The 2022 Europe and Eurasia Civil Society Organization Census and Constituency Survey was produced by AidData, a research lab at William & Mary’s Global Research Institute. The CSO Census and Constituency Survey was fielded online in April-May, 2022 using the Qualtrics survey platform across 16 E&E countries. The purpose of the survey was to triangulate information on the health of CSOs across the E&E region by surfacing the perspectives of CSO staff and the views of their constituents in a comparable way. CSO staff answered a Census Survey with modules focused on documenting the organization’s activities, target audiences, partners, the broader operating environment, and organization statistics. Constituents of CSOs answered a Constituency Survey with modules focused on awareness and attitudes towards CSOs, performance of CSOs, and the broader environment for civil society. Both groups answered questions to assess the perceived influence of international actors in a country’s civic space and examined areas where international support might help or hinder the credibility of CSOs.

Occupation describes the kind of work a person does on the job. Occupation data were derived from answers to questions 45 and 46 in the 2015 American Community Survey (ACS). Question 45 asks: “What kind of work was this person doing?” Question 46 asks: “What were this person’s most important activities or duties?” These questions were asked of all people 15 years old and over who had worked in the past 5 years. For employed people, the data refer to the person’s job during the previous week. For those who worked two or more jobs, the data refer to the job where the person worked the greatest number of hours. For unemployed people and people who are not currently employed but report having a job within the last five years, the data refer to their last job. These questions describe the work activity and occupational experience of the American labor force. Data are used to formulate policy and programs for employment, career development, and training; to provide information on the occupational skills of the labor force in a given area to analyze career trends; and to measure compliance with antidiscrimination policies. Companies use these data to decide where to locate new plants, stores, or offices.

Abstract

A census gives a complete and comprehensive picture of the nation as well as groups of people living in specific areas. In what type of buildings and housing units are we living? What are the amenities and facilities that are available therein? How many rooms are there and what is the extent of overcrowding? How many people live in a given town or locality? How many children are there? How many women are there? How many are old enough to vote? What kind of jobs are we doing? What is our level of education? Do we have the required qualifications or skills to satisfy the needs of the labour market? The census helps to answer these questions and many others.

It provides up-to-date and disaggregated data on the housing conditions, the spatial distribution, and the demographic and socio-economic characteristics of the population. These data are essential for assessing the country's demographic, social and economic performance and for developing sound policies and programmes aimed at fostering the welfare of the country and its population.

Census data are also useful to business, industrial and commercial organisations to estimate and forecast demand for their products and services, and to assess the supply of manpower with the relevant skills to run their activities.

Furthermore, census data are used in the derivation of many important and meaningful social indicators that are needed by local and international organizations. Thus, many social indicators, as defined in the set of indicators recommended by the United Nations Statistics Division, can only be worked out from census data.

Legal framework Census 2000 was conducted according to provisions of the Statistics Act of 7 April 1951. The underlying procedures are given in Sections 5, 6 and 13 of the Act. In March 1998, the Cabinet agreed to the conduct of a housing and population census in year 2000. In June 1999, it gave its approval to the census dates and to the topics to be investigated. The regulations for the Housing Census, prescribing the particulars and information to be collected, were subsequently prepared and approved by the President in November 1999. The regulations were published as Government Notice 170 of 1999. In December 1999, the President made an order to the effect that a census of the population be taken between 19 June and 16 July 2000 in respect of all persons alive at midnight on 2 July 2000. The Order was gazetted in December 1999. The regulations for the Population Census, prescribing the particulars and information to be collected were approved by the President in April 2000 and published as Government Notice 57 of 2000.

Geographic coverage

Housing and population enumerations were conducted on the Islands of Mauritius, Rodrigues and Agalega. As regards St Brandon islands, only a count of persons spending census night on the islands was made, these islands being fishing stations with no resident population.

Analysis unit

• Household
• Individual
• Housing unit

Universe

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

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

Kind of data

Census/enumeration data [cen]

Mode of data collection

Self administered and face to face

Research instrument

Questionnaire Design Consultation with stakeholders from Government Ministries and Departments started in 1998. Heads of Government Ministries and Departments were invited via a circular letter to submit a list of demographic, social and economic data they considered essential for administration, planning and policy-making and which could be collected at the census. The proposals received were discussed at various levels. In the light of these discussions and taking into account recommendations of the United Nations Statistics Division on subject matters that can be investigated at a census, final selection of topics was made at a meeting with subject matter specialists from our parent Ministry.

The main considerations in the final selection of topics were: - the importance of the topics to the country - the cost for collecting and processing data on a given item - where it was possible by other means to obtain satisfactory information more cheaply, the topic was not selected - the suitability of topics - sensitive and controversial issues as well as questions that were too complicated or difficult for the average respondent to answer were avoided - whether the census was the appropriate method for data collection - topics that required detailed investigation or highly qualified staff were not included since they would be best canvassed by sample surveys.

Housing Census Questionnaire All topics investigated at the 1990 Census were included in the 2000 Housing Census questionnaire. Three new items were however added. These were: “Availability of domestic water tank/reservoir”, “Principal fuel used in bathroom” and “Fruit trees on premises”.

The housing census questionnaire was divided into seven parts. A list of topics and items included in the questionnaire is given below: Part I - Location Part II - Type of Building Part III - Characteristics of buildings - Storeys above ground floor
- Year of completion
- Principal material of construction used for roof and walls
Part IV - Characteristics of housing units - Ownership
- Occupancy
- Water supply
- Domestic water tank/reservoir - Availability of electricity
- Toilet facilities
- Bathing facilities
- Availability of kitchen - Refuse disposal Part V - Characteristics of households - Household type - Name and address of head of household - Number of persons by sex - Tenure - Number of rooms for living purposes - Number of rooms for business or profession - Monthly rent - Principal fuel used for cooking - Principal fuel used in bathroom Part VI - Commercial and industrial establishments, hotels and boarding houses - Name and address of establishment or working proprietor/manager - Main activity in which the establishment is engaged - Number of persons engaged at the time of enumeration Part VII - Fruit-trees on premises - Number of fruit trees of bearing age by type

Population Census Questionnaire The 2000 Population Census questionnaire covered most of the topics investigated at the 1990 Population Census. A question on income was added while the questions on education were reviewed to include qualifications, other than those of the primary and secondary levels, of the respondent. The topic, main activity status of person during the year, which was investigated at the previous census was not included.

Topics and items included in the population census questionnaire are given below: (i) Location (ii) Names of persons These information were asked only to ensure that all members of the household were enumerated. Also, the listing of names of each person facilitated the checking for accuracy and completeness of each entry at the time of enumeration and later, if errors or missing information still persisted on the form. It should be pointed out that names were not captured at the data entry stage, so that data collected could not be identified with any individual person, in line with the requirements of the Statistics Act. (iii) Demographic and social characteristics - Relationship to head (only one head is allowed for each household) - Sex - Age - Date of birth (This question served as a verification to the age reported earlier) - Citizenship - Marital Status - Religion - Linguistic group - Language usually spoken (iv) Whether disabled or not - Type of disability, if disabled (v) Migration characteristics - Whereabouts on Census night - Usual address - Usual address five years ago (vi) Fertility - For persons not single: - Age at first marriage - Whether married more than once - Number of children ever born (for women only) (vii) Education characteristics - For persons 2 years and above: - Languages read and written - School attendance - Primary and secondary education (viii) Current economic characteristics (ix) Income

Census Guide and Instructions A census guide and instructions booklet was prepared and distributed to all heads of households. The booklet contained extensive explanations on how to fill in the census form and answered questions that people usually asked about censuses. Thus the objectives of the census, what happened to the census forms once the enumeration was over, the confidential aspect of collected information as well as the usefulness of each item were explained.

Printing of Census Questionnaires and Guides
The census questionnaires, and the census guide and instructions booklets were printed by the Government Printer. The numbers printed were as follows: (i) Housing Census questionnaires - 16,000 booklets of 25 questionnaires (ii) Population Census questionnaires - 375,000 (iii) Census guide and instructions booklets - 312,000

Cleaning operations

Recruitment and Training of Editors and Coders About 15 clerical officers who were previously engaged in the various units of the Office and 10 newly recruited statistical officers were called on to the editing and coding of the census forms while a request for the services of 50 additional clerical officers was made to the Ministry for Civil Service Affairs and Administrative Reform. Between March 2000 and May 2001, small groups of clerical officers from the ministry joined the

Economic activity relates to whether or not a person who was working or looking for work in the week before census. Rather than a simple indicator of whether or not someone was currently in employment, it provides a measure of whether or not a person was an active participant in the labour market. A person's economic activity is derived from their 'Activity last week'. This is an indicator of their status or availability for employment - whether employed, actively looking for work, waiting to start a new job, available to start a new job, or their status if not employed or not seeking employment. Additional information included in the economic activity classification is also derived from information about the number of hours a person works and their type of employment - whether employed or self-employed. The census concept of economic activity is compatible with the standard for economic status defined by the International Labour Organisation (ILO). It is one of a number of definitions used internationally to produce accurate and comparable statistics on employment, unemployment and economic status. The 2011 Census question on religion asks for the person's current religion, or if the person does not have a religion, 'no religion'. No determination is made about whether a person was a practicing member of a religion. Unlike other census questions where missing answers are imputed, this question was voluntary, and where no answer was provided the response is categorised as 'not stated'. For the 2011 Census, a usual resident of the UK is anyone who, on census day 2011, was in the UK and had stayed or intended to stay in the UK for a period of 12 months or more, or had a permanent UK address and was outside the UK and intended to be outside the UK for less than 12 months. For more information see Weblinks.

About this dataset

Context

The dataset tabulates the population of Nome Census Area by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Nome Census Area. The dataset can be utilized to understand the population distribution of Nome Census Area by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Nome Census Area. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for Nome Census Area.

Key observations

Largest age group (population): Male # 10-14 years (621) | Female # 5-9 years (483). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis.

Variables / Data Columns

• Age Group: This column displays the age group for the Nome Census Area population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Nome Census Area is shown in the following column.
• Population (Female): The female population in the Nome Census Area is shown in the following column.
• Gender Ratio: Also known as the sex ratio, this column displays the number of males per 100 females in Nome Census Area for each age group.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Nome Census Area Population by Gender. You can refer the same here

Description of the experiment setting: location, influential climatic conditions, controlled conditions (e.g. temperature, light cycle)In Fall of 2023 the USDA Food and Nutrition Service (FNS) conducted the fourth Farm to School Census. The 2023 Census was sent via email to 18,833 school food authorities (SFAs) including all public, private, and charter SFAs, as well as residential care institutions, participating in the National School Lunch Program. The questionnaire collected data on local food purchasing, edible school gardens, other farm to school activities and policies, and outcomes and challenges of participating in farm to school activities. A total of 12,559 SFAs submitted a response to the 2023 Census.Processing methods and equipment usedThe 2023 Census was administered solely via the web. The study team cleaned the raw data to ensure the data were as correct, complete, and consistent as possible. This process involved examining the data for logical errors and removing implausible values. The study team linked the 2023 Census data to information from the National Center of Education Statistics (NCES) Common Core of Data (CCD). Records from the CCD were used to construct a measure of urbanicity, which classifies the area in which schools are located.Study date(s) and durationData collection occurred from October 2, 2023 to January 7, 2024. Questions asked about activities prior to, during and after SY 2022-23. The 2023 Census asked SFAs whether they currently participated in, had ever participated in or planned to participate in any of 32 farm to school activities. Based on those answers, SFAs received a defined set of further questions.Study spatial scale (size of replicates and spatial scale of study area)Respondents to the survey included SFAs from all 50 States as well as American Samoa, Guam, the Northern Mariana Islands, Puerto Rico, the U.S. Virgin Islands, and Washington, DC.Level of true replicationUnknownSampling precision (within-replicate sampling or pseudoreplication)No sampling was involved in the collection of this data.Level of subsampling (number and repeat or within-replicate sampling)No sampling was involved in the collection of this data.Study design (before–after, control–impacts, time series, before–after-control–impacts)None – Non-experimentalDescription of any data manipulation, modeling, or statistical analysis undertakenEach entry in the dataset contains SFA-level responses to the Census questionnaire for SFAs that responded. This file includes information from only SFAs that clicked “Submit” on the questionnaire. (The dataset used to create the 2023 Farm to School Census Report includes additional SFAs that answered enough questions for their response to be considered usable.)In addition, the file contains constructed variables used for analytic purposes. The file does not include weights created to produce national estimates for the 2023 Farm to School Census Report.The dataset identified SFAs, but to protect individual privacy the file does not include any information for the individual who completed the questionnaire. All responses to open-ended questions (i.e., containing user-supplied text) were also removed to protect privacy.Description of any gaps in the data or other limiting factorsSee the full 2023 Farm to School Census Report [https://www.fns.usda.gov/research/f2s/2023-census] for a detailed explanation of the study’s limitations.Outcome measurement methods and equipment usedNone

Office for National Statistics' national and subnational Census 2021. Schoolchildren and full-time studentsThis dataset provides Census 2021 estimates that classify all usual residents aged 5 years and over in England and Wales. The estimates are as at Census Day, 21 March 2021. Schoolchild or full-time student indicator definition: Indicates whether a person aged 5 years and over was in full-time education on Census Day, 21 March 2021. This includes schoolchildren and adults in full-time education.Schoolchildren and students in full-time education studying away from home are treated as usually resident at their term-time address.Comparability with 2011: Broadly comparable.We have removed the category Schoolchild or full-time student for Census 2021 and replaced it with Student. In the 2011 Census people aged 4 years and over were asked to answer the question, in Census 2021 people aged 5 years and over were asked to answer the question. This data is issued at (BGC) Generalised (20m) boundary type for:Country - England and WalesRegion - EnglandUTLA - England and WalesLTLA - England and WalesWard - England and WalesMSOA - England and WalesLSOA - England and WalesOA - England and WalesIf you require the data at full resolution boundaries, or if you are interested in the range of statistical data that Esri UK make available in ArcGIS Online please enquire at content@esriuk.com.The data services available from this page are derived from the National Data Service. The NDS delivers thousands of open national statistical indicators for the UK as data-as-a-service. Data are sourced from major providers such as the Office for National Statistics, Public Health England and Police UK and made available for your area at standard geographies such as counties, districts and wards and census output areas. This premium service can be consumed as online web services or on-premise for use throughout the ArcGIS system.Read more about the NDS.

Abstract

This study is an experiment designed to compare the performance of three methodologies for sampling households with migrants:

• a stratified sample using the census to sample census tracts randomly, in which each household is then listed and screened to determine whether or not it has a migrant, with the full length questionnaire then being applied in a second phase only to the households of interest;
• a snowball survey in which households are asked to provide referrals to other households with migrant members;
• an intercept point survey (or time-and-space sampling survey), in which individuals are sampled during set time periods at a prespecified set of locations where households in the target group are likely to congregate.

Researchers from the World Bank applied these methods in the context of a survey of Brazilians of Japanese descent (Nikkei), requested by the World Bank. There are approximately 1.2-1.9 million Nikkei among Brazil’s 170 million population.

The survey was designed to provide detail on the characteristics of households with and without migrants, to estimate the proportion of households receiving remittances and with migrants in Japan, and to examine the consequences of migration and remittances on the sending households.

The same questionnaire was used for the stratified random sample and snowball surveys, and a shorter version of the questionnaire was used for the intercept surveys. Researchers can directly compare answers to the same questions across survey methodologies and determine the extent to which the intercept and snowball surveys can give similar results to the more expensive census-based survey, and test for the presence of biases.

Geographic coverage

Sao Paulo and Parana states

Analysis unit

Japanese-Brazilian (Nikkei) households and individuals

The 2000 Brazilian Census was used to classify households as Nikkei or non-Nikkei. The Brazilian Census does not ask ethnicity but instead asks questions on race, country of birth and whether an individual has lived elsewhere in the last 10 years. On the basis of these questions, a household is classified as (potentially) Nikkei if it has any of the following: 1) a member born in Japan; 2) a member who is of yellow race and who has lived in Japan in the last 10 years; 3) a member who is of yellow race, who was not born in a country other than Japan (predominantly Korea, Taiwan or China) and who did not live in a foreign country other than Japan in the last 10 years.

Kind of data

Sample survey data [ssd]

Sampling procedure

1) Stratified random sample survey

Two states with the largest Nikkei population - Sao Paulo and Parana - were chosen for the study.

The sampling process consisted of three stages. First, a stratified random sample of 75 census tracts was selected based on 2000 Brazilian census. Second, interviewers carried out a door-to-door listing within each census tract to determine which households had a Nikkei member. Third, the survey questionnaire was then administered to households that were identified as Nikkei. A door-to-door listing exercise of the 75 census tracts was then carried out between October 13th, 2006, and October 29th, 2006. The fieldwork began on November 19, 2006, and all dwellings were visited at least once by December 22, 2006. The second wave of surveying took place from January 18th, 2007, to February 2nd, 2007, which was intended to increase the number of households responding.

2) Intercept survey

The intercept survey was designed to carry out interviews at a range of locations that were frequented by the Nikkei population. It was originally designed to be done in Sao Paulo city only, but a second intercept point survey was later carried out in Curitiba, Parana. Intercept survey took place between December 9th, 2006, and December 20th, 2006, whereas the Curitiba intercept survey took place between March 3rd and March 12th, 2007.

Consultations with Nikkei community organizations, local researchers and officers of the bank Sudameris, which provides remittance services to this community, were used to select a broad range of locations. Interviewers were assigned to visit each location during prespecified blocks of time. Two fieldworkers were assigned to each location. One fieldworker carried out the interviews, while the other carried out a count of the number of people with Nikkei appearance who appeared to be 18 years old or older who passed by each location. For the fixed places, this count was made throughout the prespecified time block. For example, between 2.30 p.m. and 3.30 p.m. at the sports club, the interviewer counted 57 adult Nikkeis. Refusal rates were carefully recorded, along with the sex and approximate age of the person refusing.

In all, 516 intercept interviews were collected.

3) Snowball sampling survey

The questionnaire that was used was the same as used for the stratified random sample. The plan was to begin with a seed list of 75 households, and to aim to reach a total sample of 300 households through referrals from the initial seed households. Each household surveyed was asked to supply the names of three contacts: (a) a Nikkei household with a member currently in Japan; (b) a Nikkei household with a member who has returned from Japan; (c) a Nikkei household without members in Japan and where individuals had not returned from Japan.

The snowball survey took place from December 5th to 20th, 2006. The second phase of the snowballing survey ran from January 22nd, 2007, to March 23rd, 2007. More associations were contacted to provide additional seed names (69 more names were obtained) and, as with the stratified sample, an adaptation of the intercept survey was used when individuals refused to answer the longer questionnaire. A decision was made to continue the snowball process until a target sample size of 100 had been achieved.

The final sample consists of 60 households who came as seed households from Japanese associations, and 40 households who were chain referrals. The longest chain achieved was three links.

Mode of data collection

Face-to-face [f2f]

Research instrument

1) Stratified sampling and snowball survey questionnaire

This questionnaire has 36 pages with over 1,000 variables, taking over an hour to complete.

If subjects refused to answer the questionnaire, interviewers would leave a much shorter version of the questionnaire to be completed by the household by themselves, and later picked up. This shorter questionnaire was the same as used in the intercept point survey, taking seven minutes on average. The intention with the shorter survey was to provide some data on households that would not answer the full survey because of time constraints, or because respondents were reluctant to have an interviewer in their house.

2) Intercept questionnaire

The questionnaire is four pages in length, consisting of 62 questions and taking a mean time of seven minutes to answer. Respondents had to be 18 years old or older to be interviewed.

Response rate

1) Stratified random sampling 403 out of the 710 Nikkei households were surveyed, an interview rate of 57%. The refusal rate was 25%, whereas the remaining households were either absent on three attempts or were not surveyed because building managers refused permission to enter the apartment buildings. Refusal rates were higher in Sao Paulo than in Parana, reflecting greater concerns about crime and a busier urban environment.

2) Intercept Interviews 516 intercept interviews were collected, along with 325 refusals. The average refusal rate is 39%, with location-specific refusal rates ranging from only 3% at the food festival to almost 66% at one of the two grocery stores.

Attitude of the German population and of critics of the census to the census after census day on 31 May 1987. Political attitudes. Topics: political interest; satisfaction with democracy in the Federal Republic; government orientation toward its own interests or public interest; perceived protection of rights to freedom by the political system and the current Federal Government; satisfaction with the job of the Federal Government; attitude to the census; receipt of a written request to fill out the questionnaire; intent to participate in the census before start of counting; personal willingness to participate in the census even given voluntary participation; assumed level of non-participation in the census; attitude to the census in one´s circle of friends and acquaintances; conversations about the census in social surroundings after conclusion of the survey and time of last conversation; knowledge about contents of the census survey; additionally expected questions; questions that one would not gladly answer; response or boycott behavior during the survey; attitude to government statistics; attitude to punishment of census boycotters and knowledge of cases of refusal; assumed willingness of the population to participate as well as honesty of responses given voluntary participation in the census; voluntarily providing selected personal data; preference for census or providing data already available by government offices; assumed benefit or damage from discussions about the census in the media and reasons for this assessment; attitude to earlier calls for boycott and to the time of survey; judgement on the success of the boycott movement; attitude to selected arguments for and against the census; benefit of a census; attitude to the obligation to provide information; census boycott as protest against the government; census participation as democratic duty; self-assessment on a left-right continuum; assumed position of the majority of the population on a left-right continuum; understanding of democracy and comparison of this right with reality in the Federal Republic; party preference; violation of fundamental rights by measures of authorities perceived personally or by persons from social surroundings; attitude to technology; perceived insecurity in contact with authorities and attitude to government offices; concerns regarding misuse of personal census data; trust in observance of data protection; attitude to storage of personal data; importance of data protection; assumed observance of data protection regulations; knowledge of cases of data misuse and source of information about such violations; assumed willingness to participate in a future census; attitude to opinion polls (scale); willingness to participate in a microcensus survey; willingness to provide information from one´s private sphere to friends, neighbors, census bureaus and scientific surveys; attitude to selected government statistics; willingness to respond in order to make statistics possible; fear of data misuse; concerns regarding misuse of personal data by selected institutions and government offices (scale); attitude to selected illegal actions (scale); religiousness (scale); attitude to questions of belief and the meaning of life (scale); belief in supernatural, inexplicable events as well as horoscopes and telepathy. Demography: month of birth; year of birth; sex; religious denomination; school education; employment; college in vicinity of place of residence; students in residential area; possession of a telephone. Interviewer rating: presence of third persons during interview and person desiring this presence; intervention of others in interview and person causing the intervention; attitude to the census of other persons present during interview; presence of further persons in other rooms; reliability and willingness of respondent to cooperate. Additionally encoded were: length of interview; date of interview; identification of interviewer; sex of interviewer; age of interviewer. Einstellung der bundesdeutschen Bevölkerung und von Volkszählungskritikern zur Volkszählung nach dem Stichtag am 31. Mai 1987. Politische Einstellungen. Themen: Politisches Interesse; Zufriedenheit mit der Demokratie in der Bundesrepublik; Interessen- oder Gemeinwohlorientierung der Regierung; empfundener Schutz der Freiheitsrechte durch das politische System und die gegenwärtige Bundesregierung; Zufriedenheit mit der Arbeit der Bundesregierung; Einstellung zur Volkszählung; Erhalt einer schriftlichen Aufforderung zum Ausfüllen des Fragebogens; Teilnahmeabsicht an der Volkszählung vor Beginn der Zählung; eigene Bereitschaft zur Teilnahme an der Volkszählung, auch bei freiwilliger Teilnahme; vermutete Höhe der Nichtbeteiligung an der Volkszählung; Einstellung zur Volkszählung im Freundes- und Bekanntenkreis; Gespräche über die Volkszählung im sozialen Umfeld nach Abschluß der Erhebung und Zeitpunkt des letzten Gesprächs; Kenntnisse über die Inhalte der Volkszählungsbefragung; zusätzlich erwartete Fragen; Fragen, die ungern beantwortet wurden; Antwort- bzw. Boykottverhalten bei der Erhebung; Einstellung zu staatlichen Statistiken; Einstellung zu einer Bestrafung von Volkszählungsboykotteuren und Kenntnis von Verweigerungsfällen; vermutete Teilnahmebereitschaft der Bevölkerung sowie der Antwortehrlichkeit bei Freiwilligkeit der Teilnahme an der Volkszählung; freiwillige Weitergabe ausgewählter persönlicher Daten; Präferenz für Volkszählung oder Weitergabe von bereits vorliegenden Daten durch die Ämter; vermuteter Nutzen oder Schaden der Diskussion über die Volkszählung in den Medien und Gründe für diese Einschätzung; Einstellung zu früheren Boykottaufrufen und zum Befragungszeitpunkt; Beurteilung des Erfolgs der Boykottbewegung; Einstellung zu ausgewählten Argumenten für und gegen die Volkszählung; Nutzen einer Volkszählung; Einstellung zur Auskunftspflicht; Volkszählungsboykott als Protest gegen den Staat; Volkszählungsteilnahme als demokratische Pflicht; Selbsteinschätzung auf einem Links-Rechts-Kontinuum; vermutete Position der Bevölkerungsmehrheit auf einem Links-Rechts-Kontinuum; Demokratieverständnis und Vergleich dieses Anspruchs mit der Wirklichkeit in der Bundesrepublik; Parteipräferenz; persönlich oder von Personen des sozialen Umfelds empfundene Verletzung der Grundrechte durch Behördenmaßnahmen; Einstellung zur Technik; empfundene Unsicherheiten bei Behördenkontakten und Einstellung gegenüber Ämtern; Befürchtungen hinsicht lich einer Zweckentfremdung der persönlichen Volkszählungsdaten; Vertrauen in die Einhaltung des Datenschutzes; Einstellung zur Speicherung personenbezogener Daten; Wichtigkeit des Datenschutzes vermutete Einhaltung der Datenschutzbestimmungen; Kenntnis von Fällen des Datenmißbrauchs und Informationsquelle über solche Verstöße; vermutete Teilnahmebereitschaft an einer zukünftigen Volkszählung; Einstellung zu Meinungsumfragen (Skala); Teilnahmebereitschaft an einer Mikrozensus-Erhebung; Weitergabebereitschaft von Informationen aus der Privatsphäre an Freunde, Nachbarn, statistische Ämter und in wissenschaftlichen Umfragen; Einstellung zu ausgewählten staatlichen Statistiken; Antwortbereitschaft, um Statistiken zu ermöglichen; Angst vor Datenmißbrauch; Befürchtungen hinsichtlich einer Zweckentfremdung der persönlichen Daten durch ausgewählte Institutionen und Ämter (Skala); Einstellung zu ausgewählten illegalen Handlungen (Skala); Religiosität (Skalometer); Einstellung zu Glaubensfragen und zum Sinn des Lebens (Skala); Glaube an übersinnliche, unerklärliche Ereignisse sowie an Horoskope und Telepathie. Demographie: Geburtsmonat; Geburtsjahr; Geschlecht; Konfession; Schulbildung; Berufstätigkeit; Hochschule in Wohnortnähe; Studenten in der Wohngegend; Telefonbesitz. Interviewerrating: Anwesenheit Dritter beim Interview und Person, die die Anwesenheit erwünschte; Eingriffe Dritter in das Interview und Person, die die Intervention herbeiführte; Einstellung der beim Interview zusätzlich anwesenden Person zur Volkszählung; Anwesenheit weiterer Personen in anderen Räumen; Kooperationsbereitschaft und Zuverlässigkeit des Befragten. Zusätzlich verkodet wurde: Interviewdauer; Interviewdatum; Intervieweridentifikation; Interviewergeschlecht; Intervieweralter. Re-interview of the persons interviewed in the second panel wave (ZA Study No. 1589) as well as of persons interviewed in the first panel wave (ZA Study No. 1588), but not contacted in the survey of the second panel wave. Wiederbefragung der in der 2. Panel-Welle befragten Personen (ZA-Studien-Nr. 1589) sowie von Personen, die in der 1. Panel-Well interviewt wurden (ZA-Studien-Nr. 1588), bei der Befragung der 2. Panel-Welle aber nicht angetroffen wurden.

Context

This dataset expands on my earlier New York City Census Data dataset. It includes data from the entire country instead of just New York City. The expanded data will allow for much more interesting analyses and will also be much more useful at supporting other data sets.

Content

The data here are taken from the DP03 and DP05 tables of the 2015 American Community Survey 5-year estimates. The full datasets and much more can be found at the American Factfinder website. Currently, I include two data files:

1. acs2015_census_tract_data.csv: Data for each census tract in the US, including DC and Puerto Rico.
2. acs2015_county_data.csv: Data for each county or county equivalent in the US, including DC and Puerto Rico.

The two files have the same structure, with just a small difference in the name of the id column. Counties are political subdivisions, and the boundaries of some have been set for centuries. Census tracts, however, are defined by the census bureau and will have a much more consistent size. A typical census tract has around 5000 or so residents.

The Census Bureau updates the estimates approximately every year. At least some of the 2016 data is already available, so I will likely update this in the near future.

Acknowledgements

The data here were collected by the US Census Bureau. As a product of the US federal government, this is not subject to copyright within the US.

Inspiration

There are many questions that we could try to answer with the data here. Can we predict things such as the state (classification) or household income (regression)? What kinds of clusters can we find in the data? What other datasets can be improved by the addition of census data?

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, the decennial census is the official source of population totals for April 1st of each decennial year. In between censuses, the Census Bureau's Population Estimates Program produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units for states and counties..Information about the American Community Survey (ACS) can be found on the ACS website. Supporting documentation including code lists, subject definitions, data accuracy, and statistical testing, and a full list of ACS tables and table shells (without estimates) can be found on the Technical Documentation section of the ACS website.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2022 American Community Survey 1-Year Estimates.Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..An Internet "subscription" refers to a type of service that someone pays for to access the Internet such as a cellular data plan, broadband such as cable, fiber optic or DSL, or other type of service. This will normally refer to a service that someone is billed for directly for Internet alone or sometimes as part of a bundle..Internet access refers to whether or not a household uses or connects to the Internet, regardless of whether or not they pay for the service to do so. Data about Internet access was collected by asking if the respondent or any member of the household accessed the Internet. The respondent then selected one of the following three categories: "Yes, by paying a cell phone company or Internet service provider"; "Yes, without paying a cell phone company or Internet service provider"; or "No access to the Internet at the house, apartment or mobile home". Only respondents who answered "Yes, by paying a cell phone company or Internet service provider" were asked the subsequent question about the types of service they had access to such as dial-up, broadband (high speed) service such as cable, fiber-optic, or DSL, a cellular data plan, satellite or some other service..Caution should be used when comparing data for computer and Internet use before and after 2016. Changes in 2016 to the questions involving the wording as well as the response options resulted in changed response patterns in the data. Most noticeable are increases in overall computer ownership or use, the total of Internet subscriptions, satellite subscriptions, and cellular data plans for a smartphone or other mobile device. For more detailed information about these changes, see the 2016 American Community Survey Content Test Report for Computer and Internet Use located at https://www.census.gov/library/working-papers/2017/acs/2017_Lewis_01.html or the user note regarding changes in the 2016 questions located at https://www.census.gov/programs-surveys/acs/technical-documentation/user-notes/2017-03.html..When information is missing or inconsistent, the Census Bureau logically assigns an acceptable value using the response to a related question or questions. If a logical assignment is not possible, data are filled using a statistical process called allocation, which uses a similar individual or household to provide a donor value. The "Allocated" section is the number of respondents who received an allocated value for a particular subject..The 2022 American Community Survey (ACS) data generally reflect the March 2020 Office of Management and Budget (OMB) delineations of metropolitan and micropolitan statistical areas. In certain instances the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB delineations due to differences in the effective dates of the geographic entities..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on 2020 Census data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:- The estimate could not be computed because there were an insuffic...

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, the decennial census is the official source of population totals for April 1st of each decennial year. In between censuses, the Census Bureau's Population Estimates Program produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units and the group quarters population for states and counties..Information about the American Community Survey (ACS) can be found on the ACS website. Supporting documentation including code lists, subject definitions, data accuracy, and statistical testing, and a full list of ACS tables and table shells (without estimates) can be found on the Technical Documentation section of the ACS website.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2023 American Community Survey 1-Year Estimates.ACS data generally reflect the geographic boundaries of legal and statistical areas as of January 1 of the estimate year. For more information, see Geography Boundaries by Year..Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..Users must consider potential differences in geographic boundaries, questionnaire content or coding, or other methodological issues when comparing ACS data from different years. Statistically significant differences shown in ACS Comparison Profiles, or in data users' own analysis, may be the result of these differences and thus might not necessarily reflect changes to the social, economic, housing, or demographic characteristics being compared. For more information, see Comparing ACS Data..Data about computer and Internet use were collected by asking respondents to select "Yes" or "No" to each type of computer and each type of Internet subscription. Therefore, respondents were able to select more than one type of computer and more than one type of Internet subscription..An Internet "subscription" refers to a type of service that someone pays for to access the Internet such as a cellular data plan, broadband such as cable, fiber optic or DSL, or other type of service. This will normally refer to a service that someone is billed for directly for Internet alone or sometimes as part of a bundle..Examples of "Internet access without a subscription" include cases such as free Internet service provided by a respondent's town or city or free Internet service a university may provide for their students.."Internet access" refers to whether or not a household uses or connects to the Internet, regardless of whether or not they pay for the service to do so. Data about Internet access was collected by asking if the respondent or any member of the household accessed the Internet. The respondent then selected one of the following three categories: "Yes, by paying a cell phone company or Internet service provider"; "Yes, without paying a cell phone company or Internet service provider"; or "No access to the Internet at the house, apartment or mobile home". Only respondents who answered "Yes, by paying a cell phone company or Internet service provider" were asked the subsequent question about the types of service they had access to such as dial-up, broadband (high speed) service such as cable, fiber-optic, or DSL, a cellular data plan, satellite or some other service..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on 2020 Census data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution. For a 5-year median estimate, the margin of error associated with a median was larger than the median itself.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (...

In Austria a population census takes place every 10 years; this census contains a program of important statistical data on population and employment. They roughly corresponds to the information in the Mikrozensus standard survey but are more detailed (for instance with question on the connection of the place of residence and the workplace, questions on education, confession, etc.) Population and Mikrozensus are closely linked which the name already implies: Mikrozensus means a small-scale population census; this should demonstrate that what the population census reports only every 10 years, the Mikrozensus reports through the method of ongoing sampling. These ongoing sample are also collected in the years of the population census. The Mikrozensus however is far more detailed than the survey program of the population census because the Mikrozensus special surveys offer the possibility of asking questions which are fare beyond the scope of the population census. This complementary function of Mikrozensus and population census becomes especially obvious in the June-survey: certain questions that could not be posed in the population census due to the limited program were answered in the Mikrozensus via sampling. These were the topics: questions on the social stratification of the population questions on fertility and succession of birth questions on the silent Human Resources

Graph and download economic data for Expenses for Telephone Answering Services, Establishments Subject To Federal Income Tax, Employer Firms (TASEESTFITE3561421) from 2003 to 2022 about phone, telecom, employer firms, establishments, tax, expenditures, federal, services, income, and USA.

Abstract

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

Geographic coverage

National

Analysis unit

• Household;
• Indivudual.

Universe

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

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

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

Kind of data

Census/enumeration data [cen]

Sampling procedure

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

Mode of data collection

Face-to-face [f2f]

Research instrument

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

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

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

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

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

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

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

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

Cleaning operations

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

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

About this dataset

Context

The dataset tabulates the population of Nome Census Area by gender, including both male and female populations. This dataset can be utilized to understand the population distribution of Nome Census Area across both sexes and to determine which sex constitutes the majority.

Key observations

There is a slight majority of male population, with 52.28% of total population being male. Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis. No further analysis is done on the data reported from the Census Bureau.

Variables / Data Columns

• Gender: This column displays the Gender (Male / Female)
• Population: The population of the gender in the Nome Census Area is shown in this column.
• % of Total Population: This column displays the percentage distribution of each gender as a proportion of Nome Census Area total population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Nome Census Area Population by Race & Ethnicity. You can refer the same here

This table is part of a series of tables that present a portrait of Canada based on the various census topics. The tables range in complexity and levels of geography. Content varies from a simple overview of the country to complex cross-tabulations; the tables may also cover several censuses.

Note: This version supersedes version 1: https://doi.org/10.15482/USDA.ADC/1522654. In Fall of 2019 the USDA Food and Nutrition Service (FNS) conducted the third Farm to School Census. The 2019 Census was sent via email to 18,832 school food authorities (SFAs) including all public, private, and charter SFAs, as well as residential care institutions, participating in the National School Lunch Program. The questionnaire collected data on local food purchasing, edible school gardens, other farm to school activities and policies, and evidence of economic and nutritional impacts of participating in farm to school activities. A total of 12,634 SFAs completed usable responses to the 2019 Census. Version 2 adds the weight variable, “nrweight”, which is the Non-response weight. Processing methods and equipment used The 2019 Census was administered solely via the web. The study team cleaned the raw data to ensure the data were as correct, complete, and consistent as possible. This process involved examining the data for logical errors, contacting SFAs and consulting official records to update some implausible values, and setting the remaining implausible values to missing. The study team linked the 2019 Census data to information from the National Center of Education Statistics (NCES) Common Core of Data (CCD). Records from the CCD were used to construct a measure of urbanicity, which classifies the area in which schools are located. Study date(s) and duration Data collection occurred from September 9 to December 31, 2019. Questions asked about activities prior to, during and after SY 2018-19. The 2019 Census asked SFAs whether they currently participated in, had ever participated in or planned to participate in any of 30 farm to school activities. An SFA that participated in any of the defined activities in the 2018-19 school year received further questions. Study spatial scale (size of replicates and spatial scale of study area) Respondents to the survey included SFAs from all 50 States as well as American Samoa, Guam, the Northern Mariana Islands, Puerto Rico, the U.S. Virgin Islands, and Washington, DC. Level of true replication Unknown Sampling precision (within-replicate sampling or pseudoreplication) No sampling was involved in the collection of this data. Level of subsampling (number and repeat or within-replicate sampling) No sampling was involved in the collection of this data. Study design (before–after, control–impacts, time series, before–after-control–impacts) None – Non-experimental Description of any data manipulation, modeling, or statistical analysis undertaken Each entry in the dataset contains SFA-level responses to the Census questionnaire for SFAs that responded. This file includes information from only SFAs that clicked “Submit” on the questionnaire. (The dataset used to create the 2019 Farm to School Census Report includes additional SFAs that answered enough questions for their response to be considered usable.) In addition, the file contains constructed variables used for analytic purposes. The file does not include weights created to produce national estimates for the 2019 Farm to School Census Report. The dataset identified SFAs, but to protect individual privacy the file does not include any information for the individual who completed the questionnaire. Description of any gaps in the data or other limiting factors See the full 2019 Farm to School Census Report [https://www.fns.usda.gov/cfs/farm-school-census-and-comprehensive-review] for a detailed explanation of the study’s limitations. Outcome measurement methods and equipment used None Resources in this dataset:Resource Title: 2019 Farm to School Codebook with Weights. File Name: Codebook_Update_02SEP21.xlsxResource Description: 2019 Farm to School Codebook with WeightsResource Title: 2019 Farm to School Data with Weights CSV. File Name: census2019_public_use_with_weight.csvResource Description: 2019 Farm to School Data with Weights CSVResource Title: 2019 Farm to School Data with Weights SAS R Stata and SPSS Datasets. File Name: Farm_to_School_Data_AgDataCommons_SAS_SPSS_R_STATA_with_weight.zipResource Description: 2019 Farm to School Data with Weights SAS R Stata and SPSS Datasets

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.

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, it is the Census Bureau's Population Estimates Program that produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units for states and counties..Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Technical Documentation section.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2017-2021 American Community Survey 5-Year Estimates.Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..An Internet "subscription" refers to a type of service that someone pays for to access the Internet such as a cellular data plan, broadband such as cable, fiber optic or DSL, or other type of service. This will normally refer to a service that someone is billed for directly for Internet alone or sometimes as part of a bundle..Internet access refers to whether or not a household uses or connects to the Internet, regardless of whether or not they pay for the service to do so. Data about Internet access was collected by asking if the respondent or any member of the household accessed the Internet. The respondent then selected one of the following three categories: "Yes, by paying a cell phone company or Internet service provider"; "Yes, without paying a cell phone company or Internet service provider"; or "No access to the Internet at the house, apartment or mobile home". Only respondents who answered "Yes, by paying a cell phone company or Internet service provider" were asked the subsequent question about the types of service they had access to such as dial-up, broadband (high speed) service such as cable, fiber-optic, or DSL, a cellular data plan, satellite or some other service..When information is missing or inconsistent, the Census Bureau logically assigns an acceptable value using the response to a related question or questions. If a logical assignment is not possible, data are filled using a statistical process called allocation, which uses a similar individual or household to provide a donor value. The "Allocated" section is the number of respondents who received an allocated value for a particular subject..The 2017-2021 American Community Survey (ACS) data generally reflect the March 2020 Office of Management and Budget (OMB) delineations of metropolitan and micropolitan statistical areas. In certain instances, the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB delineation lists due to differences in the effective dates of the geographic entities..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2010 data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution. For a 5-year median estimate, the margin of error associated with a median was larger than the median itself.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (X) The estimate or margin of error is not applicable or not available.median- The median falls in the lowest interval of an open-ended distribution (for example "2,500-")median+ The median falls in the highest interval of an open-ended distribution (for example "250,000+").** The margin of error could not be computed because there were an insufficient number of sample observations.*** The margin of error could not be computed because the median falls in the lowest interval or highest interval of an open-ended distribution.***** A margin of error is not appropriate because the corresponding estimate is con...