Contains 2006 Ward Census data, 2011 Ward Census data, and 2011 Ward National Household Survey (NHS) data.

Source: Statistics Canada, Census and NHS profile data for user-specified ward areas, , 2011 Census and National Household Survey, data received November 2013. Reproduced and distributed on an as is basis with the permission of Statistics Canada.

Accuracy: The 2011 National Household Survey (NHS) may contain bias due to non-response rates, especially for data pertaining to small geographic areas. The average non-response rate for the city of Ottawa was 18.9%. Further information on the NHS can be found on the Statistics Canada web site. http://www12.statcan.gc.ca/nhs-enm/2011/dp-pd/prof/help-aide/aboutdata-aproposdonnees.cfm?Lang=E

Update Frequency:Updated with each five-year national census (next census is undertaken in 2016; updated ward data are expected in 2018).

Attributes:Provides various demographic data broken down by the 23 wards of the City of Ottawa.

Contact: Royce Fu

Abstract

The 2011 Population and Housing Census of Samoa was taken on the midnight of November the 7th 2011. It counted every person in the country on that night and collected a wide range of social, economic and demographic information about each individual and their housing status.

The information were used to develop statistical indicators to support national plannning and policy-making and also to monitor MDG indicators and all other related conventions. This included population growth rates, educational attainment, employment rates, fertility rates, mortality rates, internal movements, household access to water supply, electricity, sanitation, and many other information. The full report is available at SBS website: http://www.sbs.gov.ws under the section on Population statistics and demography.

Geographic coverage

National coverage Regions Districts Village Enumeration areas

Analysis unit

Private households Institutional households Individuals Women 15-49 Housing/Buildings

Universe

The PHC 2011 covered all de facto household members, institutional households such as boarding schools, hospitals, prison inmates and expatriates residing in Samoa for more than 3 months. The PHC excluded all tourists visiting Samoa during the enumeration period and all Samoans residing overseas.

Kind of data

Census/enumeration data [cen]

Sampling procedure

Not applicable to a complete enumeration census.

Mode of data collection

Face-to-face [f2f]

Research instrument

Users' consultation seminars were conducted for three consecutive days (June 8th -10th, 2010) with financial support provided by the office of UNFPA in Suva via the Samoa Parliamentary Group for Population Development (SPGPD) annual programs. For the first time in census history, the SPGPD or members of parliament have become the target group of users to get involved in any census questionnaire consultations.

All government ministries and non-governmental organizations were invited to the consultation seminars and each was asked to make a presentation of data needs for consideration in the final census 2011 questionnaire. To avoid re-inventing the wheel in the compilation of the list of census questions for census 2011, the questionnaire from the census 2006 was reprinted and distributed to all participants and presenters to select questions that they would consider again for the census 2011 in addition to their new data needs. Users were also advised that any new question would need good justifications of how it links to national interests.

At the end of the three days seminar, all new questions were compiled for final selection by Samoa Bureau of Statistics. Not all the users' data needs have been included in the final 2011 census questionnaire due mainly to the cost involved and limited time for census enumeration. Therefore, the final selection of questions was purely based on the linkage of the data being requested to the list of statistical indicators in the 'Strategy for the Development of Samoa 2008-2012' (SDS) and the 'Millennium Development Goals' (MDGs) 2015. All data requests outside of the two frameworks were put aside to be integrated in other more appropriate survey activities by the bureau.

From July 2010-December 2010, the questionnaire was formatted using the In-Design CS4 software. It is important to note that the PHC 2011 was the first ever census using the scanning technology to process data from the census questionnaires as a replacement of the usual manual data entry process. The scanning was pilot tested in April 2011, before it was finally used for final census enumeration.

The questionnaire was designed using A3 paper size.

The Population questionnaire was administered in each household, which collected various information on household members including age, sex, citizenship, disability, orphanhood, marital status, residence (birth, usual, previous), religion, education and employment.

In the Population questionnaire, a special section was administered in each household for women age 15-49, which also asked information on their children ever born still living, died or living somewhere else. Mothers of children under one year were also asked whether their last born children were still living at the time of the census.

The Housing questionnaire was also administered in each household which collected information on the types of building the household lived, floor materials, wall materials, roof materials, land tenure, house tenure, water supply, drinking water, lighting, cooking fuel, toilet facility, telephone, computer, internet, refrigerator, radio, television and others.

Cleaning operations

Data editing was done in several stages. 1. Office manual editing and coding 2. Automatic scanning data entry edits 3. Visual verification questionnaire edits 3. Structure checking and completeness 4. Structure checks of the CSPro data files Editing program can be enquired at the Division of IT and Data Processing at email address: info.stats@sbs.gov.ws

Sampling error estimates

The census is a full-coverage of the population, therefore it is not a sample where sampling errors can be estimated.

Data appraisal

There was no post-enumeration in the census 2011. One of the normal practices by the bureau to validate the total population counts from all villages, districts and regions of Samoa in any census is the manual count of the population in all areas during the on-going census enumeration.That information is collected by the enumerators and field supervisors during the enumeration using the Enumerators and Supervisors control forms. At the end of the enumeration, the control forms which mainly contained the number of males and females per enumeration area will be collected and compiled by the Census and Survey division as the first preliminary count of the census. In the census 2011, the preliminary population counts were compiled and launched as the 'Village Directory 2011' report after 4 weeks from end of the enumeration period.

The significance of the Village Directory report is it helps to provide a qiuick overall picture of the population growth and population distribution in all villages of the country relative to previous censuses. Most important of all is that the preliminary count will provide the basis for a decision whether a post-enumeration is warrant or otherwise. If the preliminary country is close to the projected population then the post-enumeration is assumed not worth the cost because it is expensive and it will delay all other census processes. In the census 2011, the preliminary count arrived at 186,340 which was more than the projected population of 184,032 as depicted in the Statistical Abstract 2009. Therefore the decision was made that post-enumeration was not worth it.

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 Personal Interview

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

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 general aim of the Sierra Leone Integrated Household Survey (SLIHS) was to provide statistics on the living conditions of the people of Sierra Leone and to provide inputs to the government of Sierra Leone's policy making process. The study used consumption as the starting measure for household well-being and followed the standard in poverty analysis for developing countries. The SLIHS was prepared as joint work by Statistics Sierra Leone (SSL) and the World Bank Poverty Reduction and Economic Management Unit. SSL had the major responsibility of conducting the survey. The first chapter presents an overview of poverty, demographics, livelihoods, education, and health in Sierra Leone and measures progress in these indicators compared to the 2003 poverty assessment. The work was conducted as part of the poverty update and it included a series of policy notes with more detailed analysis. The objectives of the SLIHS include:

1. Provide benchmark poverty indicators against which the successes of the agenda for change (PRSP II) could be measured.
2. To measure the incidence of poverty alongside other indicators include providing information on patterns of household's consumption and expenditure at a greater level of disaggregation.
3. To provide data for the compilation of national accounts and computation of the Consumer Price Index (CPI)
4. In combination with earlier data this will give a data base for national and state planning and for the estimation of consumption as a proportion of household production.

The SLIHS was spread over a 12 month period in order to ensure a continuous recording of household consumption, expenditures and changes occurring thereof in 2011. A total of 9,671 Enumeration areas were selected and about 6,757 households were interviewed all over the country.

Geographic coverage

National

Analysis unit

• Household
• Individual

Kind of data

Sample survey data [ssd]

Sampling procedure

The Integrated Household Survey (SLIHS) was administered to a representative sample of households. A total of about 6,832 households were selected of which 6,767 households were interviewed. The analytic work underlying this survey was produced in collaboration between Statistics Sierra Leone (SSL) and the World Bank. SSL adopted the local councils as the primary domain of study, this provided measures of levels of poverty and welfare at national and sub-national levels therefore addressing the recent strengths and weaknesses of government policies and programs. The census Enumeration area was used as a primary sampling unit (PSU) for the 2011 survey. The survey used a two-stage sampling design from the 2004 census frame. At the first stage 9,671 enumeration areas were selected. At the second stage, 85 Households per EA were selected the statistics obtained from the sampling frame have no difference compared to the census report. This means that the sampling frame covers the whole country.

Mode of data collection

Face-to-face [f2f]

Research instrument

The SLIHS was comprised of a set of survey instruments. These were the following questionnaires: 1. Household Roster and Characteristics Questionnaire Part A 2. Household Consumption Expenditure and Income Questionnaire Part B

Response rate

95%

This profile presents information from the 2011 National Household Survey (NHS) for various levels of geography, including provinces and territories, census metropolitan areas/census agglomerations, census divisions, census subdivisions, census tracts and federal electoral districts. NHS data topics include: Immigration and Ethnocultural Diversity; Aboriginal Peoples; Education and Labour; Mobility and Migration; Language of work; Income and Housing.

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%.

Abstract

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

Geographic coverage

National

Analysis unit

• Household
• Individual/Person
• Members Oversea

Universe

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

Kind of data

Census/enumeration data [cen]

Mode of data collection

Face-to-face [f2f]

Research instrument

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

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

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

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

Cleaning operations

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

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

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

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

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

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

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

The National Household Survey (NHS) was conceived to replace the mandatory long-form census questionnaire. The content of the NHS 2011 is similar to the past long-form questionnaire, although some questions and sections have changed. This profile presents information from the 2011 National Household Survey (NHS) for various levels of geography, including provinces and territories, census metropolitan areas/census agglomerations, census divisions, census subdivisions, dissemination areas, federal electoral districts, and forward sortation areas. The forward sortation areas profile was created as a custom tabulation by the University of Toronto, and subsequently shared with ODESI and the DLI. NHS data topics include: Immigration and Ethnocultural Diversity; Aboriginal Peoples; Education and Labour; Mobility and Migration; Language of work; Income and Housing. 2011 Census data topics include: Population and dwelling counts; Age and sex; Families, households and marital status; Structural type of dwelling and collectives; and Language. The Aboriginal Population Profile presents information on the Aboriginal identity population from the 2011 National Household Survey (NHS). The profile for the NHS Special Collection for 13 Indian reserves and Indian settlements in Northern Ontario provides information from a special data collection following the 2011 National Household Survey (NHS).

Abstract

The Nauru Population and Housing Census 2011 is funded by UNFPA and AusAID. Technical assistant was provided by the SPC/SDP from Noumea. The Census night took place on 30th October 2011 at 12 midnight. The fieldwork was scheduled to complete in 2 weeks and the final schedule was given 1-2 weeks extension time for supervisor's editing of forms.

Geographic coverage

• National
• District
• Enumeration area
• Household members

Analysis unit

Region/EA Identity Household questionnaire Person questionnaire

Universe

The survey covered all de jure household members (usual residents), all household, all population, all age, all sex, all nationality

Kind of data

Census/enumeration data [cen]

Sampling procedure

Not applicable to a full enumeration census

Sampling deviation

Not applicable to a full enumeration census

Mode of data collection

Face-to-face [f2f]

Cleaning operations

Data editing took place at a number of stages throughout the processing, including: a) Office editing and coding b) During data entry c) Structure checking and completeness d) Secondary editing

Response rate

96%

Sampling error estimates

Not applicable to a full enumeration census

Data appraisal

Data quality tables are available to review the quality of the data and include the following:

Table H1. District by Type of building Table H2. District by Materials of Outerwalls Table H3. District by Period building first constructed Table H4. District by type of tenure Table H5A. District by Number of household rooms Table H5B. District by Number of household dining rooms Table H5C. District by Number of household kitchen Table H5D. District by Number of household total rooms Table H6. District by Shared bathroom Table H7. District by Shared kitchen Table H8A. District by Materials of roofing Table H8B. District by Roofing condition Table H9A. District by Materials of guttering Table H9B. District by Condition of guttering Table H10A. District by Materials for downpipe Table H10B. District by Condition for downpipe Table H11. District by Downpipe connected to storage Table H12. District by Main source of drinking water Table H13. District by Main source of water in general Table H14. District by Water storage capacity Table H15. District by Material of water storage Table H16. District by water availability during 'dry' periods Table H17. District by household sharing main water supply Table H18. District by Source of water when scarce Table H19A. District by purpose of underground water usage Table H19B. District by Abstraction of underground water usage Table H20. District by Main toilet facility Table H21. District by Toilet flushed with water sources Table H22. District by Toilet flushed drainage system type Table H23A.District by items working order (For sustaining quality of life) Table H23B. District by items working order (ICT and communications) Table H23C. District by items working order (Commercial or subsistence value) Table H24. District by Main source of lighting Table H25. District by main fuel for cooking Table H26. District by main source of electricity Table H27. District by Household subsistence activities Table H28. District by household have a kitchen garden Table H29. District by Agricultural Activities Table H30. District by Livestock Table H31. District by Cash Inflow during last three months Table H32. District by any household member died last 3 years

Table 1 . Total Households and Population by District Nauru:2011 Table 2. District by Broad Age Group and P2. Sex, Nauru:2011 Table 3. Population by single age by sex, Nauru:2011 Table 4. Population by District and 5 year age group and sex, NAURU:2011 Table 5. Population by District, Relationship to head of household by sex, NAURU:2011 Table 6 . Population by 5 year age group, and relationship to head of household by sex, NAURU:2011 Table 7. Population by District and Religion, Nauru:2011 Table 8. Population by religion, 5 year age group,Nauru:2011 Table 9. Population by district by country of birth, Nauru:2011 Table 10. Population by country of birth, 5 year age group and sex, Nauru:2011 Table 11. Population by district, whether mother still alive and living in the household, Nauru:2011 Table 12. Population by district and whether father is still alive, Nauru:2011 Table 13. Population by district, marital status and sex, Nauru:2011 Table 14. Population by 5 year age group, marital status and sex, Nauru:2011 Table 15. Population by district, mothers local tribe and sex, Nauru:2011 Table 16. Population by 5 year age group, mothers local tribe and sex, Nauru:2011 Table 17. Population by district, whether married to a Nauruan and sex, Nauru:2011 Table 18. Population by 5 year age group whether married to Nauruan and sex, Nauru:2011 Table 19. Population by district, nationality and sex, Nauru:2011 Table 20. Population by 5year age group, nationality and sex, Nauru:2011 Table 21. Population by district, citizenship and sex Table 22. Population by 5 year age group, citizenship and sex, Nauru:2011 Table 23. Population by district and difficulties, Nauru:2011 Table 24. Male population by district and difficulties, Nauru:2011 Table 25. Female population by district and difficulties, Nauru:2011 Table 26. Population by 5 year age group and difficulties, Nauru:2011 Table 27. Male Population by 5 year age group and difficulties, Nauru:2011 Table 28. Female Population by 5 year age group and difficulties, Nauru:2011 Table 29. Population by district, currently attending school and sex, Nauru:2011 Table 30. Popualtion 15 years and over, school attendace and sex, Nauru:2011 Table 31. Population 15 years and over by district , type of education institution attending, Nauru:2011 Table 32. Population 15 years and over by type of education institution attending and sex, Nauru:2011 Table 33. Population 15 years and over by highest qualification completed and sex, Nauru:2011 Table 34. Population 15 years and over by main activity and sex, Nauru:2011 Table 35. Population 15 years and over by labour force participation and sex, Nauru:2011 Table 36. Female population aged 15 years and over ever given birth, Nauru:2011 Table 37. Female population aged 15 years and over by total Children ever born Table 38. Female population aged 15 years and over by total male born, Nauru:2011 Table 39. Female population aged 15 years and over by total female born, Nauru:2011 Table 40. Female population aged 15 years and over and total children ever born, Nauru:2011 Table 41. Female population aged 15 years and over and total male ever born, Nauru:2011 Table 42. Female population aged 15 years and over and total female ever born, Nauru:2011

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

Abstract

The Census is the official count of population, dwellings and households in Tonga and it provides a ‘snapshot’ of the country at one specific point in time: 30th of November 2011. A Tonga census has been taken once in every ten years since 1956. However the population census of 2011 is the first population census by 5 year interval from the previous census in 2006 due to the Electoral Boundary Commission (EBC)'s request according to its Act 2010.

The census provides a unique source of detailed demographic, social and economic data relating the entire population and its most precious resource of its people. This information is used for policy making and planning, monitoring and evaluation, research and other decision-making.

The census is often the primary source of information such as used for allocation of public funding, especially in areas such as health, education and social policy. The main users of this information are the government, local authorities, education facilities (such as schools and tertiary organizations), businesses, community organizations and the public in general.

Geographic coverage

National coverage: the 2011 Tonga Census of Population and Housing cover the whole of the Kingdom of Tonga, which includes every islands of the 5 divisions and in both urban and rural areas.

Analysis unit

Household and Individual.

Universe

The main objective of the census is to record the people in Tonga at one particular point in time, i.e. the night of Wednesday 30th November 2011 or exactly, the 30th November before it changes at midnight to 1st December. All persons alive in Tonga on Census night are to be included. Babies born before midnight on 30th November are to be included and persons who die before midnight on Census night are to be excluded.

Kind of data

Census/enumeration data [cen]

Sampling procedure

There is no sampling for the population census since it is a full enumeration.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaires for the 2011 Tonga Census of Population and Housing were structured based on the one from 2006 Tonga Census of Population and Housing with some modifications and additions. There were mainly two questionnaires, one is the household questionnaire and the other is the personal questionnaire.

The household questionnaire was designed for each household to collect various information of the dwelling's characteristics, housing utilities and durable goods, household waste disposal, information technology, income, remittances and the mortality.

The personal questionnaire includes personal characteristics, migration, disability, smoking habit, education, labour and employment, voting eligibility, and fertility. Some questions has age restrictions like the education and qualification, literacy, smoking habits questions were ask to 5 years and older only. Labour, employment and fertility questions were for 15 years and older only. And the electoral vote questions were eligible only for 22 years and older e.g. for those that turned 21 in November 2010. This questionnaire is split into 3 categories and form 3 questionnaires: 1) Personal Questionnaire: for individual in a household 2) Questionnaire For Institution Tongan Residents: for resident in an institution 3) Personal Questionnaire For Institution Resident (Visitors/Foreigners): for visitor/ foreigner in an institution

All questionnaires were published in both English and Tongan and were both piloted as part of the survey pre-test.

All questionnaires and modules are provided as external resources.

Cleaning operations

Data editing took place at a number of stages throughout the processing, including: 1) Office editing and coding 2) Data entry 3) Structure and completeness checking 4) Verification entry 5) Comparison of verification data 6) Back up of raw data 7) Secondary editing 9) Edited data back up

The software used in processing the data was CSPro 4.1

Abstract

The Estimating the Size of Populations through a Household Survey (EPSHS), sought to assess the feasibility of the network scale-up and proxy respondent methods for estimating the sizes of key populations at higher risk of HIV infection and to compare the results to other estimates of the population sizes. The study was undertaken based on the assumption that if these methods proved to be feasible with a reasonable amount of data collection for making adjustments, countries would be able to add this module to their standard household survey to produce size estimates for their key populations at higher risk of HIV infection. This would facilitate better programmatic responses for prevention and caring for people living with HIV and would improve the understanding of how HIV is being transmitted in the country.

The specific objectives of the ESPHS were: 1. To assess the feasibility of the network scale-up method for estimating the sizes of key populations at higher risk of HIV infection in a Sub-Saharan African context; 2. To assess the feasibility of the proxy respondent method for estimating the sizes of key populations at higher risk of HIV infection in a Sub-Saharan African context; 3. To estimate the population size of MSM, FSW, IDU, and clients of sex workers in Rwanda at a national level; 4. To compare the estimates of the sizes of key populations at higher risk for HIV produced by the network scale-up and proxy respondent methods with estimates produced using other methods; and 5. To collect data to be used in scientific publications comparing the use of the network scale-up method in different national and cultural environments.

Geographic coverage

National

Analysis unit

• Household
• Individual

Sampling procedure

The Estimating the Size of Populations through a Household Survey (ESPHS) used a two-stage sample design, implemented in a representative sample of 2,125 households selected nationwide in which all women and men age 15 years and above where eligible for an individual interview. The sampling frame used was the preparatory frame for the Rwanda Population and Housing Census (RPHC), which was conducted in 2012; it was provided by the National Institute of Statistics of Rwanda (NISR).

The sampling frame was a complete list of natural villages covering the whole country (14,837 villages). Two strata were defined: the city of Kigali and the rest of the country. One hundred and thirty Primary Sampling Units (PSU) were selected from the sampling frame (35 in Kigali and 95 in the other stratum). To reduce clustering effect, only 20 households were selected per cluster in Kigali and 15 in the other clusters. As a result, 33 percent of the households in the sample were located in Kigali.

The list of households in each cluster was updated upon arrival of the survey team in the cluster. Once the listing had been updated, a number was assigned to each existing household in the cluster. The supervisor then identified the households to be interviewed in the survey by using a table in which the households were randomly pre-selected. This table also provided the list of households pre-selected for each of the two different definitions of what it means "to know" someone.

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

Mode of data collection

Face-to-face [f2f]

Research instrument

The Estimating the Size of Populations through a Household Survey (ESPHS) used two types of questionnaires: a household questionnaire and an individual questionnaire. The same individual questionnaire was used to interview both women and men. In addition, two versions of the individual questionnaire were developed, using two different definitions of what it means “to know” someone. Each version of the individual questionnaire was used in half of the selected households.

Cleaning operations

The processing of the ESPHS data began shortly after the fieldwork commenced. Completed questionnaires were returned periodically from the field to the SPH office in Kigali, where they were entered and checked for consistency by data processing personnel who were specially trained for this task. Data were entered using CSPro, a programme specially developed for use in DHS surveys. All data were entered twice (100 percent verification). The concurrent processing of the data was a distinct advantage for data quality, because the School of Public Health had the opportunity to advise field teams of problems detected during data entry. The data entry and editing phase of the survey was completed in late August 2011.

Response rate

A total of 2,125 households were selected in the sample, of which 2,120 were actually occupied at the time of the interview. The number of occupied households successfully interviewed was 2,102, yielding a household response rate of 99 percent.

From the households interviewed, 2,629 women were found to be eligible and 2,567 were interviewed, giving a response rate of 98 percent. Interviews with men covered 2,102 of the eligible 2,149 men, yielding a response rate of 98 percent. The response rates do not significantly vary by type of questionnaire or residence.

Sampling error estimates

The estimates from a sample survey are affected by two types of errors: (1) non-sampling errors, and (2) sampling errors. Non-sampling 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 to minimize this type of error during the implementation of the Rwanda ESPHS 2011, non-sampling 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 ESPHS 2011 is only one of many samples that could have been selected from the same population, using the same design and identical 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 between all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results.

A 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 percent 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 ESPHS 2011 sample is the result of a multi-stage stratified design, and, consequently, it was necessary to use more complex formulae. The computer software used to calculate sampling errors for the ESPHS 2011 is a SAS program. This program uses the Taylor linearization method for variance estimation for survey estimates that are means or proportions.

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

This dataset consists of semi-custom tabulations of the 1971, 1981, 1986, 1991, 1996, 2001, 2006 and 2011 Censuses as well as the 2011 National Household Survey (NHS) containing Census and NHS Profile variables aggregated to 2016 Dissemination Area boundaries for the Toronto and Vancouver CMAs.

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 Post-Apartheid South African government has conducted three Censuses, in 1996, 2001 and 2011.

Geographic coverage

The South African Census 2011 has national coverage.

Analysis unit

Households and individuals

Universe

The South African Census 2011 covered every person present in South Africa on Census Night, 9-31 October 2011 including all de jure household members and residents of institutions.

Kind of data

Census/enumeration data

Sampling procedure

The sampling frame for the PES was the complete list of Census 2011 EAs, amounting to 103 576 EAs. The primary sampling units (PSUs) were the Census EAs. The principle for selecting the PES sample is that the EA boundaries for sampled EAs should have well defined boundaries, and these boundaries should correspond with those of Census EAs to allow for item-by-item comparison between the Census and PES records. The stratification and sampling process followed will allow for the provision of estimates at national, provincial, urban (geography type = urban) and non-urban (geography type = farm and traditional) levels, but estimates will only be reliable at national and provincial levels. The sample of 600 EAs was selected and allocated to the provinces based on expected standard errors which were based on those obtained in PES 2001. Populations in institutions (other than Workers' Hostels), floating and homeless individuals were excluded from the PES sample.

The data files in the dataset include Household, Person, and Mortality files. The 10% sample for the Mortality data file was sampled separately and is not the same as the 10% sample for Household file and Person file.

Mode of data collection

Face-to-face

Research instrument

Three sets of questionnaires were developed for Census 2011: 1. Questionnaire A - the household questionnaire - administed to the population in a household set-up including those households that were found within an institution, such as staff residences 2. Questionnaire B - the population in transit (departing) and those on holiday on reference night (9/10 October 2011). The homeless were also enumerated using this set of questions 3. Questionnaire C - the institutions questionnaire administered to the population in collective living quarters (people who spent census night 9/10 October 2011 at the institution)

A Post-Enumeration Survey was carried out after the census, which used a PES questionnaire.

Sampling error estimates

Comparison of Census 2011 with previous Censuses requires alignment of the data to 2011 municipal boundaries Questions on disability asked in former censuses were replaced in census 2011 with General health and functioning questions. Misreporting on general health and functioning for children younger than five years means data for this variable are only profiled for persons five years and older.

Data appraisal

The dataset does not have a code list for the “geotype” variable which has 3 values (1,2,3).

The American Community Survey (ACS) Public Use Microdata Sample (PUMS) contains a sample of responses to the ACS. The ACS PUMS dataset includes variables for nearly every question on the survey, as well as many new variables that were derived after the fact from multiple survey responses (such as poverty status).Each record in the file represents a single person, or, in the household-level dataset, a single housing unit. In the person-level file, individuals are organized into households, making possible the study of people within the contexts of their families and other household members. Individuals living in Group Quarters, such as nursing facilities or college facilities, are also included on the person file. ACS PUMS data are available at the nation, state, and Public Use Microdata Area (PUMA) levels. PUMAs are special non-overlapping areas that partition each state into contiguous geographic units containing roughly 100,000 people each. ACS PUMS files for an individual year, such as 2019, contain data on approximately one percent of the United States population.

Abstract

The 2011 Mauritius Housing & Population Census will be carried out by the Central Statistics Office in two distinct rounds: the Housing Census from 31 January 2011 to June 2011 followed by the Population Census from 20 June to 31 July 2011 in respect of all persons alive on the night of 3 - 4 July 2011. The main objective of the Housing and Population census is to provide up-to-date and disaggregated data on the housing conditions, the spatial distribution, and the demographic and socio-economic characteristics of the Mauritian population.

Geographic coverage

National

Analysis unit

• Household;
• Indivudual.

Universe

The Housing Census will enumerate all buildings, housing units, households, commercial and industrial establishments, hotels and boarding houses as well as fruit trees of bearing age on residential premises.

The Population Census will enumerate all persons present on census night in all households and communal establishments, as well as usual residents who are away on census night.

Housing and population enumerations will be conducted in the islands of Mauritius, Rodrigues and Agalega.

Kind of data

Census/enumeration data [cen]

Sampling procedure

Census 2011, like the four previous ones, was taken in two distinct rounds: the Housing Census followed by the Population Census four months later. This enumeration procedure was adopted in order to obtain at the Housing Census a list of names and addresses of heads of households which served as frame for the Population Census.

Mode of data collection

Face-to-face [f2f]

Research instrument

4.1 Questionnaire design The questionnaire type, format and contents were determined on the basis of the following factors:

Data to be collected Data collected were in line with UN recommendations and, in addition, catered for local data needs.

Method of enumeration For Census 2011, the questionnaires were completed by enumerators who carried out field interviews.

Data capture and processing techniques The office used scanning and recognition technology for census data capture directly from the questionnaires.

4.2 Contents of questionnaire The questionnaire contents were determined as follows: (i) The data needs of main stakeholders from Government Ministries and Departments were considered. As from 2008, heads of Government Ministries and Departments were invited via a circular letter to submit their requirements for demographic, social and economic data considered essential for administration, planning and policy-making and which could be collected at the census. Topics were retained after considering: - their usefulness to the country; - the cost for data collection and processing - where it is possible by other means to obtain satisfactory information more cheaply, the topic was not selected; and - their suitability for data collection at a Census - sensitive and controversial issues as well as questions that are too complicated or difficult for the average respondent to answer were avoided. (ii) The concepts and questions used for the previous census were examined for relevance and only those found relevant were kept. (iii) The latest “Principles and Recommendations for Population and Housing Censuses” were reviewed to determine whether to add questions or to modify existing questions. (iv) The questions thus arrived at were tested during a pilot census conducted in September 2010. In the light of observations made on the field, some changes were made to the wording and sequence of the questions and a final set of questions adopted. 4.2.1 The Housing Census questionnaire The Housing Census questionnaire covered all topics and items covered at Census 2000; some new items were added for the reasons given in the column “Remarks”.

The questionnaire was designed to cover 1 housing unit, up to two households, up to three planters and 1 commercial/industrial establishment, guest house or tourist residence. More than one questionnaire was used in other cases.

4.2.2 The Population Census questionnaire The 2011 Population Census questionnaire included the topics covered at the 2000 Population Census except that on income. Questions were added on National Identity number of each person as well as on residence for the reasons mentioned in the column “Remarks”.

4.3 Questionnaire layout and size The layout and design of response areas was done to ensure optimum conditions for data capture through scanning and recognition technology. The layout was also influenced by the cost (the number of pages had to be kept to a minimum to cut down on paper, printing and scanning costs) while at the same time ensuring ease of recording the answers on the field.

Cleaning operations

The quality of information collected depends not only on the training of field workers, but also on the day-to-day control and supervision of the fieldwork. Supervisors had to accompany each of their Enumerators in the first visits to ensure that interviews were done according to instructions given and that all concepts were clearly understood. Surprise and pre-arranged field checks as well as re-interviews also helped to increase the reliability of the information collected. Furthermore, Supervisors had to check all completed questionnaires at the early stage of enumeration and later a sample of the completed questionnaires to ensure that the quality of work was satisfactory. Meetings were held regularly to take stock of the field situation and to solve problems met on the field.

All supervisory staff had to record their field activities in provided diaries. The day-today record outlined the activities carried out, the dates and the places at which the activities were carried out, problems encountered and remedial actions taken. The day-to-day recording of activities allowed supervisory staff to follow the progress of work and to assess the performance of each and every staff working under their supervision. Furthermore, it ensured that supervisory control prevailed all along the fieldwork.

Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Data and Documentation section...Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, it is the Census Bureau''s Population Estimates Program that produces and disseminates the official estimates of the population for the nation, states, counties, cities and towns and estimates of housing units for states and counties..Explanation of Symbols:An ''**'' entry in the margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate..An ''-'' entry in the estimate column indicates that either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution..An ''-'' following a median estimate means the median falls in the lowest interval of an open-ended distribution..An ''+'' following a median estimate means the median falls in the upper interval of an open-ended distribution..An ''***'' entry in the margin of error column indicates that the median falls in the lowest interval or upper interval of an open-ended distribution. A statistical test is not appropriate..An ''*****'' entry in the margin of error column indicates that the estimate is controlled. A statistical test for sampling variability is not appropriate. .An ''N'' entry in the estimate and margin of error columns indicates that data for this geographic area cannot be displayed because the number of sample cases is too small..An ''(X)'' means that the estimate is not applicable or not available..Estimates of urban and rural population, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2000 data. Boundaries for urban areas have not been updated since Census 2000. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..While the 2007-2011 American Community Survey (ACS) data generally reflect the December 2009 Office of Management and Budget (OMB) definitions of metropolitan and micropolitan statistical areas; in certain instances the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB definitions due to differences in the effective dates of the geographic entities..Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables..Source: U.S. Census Bureau, 2007-2011 American Community Survey

Abstract copyright UK Data Service and data collection copyright owner.

The General Household Survey (GHS), ran from 1971-2011 (the UKDS holds data from 1972-2011). It was a continuous annual national survey of people living in private households, conducted by the Office for National Statistics (ONS). The main aim of the survey was to collect data on a range of core topics, covering household, family and individual information. This information was used by government departments and other organisations for planning, policy and monitoring purposes, and to present a picture of households, families and people in Great Britain. In 2008, the GHS became a module of the Integrated Household Survey (IHS). In recognition, the survey was renamed the General Lifestyle Survey (GLF). The GLF closed in January 2012. The 2011 GLF is therefore the last in the series. A limited number of questions previously run on the GLF were subsequently included in the Opinions and Lifestyle Survey (OPN).

Secure Access GHS/GLF
The UKDS holds standard access End User Licence (EUL) data for 1972-2006. A Secure Access version is available, covering the years 2000-2011 - see SN 6716 General Lifestyle Survey, 2000-2011: Secure Access.

History
The GHS was conducted annually until 2011, except for breaks in 1997-1998 when the survey was reviewed, and 1999-2000 when the survey was redeveloped. Further information may be found in the ONS document An overview of 40 years of data (General Lifestyle Survey Overview - a report on the 2011 General Lifestyle Survey) (PDF). Details of changes each year may be found in the individual study documentation.

EU-SILC
In 2005, the European Union (EU) made a legal obligation (EU-SILC) for member states to collect additional statistics on income and living conditions. In addition, the EU-SILC data cover poverty and social exclusion. These statistics are used to help plan and monitor European social policy by comparing poverty indicators and changes over time across the EU. The EU-SILC requirement was integrated into the GHS/GLF in 2005. After the closure of the GLF, EU-SILC was collected via the Family Resources Survey (FRS) until the UK left the EU in 2020.

Reformatted GHS data 1973-1982 - Surrey SPSS Files
SPSS files were created by the University of Surrey for all GHS years from 1973 to 1982 inclusive. The early files were restructured and the case changed from the household to the individual with all of the household information duplicated for each individual. The Surrey SPSS files contain all the original variables as well as some extra derived variables (a few variables were omitted from the data files for 1973-76). In 1973 only, the section on leisure was not included in the Surrey SPSS files. This has subsequently been made available, however, and is now held in a separate study, General Household Survey, 1973: Leisure Questions (SN 3982). Records for the original GHS 1973-1982 ASCII files have been removed from the UK Data Archive catalogue, but the data are still preserved and available upon request.

The main GHS consisted of a household questionnaire, completed by the Household Reference Person (HRP), and an individual questionnaire, completed by all adults aged 16 and over resident in the household. A number of different trailers each year covering extra topics were included in later (post-review) surveys in the series from 2000.

• The household questionnaire covered the following topics: household information, accommodation type, housing tenure/costs, and consumer durables including vehicle ownership.
• The individual questionnaire included data from the household dataset, and additional sections on migration/citizenship/national identity/ethnicity, employment, pensions, education, health, child care, smoking, drinking, family information, financial situation, and income.
  

Abstract

The 2011 Ethiopia Demographic and Health Survey (EDHS) was conducted by the Central Statistical Agency (CSA) under the auspices of the Ministry of Health.

The principal objective of the 2011 Ethiopia Demographic and Health Survey (EDHS) is to provide current and reliable data on fertility and family planning behaviour, child mortality, adult and maternal mortality, children’s nutritional status, use of maternal and child health services, knowledge of HIV/AIDS, and prevalence of HIV/AIDS and anaemia. The specific objectives are these: - Collect data at the national level that will allow the calculation of key demographic rates; - Analyse the direct and indirect factors that determine fertility levels and trends; - Measure the levels of contraceptive knowledge and practice of women and men by family planning method, urban-rural residence, and region of the country; - Collect high-quality data on family health, including immunisation coverage among children, prevalence and treatment of diarrhoea and other diseases among children under ge five, and maternity care indicators, including antenatal visits and assistance at delivery; - Collect data on infant and child mortality and maternal mortality; - Obtain data on child feeding practices, including breastfeeding, and collect anthropometric measures to assess the nutritional status of women and children; - Collect data on knowledge and attitudes of women and men about sexually transmitted diseases and HIV/AIDS and evaluate patterns of recent behaviour regarding condom use; - Conduct haemoglobin testing on women age 15-49 and children 6-59 months to provide information on the prevalence of anaemia among these groups; - Carry out anonymous HIV testing on women and men of reproductive age to provide information on the prevalence of HIV.

This information is essential for informed policy decisions, planning, monitoring, and evaluation of programmes on health in general and reproductive health in particular at both the national and regional levels. A long-term objective of the survey is to strengthen the technical capacity of the Central Statistical Agency to plan, conduct, process, and analyse data from complex national population and health surveys.

Moreover, the 2011 EDHS provides national and regional estimates on population and health that are comparable to data collected in similar surveys in other developing countries and to Ethiopia’s two previous DHS surveys, conducted in 2000 and 2005. Data collected in the 2011 EDHS add to the large and growing international database of demographic and health indicators.

The survey was intentionally planned to be fielded at the beginning of the last term of the MDG reporting period to provide data for the assessment of the Millennium Development Goals (MDGs).

The survey interviewed a nationally representative population in about 18,500 households, and all women age 15-49 and all men age 15-59 in these households. In this report key indicators relating to family planning, fertility levels and determinants, fertility preferences, infant, child, adult and maternal mortality, maternal and child health, nutrition, women’s empowerment, and knowledge of HIV/AIDS are provided for the nine regional states and two city administrations. In addition, this report also provides data by urban and rural residence at the country level.

Major stakeholders from various government, non-government, and UN organizations have been involved and have contributed in the technical, managerial, and operational aspects of the survey.

Geographic coverage

A nationally representative sample of 17,817 households was selected.

Universe

All women 15-49 who were usual residents or who slept in the selected households the night before the survey were eligible for the survey. A male survey was also conducted. All men 15-49 who were usual residents or who slept in the selected households the night before the survey were eligible for the male survey.

Kind of data

Sample survey data

Sampling procedure

The sample for the 2011 EDHS was designed to provide population and health indicators at the national (urban and rural) and regional levels. The sample design allowed for specific indicators, such as contraceptive use, to be calculated for each of Ethiopia's 11 geographic/administrative regions (the nine regional states and two city administrations). The 2007 Population and Housing Census, conducted by the CSA, provided the sampling frame from which the 2011 EDHS sample was drawn.

Administratively, regions in Ethiopia are divided into zones, and zones, into administrative units called weredas. Each wereda is further subdivided into the lowest administrative unit, called kebele. During the 2007 census each kebele was subdivided into census enumeration areas (EAs), which were convenient for the implementation of the census. The 2011 EDHS sample was selected using a stratified, two-stage cluster design, and EAs were the sampling units for the first stage. The sample included 624 EAs, 187 in urban areas and 437 in rural areas.

Households comprised the second stage of sampling. A complete listing of households was carried out in each of the 624 selected EAs from September 2010 through January 2011. Sketch maps were drawn for each of the clusters, and all conventional households were listed. The listing excluded institutional living arrangements and collective quarters (e.g., army barracks, hospitals, police camps, and boarding schools). A representative sample of 17,817 households was selected for the 2011 EDHS. Because the sample is not self-weighting at the national level, all data in this report are weighted unless otherwise specified.

In the Somali region, in 18 of the 65 selected EAs listed households were not interviewed for various reasons, such as drought and security problems, and 10 of the 65 selected EAs were not listed due to security reasons. Therefore, the data for Somali may not be totally representative of the region as a whole. However, national-level estimates are not affected, as the percentage of the population in the EAs not covered in the Somali region is proportionally very small.

SAMPLING FRAME

The sampling frame used for 2011 EDHS is the Population and Housing Census (PHC) conducted in 2007 provided by the Central Statistical Agency (CSA, 2008). CSA has an electronic file consisting of 81,654 Enumeration Areas (EA) created for the 2007 census in 10 of its 11 geographic regions. An EA is a geographic area consisting of a convenient number of dwelling units which served as counting unit for the census. The frame file contains information about the location, the type of residence, and the number of residential households for each of the 81,654 EAs. Sketch maps are also available for each EA which delimitate the geographic boundaries of the EA. The 2007 PHC conducted in the Somali region used a different methodology due to difficulty of access. Therefore, the sampling frame for the Somali region is in a different file and in different format. Due to security concerns in the Somali region, in the beginning it was decided that 2011 EDHS would be conducted only in three of nine zones in the Somali region: Shinile, Jijiga, and Liben, same as in the 2000 and 2005 EDHS. However, a later decision was made to include three other zones: Afder, Gode and Warder. This was the first time that these three zones were included in a major nationwide survey such as the 2011 EDHS. The sampling frame for the 2011 EDHS consists of a total of 85,057 EAs.

The sampling frame excluded some special EAs with disputed boundaries. These EAs represent only 0.1% of the total population.

Ethiopia is divided into 11 geographical regions. Each region is sub-divided into zones, each zone into Waredas, each Wareda into towns, and each town into Kebeles. Among the 85,057 EAs, 17,548 (21 percent) are in urban areas and 67,509 (79 percent) are in rural areas. The average size of EA in number of households is 169 in an urban EA and 180 in a rural EA, with an overall average of 178 households per EA. Table A.2 shows the distributions of households in the sampling frame, by region and residence. The data show that 81 percent of the Ethiopia’s households are concentrated in three regions: Amhara, Oromiya and SNNP, while 4 percent of all households are in the five smallest regions: Afar, Benishangul-Gumuz, Gambela, Harari and Dire Dawa.

Mode of data collection

Face-to-face [f2f]

Research instrument

The 2011 EDHS used three questionnaires: the Household Questionnaire, the Woman’s Questionnaire, and the Man’s Questionnaire. These questionnaires were adapted from model survey instruments developed for the MEASURE DHS project to reflect the population and health issues relevant to Ethiopia. Issues were identified at a series of meetings with the various stakeholders. In addition to English, the questionnaires were translated into three major languages—Amharigna, Oromiffa, and Tigrigna.

The Household Questionnaire was used to list all the usual members and visitors of selected households. Basic information was collected on the characteristics of each person listed, including age, sex, education, and relationship to the head of the household. For children under age 18, survival status of the parents was determined. The data on the age and sex of household members obtained in the Household Questionnaire were used to identify women and men who were eligible for the individual interview. The Household Questionnaire also collected information on characteristics of the household’s dwelling unit, such as the source of water, type of toilet facilities, materials used for the floor of the house, and ownership of various consumer