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analyze the american community survey (acs) with r and monetdb experimental. think of the american community survey (acs) as the united states' census for off-years - the ones that don't end in zero. every year, one percent of all americans respond, making it the largest complex sample administered by the u.s. government (the decennial census has a much broader reach, but since it attempts to contact 100% of the population, it's not a sur vey). the acs asks how people live and although the questionnaire only includes about three hundred questions on demography, income, insurance, it's often accurate at sub-state geographies and - depending how many years pooled - down to small counties. households are the sampling unit, and once a household gets selected for inclusion, all of its residents respond to the survey. this allows household-level data (like home ownership) to be collected more efficiently and lets researchers examine family structure. the census bureau runs and finances this behemoth, of course. the dow nloadable american community survey ships as two distinct household-level and person-level comma-separated value (.csv) files. merging the two just rectangulates the data, since each person in the person-file has exactly one matching record in the household-file. for analyses of small, smaller, and microscopic geographic areas, choose one-, three-, or fiv e-year pooled files. use as few pooled years as you can, unless you like sentences that start with, "over the period of 2006 - 2010, the average american ... [insert yer findings here]." rather than processing the acs public use microdata sample line-by-line, the r language brazenly reads everything into memory by default. to prevent overloading your computer, dr. thomas lumley wrote the sqlsurvey package principally to deal with t his ram-gobbling monster. if you're already familiar with syntax used for the survey package, be patient and read the sqlsurvey examples carefully when something doesn't behave as you expect it to - some sqlsurvey commands require a different structure (i.e. svyby gets called through svymean) and others might not exist anytime soon (like svyolr). gimme some good news: sqlsurvey uses ultra-fast monetdb (click here for speed tests), so follow the monetdb installation instructions before running this acs code. monetdb imports, writes, recodes data slowly, but reads it hyper-fast . a magnificent trade-off: data exploration typically requires you to think, send an analysis command, think some more, send another query, repeat. importation scripts (especially the ones i've already written for you) can be left running overnight sans hand-holding. the acs weights generalize to the whole united states population including individuals living in group quarters, but non-residential respondents get an abridged questionnaire, so most (not all) analysts exclude records with a relp variable of 16 or 17 right off the bat. this new github repository contains four scripts: 2005-2011 - download all microdata.R create the batch (.bat) file needed to initiate the monet database in the future download, unzip, and import each file for every year and size specified by the user create and save household- and merged/person-level replicate weight complex sample designs create a well-documented block of code to re-initiate the monet db server in the future fair warning: this full script takes a loooong time. run it friday afternoon, commune with nature for the weekend, and if you've got a fast processor and speedy internet connection, monday morning it should be ready for action. otherwise, either download only the years and sizes you need or - if you gotta have 'em all - run it, minimize it, and then don't disturb it for a week. 2011 single-year - analysis e xamples.R run the well-documented block of code to re-initiate the monetdb server load the r data file (.rda) containing the replicate weight designs for the single-year 2011 file perform the standard repertoire of analysis examples, only this time using sqlsurvey functions 2011 single-year - variable reco de example.R run the well-documented block of code to re-initiate the monetdb server copy the single-year 2011 table to maintain the pristine original add a new age category variable by hand add a new age category variable systematically re-create then save the sqlsurvey replicate weight complex sample design on this new table close everything, then load everything back up in a fresh instance of r replicate a few of the census statistics. no muss, no fuss replicate census estimates - 2011.R run the well-documented block of code to re-initiate the monetdb server load the r data file (.rda) containing the replicate weight designs for the single-year 2011 file match every nation wide statistic on the census bureau's estimates page, using sqlsurvey functions click here to view these four scripts for more detail about the american community survey (acs), visit: < ul> the us census...
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.
National coverage as the Population Census covers the whole of Nauru.
The Census covers all individuals living in private and non-private dwellings and institutions.
Census/enumeration data [cen]
There is no sampling for the population census, full coverage.
Face-to-face [f2f]
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
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 was compared with Administrative records after the Census to review the quality and reliability of the data.
The 2022 Music Census Details is the underlying geographic dataset for the 2022 Music Census administered by Sound Music Cities. This data is comprehensive of the respondent feedback by ZIP code. Read more about this collection of data here: https://data.austintexas.gov/stories/s/rpy8-prg4
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Key Table Information.Table Title.Revenue of Public Elementary-Secondary School Systems in the United States: Fiscal Year 2012 - 2023.Table ID.GOVSTIMESERIES.GS00SS12.Survey/Program.Public Sector.Year.2024.Dataset.PUB Public Sector Annual Surveys and Census of Governments.Source.U.S. Census Bureau, Public Sector.Release Date.2025-05-01.Release Schedule.The Annual Survey of School System Finances occurs every year. Data are typically released in early May. There are approximately two years between the reference period and data release..Dataset Universe.Census of Governments - Organization (CG):The universe of this file is all federal, state, and local government units in the United States. In addition to the federal government and the 50 state governments, the Census Bureau recognizes five basic types of local governments. The government types are: County, Municipal, Township, Special District, and School District. Of these five types, three are categorized as General Purpose governments: County, municipal, and township governments are readily recognized and generally present no serious problem of classification. However, legislative provisions for school district and special district governments are diverse. These two types are categorized as Special Purpose governments. Numerous single-function and multiple-function districts, authorities, commissions, boards, and other entities, which have varying degrees of autonomy, exist in the United States. The basic pattern of these entities varies widely from state to state. Moreover, various classes of local governments within a particular state also differ in their characteristics. Refer to the Individual State Descriptions report for an overview of all government entities authorized by state.The Public Use File provides a listing of all independent government units, and dependent school districts active as of fiscal year ending June 30, 2024. The Annual Surveys of Public Employment & Payroll (EP) and State and Local Government Finances (LF):The target population consists of all 50 state governments, the District of Columbia, and a sample of local governmental units (counties, cities, townships, special districts, school districts). In years ending in '2' and '7' the entire universe is canvassed. In intervening years, a sample of the target population is surveyed. Additional details on sampling are available in the survey methodology descriptions for those years.The Annual Survey of Public Pensions (PP):The target population consists of state- and locally-administered defined benefit funds and systems of all 50 state governments, the District of Columbia, and a sample of local governmental units (counties, cities, townships, special districts, school districts). In years ending in '2' and '7' the entire universe is canvassed. In intervening years, a sample of the target population is surveyed. Additional details on sampling are available in the survey methodology descriptions for those years.The Annual Surveys of State Government Finance (SG) and State Government Tax Collections (TC):The target population consists of all 50 state governments. No local governments are included. For the purpose of Census Bureau statistics, the term "state government" refers not only to the executive, legislative, and judicial branches of a given state, but it also includes agencies, institutions, commissions, and public authorities that operate separately or somewhat autonomously from the central state government but where the state government maintains administrative or fiscal control over their activities as defined by the Census Bureau. Additional details are available in the survey methodology description.The Annual Survey of School System Finances (SS):The Annual Survey of School System Finances targets all public school systems providing elementary and/or secondary education in all 50 states and the District of Columbia..Methodology.Data Items and Other Identifying Records.Fall enrollmentTotal revenueTotal revenue from federal sourcesRevenue from federal sources - Distributed through the state - Title IRevenue from federal sources - Distributed through the state - Special EducationRevenue from federal sources - Distributed through the state - Child nutritionRevenue from federal sources - Distributed through the state - Other and nonspecifiedTotal revenue from state sourcesRevenue from state sources - General formula assistanceRevenue from state sources - Special educationRevenue from state sources - Transportation programsRevenue from state sources - Other and nonspecified state aidTotal revenue from local sourcesRevenue from local sources - Total taxesRevenue from local sources - Property taxesRevenue from local sources - Parent government contributionsRevenue from local sources - Revenue from cities and countiesRevenue from local sources - Revenue from other school systemsRevenue from local sources - Current chargesRevenue from local sources - Other local revenueDefinit...
This dataset includes all individuals from the 1860 US census.
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This dataset was developed through a collaboration between the Minnesota Population Center and the Church of Jesus Christ of Latter-Day Saints. The data contain demographic variables, economic variables, migration variables and race variables. Unlike more recent census datasets, pre-1900 census datasets only contain individual level characteristics and no household or family characteristics, but household and family identifiers do exist.
The official enumeration day of the 1860 census was 1 June 1860. The main goal of an early census like the 1860 U.S. census was to allow Congress to determine the collection of taxes and the appropriation of seats in the House of Representatives. Each district was assigned a U.S. Marshall who organized other marshals to administer the census. These enumerators visited households and recorder names of every person, along with their age, sex, color, profession, occupation, value of real estate, place of birth, parental foreign birth, marriage, literacy, and whether deaf, dumb, blind, insane or “idiotic”.
Sources: Szucs, L.D. and Hargreaves Luebking, S. (1997). Research in Census Records, The Source: A Guidebook of American Genealogy. Ancestry Incorporated, Salt Lake City, UT Dollarhide, W.(2000). The Census Book: A Genealogist’s Guide to Federal Census Facts, Schedules and Indexes. Heritage Quest, Bountiful, UT
The purpose of the census was to provide demographic and socio-economic statistics in Uganda. The long term objective of the 2002 census was to maintain approximate decennial censuses and ensure availability of time series population benchmark statistical information at various administrative levels for the development of a coordinated and integrated data collection system in the country.The enumeration covered all persons resident in Uganda on the census night. Special arrangements were made to enumerate institutional, homeless, hotel and mobile populations. The census collected data on the demographic and socio-economic characteristics of the population; household and housing conditions, agriculture, activities of micro and small enterprises and the community characteristics.
The main purpose of the Agricultural module was to provide appropriate sampling frames for a detailed Census of Agriculture in 2003, and a Census of Livestock in 2004. There was evidence of deliberate falsification of data from Kotido District. Therefore the analysis excludes data for Kotido District.
The immediate objectives of the census were: - To create/update census field maps and lists of EAs for the control of the 2002 census and construction of efficient area sampling frames; - Effectively complete conducting a Population and Housing census with an Agricultural and Livestock module; - To generate basic demographic and socio-economic data from the 2002 census disaggregated by sex, age and administrative areas; - To compile agricultural and livestock sampling frames to be used in the subsequent sample surveys of these components; - To evaluate, analyze and disseminate the census results at all administrative levels.
The census covered the whole country.
The census covered all the household members, all persons aged 5 years and above resident in the houseold, all persons aged 10 years and above resident in the household and all women aged 12 to 54 years resident in the household.
Census/enumeration data [cen]
Face-to-face [f2f]
The questionnaires for the 2002 Uganda Population and Housing Census were based on 1991 Census model with some modifications and additions. A household questionnaire was administered in each household, which collected various information on household members including sex, age, disability, religion, date of birth and orphanhood status. The household questionnaire also included the agricultural and micro and small enterprises modules. In addition to a household questionnaire, questionnaires were administered in each household for women aged 12-54, all persons aged 5 years and above, and also all persons aged 10 years and above.
Preliminary editing was carried out to identify, investigate and resolve inconsistencies resulting from possible data entry and / or coding errors. After completion of the preliminary editing, the edited data was subjected to the edit programmes in two phases. The first run was to undertake structural edits which in turn was ensuring that the entries were logical. The second run of the programme was aimed at ensuring completeness of content and as a result, missing values had to be imputed following logic embedded in the computer programs according to the editing specifications or rules established.
A series of data quality tables are available to review the quality of the data and include the following: - Estimation of Population in an Area - Distribution of Households and Primary Sampling Units among strata - Age Tolerance limits used in matching individuals - Distribution of missing EAs during matching by strata - Distribution of EAs among strata - Un-weighted Number of matched and non-matched cases - Estimates of the Coverage rates - Population Estimates - Rate of Agreement by characteristics, residence and Region - Net Difference rate and Index of Inconsistency by characteristics - A list of PES indicators selected for computation of sampling errors - Reliability of Estimates Based on Selected Indicators at National Level - Reliability of Estimates Based on Selected Indicators For Urban Areas - Reliability of estimates Based on Selected indicators for rural Areas by Regions
The results of each of these data quality tables are shown in the appendix of the final report and are also given in the external resources section
Census Designated PlacesCensus Designated Places (CDPs) are the statistical counterparts of incorporated places and are delineated to provide data for settled concentrations of population that are identifiable by name but are not legally incorporated under the laws of the state in which they are located. The boundaries usually are defined in cooperation with local or tribal officials and generally updated prior to each decennial census. These boundaries, which usually coincide with visible features or the boundary of an adjacent incorporated place or another legal entity boundary, have no legal status, nor do these places have officials elected to serve traditional municipal functions. CDP boundaries may change from one decennial census to the next with changes in the settlement pattern; a CDP with the same name as in an earlier census does not necessarily have the same boundary. CDPs must be contained within a single state and may not extend into an incorporated place. There are no population size requirements for CDPs.Incorporated PlacesIncorporated Places are those reported to the Census Bureau as legally in existence as of the latest Boundary and Annexation Survey (BAS), under the laws of their respective states. An incorporated place is established to provide governmental functions for a concentration of people as opposed to a minor civil division, which generally is created to provide services or administer an area without regard, necessarily, to population. Places always are within a single state or equivalent entity, but may extend across county and county subdivision boundaries. An incorporated place usually is a city, town, village, or borough but can have other legal descriptions.
https://www.icpsr.umich.edu/web/ICPSR/studies/29502/termshttps://www.icpsr.umich.edu/web/ICPSR/studies/29502/terms
The Bureau of Justice Statistics' (BJS) 2007 Census of Public Defender Offices (CPDO) collected data from public defender offices located across 49 states and the District of Columbia. Public defender offices are one of three methods through which states and localities ensure that indigent defendants are granted the Sixth and Fourteenth Amendment right to counsel. (In addition to defender offices, indigent defense services may also be provided by court-assigned private counsel or by a contract system in which private attorneys contractually agree to take on a specified number of indigent defendants or indigent defense cases.) Public defender offices have a salaried staff of full- or part-time attorneys who represent indigent defendants and are employed as direct government employees or through a public, nonprofit organization. Public defenders play an important role in the United States criminal justice system. Data from prior BJS surveys on indigent defense representation indicate that most criminal defendants rely on some form of publicly provided defense counsel, primarily public defenders. Although the United States Supreme Court has mandated that the states provide counsel for indigent persons accused of crime, documentation on the nature and provision of these services has not been readily available. States have devised various systems, rules of organization, and funding mechanisms for indigent defense programs. While the operation and funding of public defender offices varies across states, public defender offices can be generally classified as being part of either a state program or a county-based system. The 22 state public defender programs functioned entirely under the direction of a central administrative office that funded and administered all the public defender offices in the state. For the 28 states with county-based offices, indigent defense services were administered at the county or local jurisdictional level and funded principally by the county or through a combination of county and state funds. The CPDO collected data from both state- and county-based offices. All public defender offices that were principally funded by state or local governments and provided general criminal defense services, conflict services, or capital case representation were within the scope of the study. Federal public defender offices and offices that provided primarily contract or assigned counsel services with private attorneys were excluded from the data collection. In addition, public defender offices that were principally funded by a tribal government, or provided primarily appellate or juvenile services were outside the scope of the project and were also excluded. The CPDO gathered information on public defender office staffing, expenditures, attorney training, standards and guidelines, and caseloads, including the number and type of cases received by the offices. The data collected by the CPDO can be compared to and analyzed against many of the existing national standards for the provision of indigent defense services.
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Key Table Information.Table Title.Government Units: U.S. and State: Census Years 1942 - 2022.Table ID.GOVSTIMESERIES.CG00ORG01.Survey/Program.Public Sector.Year.2024.Dataset.PUB Public Sector Annual Surveys and Census of Governments.Source.U.S. Census Bureau, Public Sector.Release Date.2023-08-24.Release Schedule.For information about Census of Governments planned data product releases, see https://www.census.gov/programs-surveys/gus/newsroom/updates.html.Dataset Universe.Census of Governments - Organization (CG):The universe of this file is all federal, state, and local government units in the United States. In addition to the federal government and the 50 state governments, the Census Bureau recognizes five basic types of local governments. The government types are: County, Municipal, Township, Special District, and School District. Of these five types, three are categorized as General Purpose governments: County, municipal, and township governments are readily recognized and generally present no serious problem of classification. However, legislative provisions for school district and special district governments are diverse. These two types are categorized as Special Purpose governments. Numerous single-function and multiple-function districts, authorities, commissions, boards, and other entities, which have varying degrees of autonomy, exist in the United States. The basic pattern of these entities varies widely from state to state. Moreover, various classes of local governments within a particular state also differ in their characteristics. Refer to the Individual State Descriptions report for an overview of all government entities authorized by state.The Public Use File provides a listing of all independent government units, and dependent school districts active as of fiscal year ending June 30, 2024. The Annual Surveys of Public Employment & Payroll (EP) and State and Local Government Finances (LF):The target population consists of all 50 state governments, the District of Columbia, and a sample of local governmental units (counties, cities, townships, special districts, school districts). In years ending in '2' and '7' the entire universe is canvassed. In intervening years, a sample of the target population is surveyed. Additional details on sampling are available in the survey methodology descriptions for those years.The Annual Survey of Public Pensions (PP):The target population consists of state- and locally-administered defined benefit funds and systems of all 50 state governments, the District of Columbia, and a sample of local governmental units (counties, cities, townships, special districts, school districts). In years ending in '2' and '7' the entire universe is canvassed. In intervening years, a sample of the target population is surveyed. Additional details on sampling are available in the survey methodology descriptions for those years.The Annual Surveys of State Government Finance (SG) and State Government Tax Collections (TC):The target population consists of all 50 state governments. No local governments are included. For the purpose of Census Bureau statistics, the term "state government" refers not only to the executive, legislative, and judicial branches of a given state, but it also includes agencies, institutions, commissions, and public authorities that operate separately or somewhat autonomously from the central state government but where the state government maintains administrative or fiscal control over their activities as defined by the Census Bureau. Additional details are available in the survey methodology description.The Annual Survey of School System Finances (SS):The Annual Survey of School System Finances targets all public school systems providing elementary and/or secondary education in all 50 states and the District of Columbia..Methodology.Data Items and Other Identifying Records.Total federal, state, and local government units by state.Unit(s) of Observation.The basic reporting unit is the governmental unit, defined as an organized entity which in addition to having governmental character, has sufficient discretion in the management of its own affairs to distinguish it as separate from the administrative structure of any other governmental unit.The reporting units for the Annual Survey of School System Finances are public school systems that provide elementary and/or secondary education. The term "public school systems" includes two types of government entities with responsibility for providing education services: (1) school districts that are administratively and fiscally independent of any other government and are counted as separate governments; and (2) public school systems that lack sufficient autonomy to be counted as separate governments and are classified as a dependent agency of some other government—a county, municipal, township, or state government. Charter school systems whose charters are held by nongovernmental entities are deemed to be out of...
NOTE: As of 2/16/2023, this page is not being updated. For data on updated (bivalent) COVID-19 booster vaccination click here: https://app.powerbigov.us/view?r=eyJrIjoiODNhYzVkNGYtMzZkMy00YzA3LWJhYzUtYTVkOWFlZjllYTVjIiwidCI6IjExOGI3Y2ZhLWEzZGQtNDhiOS1iMDI2LTMxZmY2OWJiNzM4YiJ9 This table shows the number and percent of people that have initiated COVID-19 vaccination and are fully vaccinated by CT census tract (including residents of all ages). It also shows the number of people who have not received vaccine and who are not yet fully vaccinated. All data in this report are preliminary; data for previous dates will be updated as new reports are received and data errors are corrected. A person who has received at least one dose of any vaccine is considered to have initiated vaccination. A person is considered fully vaccinated if they have completed a primary series by receiving 2 doses of the Pfizer, Novavax or Moderna vaccines or 1 dose of the Johnson & Johnson vaccine. The fully vaccinated are a subset of the number who have received at least one dose. The percent with at least one dose many be over-estimated and the percent fully vaccinated may be under-estimated because of vaccine administration records for individuals that cannot be linked because of differences in how names or date of birth are reported. Population data obtained from the 2019 Census ACS (www.census.gov) Geocoding is used to determine the census tract in which a person lives. People for who a census tract cannot be determined based on available address data are not included in this table. DPH recommends that these data are primarily used to identify areas that require additional attention rather than to establish and track the exact level of vaccine coverage. Census tract coverage estimates can play an important role in planning and evaluating vaccination strategies. However, inaccuracies in the data that are inherent to population surveillance may be magnified when analyses are performed down to the census tract level. We make every effort to provide accurate data, but inaccuracies may result from things like incomplete or inaccurate addresses, duplicate records, and sampling error in the American Community Survey that is used to estimate census tract population size and composition. These things may result in overestimates or underestimates of vaccine coverage. Some census tracts are suppressed. This is done if the number of people vaccinated is less than 5 or if the census population estimate is considered unreliable (coefficient of variance > 30%). Coverage estimates over 100% are shown as 100%. Connecticut COVID-19 Vaccine Program providers are required to report information on all COVID-19 vaccine doses administered to CT WiZ, the Connecticut Immunization Information System. Data on doses administered to CT residents out-of-state are being added to CT WiZ jurisdiction-by-jurisdiction. Doses administered by some Federal entities (including Department of Defense, Department of Correction, Department of Veteran’s Affairs, Indian Health Service) are not yet reported to CT WiZ. Data reported here reflect the vaccination records currently reported to CT WiZ. Caution should be used when interpreting coverage estimates in towns with large college/university populations since coverage may be underestimated. In the census, college/university students who live on or just off campus would be counted in the college/university town. However, if a student was vaccinated while studying remotely in his/her hometown, the student may be counted as a vaccine recipient in that town. As part of continuous data quality improvement efforts, duplicate records were removed from the COVID-19 vaccination data during the weeks of 4/19/2021 and 4/26/2021. As of 1/13/2021, census tract level data are provider by town for all ages. Data by age group is no longer available.
Persons, households, and dwellings
UNITS IDENTIFIED: - Dwellings: yes - Vacant Units: no - Households: yes - Individuals: yes - Group quarters: yes
UNIT DESCRIPTIONS: - Dwellings: The accommodation occupied by one household is the dwelling unit. - Households: A household is a group of persons who normally live and eat together, regardless of whether they are related. - Group quarters: Sometimes groups of people live together but cannot be said to belong to a household. Persons in hospitals, colleges, barracks and prisons are examples.
All persons who are in Uganda the night of the census, regardless of their nationality. Floating population refers to those who will not spend census night in households, institutions or hotels. They include persons who are travelling on census night, those in transit at airports or on ships or in railway stations. They include also beggars, vagrants and other homeless people who spend the night at bus parks, on the streets or similar places.
Population and Housing Census [hh/popcen]
MICRODATA SOURCE: Uganda Bureau of Statistics
SAMPLE SIZE (person records): 1548460.
SAMPLE DESIGN: A sample of approximately 10% of the rural enumeration areas where a long questionnaire was administered to the households, while all urban areas were enumerated with a long questionnaire. Thus the data set consists of these two sets (LONG RURAL and URBAN). Use the weights that are record specific to be representative of the household population. Floating population refers to those who will not spend census night in households, institutions or hotels. They include persons who are travelling on census night, those in transit at airports or on ships or in railway stations. They include also beggars, vagrants and other homeless people who spend the night at bus parks, on the streets or similar places.
Face-to-face [f2f]
Schedule A: short form and Schedule B: long form
Persons, households, and dwellings
UNITS IDENTIFIED: - Dwellings: yes - Vacant Units: no - Households: yes - Individuals: yes - Group quarters: yes
UNIT DESCRIPTIONS: - Dwellings: Not available - Households: An individual or group of people living who inhabit part or all of the physical or census building who make common provisions for food and other living essentials. - Group quarters: Institutional households consist of individuals in a residence that manages everyday needs, usually arranged by an organization such as a non-profit institution, school, the military, etc. Includes reformatories, prisons and similar living quarters. Also includes households that rent rooms or parts of buildings lodging ten or more people.
All population residing in the geographic area of Indonesia regardless of residence status. Homeless, boat people, etc were enumerated.
Population and Housing Census [hh/popcen]
MICRODATA SOURCE: Central Bureau of Statistics
SAMPLE SIZE (person records): 912544.
SAMPLE DESIGN: Data are derived from the sample of census blocks that received the long form questionnaire, stratified by urban-rural status.
Face-to-face [f2f]
Long form questionnaire SP90-S containing houseing and individual questions distributed to 5% of households.
Census designated places (CDPs) are statistical geographic entities representing closely settled, unincorporated communities that are locally recognized and identified by name. They are statistical equivalents of incorporated places, with the primary differences being the lack of both a legally defined boundary and an active, functioning governmental structure, chartered by the state and administered by elected officials. The purpose of CDPs is to provide meaningful statistics for well-known, unincorporated communities. The U.S. Census Bureau uses CDPs in the tabulation and presentation of data from the decennial census, the American Community Survey (ACS), the Economic Census, and the Longitudinal Employer-Household Dynamics (LEHD) Program.Census Geography
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Key Table Information.Table Title.Income and Apportionment of State-Administered Lottery Funds: U.S. and States: 2012 - 2023.Table ID.GOVSTIMESERIES.GS00SG02.Survey/Program.Public Sector.Year.2024.Dataset.PUB Public Sector Annual Surveys and Census of Governments.Source.U.S. Census Bureau, Public Sector.Release Date.2025-04-10.Release Schedule.The Annual Survey of State Government Finances occurs every year. Data are released every January. There are approximately 18 months between the reference period and data release. Revisions to published data occur annually going back to the previous Census of Goverments. Census of Governments years, those ending in '2' and '7' may have slightly later releases due to extended processing time..Dataset Universe.Census of Governments - Organization (CG):The universe of this file is all federal, state, and local government units in the United States. In addition to the federal government and the 50 state governments, the Census Bureau recognizes five basic types of local governments. The government types are: County, Municipal, Township, Special District, and School District. Of these five types, three are categorized as General Purpose governments: County, municipal, and township governments are readily recognized and generally present no serious problem of classification. However, legislative provisions for school district and special district governments are diverse. These two types are categorized as Special Purpose governments. Numerous single-function and multiple-function districts, authorities, commissions, boards, and other entities, which have varying degrees of autonomy, exist in the United States. The basic pattern of these entities varies widely from state to state. Moreover, various classes of local governments within a particular state also differ in their characteristics. Refer to the Individual State Descriptions report for an overview of all government entities authorized by state.The Public Use File provides a listing of all independent government units, and dependent school districts active as of fiscal year ending June 30, 2024. The Annual Surveys of Public Employment & Payroll (EP) and State and Local Government Finances (LF):The target population consists of all 50 state governments, the District of Columbia, and a sample of local governmental units (counties, cities, townships, special districts, school districts). In years ending in '2' and '7' the entire universe is canvassed. In intervening years, a sample of the target population is surveyed. Additional details on sampling are available in the survey methodology descriptions for those years.The Annual Survey of Public Pensions (PP):The target population consists of state- and locally-administered defined benefit funds and systems of all 50 state governments, the District of Columbia, and a sample of local governmental units (counties, cities, townships, special districts, school districts). In years ending in '2' and '7' the entire universe is canvassed. In intervening years, a sample of the target population is surveyed. Additional details on sampling are available in the survey methodology descriptions for those years.The Annual Surveys of State Government Finance (SG) and State Government Tax Collections (TC):The target population consists of all 50 state governments. No local governments are included. For the purpose of Census Bureau statistics, the term "state government" refers not only to the executive, legislative, and judicial branches of a given state, but it also includes agencies, institutions, commissions, and public authorities that operate separately or somewhat autonomously from the central state government but where the state government maintains administrative or fiscal control over their activities as defined by the Census Bureau. Additional details are available in the survey methodology description.The Annual Survey of School System Finances (SS):The Annual Survey of School System Finances targets all public school systems providing elementary and/or secondary education in all 50 states and the District of Columbia..Methodology.Data Items and Other Identifying Records.Detail of state-administered lottery funds:Lottery incomeLottery prizesLottery adminstrationLottery proceeds availableDefinitions can be found by clicking on the column header in the table or by accessing the Glossary.For detailed information, see Government Finance and Employment Classification Manual..Unit(s) of Observation.The basic reporting unit is the governmental unit, defined as an organized entity which in addition to having governmental character, has sufficient discretion in the management of its own affairs to distinguish it as separate from the administrative structure of any other governmental unit.The reporting units for the Annual Survey of School System Finances are public school systems that provide elementary and/or secondary education. The term "public school systems" includes two types ...
The 2011 Population and Housing Census of Samoa was taken on the midnight of November the 7th 2011. It counted every person in the country on that night and collected a wide range of social, economic and demographic information about each individual and their housing status.
The information were used to develop statistical indicators to support national plannning and policy-making and also to monitor MDG indicators and all other related conventions. This included population growth rates, educational attainment, employment rates, fertility rates, mortality rates, internal movements, household access to water supply, electricity, sanitation, and many other information. The full report is available at SBS website: http://www.sbs.gov.ws under the section on Population statistics and demography.
National coverage Regions Districts Village Enumeration areas
Private households Institutional households Individuals Women 15-49 Housing/Buildings
The PHC 2011 covered all de facto household members, institutional households such as boarding schools, hospitals, prison inmates and expatriates residing in Samoa for more than 3 months. The PHC excluded all tourists visiting Samoa during the enumeration period and all Samoans residing overseas.
Census/enumeration data [cen]
Not applicable to a complete enumeration census.
Face-to-face [f2f]
Users' consultation seminars were conducted for three consecutive days (June 8th -10th, 2010) with financial support provided by the office of UNFPA in Suva via the Samoa Parliamentary Group for Population Development (SPGPD) annual programs. For the first time in census history, the SPGPD or members of parliament have become the target group of users to get involved in any census questionnaire consultations.
All government ministries and non-governmental organizations were invited to the consultation seminars and each was asked to make a presentation of data needs for consideration in the final census 2011 questionnaire. To avoid re-inventing the wheel in the compilation of the list of census questions for census 2011, the questionnaire from the census 2006 was reprinted and distributed to all participants and presenters to select questions that they would consider again for the census 2011 in addition to their new data needs. Users were also advised that any new question would need good justifications of how it links to national interests.
At the end of the three days seminar, all new questions were compiled for final selection by Samoa Bureau of Statistics. Not all the users' data needs have been included in the final 2011 census questionnaire due mainly to the cost involved and limited time for census enumeration. Therefore, the final selection of questions was purely based on the linkage of the data being requested to the list of statistical indicators in the 'Strategy for the Development of Samoa 2008-2012' (SDS) and the 'Millennium Development Goals' (MDGs) 2015. All data requests outside of the two frameworks were put aside to be integrated in other more appropriate survey activities by the bureau.
From July 2010-December 2010, the questionnaire was formatted using the In-Design CS4 software. It is important to note that the PHC 2011 was the first ever census using the scanning technology to process data from the census questionnaires as a replacement of the usual manual data entry process. The scanning was pilot tested in April 2011, before it was finally used for final census enumeration.
The questionnaire was designed using A3 paper size.
The Population questionnaire was administered in each household, which collected various information on household members including age, sex, citizenship, disability, orphanhood, marital status, residence (birth, usual, previous), religion, education and employment.
In the Population questionnaire, a special section was administered in each household for women age 15-49, which also asked information on their children ever born still living, died or living somewhere else. Mothers of children under one year were also asked whether their last born children were still living at the time of the census.
The Housing questionnaire was also administered in each household which collected information on the types of building the household lived, floor materials, wall materials, roof materials, land tenure, house tenure, water supply, drinking water, lighting, cooking fuel, toilet facility, telephone, computer, internet, refrigerator, radio, television and others.
Data editing was done in several stages. 1. Office manual editing and coding 2. Automatic scanning data entry edits 3. Visual verification questionnaire edits 3. Structure checking and completeness 4. Structure checks of the CSPro data files Editing program can be enquired at the Division of IT and Data Processing at email address: info.stats@sbs.gov.ws
The census is a full-coverage of the population, therefore it is not a sample where sampling errors can be estimated.
There was no post-enumeration in the census 2011. One of the normal practices by the bureau to validate the total population counts from all villages, districts and regions of Samoa in any census is the manual count of the population in all areas during the on-going census enumeration.That information is collected by the enumerators and field supervisors during the enumeration using the Enumerators and Supervisors control forms. At the end of the enumeration, the control forms which mainly contained the number of males and females per enumeration area will be collected and compiled by the Census and Survey division as the first preliminary count of the census. In the census 2011, the preliminary population counts were compiled and launched as the 'Village Directory 2011' report after 4 weeks from end of the enumeration period.
The significance of the Village Directory report is it helps to provide a qiuick overall picture of the population growth and population distribution in all villages of the country relative to previous censuses. Most important of all is that the preliminary count will provide the basis for a decision whether a post-enumeration is warrant or otherwise. If the preliminary country is close to the projected population then the post-enumeration is assumed not worth the cost because it is expensive and it will delay all other census processes. In the census 2011, the preliminary count arrived at 186,340 which was more than the projected population of 184,032 as depicted in the Statistical Abstract 2009. Therefore the decision was made that post-enumeration was not worth it.
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The 2015 TIGER Geodatabases are extracts of selected nation based and state based geographic and cartographic information from the U.S. Census Bureau's Master Address File/Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) database. The geodatabases include feature class layers of information for the fifty states, the District of Columbia, Puerto Rico, and the Island areas (American Samoa, the Commonwealth of the Northern Mariana Islands, Guam, and the United States Virgin Islands). The geodatabases do not contain any sensitive data. The 2015 TIGER Geodatabases are designed for use with Esriâ s ArcGIS.
The State Geodatabase for Indiana geodatabase contains multiple layers. These layers are the Block, Block Group, Census Designated Place, Census
Tract, Consolidated City, County, County Subdivision and Incorporated Place layers.
Block Groups (BGs) are clusters of blocks within the same census tract. Each census tract contains at least one BG, and BGs are uniquely numbered
within census tracts. BGs have a valid code range of 0 through 9. BGs have the same first digit of their 4-digit census block number from the same
decennial census. For example, tabulation blocks numbered 3001, 3002, 3003,.., 3999 within census tract 1210.02 are also within BG 3 within that
census tract. BGs coded 0 are intended to only include water area, no land area, and they are generally in territorial seas, coastal water, and
Great Lakes water areas. Block groups generally contain between 600 and 3,000 people. A BG usually covers a contiguous area but never crosses
county or census tract boundaries. They may, however, cross the boundaries of other geographic entities like county subdivisions, places, urban
areas, voting districts, congressional districts, and American Indian / Alaska Native / Native Hawaiian areas. The BG boundaries in this release are
those that were delineated as part of the Census Bureau's Participant Statistical Areas Program (PSAP) for the 2010 Census.
An incorporated place, or census designated place, is established to provide governmental functions for a concentration of people as opposed to a
minor civil division (MCD), which generally is created to provide services or administer an area without regard, necessarily, to population. Places
always nest within a state, but may extend across county and county subdivision boundaries. An incorporated place usually is a city, town, village,
or borough, but can have other legal descriptions. CDPs are delineated for the decennial census as the statistical counterparts of incorporated
places. CDPs are delineated to provide data for settled concentrations of population that are identifiable by name, but are not legally
incorporated under the laws of the state in which they are located. The boundaries for CDPs often are defined in partnership with state, local,
and/or tribal officials and usually coincide with visible features or the boundary of an adjacent incorporated place or another legal entity. CDP
boundaries often change from one decennial census to the next with changes in the settlement pattern and development; a CDP with the same name as in
an earlier census does not necessarily have the same boundary. The only population/housing size requirement for CDPs is that they must contain some
housing and population. The boundaries of most incorporated places in this shapefile are as of January 1, 2013, as reported through the Census
Bureau's Boundary and Annexation Survey (BAS). Limited updates that occurred after January 1, 2013, such as newly incorporated places, are also
included. The boundaries of all CDPs were delineated as part of the Census Bureau's Participant Statistical Areas Program (PSAP) for the 2010
Census.
The primary purpose of census tracts is to provide a stable set of geographic units for the presentation of census data and comparison back to
previous decennial censuses. Census tracts generally have a population size between 1,200 and 8,000 people, with an optimum size of 4,000 people.
When first delineated, census tracts were designed to be homogeneous with respect to population characteristics, economic status, and living
conditions. The spatial size of census tracts varies widely depending on the density of settlement. Physical changes in street patterns caused by
highway construction, new development, and so forth, may require boundary revisions. In addition, census tracts occasionally are split due to
population growth, or combined as a result of substantial population decline. Census tract boundaries generally follow visible and identifiable
features. They may follow legal boundaries such as minor civil division (MCD) or incorporated place boundaries in some States and situations to
allow for census tract-to-governmental unit relationships where the governmental boundaries tend to remain unchanged between censuses. State and
county boundaries always are census tract boundaries in the standard census geographic hierarchy. In a few rare instances, a census tract may
consist of noncontiguous areas. These noncontiguous areas may occur where the census tracts are coextensive with all or parts of legal entities
that are themselves noncontiguous. For the 2010 Census, the census tract code range of 9400 through 9499 was enforced for census tracts that
include a majority American Indian population according to Census 2000 data and/or their area was primarily covered by federally recognized American
Indian reservations and/or off-reservation trust lands; the code range 9800 through 9899 was enforced for those census tracts that contained little
or no population and represented a relatively large special land use area such as a National Park, military installation, or a business/industrial
park; and the code range 9900 through 9998 was enforced for those census tracts that contained only water area, no land area.
A consolidated city is a unit of local government for which the functions of an incorporated place and its county or minor civil division (MCD) have
merged. This action results in both the primary incorporated place and the county or MCD continuing to exist as legal entities, even though the
county or MCD performs few or no governmental functions and has few or no elected officials. Where this occurs, and where one or more other
incorporated places in the county or MCD continue to function as separate governments, even though they have been included in the consolidated
government, the primary incorporated place is referred to as a consolidated city. The Census Bureau classifies the separately incorporated places
within the consolidated city as place entities and creates a separate place (balance) record for the portion of the consolidated city not within any
other place. The boundaries of the consolidated cities are those as of January 1, 2013, as reported through the Census Bureau's Boundary and
Annexation Survey(BAS).
The primary legal divisions of most states are termed counties. In Louisiana, these divisions are known as parishes. In Alaska, which has no
counties, the equivalent entities are the organized boroughs, city and boroughs, municipalities, and for the unorganized area, census areas. The
latter are delineated cooperatively for statistical purposes by the State of Alaska and the Census Bureau. In four states (Maryland, Missouri,
Nevada, and Virginia), there are one or more incorporated places that are independent of any county organization and thus constitute primary
divisions of their states. These incorporated places are known as independent cities and are treated as equivalent entities for purposes of data
presentation. The District of Columbia and Guam have no primary divisions, and each area is considered an equivalent entity for purposes of data
presentation. The Census Bureau treats the following entities as equivalents of counties for purposes of data presentation: Municipios in Puerto
Rico, Districts and Islands in American Samoa, Municipalities in the Commonwealth of the Northern Mariana Islands, and Islands in the U.S. Virgin
Islands. The entire area of the United States, Puerto Rico, and the Island Areas is covered by counties or equivalent entities. The boundaries for
counties and equivalent entities are mostly as of January 1, 2013, primarily as reported through the Census Bureau's Boundary and Annexation Survey
(BAS). However, some changes made after January 2013, including the addition and deletion of counties, are included.
County subdivisions are the primary divisions of
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Key Table Information.Table Title.State and Locally-Administered Defined Benefit Pension Systems: U.S. and States: 2012 - 2016.Table ID.GOVSTIMESERIES.GS00PP01.Survey/Program.Public Sector.Year.2024.Dataset.PUB Public Sector Annual Surveys and Census of Governments.Source.U.S. Census Bureau, Public Sector.Release Date.2020-07-28.Release Schedule.The Annual Survey of Public Pensions occurs every year. Data are typically released yearly in the second quarter. There is approximately one year between the reference period and data release. Revisions to published data occur annually going back to the previous Census of Goverments. Census of Governments years, those ending in '2' and '7' may have slightly later releases due to extended processing time..Dataset Universe.Census of Governments - Organization (CG):The universe of this file is all federal, state, and local government units in the United States. In addition to the federal government and the 50 state governments, the Census Bureau recognizes five basic types of local governments. The government types are: County, Municipal, Township, Special District, and School District. Of these five types, three are categorized as General Purpose governments: County, municipal, and township governments are readily recognized and generally present no serious problem of classification. However, legislative provisions for school district and special district governments are diverse. These two types are categorized as Special Purpose governments. Numerous single-function and multiple-function districts, authorities, commissions, boards, and other entities, which have varying degrees of autonomy, exist in the United States. The basic pattern of these entities varies widely from state to state. Moreover, various classes of local governments within a particular state also differ in their characteristics. Refer to the Individual State Descriptions report for an overview of all government entities authorized by state.The Public Use File provides a listing of all independent government units, and dependent school districts active as of fiscal year ending June 30, 2024. The Annual Surveys of Public Employment & Payroll (EP) and State and Local Government Finances (LF):The target population consists of all 50 state governments, the District of Columbia, and a sample of local governmental units (counties, cities, townships, special districts, school districts). In years ending in '2' and '7' the entire universe is canvassed. In intervening years, a sample of the target population is surveyed. Additional details on sampling are available in the survey methodology descriptions for those years.The Annual Survey of Public Pensions (PP):The target population consists of state- and locally-administered defined benefit funds and systems of all 50 state governments, the District of Columbia, and a sample of local governmental units (counties, cities, townships, special districts, school districts). In years ending in '2' and '7' the entire universe is canvassed. In intervening years, a sample of the target population is surveyed. Additional details on sampling are available in the survey methodology descriptions for those years.The Annual Surveys of State Government Finance (SG) and State Government Tax Collections (TC):The target population consists of all 50 state governments. No local governments are included. For the purpose of Census Bureau statistics, the term "state government" refers not only to the executive, legislative, and judicial branches of a given state, but it also includes agencies, institutions, commissions, and public authorities that operate separately or somewhat autonomously from the central state government but where the state government maintains administrative or fiscal control over their activities as defined by the Census Bureau. Additional details are available in the survey methodology description.The Annual Survey of School System Finances (SS):The Annual Survey of School System Finances targets all public school systems providing elementary and/or secondary education in all 50 states and the District of Columbia..Methodology.Data Items and Other Identifying Records.Detail of revenues, expenditures, financial assets, and membership information.Definitions can be found by clicking on the column header in the table or by accessing the Glossary.For detailed information, see Government Finance and Employment Classification Manual..Unit(s) of Observation.The basic reporting unit is the governmental unit, defined as an organized entity which in addition to having governmental character, has sufficient discretion in the management of its own affairs to distinguish it as separate from the administrative structure of any other governmental unit.The reporting units for the Annual Survey of School System Finances are public school systems that provide elementary and/or secondary education. The term "public school systems" includes two types of government entities w...
The PHC 2006 provides a population count of all people that resided in Samoa on the 6th of November, 2006. It collected a range of socio-economic and demographic information pertaining to household members and their associated housing facilities and household status. The information were used to develop statistical indicators to support national plannning and policy-making and also to monitor MDG indicators and all other related conventions. This included population growth rates, educational attainment, employment rates, fertility rates, mortality rates, internal movements, household access to water supply, electricity, sanitation, and many other information. The full report is available at SBS website: http://www.sbs.gov.ws under the section on Publications and Reports.
National coverage
Private households Institution households Individuals Women 15-49 Housing facilities
The PHC covered all de facto household members, institutional households such as boarding schools, hospitals, prison inmates, expatriats residing in Samoa for more than 3 months and also all women 15-49 years .The PHC excluded tourists visiting Samoa and Samoans living overseas.
Census/enumeration data [cen]
Not applicable to census-undertaking
Not applicable to census-undertaking
Face-to-face [f2f]
The PHC 2006 questionnaire was developed on the basis of the PHC 2001 with some modifications and additions. The Questionnaire has separate A-3 page for the Population questionnaire and a separate A4 page for the Housing questionnaire.
A Population questionnaire was administered in each household, which collected various information on household members including age, sex, citizenship, ethnicity, orphanhood, marital status, matai status, disability, language of communication, residence (birth, usual, previous), religion, education and employment.
In the Population questionnaire, a special section was administered in each household for women age 15-49, which also asked information on their children ever born still living, died or living somewhere else. Mothers of children under one year were also asked whether they have immunized their babies for measles and rubella.
The Housing questionnaire was also administered in each household which collected information on the types of building the household lived, floor materials, wall materials, roof materials, land tenure, house tenure, water supply, drinking water, lighting, cooking fuel, waste disposal, toilet facility, telephone, computer, internet, cell phones, homezone phone, refrigerator, radio, television, play-station or kidz video games, vehicle, and also the household three main sources of income.
In the Housing questionnaire, a special section was designed to capture household deaths and maternal deaths between November 2004-2006 including the deceased's sex, age at death, and ,the main cause of death.
how to edit on field and in the office to data processing
Data editing took place at a number of stages throughout the processing, including: a) Office editing and coding b) During data entry c) Structure checking and completeness d) Secondary editing e) Structural checking of SPSS data files Detailed documentation of the editing of data can be found in the "Data processing guidelines" document provided as an external resource.
At SBS, a team of Office editors was responsible for reviewing each completed questionnaire that came into the office and checking for missed questions, skip errors, fields incorrectly completed, and checking for inconsistencies in the data. In problematic EA, the Office editors liased with the ACEO:Census-Survey and recommended re-enumeration in areas where coverage was not good or quality of the questionnaire was poor. In 2006, the re-enumeration was carried out in some of the villages in the Apia urban region and some areas of Vaitele mainly due to the unavailability of household members during the allocated enumeration period, and, also due to poor quality of data collection.
On the other hand, the good completed questionnaires were passed on by the Office editors to the Office coders who then performed their coding processes of all the questionnaires in a sequential order. After each questionnaire is coded, the Office coders recorded their dates of completion and then passed on the coded questionnaires to the Data processing team for their controls and data entry processes.
The Data processing team is lead by the Computer Manager and Programmer who also works closely with the ACEO Census-Surveys in monitoring the flow of work. The Computer Manager/Programmer designed the data entry and editing programs, conducted the data entry training and then monitored the data entry and made progress reports. Any problems relating to coding at the data entry will be reported to the ACEO Census-Surveys for improvement.
The Computer Manager/Programmer ran data structural checkings and monitored completeness of data entries. Data verfication had also been closely monitored and double data entry was made at 50%. The ACEO Census-Surveys produced the Tabulation plan in which the Computer Programmer also used to monitor structural checks and data quality.
Any detalied information can be asked directly to the Computer Progammer/Manager of SBS or check into our website at http://www.sbs.gov.ws
Not applicable to census-undertaking
Not applicable to census-undertaking
The TIGER/Line Files include both incorporated places (legal entities) and census designated places or CDPs (statistical entities). An incorporated place is established to provide governmental functions for a concentration of people as opposed to a minor civil division (MCD), which generally is created to provide services or administer an area without regard, necessarily, to population. Places always nest within a State, but may extend across county and county subdivision boundaries. An incorporated place usually is a city, town, village, or borough, but can have other legal descriptions. CDPs are delineated for the decennial census as the statistical counterparts of incorporated places. CDPs are delineated to provide data for settled concentrations of population that are identifiable by name, but are not legally incorporated under the laws of the State in which they are located. The boundaries for CDPs often are defined in partnership with State, local, and/or tribal officials and usually coincide with visible features or the boundary of an adjacent incorporated place or another legal entity. CDP boundaries often change from one decennial census to the next with changes in the settlement pattern and development; a CDP with the same name as in an earlier census does not necessarily have the same boundary. The only population/housing size requirement for CDPs for the 2010 Census is that they must contain some housing and population. The boundaries of all 2020 Census incorporated places are as of January 1, 2020 as reported through the Census Bureau's Boundary and Annexation Survey (BAS). The boundaries of all 2020 Census CDPs were delineated as part of the Census Bureau's Participant Statistical Areas Program (PSAP).STATEFP 2 String State FIPS codeCONCTYFP 5 String Consolidated city FIPS codeCONCTYNS 8 String Consolidated city GNIS codeGEOID 7 String Consolidated city identifier; a concatenation of current state FIPS code and consolidated city FIPS codeNAME 100 String Consolidated city nameNAMELSAD 100 String Name and the translated legal/statistical area description for consolidated cityLSAD 2 String Legal/statistical area description code for consolidated cityCLASSFP 2 String FIPS class codeMTFCC 5 String MAF/TIGER Feature Class Code (G4120)FUNCSTAT 1 String Functional statusALAND 14 Number Land areaAWATER 14 Number Water areaINTPTLAT 11 String Latitude of the internal pointINTPTLON 12 String Longitude of the internal poinhttps://www2.census.gov/geo/pdfs/maps-data/data/tiger/tgrshp_rd18/TGRSHPRD18_TechDoc.pdf
Census Current (2022) Legal and Statistical Entities Web Map Service; January 1, 2022 vintage.
Incorporated Places are those reported to the Census Bureau as legally in existence as of the latest Boundary and Annexation Survey (BAS), under the laws of their respective states. An incorporated place is established to provide governmental functions for a concentration of people as opposed to a minor civil division, which generally is created to provide services or administer an area without regard, necessarily, to population. Places always are within a single state or equivalent entity, but may extend across county and county subdivision boundaries. An incorporated place usually is a city, town, village, or borough but can have other legal descriptions. For Census Bureau data tabulation and presentation purposes, incorporated places exclude:
1) The boroughs in Alaska (treated as statistical equivalents of counties).
2) Towns in the New England states, New York, and Wisconsin (treated as MCDs).
3) The boroughs in New York (treated as MCDs).
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analyze the american community survey (acs) with r and monetdb experimental. think of the american community survey (acs) as the united states' census for off-years - the ones that don't end in zero. every year, one percent of all americans respond, making it the largest complex sample administered by the u.s. government (the decennial census has a much broader reach, but since it attempts to contact 100% of the population, it's not a sur vey). the acs asks how people live and although the questionnaire only includes about three hundred questions on demography, income, insurance, it's often accurate at sub-state geographies and - depending how many years pooled - down to small counties. households are the sampling unit, and once a household gets selected for inclusion, all of its residents respond to the survey. this allows household-level data (like home ownership) to be collected more efficiently and lets researchers examine family structure. the census bureau runs and finances this behemoth, of course. the dow nloadable american community survey ships as two distinct household-level and person-level comma-separated value (.csv) files. merging the two just rectangulates the data, since each person in the person-file has exactly one matching record in the household-file. for analyses of small, smaller, and microscopic geographic areas, choose one-, three-, or fiv e-year pooled files. use as few pooled years as you can, unless you like sentences that start with, "over the period of 2006 - 2010, the average american ... [insert yer findings here]." rather than processing the acs public use microdata sample line-by-line, the r language brazenly reads everything into memory by default. to prevent overloading your computer, dr. thomas lumley wrote the sqlsurvey package principally to deal with t his ram-gobbling monster. if you're already familiar with syntax used for the survey package, be patient and read the sqlsurvey examples carefully when something doesn't behave as you expect it to - some sqlsurvey commands require a different structure (i.e. svyby gets called through svymean) and others might not exist anytime soon (like svyolr). gimme some good news: sqlsurvey uses ultra-fast monetdb (click here for speed tests), so follow the monetdb installation instructions before running this acs code. monetdb imports, writes, recodes data slowly, but reads it hyper-fast . a magnificent trade-off: data exploration typically requires you to think, send an analysis command, think some more, send another query, repeat. importation scripts (especially the ones i've already written for you) can be left running overnight sans hand-holding. the acs weights generalize to the whole united states population including individuals living in group quarters, but non-residential respondents get an abridged questionnaire, so most (not all) analysts exclude records with a relp variable of 16 or 17 right off the bat. this new github repository contains four scripts: 2005-2011 - download all microdata.R create the batch (.bat) file needed to initiate the monet database in the future download, unzip, and import each file for every year and size specified by the user create and save household- and merged/person-level replicate weight complex sample designs create a well-documented block of code to re-initiate the monet db server in the future fair warning: this full script takes a loooong time. run it friday afternoon, commune with nature for the weekend, and if you've got a fast processor and speedy internet connection, monday morning it should be ready for action. otherwise, either download only the years and sizes you need or - if you gotta have 'em all - run it, minimize it, and then don't disturb it for a week. 2011 single-year - analysis e xamples.R run the well-documented block of code to re-initiate the monetdb server load the r data file (.rda) containing the replicate weight designs for the single-year 2011 file perform the standard repertoire of analysis examples, only this time using sqlsurvey functions 2011 single-year - variable reco de example.R run the well-documented block of code to re-initiate the monetdb server copy the single-year 2011 table to maintain the pristine original add a new age category variable by hand add a new age category variable systematically re-create then save the sqlsurvey replicate weight complex sample design on this new table close everything, then load everything back up in a fresh instance of r replicate a few of the census statistics. no muss, no fuss replicate census estimates - 2011.R run the well-documented block of code to re-initiate the monetdb server load the r data file (.rda) containing the replicate weight designs for the single-year 2011 file match every nation wide statistic on the census bureau's estimates page, using sqlsurvey functions click here to view these four scripts for more detail about the american community survey (acs), visit: < ul> the us census...