis unit

The units of analysis in the study were individuals and households

Universe

The target population of the survey consisted of all private households in all nine provinces of South Africa and residents in workers' hostels. The survey did not cover other collective living quarters such as students' hostels, old-age homes, hospitals, prisons and military barracks.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample design for the VOCS 2011 was based on a master sample (MS) originally designed as the sampling frame for the Quarterly Labour Force Survey (QLFS). The MS is based on information collected during the 2001 Population Census conducted by Stats SA. The MS has been developed as a general-purpose household survey frame that can be used by all household-based surveys, irrespective of the sample size requirement of the survey. The VOCS 2011, like all other household-based surveys, uses a MS of primary sampling units (PSUs) which comprises census enumeration areas (EAs) that are drawn from across the country.

The sample for the VOCS 2011 used a stratified two-stage design with probability proportional to size (PPS) sampling of PSUs in the first stage, and sampling of dwelling units (DUs) with systematic sampling in the second stage. The sample was designed to be representative at provincial level. A self-weighting design at provincial level was used and MS stratification was divided into two levels. Primary stratification was defined by metropolitan and non-metropolitan geographic area type. During secondary stratification, the Census 2001 data were summarised at PSU level. The following variables were used for secondary stratification: household size, education, occupancy status, gender, industry and income. A randomised probability proportional to size (RPPS) systematic sample of PSUs was drawn in each stratum, with the measure of size being the number of households in the PSU. The sample size of 3 080 PSUs was selected. In each selected PSU a systematic sample of dwelling units was drawn. The number of DUs selected per PSU varies from PSU to PSU and depends on the inverse sampling ratios (ISR) of each PSU. The sample size for the VOCS 2011 is 29 754 dwelling units.

Mode of data collection

Face-to-face [f2f]

Research instrument

The VOCS 2011 questionnaire was based on the questionnaires used in the International Crime Victim Survey (ICVS) and previous VOCSs conducted by the Institute for Security Studies (ISS) and Statistics SA. The questions are covered in 27 sections and deal with the following topics:

Flap Demographic information (name, sex, age, population group, etc.) Section 1 Household-specific characteristics (education, economic activities and household income sources Section 2 Beliefs about crime Section 3 Individual and community response to crime Section 4 Victim support and other interventions Section 5 Citizen interaction or community cohesion Section 6 Perception of the police service Section 7 Perception of the courts Section 8 Perception of correctional services Section 9 Corruption experienced by the respondent Section 10 Experience of household crime (screening table) Section 11 Theft of car experienced by a household member(s) in the previous 12 months Section 12 Housebreaking or burglary when no one was at home in the previous 12 months Section 13 Theft of livestock, poultry and other animals in the previous 12 months Section 14 Theft of crops planted by the household in the previous 12 months Section 15 Murder experienced by a household member(s) in the past 12 months Section 16 Theft out of a motor vehicle experienced by a household member(s) in the previous 12 months Section 17 Deliberate damaging/burning or destruction of dwelling experienced by a household member(s) in the previous 12 months Section 18 Motor vehicle vandalism or deliberate damage of a motor vehicle experienced by a household member(s) in the previous 12 months Section 19 Home robbery (including robbery often around or inside the household’s dwelling) experienced by a household member(s) in the previous 12 months

Sections 20–27 of this questionnaire required that an individual be randomly selected from the household to respond to questions classified as individual crimes. The methodology used was to select a person 16 years or older, whose birthday was the first to follow the survey date. These sections collected data on:

Section 20 Experiences of individual crimes (screening table) in the past 5 years and in the previous 12 months Section 21 Theft of bicycle experienced in the previous 12 months Section 22 Theft of motorbike or scooter experienced in the past 12 months Section 23 Car hijacking (including attempted hijacking) experienced in the previous 12 months Section 24 Robbery (including street robberies and other non-residential robberies, excluding car or truck hijackings, and home robberies) experienced in the previous 12 months Section 25 Assault experienced in the previous 12 months Section 26 Sexual offences (including rape) experienced in the previous 12 months Section 27 Consumer fraud experienced by the individual experienced in the previous 12 months All sections Comprehensive coverage of all aspects of domestic tourism and expenditure

The final data files correspond to sections of the questionnaireas follows:

Person: Data from Flap and Section 1 (excluding Section 1.6 and 1.7) Household: Data from Section 1.7 and Section 10-19 Section 20-27: Data from Section 20-27

The VOCS 2011 is comparable to the previous VOCSs in that several questions have remained unchanged over time. Where possible, it was generally indicated in the report. However, it must be noted that the VOCS 2011 sample size was more than double of the previous surveys. The current survey can thus provide more accurate estimates than the previous surveys, for example at provincial level and for domain variables, such as gender and race. Caution should be exercised when running cross tabulation of different crimes by province and other variables as in most cases the reported cases were too few for this type of analysis.

Cleaning operations

Capture was undertaken on Epi-Info. A process of double capture was undertaken in order to eliminate capture error.

The data relates to the paper that analyses the determinants or factors that best explain student research skills and success in the honours research report module during the COVID-19 pandemic in 2021. The data used have been gathered through an online survey created on the Qualtrics software package. The research questions were developed from demographic factors and subject knowledge including assignments to supervisor influence and other factors in terms of experience or belonging that played a role (see anonymous link at https://unisa.qualtrics.com/jfe/form/SV_86OZZOdyA5sBurY. An SMS was sent to all students of the 2021 module group to make them aware of the survey. They were under no obligation to complete it and all information was regarded as anonymous. We received 39 responses. The raw data from the survey was processed through the SPSS statistical, software package. The data file contains the demographics, frequencies, descriptives, and open questions processed.
The study reported in this paper employed the mixed methods approach comprising a quantitative and qualitative analysis. The quantitative and econometric analysis of the dependent variable, namely, the final marks for the research report and the independent variables that explain it. The results show significance in terms of the assignments and existing knowledge marks in terms of their bachelor’s average mark. We extended the analysis to a qualitative and quantitative survey, which indicated that the mean statistical feedback was above average and therefore strongly agreed/agreed except for library use by the student. Students, therefore, need more guidance in terms of library use and the open questions showed a need for a research methods course in the future. Furthermore, supervision tends to be a significant determinant in all cases. It is also here where supervisors can use social media instruments such as WhatsApp and Facebook to inform students further. This study contributes as the first to investigate the preparation and research skills of students for master's and doctoral studies during the COVID-19 pandemic in an online environment.

As of the fourth quarter of 2023, the unemployment rate in South Africa stood at 32.1 percent. The majority of unemployed individuals had an education level below matric (grade 12), while those that had finished their matric year represented around 34 percent. Graduates had the lowest share of unemployment at approximately 10 percent.

Abstract

This report has two main objectives: firstly, to present the key findings of the GHS 2011 in the context of the trends that were measured since the first GHS was conducted in 2002; and secondly, to provide a more in-depth analysis of the detailed questions related to selected service delivery issues.

Geographic coverage

All private households all nine provinces of South Africa.

Analysis unit

• Households
• Individuals

Universe

The survey covers all household members (usual residents) of households in the nine provinces of South Africa and residents in workers' hostels. The survey does not cover other collective living quarters such as students' hostels, old-age homes, hospitals, prisons and military barracks, and is therefore only representative of non-institutionalised and non-military persons or households in South Africa.

Kind of data

Sample survey data [ssd]

Frequency of data collection

Periodicity of Data collection: Annual.

Sampling procedure

A multi-stage design was used, which is based on a stratified design with probability proportional to size selection of primary sampling units (PSUs) at the first stage and sampling of dwelling units (DUs) with systematic sampling at the second stage. After allocating the sample to the provinces, the sample was further stratified by geography (primary stratification), and by population attributes using Census 2001 data (secondary stratification). Survey officers employed and trained by Stats SA visited all the sampled dwelling units in each of the nine provinces. During the first phase of the survey, sampled dwelling units were visited and informed about the coming survey as part of the publicity campaign. The actual interviews took place four weeks later. A total of 25 653 households (including multiple households) were successfully interviewed during face-to-face interviews.

Sampling deviation

The sample design for the GHS 2011 was based on a master sample (MS) that was originally designed for the QLFS and was used for the first time for the GHS in 2008. This master sample is shared by the Quarterly Labour Force Surveys (QLFS), General Household Survey (GHS), Living Conditions Survey (LCS), Domestic Tourism Survey (DTS) and the Income and Expenditure Surveys (IES). The master sample used a two-stage, stratified design with probability-proportional-to-size (PPS) sampling of PSUs from within strata, and systematic sampling of dwelling units (DUs) from the sampled primary sampling units (PSUs). A self-weighting design at provincial level was used and MS stratification was divided into two levels. Primary stratification was defined by metropolitan and non-metropolitan geographic area type. During secondary stratification, the Census 2001 data were summarised at PSU level. The following variables were used for secondary stratification: household size, education, occupancy status, gender, industry and income.

Research instrument

Most questions in the GHS questionnaire are pre-coded, i.e. there are a set number of choices from which one or more must be selected. For open-ended 'write-in' questions, the description will state that post-coding occurred and explain how this was done. Most variables have been pre-coded from the questionnaire and are not repeated in the variable description. Where the coding is not apparent, the description either provides the codes or indicates where code lists are to be found. One limitation of th study mentions that, it is important to note that the questionnaires for the GHS series were revised extensively in 2009 and that some questions might not be exactly comparable to the data series before then. The details of the questions included in the GHS questionnaire are covered in four sections, each focusing on a particular aspect. Depending on the need for additionalinformation, the questionnaire is adapted on an annual basis. New sections may be introduced on a specific topic for which information is needed or additional questions may be added to existing sections. Likewise, questions that are no longer necessary may be removed. The GHS questionnaire has undergone some revisions over time. These changes were primarily the result of shifts in focus of government programmes over time. The 2002–2004 questionnaires were very similar. Changes made to the GHS 2005 questionnaire included additional questions in the education section with a total of 179 questions. Between 2006 and 2008, the questionnaire remained virtually unchanged. In preparation for GHS 2009. Extensive stakeholder consultation took place during which the questionnaire was reviewed to be more in line with the monitoring and evaluation frameworks of the various government departments. Particular sections that were modified substantially during the review were the sections on education, social development, housing, agriculture, and food security. Even though the number of sections and pages in the questionnaire remained the same, questions in the GHS 2009 were increased from 166 to 185 between 2006 and 2008. Following the introduction of a dedicated survey on Domestic Tourism, the section on tourism was dropped for GHS 2010. Due to a further rotation of questions, the GHS 2011 questionnaire contained 166 questions as follows:

Contents of the GHS 2011 questionnaire

Section Number of Details of each section questions Cover page Household information, response details, field staff information, result codes, etc. Flap 6 Demographic information (name, sex, age, population group, etc.) Section 1 55 Biographical information (education, health, disability, welfare) Section 2 20 Economic activities Section 3 65 Household information (type of dwelling, ownership of dwelling, electricity, water and sanitation, environmental issues, services, transport, etc.) Section 4 20 Food security, income and expenditure (food supply, agriculture, expenditure, etc.) All sections 166 Comprehensive coverage of living conditions and service delivery

Cleaning operations

Historically the GHS used a conservative and hands-off approach to editing. Manual editing, and little if any imputation was done. The focus of the editing process was on clearing skip violations and ensuring that each variable only contains valid values. Very few limits to valid values were set and data were largely released as it was received from the field. With GHS 2009, Stats SA introduced an automated editing and imputation system that was continued for GHS 2010 and GHS 2011. The challenge was to remain as much as possible true to the conservative approach used prior to GHS 2009 and yet, at the same time, to develop a standard set of rules to be used during editing which could be applied consistently across time. When testing for skip violations and doing automated editing, the following general rules are applied in cases where one question follows the filter question and the skip is violated:

• If the filter question had a missing value, the filter is allocated the value that corresponds with the subsequent question which had a valid value. • If the values of the filter question and subsequent question are inconsistent, the filter question’s value is set to missing and imputed using either the hot-deck or nearest neighbour imputation techniques. The imputed value is then once again tested against the skip rule. If the skip rule remains violated the question subsequent to the filter question is dealt with by either setting it to missing and imputing or if that fails printing a message of edit failure for further investigation, decision-making and manual editing.

In cases where skip violations take place for questions where multiple questions follow the filter question, the rules used are as follows: • If the filter question has a missing value, the filter is allocated the value that corresponds with the value expected given the completion of the remainder of the question set. • If the filter question and the values of subsequent questions values were inconsistent, a counter is set to see what proportion of the subsequent questions have been completed. If more than 50% of the subsequent questions have been completed the filter question’s value is modified to correspond with the fact that the rest of the questions in the set were completed. If less than 50% of the subsequent questions in the set were completed, the value of the filter question is set to missing and imputed using either the hot-deck or nearest neighbour imputation techniques. The imputed value is then once again tested against the skip rule. If the skip rule remains violated the questions in the set that follows the filter question are set to missing.

Response rate

Response rates per province, 2011

Province Per cent Western Cape 91,3 Eastern Cape 98,9 Northern Cape 94,1 Free State 97,3 KwaZulu-Natal 99,2 North West 97,0 Gauteng

Abstract

The GHS is an annual household survey, specifically designed to measure various aspects of the living circumstances of South African households. The key findings reported here focus on the five broad areas covered by the GHS, namely: education, health, activities related to work and unemployment, housing and household access to services and facilities.

Geographic coverage

The scope of the General Household Survey 2007 was national coverage.

Analysis unit

The units of anaylsis for the General Household Survey 2007 are individuals and households.

Universe

The survey covered all de jure household members (usual residents) of households in the nine provinces of South Africa and residents in workers' hostels. The survey does not cover collective living quarters such as students' hostels, old age homes, hospitals, prisons and military barracks.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample design for the GHS 2007 was based on a master sample (MS) that was designed during 2003 and used for the first time in 2004. This master sample was developed specifically for household sample surveys that were conducted by Statistics South Africa between 2004 and 2007. These include surveys such as the annual Labour Force Surveys (LFS), General Household Survey (GHS) and the Income and Expenditure Survey (IES).

A multi-stage stratified area probability sample design was used. Stratification was done per province (nine provinces) and according to district council (DC) (53 DCs) within provinces. These stratification variables were mainly chosen to ensure better geographical coverage, and to enable analysts to disaggregate the data at DC level.

The design included two stages of sampling. Firstly PSUs were systematically selected using Probability Proportional to Size (PPS) sampling techniques. During the second stage of sampling, Dwelling Units (DUs) were systematically selected as Secondary Sampling Units (SSUs). Census Enumeration Areas (EAs) as delineated for Census 2001 formed the basis of the PSUs. EAs were pooled when needed to form PSUs of adequate size (72 dwelling units or more) for the first stage of sampling. The following criteria were used for PSU formation:

• No overlapping between any two PSUs; • Complete coverage of the sampling population; • Fully identifiable (e.g. in the case of a household survey, information on the geographical boundaries of the PSU should enable the exact location of the PSU); • Secondary sampling units (SSUs) must be clearly identifiable within PSUs; • Updated information on the number of SSUs within all the PSUs had to be available; • PSUs must be sufficiently large in respect of the number of SSUs included to enable the forming of a predetermined number of clusters of SSUs, with the size of a cluster equal to the sample take of SSUs within a PSU, taking all types of surveys into consideration; and • PSUs must also be sufficiently small to facilitate the listing and also regular updating of the SSUs within them.

A PPS sample of PSUs was drawn in each stratum, with the measure of size being the number of households in the PSU. Altogether approximately 3 000 PSUs were selected. In each selected PSU a systematic sample of ten dwelling units was drawn, thus, resulting in approximately 30 000 dwelling units. All households in the sampled dwelling units were enumerated.

Mode of data collection

Face-to-face [f2f]

Research instrument

The GHS 2007 questionnaire collected data on: Household characteristics: Dwelling type, home ownership, access to water and sanitation facilities, access to services, transport, household assets, land ownership, agricultural production Individuals' characteristics: demographic characteristics, relationship to household head, marital status, language, education, employment, income, health, disability, access to social services, mortality. Women's characteristics: fertility

Response rate

29 311 (84,0%) of the expected 34 902 interviews were successfully completed. This response rate is 2,0% points down from the 86,0% response rate as reported in the GHS 2006 report. It was not possible to complete interviews in 5,1% of the sampled dwelling units because of reasons such as refusals or absenteeism. An additional 10,9% of all interviews were not conducted for various reasons such as the sampled dwelling units had become vacant or had changed status (e.g.,. they were used as shops/small businesses at the time of the enumeration, but were originally listed as dwelling units).

Sampling error estimates

Estimation and use of standard error The published results of the General Household Survey are based on representative probability samples drawn from the South African population, as discussed in the section on sample design. Consequently, all estimates are subject to sampling variability. This means that the sample estimates may differ from the population figures that would have been produced if the entire South African population had been included in the survey. The measure usually used to indicate the probable difference between a sample estimate and the corresponding population figure is the standard error (SE), which measures the extent to which an estimate might have varied by chance because only a sample of the population was included. There are two major factors which influence the value of a standard error. The first factor is the sample size. Generally speaking, the larger the sample size, the more precise the estimate and the smaller the standard error. Consequently, in a national household survey such as the GHS, one expects more precise estimates at the national level than at the provincial level due to the larger sample size involved. The second factor is the variability between households of the parameter of the population being estimated, for example, the number of unemployed persons in the household.

Abstract

In April 2018, StatsSA launched the Governance Public Safety and Justice Survey (GPSJS) in response to the need for standardised international reporting standards on governance and access to justice that are recommended by the SDGs, ShaSA and Agenda 2063. In compliance with these standards, Stats SA discontinued the separate publication of the Victims of Crime Survey (VCS) and incorporated it within the new GPSJS series. Therefore, the GPSJS represents the new source of microdata on the experience and prevalence of particular kinds of crime within South Africa.

The GPSJS is a countrywide household-based survey which collects data on two types of crimes, namely, vehicle hijacking and home robbery. Business robbery is not covered by the survey. The survey includes information on victimisation experienced by individuals and households and their perspectives on community responses to crime. Additionally, the survey data includes information on legitimacy, voice, equity and discrimination. Therefore, GPSJS data can be used for research in the development of policies and strategies for governance, crime prevention, public safety and justice programmes. The main objectives of the survey are to:

• Provide information about the dynamics of crime from the perspective of households and the victims of crime.

• Explore public perceptions of the activities of the police, prosecutors, courts and correctional services in the prevention of crime and victimisation.

• Provide complimentary data on the level of crime within South Africa in addition to the statistics published annually by the South African Police Service.

NOTE: The GPSJS is a continuation of the VCS series, which ended with VCS 2017/18. Therefore, the VCS 2018/19 can be exctracted from GPSJS 2018/19 and is comparable to previous VCS's only where questions remained the same. Please see Data Quality Notes for more infomation on comparability.

Geographic coverage

National coverage

Analysis unit

Households and individuals

Universe

The target population of the survey consists of all private households in all nine provinces of South Africa, as well as residents in workers' hostels. The survey does not cover other collective living quarters such as students' hostels, old-age homes, hospitals, prisons and military barracks. It is only representative of non-institutionalised and non-military persons or households in South Africa.

Kind of data

Sample survey data [ssd]

Sampling procedure

The GPSJS 2021/22 uses the master sample (MS) sampling frame which has been developed as a general-purpose household survey frame that can be used by all other Stats SA household-based surveys having design requirements that are reasonably compatible with GPSJS. The GPSJS 2021/22 collection was drawn from the 2013 master sample. This master sample is based on information collected during Census 2011. In preparation for Census 2011, the country was divided into 103 576 enumeration areas (EAs). The census EAs, together with the auxiliary information for the EAs, were used as the frame units or building blocks for the formation of primary sampling units (PSUs) for the master sample, since they covered the entire country and had other information that is crucial for stratification and creation of PSUs.

There are 3 324 primary sampling units (PSUs) in the master sample with an expected sample of approximately 33 000 dwelling units (DUs). The number of PSUs in the current master sample (3 324) reflect an 8,0% increase in the size of the master sample compared to the previous (2008) master sample (which had 3 080 PSUs). The larger master sample of PSUs was selected to improve the precision (smaller coefficients of variation, known as CVs) of the GPSJS estimates.

Mode of data collection

Computer Assisted Telephone Interview [cati]

Research instrument

The GPSJS 2020/21 questionnaire is based on international reporting standards of governance, public safety and justice defined by the SDGs.

Sections 1 to 3 of the questionnaire relate to household crimes. A proxy respondent (preferably head of the household or acting head of household) answered on behalf of the household. Section 4 to 9 of the questionnaire relate to crimes experienced by individuals and were asked of a household member who was selected using the birthday section method. This methodology selects an individual who is 16 years or older, whose birthday is soonest after the survey date.

Data appraisal

Comparability to VCS series:

While redesigning the VCS into the GPSJS, some questions were modified in order to align the series with international reporting demands (e.g. SDGs) and to improve the accuracy of victim reporting. This caused a break of series for affected questions, in particular questions on 12-month experience of crime. The question on 5-year experience of crime was not changed and hence there is no break of series. The 5-year trends can therefore be used as a proxy for the 12-month series as the two follow similar patterns. Similarity of shapes of the two series makes it possible to predict increase or decrease of crime during the past 12 months using the 5-year series.

Abstract

The primary objective of the South Africa Demographic and Health Survey (SADHS) 2016 is to provide up-to-date estimates of basic demographic and health indicators. Specifically, the SADHS 2016 collected information on fertility levels; marriage; sexual activity; fertility preferences; awareness and use of contraceptives; breastfeeding practices; nutrition; childhood and maternal mortality; maternal health, including antenatal and postnatal care; key aspects of child health, including immunisation coverage and prevalence and treatment of acute respiratory infection (ARI), fever, and diarrhoea; potential exposure to the risk of HIV infection; coverage of HIV counselling and testing (HCT); and physical and sexual violence against women. Another critical objective of the SADHS 2016 is to provide estimates of health and behaviour indicators for adults age 15 and older, including use of tobacco, alcohol, and codeine-containing medications. In addition, the SADHS 2016 provides estimates of the prevalence of anaemia among children age 6-59 months and adults age 15 and older, and the prevalence of hypertension, anaemia, high HbA1c levels (an indicator of diabetes), and HIV among adults age 15 and older.

The information collected through the SADHS 2016 is intended to assist policymakers and programme managers in evaluating and designing programmes and strategies for improving the health of the country’s population.

Geographic coverage

National

Analysis unit

• Household
• Individual
• Children age 0-5
• Woman age 15-49
• Man age 15-59

Universe

The survey covered all de jure household members (usual residents), children age 0-5 years, women age 15-49 years and men age 15-59 years resident in the household.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling frame used for the SADHS 2016 is the Statistics South Africa Master Sample Frame (MSF), which was created using Census 2011 enumeration areas (EAs). In the MSF, EAs of manageable size were treated as primary sampling units (PSUs), whereas small neighbouring EAs were pooled together to form new PSUs, and large EAs were split into conceptual PSUs. The frame contains information about the geographic type (urban, traditional, or farm) and the estimated number of residential dwelling units (DUs) in each PSU. The sampling convention used by Stats SA is DUs. One or more households may be located in any given DU; recent surveys have found 1.03 households per DU on average.

Administratively, South Africa is divided into nine provinces. The sample for the SADHS 2016 was designed to provide estimates of key indicators for the country as a whole, for urban and non-urban areas separately, and for each of the nine provinces in South Africa. To ensure that the survey precision is comparable across provinces, PSUs were allocated by a power allocation rather than a proportional allocation. Each province was stratified into urban, farm, and traditional areas, yielding 26 sampling strata.

The SADHS 2016 followed a stratified two-stage sample design with a probability proportional to size sampling of PSUs at the first stage and systematic sampling of DUs at the second stage. The Census 2011 DU count was used as the PSU measure of size. A total of 750 PSUs were selected from the 26 sampling strata, yielding 468 selected PSUs in urban areas, 224 PSUs in traditional areas, and 58 PSUs in farm areas.

For further details on sample design, see Appendix A of the final report.

Mode of data collection

Face-to-face [f2f]

Research instrument

Five questionnaires were used in the SADHS 2016: the Household Questionnaire, the individual Woman’s Questionnaire, the individual Man’s Questionnaire, the Caregiver’s Questionnaire, and the Biomarker Questionnaire. These questionnaires, based on The DHS Program’s standard Demographic and Health Survey questionnaires, were adapted to reflect the population and health issues relevant to South Africa. Input was solicited from various stakeholders representing government ministries and agencies, nongovernmental organisations, and international donors. After the preparation of the questionnaires in English, the questionnaires were translated into South Africa’s 10 other official languages. In addition, information about the fieldworkers for the survey was collected through a self-administered Fieldworker Questionnaire.

Cleaning operations

All electronic data files for the SADHS 2016 were transferred via the IFSS to the Stats SA head office in Pretoria, where they were stored on a password-protected computer. The data processing operation included secondary editing, which required resolution of computer-identified inconsistencies and coding of open-ended questions. The data were processed by a core group of four people; secondary editing was completed by 11 people. All persons involved in data processing took part in the main fieldwork training, and they were supervised by senior staff from Stats SA with support from ICF. Data editing was accomplished using CSPro software. Secondary editing was initiated in October 2016 and completed in February 2017. Checking inconsistencies in dates of immunisations was aided by the digital images of the immunisation page of the Road-to-Health booklet that had been collected on the tablet by fieldworkers at the time of the interview for that purpose.

Response rate

A total of 15,292 households were selected for the sample, of which 13,288 were occupied. Of the occupied households, 11,083 were successfully interviewed, yielding a response rate of 83%.

In the interviewed households, 9,878 eligible women age 15-49 were identified for individual interviews; interviews were completed with 8,514 women, yielding a response rate of 86%. In the subsample of households selected for the male survey, 4,952 eligible men age 15-59 were identified and 3,618 were successfully interviewed, yielding a response rate of 73%. In this same subsample, 12,717 eligible adults age 15 and older were identified and 10,336 were successfully interviewed with the adult health module, yielding a response rate of 81%. Response rates were consistently lower in urban areas than in nonurban areas.

Sampling error estimates

The estimates from a sample survey are affected by two types of errors: nonsampling errors and sampling errors. Nonsampling errors are the results of mistakes made in implementing data collection and data processing, such as failure to locate and interview the correct household, misunderstanding of the questions on the part of either the interviewer or the respondent, and data entry errors. Although numerous efforts were made during the implementation of the SADHS 2016 to minimize this type of error, nonsampling errors are impossible to avoid and difficult to evaluate statistically.

Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents selected in the SADHS 2016 is only one of many samples that could have been selected from the same population, using the same design and expected size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability among all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results.

Sampling error is usually measured in terms of the standard error for a particular statistic (mean, percentage, etc.), which is the square root of the variance. The standard error can be used to calculate confidence intervals within which the true value for the population can reasonably be assumed to fall. For example, for any given statistic calculated from a sample survey, the value of that statistic will fall within a range of plus or minus two times the standard error of that statistic in 95% of all possible samples of identical size and design.

If the sample of respondents had been selected as a simple random sample, it would have been possible to use straightforward formulas for calculating sampling errors. However, the SADHS 2016 sample is the result of a multi-stage stratified design, and, consequently, it was necessary to use more complex formulas. Sampling errors are computed in SAS, using programs developed by ICF. These programs use the Taylor linearization method to estimate variances for survey estimates that are means, proportions, or ratios. The Jackknife repeated replication method is used for variance estimation of more complex statistics such as fertility and mortality rates.

A more detailed description of estimates of sampling errors are presented in Appendix B of the survey final report.

Data appraisal

Data Quality Tables - Household age distribution - Age distribution of eligible and interviewed women - Age distribution of eligible and interviewed men - Completeness of reporting - Births by calendar years - Reporting of age at death in days - Reporting of age at death in months - Height and weight data completeness and quality for children - Completeness of information on siblings - Sibship size and sex ratio of siblings

See details of the data quality tables in Appendix C of the survey final report.

Abstract

The GHS is a household survey that has been executed annually by Stats SA since 2002. The survey in its present form was instituted as a result of the need identified by the Government of South Africa to determine the level of development in the country and the performance of programmes and projects on a regular basis. The survey was specifically designed to measure multiple facets of the living conditions of South African households, as well as the quality of service delivery in a number of key service sectors. The GHS covers six broad areas, namely: education, health, social development, housing, household access to services and facilities, food security and agriculture.

Geographic coverage

The nine provinces of South Africa

Analysis unit

Households Individuals

Universe

The target population of the survey consists of all private households in all nine provinces of South Africa and residents in workers' hostels. The survey does not cover other collective living quarters such as students' hostels, old-age homes, hospitals, prisons and military barracks, and is therefore only representative of non-institutionalised and non-military persons or households in South Africa.

Kind of data

Données échantillonées [ssd]

Sampling procedure

A multi-stage, stratified random sample was drawn using probability-proportional-to-size principles. Firstlevel stratification was based on province and second-tier stratification on district council. Field staff employed and trained by Stats SA visited all the sampled dwelling units in each of the nine provinces.During the first phase of the survey, sampled dwelling units were visited and informed about the coming survey as part of the publicity campaign.

The GHS 2009 represents the second year of a new master sample (MS) that was originally designed for the QLFS and was used for the first time for the GHS in 2008. This master sample is shared by the Quarterly Labour Force Surveys (QLFS), General Household Survey (GHS), Living Conditions Survey (LCS), Domestic Tourism Survey and the Income and Expenditure Surveys (IES). The master sample used a two-stage, stratified design with probability-proportional-to-size (PPS) sampling of PSUs from within strata, and systematic sampling of dwelling units (DUs) from the sampled primary sampling units (PSUs). A self-weighting design at provincial level was used and MS stratification was divided into two levels. Primary stratification was defined by metropolitan and non-metropolitan geographic area type. During secondary stratification, the Census 2001 data were summarised at PSU level. The following variables were used for secondary stratification; household size, education, occupancy status, gender, industry and income. Census enumeration areas (EAs) as delineated for Census 2001 formed the basis of the PSUs. The following additional rules were used: • Where possible, PSU sizes were kept between 100 and 500 dwelling units (DUs); • EAs with fewer than 25 DUs were excluded; • EAs with between 26 and 99 DUs were pooled to form larger PSUs and the criteria used was same settlement type; • Virtual splits were applied to large PSUs: 500 to 999 split into two; 1 000 to 1 499 split into three; and 1 500 plus split into four PSUs; and • Informal PSUs were segmented.

A Randomised Probability Proportional to Size (RPPS) systematic sample of PSUs was drawn in each stratum, with the measure of size being the number of households in the PSU. Altogether approximately 3 080 PSUs were selected. In each selected PSU a systematic sample of dwelling units was drawn. The number of DUs selected per PSU varies from PSU to PSU and depends on the Inverse Sampling Ratios (ISR) of each PSU.

Mode of data collection

Interview face à face [f2f]

Research instrument

The questionnaire covers five core areas of importance with sections on education, health, non-remunerated trips undertaken by the household, housing, and household access to services and facilities. These are covered in four sections, each focusing on a particular aspect. Depending on the need for additional information, the questionnaire is adapted on an annual basis. New sections may be introduced on a specific topic for which information is needed or additional questions may be added to existing sections. Likewise, questions that are no longer necessary may be removed.

Contents of the GHS questionnaire · The Cover page contains particulars of households, response details, field staff information, result codes, etc. (This information is not contained in the data supplied) · The Flap covers demographic information (name, sex, age, population group, etc.) · Section 1 covers biographical information (education, health, disability, welfare) · Section 2 covers non-remunerated trips undertaken in the 12 months prior to the survey. · Section 3 and 4, this sections covers Household information (type of dwelling, ownership of dwelling and other assets, electricity, water and sanitation, environmental issues, services, transport, expenditure etc.

Response rate

25361 Housholds of 32636 were successfully interviewed (77.7% as response rate)

Abstract

The DTS is a large-scale household survey aimed at collecting accurate statistics on the travel behaviour and expenditure of South African residents travelling within the borders of the country. Such information is crucial when determining the contribution of tourism to the South African economy, as well as helping with planning, marketing, policy formulation, and the regulation of tourism-related activities.

Geographic coverage

The survey had national coverage

Analysis unit

Households and individuals

Universe

The target population of the survey consists of all private households in all nine provinces of South Africa and residents in workers’ hostels. The survey does not cover other collective living quarters such as students’ hostels, oldage homes, hospitals, prisons and military barracks, and is therefore only representative of non-institutionalised and non-military persons or households in South Africa.

Kind of data

Sample survey data

Sampling procedure

The sample design for the DTS 2020 was based on a Master Sample (MS) that has been designed for all household surveys conducted by Statistics South Africa.

The Master Sample used a two-staged, stratified design with probability-proportional-to-size (PPS) sampling of PSUs from within strata, and systematic sampling of dwelling units (DUs) from the sampled primary sampling units (PSUs). A self-weighting design at provincial level was used. Stratification was done in two stages: Primary stratification was defined by metropolitan and non-metropolitan geographic area type. During secondary stratification, the Census 2011 data were summarised at PSU level. The following variables were used for secondary stratification: household size, education, occupancy status, gender, industry and income.

Mode of data collection

Computer Assisted Telephone Interview

Abstract

The General Household Survey (GHS) 2017 is an annual household survey which measures the living circumstances of South African households. The GHS collects data on education, health, and social development, housing, access to services and facilities, food security, and agriculture.

Geographic coverage

National coverage

Analysis unit

Households and individuals

Universe

The survey covers all de jure household members (usual residents) of households in the nine provinces of South Africa, and residents in workers' hostels. The survey does not cover collective living quarters such as student hostels, old age homes, hospitals, prisons, and military barracks.

Kind of data

Sample survey data [ssd]

Sampling procedure

From 2015 the General Household Survey (GHS) uses a Master Sample (MS) frame developed in 2013 as a general-purpose sampling frame to be used for all Stats SA household-based surveys. This MS has design requirements that are reasonably compatible with the GHS. The 2013 Master Sample is based on information collected during the 2011 Census conducted by Stats SA. In preparation for Census 2011, the country was divided into 103 576 enumeration areas (EAs). The census EAs, together with the auxiliary information for the EAs, were used as the frame units or building blocks for the formation of primary sampling units (PSUs) for the Master Sample, since they covered the entire country, and had other information that is crucial for stratification and creation of PSUs. There are 3 324 primary sampling units (PSUs) in the Master Sample, with an expected sample of approximately 33 000 dwelling units (DUs). The number of PSUs in the current Master Sample (3 324) reflect an 8,0% increase in the size of the Master Sample compared to the previous (2008) Master Sample (which had 3 080 PSUs). The larger Master Sample of PSUs was selected to improve the precision (smaller coefficients of variation, known as CVs) of the GHS estimates. The Master Sample is designed to be representative at provincial level and within provinces at metro/non-metro levels. Within the metros, the sample is further distributed by geographical type. The three geography types are Urban, Tribal and Farms. This implies, for example, that within a metropolitan area, the sample is representative of the different geography types that may exist within that metro.

The sample for the GHS is based on a stratified two-stage design with probability proportional to size (PPS) sampling of PSUs in the first stage, and sampling of dwelling units (DUs) with systematic sampling in the second stage.After allocating the sample to the provinces, the sample was further stratified by geography (primary stratification), and by population attributes using Census 2011 data (secondary stratification).

Mode of data collection

Face-to-face [f2f]

Research instrument

Data was collected with a household questionnaire and a questionnaire administered to a household member to elicit information on household members.

Data appraisal

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