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

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

Version 1.0 - edited; non-anonymized; basis for published reports.

The scope of the 2005 Palau Census of Population and Housing includes collecting, compiling, evaluating, analysing and releasing demographic and housing, economic and social data pertaining to all persons and their living quarters.

• Collection start: 2005
• Collection end: 2005

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

In discussing census objectives, it is useful to distinguish between short-term objectives, which basically entail the delivery of data for immediate uses, and long-term aims which point more towards the infrastructure and capacity building of the statistical system. Long Term Objectives: - The provision and maintenance of a time series of relevant population data at national and sub-national levels. A series of periodic censuses, at regular intervals, is important in assessing trends. The past can be appraised, the present assessed and the future estimated based on benchmark data from censuses. - The development of national capacity to undertake censuses and related statistical activities. Zimbabwe's capability to undertake censuses and surveys has improved over the years. For example, three professionals among those directly involved in the 1992 census are working on the 2002 Census. The long-term objective of capacity building entails: - Developing Central Statistical Office (CSO)'s capacity to produce and to co-ordinate the production and dissemination of relevant, accurate and timely statistics to meet the information needs of various agencies; - Improving its capability to advise other Government departments and agencies involved in the production and dissemination of statistics; - General strengthening of the infrastructure at CSO. In this process the census project constitutes one of the major ways through which such capacity is built. It involves acquisition of significant hardware for various purposes and acquisition of skills by CSO staff through on-the-job training provided by international consultants and formal training through fellowships provided by various agencies. The type of training involved covers a wide range of areas e.g. project planning and implementation, data processing, demographic analysis, sampling techniques, etc. - Provision of a frame for other statistical activities such as the household survey programme. Since 1982, the census has become an important data set for establishing sampling frames and weighting factors for Zimbabwe's National Household Surveys Capability programme. The frame and factors are to be revised after every population census e.g. the 2002 census. It is important to stress this linkage between the census and the survey programme. In essence, the census provides the baseline for the survey programme in terms of maps and household data, which are required in creating the master sample and sub-sample for the survey programme. Immediate Objectives: In general this involves the provision of current information on demographic and related socio-economic characteristics of the population at national level and various sub-national levels to facilitate effective planning and evaluation of various programmes of government, private sector etc. This needs to be performed in a manner that ensures effective application by the various agencies representing the main census data users.

Geographic coverage

National

Analysis unit

• Households
• Individuals
• Persons aged 10 and above
• Women aged 12 - 49

Kind of data

Census/enumeration data [cen]

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaire for the Population Census 2002 is divided into the following sections: A Household identification B Household composition and individual characteristics - For all persons (except questions 12 and 13 for people 15 years and below) C Education - for persons 3 years and older and for persons 3-24 years D Economic activity - for persons 10 years and above E Births - for women aged 12-49 years F Living conditions G Deaths in the household H Total number of persons in the households

The questionnaire is in English, and is provided as external resources.

The Census is the official count of population and dwellings in Tonga, providing a ‘snapshot’ of the society and its most precious resource, its people, at a point in time. The official reference period of the census was midnight, the 30th of November, 2006.

The census provides a unique source of detailed demographic, social and economic data relating the entire population at a single point in time. Census information is used for policy setting and implementation, research, planning and other decision-making. The census is often the primary source of information used for the 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.

The 2006 Census was taken under the authority of Section 8 of Statistical Act Chap. 53 of 1978 which empowers the Minister of Finance to make regulations necessary to conduct the population Census. This regulation was approved by the Cabinet and cited as Census Regulation 2006. The Census regulations also indicate that the Government Statistician would be responsible for the administration and completion of the Census. In addition, the regulations enabled the Statistics Department to carry out the necessary activities required to plan, manage and implement all the necessary Census activities.

Census planning and management

From a planning and management perspective, the Census had two main objectives. Firstly, it was to ensure that the process of collecting, compiling, evaluating, analyzing and disseminating of demographic, economic and social data was conducted in a timely and accurate manner. The development of procedures and processes for the 2006 Census of Population and Housing made use of the lessons learned in previous censuses, and built upon recommendations for improvements.

Secondly, it was a valuable opportunity for building the capacities of employees of the Statistics Department (SD), thus resulting in enhancing the image, credibility and reputation of the Department and at the same time, strengthening its infrastructure. Emphasis was placed on having a senior staff with a wide perspective and leadership qualities. Through the use of vision, planning, coordination, delegation of responsibility and a strong team spirit, the census work was conducted in an effective and efficient manner. Staffs at all levels were encouraged to have an innovative mindset in addressing issues. Incentives for other parties to participate, both within Statistics Department Tonga Tonga 2006 Census of Population and Housing viii and outside the government, were encouraged. As a result, the wider community including donors such as AusAID, the Secretariat of the Pacific Community (SPC) in Noumea, that provided the technical assistance and the general public, were able to support the census project.

Extensive and detailed planning is needed to conduct a successful census. Areas that required planning include: enumeration procedures and fieldwork, public communication, data processing and output systems, mapping and the design of census block boundaries, dissemination procedures, content determination and questionnaire development and training. These aspects, and how they interacted with each other, played a crucial role in determining the quality of all of the census outputs. Each phase therefore required careful, methodical planning and testing. The details of such activities, and their implementation and responsibilities were assigned to 5 subcommittees composed of staff members of the SD.

Organizational structure of the Census

A census organizational structure is designed to implement a number of interrelated activities. Each of these activities was assigned to a specific sub-committee. The census manuals provided guidelines on processes, organizational structures, controls for quality assurance and problem solving. The challenge for managers was developing a work environment that enabled census personnel to perform all these tasks with a common goal in mind. Each sub-committee was responsible for its own outputs, and specific decisions for specific situations were delegated to the lowest level possible. Problem situations beyond the scope of the sub-committee were escalated to the next higher level.

The organizational structure of the census was as follows: a) The Steering Committee (consisting of the Head of both Government and nongovernment organizations), chaired by Secretary for Finance with the Government Statistician (GS) as secretary. b) The Census Committee (consisted of all sub-committee leaders plus the GS, and chaired by the Assistant Government Statistician (AGS) who was the officer in charge of all management and planning of the Census 2006 operations. c) There were five Sub-committees (each sub-committee consisted of about 5 members and were chaired by their Sub-committee leader). These committees included: Mapping, Publicity, Fieldwork, Training and Data Processing. In this way, every staff member of the SD was involved with the census operation through their participation on these committees.

The census steering committee was a high level committee that approved and endorsed the plans and activities of the census. Policy issues that needed to be addressed were submitted to the steering committee for approval prior to the census team and sub-committees designation of the activities necessary to address the tasks.

Part of the initial planning of the 2006 Census involved the establishment of a work-plan with specific time frames. This charted all activities that were to be undertaken and, their impact and dependencies on other activities. These time frames were an essential part of the overall exercise, as they provided specific guides to the progress of each area, and alerted subcommittees’ team leaders (TL) to areas where problems existed and needed to be addressed. These also provided the SD staff with a clear indication of where and how their roles impacted the overall Census process.

Monitoring of the timeframe was an essential part of the management of the Census program. Initially, weekly meetings were held which involved the GS, AGS and team leaders (TL) of the Census committee. As the Census projects progressed, the AGS and TL’s met regularly with their sub-committees to report on the progress of each area. Decisions were made on necessary actions in order to meet the designated dates. Potential risks that could negatively affect the deadlines and actions were also considered at these meetings.

For the 5 sub-committees, one of their first tasks was to verify and amend their terms of reference using the “Strengths, Weaknesses, Opportunities and Threats” (SWOT) analysis methodology, as it applied to past censuses. Each committee then prepared a work-plan and listed all activities for which that particular sub-committee was responsible. This listing included the assignment of a responsible person, together with the timeline indicating the start and end dates required to complete that particular activity. These work-plans, set up by all the 5 sub-committees, were then used by the AGS to develop a detailed operational plan for all phases of the census, the activities required to complete these phases, start and end dates, the person responsible and the dependencies, - all in a Ghant chart format. These combined work-plans were further discussed and amended in the Census team and reported to the Steering committee on regular basis as required.

Version 01 - Edited, cleaned, de-identified and labelled version of the Master file.

The scope of the National Population Census includes personal information on individual characteristics, health, education, literacy, labor market and reproduction.

The scope of the Household module includes information on dwelling style, energy, goods present in the HH, technology, waste, tenure, income, remittances and mortality.

• Collection start: 2006
• Collection end: 2006

What is unique about LA County’s data?It is clipped to the ocean boundary. Raw Census data includes a 3 mile buffer into the ocean, which impacts cartography.IMPORTANT! It has been updated to the 2012 Census Geography Update, which merged Tracts 1370.00 and 9304.01 into the combined tract 1370.00. So the CT10 field actually reflects the 2012 Census update, which is used for all population products 2012 and later.How was this data created?This data was downloaded from Census Bureau website: http://www.census.gov/cgi-bin/geo/shapefiles2010/file-download and clipped to the County Boundary using ESRI’s ArcGIS Desktop. Two new fields were added in census tract data – area in square feet and shape length in feet. This dataset has unique identifier field “GEOID10” for each record and the census tract number fields “CT10” and “LABEL” (6-digit number and 6-digit number with decimal point, respectively).

The once-a-decade decennial census was conducted in April 2010 by the U.S. Census Bureau. This count of every resident in the United States was mandated by Article I, Section 2 of the Constitution and all households in the U.S. and individuals living in group quarters were required by law to respond to the 2010 Census questionnaire. The data collected by the decennial census determine the number of seats each state has in the U.S. House of Representatives and is also used to distribute billions in federal funds to local communities. The questionnaire consisted of a limited number of questions but allowed for the collection of information on the number of people in the household and their relationship to the householder, an individual's age, sex, race and Hispanic ethnicity, the number of housing units and whether those units are owner- or renter-occupied, or vacant. The first wave of results for sub-state geographic areas in New Mexico was released on March 15, 2011, through the Redistricting Data (PL94-171) Summary File. This batch of data covers the state, counties, places (both incorporated and unincorporated communities), tribal lands, school districts, neighborhoods (census tracts and block groups), individual census blocks, and other areas. The Redistricting products provide counts by race and Hispanic ethnicity for the total population and the population 18 years and over, and housing unit counts by occupancy status. The 2010 Census Redistricting Data Summary File can be used to redraw federal, state and local legislative districts under Public Law 94-171. This is an important purpose of the file and, indeed, state officials use the Redistricting Data to realign congressional and state legislative districts in their states, taking into account population shifts since the 2000 Census. More detailed population and housing characteristics will be released in the summer of 2011. The data in these particular RGIS Clearinghouse tables are for all Census Tracts in New Mexico. There are two data tables. One provides total counts by major race groups and by Hispanic ethnicity, while the other provides proportions of the total population for these same groups. These files, along with file-specific descriptions (in Word and text formats) are available in a single zip file.

Abstract copyright UK Data Service and data collection copyright owner.

The Opinions and Lifestyle Survey (OPN) is an omnibus survey that collects data on a range of subjects commissioned by both the ONS internally and external clients (limited to other government departments, charities, non-profit organisations and academia).

Data are collected from one individual aged 16 or over, selected from each sampled private household. Personal data include data on the individual, their family, address, household, income and education, plus responses and opinions on a variety of subjects within commissioned modules.

The questionnaire collects timely data for research and policy analysis evaluation on the social impacts of recent topics of national importance, such as the coronavirus (COVID-19) pandemic and the cost of living, on individuals and households in Great Britain.

From April 2018 to November 2019, the design of the OPN changed from face-to-face to a mixed-mode design (online first with telephone interviewing where necessary). Mixed-mode collection allows respondents to complete the survey more flexibly and provides a more cost-effective service for customers.

In March 2020, the OPN was adapted to become a weekly survey used to collect data on the social impacts of the coronavirus (COVID-19) pandemic on the lives of people of Great Britain. These data are held in the Secure Access study, SN 8635, ONS Opinions and Lifestyle Survey, 2019-2023: Secure Access. Other Secure Access OPN data cover modules run at various points from 1997-2019, on Census religion (SN 8078), cervical cancer screening (SN 8080), contact after separation (SN 8089), contraception (SN 8095), disability (SNs 8680 and 8096), general lifestyle (SN 8092), illness and activity (SN 8094), and non-resident parental contact (SN 8093).

From August 2021, as coronavirus (COVID-19) restrictions were lifting across Great Britain, the OPN moved to fortnightly data collection, sampling around 5,000 households in each survey wave to ensure the survey remains sustainable.

The OPN has since expanded to include questions on other topics of national importance, such as health and the cost of living. For more information about the survey and its methodology, see the ONS OPN Quality and Methodology Information webpage.

Main Topics:
Each month's questionnaire consists of two elements: core questions, covering demographic information, are asked each month together with non-core questions that vary from month to month.

The non-core questions for these months were:

Census Religion (Module MCG): this module was asked on behalf of the Office for National Statistics. The questions aimed to help inform decisions on the final wording of questions in the 2011 Census and covered religion and citizenship.
Census Religion (Module MCGb): this module, also asked on behalf of the Office for National Statistics, is a shortened version of Module MCG which ran in April and May 2009.

This dataset gives a comprehensive view of demographic details from the 2010 Census, zooming in on smaller regions called census tracts, specifically within the City of Carlsbad. It includes important factors like population distribution, racial makeup, family structures, household types, and housing details. Tailored for visualizing and analyzing local demographics, it's especially helpful for understanding trends within specific regions. The dataset aims to support informed decision-making by providing a detailed look at the social and housing landscape at a more localized level within the City of Carlsbad.It's important to note that the original dataset was sourced from the San Diego Geographic Information Source (SANGIS). Initially covering census tracts for the entire San Diego County, we refined the dataset by clipping it to the specific boundary line of the City of Carlsbad. This process was undertaken to tailor the dataset to the unique demographic profile of Carlsbad, making it more pertinent for local analyses and mapping.For additional details and metadata regarding the broader San Diego Countywide layer, it is recommended to visit the SanGIS website. Accessing the metadata on the SANGIS website will provide users with a deeper understanding of the dataset's origins, characteristics, and any additional information relevant to the broader county context.Point of Contact:Point of Contact Operations Manager, Operations Manager U.S. Department of Commerce, U.S. Census Bureau, Geography Division, Geographic Products Branch 4600 Silver Hill Road, Stop 7400 Washington, DC. 20233-7400 geo.tiger@census.gov 301-763-1128

Abstract copyright UK Data Service and data collection copyright owner.

The Opinions and Lifestyle Survey (formerly known as the ONS Opinions Survey or Omnibus) is an omnibus survey that began in 1990, collecting data on a range of subjects commissioned by both the ONS internally and external clients (limited to other government departments, charities, non-profit organisations and academia).

Data are collected from one individual aged 16 or over, selected from each sampled private household. Personal data include data on the individual, their family, address, household, income and education, plus responses and opinions on a variety of subjects within commissioned modules.

The questionnaire collects timely data for research and policy analysis evaluation on the social impacts of recent topics of national importance, such as the coronavirus (COVID-19) pandemic and the cost of living, on individuals and households in Great Britain.

From April 2018 to November 2019, the design of the OPN changed from face-to-face to a mixed-mode design (online first with telephone interviewing where necessary). Mixed-mode collection allows respondents to complete the survey more flexibly and provides a more cost-effective service for customers.

In March 2020, the OPN was adapted to become a weekly survey used to collect data on the social impacts of the coronavirus (COVID-19) pandemic on the lives of people of Great Britain. These data are held in the Secure Access study, SN 8635, ONS Opinions and Lifestyle Survey, Covid-19 Module, 2020-2022: Secure Access.

From August 2021, as coronavirus (COVID-19) restrictions were lifting across Great Britain, the OPN moved to fortnightly data collection, sampling around 5,000 households in each survey wave to ensure the survey remains sustainable.

The OPN has since expanded to include questions on other topics of national importance, such as health and the cost of living. For more information about the survey and its methodology, see the ONS OPN Quality and Methodology Information webpage.

Secure Access Opinions and Lifestyle Survey data

Other Secure Access OPN data cover modules run at various points from 1997-2019, on Census religion (SN 8078), cervical cancer screening (SN 8080), contact after separation (SN 8089), contraception (SN 8095), disability (SNs 8680 and 8096), general lifestyle (SN 8092), illness and activity (SN 8094), and non-resident parental contact (SN 8093). See Opinions and Lifestyle Survey: Secure Access for details.

The objective of the project was to develop a light time budget instrument suitable for use as an add-on component to other surveys, without adding unduly to respondent burden. In the course of the activity, a development programme was undertaken, involving workshops, field-testing of alternative experimental instruments, evaluation and redesign of these, and a full-scale pilot study. The instrument is designed to be used in both self-response and interview completion modes.
Some 2005 Omnibus Survey respondents were asked to provide a retrospective diary-type account on a designated day. The pilot study has thus yielded useful statistical information, sufficient to make broad national estimates of adult time use patterns in the early summer of 1995. The sample is sufficient to make reliable contrasts between broad time use aggregates for subgroups at, for example, a full-time employed woman vs part-time employed woman level. It is too small to make reliable estimates for smaller time use categories and for smaller classificatory categories. Despite the presence of geographic classificatory variables (Standard Regions), the sample size is not sufficiently large to make reliable sub-national estimates of any of the time use categories.
Main Topics:
Each month's questionnaire consists of two elements: core questions, covering demographic information, are asked each month together with non-core questions that vary from month to month.
The non-core questions for this month were:

Time use (module 117): Each case records data for each of the 2005 people surveyed. There are around 100 classificatory variables which have SPSS data labels which are largely self-explanatory. These data were derived by interviewer or self-completion of a questionnaire.
The remaining 96 variables record activities in each of the 96 quarter hour periods throughout the designated day being measured. These data were derived from a self-completion diary, and again the data variables in the SPSS datasets are largely self-explanatory. Respondents were asked to code their major activity in each of the quarter hour periods, according to a coding frame specifying 30 separate activity codes.
Standard Measures: Prevailing Government Standard Socio-Economic Classificatory Variables were...

Abstract copyright UK Data Service and data collection copyright owner.The Opinions and Lifestyle Survey (formerly known as the ONS Opinions Survey or Omnibus) is an omnibus survey that began in 1990, collecting data on a range of subjects commissioned by both the ONS internally and external clients (limited to other government departments, charities, non-profit organisations and academia).Data are collected from one individual aged 16 or over, selected from each sampled private household. Personal data include data on the individual, their family, address, household, income and education, plus responses and opinions on a variety of subjects within commissioned modules. The questionnaire collects timely data for research and policy analysis evaluation on the social impacts of recent topics of national importance, such as the coronavirus (COVID-19) pandemic and the cost of living, on individuals and households in Great Britain. From April 2018 to November 2019, the design of the OPN changed from face-to-face to a mixed-mode design (online first with telephone interviewing where necessary). Mixed-mode collection allows respondents to complete the survey more flexibly and provides a more cost-effective service for customers. In March 2020, the OPN was adapted to become a weekly survey used to collect data on the social impacts of the coronavirus (COVID-19) pandemic on the lives of people of Great Britain. These data are held in the Secure Access study, SN 8635, ONS Opinions and Lifestyle Survey, Covid-19 Module, 2020-2022: Secure Access. From August 2021, as coronavirus (COVID-19) restrictions were lifting across Great Britain, the OPN moved to fortnightly data collection, sampling around 5,000 households in each survey wave to ensure the survey remains sustainable. The OPN has since expanded to include questions on other topics of national importance, such as health and the cost of living. For more information about the survey and its methodology, see the ONS OPN Quality and Methodology Information webpage.Secure Access Opinions and Lifestyle Survey dataOther Secure Access OPN data cover modules run at various points from 1997-2019, on Census religion (SN 8078), cervical cancer screening (SN 8080), contact after separation (SN 8089), contraception (SN 8095), disability (SNs 8680 and 8096), general lifestyle (SN 8092), illness and activity (SN 8094), and non-resident parental contact (SN 8093). See Opinions and Lifestyle Survey: Secure Access for details. The objective of the project was to develop a light time budget instrument suitable for use as an add-on component to other surveys, without adding unduly to respondent burden. In the course of the activity, a development programme was undertaken, involving workshops, field-testing of alternative experimental instruments, evaluation and redesign of these, and a full-scale pilot study. The instrument is designed to be used in both self-response and interview completion modes. Some 2005 Omnibus Survey respondents were asked to provide a retrospective diary-type account on a designated day. The pilot study has thus yielded useful statistical information, sufficient to make broad national estimates of adult time use patterns in the early summer of 1995. The sample is sufficient to make reliable contrasts between broad time use aggregates for subgroups at, for example, a full-time employed woman vs part-time employed woman level. It is too small to make reliable estimates for smaller time use categories and for smaller classificatory categories. Despite the presence of geographic classificatory variables (Standard Regions), the sample size is not sufficiently large to make reliable sub-national estimates of any of the time use categories. Main Topics:Each month's questionnaire consists of two elements: core questions, covering demographic information, are asked each month together with non-core questions that vary from month to month. The non-core questions for this month were: Time use (module 117): Each case records data for each of the 2005 people surveyed. There are around 100 classificatory variables which have SPSS data labels which are largely self-explanatory. These data were derived by interviewer or self-completion of a questionnaire. The remaining 96 variables record activities in each of the 96 quarter hour periods throughout the designated day being measured. These data were derived from a self-completion diary, and again the data variables in the SPSS datasets are largely self-explanatory. Respondents were asked to code their major activity in each of the quarter hour periods, according to a coding frame specifying 30 separate activity codes. Standard Measures: Prevailing Government Standard Socio-Economic Classificatory Variables were used. Multi-stage stratified random sample Self-completion Diaries Face-to-face interview

Abstract

The Census is the official count of population and dwellings in Tonga, providing a ‘snapshot’ of the society and its most precious resource, its people, at a point in time. The official reference period of the census was midnight, the 30th of November, 2006.

The census provides a unique source of detailed demographic, social and economic data relating the entire population at a single point in time. Census information is used for policy setting and implementation, research, planning and other decision-making. The census is often the primary source of information used for the 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.

The 2006 Census was taken under the authority of Section 8 of Statistical Act Chap. 53 of 1978 which empowers the Minister of Finance to make regulations necessary to conduct the population Census. This regulation was approved by the Cabinet and cited as Census Regulation 2006. The Census regulations also indicate that the Government Statistician would be responsible for the administration and completion of the Census. In addition, the regulations enabled the Statistics Department to carry out the necessary activities required to plan, manage and implement all the necessary Census activities.

Census Planning and Management From a planning and management perspective, the Census had two main objectives. Firstly, it was to ensure that the process of collecting, compiling, evaluating, analyzing and disseminating of demographic, economic and social data was conducted in a timely and accurate manner. The development of procedures and processes for the 2006 Census of Population and Housing made use of the lessons learned in previous censuses, and built upon recommendations for improvements.

Secondly, it was a valuable opportunity for building the capacities of employees of the Statistics Department (SD), thus resulting in enhancing the image, credibility and reputation of the Department and at the same time, strengthening its infrastructure. Emphasis was placed on having a senior staff with a wide perspective and leadership qualities. Through the use of vision, planning, coordination, delegation of responsibility and a strong team spirit, the census work was conducted in an effective and efficient manner. Staffs at all levels were encouraged to have an innovative mindset in addressing issues. Incentives for other parties to participate, both within Statistics Department Tonga Tonga 2006 Census of Population and Housing viii and outside the government, were encouraged. As a result, the wider community including donors such as AusAID, the Secretariat of the Pacific Community (SPC) in Noumea, that provided the technical assistance and the general public, were able to support the census project.

Extensive and detailed planning is needed to conduct a successful census. Areas that required planning include: enumeration procedures and fieldwork, public communication, data processing and output systems, mapping and the design of census block boundaries, dissemination procedures, content determination and questionnaire development and training. These aspects, and how they interacted with each other, played a crucial role in determining the quality of all of the census outputs. Each phase therefore required careful, methodical planning and testing. The details of such activities, and their implementation and responsibilities were assigned to 5 subcommittees composed of staff members of the SD.

Organizational Structure of the Census A census organizational structure is designed to implement a number of interrelated activities. Each of these activities was assigned to a specific sub-committee. The census manuals provided guidelines on processes, organizational structures, controls for quality assurance and problem solving. The challenge for managers was developing a work environment that enabled census personnel to perform all these tasks with a common goal in mind. Each sub-committee was responsible for its own outputs, and specific decisions for specific situations were delegated to the lowest level possible. Problem situations beyond the scope of the sub-committee were escalated to the next higher level.

The organizational structure of the census was as follows: a) The Steering Committee (consisting of the Head of both Government and nongovernment organizations), chaired by Secretary for Finance with the Government Statistician (GS) as secretary. b) The Census Committee (consisted of all sub-committee leaders plus the GS, and chaired by the Assistant Government Statistician (AGS) who was the officer in charge of all management and planning of the Census 2006 operations. c) There were five Sub-committees (each sub-committee consisted of about 5 members and were chaired by their Sub-committee leader). These committees included: Mapping, Publicity, Fieldwork, Training and Data Processing. In this way, every staff member of the SD was involved with the census operation through their participation on these committees.

The census steering committee was a high level committee that approved and endorsed the plans and activities of the census. Policy issues that needed to be addressed were submitted to the steering committee for approval prior to the census team and sub-committees designation of the activities necessary to address the tasks.

Part of the initial planning of the 2006 Census involved the establishment of a work-plan with specific time frames. This charted all activities that were to be undertaken and, their impact and dependencies on other activities. These time frames were an essential part of the overall exercise, as they provided specific guides to the progress of each area, and alerted subcommittees’ team leaders (TL) to areas where problems existed and needed to be addressed. These also provided the SD staff with a clear indication of where and how their roles impacted the overall Census process.

Monitoring of the timeframe was an essential part of the management of the Census program. Initially, weekly meetings were held which involved the GS, AGS and team leaders (TL) of the Census committee. As the Census projects progressed, the AGS and TL’s met regularly with their sub-committees to report on the progress of each area. Decisions were made on necessary actions in order to meet the designated dates. Potential risks that could negatively affect the deadlines and actions were also considered at these meetings.

For the 5 sub-committees, one of their first tasks was to verify and amend their terms of reference using the “Strengths, Weaknesses, Opportunities and Threats” (SWOT) analysis methodology, as it applied to past censuses. Each committee then prepared a work-plan and listed all activities for which that particular sub-committee was responsible. This listing included the assignment of a responsible person, together with the timeline indicating the start and end dates required to complete that particular activity. These work-plans, set up by all the 5 sub-committees, were then used by the AGS to develop a detailed operational plan for all phases of the census, the activities required to complete these phases, start and end dates, the person responsible and the dependencies, - all in a Ghant chart format. These combined work-plans were further discussed and amended in the Census team and reported to the Steering committee on regular basis as required.

Geographic coverage

The Population Census covers the whole of the Kingdom of Tonga, which includes the 5 Divisions and both Urban and Rural Areas.

Analysis unit

Individuals, families and private households

Universe

All individuals in private and institutional households.

Kind of data

Census/enumeration data [cen]

Sampling procedure

The National Population Census was a complete enumeration census, hence no sampling procedure was employed. A Mapping Sub-committee was formed to ensure complete coverage of the country.

The Mapping Sub-committee Led by Mr. Winston Fainga'anuku, this committee's mandate was to ensure that good quality maps were produced. The objective was to ensure that the maps provided complete coverage of the country, were designed to accommodate a reasonable workload of one census enumerator and, that geographic identifiers could be used for dissemination purposes by the PopGIS system. Collaborations with the Ministry of Land, Survey and Natural Resources (MLSNR) began in 2004 to ensure that digitized maps for Tonga could be used for 2006 Census. Mr. Fainga'anuku was attached to the MLSNR in April 2005 to assist 'Atelea Kautoke, Samuela Mailau, Lilika and others to complete the task of digitizing the maps for Tonga. In addition, frequent visits by Mr. Scott Pontifex from the Secretariat of the Pacific Community (SPC) in Noumea, assisted to ensure that quality digitized maps were prepared. SPC also assisted by lending its digitizer which was used in this mapping project. The staff of the Statistics Department (SD) visited household sites throughout Tongatapu and the main outer islands. This exercise was to redesign the Census Block boundaries by amalgamating or splitting existing census blocks to achieve an average of 50 households per census block. Various updates within the census block maps were made. These included the names of the head of household; roads and other landmarks to ensure that current and accurate information was provided to the enumerators. Reliable maps, both for enumerators and supervisors are necessary ingredients to assist in

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Abstract

This data is from a quantitative survey administered in 2023 to 2,000 married Nepali women and men from 4 provinces in the country about their own beliefs regarding norms-related behaviors, their expectations of how common it is for others in their social group to engage in those behaviors, and the expected social consequences surrounding those behaviors. It is the primary dataset used to author the working paper titled "Women’s Labor Force Participation in Nepal: An Exploration of The Role of Social Norms" - which presents rigorous evidence on whether and the extent to which social norms matter for women's labor force participation in Nepal.

Geographic coverage

The survey data includes a representative sample of households from 4 out of 7 provinces in Nepal: 1. Bagmati Province 2. Sudurpashchim Province 3. Madhesh Province 4. Gandaki Province

Analysis unit

Individual

Universe

The sampling frame is a list of all wards within each selected province.

Kind of data

Sample survey data [ssd]

Sampling procedure

Ward (cluster) selection: The sampling frame consisted of the list of all wards within each selected province. Each province comprises districts and within each district are municipalities (urban and rural municipalities) which are further broken down into wards – the smallest administrative units. The list of wards and their population figures were taken from the latest available 2021 Census. First, the universe of all districts was stratified by urban and rural to ensure greater statistical power for detecting differences between the 2 localities. The stratification by urban-rural proportionate to the population proportion of each group within a province resulted in a self-weighted sample, allowing for analysis of data at the province level and further at locality level within each province. To select the wards, a random start point was generated to negate any bias in the list and to provide an independent chance of selection from the list. The sampling method used here, probability proportionate to size (PPS), gives an independent chance of selection to each ward as per its population size, i.e., a higher chance of selection to wards with a higher population size.38 As a first step of random selection of wards, the cumulative frequency (CF) of the population of households in a ward was calculated. Since the unit of analysis for our study purpose was households having certain criteria and we expected the main outcome variables (social norms) to vary at household levels (as opposed to at an individual level), the household population figures served as the basis for sampling purpose (as opposed to the population size of individuals for a ward). Applying PPS, in the first step, the required number of wards were selected for Categories 1 and 2 households (households with working and non-working females respectively). Following this, the clusters allocated for Category 3 (households with migrant population) households were taken as a subset of the wards selected for Categories 1 and 2.

Selection of the random starting point within each ward during in-field random sampling of households: The selection of the random starting point within a PSU was done by the survey supervisors. For every ward, a predefined landmark for the starting point was chosen. The predefined landmark consisted of i) school, ii) health post, iii) central marketplace, or iv) ward office. The selection of a predefined landmark was the basis of the starting point which was made at the central office. The chosen landmark for every cluster was rotated to account for randomization and to avoid interviewer bias. Once the landmark was chosen, each enumerator used the spin-the-bottle method to randomize the direction in which the survey took place. After starting with a household, enumerators used a skip interval to survey every third household in rural and every fifth household in urban areas. Once the household was chosen, the interviewer used the screener to ascertain the eligibility as per the category quota set aside for them.

Respondent selection: The respondents were selected based on a screener instrument that surveyed the following factors: 1. Gender: Since the views about social norms and labor market outcomes vary by gender, both males and females within a household were interviewed. However, for households with migrant men, only the women were interviewed. 2. Age group: For all women, the screener was applied so as to ensure that only women within the economically active age range, i.e., between the ages of 18-59 years were interviewed. For spouses of female respondents, they had to be at least 18 years of age with no maximum age limit set. 3. Ethnicity: Nepal has more than a hundred ethnic groups residing across the country, and thus the major 8-10 groups are captured in the sample. The other objective of applying a screener for monitoring ethnic composition was to ensure that marginalized ethnic groups such as Dalits were sufficiently represented in the survey. 4. Marital Status: Only married men and women were interviewed since marriage and the responsibilities that come with are sown to impose greater social barriers and restrictions on mobility and work of females. 5. Location: The survey was carried out in both rural and urban locations in a total of 4 provinces. 6. General demographic factors include: • Perceived economic situation: Low to middle-income • It was ensured that both the respondents (male and female for Categories 1 and 2) and female respondent for Category 3 belonged to the second generation of the selected household (for example, not the in-laws residing in a household but their son and his wife.

Mode of data collection

Computer Assisted Personal Interview [capi]

Abstract copyright UK Data Service and data collection copyright owner.

The Opinions and Lifestyle Survey (OPN) is an omnibus survey that collects data on a range of subjects commissioned by both the ONS internally and external clients (limited to other government departments, charities, non-profit organisations and academia).

Data are collected from one individual aged 16 or over, selected from each sampled private household. Personal data include data on the individual, their family, address, household, income and education, plus responses and opinions on a variety of subjects within commissioned modules.

The questionnaire collects timely data for research and policy analysis evaluation on the social impacts of recent topics of national importance, such as the coronavirus (COVID-19) pandemic and the cost of living, on individuals and households in Great Britain.

From April 2018 to November 2019, the design of the OPN changed from face-to-face to a mixed-mode design (online first with telephone interviewing where necessary). Mixed-mode collection allows respondents to complete the survey more flexibly and provides a more cost-effective service for customers.

In March 2020, the OPN was adapted to become a weekly survey used to collect data on the social impacts of the coronavirus (COVID-19) pandemic on the lives of people of Great Britain. These data are held in the Secure Access study, SN 8635, ONS Opinions and Lifestyle Survey, 2019-2023: Secure Access. Other Secure Access OPN data cover modules run at various points from 1997-2019, on Census religion (SN 8078), cervical cancer screening (SN 8080), contact after separation (SN 8089), contraception (SN 8095), disability (SNs 8680 and 8096), general lifestyle (SN 8092), illness and activity (SN 8094), and non-resident parental contact (SN 8093).

From August 2021, as coronavirus (COVID-19) restrictions were lifting across Great Britain, the OPN moved to fortnightly data collection, sampling around 5,000 households in each survey wave to ensure the survey remains sustainable.

The OPN has since expanded to include questions on other topics of national importance, such as health and the cost of living. For more information about the survey and its methodology, see the ONS OPN Quality and Methodology Information webpage.

ONS Opinions and Lifestyle Survey, 2019-2023: Secure Access

The aim of the COVID-19 Module within this study was to help understand the impact of the coronavirus (COVID-19) pandemic on people, households and communities in Great Britain. It was a weekly survey initiated in March 2020, and since August 2021, as COVID-19 restrictions were lifted, the survey has moved to fortnightly data collection, sampling around 5,000 households in each survey wave. The study allows the breakdown of impacts by at-risk age, gender and underlying health condition. The samples are randomly selected from those that had previously completed other ONS surveys (e.g., Labour Market Survey, Annual Population Survey). From each household, one adult is randomly selected but with unequal probability: younger people are given a higher selection probability than older people because of under-estimation in the samples available for the survey.

The study also includes data for the Internet Access Module from 2019 onwards. Data from this module for previous years are available as End User Licence studies within GN 33441. Also included are data from the Winter Lifestyle Survey for January and February 2023.

Latest edition information

For the eleventh edition (March 2024), data and documentation for the main OPN survey for waves DN (June 2023) to EB (December 2023) have been added. Data and documentation for the Winter Lifestyle Survey for January-February 2023 have also been added.

Main Topics:
Each month's questionnaire consists of two elements: core questions, covering demographic information, are asked each month together with non-core questions that vary from month to month.

The questions and topics covered by the main OPN survey have changed over time. Topics covered have included:

• health conditions
• concerns about work
• working from home
  
• understanding information about COVID-19
• actions undertaken to prevent the spread of the virus
• coping whilst staying at home and community support networks
• indicators of well-being and loneliness
• ways pandemic has effected life, work and finances
  
• caring responsibilities
• returning to school or college
  
• leaving home
• modes of transport used
• cost of living
  
• problems with companies
• vaccinations
  
• individual characteristics (e.g., age, gender, health conditions, qualifications, ethnicity, employment,...

This layer was developed by the Research & Analytics Division of the Atlanta Regional Commission using data from the U.S. Census Bureau.

The user should note that American Community Survey data represent estimates derived from a surveyed sample of the population, which creates some level of uncertainty, as opposed to an exact measure of the entire population (the full census count is only conducted once every 10 years and does not cover as many detailed characteristics of the population). Therefore, any measure reported by ACS should not be taken as an exact number – this is why a corresponding margin of error (MOE) is also given for ACS measures. The size of the MOE relative to its corresponding estimate value provides an indication of confidence in the accuracy of each estimate. Each MOE is expressed in the same units as its corresponding measure; for example, if the estimate value is expressed as a number, then its MOE will also be a number; if the estimate value is expressed as a percent, then its MOE will also be a percent.

The user should also note that for relatively small geographic areas, such as census tracts shown here, ACS only releases combined 5-year estimates, meaning these estimates represent rolling averages of survey results that were collected over a 5-year span (in this case 2014-2018). Therefore, these data do not represent any one specific point in time or even one specific year. For geographic areas with larger populations, 3-year and 1-year estimates are also available.

For a deep dive into the data model including every specific metric, see the Infrastructure Manifest. The manifest details ARC-defined naming conventions, field names/descriptions and topics, summary levels; source tables; notes and so forth for all metrics.

For further explanation of ACS estimates and margin of error, visit Census ACS website.

Naming conventions:

Prefixes:

None

Count

p

Percent

r

Rate

m

Median

a

Mean (average)

t

Aggregate (total)

ch

Change in absolute terms (value in t2 - value in t1)

pch

Percent change ((value in t2 - value in t1) / value in t1)

chp

Change in percent (percent in t2 - percent in t1)

s

Significance flag for change: 1 = statistically significant with a 90% Confidence Interval, 0 = not statistically significant, blank = cannot be computed

Suffixes:

_e18

Estimate from 2014-18 ACS

_m18

Margin of Error from 2014-18 ACS

_00_v18

Decennial 2000 in 2018 geography boundary

_00_18

Change, 2000-18

_e10_v18

Estimate from 2006-10 ACS in 2018 geography boundary

_m10_v18

Margin of Error from 2006-10 ACS in 2018 geography boundary

_e10_18

Change, 2010-18

Abstract copyright UK Data Service and data collection copyright owner.The Opinions and Lifestyle Survey (OPN) is an omnibus survey that collects data on a range of subjects commissioned by both the ONS internally and external clients (limited to other government departments, charities, non-profit organisations and academia). Data are collected from one individual aged 16 or over, selected from each sampled private household. Personal data include data on the individual, their family, address, household, income and education, plus responses and opinions on a variety of subjects within commissioned modules. The questionnaire collects timely data for research and policy analysis evaluation on the social impacts of recent topics of national importance, such as the coronavirus (COVID-19) pandemic and the cost of living, on individuals and households in Great Britain. From April 2018 to November 2019, the design of the OPN changed from face-to-face to a mixed-mode design (online first with telephone interviewing where necessary). Mixed-mode collection allows respondents to complete the survey more flexibly and provides a more cost-effective service for customers. In March 2020, the OPN was adapted to become a weekly survey used to collect data on the social impacts of the coronavirus (COVID-19) pandemic on the lives of people of Great Britain. These data are held in the Secure Access study, SN 8635, ONS Opinions and Lifestyle Survey, 2019-2023: Secure Access. Other Secure Access OPN data cover modules run at various points from 1997-2019, on Census religion (SN 8078), cervical cancer screening (SN 8080), contact after separation (SN 8089), contraception (SN 8095), disability (SNs 8680 and 8096), general lifestyle (SN 8092), illness and activity (SN 8094), and non-resident parental contact (SN 8093).From August 2021, as coronavirus (COVID-19) restrictions were lifting across Great Britain, the OPN moved to fortnightly data collection, sampling around 5,000 households in each survey wave to ensure the survey remains sustainable. The OPN has since expanded to include questions on other topics of national importance, such as health and the cost of living. For more information about the survey and its methodology, see the ONS OPN Quality and Methodology Information webpage. ONS Opinions and Lifestyle Survey, 2019-2023: Secure AccessThe aim of the COVID-19 Module within this study was to help understand the impact of the coronavirus (COVID-19) pandemic on people, households and communities in Great Britain. It was a weekly survey initiated in March 2020, and since August 2021, as COVID-19 restrictions were lifted, the survey has moved to fortnightly data collection, sampling around 5,000 households in each survey wave. The study allows the breakdown of impacts by at-risk age, gender and underlying health condition. The samples are randomly selected from those that had previously completed other ONS surveys (e.g., Labour Market Survey, Annual Population Survey). From each household, one adult is randomly selected but with unequal probability: younger people are given a higher selection probability than older people because of under-estimation in the samples available for the survey.The study also includes data for the Internet Access Module from 2019 onwards. Data from this module for previous years are available as End User Licence studies within GN 33441. Also included are data from the Winter Lifestyle Survey for January and February 2023.Latest edition informationFor the eleventh edition (March 2024), data and documentation for the main OPN survey for waves DN (June 2023) to EB (December 2023) have been added. Data and documentation for the Winter Lifestyle Survey for January-February 2023 have also been added. Main Topics:Each month's questionnaire consists of two elements: core questions, covering demographic information, are asked each month together with non-core questions that vary from month to month.

This layer was developed by the Research & Analytics Division of the Atlanta Regional Commission using data from the U.S. Census Bureau.

The user should note that American Community Survey data represent estimates derived from a surveyed sample of the population, which creates some level of uncertainty, as opposed to an exact measure of the entire population (the full census count is only conducted once every 10 years and does not cover as many detailed characteristics of the population). Therefore, any measure reported by ACS should not be taken as an exact number – this is why a corresponding margin of error (MOE) is also given for ACS measures. The size of the MOE relative to its corresponding estimate value provides an indication of confidence in the accuracy of each estimate. Each MOE is expressed in the same units as its corresponding measure; for example, if the estimate value is expressed as a number, then its MOE will also be a number; if the estimate value is expressed as a percent, then its MOE will also be a percent.

The user should also note that for relatively small geographic areas, such as census tracts shown here, ACS only releases combined 5-year estimates, meaning these estimates represent rolling averages of survey results that were collected over a 5-year span (in this case 2014-2018). Therefore, these data do not represent any one specific point in time or even one specific year. For geographic areas with larger populations, 3-year and 1-year estimates are also available.

For a deep dive into the data model including every specific metric, see the Infrastructure Manifest. The manifest details ARC-defined naming conventions, field names/descriptions and topics, summary levels; source tables; notes and so forth for all metrics.

For further explanation of ACS estimates and margin of error, visit Census ACS website.

Naming conventions:

Prefixes:

None

Count

p

Percent

r

Rate

m

Median

a

Mean (average)

t

Aggregate (total)

ch

Change in absolute terms (value in t2 - value in t1)

pch

Percent change ((value in t2 - value in t1) / value in t1)

chp

Change in percent (percent in t2 - percent in t1)

s

Significance flag for change: 1 = statistically significant with a 90% Confidence Interval, 0 = not statistically significant, blank = cannot be computed

Suffixes:

_e18

Estimate from 2014-18 ACS

_m18

Margin of Error from 2014-18 ACS

_00_v18

Decennial 2000 in 2018 geography boundary

_00_18

Change, 2000-18

_e10_v18

Estimate from 2006-10 ACS in 2018 geography boundary

_m10_v18

Margin of Error from 2006-10 ACS in 2018 geography boundary

_e10_18

Change, 2010-18

Abstract

The Census provides a unique source of detailed demographic, social and economic data relating to the entire population at a single point in time. The most fundamental questions it will answer concern the size and distribution of the entire population, the extent to which men and women participate in the economy, and the nature of housing and household facilities.

Our country is constantly changing and information collected will allow policy planners to measure the developments of our society and to make decisions about future needs of our communities. Emphasis for the CPD is on renewable energy. Government has set itself policy goals that by 2015, 50 percent of Cook Islands electricity demand will be provided by renewable energy and 100 percent in 2020. Culture has also been identified as a priority of Government.

The topic content of the 2011 Census has been driven principally by the demands and requirements of users of census statistics, the evaluation of the 2006 Census, and the priorities of the Government as stated in its manifesto, and the advice and guidance of organisations with experience of similar operations. These have been determined by extensive consultations with various Ministries of government and non government organizations (NGO).

The topics proposed for the census are those most needed by the major users of census information and questions have been devised to produce reliable and accurate data. In each case, no other comparable and accessible source of the information is available in combination with other items in the census.

In assessing which topics should be included in the census, Statistics Office has had to consider a number of factors. The criteria for evaluating the strength of users' requirements for information were that:

· there should be a clearly demonstrated and significant need · the information collected was of major national importance · users' requirements could not adequately be met by information from other sources · there should be a requirement for multivariate analysis (that is the ability to cross-analyze one variable against other), and · there should be consideration of the ability for comparison with the 2006 Census wherever possible

Geographic coverage

National coverage.

Analysis unit

-Household -Individual.

Universe

A Dwelling Questionnaire must be completed for every occupied dwelling as at midnight on Census Night. A Personal Questionnaire must be completed for each and every man, woman and child alive at midnight on Census Night within the geographical boundaries of the Cook Islands, excluding those persons on foreign vessels, yachts and aircraft flying through or stopping temporarily (transit).

Kind of data

Census/enumeration data [cen]

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaire which was published in English, can be found as External Resources.

The questionnaire of the early Cook Islands censuses was limited; they consisted oh head counts only. With the passage of time, the topics covered by the questionnaires expanded. Gradually, questions on sex, age, marital status, religion, education, employment, etc have been included. Questions on unpaid work and income earned were included for the first time in the 1996 Census. In the 2011 Census, questions on renewable energy and culture was included.

The questionnaire of the 2011 Census of Cook Islands is divided into 2 main forms: -Dwelling form: which covers topics like: Household characteristics, water supply, energy, toilet, tradition, communication & technology, waste management, involvment in agriculture, fishing, farming, equipment, transport. -Personal form: which covers topics like: Individual characteristics, disability, literacy and language, information & technology, education, economic activity, income, narcotics, cultural activities and fertility.

SELECTION OF TOPICS AND QUESTIONS: The topic content of the 2011 Census has been driven principally by the demands and requirements of users of census statistics, the evaluation of the 2006 Census, and the priority of government as stated in this Governments Manifesto, and the advice and guidance of organizations with experience of similar operations. These have been determined by extensive consultation with various Ministries of government and NGO's. Emphasis for this Census was on Renewable Energy and Cultural Statistics. Government had set itself a policy goal that 50 percent of its electricity demands to be provided by renewable energy in 2015 and 100 percent in 2020.

The 2011 Census questionnaire is designed to be machine readable that is questionnaires will be scanned.

This dataset was developed by the Research & Analytics Group at the Atlanta Regional Commission using data from the U.S. Census Bureau across all standard and custom geographies at statewide summary level where applicable.

For a deep dive into the data model including every specific metric, see the ACS 2016-2020 Data Manifest. The manifest details ARC-defined naming conventions, field names/descriptions and topics, summary levels; source tables; notes and so forth for all metrics.

Prefixes:

None

Count

p

Percent

r

Rate

m

Median

a

Mean (average)

t

Aggregate (total)

ch

Change in absolute terms (value in t2 - value in t1)

pch

Percent change ((value in t2 - value in t1) / value in t1)

chp

Change in percent (percent in t2 - percent in t1)

s

Significance flag for change: 1 = statistically significant with a 90% CI, 0 = not statistically significant, blank = cannot be computed

Suffixes:

_e20

Estimate from 2016-20 ACS

_m20

Margin of Error from 2016-20 ACS

_e10

2006-10 ACS, re-estimated to 2020 geography

_m10

Margin of Error from 2006-10 ACS, re-estimated to 2020 geography

_e10_20

Change, 2010-20 (holding constant at 2020 geography)

Geographies

AAA = Area Agency on Aging (12 geographic units formed from counties providing statewide coverage)

ARWDB7 = Atlanta Regional Workforce Development Board (7 counties merged to a single geographic unit)

Census Tracts (statewide)

CFGA23 = Community Foundation for Greater Atlanta (23 counties merged to a single geographic unit)

City (statewide)

City of Atlanta Council Districts (City of Atlanta)

City of Atlanta Neighborhood Planning Unit (City of Atlanta)

City of Atlanta Neighborhood Planning Unit STV (subarea of City of Atlanta)

City of Atlanta Neighborhood Statistical Areas (City of Atlanta)

County (statewide)

Georgia House (statewide)

Georgia Senate (statewide)

MetroWater15 = Atlanta Metropolitan Water District (15 counties merged to a single geographic unit)

Regional Commissions (statewide)

State of Georgia (statewide)

Superdistrict (ARC region)

US Congress (statewide)

UWGA13 = United Way of Greater Atlanta (13 counties merged to a single geographic unit)

WFF = Westside Future Fund (subarea of City of Atlanta)

ZIP Code Tabulation Areas (statewide)

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The user should also note that for relatively small geographic areas, such as census tracts shown here, ACS only releases combined 5-year estimates, meaning these estimates represent rolling averages of survey results that were collected over a 5-year span (in this case 2016-2020). Therefore, these data do not represent any one specific point in time or even one specific year. For geographic areas with larger populations, 3-year and 1-year estimates are also available.

For further explanation of ACS estimates and margin of error, visit Census ACS website.

Source: U.S. Census Bureau, Atlanta Regional Commission Date: 2016-2020 Data License: Creative Commons Attribution 4.0 International (CC by 4.0)

Link to the manifest: https://opendata.atlantaregional.com/documents/GARC::acs-2020-data-manifest/about

Abstract

The Sudan Demographic and Health Survey (SDHS) was conducted in two phases between November 15, 1989 and May 21, 1990 by the Department of Statistics of the Ministry of Economic and National Planning. The survey collected information on fertility levels, marriage patterns, reproductive intentions, knowledge and use of contraception, maternal and child health, maternal mortality, and female circumcision. The survey findings provide the National Population Committee and the Ministry of Health with valuable information for use in evaluating population policy and planning public health programmes.

A total of 5860 ever-married women age 15-49 were interviewed in six regions in northern Sudan; three regions in southern Sudan could not be included in the survey because of civil unrest in that part of the country. The SDHS provides data on fertility and mortality comparable to the 1978-79 Sudan Fertility Survey (SFS) and complements the information collected in the 1983 census.

The primary objective of the SDHS was to provide data on fertility, nuptiality, family planning, fertility preferences, childhood mortality, indicators of maternal health care, and utilization of child health services. Additional information was coUected on educational level, literacy, source of household water, and other housing conditions.

The SDHS is intended to serve as a source of demographic data for comparison with the 1983 census and the Sudan Fertility Survey (SFS) 1978-79, and to provide population and health data for policymakers and researchers. The objectives of the survey are to: - assess the overall demographic situation in Sudan, - assist in the evaluation of population and health programmes, - assist the Department of Statistics in strengthening and improving its technical skills for conducting demographic and health surveys, - enable the National Population Committee (NPC) to develop a population policy for the country, and - measure changes in fertility and contraceptive prevalence, and study the factors which affect these changes, and - examine the basic indicators of maternal and child health in Sudan.

MAIN RESULTS

Fertility levels and trends

Fertility has declined sharply in Sudan, from an average of six children per women in the Sudan Fertility Survey (TFR 6.0) to five children in the Sudan DHS survey flTR 5.0). Women living in urban areas have lower fertility (TFR 4.1) than those in rural areas (5.6), and fertility is lower in the Khartoum and Northern regions than in other regions. The difference in fertility by education is particularly striking; at current rates, women who have attained secondary school education will have an average of 3.3 children compared with 5.9 children for women with no education, a difference of almost three children.

Although fertility in Sudan is low compared with most sub-Saharan countries, the desire for children is strong. One in three currently married women wants to have another child within two years and the same proportion want another child in two or more years; only one in four married women wants to stop childbearing. The proportion of women who want no more children increases with family size and age. The average ideal family size, 5.9 children, exceeds the total fertility rate (5.0) by approximately one child. Older women are more likely to want large families than younger women, and women just beginning their families say they want to have about five children.

Marriage

Almost all Sudanese women marry during their lifetime. At the time of the survey, 55 percent of women 15-49 were currently married and 5 percent were widowed or divorced. Nearly one in five currently married women lives in a polygynous union (i.e., is married to a man who has more than one wife). The prevalence of polygyny is about the same in the SDHS as it was in the Sudan Fertility Survey.

Marriage occurs at a fairly young age, although there is a trend toward later marriage among younger women (especially those with junior secondary or higher level of schooling). The proportion of women 15-49 who have never married is 12 percentage points higher in the SDHS than in the Sudan Fertiliy Survey.

There has been a substantial increase in the average age at first marriage in Sudan. Among SDHS. Since age at first marriage is closely associated with fertility, it is likely that fertility will decrease in the future. With marriages occurring later, women am having their first birth at a later age. While one in three women age 45-49 had her first birth before age 18, only one in six women age 20-24 began childbearing prior to age 18. The women most likely to postpone marriage and childbearing are those who live in urban areas ur in the Khartoum and Northern regions, and women with pest-primary education.

Breastfeeding and postpartum abstinence

Breastfeeding and postpartum abstinence provide substantial protection from pregnancy after the birth uf a child. In addition to the health benefits to the child, breastfeeding prolongs the length of postpartum amenorrhea. In Sudan, almost all women breastfeed their children; 93 percent of children are still being breastfed 10-11 months after birth, and 41 percent continue breastfeeding for 20-21 months. Postpartum abstinence is traditional in Sudan and in the first two months following the birth of a child 90 percent of women were abstaining; this decreases to 32 percent after two months, and to 5 percent at~er one year. The survey results indicate that the combined effects of breastfeeding and postpartum abstinence protect women from pregnancy for an average of 15 months after the birth of a child.

Knowledge and use of contraception

Most currently married women (71 percent) know at least one method of family planning, and 59 percent know a source for a method. The pill (70 percent) is the most widely known method, followed by injection, female sterilisation, and the IUD. Only 39 percent of women knew a traditional method of family planning.

Despite widespread knowledge of family planning, only about one-fourth of ever-married women have ever used a contraceptive method, and among currently married women, only 9 percent were using a method at the time of the survey (6 percent modem methods and 3 percent traditional methods). The level of contraceptive use while still low, has increased from less than 5 percent reported in the Sudan Fertility Survey.

Use of family planning varies by age, residence, and level of education. Current use is less than 4 percent among women 15-19, increases to 10 percent for women 30-44, then decreases to 6 percent for women 45-49. Seventeen percent of urban women practice family planning compared with only 4 percent of rural women; and women with senior secondary education are more likely to practice family planning (26 percent) than women with no education (3 percent).

There is widespread approval of family planning in Sudan. Almost two-thirds of currently married women who know a family planning method approve of the use of contraception. Husbands generally share their wives's views on family planning. Three-fourths of married women who were not using a contraceptive method at the time of the survey said they did not intend to use a method in the future.

Communication between husbands and wives is important for successful family planning. Less than half of currently married women who know a contraceptive method said they had talked about family planning with their husbands in the year before the survey; one in four women discussed it once or twice; and one in five discussed it more than twice. Younger women and older women were less likely to discuss family planning than those age 20 to 39.

Mortality among children

The neonatal mortality rate in Sudan remained virtually unchanged in the decade between the SDHS and the SFS (44 deaths per 1000 births), but under-five mortality decreased by 14 percent (from 143 deaths per 1000 births to 123 per thousand). Under-five mortality is 19 percent lower in urban areas (117 per 1000 births) than in rural areas (144 per 10(30 births).

The level of mother's education and the length of the preceding birth interval play important roles in child survival. Children of mothers with no education experience nearly twice the level of under-five mortality as children whose mother had attained senior secondary or nigher education. Mortality among children under five is 2.7 times higher among children born after an interval of less than 24 months than among children born after interval of 48 months or more.

Maternal mortality

The maternal mortality rate (maternal deaths per 1000 women years of exposure) has remained nearly constant over the twenty years preceding the survey, while the maternal mortality ratio (number of maternal deaths per 100,000 births), has increased (despite declining fertility). Using the direct method of estimation, the maternal mortality ratio is 352 maternal deaths per 100,000 births for the period 1976-82, and 552 per 100,000 births for the period 1983-89. The indirect estimate for the maternal mortality ratio is 537. The latter estimate is an average of women's experience over an extended period before the survey centred on 1977.

Maternal health care

The health care mothers receive during pregnancy and delivery is important to the survival and well-being of both children and mothers. The SDHS results indicate that most women in Sudan made at least one antenatal visit to a doctor or trained health worker/midwife. Eighty-seven percent of births benefitted from professional antenatal care in urban areas compared with 62 percent in rural areas. Although the proportion of pregnant mothers seen by trained health workers/midwives are similar in urban and rural areas, doctors provided antenatal care for 42 percent and 19 percent of births in urban and rural areas, respectively.

Neonatal tetanus, a major