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

Abstract

The key objective of every census is to count every person (man, woman, child) resident in the country on census night, and also collect information on assorted demographic (sex, age, marital status, citizenship) and socio-economic (education/qualifications; labour force and economic activity) information, as well as data pertinent to household and housing characteristics. This count provides a complete picture of the population make-up in each village and town, of each island and region, thus allowing for an assessment of demographic change over time.

The need for a national census became obvious to the Census Office (Bureau of Statistics) during 1997 when a memo was submitted to government officials proposing the need for a national census in an attempt to update old socio-economic figures. The then Acting Director of the Bureau of Statistics and his predecessor shared a similar view: that the 'heydays' and 'prosperity' were nearing their end. This may not have been apparent, as it took until almost mid-2001 for the current Acting Government Statistician to receive instructions to prepare planning for a national census targeted for 2002. It has been repeatedly said that for adequate planning at the national level, information about the characteristics of the society is required. With such information, potential impacts can be forecast and policies can be designed for the improvement and benefit of society. Without it, the people, national planners and leaders will inevitably face uncertainties.

Geographic coverage

National coverage as the Population Census covers the whole of Nauru.

Analysis unit

• Household
• Individual (in a private household dwelling, institutions and non-private dwelling).

Universe

The Census covers all individuals living in private and non-private dwellings and institutions.

Kind of data

Census/enumeration data [cen]

Sampling deviation

There is no sampling for the population census, full coverage.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaire was based on the Pacific Islands Model Population and Housing Census Form and the 1992 census, and comprised two parts: a set of household questions, asked only of the head of household, and an individual questionnaire, administered to each household member. Unlike the previous census, which consisted of a separate household form plus two separate individual forms for Nauruans and non-Nauruans, the 2 002 questionnaire consisted of only one form separated into different parts and sections. Instructions (and skips) were desi

The questionnaire cover recorded various identifiers: district name, enumeration area, house number, number of households (family units) residing, total number of residents, gender, and whether siblings of the head of the house were also recorded. The second page, representing a summary page, listed every individual residing within the house. This list was taken by the enumerator on the first visit, on the eve of census night. The first part of the census questionnaire focused on housing-related questions. It was administered only once in each household, with questions usually asked of the household head. The household form asked the same range of questions as those covered in the 1992 census, relating to type of housing, structure of outer walls, water supply sources and storage, toilet and cooking facilities, lighting, construction materials and subsistence-type activities. The second part of the census questionnaire focused on individual questions covering all household members. This section was based on the 1992 questions, with notable differences being the exclusion of income-level questions and the expansion of fertility and mortality questions. As in 1992, a problem emerged during questionnaire design regarding the question of who or what should determine a ‘Nauruan’. Unlike the 1992 census, where the emphasis was on blood ties, the issue of naturalisation and citizenship through the sale of passports seriously complicated matters in 2 002. To resolve this issue, it was decided to apply two filtering processes: Stage 1 identified persons with tribal heritage through manual editing, and Stage 2 identified persons of Nauruan nationality and citizenship through designed skips in the questionnaire that were incorporated in the data-processing programming.

The topics of questions for each of the parts include: - Person Particulars: - name - relationship - sex - ethnicity - religion - educational attainment - Economic Activity (to all persons 15 years and above): - economic activity - economic inactive - employment status - Fertility: - Fertility - Mortality - Labour Force Activity: - production of cash crops - fishing - own account businesses - handicrafts. - Disability: - type of disability - nature of disability - Household and housing: - electricity - water - tenure - lighting - cooking - sanitation - wealth ownerships

Cleaning operations

Coding, data entry and editing Coding took longer than expected when the Census Office found that more quality-control checks were required before coding could take place and that a large number of forms still required attention. While these quality-control checks were supposed to have been done by the supervisors in the field, the Census Office decided to review all census forms before commencing the coding. This process took approximately three months, before actual data processing could begin. The amount of additional time required to recheck the quality of every census form meant that data processing fell behind schedule. The Census Office had to improvise, with a little pressure from external stakeholders, and coding, in conjunction with data entry, began after recruiting two additional data entry personnel. All four Census Office staff became actively involved with coding, with one staff member alternating between coding and data entry, depending on which process was dropping behind schedule. In the end, the whole process took almost two months to complete. Prior to commencing data entry, the Census Office had to familiarise itself with the data entry processing system. For this purpose, SPC’s Demography/Population Programme was invited to lend assistance. Two office staff were appointed to work with Mr Arthur Jorari, SPC Population Specialist, who began by revising their skills for the data processing software that had been introduced by Dr McMurray. This training attachment took two weeks to complete. Data entry was undertaken using the 2 .3 version of the US Census Bureau’s census and surveying processing software, or CSPro2.3. This version was later updated to CSPro2.4, and all data were transferred accordingly. Technical assistance for data editing was provided by Mr Jorari over a two-week period. While most edits were completed during this period, it was discovered that some batches of questionnaires had not been entered during the initial data capturing. Therefore, batch-edit application had to be regenerated. This process was frequently interrupted by power outages prevailing at the time, which delayed data processing considerably and also required much longer periods of technical support to the two Nauru data processing staff via phone or email (when available).

Data appraisal

Data was compared with Administrative records after the Census to review the quality and reliability of the data.

Abstract

The first national census of Timor-Leste was conducted from the 11th of July to the 30th of July in 2004 with 4,000 interviewers visiting over 190,000 households across the country. The Census provides Asia's newest nation with its first full population count after the traumatic events of 1999 and base line statistics on housing, employment, fertility and literacy. The census statistical data and indicators, at both national and district levels, will assist the country's administrators and international organisations in planning for sustainable development programs.

In July 2002, a mission comprised of experts from the United Nations Population Division, the Australian Bureau of Statistics, and the Malaysian Department of Statistics was asked to explore the feasibility of conducting a Population and Housing Census in the newly independent Timor-Leste. Although considered as a difficult undertaking, it was determined to be viable.

UNFPA organized the necessary technical and human resource support and provided the major part of the funding needed to carry out the census. Since 2002 two UNFPA Census Projects have been supporting census activities and have expended more than three million dollars. This major financial contribution was supplemented by the assistance of other donors: the United States, which among other things paid for some equipment, the printing of questionnaires and other forms, and also funded technical assistance for data editing; Ireland, which funded the census publicity campaign; New Zealand, which provided funding for technical experts; and Australia, which assisted in the training of data input personnel and in funding several technical assistance missions.

Geographic coverage

National

Analysis unit

• Individual,
• Households.

Kind of data

Census/enumeration data [cen]

Sampling procedure

No sampling - whole universe covered

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaire developed for the pilot census went through a review. A consultant from Statistics New Zealand worked on the questionnaires and talked with government ministries, various UN agencies, NGO's and other interested parties about content and format. Where changes were made, small field tests were carried out to confirm workability and acceptability. By January 2004, the questionnaires were ready to present to the Census Technical Committee and then to government agencies for formal acceptance. During that process, some minor changes were made, but the basic questionnaire was maintained.

Three types of questionnaires were used: one for households, one for institutions (prisons, orphanages, convents, hospitals and boarding schools) and one for hotels. This section refers only to the household questionnaire.

The household questionnaire was prepared in four languages: Tetum, Portuguese, Indonesian and English.

The questionnaire was well designed. The format, wording and arrangement of questions received a great deal of attention. It was short, simple, easy to apply, and included most of the standard census questions and items. The purpose here is not to evaluate the questionnaire in detail, but it is important to mention that the data collected with it has proved to be extremely useful for a number or purposes. The usefulness of the data is a good indicator of the format adequacy and organization of the questionnaire and the relevance of the questions included. It is also important to highlight that, up to now, various data analyses have shown that most of the information is reliable. However, it is also important to recognize there is plenty of space for improvement and the questionnaire for the 2010 Census will be much better. Actually, several analyses of the data obtained with the questionnaire clearly show the need to modify the next census questionnaire and, especially, include additional questions.

Cleaning operations

The first activity was checking and editing the waypoint file. Three main problems were found: duplicate waypoints, waypoints where letters were used instead of numbers, and invalid waypoint numbers. In all cases the errors were manually corrected. Duplicate waypoints were removed, alphanumeric numbers with "o" instead of "0" or "B" instead of "8" were rectified, and waypoints close to invalid waypoints were compared to obtain a clue as to what the likely correct number should be.

After linking waypoints with questionnaire data it was realized that the vast majority of waypoint numbers could be linked to their corresponding dwelling sticker numbers. However, it also became apparent that there were still discrepancies between the two databases: Some questionnaires could not be linked to waypoints and some waypoints could not be linked to questionnaires. These problems were solved with the help of maps, comparisons with nearby waypoints and, in some cases, with new visits to suspect dwellings or entire areas. CSPro, a software package developed by the US Bureau of the Census, was used to capture, process, and edit data.

The data capture team was formed as soon as the interviewing was completed. Staff received training in subjects such as understanding the census process, the design of the census forms, and how to operate the data-entry program. Approximately 38 data-entry operators undertook the work in several shifts. The data was captured by keyboard.

After the data was entered, a process of editing and imputation of data was conducted.

It is important to mention data capture and processing was a weak part of the census operation. Data entry had to be repeated because of the many mistakes and errors done the first time. In addition, after the data was finally entered, it took an unnecessarily long period to process end edit it. Data-capture ended in February 2005 and the edited master file was not ready until December 2005. Even then there were still some inconsistencies, especially in fertility and school enrolment data. Such inconsistencies are minor, but they may reduce the credibility of some results.

The underlying causes of the previous problems were poor use of technical assistance, largely due to lack of management continuity. The NSD is aware of this weakness and the need to address it for the next census.

Abstract

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

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

Geographic coverage

A hierarchical geographic presentation shows the geographic entities in a superior/subordinate structure in census products. This structure is derived from the legal, administrative, or areal relationships of the entities. The hierarchical structure is depicted in report tables by means of indentation. The following structure is used for the 2005 Census of the Republic of Palau:

Republic of Palau State Hamlet/Village Enumeration District Block

Analysis unit

Individuals Families Households General Population

Universe

The Census covered all the households and respective residents in the entire country.

Kind of data

Census/enumeration data [cen]

Sampling procedure

Not applicable to a full enumeration census.

Mode of data collection

Face-to-face [f2f]

Research instrument

The 2005 Palau Census of Population and Housing comprises three parts: 1. Housing - one form for each household 2. Population - one for for each member of the household 3. People who have left home - one form for each household.

Cleaning operations

Full scale processing and editing activiities comprised eight separate sessions either with or separately but with remote guidance of the U.S. Census Bureau experts to finalize all datasets for publishing stage.

Processing operation was handled with care to produce a set of data that describes the population as clearly and accurately as possible. To meet this objective, questionnaires were reviewed and edited during field data collection operations by crew leaders for consistency, completeness, and acceptability. Questionnaires were also reviewed by census clerks in the census office for omissions, certain inconsistencies, and population coverage. For example, write-in entries such as "Don't know" or "NA" were considered unacceptable in certain quantities and/or in conjunction with other data omissions.

As a result of this review operation, a telephone or personal visit follow-up was made to obtain missing information. Potential coverage errors were included in the follow-up, as well as questionnaires with omissions or inconsistencies beyond the completeness and quality tolerances specified in the review procedures.

Subsequent to field operations, remaining incomplete or inconsistent information on the questionnaires was assigned using imputation procedures during the final automated edit of the collected data. Allocations, or computer assignments of acceptable data in place of unacceptable entries or blanks, were needed most often when an entry for a given item was lacking or when the information reported for a person or housing unit on that item was inconsistent with other information for that same person or housing unit. As in previous censuses, the general procedure for changing unacceptable entries was to assign an entry for a person or housing unit that was consistent with entries for persons or housing units with similar characteristics. The assignment of acceptable data in lace of blanks or unacceptable entries enhanced the usefulness of the data.

Another way to make corrections during the computer editing process is substitution. Substitution is the assignment of a full set of characteristics for a person or housing unit. Because of the detailed field operations, substitution was not needed for the 2005 Census.

Sampling error estimates

Sampling Error is not applicable to full enumeration censuses.

Data appraisal

In any large-scale statistical operation, such as the 2005 Census of the Republic of Palau, human- and machine-related errors were anticipated. These errors are commonly referred to as nonsampling errors. Such errors include not enumerating every household or every person in the population, not obtaining all required information form the respondents, obtaining incorrect or inconsistent information, and recording information incorrectly. In addition, errors can occur during the field review of the enumerators' work, during clerical handling of the census questionnaires, or during the electronic processing of the questionnaires.

To reduce various types of nonsampling errors, a number of techniques were implemented during the planning, data collection, and data processing activities. Quality assurance methods were used throughout the data collection and processing phases of the census to improve the quality of the data.

Abstract

The 2007/08 Agricultural Sample Census was designed to meet the data needs of a wide range of users down to district level including policy makers at local, regional and national levels, rural development agencies, funding institutions, researchers, NGOs, farmers' organizations, and others. The dataset is both more numerous in its sample and detailed in its scope and coverage so as to meet the user demand.

The census was carried out in order to:

• Identify any structural changes,in the size of farm household holdings, crop and livestock production, farm input and implement use. It also seeks to determine if there are any improvements in the rural infrastructure and the level of agricultural households living conditions;

-Provide benchmark data on productivity, production and agricultural practices in relation to policies and interventions promoted by the Ministry of Agriculture and Food Security and other stakeholders; and

• Obtain data that will be used to address specific issues such as: food security, rural poverty, gender, agro-processing, marketing and service delivery.

Geographic coverage

Tanzania Mainland and Zanzibar

Analysis unit

Community, Household, Individual

Universe

Small scale farmers, Large Scale Farmers, Community

Kind of data

Sample survey data [ssd]

Sampling procedure

The Mainland sample consisted of 3,192 villages. The total Mainland sample was 47,880 agricultural households while in Zanzibar, a total of 317 EAs were selected and 4,755 agricultural households were covered.

The villages were drawn from the National Master Sample (NMS) developed by the National Bureau of Statistics (NBS) to serve as a national framework for the conduct of household based surveys in the country. The National Master Sample was developed from the previous 2002 Population and Housing Census.

The numbers of villages/Enumeration Areas (EAs) were selected for the first stage with a probability proportional to the number of villages/EAs in each district. In the second stage, 15 households were selected from a list of agricultural households in each village/EA using systematic random sampling.

Mode of data collection

Face-to-face [f2f]

Research instrument

The census used three different questionnaires: - Small scale farm questionnaire - Community level questionnaire - Large scale farm questionnaire

The small scale farm questionnaire was the main census instrument and it included questions related to crop and livestock production and practices; population demographics; access to services, community resources and infrastructure; issues on poverty and gender. The main topics covered were:

• Household demographics and activities of the household members
• Land access, ownership, tenure and use
• Crop and livestock production and productivity
• Access to inputs and farming implements
• Access and use of credit
• Access to infrastructure (roads, district and regional headquarters, markets, advisory services, schools, hospitals).
• Crop marketing, storage and agro processing
• Tree farming, agro-forestry, and fish farming
• Access and use of communal resources (grazing land, communal forests, water for humans and livestock, beekeeping)
• Investment activities ( irrigation structures, water harvesting, erosion control, fencing)
• Off farm income and non agricultural related activities
• Households living conditions (housing, sanitary facilities )
• Livelihood constraints
• Poverty Indicators

The community level questionnaire was designed to collect village level data such as access and use of common resources, community tree plantation and seasonal farm gate prices.

The Large Scale Farm questionnaire was administered to large farms either privately or corporately managed.

Cleaning operations

Data editing took place at a number of stages throughout the processing, including: - Manual cleaning exercisePrior to scanning. (Questionnaires found dirty or damaged and generally unsuitable for scanning were put aside for manual data entry ) - CSPro was used for data entry of all Large Scale Farms and Community based questionnaires - Scanning and ICR data capture technology for the smallholder questionnaire - There was an Interactive validation during the ICR extraction process. - The use of a batch validation program developed in CSPro. This was used in order to identify inconsistencies within a questionnaire. - Statistical Package for Social Sciences (SPSS) was used to produce the Census tabulations - Microsoft Excel was used to organize the tables, charts and compute additional indicators -Arc GIS (Geographical Information System) was used in producing the maps. - Microsoft Word was used in compiling and writing up the reports

Abstract

Agriculture significantly contributes to Indonesia’s economy. Up to 2013, this sector is the second largest contribution behind manufacturing industry sector, even though the value of the contribution keeps declining from time to time. However, the interesting fact is that approximately a third of total labor force depends on this sector (National Labor Force Survey, August 2013). To develop agriculture sector requires detailed and accurate data on various characteristics of agricultural holdings. Therefore, to meet the requirement for the data, BPS (Statistics Indonesia) as the national statistical office has conducted not only surveys but also census on agriculture. Since independence, Indonesia has carried out national agricultural census six times. The first was the 1963 Agricultural Census that might hardly be successful in practice but served as a reference to the next censuses refinement.

Objectives of Agricultural Census 2013:

The data obtained from the census has distinct characteristics compared to the data from annual agricultural surveys. The main purposes of the 2013 Census are as follows:

a. Collecting accurate and comprehensive data that delineate agriculture condition in Indonesia.

b. Building sampling frame to be used for agricultural surveys.

c. Collecting information on agricultural population, peasants or farmers with = 0.5 hectare of farmland), crops and livestock, landowning and cultivation, etc. The result of the 2013 Census will be used as benchmarks for various agricultural surveys.

Geographic coverage

National coverage

Analysis unit

Households

Universe

The statistical unit was the agricultural holding, defined as an activity producing agricultural products with the aim of partially or completely selling or exchanging the products, except when food crops were exclusively for self-consumption. In general, two types of holdings were covered in the household sector: agricultural production households ("household agricultural holding") and other households ("non-agricultural households").

Kind of data

Census/enumeration data [cen]

Sampling procedure

(a) Complete Enumeration The 2013 Agricultural Census applied complete enumeration of agricultural households. It was meant to collect data and information on population of agricultural holdings, number of crops and livestock, and farmland area distribution. The result of the census will be used as sampling frame and benchmark for further agricultural surveys.The agricultural census activities also included the surveys that provide supporting data for the census itself. The beginning activity in the implementation stage was updating households and buildings, conducted in May 2013, in order to discover current information on agricultural households in every census block. The result will be in the form of lists that distinguish between agricultural and non-agricultural households. In operation, the census was supported by 246,412 enumerators and team coordinators.

(b) Strategy There were two methods of enumeration, door to door and snowball. Door to door was conducting visit to all households both listed and unlisted in the block census. Area coverage of this method was rural villages and urban villages with the majority of agricultural business (in district) and the areas with the majority of agricultural business (in municipality). Meanwhile, the snowball method was carried out in urban villages with the majority of agricultural business (in district) and urban areas with the majority of nonagricultural business (in municipality). Through the enumeration, it was founded there are 26,135,469 agricultural households.

Mode of data collection

Face-to-face [f2f]

Research instrument

1. The listing of households engaged in the agricultural sector was conducted using the ST2013-P form ("door-to-door" and "snowball").

2. The census questionnaire used the ST2013-L form.

3. Other specific questionnaires were used for collecting information in subsequent surveys as part of the CA 2013 programme:

(i) the Agricultural Household Income Survey, in 2013 (ST2013-SPP.S form) (ii) the Agricultural Households Sub-sector Survey, in 2014 (iii) the Survey of Forestry Households in 2014 (ST2013-SKH form)

The CA 2013 questionnaire covered all 16 core items recommended for the WCA 2010 round, namely;

0001 Identification and location of agricultural holding 0002+ Legal status of agricultural holder 0003 Sex of agricultural holder 0004 Age of agricultural holder 0005 Household size 0006 Main purpose of production of the holding 0007 Area of holding according to land use types 0008 Total area of holding 0009 Land tenure types on the holding 0010 Presence of irrigation on the holding 0011 Types of temporary crops on the holding 0012 Types of permanent crops on the holding and whether in compact plantation 0013 Number of animals on the holding for each livestock type 0014 Presence of aquaculture on the holding 0015+ Presence of forest and other wooded land on the holding 0016 Other economic production activities of the holding's enterprise

See questionnaire in external materials tab

Cleaning operations

(a) Data Processing Data processing of The 2013 Agricultural Census is a follow-up activity after the enumeration. This activity will produce the intended data in accurate and timely manner. It doing the data processing, it was supported by data capture technologies by scanner machine in all provinces and district/municipalities from June to December 2013. The stages of the data processing were as follows:

1. Pre-computer processing:
2. Document receiving
3. Document batching

4. Editing and coding

5. Computer processing:

6. Data scanning

7. Data tabulation

All data processing used a particular network system in processing center. This network system was made for the census data processing purposes only. It was separated from local and other networking, so it can prevent the large data traffic that could slow down the data processing.

Sampling error estimates

(nonsampling error). Errors made by the enumerators might be in the forms of coverage error (either under-coverage or over-coverage), and content error. Error in completing the questionnaire were mostly derived from the respondents which was called response error.

Data appraisal

PES was conducted immediately after the completion of the data collection process and independently from the census enumeration. This survey sought to determine the level of coverage accuracy, the level of content accuracy in the implementation of the CA 2013, and to facilitate the use of census data by giving deeper insights on the quality and limitations of census data

Abstract

The primary objective of the 2017 Indonesia Dmographic and Health Survey (IDHS) is to provide up-to-date estimates of basic demographic and health indicators. The IDHS provides a comprehensive overview of population and maternal and child health issues in Indonesia. More specifically, the IDHS was designed to: - provide data on fertility, family planning, maternal and child health, and awareness of HIV/AIDS and sexually transmitted infections (STIs) to help program managers, policy makers, and researchers to evaluate and improve existing programs; - measure trends in fertility and contraceptive prevalence rates, and analyze factors that affect such changes, such as residence, education, breastfeeding practices, and knowledge, use, and availability of contraceptive methods; - evaluate the achievement of goals previously set by national health programs, with special focus on maternal and child health; - assess married men’s knowledge of utilization of health services for their family’s health and participation in the health care of their families; - participate in creating an international database to allow cross-country comparisons in the areas of fertility, family planning, and health.

Geographic coverage

National coverage

Analysis unit

• Household
• Individual
• Children age 0-5
• Woman age 15-49
• Man age 15-54

Universe

The survey covered all de jure household members (usual residents), all women age 15-49 years resident in the household, and all men age 15-54 years resident in the household.

Kind of data

Sample survey data [ssd]

Sampling procedure

The 2017 IDHS sample covered 1,970 census blocks in urban and rural areas and was expected to obtain responses from 49,250 households. The sampled households were expected to identify about 59,100 women age 15-49 and 24,625 never-married men age 15-24 eligible for individual interview. Eight households were selected in each selected census block to yield 14,193 married men age 15-54 to be interviewed with the Married Man's Questionnaire. The sample frame of the 2017 IDHS is the Master Sample of Census Blocks from the 2010 Population Census. The frame for the household sample selection is the updated list of ordinary households in the selected census blocks. This list does not include institutional households, such as orphanages, police/military barracks, and prisons, or special households (boarding houses with a minimum of 10 people).

The sampling design of the 2017 IDHS used two-stage stratified sampling: Stage 1: Several census blocks were selected with systematic sampling proportional to size, where size is the number of households listed in the 2010 Population Census. In the implicit stratification, the census blocks were stratified by urban and rural areas and ordered by wealth index category.

Stage 2: In each selected census block, 25 ordinary households were selected with systematic sampling from the updated household listing. Eight households were selected systematically to obtain a sample of married men.

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

Mode of data collection

Face-to-face [f2f]

Research instrument

The 2017 IDHS used four questionnaires: the Household Questionnaire, Woman’s Questionnaire, Married Man’s Questionnaire, and Never Married Man’s Questionnaire. Because of the change in survey coverage from ever-married women age 15-49 in the 2007 IDHS to all women age 15-49, the Woman’s Questionnaire had questions added for never married women age 15-24. These questions were part of the 2007 Indonesia Young Adult Reproductive Survey Questionnaire. The Household Questionnaire and the Woman’s Questionnaire are largely based on standard DHS phase 7 questionnaires (2015 version). The model questionnaires were adapted for use in Indonesia. Not all questions in the DHS model were included in the IDHS. Response categories were modified to reflect the local situation.

Cleaning operations

All completed questionnaires, along with the control forms, were returned to the BPS central office in Jakarta for data processing. The questionnaires were logged and edited, and all open-ended questions were coded. Responses were entered in the computer twice for verification, and they were corrected for computer-identified errors. Data processing activities were carried out by a team of 34 editors, 112 data entry operators, 33 compare officers, 19 secondary data editors, and 2 data entry supervisors. The questionnaires were entered twice and the entries were compared to detect and correct keying errors. A computer package program called Census and Survey Processing System (CSPro), which was specifically designed to process DHS-type survey data, was used in the processing of the 2017 IDHS.

Response rate

Of the 49,261 eligible households, 48,216 households were found by the interviewer teams. Among these households, 47,963 households were successfully interviewed, a response rate of almost 100%.

In the interviewed households, 50,730 women were identified as eligible for individual interview and, from these, completed interviews were conducted with 49,627 women, yielding a response rate of 98%. From the selected household sample of married men, 10,440 married men were identified as eligible for interview, of which 10,009 were successfully interviewed, yielding a response rate of 96%. The lower response rate for men was due to the more frequent and longer absence of men from the household. In general, response rates in rural areas were higher than those in urban areas.

Sampling error estimates

The estimates from a sample survey are affected by two types of errors: (1) nonsampling errors and (2) sampling errors. Nonsampling errors result from mistakes made in implementing data collection and data processing, such as failure to locate and interview the correct household, misunderstanding the questions on the part of either the interviewer or the respondent, and data entry errors. Although numerous efforts were made during the implementation of the 2017 Indonesia Demographic and Health Survey (2017 IDHS) to minimize this type of error, nonsampling errors are impossible to avoid and difficult to evaluate statistically.

Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents selected in the 2017 IDHS is only one of many samples that could have been selected from the same population, using the same design and identical size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling error is a measure of the variability among all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results.

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

If the sample of respondents had been selected as a simple random sample, it would have been possible to use straightforward formulas for calculating sampling errors. However, the 2017 IDHS sample is the result of a multi-stage stratified design, and, consequently, it was necessary to use more complex formulas. The computer software used to calculate sampling errors for the 2017 IDHS is a STATA program. This program used the Taylor linearization method for variance estimation for survey estimates that are means or proportions. The Jackknife repeated replication method is used for variance estimation of more complex statistics such as fertility and mortality rates.

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

Data appraisal

Data Quality Tables - Household age distribution - Age distribution of eligible and interviewed women - Age distribution of eligible and interviewed men - Completeness of reporting - Births by calendar year - Reporting of age at death in days - Reporting of age at death in months

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

The once-a-decade decennial census was conducted in April 2010 by the U.S. Census Bureau. This count of every resident in the United States was mandated by Article I, Section 2 of the Constitution and all households in the U.S. and individuals living in group quarters were required by law to respond to the 2010 Census questionnaire. The data collected by the decennial census determine the number of seats each state has in the U.S. House of Representatives and is also used to distribute billions in federal funds to local communities. The questionnaire consisted of a limited number of questions but allowed for the collection of information on the number of people in the household and their relationship to the householder, an individual's age, sex, race and Hispanic ethnicity, the number of housing units and whether those units are owner- or renter-occupied, or vacant. Results for sub-state geographic areas in New Mexico were released in a series of data products. These data come from Summary File 1 (SF-1). The geographic coverage for SF-1 includes the state, counties, places (both incorporated and unincorporated communities), tribal lands, school districts, census tracts, block groups and blocks, among others. The data in these particular RGIS Clearinghouse tables are for New Mexico and all census tracts in the state. There are two data tables in this file. Table DC10_00586 shows the number of households by the following categories--total households; total family households; husband-wife family households; total other family households; male householder, no wife present; female householder, no husband present; total nonfamily households; nonfamily households with householder living along; and finally, nonfamily households with householder not living alone. Table DC10_00587 shows percent distribution of households for each of these same categories. These files, along with file-specific descriptions (in Word and text formats) are available in a single zip file.

Completed 1961 questionnaires

Abstract copyright UK Data Service and data collection copyright owner.

The objectives of the project were :
to prepare the case for the ESRC/JISC purchase of 2001 Census datasets and to prepare the case for a Census Programme and suggest directions it might take;
to prepare options for ESRC/JISC on the dissemination of the datasets;
to prepare proposals to the Census Offices on Census questions, methods and products;
to prepare proposals to the Census Offices on collaborative ventures;
to advise on a strategy for negotiations with the Census Offices.

A similar survey, for the 1991 Census, was conducted in 1987 by Marsh, C. et al : the data from this study are held at the Data Archive under SN:2460.
Main Topics:

The dataset contains the responses of 140 academic users of census data on their views about the 2001 Census of population. Questions were asked under the following four themes :
1. Topics and questions proposed for the 2001 Census.

1. Proposed changes in concepts for the 2001 Census.
   
2. Proposed changes in outputs for the 2001 Census : Area Statistics, Samples of Anonymised Records (SARS), Migration Statistics, Workplace Statistics, the ONS Longitudinal Study - inclusion of the 2001 Census, boundary data, look up tables, flexible outputs from the 2001 Census.
   
3. ESRC/JISC Census Programme services : registration procedures, help with census data, documentation and training, methods of access, software for extraction and analysis of census data, shape of the ESRC/JISC Census Programme after 2001.
   
   Measurement Scales
   The main scale used was a five-part categorisation of usefulness/importance for the respondent's research :
   essential; highly desirable; of interest; very low priority; not of interest.

Abstract

The 2005 Census of Population and Housing was the third comprehensive data collection of population and housing characteristics taken by the Republic since Compact Implementation in October 1994. The 2005 Census of Palau had two volumes. This first volume contained the basic tables, which can be used instantly for planning and policy determination. A second volume, the Census monograph, contained analyses of trends and comparisons of the States.

Geographic coverage

National

Analysis unit

Individuals Families Households General Population

Universe

The Census covered all the households and respective residents in the entire country.

Kind of data

Census/enumeration data [cen]

Sampling procedure

Not applicable to a full enumeration census. For details please refer to the attached Basic Tables and Monograph.

Mode of data collection

Face-to-face [f2f]

Cleaning operations

Full scale processing and editing activiities comprised eight separate sessions either with or separately but with remote guidance of the U.S. Census Bureau experts to finalize all datasets for publishing stage.

Response rate

In any large-scale statistical operation, such as the 2005 Census of the Republic of Palau, human- and machine-related errors do occur. These errors are commonly referred to as nonsampling errors. Such errors include not enumerating every household or every person in the population, not obtaining all required information form the respondents, obtaining incorrect or inconsistent information, and recording information incorrectly. In addition, errors can occur during the field review of the enumerators' work, during clerical handling of the census questionnaires, or during the electronic processing of the questionnaires.

To reduce various types of nonsampling errors, a number of techniques were implemented during the planning, data collection, and data processing activities. Quality assurance methods were used throughout the data collection and processing phases of the census to improve the quality of the data.

Sampling error estimates

Sampling Error is not applicable to censuses; however, a processing operation was handled with care to produce a set of data that describes the population as clearly and accurately as possible. To meet this objective, questionnaires were reviewed and edited during field data collection operations by crew leaders for consistency, completeness, and acceptability. Questionnaires were also reviewed by census clerks in the census office for omissions, certain inconsistencies, and population coverage. For example, write-in entries such as “Don't know” or “NA” were considered unacceptable in certain quantities and/or in conjunction with other data omissions.

As a result of this review operation, a telephone or personal visit follow-up was made to obtain missing information. Potential coverage errors were included in the follow-up, as well as questionnaires with omissions or inconsistencies beyond the completeness and quality tolerances specified in the review procedures.

Subsequent to field operations, remaining incomplete or inconsistent information on the questionnaires was assigned using imputation procedures during the final automated edit of the collected data. Allocations, or computer assignments of acceptable data in place of unacceptable entries or blanks, were needed most often when an entry for a given item was lacking or when the information reported for a person or housing unit on that item was inconsistent with other information for that same person or housing unit. As in previous censuses, the general procedure for changing unacceptable entries was to assign an entry for a person or housing unit that was consistent with entries for persons or housing units with similar characteristics. The assignment of acceptable data in lace of blanks or unacceptable entries enhanced the usefulness of the data.

Another way to make corrections during the computer editing process is substitution. Substitution is the assignment of a full set of characteristics for a person or housing unit. Because of the detailed field operations, substitution was not needed for the 2005 Census.

Data appraisal

In any large-scale statistical operation, such as the 2005 Census of the Republic of Palau, human- and machine-related errors were anticipated. These errors are commonly referred to as nonsampling errors. Such errors include not enumerating every household or every person in the population, not obtaining all required information form the respondents, obtaining incorrect or inconsistent information, and recording information incorrectly. In addition, errors can occur during the field review of the enumerators' work, during clerical handling of the census questionnaires, or during the electronic processing of the questionnaires.

To reduce various types of nonsampling errors, a number of techniques were implemented during the planning, data collection, and data processing activities. Quality assurance methods were used throughout the data collection and processing phases of the census to improve the quality of the data.

Summary Tape File (STF) 1 consists of four sets of computer-readable data files containing detailed tabulations of the nation's population and housing characteristics produced from the 1980 Census. This series is comprised of STF 1A, STF 1B, STF 1C, and STF 1D. All files in the STF 1 series are identical, containing 321 substantive data variables organized in the form of 59 "tables," as well as standard geographic identification variables. All of the data items contained in the STF 1 files were tabulated from the "complete count" or "100-percent" questions included on the 1980 Census questionnaire. All four groups of files within the STF 1 series have identical record formats and technical characteristics and differ only in the types of geographical areas for which the summarized data items are presented. STF 1D provides summaries for state or state equivalent, congressional district (as constituted for the 98th Congress), county or county equivalent, places of 10,000 or more people, and minor civil divisions (MCD) or census county divisions (CCD). Housing items tabulated include occupancy/vacancy status, tenure, contract rent, value, condominium status, number of rooms, and plumbing facilities. Population items include demographic information such as age, sex, race, marital status, Spanish origin, household relationship, and household type. Selected aggregates, means, and medians are also provided. See the related collection, CENSUS OF POPULATION AND HOUSING, 1980 [UNITED STATES]: SUMMARY TAPE FILE 1H (ICPSR 8401).

Abstract

The 2012 Population and Housing census of Tuvalu is the third census conducted by the Central Statistics Division since Tuvalu gained political independence in 1978. This document provides the population and housing information on areas covering general health, education, labour force, employment, disability, children, youth, aging-population, gender, communication, technology, urbanization, home appliances and many others.

Geographic coverage

National Coverage

Analysis unit

Individuals and Household-levels

Universe

The Census covered the whole population of Tuvalu

Kind of data

Census/enumeration data [cen]

Sampling procedure

This is a Census of the Population which covers 100% of the Tuvalu population which does not have any sampling procedures.

Mode of data collection

Face-to-face [f2f]

Research instrument

The 2012 Tuvalu Census questionnaires is divided into 2 sections:

1) A household questionnaire which was used to collect information on all household characteristics (dwelling). 2) A personal questionnaire administered in each household to all household members currently residing or away on temporary basis during census night.

The Household section of the questionnaire covers areas of household characteristics such as the type of living quaters, house ownership, construction of the house, source of drinking water, source of cooking energy, source of lighting, electrical appliances, etc.

The second section of the Questionnaire module or the Personal (Individual) section covers all household members demographic characteristics, social and economical backgrounds.

The Census Questionnaires has questions both in English and also in the local Tuvaluan language.

The UK's contribution of census data to the United Nations project, United Nations Questionnaires on Population and Housing Census.

Abstract

The 2011 Population and Housing Census is the third national Census to be conducted in Namibia after independence. The first was conducted 1991 followed by the 2001 Census. Namibia is therefore one of the countries in sub-Saharan Africa that has participated in the 2010 Round of Censuses and followed the international best practice of conducting decennial Censuses, each of which attempts to count and enumerate every person and household in a country every ten years. Surveys, by contrast, collect data from samples of people and/or households.

Censuses provide reliable and critical data on the socio-economic and demographic status of any country. In Namibia, Census data has provided crucial information for development planning and programme implementation. Specifically, the information has assisted in setting benchmarks, formulating policy and the evaluation and monitoring of national development programmes including NDP4, Vision 2030 and several sector programmes. The information has also been used to update the national sampling frame which is used to select samples for household-based surveys, including labour force surveys, demographic and health surveys, household income and expenditure surveys. In addition, Census information will be used to guide the demarcation of Namibia's administrative boundaries where necessary.

At the international level, Census information has been used extensively in monitoring progress towards Namibia's achievement of international targets, particularly the Millennium Development Goals (MDGs).

The latest and most comprehensive Census was conducted in August 2011. Preparations for the Census started in the 2007/2008 financial year under the auspices of the then Central Bureau of Statistics (CBS) which was later transformed into the Namibia Statistics Agency (NSA). The NSA was established under the Statistics Act No. 9 of 2011, with the legal mandate and authority to conduct population Censuses every 10 years. The Census was implemented in three broad phases; pre-enumeration, enumeration and post enumeration.

During the first pre-enumeration phase, activities accomplished including the preparation of a project document, establishing Census management and technical committees, and establishing the Census cartography unit which demarcated the Enumeration Areas (EAs). Other activities included the development of Census instruments and tools, such as the questionnaires, manuals and field control forms.

Field staff were recruited, trained and deployed during the initial stages of the enumeration phase. The actual enumeration exercise was undertaken over a period of about three weeks from 28 August to 15 September 2011, while 28 August 2011 was marked as the reference period or 'Census Day'.

Great efforts were made to check and ensure that the Census data was of high quality to enhance its credibility and increase its usage. Various quality controls were implemented to ensure relevance, timeliness, accuracy, coherence and proper data interpretation. Other activities undertaken to enhance quality included the demarcation of the country into small enumeration areas to ensure comprehensive coverage; the development of structured Census questionnaires after consultat.The post-enumeration phase started with the sending of completed questionnaires to Head Office and the preparation of summaries for the preliminary report, which was published in April 2012. Processing of the Census data began with manual editing and coding, which focused on the household identification section and un-coded parts of the questionnaire. This was followed by the capturing of data through scanning. Finally, the data were verified and errors corrected where necessary. This took longer than planned due to inadequate technical skills.

Geographic coverage

National coverage

Analysis unit

Households and persons

Universe

The sampling universe is defined as all households (private and institutions) from 2011 Census dataset.

Kind of data

Census/enumeration data [cen]

Sampling procedure

Sample Design

The stratified random sample was applied on the constituency and urban/rural variables of households list from Namibia 2011 Population and Housing Census for the Public Use Microdata Sample (PUMS) file. The sampling universe is defined as all households (private and institutions) from 2011 Census dataset. Since urban and rural are very important factor in the Namibia situation, it was then decided to take the stratum at the constituency and urban/rural levels. Some constituencies have very lower households in the urban or rural, the office therefore decided for a threshold (low boundary) for sampling within stratum. Based on data analysis, the threshold for stratum of PUMS file is 250 households. Thus, constituency and urban/rural areas with less than 250 households in total were included in the PUMS file. Otherwise, a simple random sampling (SRS) at a 20% sample rate was applied for each stratum. The sampled households include 93,674 housing units and 418,362 people.

Sample Selection

The PUMS sample is selected from households. The PUMS sample of persons in households is selected by keeping all persons in PUMS households. Sample selection process is performed using Census and Survey Processing System (CSPro).

The sample selection program first identifies the 7 census strata with less than 250 households and the households (private and institutions) with more than 50 people. The households in these areas and with this large size are all included in the sample. For the other households, the program randomly generates a number n from 0 to 4. Out of every 5 households, the program selects the nth household to export to the PUMS data file, creating a 20 percent sample of households. Private households and institutions are equally sampled in the PUMS data file.

Note: The 7 census strata with less than 250 households are: Arandis Constituency Rural, Rehoboth East Urban Constituency Rural, Walvis Bay Rural Constituency Rural, Mpungu Constituency Urban, Etayi Constituency Urban, Kalahari Constituency Urban, and Ondobe Constituency Urban.

Mode of data collection

Face-to-face [f2f]

Research instrument

The following questionnaire instruments were used for the Namibia 2011 Population and and Housing Census:

Form A (Long Form): For conventional households and residential institutions

Form B1 (Short Form): For special population groups such as persons in transit (travellers), police cells, homeless and off-shore populations

Form B2 (Short Form): For hotels/guesthouses

Form B3 (Short Form): For foreign missions/diplomatic corps

Cleaning operations

Data editing took place at a number of stages throughout the processing, including: a) During data collection in the field b) Manual editing and coding in the office c) During data entry (Primary validation/editing) Structure checking and completeness using Structured Query Language (SQL) program d) Secondary editing: i. Imputations of variables ii. Structural checking in Census and Survey Processing System (CSPro) program

Sampling error estimates

Sampling Error The standard errors of survey estimates are needed to evaluate the precision of the survey estimation. The statistical software package such as SPSS or SAS can accurately estimate the mean and variance of estimates from the survey. SPSS or SAS software package makes use of the Taylor series approach in computing the variance.

Data appraisal

Data quality Great efforts were made to check and ensure that the Census data was of high quality to enhance its credibility and increase its usage. Various quality controls were implemented to ensure relevance, timeliness, accuracy, coherence and proper data interpretation. Other activities undertaken to enhance quality included the demarcation of the country into small enumeration areas to ensure comprehensive coverage; the development of structured Census questionnaires after consultation with government ministries, university expertise and international partners; the preparation of detailed supervisors' and enumerators' instruction manuals to guide field staff during enumeration; the undertaking of comprehensive publicity and advocacy programmes to ensure full Government support and cooperation from the general public; the testing of questionnaires and other procedures; the provision of adequate training and undertaking of intensive supervision using four supervisory layers; the editing of questionnaires at field level; establishing proper mechanisms which ensured that all completed questionnaires were properly accounted for; ensuring intensive verification, validating all information and error corrections; and developing capacity in data processing with support from the international community.

Abstract

The 2017 Population and Housing Census of Tuvalu is the many censuses conducted by the Central Statistics Division since Tuvalu gained political independence in 1978. This document provides the population and housing information on areas covering general health, education, labour force, employment, disability, children, youth, aging-population, gender, communication, technology, urbanization, home appliances and many others.

Geographic coverage

National Coverage.

Analysis unit

Individuals and Households.

Universe

The Census covered the whole population of Tuvalu.

Kind of data

Census/enumeration data [cen]

Sampling procedure

This is a Census of the Population which covers 100% of the Tuvalu population which does not have any sampling procedures.

Mode of data collection

Face-to-face [f2f]

Research instrument

The 2017 Tuvalu Mini-Census CAPI questionnaires is divided into 2 sections:

1) A household questionnaire which was used to collect information on all household characteristics (dwelling). 2) A personal questionnaire administered in each household to all household members currently residing or away on temporary basis during census night.

The Household section of the questionnaire covers areas of household characteristics such as the type of living quaters, house ownership, construction of the house, source of drinking water, source of cooking energy, source of lighting, electrical appliances, etc. The second section of the Questionnaire module or the Personal (Individual) section covers all household members demographic characteristics, social and economical backgrounds.

The Census Questionnaires has questions both in English and also in the local Tuvaluan language.

Cleaning operations

As the 2017 Mini-Census was the first to use the CAPI devises, it minimizes the entry errors as it contains automatic skips depending on certain conditions and other validation codings, etc. However, the cleaning and data editing mostly took place during the "Processing phase".

Sampling error estimates

As this is a Census, it covers the whole population.

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

Dwelling

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

UNIT DESCRIPTIONS: - Dwellings: All places defined by walls and roofs where one or more people live regularly, that is where they sleep, cook and protect themselves from the elements. Also people can enter and leave the mentioned without passing through another house, having direct access from the street, passage, path or passing through common areas such as patios, hallways, corridors or stairs. - Households: Group of people who live as a family - Group quarters: This is a place or building where a group of people without family ties resides and share the space for reasons of lodging, health, education, military, religion, old age, orphanhood, etc. This includes hotels, boarding houses, guest houses, hospitals, homes for the elderly, internment schools, hospices, jails, etc.

Universe

All people who live in the country and all households nationally.

Kind of data

Census/enumeration data [cen]

Sampling procedure

MICRODATA SOURCE: General Directorate of Statistics and Censuses

SAMPLE DESIGN: Stratified systematic sample.

SAMPLE UNIT: Households

SAMPLE FRACTION: 10%

SAMPLE SIZE (person records): 510,760

Mode of data collection

Face-to-face [f2f]

Research instrument

Census questionnaire containing questions on demographic and socio-economic characteristics of the population, dwelling unit characteristics, emigration, and mortality.

Abstract

The Census provides a great deal of useful information about demographic, social and economic characteristics of the population. The 1991 Census counted all persons who were living in Western Samoa on census night. It excluded Western Samoans living in other countries. The 1991 census was processed in house in the newly established Data Processing Division of the Department of Statistics. Two publications of the 1991 census have already been released. The village directory was released in October 1992 and a publication of selected tables in May 1993. The census process began with a decision by the Statistics Advisory Board late in 1989 to take a census in November 1991. A project document was prepared with the assistance from ESCAP, through its Regional Adviser for Censuses and Surveys, and submitted to UNFPA for support. The document was subsequently approved and UNFPA assistance was secured. The Minister of Statistics also gave assurance of government suport which provided the impetus for preparatory work. The first step was to draw up a detailed work plan complete with timing and duration of each activity its cost and its expected output. Once this plan was approved, some important elements could be into place. The first was to ensure that the department of statistics and cooperating agencies were organised in a way conducive to performing key census tasks.

Geographic coverage

The national coverage was based on four main regions; Apia Urban Area, North West Upolu, Rest of Upolu and Savaii.

Analysis unit

A Census of Population and Housing with community-level questionnaire would have the following units of analysis: individuals and households

Universe

The 1991 Census counted all persons who were living in Western Samoa on census night. The survey covered all household; private households and institutions. The survey covered all household members (usual residents), all women aged 15-49 years resident in the household, and all children aged 0-4 years (under age 5) resident in the household.

Kind of data

Census/enumeration data [cen]

Mode of data collection

Face-to-face [f2f]

Research instrument

Other essential tasks included the design of the questionnaires and the census processing system. Some important developments had occured since 1986, leading to a need for modifications in data collection or processing. Thus while consistency between the 1991 and earlier censuses was important, it was equally vital that improvements be made and proper field tests carried out in time. Among the changes to the questionnaire were included a reintroduction of a question on literacy and a more intensive approach to collecting data on economic activity. This included and additional question to enable responses to be classified to the revised skill based International Classification of Occupations (ISCO 1988) and greater probing on the activities of womendescribed as housewives, in the belief that in earlier censuses may had erroneously been excluded from labour force. In addition, the census was designed to cover housing characteristics, the first time since 1981. Two sets of questionnaires were used in the census:

1) A household questionnaire which was used to collect information on all household members (usual residents), the household, and the dwelling. 2) A housing questionnaire gives information about the building occupied by the household and some details on the household occupying the building

Cleaning operations

The 1986 census was the first to be processed in-house. Many lessons were learned during that processing which were applied in the processing of the 1991 census. The system was based on an integrated software package known as U-SP. The system was designed and tested well before the census, utilising the completed pre-test schedules. The processing of the 1989 Census of Agriculture also helped in providing experience. Processing was entirely interactive. Data entry, editing and amendments were completed by statisticians who worked "hands-on" at the computer terminals. As a result processing was faster and more efficient than in any previous census. There were some problems however. Checking and coding were delayed for at least 2 months when a state of emergency was declared following cyclone Val early in December 1991. Damage to the office building and frequent electricity failures delayed work further.

Data appraisal

Population Pyramid Sex Ratio by Age Group

The once-a-decade decennial census was conducted in April 2010 by the U.S. Census Bureau. This count of every resident in the United States was mandated by Article I, Section 2 of the Constitution and all households in the U.S. and individuals living in group quarters were required by law to respond to the 2010 Census questionnaire. The data collected by the decennial census determine the number of seats each state has in the U.S. House of Representatives and is also used to distribute billions in federal funds to local communities. The questionnaire consisted of a limited number of questions but allowed for the collection of information on the number of people in the household and their relationship to the householder, an individual's age, sex, race and Hispanic ethnicity, the number of housing units and whether those units are owner- or renter-occupied, or vacant. Results for sub-state geographic areas in New Mexico were released in a series of data products. These data come from Summary File 1 (SF-1). The geographic coverage for SF-1 includes the state, counties, places (both incorporated and unincorporated communities), tribal lands, school districts, census tracts, block groups and blocks, among others. The data in this particular RGIS Clearinghouse table is for Los Alamos County and all census blocks in the county. Table DC10_01114 shows counts of housing units by vacancy status (type of vacancy). The table includes the number of vacant housing units by the following categories; total, for rent, rented but not yet occupied, for sale only, sold but not yet occupied, seasonal or recreational or occasional use, for migrant workers, and vacant for some other reason. This file, along with file-specific descriptions (in Word and text formats) are available in a single zip file.

The once-a-decade decennial census was conducted in April 2010 by the U.S. Census Bureau. This count of every resident in the United States was mandated by Article I, Section 2 of the Constitution and all households in the U.S. and individuals living in group quarters were required by law to respond to the 2010 Census questionnaire. The data collected by the decennial census determine the number of seats each state has in the U.S. House of Representatives and is also used to distribute billions in federal funds to local communities. The questionnaire consisted of a limited number of questions but allowed for the collection of information on the number of people in the household and their relationship to the householder, an individual's age, sex, race and Hispanic ethnicity, the number of housing units and whether those units are owner- or renter-occupied, or vacant. Results for sub-state geographic areas in New Mexico were released in a series of data products. These data come from Summary File 1 (SF-1). The geographic coverage for SF-1 includes the state, counties, places (both incorporated and unincorporated communities), tribal lands, school districts, census tracts, block groups and blocks, among others. The data in these particular RGIS Clearinghouse tables are for Santa Fe County and all census blocks within the county. There is one data table in this file. Table DC10_00680 shows the number of households by the following categories--total households; total family households; husband-wife family households; total other family households; male householder, no wife present; female householder, no husband present; total nonfamily households; nonfamily households with householder living along; and finally, nonfamily households with householder not living alone. This file, along with file-specific descriptions (in Word and text formats) are available in a single zip file.