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.

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

National coverage, which includes the 5 Divisions and both Urban and Rural Areas of Tonga.

Analysis unit

Individual and 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 avoiding any under or over - counting during

Selected housing and population indicators derived from the "2010 Census Summary File 1" published by the U.S. Census Bureau, summarized on a census block basis. All indicators have numerators and denominators except in cases of total population counts and averages. Numerators are denoted with "_N" and Denominators with "_D". These data are intended for use in demographic analysis and visualization. Users are strongly advised to thoroughly read this metadata record and 2010 Summary File 1 documentation available from the U.S. Census Bureau at http://www.census.gov/prod/cen2010/doc/sf1.pdf. A copy of this technical documentation is included with the data download file available from RIGIS. The primary data source,"2010 Census Summary File 1" published by the U.S. Census Bureau, may be accessed online via American Fact Finder (http://factfinder2.census.gov) or directly via http://www2.census.gov/census_2010/04-Summary_File_1/Rhode_Island. The original TIGER/Line shapefile that serves as the spatial reference for these data may be downloaded from https://www.census.gov/geo/maps-data/data/tiger-line.html

The manual contains a list of mandatory requirements for conducting a census, as well as a number of guidelines and recommendations. The first sections of the manual describe the authority for conducting a municipal census, the role of the municipal council, and how to apply the Freedom of Information and Protection of Privacy Act (FOIP) to a municipal census. The subsequent sections describe the roles of census coordinator and the census enumerator. The final section provides a set of additional census questions that municipalities may choose to use in their census. The appendices contain various sample census materials. The methodologies, terms, and techniques for census-taking described in this manual are accepted by Alberta Municipal Affairs for determining the population of municipalities as described in the Determination of Population Regulation. The statistical concepts and principles reflected in this manual are based on those recognized by Statistics Canada and other statistical agencies.

Abstract

IPUMS-International is an effort to inventory, preserve, harmonize, and disseminate census microdata from around the world. The project has collected the world's largest archive of publicly available census samples. The data are coded and documented consistently across countries and over time to facillitate comparative research. IPUMS-International makes these data available to qualified researchers free of charge through a web dissemination system.

The IPUMS project is a collaboration of the Minnesota Population Center, National Statistical Offices, and international data archives. Major funding is provided by the U.S. National Science Foundation and the Demographic and Behavioral Sciences Branch of the National Institute of Child Health and Human Development. Additional support is provided by the University of Minnesota Office of the Vice President for Research, the Minnesota Population Center, and Sun Microsystems.

Geographic coverage

National coverage

Analysis unit

Household

UNITS IDENTIFIED: - Dwellings: No - Vacant units: No - Households: Yes - Individuals: Yes - Group quarters: No - Special populations: No

UNIT DESCRIPTIONS: - Dwellings: A census building is a free standing structure which is fixed on earth or on water permanently or temporarily (regardless the material used in building it) and it is used for residence or doing any activity in it (work, sport, pious work?.etc.). - Households: Consist of one person or a group of persons (related or non related to each other) sharing their housing unit and food together. A household includes: a) servants and the like who are living with the household; b) visitors who spent the census night with the household (except military persons); c) household members who spent the census night apart from their household, like members of armed forces and persons who always or temporarily work at night shifts or otherwise would not be counted by the census elsewhere; d) workers on Egyptian or foreign means of transporation who were present within or out of the territorial boundaries but have no residing place outside the country. - Group quarters: Not applicable

Universe

All individuals (Egyptians and foreigners) who were present within the political boundaries of Egypt at census night.

Kind of data

Census/enumeration data [cen]

Sampling procedure

MICRODATA SOURCE: Central Agency for Public Mobilisation and Statistics

SAMPLE DESIGN: Sample of private households drawn by Egyptian statistical office. Sample method unknown.

SAMPLE UNIT: Household

SAMPLE FRACTION: 10%

SAMPLE SIZE (person records): 5,902,243

Mode of data collection

Face-to-face [f2f]

Research instrument

Special Households Questionnaires; Public Living Quarters Questionnaire; Household and Housing Condition Questionnaire

Release Date: 2020-11-19.Release Schedule:.The data in this file are based on the 2017 Economic Census. For information about economic census planned data product releases, see Economic Census: About: 2017 Release Schedules...Key Table Information:.Includes only establishments of firms with payroll..Data may be subject to employment- and/or sales-size minimums that vary by industry..Product lines are referenced by NAPCS collection codes in the table. For information about NAPCS, see North American Product Classification System...For the 2017 Economic Census, there has been a change to how Units of Measure is published as compared to prior Census Years. Manufacturing and Mining sectors are now publishing these units as they were collected on the forms. There is no longer a conversion factor applied prior to their published figures. For example, in prior Census Years, Mining collected quantities in the unit of measure shorts tons; however, it was published as a unit of measure code of 250, which represented quantities of short tons with the display label of 1,000 s tons. For 2017, Mining collected quantities in the unit of measure short tons, and it is being published as a unit of measure code of 910, which represents the display label of quantities of short tons as short tons with no conversion factor. ..The value displayed in the table is the percent of broad product sales, value of shipments, or revenue that was withheld due to additional protection requirements that were added from recently updated Census Bureau and IRS data confidentiality agreements, to avoid disclosing data for individual companies, or because the estimate does not meet publication standards for quality. The numerator is calculated as the sum of the broad product sales withheld from publication at the 6-digit NAICS level and then aggregated to the 2-digit NAICS level. The denominator is the published total sales, value of shipments, or revenue at the 2-digit NAICS level. ...Sector (6-digit NAICS level)Percent of total broad product sales, value of shipments, or revenue withheld from publication .21 4.9% .22 9.6% .23 2.6% .31-33 26.4% .42 12.5% .44-45 1.3% .48-49 12.5% .51 2.4% .52 15.9% .53 2.8% .54 3.3% .55 2.2% .56 0.6% .61 1.5% .62 0.6% .71 0.5% .72 0.0% .81 0.4% ....Data Items and Other Identifying Records: .Number of establishments.Total sales, value of shipments, or revenue of establishments with the NAPCS collection code ($1,000).Quantity produced for the NAPCS collection code (sectors 21 and 31-33 only).Quantity shipped for the NAPCS collection code (sectors 21 and 31-33 only).Sales, value of shipments, or revenue of NAPCS collection code ($1,000).NAPCS collection code sales, value of shipments, or revenue as % of industry sales, value of shipments, or revenue (%).NAPCS collection code sales, value of shipments, or revenue as % of total sales, value of shipments, or revenue of establishments with the NAPCS collection code (%).Number of establishments with NAPCS collection code as % of industry establishments (%).Range indicating percent of total NAPCS collection code sales, value of shipments, or revenue imputed.Relative standard error of NAPCS collection code sales, value of shipments, or revenue (%)..Each record includes a code which represents various types of products produced or carried, or services rendered, by an establishment...For Wholesale Trade (42), data are published by Type of Operation (All establishments)...Geography Coverage:.The data are shown for employer establishments at the U.S. level for all sectors and at the U.S. and state level for sectors 44-45, 61, 62, 71, 72, and 81. For information about economic census geographies, including changes for 2017, see Economic Census: Economic Geographies...Industry Coverage:.The data are shown at the 2- through 6-digit 2017 NAICS code levels for all NAICS industries and selected 7 and 8 digit 2017 NAICS code levels for select industries. For information about NAICS, see Economic Census: Technical Documentation: Code Lists...Footnotes:.Transportation and Warehousing (48-49): footnote 106- Railroad transportation and U.S. Postal Service are out of scope...FTP Download:.Download the entire table at: https://www2.census.gov/programs-surveys/economic-census/data/2017/sector00..API Information:.Economic census data are housed in the Census Bureau API. For more information, see Explore Data: Developers: Available APIs: Economic Census..Methodology:.To maintain confidentiality, the U.S. Census Bureau suppresses data to protect the identity of any business or individual. The census results in this file contain sampling and/or nonsampling error. Data users who create their own estimates using data from this file should cite the U.S. Census Bureau as the source of the original data only...To comply with disclosure avoidance guidelines, data rows with fewer than three contributing establishments are not presented. Additionally, establishment counts are suppressed when ...

Abstract

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

Geographic coverage

The South African Census 1996 has national coverage.

Analysis unit

Households and individuals

Universe

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

Kind of data

Census enumeration data

Sampling procedure

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

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

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

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

Mode of data collection

Face-to-face [f2f]

Research instrument

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

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

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

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

Response rate

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

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

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

South Africa 10,69

As of 1/13/2022, this dataset is no longer being updated and has been replaced with a new dataset, which can be accessed here: https://data.ct.gov/Health-and-Human-Services/COVID-19-Vaccinations-by-Census-Tract/ekim-wqrr

COVID-19 Vaccinations by Census Tract and Age Groups, including Ages 16+, Ages 16-44, Ages 45-64, and Ages 65+.

CT Vaccination Program (COVP) data obtained from CTWiZ. COVP Coverage data suppressed if the any of the following conditions were met: -Coefficient of Variation of Denominator is > 30%
-Numerator is <5 -Population is estimated to be 0 (zero)

Population data obtained from the 2019 Census ACS (www.census.gov)

DPH recommends that these data are primarily used to identify areas that require additional attention rather than to establish and track the exact level of vaccine coverage.

All analyses are provisional and subject to change.

Census tract coverage estimates can play an important role in planning and evaluating vaccination strategies. However, inaccuracies in the data that are inherent to population surveillance may be magnified when analyses are performed on population subgroups within census tracts. We make every effort to provide accurate data, but inaccuracies may result from things like incomplete or inaccurate addresses, duplicate records, and sampling error in the American Community Survey that is used to estimate census tract population size and composition. These things may result in overestimates or underestimates of vaccine coverage.

Some census tracts are suppressed. This is done if the number of people vaccinated is less than 5 or if the census population estimate is considered to be unreliable (coefficient of variance > 30%). Coverage estimates over 100% are shown as 100%. We suggest that the data are used primarily to identify areas that require additional attention rather than to establish and track the exact level of vaccine coverage. All analyses are provisional and subject to change.

Caution should be used when interpreting coverage estimates for towns with large college/university populations since coverage may be underestimated. In the census, college/university students who live on or just off campus would be counted in the college/university town. However, if a student was vaccinated while studying remotely in his/her hometown, the student may be counted as a vaccine recipient in that town.

This layer contains details about home ownership by census tract in King County. It has been developed for the Determinant of Equity - Community Economic Development presentation Home Ownership Rates equity indicator. Fields describe the total number of people (Denominator), number of people that own a home (Numerator), the type of equity indicator being measured (Indicator), and the value that describes this measurement (Indicator Value).

The data for this dataset was compiled from the American Community Survey (ACS) 5-year estimates.

Vintages: 2013-2017, 2014-2018, 2015-2019, 2016-2020, 2017-2021, 2018 - 2022 Variable(s): B25003 - TENURE

For more information about King County's equity efforts, please see:

Equity, Racial & Social Justice Vision Ordinance 16948 describing the determinates of equity Determinants of Equity and Data Tool

Abstract

The 2009 Population and Housing Census was implemented according to Prime Ministerial Decision No. 94/2008/QD-TTg dated 10 July, 2008. This was the fourth population census and the third housing census implemented in Vietnam since the nation was reunified in 1975. The Census aimed to collect basic data on the population and housing for the entire territory of the Socialist Republic of Vietnam, to provide data for research and analysis of population and housing developments nationally and for each locality. It responded to information needs for assessing implementation of socio-economic development plans covering the period 2001 to 2010, for developing the socio-economic development plans for 2011 to 2020 and for monitoring performance on Millennium Development Goals of the United Nations to which the Vietnamese Government is committed.

Geographic coverage

National

Analysis unit

Households Individuals Dwelling

Universe

The 2009 Population and Housing Census enumerated all Vietnamese regularly residing in the territory of the Socialist Republic of Vietnam at the reference point of 0:00 on 01 April, 2009; Vietnamese citizens given permission by the authorities to travel overseas and still within the authorized period; deaths (members of the household) that occurred between the first day of the Lunar Year of the Rat (07 February, 2008) to 31 March, 2009; and residential housing of the population.

Population and housing censuses were implemented simultaneously taking the household as the survey unit. The household could include one individual who eats and resides alone or a group of individuals who eat and reside together. For household with 2 persons and over, its members may or may not share a common budget; or be related by blood or not; or marital or adoptive relationship or not; or in combination of both. The household head was the main respondent. For information of which the head of household was unaware, the enumerator was required to directly interview the survey subject. For information on labour and employment, the enumerator was required to directly interview all respondents aged 15 and older; for questions on births, the enumerator was required to directly interview women in childbearing ages (from 15 to 49 years of age) to determine the responses. For information on housing, the enumerator was required to directly survey the household head and/or combine this with direct observation to determine the information to record in the forms.

Kind of data

Census/enumeration data [cen]

Sampling procedure

Sample size In the 2009 Population and Housing Census, besides a full enumeration, some indicators were collected in a sample survey. The census sample survey was designed to: (1) expand survey contents; (2) improve survey quality, especially for sensitive and complicated questions; and (3) save on survey costs. To improve the efficiency and reliability of the census sample data, the sample size was 15% of the total population of the country. The sample of the census is a single-stage cluster sample design with stratification and systematic sample selection. Sample selection is implemented in two steps: Step 1, select the strata to determine the sample size for each district. Step 2, independently and systematically select from the sample frame of enumeration areas in each district to determine the specific enumeration areas in the sample.

The sample size of the two census sample surveys in 1989 and 1999 was 5% and 3% respectively, only representative at the provincial level; sample survey indicators covered fertility history of women aged 15-49 years and deaths in the household in the previous 12 months. In the 2009 Census, besides the above two indicators, many other indicators were also included in the census sample survey. The census sample survey provides data representative at the district level. When determining sample size and allocation, the frequency of events was taken into account for various indicators including birth and deaths in the 12 months prior to the survey, and the number of people unemployed in urban areas, etc.; efforts were also made to ensure the ability to compare results between districts within the same province/municipality and between provinces/ municipalities.

Stratification and sample allocation across strata To ensure representativeness of the sample for each district throughout the country and because the population size is not uniform across districts or provinces, the Central Steering Committee decided to allocate the sample directly to 682 out of 684 districts (excluding 2 island districts) throughout the country in 2 steps:

Step 1: Determine the sampling rate f(r) for 3 regions including: - Region 1: including 132 urban districts; - Region 2: including 294 delta and coastal rural districts; - Region 3: including 256 mountainous and island districts.

Step 2: Allocate the sample across districts in each region based on the sampling rates for each region as determined in Step 1 using the inverse sampling allocation method. Through applying to this allocation method, the number of sampling units in each small district is increased adequately to ensure representativeness. The formula used to calculate the sample rate for each district in each region is provided on page 22 of the Census Report (Part1) provided as external resources.

Sampling unit and method The sampling unit is the enumeration area that was ascertained in the step to delimit enumeration areas. The sampling frame is the list of all enumeration areas that was made following the order of the list of administrative units at the commune level within each district. In this way, the whole country has 682 sample frames (682 strata).

The provincial steering committee was responsible for selecting sample enumeration areas using systematic random sampling as follows: Step 1: Take the total of all enumeration areas in the district, divide by the number of enumeration areas needed in the sampleto determine the skip (k), which is calculated with precision up to 1 decimal point. Step 2: Select the first enumeration area (b, with b = k), corresponding to the first enumeration area to be selected. Each successive enumeration area to be selected will correspond to the order number: bi = b + i x k ; here i = 1, 2, 3…. Stopping when the number of enumeration areas needed has been selected.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaires and survey materials were designed and tested three times before final approval.

Cleaning operations

The 2009 Population and Housing Census applied Intelligent Character Recognition technology/scanning technology for direct data entry from census forms to the computer to replace the traditional keyboard data entry that is commonly used in Vietnam at present. This is an advanced technology, and the first time it had been applied in a statistical survey in Vietnam. Preparatory work had to be done carefully and meticulously. Through organization of many workshops and 7 pilot applications with technical and financial assistance from the UNFPA, the new technology was mastered, and the Census Steering Committee Standing Committee approved use of this technology to process the entire results of the 2009 Population and Housing Census. The Government decided to allocate funds through the project on Modernization of the General Statistics Office using World Bank Loan funds to procure the scanning system equipment, software and technical assistance. The successful use of this technology will create a precedent for continued use of scanning technology in other statistical surveys

After checking and coding at the Provincial/municipal steering committee office, (both the complete census and the census sample survey), forms were checked and accepted then transferred for processing to one of three Statistical Computing Centres in Hanoi, Ho Chi Minh City and Da Nang. Data processing was implemented in only a few locations, following standard procedures and a fixed timeline. The steering committee at each level and processing centres fully implemented their assigned responsibilities, especially the checking, transmitting and maintenance of survey forms in good condition. The Central Steering Committee collaborated with the Statistical Computer Centres to set up a plan for processing and compiling results, setting up tabulation plans, interpreting and synthesizing output tables, and developing options for extrapolating from sample to population estimates.

The General Statistics Office completed the work of developing software applications and training using ReadSoft software (the one used in pilot testing), organized training on network management and training on systems and programs for logic checks and data editing, developed a data processing protocol, integrated these systems and completed data flow management programs. The General Statistics Office collaborated with the contractor, FPT, to develop software applications, train staff, testl the system and complete the programs using the new TIS and E-form software.

Compilation of results was implemented in 2 stages. In stage 1 data were compiled from the Census Sample Survey by the end of October, 2009, and in stage 2, data were compiled from the completed census forms, with work finalized in May 2010.

Sampling error estimates

Estimates from the Census sample survey were affected by two types of error: (1) non-sampling error, and (2) sampling error. Non-sampling error is the result of errors in implementation of data collection and processing such as visiting the

Analysis of ‘COVID-19 Vaccinations by Census Tract - ARCHIVE’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/4d4b5bc7-d5be-471a-ad5e-82cea2b3704d on 12 February 2022.

--- Dataset description provided by original source is as follows ---

As of 1/13/2022, this dataset is no longer being updated and has been replaced with a new dataset, which can be accessed here: https://data.ct.gov/Health-and-Human-Services/COVID-19-Vaccinations-by-Census-Tract/ekim-wqrr

COVID-19 Vaccinations by Census Tract and Age Groups, including Ages 16+, Ages 16-44, Ages 45-64, and Ages 65+.

CT Vaccination Program (COVP) data obtained from CTWiZ. COVP Coverage data suppressed if the any of the following conditions were met: -Coefficient of Variation of Denominator is > 30%
-Numerator is <5 -Population is estimated to be 0 (zero)

Population data obtained from the 2019 Census ACS (www.census.gov)

DPH recommends that these data are primarily used to identify areas that require additional attention rather than to establish and track the exact level of vaccine coverage.

All analyses are provisional and subject to change.

Census tract coverage estimates can play an important role in planning and evaluating vaccination strategies. However, inaccuracies in the data that are inherent to population surveillance may be magnified when analyses are performed on population subgroups within census tracts. We make every effort to provide accurate data, but inaccuracies may result from things like incomplete or inaccurate addresses, duplicate records, and sampling error in the American Community Survey that is used to estimate census tract population size and composition. These things may result in overestimates or underestimates of vaccine coverage.

Some census tracts are suppressed. This is done if the number of people vaccinated is less than 5 or if the census population estimate is considered to be unreliable (coefficient of variance > 30%). Coverage estimates over 100% are shown as 100%. We suggest that the data are used primarily to identify areas that require additional attention rather than to establish and track the exact level of vaccine coverage. All analyses are provisional and subject to change.

Caution should be used when interpreting coverage estimates for towns with large college/university populations since coverage may be underestimated. In the census, college/university students who live on or just off campus would be counted in the college/university town. However, if a student was vaccinated while studying remotely in his/her hometown, the student may be counted as a vaccine recipient in that town.

--- Original source retains full ownership of the source dataset ---

Abstract

This study was undertaken to investigate public attitudes on national priorities, social issues, political parties and the South African government’s service delivery programme. It also aimed to reflect the extent of and attitudes towards the transition from the previous apartheid system to a constitutional democracy. The survey was a project of the HSRC’s Public Opinion Analysis Programme, which aimed to provide regular and reliable data and analysis of national social priority issues.

Geographic coverage

The survey had national coverage

Analysis unit

Units of analysis in the survey were individuals 18 years and older.

Universe

The survey covered all people in the country, 18 years and older.

Kind of data

Sample survey data [ssd]

Sampling procedure

The population was stratified according to nine socio-economic area types. The allocation was roughly proportional to the adjusted 1991 population census figures. Multistage cluster (probability) sampling was used to draw the respondents, using the adjusted 1991 population census figures as a sampling frame. Census enumerator areas and similar areas were used as the clusters in the penultimate sampling stage, from which an equal number of households were drawn. All the clusters were drawn from the final clusters with equal probability (systematically). The respondents were drawn at random from qualifying household members.

Mode of data collection

Face-to-face [f2f]

Poverty threshold available at https://www.census.gov/hhes/www/poverty/data/threshld/index.html

Additional information about how the Census Bureau measures poverty is available at https://www.census.gov/hhes/www/poverty/about/overview/measure.html

How Poverty is Calculated in the ACS

Poverty statistics presented in ACS reports and tables adhere to the standards specified by the Office of Management and Budget in Statistical Policy Directive 14. The Census Bureau uses a set of dollar value thresholds that vary by family size and composition to determine who is in poverty. Further, poverty thresholds for people living alone or with nonrelatives (unrelated individuals) and two-person families vary by age (under 65 years or 65 years and older).

If a family’s total income is less than the dollar value of the appropriate threshold, then that family and every individual in it are considered to be in poverty. Similarly, if an unrelated individual’s total income is less than the appropriate threshold, then that individual is considered to be in poverty. The poverty thresholds do not vary geographically. They are updated annually to allow for changes in the cost of living (inflation factor) using the Consumer Price Index (CPI).

Poverty status was determined for all people except institutionalized people, people in military group quarters, people in college dormitories, and unrelated individuals under 15 years old. These groups were excluded from the numerator and denominator when calculating poverty rates.

Since the ACS is a continuous survey, people respond throughout the year. Because the income items specify a period covering the last 12 months, the appropriate poverty thresholds are determined by multiplying the base-year poverty thresholds (1982) by the monthly inflation factor based on the 12 monthly CPIs and the base-year CPI. (Source: https://www.census.gov/hhes/www/poverty/poverty-cal-in-acs.pdf)

Abstract

The October Household Survey (OHS) of 1995 is the second official survey undertaken by Statistics South Africa (Stats SA) with the specific aim of making data available for the South African government's Reconstruction and Development Programme (RDP). Data collected includes population data, particulars of dwellings and data on services and on perceived quality of life.

Geographic coverage

The survey has national coverage

Analysis unit

Households and individuals

Universe

The survey covered households and household members in households in the nine provinces of South Africa

Kind of data

Sample survey data

Sampling procedure

A sample of 30 000 households was drawn in 3 000 enumerator areas (EA's) (that is 10 households per Enumerator Area). A two stage sampling procedure was applied and the sample was stratified, clustered and selected to meet the requirement of probability sampling. The sample was based on the 1991 Population Census enumerator areas. The sampled population excluded all prisoners in prisons, patients in hospitals, people residing in boarding houses and hotels (whether temporary or semi-permanent). The sample was explicitly stratified by province, Magisterial District, Urban/rural and Population group. The allocated number of EA's was systematically selected with probability proportional to size in each stratum The measure of size was the estimated number of people. In each EA, a systematic sample of 10 households was drawn.

Mode of data collection

Face-to-face [f2f]

Research instrument

The data files in the October Household Survey 1995 (OHS 1995) correspond to the following sections in the questionnaire:

House: Data from FLAP, Section 1 Person: Data from Section 2 Worker: Data from Section 3 Death: Data from Section 4 Births: Data from Section 5

Part two of the questionnaire collected income and expenditure data, which is available in the Income and Expenditure Survey 1995 (IES 1995) dataset. The OHS 1995 and IES 1995 enumerated the same households.

This layer contains details about computer ownership and internet subscription by census tract in King County. This dataset has been developed for the Determinant of Equity - Digital Equity presentation. In includes information about Access to an Internet Subscription and Computer in the Household equity indicators. Fields describe the total number of households (Denominator), number of households without a computer or without an internet subscription (Numerator), the type of equity indicator being measured (Indicator), and the value that describes this measurement (Indicator Value).

The data for this dataset was compiled from the American Community Survey (ACS) 5-year estimates.Vintages1-year estimates: 2017-2019, 2021-20225-year estimates: 2013-2017, 2014-2018, 2015-2019, 2016-2020, 2017-2021, 2018-2022Variables B28002 - PRESENCE AND TYPES OF INTERNET SUBSCRIPTIONS IN HOUSEHOLD

For more information about King County's equity efforts, please see:

Equity, Racial & Social Justice Vision Ordinance 16948 describing the determinates of equity Determinants of Equity and Data Tool

This layer contains details about residential mobility in King County by Census Tract from 2017 to 2021. This dataset has been developed for the Determinant of Equity - Neighborhoods presentation. In includes information about Residential Mobility equity indicators. Fields describe the total number of households (Denominator), number of households who have moved (Numerator), the type of equity indicator being measured (Indicator), and the value that describes this measurement (Indicator Value).

For more information about King County's equity efforts, please see:

Equity, Racial & Social Justice Vision Ordinance 16948 describing the determinates of equity Determinants of Equity and Data Tool

Abstract

The October Household Survey is an annual survey based on a survey of a large number of households (ranging from 16 000 in 1996 through to 30 000 in 1997 and 1998, depending on the availability of funding). It covers a range of development indicators, including unemployment rates (official and expanded), according to standard definitions of the International Labour Organisation (ILO).

Geographic coverage

The survey had national coverage.

Analysis unit

Households and individuals

Universe

The survey covered households and household members in households in the nine provinces of South Africa

Kind of data

Sample survey data

Sampling procedure

A sample of 20 000 households was drawn in 2 000 enumerator areas (EAs) (that is 10 households per enumerator area). A two-stage sampling procedure was applied and the sample was stratified, clustered and selected to meet the requirements of probability sampling. The sample was based on the 1996 Population Census enumerator areas and the estimated number of people from the administrative records of the 1996 population Census. The sampled population excluded all prisoners in prisons, patients in hospitals, people residing in boarding houses and hotels (whether temporary or semi-permanent). The sample was explicitly stratified by province, Transitional Metropolitan Council (TMC)and District Council (DC). A square root method was used for the allocation of the sample EAs to the explicit strata.

Within each explicit stratum the EAs were stratified by simply arranging them in geographical order by magisterial district and, within the magisterial district, by EA. The allocated number of EAs was systematically selected with probability proportional to size in each stratum. The measure of size was the estimated number of people in Each EA. A systematic sample of 10 households was drawn.

Mode of data collection

Face-to-face [f2f]

Research instrument

The data files in the October Household Survey 1997 (OHS 1997) correspond to the following sections in the questionnaire:
PERSON: Indivitual-level data from Section 1 and Section 4; BIRTHS: Data from Section 2; CHILDREN: Data from Section2; WORKER: Data from Section 3; MIGRANT: Data from Section 5; DEATHS: Data from Section 6; MIGRATION: Data from Section 7; DOMESTIC: Data from Section 8; HOUSE: Household-level data from Section 9

Errors in the marital codes in the original OHS 1998 questionnaire: The questionnaire for the OHS 1998 originally provided by Statistics SA with the data files was incorrect. It was the OHS 1997 questionnaire with a OHS 1998 flap. The marital codes were different in the two surveys. In 1997, the codes for the variable Marital Status were: 1 Never married 2 Married - civil 3 Married - customary 4 Living together 5 Widowed 6 Divorced

In the 1998 survey, the codes for the variable Marital Status are:

1 Married - civil 2 Married - traditional (customary) 3 Living together 4 Widower/widow 5 Divorced/separated 6 Never married

DataFirst notified Statistics SA of this error on 13 July 2007 and they sent a corrected questionnaire. The correct questionnaire is version 2, available with the data since 2007.

Data appraisal

Errors in the marital codes in the original OHS 1998 questionnaire:

The questionnaire for the OHS 1998 originally provided by Statistics SA with the data files was incorrect. It was the OHS 1997 questionnaire with a OHS 1998 flap. The marital codes were different in the two surveys. In 1997, the codes for the variable Marital Status were: 1 Never married 2 Married - civil 3 Married - customary 4 Living together 5 Widowed 6 Divorced

In the 1998 survey, the codes for the variable Marital Status are:

1 Married - civil 2 Married - traditional (customary) 3 Living together 4 Widower/widow 5 Divorced/separated 6 Never married

DataFirst notified Statistics SA of this error on 13 July 2007 and they sent a corrected questionnaire. The correct questionnaire is version 2, available with the data since 2007.

Abstract

An omnibus survey is done quarterly and its purpose is to give clients an opportunity to participate in a national survey at low cost. A number of clients’ questions are combined into one questionnaire. This questionnaire is usually administered to probability sample of 2 220 respondents in the whole country (South Africa). The October 1994 omnibus survey was undertaken over the period 10 October to 28 October 1994. The fieldwork was done on a countrywide basis including all nine provinces.

Geographic coverage

The survey had national coverage, including coverage of the 'homelands" of Ciskei and Venda.

The lowest level of geographic aggregation for the data is Magisterial district.

Analysis unit

Units of analysis in the survey included individuals

Universe

The universe included all household residents 18 years old or older

Kind of data

Sample survey data [ssd]

Sampling procedure

The South African population of persons 18 years and older was stratified according to: Province (Western Cape, Eastern Cape, Northern Cape, Orange Free State, Natal/KwaZulu, Eastern Transvaal, PWV, North Western Province, Northern Transvaal) Socio-economic classification: Rural areas in former self-governing and TBVC states Squatter areas in former non-white urban (metro and non- metro areas) Hostels and hotels Former urban areas for coloureds Former urban areas for a Asians Former urban areas for blacks Former urban (non- metro) areas for whites Former urban (metro) areas for whites Rural areas, excluding the former self-governing and TBVC states

The sample allocation to these strata was done roughly proportional to the adjusted 1991 populatio n census figures with a few exceptions, among which was to ensure a minimal provincial total of 120. Multistage stratified cluster (probability) sampling was used to draw the respondents with the adjusted 1991 population census figures as measure of size. Census enumerator areas and similar areas were used as the clusters in the pen-ultimate sampling stage, from which an equal number, viz. one or two by four households were drawn. All clusters were drawn with probability proportional to size, whilst households were drawn from the final clusters with equal probability (systematically). Respondents were drawn at random from qualifying household members. In addition, population of live-in domestic workers was sampled in relation to their residence in already drawn households.

Mode of data collection

Face-to-face [f2f]

This layer contains details about youth (16 to 19 Years) who are in school or working in King County. This dataset has been developed for the Education presentation. It includes information about Youth and Young Adults (16 to 24 Years) who are in School or Working equity indicator(s). Fields describe all youth (16 to 19 Years) who are in school or working (Denominator), youth (16 to 19 Years) who are in school or working (Numerator), for King County (Group), and the value that describes this measurement (Indicator Value).The data for this dataset was compiled from the American Community Survey (ACS).B14005: SEX BY SCHOOL ENROLLMENT BY EDUCATIONAL ATTAINMENT BY EMPLOYMENT STATUS FOR THE POPULATION 16 TO 19 YEARSFor more information about King County's equity efforts, please see:Equity, Racial & Social Justice VisionOrdinance 16948 describing the determinants of equityDeterminants of Equity and Data Tool

Abstract

The Survey of Activities of Young People was conducted by Statistics South Africa and commissioned by the Department of Labour, primarily to gather information necessary for formulating an effective programme of action to address the issue of harmful work done by children in South Africa. Technical assistance for the survey was provided by the International Labour Organisation (ILO) and a consultant appointed by the Department of Labour. Stats SA also worked with an advisory committee, consisting of representatives from national government departments most directly concerned with child labour (the Departments of Labour,Welfare,Education and Health), non-governmental organisations, and the United Nations Children's Fund (Unicef).

Geographic coverage

The survey has national coverage

Analysis unit

Households and individuals

Universe

The sampled population was household members in South Africa. The survey excluded all people in prison, patients in hospitals, people residing in boarding houses and hotels, and boarding schools. Any single person households were screened out in all areas before the sample was drawn. Families living in hostels were treated as households.

Kind of data

Sample survey data

Sampling procedure

The sample frame was based on the 1996 Population Census Enumerator Areas (EA) and the number of households counted in 1996 Population Census. The sampled population excluded all prisoners in prison, patients in hospitals, people residing in boarding houses and hotels (whether temporary or semi-permanent), and boarding schools. Any single person households were screened out in all areas before the sample was drawn. Families living in hostels were treated as households. Coverage rules for the survey were that all children of usual residents were to be included even if they were not present. This means that most boarding school pupils were included in their parents’ household. The 16 EA types from the 1996 Population Census were condensed into four area types. The four area types were Formal Urban, Informal Urban, Tribal, and Commercial Farms. A decision was made to drop the Institution type EAs.

The EAs were stratified by province, and within a province by the four area types defined above. The sample size (6110 households) was disproportionately allocated to strata by using the square root method. Within the strata the EAs were ordered by magisterial district and the EA-types included in the area type (implicit stratification). PSUs consisted of ONE or more EAs of size 100 households to ensure sufficient numbers for screening. Statistics SA was advised by child labour experts that there was a likelihood of high rates of child labour in the Urban Informal and Rural Farm areas. The sample allocation to Rural Commercial Farms was therefore increased to a minimum of 20 PSUs.

Mode of data collection

Face-to-face [f2f]

Research instrument

The Phase one questionnaire covered the following topics: Living conditions of the household, including the type of dwelling, fuels used for cooking, lighting and heating,water source for domestic use, land ownership,tenure and cultivation; demographic information on members of the household, both adults and children. Questions covered the age, gender and population group of each household member, their marital status, their relationships to each other, and their levels of education; migration details; household income; school attendance of children aged 5 -17 years; information on economic and non-economic activities of children aged 5-17 years in the 12 months prior to the survey

Phase two questionnaire The second phase questionnaire was administered to the sampled sub-set of households in which at least one child was involved in some form of work in the year prior to the interview. It covered activities of children in much more detail than in phase one, and the work situation of related adults in the household. Both adults and children were asked to respond.

The data files contain data from sections of the questionnaires as follows:

PERSON: Data from Section 1, 2 and 3 of the questionnaire HHOLD : Data from Section 4 ADULT : Data from Section 5 YOUNGP: Data from Section 6, 7, 8 and 9