31 datasets found
  1. w

    Demographic Data - TIGER/Line Shapefile, 2010, 2010 county, Miami-Dade...

    • data.wu.ac.at
    • datadiscoverystudio.org
    xml
    Updated Aug 19, 2017
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    NSGIC Local Govt | GIS Inventory (2017). Demographic Data - TIGER/Line Shapefile, 2010, 2010 county, Miami-Dade County, FL, 2010 Census Census Tract County-based [Dataset]. https://data.wu.ac.at/schema/data_gov/MzFiNWVlZTgtZThlMS00ZjE5LTg3YzEtZDczMjVmMmYzMTBj
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    xmlAvailable download formats
    Dataset updated
    Aug 19, 2017
    Dataset provided by
    NSGIC Local Govt | GIS Inventory
    Area covered
    e542f162cd008c18420b5022876ee15bab71f11e
    Description

    The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line File is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Census tracts are small, relatively permanent statistical subdivisions of a county or equivalent entity, and were defined by local participants as part of the 2010 Census Participant Statistical Areas Program. The Census Bureau delineated the census tracts in situations where no local participant existed or where all the potential participants declined to participate. 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. This census data layer has been imported into the Miami-Dade County ArcSDE infrastructure and re-projected to: Projected Coordinate System: NAD_1983_StatePlane_Florida_East_FIPS_0901_Feet Projection: Transverse_Mercator False_Easting: 656166.66666667 False_Northing: 0.00000000 Central_Meridian: -81.00000000 Scale_Factor: 0.99994118 Latitude_Of_Origin: 24.33333333 Linear Unit: Foot_US The boundaries have been aligned to Miami-Dade County base data where they have been found to NOT be within +/- 10 ft Population figures have been appended to the end of the feature classes attribute table: Pop2010, HU2010, HISPAN, WHITENH, BLACKNH, AMERINDIANNH, ASIANNH, HAWIANNH, OTHERNH, and MULTIRACE. Definitions can be found in the census documentation.

  2. w

    Afrobarometer Survey 1 1999-2000, Merged 7 Country - Botswana, Lesotho,...

    • microdata.worldbank.org
    • catalog.ihsn.org
    • +1more
    Updated Apr 27, 2021
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    Institute for Democracy in South Africa (IDASA) (2021). Afrobarometer Survey 1 1999-2000, Merged 7 Country - Botswana, Lesotho, Malawi, Namibia, South Africa, Zambia, Zimbabwe [Dataset]. https://microdata.worldbank.org/index.php/catalog/889
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    Dataset updated
    Apr 27, 2021
    Dataset provided by
    Ghana Centre for Democratic Development (CDD-Ghana)
    Michigan State University (MSU)
    Institute for Democracy in South Africa (IDASA)
    Time period covered
    1999 - 2000
    Area covered
    Africa, Namibia, Lesotho, South Africa, Botswana, Zimbabwe, Zambia, Malawi
    Description

    Abstract

    Round 1 of the Afrobarometer survey was conducted from July 1999 through June 2001 in 12 African countries, to solicit public opinion on democracy, governance, markets, and national identity. The full 12 country dataset released was pieced together out of different projects, Round 1 of the Afrobarometer survey,the old Southern African Democracy Barometer, and similar surveys done in West and East Africa.

    The 7 country dataset is a subset of the Round 1 survey dataset, and consists of a combined dataset for the 7 Southern African countries surveyed with other African countries in Round 1, 1999-2000 (Botswana, Lesotho, Malawi, Namibia, South Africa, Zambia and Zimbabwe). It is a useful dataset because, in contrast to the full 12 country Round 1 dataset, all countries in this dataset were surveyed with the identical questionnaire

    Geographic coverage

    Botswana Lesotho Malawi Namibia South Africa Zambia Zimbabwe

    Analysis unit

    Basic units of analysis that the study investigates include: individuals and groups

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    A new sample has to be drawn for each round of Afrobarometer surveys. Whereas the standard sample size for Round 3 surveys will be 1200 cases, a larger sample size will be required in societies that are extremely heterogeneous (such as South Africa and Nigeria), where the sample size will be increased to 2400. Other adaptations may be necessary within some countries to account for the varying quality of the census data or the availability of census maps.

    The sample is designed as a representative cross-section of all citizens of voting age in a given country. The goal is to give every adult citizen an equal and known chance of selection for interview. We strive to reach this objective by (a) strictly applying random selection methods at every stage of sampling and by (b) applying sampling with probability proportionate to population size wherever possible. A randomly selected sample of 1200 cases allows inferences to national adult populations with a margin of sampling error of no more than plus or minus 2.5 percent with a confidence level of 95 percent. If the sample size is increased to 2400, the confidence interval shrinks to plus or minus 2 percent.

    Sample Universe

    The sample universe for Afrobarometer surveys includes all citizens of voting age within the country. In other words, we exclude anyone who is not a citizen and anyone who has not attained this age (usually 18 years) on the day of the survey. Also excluded are areas determined to be either inaccessible or not relevant to the study, such as those experiencing armed conflict or natural disasters, as well as national parks and game reserves. As a matter of practice, we have also excluded people living in institutionalized settings, such as students in dormitories and persons in prisons or nursing homes.

    What to do about areas experiencing political unrest? On the one hand we want to include them because they are politically important. On the other hand, we want to avoid stretching out the fieldwork over many months while we wait for the situation to settle down. It was agreed at the 2002 Cape Town Planning Workshop that it is difficult to come up with a general rule that will fit all imaginable circumstances. We will therefore make judgments on a case-by-case basis on whether or not to proceed with fieldwork or to exclude or substitute areas of conflict. National Partners are requested to consult Core Partners on any major delays, exclusions or substitutions of this sort.

    Sample Design

    The sample design is a clustered, stratified, multi-stage, area probability sample.

    To repeat the main sampling principle, the objective of the design is to give every sample element (i.e. adult citizen) an equal and known chance of being chosen for inclusion in the sample. We strive to reach this objective by (a) strictly applying random selection methods at every stage of sampling and by (b) applying sampling with probability proportionate to population size wherever possible.

    In a series of stages, geographically defined sampling units of decreasing size are selected. To ensure that the sample is representative, the probability of selection at various stages is adjusted as follows:

    The sample is stratified by key social characteristics in the population such as sub-national area (e.g. region/province) and residential locality (urban or rural). The area stratification reduces the likelihood that distinctive ethnic or language groups are left out of the sample. And the urban/rural stratification is a means to make sure that these localities are represented in their correct proportions. Wherever possible, and always in the first stage of sampling, random sampling is conducted with probability proportionate to population size (PPPS). The purpose is to guarantee that larger (i.e., more populated) geographical units have a proportionally greater probability of being chosen into the sample. The sampling design has four stages

    A first-stage to stratify and randomly select primary sampling units;

    A second-stage to randomly select sampling start-points;

    A third stage to randomly choose households;

    A final-stage involving the random selection of individual respondents

    We shall deal with each of these stages in turn.

    STAGE ONE: Selection of Primary Sampling Units (PSUs)

    The primary sampling units (PSU's) are the smallest, well-defined geographic units for which reliable population data are available. In most countries, these will be Census Enumeration Areas (or EAs). Most national census data and maps are broken down to the EA level. In the text that follows we will use the acronyms PSU and EA interchangeably because, when census data are employed, they refer to the same unit.

    We strongly recommend that NIs use official national census data as the sampling frame for Afrobarometer surveys. Where recent or reliable census data are not available, NIs are asked to inform the relevant Core Partner before they substitute any other demographic data. Where the census is out of date, NIs should consult a demographer to obtain the best possible estimates of population growth rates. These should be applied to the outdated census data in order to make projections of population figures for the year of the survey. It is important to bear in mind that population growth rates vary by area (region) and (especially) between rural and urban localities. Therefore, any projected census data should include adjustments to take such variations into account.

    Indeed, we urge NIs to establish collegial working relationships within professionals in the national census bureau, not only to obtain the most recent census data, projections, and maps, but to gain access to sampling expertise. NIs may even commission a census statistician to draw the sample to Afrobarometer specifications, provided that provision for this service has been made in the survey budget.

    Regardless of who draws the sample, the NIs should thoroughly acquaint themselves with the strengths and weaknesses of the available census data and the availability and quality of EA maps. The country and methodology reports should cite the exact census data used, its known shortcomings, if any, and any projections made from the data. At minimum, the NI must know the size of the population and the urban/rural population divide in each region in order to specify how to distribute population and PSU's in the first stage of sampling. National investigators should obtain this written data before they attempt to stratify the sample.

    Once this data is obtained, the sample population (either 1200 or 2400) should be stratified, first by area (region/province) and then by residential locality (urban or rural). In each case, the proportion of the sample in each locality in each region should be the same as its proportion in the national population as indicated by the updated census figures.

    Having stratified the sample, it is then possible to determine how many PSU's should be selected for the country as a whole, for each region, and for each urban or rural locality.

    The total number of PSU's to be selected for the whole country is determined by calculating the maximum degree of clustering of interviews one can accept in any PSU. Because PSUs (which are usually geographically small EAs) tend to be socially homogenous we do not want to select too many people in any one place. Thus, the Afrobarometer has established a standard of no more than 8 interviews per PSU. For a sample size of 1200, the sample must therefore contain 150 PSUs/EAs (1200 divided by 8). For a sample size of 2400, there must be 300 PSUs/EAs.

    These PSUs should then be allocated proportionally to the urban and rural localities within each regional stratum of the sample. Let's take a couple of examples from a country with a sample size of 1200. If the urban locality of Region X in this country constitutes 10 percent of the current national population, then the sample for this stratum should be 15 PSUs (calculated as 10 percent of 150 PSUs). If the rural population of Region Y constitutes 4 percent of the current national population, then the sample for this stratum should be 6 PSU's.

    The next step is to select particular PSUs/EAs using random methods. Using the above example of the rural localities in Region Y, let us say that you need to pick 6 sample EAs out of a census list that contains a total of 240 rural EAs in Region Y. But which 6? If the EAs created by the national census bureau are of equal or roughly equal population size, then selection is relatively straightforward. Just number all EAs consecutively, then make six selections using a table of random numbers. This procedure, known as simple random sampling (SRS), will

  3. g

    Attraction CBD

    • datahub.gpmarinelitter.org
    Updated Aug 26, 2021
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    Global Partnership on Marine Litter (2021). Attraction CBD [Dataset]. https://datahub.gpmarinelitter.org/datasets/attraction-cbd
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    Dataset updated
    Aug 26, 2021
    Dataset authored and provided by
    Global Partnership on Marine Litter
    Area covered
    Description

    Population Density : This vector dataset provides the population density by commune in Cambodia, as provided by Cambodian Demographic Census 2008 (Ministry of Planning, National Institute of Statistics). Dataset were provided to Open Development Cambodia (ODC) in vector format by Save Cambodia's Wildlife's Atlas Working Group.Urban Density in Cambodia (2011) : This vector dataset provides the urban density in Cambodia, as given by the United Nations Population Fund (UNFPA). Dataset were provided to Open Development Cambodia (ODC) by Save Cambodia's Wildlife's Atlas Working Group.Population Projections for 2030 in Cambodia (2010) : This dataset provides projected population of 2030, projected annual growth rate in each province in Cambodia, given by National Institute of Statistics and the United Nations. Data were provided to Open Development Cambodia (ODC) in vector format by Save Cambodia's Wildlife's Atlas Working Group.River networks of Cambodia : Vector polyline data of river networks in Cambodia. Attributes include: name of river, name of basin, name of sub-basin, Strahler number.Canals in Cambodia (2008) : This dataset is included geographical locations of canals and types of canal such as earthen, levee and masonry. The data is released by Department of Geography of Ministry of Land Management, Urban Planning, and Construction of Cambodia, and then it is contributed by Office for the Coordination of Humanitarian Affairs (OCHA) and shared on Humanitarian Data Exchange (HDX). ODC's map and data team has collected the data from HDX website in Shapefile format and re-published it on ODC's website.Special economic zone in Cambodia (2006-2019) : This dataset describes the information of special economic zone (SEZ) in Cambodia from 2006 to 2019. The total number of 42 SEZ is recorded. The data was collected from many sources by ODC’s mappers such as the royal gazette of Cambodia's government, and reports of the governmental ministries in hard and soft copies of pdf format. Geographic data is encoded in the WGS 84, Zone 48 North coordinate reference system.Road and railway networks in Cambodia (2012- 2019) : Road networks are produced by Open Street Map. ODC's map and data team extracted the data in vector format. Moreover, the polyline data of railway​ given by Save Cambodia's Wildlife's Atlas Working Group in Cambodia for two statuses such as existing, proposed new lines in Cambodia.Forest cover in Cambodia (2015-2018) : This forest cover is extracted from the Forest Monitoring System (https://rlcms-servir.adpc.net/en/forest-monitor/) which is developed by SERVIR-Mekong and the Global Land Analysis and Discovery Lab (GLAD) from University of Maryland. The definition of forest for this dataset is the tree canopy greater than 10% with height more than 5 meters.Schools in flood-prone area 2013 (information 2012-2014) : This dataset is created by clipping between Cambodia flood-prone areas in 2013 dataset and Basic information of school dataset to identify schools are under the flood extend in 2013. The basic information of school contains the spatial location of school, the attribute information in 2014, and total enrollment in 2012.Basic map of Cambodia (2014) : These datasets contain three different types of administrative boundary levels: provincial, district and commune which were contributed by Office for the Coordination of Humanitarian Affairs (OCHA) to Humanitarian Data Exchange (HDX). The datasets were obtained from the Department of Geography of Ministry of Land Management, Urban Planning and Construction (MLMUPC) in 2008 and then unofficially updated in 2014 by referring to Sub-decrees on administrative modifications. Most Recent Changes: New province added (Tbong Khmum), with underlying districts and communes.Land cover in Cambodia (2012- 2016) : The land cover is extracted from the Regional Land Cover Monitoring System (https://rlcms-servir.adpc.net/en/landcover/) which is developed by SERVIR-Mekong. The primitives are calculated from remote sensing indices which were made from yearly Landsat surface reflectance composites. The training data were collected by combining field information with high-resolution satellite imagery.Cropland in Cambodia : This dataset contains information of cropland and location of croplands in Cambodia which was downloaded from World Food Programme GeoNode (WFPGeoNode) using data in 2013 from​ the Department of Land and Geography of the Ministry of Land Management, Urban Planning and Construction.Community Fisheries Map for Cambodia (2011) : This dataset provides 2011 geographic boundaries, size and the number of villages covered by each community fishery for which coordinates are available in Cambodia, as given by the Fisheries Administration. For those community fisheries sites without coordinates, locations are given as the center points of communes and metrics are taken from the Commune Database of 2011. Geographic data is encoded in the WGS 84 coordinate reference system. Data were provided to ODC in vector format by Save Cambodia's Wildlife's Atlas Working Group.Digital Elevation Model (DEM 12.5 m) in 2010 : This raster dataset provides the Digital Elevation Model in the world. Dataset were provided to ASF Data Search Vertex by EarthData. This dataset has high resolution terrain at 12.5 meter. Alaska Satellite Facility (ASF) : making remote-sensing data accessible. ASF operates the NASA archive of synthetic aperture radar (SAR) data from a variety of satellites and aircraft, providing these data and associated specialty support services to researchers in support of NASA’s Earth Science Data and Information System (ESDIS) project.Function Area : This dataset are produced by Open Street Map. The data extracted the data in vector format (point feature).Tourism area (Museum, Attraction) : This dataset are produced by Open Street Map. The data extracted the data in vector format (point feature).Entity : Royal Government of Cambodia, Ministry of Planning, National Institute of Statistics; Cambodian Demographic Census 2008. Phnom Penh, 2008; Save Cambodia's Wildlife; In Atlas of Cambodia: maps on socio-economic development and environment;Time period : 2006-2018Frequency of update : Always up-to-dateGeo-coverage() : NationalGeo-coverage: National() : Cambodia

  4. w

    R2 & NE: Tract Level 2006-2010 ACS Population Summary

    • data.wu.ac.at
    • datadiscoverystudio.org
    tgrshp (compressed)
    Updated Jan 13, 2018
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    U.S. Environmental Protection Agency (2018). R2 & NE: Tract Level 2006-2010 ACS Population Summary [Dataset]. https://data.wu.ac.at/odso/data_gov/Yjk4NjA3N2EtNDM1My00NjFkLTlhOWEtYmEyOTAzM2I3YWVi
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    tgrshp (compressed)Available download formats
    Dataset updated
    Jan 13, 2018
    Dataset provided by
    U.S. Environmental Protection Agency
    License

    U.S. Government Workshttps://www.usa.gov/government-works
    License information was derived automatically

    Area covered
    ad4bfb9d41cff80fae3adba549976db2a10b8b44
    Description

    The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line File is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Census tracts are small, relatively permanent statistical subdivisions of a county or equivalent entity, and were defined by local participants as part of the 2010 Census Participant Statistical Areas Program. The Census Bureau delineated the census tracts in situations where no local participant existed or where all the potential participants declined to participate. 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.

    This table contains data on race, age, sex, and marital status from the American Community Survey 2006-2010 database for tracts. The American Community Survey (ACS) is a household survey conducted by the U.S. Census Bureau that currently has an annual sample size of about 3.5 million addresses. ACS estimates provides communities with the current information they need to plan investments and services. Information from the survey generates estimates that help determine how more than $400 billion in federal and state funds are distributed annually. Each year the survey produces data that cover the periods of 1-year, 3-year, and 5-year estimates for geographic areas in the United States and Puerto Rico, ranging from neighborhoods to Congressional districts to the entire nation. This table also has a companion table (Same table name with MOE Suffix) with the margin of error (MOE) values for each estimated element. MOE is expressed as a measure value for each estimated element. So a value of 25 and an MOE of 5 means 25 +/- 5 (or statistical certainty between 20 and 30). There are also special cases of MOE. An MOE of -1 means the associated estimates do not have a measured error. An MOE of 0 means that error calculation is not appropriate for the associated value. An MOE of 109 is set whenever an estimate value is 0. The MOEs of aggregated elements and percentages must be calculated. This process means using standard error calculations as described in "American Community Survey Multiyear Accuracy of the Data (3-year 2008-2010 and 5-year 2006-2010)". Also, following Census guidelines, aggregated MOEs do not use more than 1 0-element MOE (109) to prevent over estimation of the error. Due to the complexity of the calculations, some percentage MOEs cannot be calculated (these are set to null in the summary-level MOE tables).

    The name for table 'ACS10POPTRMOE' was added as a prefix to all field names imported from that table. Be sure to turn off 'Show Field Aliases' to see complete field names in the Attribute Table of this feature layer. This can be done in the 'Table Options' drop-down menu in the Attribute Table or with key sequence '[CTRL]+[SHIFT]+N'. Due to database restrictions, the prefix may have been abbreviated if the field name exceded the maximum allowed characters.

  5. S

    Meshblock 2015 (generalised version)

    • datafinder.stats.govt.nz
    csv, dwg, geodatabase +6
    Updated Apr 30, 2025
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    Stats NZ (2025). Meshblock 2015 (generalised version) [Dataset]. https://datafinder.stats.govt.nz/layer/122190-meshblock-2015-generalised-version/
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    shapefile, geopackage / sqlite, pdf, mapinfo tab, mapinfo mif, geodatabase, csv, dwg, kmlAvailable download formats
    Dataset updated
    Apr 30, 2025
    Dataset provided by
    Statistics New Zealandhttp://www.stats.govt.nz/
    Authors
    Stats NZ
    License

    https://datafinder.stats.govt.nz/license/attribution-4-0-international/https://datafinder.stats.govt.nz/license/attribution-4-0-international/

    Area covered
    Description

    This dataset is the definitive set of meshblock boundaries as defined by Statistics New Zealand as at 1 January 2015.

    Statistics New Zealand maintains an annual meshblock pattern for collecting and producing statistical data. This allows data to be compared over time. A meshblock is the smallest geographic unit for which statistical data is collected and processed by Statistics New Zealand. A meshblock is defined by a geographic area, which can vary in size from part of a city block to a large area of rural land. Each meshblock borders on another to form a network covering all of New Zealand, including coasts and inlets and extending out to the 200-mile economic zone. Meshblocks are added together to build up larger geographic areas such as area units and urban areas. They are also used to define electoral districts, territorial authorities, and regional councils.

    There are two ways of amending meshblock boundaries.

    1. Splitting is subdividing a meshblock into two or more meshblocks.
    2. Nudging is shifting a boundary to a more appropriate position.

    Reasons for splits and nudges include:

    • to accommodate changes to local government boundaries, which are required by the Local Government Act 2002 to follow meshblocks for electoral purposes
    • to accommodate changes to parliamentary electoral boundaries, following each Electoral Representation Commission review after each five-yearly Census of Population and Dwellings
    • to make changes to statistical boundaries such as area units and urban areas
    • to enable changes to census collection districts
    • to improve the size balance of meshblocks in areas where there has been population growth
    • to separate land and water – eg mainland, islands, inlets, and oceanic are defined separately.
    • to accommodate requests from other users of the meshblock pattern eg the NZ Police for their station, area, and district boundaries.

    Meshblock numbering process until 2014 (MB 2014)

    Meshblocks were allocated a unique seven-digit number. The first five digits were unique, and referred to the original 1976 meshblock code. The two end numbers refer to sequential meshblock splits to the original meshblock. When a meshblock is split the final two digits of the original meshblock number are changed. Exceptions to this rule are a small number of meshblocks where no more numbers in the sequence are available. Accordingly there were some meshblocks in Auckland and Tauranga City starting with 32xxxxx. Statistics New Zealand maintains a concordance file to ensure that boundaries relating to earlier meshblock patterns can also be produced.

    Meshblock numbering process from 2015 (MB 2015)

    Due to new technology being introduced for splitting and nudging meshblocks, the process for allocating a unique seven-digit number has changed. New meshblock numbering is approximately sequential. The first meshblock number in this new sequential numbering pattern is 4000000. This differentiates meshblocks split from MB2015 onwards, and allows for a large number of unique seven digit identifiers to be allocated. Now when a meshblock is split it takes on the next available number, rather than following the former process described above.

    Digital geographic boundary data became freely available on 1 July 2007.

  6. i

    Afrobarometer Survey 2005-2006 - Africa

    • dev.ihsn.org
    Updated Apr 25, 2019
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    Institute for Democracy in South Africa (IDASA) (2019). Afrobarometer Survey 2005-2006 - Africa [Dataset]. https://dev.ihsn.org/nada/catalog/study/AFR_2005_AFB-18_v01_M
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    Dataset updated
    Apr 25, 2019
    Dataset provided by
    Ghana Centre for Democratic Development (CDD-Ghana)
    Michigan State University (MSU)
    Institute for Democracy in South Africa (IDASA)
    Time period covered
    2005 - 2006
    Area covered
    Africa
    Description

    Abstract

    The Afrobarometer project assesses attitudes and public opinion on democracy, markets, and civil society in several sub-Saharan African.This dataset was compiled from the studies in Round 3 of the Afrobarometer survey, conducted from 2005-2006 in 18 African countries (Benin, Botswana, Cape Verde, Ghana, Kenya, Lesotho, Madagascar, Malawi, Mali, Mozambique, Namibia, Nigeria, Senegal, South Africa, Tanzania, Uganda, Zambia, Zimbabwe).

    Geographic coverage

    The Afrobarometer surveys have national coverage

    Botswana Lesotho Malawi Namibia South Africa Zambia Zimbabwe Ghana Mali Nigeria Tanzania Uganda Cape Verde Mozambique Senegal Kenya Benin Madagascar

    Analysis unit

    Basic units of analysis that the study investigates include: individuals and groups

    Universe

    The sample universe for Afrobarometer surveys includes all citizens of voting age within the country. In other words, we exclude anyone who is not a citizen and anyone who has not attained this age (usually 18 years) on the day of the survey. Also excluded are areas determined to be either inaccessible or not relevant to the study, such as those experiencing armed conflict or natural disasters, as well as national parks and game reserves. As a matter of practice, we have also excluded people living in institutionalized settings, such as students in dormitories and persons in prisons or nursing homes.

    What to do about areas experiencing political unrest? On the one hand we want to include them because they are politically important. On the other hand, we want to avoid stretching out the fieldwork over many months while we wait for the situation to settle down. It was agreed at the 2002 Cape Town Planning Workshop that it is difficult to come up with a general rule that will fit all imaginable circumstances. We will therefore make judgments on a case-by-case basis on whether or not to proceed with fieldwork or to exclude or substitute areas of conflict. National Partners are requested to consult Core Partners on any major delays, exclusions or substitutions of this sort.

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    A new sample has to be drawn for each round of Afrobarometer surveys. Whereas the standard sample size for Round 3 surveys will be 1200 cases, a larger sample size will be required in societies that are extremely heterogeneous (such as South Africa and Nigeria), where the sample size will be increased to 2400. Other adaptations may be necessary within some countries to account for the varying quality of the census data or the availability of census maps.

    The sample is designed as a representative cross-section of all citizens of voting age in a given country. The goal is to give every adult citizen an equal and known chance of selection for interview. We strive to reach this objective by (a) strictly applying random selection methods at every stage of sampling and by (b) applying sampling with probability proportionate to population size wherever possible. A randomly selected sample of 1200 cases allows inferences to national adult populations with a margin of sampling error of no more than plus or minus 2.5 percent with a confidence level of 95 percent. If the sample size is increased to 2400, the confidence interval shrinks to plus or minus 2 percent.

    Sample Universe

    The sample universe for Afrobarometer surveys includes all citizens of voting age within the country. In other words, we exclude anyone who is not a citizen and anyone who has not attained this age (usually 18 years) on the day of the survey. Also excluded are areas determined to be either inaccessible or not relevant to the study, such as those experiencing armed conflict or natural disasters, as well as national parks and game reserves. As a matter of practice, we have also excluded people living in institutionalized settings, such as students in dormitories and persons in prisons or nursing homes.

    What to do about areas experiencing political unrest? On the one hand we want to include them because they are politically important. On the other hand, we want to avoid stretching out the fieldwork over many months while we wait for the situation to settle down. It was agreed at the 2002 Cape Town Planning Workshop that it is difficult to come up with a general rule that will fit all imaginable circumstances. We will therefore make judgments on a case-by-case basis on whether or not to proceed with fieldwork or to exclude or substitute areas of conflict. National Partners are requested to consult Core Partners on any major delays, exclusions or substitutions of this sort.

    Sample Design

    The sample design is a clustered, stratified, multi-stage, area probability sample.

    To repeat the main sampling principle, the objective of the design is to give every sample element (i.e. adult citizen) an equal and known chance of being chosen for inclusion in the sample. We strive to reach this objective by (a) strictly applying random selection methods at every stage of sampling and by (b) applying sampling with probability proportionate to population size wherever possible.

    In a series of stages, geographically defined sampling units of decreasing size are selected. To ensure that the sample is representative, the probability of selection at various stages is adjusted as follows:

    The sample is stratified by key social characteristics in the population such as sub-national area (e.g. region/province) and residential locality (urban or rural). The area stratification reduces the likelihood that distinctive ethnic or language groups are left out of the sample. And the urban/rural stratification is a means to make sure that these localities are represented in their correct proportions. Wherever possible, and always in the first stage of sampling, random sampling is conducted with probability proportionate to population size (PPPS). The purpose is to guarantee that larger (i.e., more populated) geographical units have a proportionally greater probability of being chosen into the sample. The sampling design has four stages

    A first-stage to stratify and randomly select primary sampling units;

    A second-stage to randomly select sampling start-points;

    A third stage to randomly choose households;

    A final-stage involving the random selection of individual respondents

    We shall deal with each of these stages in turn.

    STAGE ONE: Selection of Primary Sampling Units (PSUs)

    The primary sampling units (PSU's) are the smallest, well-defined geographic units for which reliable population data are available. In most countries, these will be Census Enumeration Areas (or EAs). Most national census data and maps are broken down to the EA level. In the text that follows we will use the acronyms PSU and EA interchangeably because, when census data are employed, they refer to the same unit.

    We strongly recommend that NIs use official national census data as the sampling frame for Afrobarometer surveys. Where recent or reliable census data are not available, NIs are asked to inform the relevant Core Partner before they substitute any other demographic data. Where the census is out of date, NIs should consult a demographer to obtain the best possible estimates of population growth rates. These should be applied to the outdated census data in order to make projections of population figures for the year of the survey. It is important to bear in mind that population growth rates vary by area (region) and (especially) between rural and urban localities. Therefore, any projected census data should include adjustments to take such variations into account.

    Indeed, we urge NIs to establish collegial working relationships within professionals in the national census bureau, not only to obtain the most recent census data, projections, and maps, but to gain access to sampling expertise. NIs may even commission a census statistician to draw the sample to Afrobarometer specifications, provided that provision for this service has been made in the survey budget.

    Regardless of who draws the sample, the NIs should thoroughly acquaint themselves with the strengths and weaknesses of the available census data and the availability and quality of EA maps. The country and methodology reports should cite the exact census data used, its known shortcomings, if any, and any projections made from the data. At minimum, the NI must know the size of the population and the urban/rural population divide in each region in order to specify how to distribute population and PSU's in the first stage of sampling. National investigators should obtain this written data before they attempt to stratify the sample.

    Once this data is obtained, the sample population (either 1200 or 2400) should be stratified, first by area (region/province) and then by residential locality (urban or rural). In each case, the proportion of the sample in each locality in each region should be the same as its proportion in the national population as indicated by the updated census figures.

    Having stratified the sample, it is then possible to determine how many PSU's should be selected for the country as a whole, for each region, and for each urban or rural locality.

    The total number of PSU's to be selected for the whole country is determined by calculating the maximum degree of clustering of interviews one can accept in any PSU. Because PSUs (which are usually geographically small EAs) tend to be socially homogenous we do not want to select too many people in any one place. Thus, the Afrobarometer has established a standard of no more than 8 interviews per PSU. For a sample size of 1200, the sample must therefore contain 150 PSUs/EAs (1200 divided by 8). For a sample size of 2400, there must be 300 PSUs/EAs.

    These PSUs should then be allocated

  7. W

    R2 & NE: Tract Level 2006-2010 ACS Income Summary

    • cloud.csiss.gmu.edu
    Updated Mar 6, 2021
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    United States (2021). R2 & NE: Tract Level 2006-2010 ACS Income Summary [Dataset]. https://cloud.csiss.gmu.edu/uddi/dataset/r2-ne-tract-level-2006-2010-acs-income-summary
    Explore at:
    Dataset updated
    Mar 6, 2021
    Dataset provided by
    United States
    Description

    The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line File is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Census tracts are small, relatively permanent statistical subdivisions of a county or equivalent entity, and were defined by local participants as part of the 2010 Census Participant Statistical Areas Program. The Census Bureau delineated the census tracts in situations where no local participant existed or where all the potential participants declined to participate. 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.

    This table contains data on household income and poverty status from the American Community Survey 2006-2010 database for tracts. The American Community Survey (ACS) is a household survey conducted by the U.S. Census Bureau that currently has an annual sample size of about 3.5 million addresses. ACS estimates provides communities with the current information they need to plan investments and services. Information from the survey generates estimates that help determine how more than $400 billion in federal and state funds are distributed annually. Each year the survey produces data that cover the periods of 1-year, 3-year, and 5-year estimates for geographic areas in the United States and Puerto Rico, ranging from neighborhoods to Congressional districts to the entire nation. This table also has a companion table (Same table name with MOE Suffix) with the margin of error (MOE) values for each estimated element. MOE is expressed as a measure value for each estimated element. So a value of 25 and an MOE of 5 means 25 +/- 5 (or statistical certainty between 20 and 30). There are also special cases of MOE. An MOE of -1 means the associated estimates do not have a measured error. An MOE of 0 means that error calculation is not appropriate for the associated value. An MOE of 109 is set whenever an estimate value is 0. The MOEs of aggregated elements and percentages must be calculated. This process means using standard error calculations as described in "American Community Survey Multiyear Accuracy of the Data (3-year 2008-2010 and 5-year 2006-2010)". Also, following Census guidelines, aggregated MOEs do not use more than 1 0-element MOE (109) to prevent over estimation of the error. Due to the complexity of the calculations, some percentage MOEs cannot be calculated (these are set to null in the summary-level MOE tables).

    The name for table 'ACS10INCTRMOE' was added as a prefix to all field names imported from that table. Be sure to turn off 'Show Field Aliases' to see complete field names in the Attribute Table of this feature layer. This can be done in the 'Table Options' drop-down menu in the Attribute Table or with key sequence '[CTRL]+[SHIFT]+N'. Due to database restrictions, the prefix may have been abbreviated if the field name exceded the maximum allowed characters.

  8. a

    Census Tracts 2010

    • gisopendata-countyofriverside.opendata.arcgis.com
    • hub.arcgis.com
    • +2more
    Updated Apr 23, 2019
    + more versions
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    Riverside County Mapping Portal (2019). Census Tracts 2010 [Dataset]. https://gisopendata-countyofriverside.opendata.arcgis.com/datasets/census-tracts-2010
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    Dataset updated
    Apr 23, 2019
    Dataset authored and provided by
    Riverside County Mapping Portal
    Area covered
    Description

    The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line File is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Census tracts are small, relatively permanent statistical subdivisions of a county or equivalent entity, and were defined by local participants as part of the 2010 Census Participant Statistical Areas Program. The Census Bureau delineated the census tracts in situations where no local participant existed or where all the potential participants declined to participate. 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.Field Definition:STATEFP10 - 2010 Census State FIPS codesCOUNTYFP10 - 2010 Census County FIPS CodesTRACTCE10 - 2010 Census Census TractGEOID10 - "Census tract identifier; a concatenation of 2010 Census state FIPS code, county FIPS code, and census tract code"NAME10 - "2010 Census census tract name, this is the census tract code converted to an integer or integer plus two-digit decimal if the last two characters of the code are not both zeros"NAMELSAD10 - 2010 Census translated legal/statistical area description and the census tract nameMTFCC10 - 2010 Census MAF/TIGER featture class codeFUNCSTAT10 - 2010 Census Functional Statitical CodeALAND10 - 2010 Census Area LandAWATER10 - 2010 Census Area waterINTPTLAT10 - 2010 Census Internal Point (Latitude)INTPTLON10 - 2010 Census Internal Point (Longtitude)POPULATION - Total PopulationHOUSING_UNITS - Total Housing units

  9. i

    Afrobarometer Survey 2002-2004 - Africa

    • dev.ihsn.org
    Updated Apr 25, 2019
    + more versions
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    Institute for Democracy in South Africa (IDASA) (2019). Afrobarometer Survey 2002-2004 - Africa [Dataset]. https://dev.ihsn.org/nada/catalog/study/AFR_2002_AFB-16_v01_M
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    Dataset updated
    Apr 25, 2019
    Dataset provided by
    Ghana Centre for Democratic Development (CDD-Ghana)
    Michigan State University (MSU)
    Institute for Democracy in South Africa (IDASA)
    Time period covered
    2002 - 2004
    Area covered
    Africa
    Description

    Abstract

    The Afrobarometer project assesses attitudes and public opinion on democracy, markets, and civil society in several sub-Saharan African.This dataset was compiled from the studies in Round II of the Afrobarometer, conducted from 2002-2004 in 16 countries, including Botswana, Cape Verde, Ghana, Kenya, Lesotho, Malawi, Mali, Mozambique, Namibia, Nigeria, Senegal, South Africa, Tanzania, Uganda, Zambia, and Zimbabwe

    Geographic coverage

    The Afrobarometer surveys have national coverage

    Botswana Lesotho Malawi Namibia South Africa Zambia Zimbabwe Ghana Mali Nigeria Tanzania Uganda Cape Verde Mozambique Senegal Kenya

    Analysis unit

    Basic units of analysis that the study investigates include: individuals and groups

    Universe

    The sample universe for Afrobarometer surveys includes all citizens of voting age within the country. In other words, we exclude anyone who is not a citizen and anyone who has not attained this age (usually 18 years) on the day of the survey. Also excluded are areas determined to be either inaccessible or not relevant to the study, such as those experiencing armed conflict or natural disasters, as well as national parks and game reserves. As a matter of practice, we have also excluded people living in institutionalized settings, such as students in dormitories and persons in prisons or nursing homes.

    What to do about areas experiencing political unrest? On the one hand we want to include them because they are politically important. On the other hand, we want to avoid stretching out the fieldwork over many months while we wait for the situation to settle down. It was agreed at the 2002 Cape Town Planning Workshop that it is difficult to come up with a general rule that will fit all imaginable circumstances. We will therefore make judgments on a case-by-case basis on whether or not to proceed with fieldwork or to exclude or substitute areas of conflict. National Partners are requested to consult Core Partners on any major delays, exclusions or substitutions of this sort.

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    A new sample has to be drawn for each round of Afrobarometer surveys. Whereas the standard sample size for Round 3 surveys will be 1200 cases, a larger sample size will be required in societies that are extremely heterogeneous (such as South Africa and Nigeria), where the sample size will be increased to 2400. Other adaptations may be necessary within some countries to account for the varying quality of the census data or the availability of census maps.

    The sample is designed as a representative cross-section of all citizens of voting age in a given country. The goal is to give every adult citizen an equal and known chance of selection for interview. We strive to reach this objective by (a) strictly applying random selection methods at every stage of sampling and by (b) applying sampling with probability proportionate to population size wherever possible. A randomly selected sample of 1200 cases allows inferences to national adult populations with a margin of sampling error of no more than plus or minus 2.5 percent with a confidence level of 95 percent. If the sample size is increased to 2400, the confidence interval shrinks to plus or minus 2 percent.

    Sample Universe

    The sample universe for Afrobarometer surveys includes all citizens of voting age within the country. In other words, we exclude anyone who is not a citizen and anyone who has not attained this age (usually 18 years) on the day of the survey. Also excluded are areas determined to be either inaccessible or not relevant to the study, such as those experiencing armed conflict or natural disasters, as well as national parks and game reserves. As a matter of practice, we have also excluded people living in institutionalized settings, such as students in dormitories and persons in prisons or nursing homes.

    What to do about areas experiencing political unrest? On the one hand we want to include them because they are politically important. On the other hand, we want to avoid stretching out the fieldwork over many months while we wait for the situation to settle down. It was agreed at the 2002 Cape Town Planning Workshop that it is difficult to come up with a general rule that will fit all imaginable circumstances. We will therefore make judgments on a case-by-case basis on whether or not to proceed with fieldwork or to exclude or substitute areas of conflict. National Partners are requested to consult Core Partners on any major delays, exclusions or substitutions of this sort.

    Sample Design

    The sample design is a clustered, stratified, multi-stage, area probability sample.

    To repeat the main sampling principle, the objective of the design is to give every sample element (i.e. adult citizen) an equal and known chance of being chosen for inclusion in the sample. We strive to reach this objective by (a) strictly applying random selection methods at every stage of sampling and by (b) applying sampling with probability proportionate to population size wherever possible.

    In a series of stages, geographically defined sampling units of decreasing size are selected. To ensure that the sample is representative, the probability of selection at various stages is adjusted as follows:

    The sample is stratified by key social characteristics in the population such as sub-national area (e.g. region/province) and residential locality (urban or rural). The area stratification reduces the likelihood that distinctive ethnic or language groups are left out of the sample. And the urban/rural stratification is a means to make sure that these localities are represented in their correct proportions. Wherever possible, and always in the first stage of sampling, random sampling is conducted with probability proportionate to population size (PPPS). The purpose is to guarantee that larger (i.e., more populated) geographical units have a proportionally greater probability of being chosen into the sample. The sampling design has four stages

    A first-stage to stratify and randomly select primary sampling units;

    A second-stage to randomly select sampling start-points;

    A third stage to randomly choose households;

    A final-stage involving the random selection of individual respondents

    We shall deal with each of these stages in turn.

    STAGE ONE: Selection of Primary Sampling Units (PSUs)

    The primary sampling units (PSU's) are the smallest, well-defined geographic units for which reliable population data are available. In most countries, these will be Census Enumeration Areas (or EAs). Most national census data and maps are broken down to the EA level. In the text that follows we will use the acronyms PSU and EA interchangeably because, when census data are employed, they refer to the same unit.

    We strongly recommend that NIs use official national census data as the sampling frame for Afrobarometer surveys. Where recent or reliable census data are not available, NIs are asked to inform the relevant Core Partner before they substitute any other demographic data. Where the census is out of date, NIs should consult a demographer to obtain the best possible estimates of population growth rates. These should be applied to the outdated census data in order to make projections of population figures for the year of the survey. It is important to bear in mind that population growth rates vary by area (region) and (especially) between rural and urban localities. Therefore, any projected census data should include adjustments to take such variations into account.

    Indeed, we urge NIs to establish collegial working relationships within professionals in the national census bureau, not only to obtain the most recent census data, projections, and maps, but to gain access to sampling expertise. NIs may even commission a census statistician to draw the sample to Afrobarometer specifications, provided that provision for this service has been made in the survey budget.

    Regardless of who draws the sample, the NIs should thoroughly acquaint themselves with the strengths and weaknesses of the available census data and the availability and quality of EA maps. The country and methodology reports should cite the exact census data used, its known shortcomings, if any, and any projections made from the data. At minimum, the NI must know the size of the population and the urban/rural population divide in each region in order to specify how to distribute population and PSU's in the first stage of sampling. National investigators should obtain this written data before they attempt to stratify the sample.

    Once this data is obtained, the sample population (either 1200 or 2400) should be stratified, first by area (region/province) and then by residential locality (urban or rural). In each case, the proportion of the sample in each locality in each region should be the same as its proportion in the national population as indicated by the updated census figures.

    Having stratified the sample, it is then possible to determine how many PSU's should be selected for the country as a whole, for each region, and for each urban or rural locality.

    The total number of PSU's to be selected for the whole country is determined by calculating the maximum degree of clustering of interviews one can accept in any PSU. Because PSUs (which are usually geographically small EAs) tend to be socially homogenous we do not want to select too many people in any one place. Thus, the Afrobarometer has established a standard of no more than 8 interviews per PSU. For a sample size of 1200, the sample must therefore contain 150 PSUs/EAs (1200 divided by 8). For a sample size of 2400, there must be 300 PSUs/EAs.

    These PSUs should then be allocated proportionally to the urban and rural

  10. w

    Household Risk and Vulnerability Survey 2016, Wave 1 - Nepal

    • microdata.worldbank.org
    • catalog.ihsn.org
    Updated Oct 5, 2017
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    Hanan Jacoby (2017). Household Risk and Vulnerability Survey 2016, Wave 1 - Nepal [Dataset]. https://microdata.worldbank.org/index.php/catalog/2905
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    Dataset updated
    Oct 5, 2017
    Dataset provided by
    Thomas Walker
    Hanan Jacoby
    Time period covered
    2016
    Area covered
    Nepal
    Description

    Abstract

    The objective of this three-year panel survey is to provide the Government of Nepal with empirical evidence on the patterns of exposure to shocks at the household level and on the vulnerability of households’ welfare to these shocks. It covers 6,000 households in non-metropolitan areas of Nepal, which were interviewed in mid 2016. Being a relatively comprehensive and representative (rural) sample household survey, it can also be used for other research into living conditions of Nepali households in rural areas. This is the entire dataset for the first wave of the survey. The same households will be reinterviewed in mid 2017 and mid 2018. The survey dataset contains a multi-topic survey which was completed for each of the 6,000 households, and a community survey fielded to a senior community representative at the village development committee (VDC) level in each of the 400 PSUs.

    Geographic coverage

    All non-metropolitan areas in Nepal. Non-metropolitan areas are as defined by the 2010 Census.

    Analysis unit

    Household, following the NLSS definition.

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    The sample frame was all households in non-metropolitan areas per the 2010 Census definition, excluding households in the Kathmandu valley (Kathmandu, Lalitpur and Bhaktapur districts). The country was segmented into 11 analytical strata, defined to correspond to those used in the NLSS III (excluding the three urban strata used there). To increase the concentration of sampled households, 50 of the 75 districts in Nepal were selected with probability proportional to size (the measure of size being the number of households). PSUs were selected with probability proportional to size from the entire list of wards in the 50 selected districts, one stratum at a time. The number of PSUs per stratum is proportional to the stratum's population share, and corresponds closely to the allocations used in the LFS-II and NLSS-III (adjusted for different overall numbers of PSUs in those surveys).

    In each of the selected PSUs (administrative wards), survey teams compiled a list of households in the ward based on existing administrative records, and cross-checked with local leaders. The number of households shown in the list was compared to the ward population in the 2010 Census, adjusted for likely population growth. Where the listed population deviated by more than 10% from the projected population based on the Census data, the team conducted a full listing of households in the ward. 15 households were selected at random from the ward list for interviewing, and a further 5 households were selected as potential replacements.

    Sampling deviation

    During the fieldwork, one PSU in Lapu VDC was inaccessible due to weather, and was replaced by a ward in Hastichaur VDC using PPS sampling on that stratum (excluding the already selected PSUs). All other sampled PSUs were reached, and a full sample of 6,000 households was interviewed in the first wave.

    Mode of data collection

    Computer Assisted Personal Interview [capi]

    Research instrument

    The household questionnaire contained 16 modules: the household roster; education; health; housing and access to facilities; food expenses and home production; non-food expenditures and inventory of durable goods; jobs and time use; wage jobs; farming and livestock; non-agriculture enterprises/activities; migration; credit, savings, and financial assets; private assistance; public assistance; shocks; and anthropometrics (for children less than 5 years). Where possible, the style of questions was kept similar to those used in the NLSS-III questionnaire for comparability reasons. In some cases, new modules needed to be developed. The shocks questionnaire was developed by the World Bank team. A food security module was added based on the design recommended by USAID, and a psychosocial questionnaire was also developed by social development specialists in the World Bank. The section on government and other assistance was also redesigned to cover a broader range of programs and elicit information on details such as experience with enrollment and frequency of payment.

    The community questionnaire was fielded to a senior community representative at the VDC level in each of the 400 PSUs. The purpose of the community questionnaire was to obtain further details on access to services in each PSU, to gather information on shocks at the community level, and to collect market price data. The questionnaire had six modules: respondent details; community characteristics; access to facilities; educational facilities; community shocks, household shocks; and market price.

    Cleaning operations

    These are the raw data entered and checked by the survey firm, formatted to conform to the original questionnaire numbering system and confidentialized. The data were cleaned for spelling errors and translation of Nepali phrases, and suspicious values were checked by calling respondents. No other transformations have taken place.

    Response rate

    Of the 6,000 originally sampled households, 5,191 agreed to be interviewed. Of the 13.5% of households that were not interviewed, 11.1% were resident but could not be located by the team after two attempts, 0.9% were found to have outmigrated, and 1.4% refused. The 809 replacement households were drawn in order from the randomized list created during sampling (see above).

  11. d

    R2 & NE: Tract Level 2006-2010 ACS Place of Birth Summary.

    • datadiscoverystudio.org
    Updated Jan 9, 2018
    + more versions
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    (2018). R2 & NE: Tract Level 2006-2010 ACS Place of Birth Summary. [Dataset]. http://datadiscoverystudio.org/geoportal/rest/metadata/item/b1ee9466cdcd4e128e85ce46a1ea4520/html
    Explore at:
    Dataset updated
    Jan 9, 2018
    Description

    description: The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line File is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Census tracts are small, relatively permanent statistical subdivisions of a county or equivalent entity, and were defined by local participants as part of the 2010 Census Participant Statistical Areas Program. The Census Bureau delineated the census tracts in situations where no local participant existed or where all the potential participants declined to participate. 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.

    This table contains data on the country of birth of foreign born individuals from the American Community Survey 2006-2010 database for tracts. The American Community Survey (ACS) is a household survey conducted by the U.S. Census Bureau that currently has an annual sample size of about 3.5 million addresses. ACS estimates provides communities with the current information they need to plan investments and services. Information from the survey generates estimates that help determine how more than $400 billion in federal and state funds are distributed annually. Each year the survey produces data that cover the periods of 1-year, 3-year, and 5-year estimates for geographic areas in the United States and Puerto Rico, ranging from neighborhoods to Congressional districts to the entire nation. This table also has a companion table (Same table name with MOE Suffix) with the margin of error (MOE) values for each estimated element. MOE is expressed as a measure value for each estimated element. So a value of 25 and an MOE of 5 means 25 +/- 5 (or statistical certainty between 20 and 30). There are also special cases of MOE. An MOE of -1 means the associated estimates do not have a measured error. An MOE of 0 means that error calculation is not appropriate for the associated value. An MOE of 109 is set whenever an estimate value is 0. The MOEs of aggregated elements and percentages must be calculated. This process means using standard error calculations as described in "American Community Survey Multiyear Accuracy of the Data (3-year 2008-2010 and 5-year 2006-2010)". Also, following Census guidelines, aggregated MOEs do not use more than 1 0-element MOE (109) to prevent over estimation of the error. Due to the complexity of the calculations, some percentage MOEs cannot be calculated (these are set to null in the summary-level MOE tables).; abstract: The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line File is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Census tracts are small, relatively permanent statistical subdivisions of a county or equivalent entity, and were defined by local participants as part of the 2010 Census Participant Statistical Areas Program. The Census Bureau delineated the census tracts in situations where no local participant existed or where all the potential participants declined to participate. 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.

    This table contains data on the country of birth of foreign born individuals from the American Community Survey 2006-2010 database for tracts. The American Community Survey (ACS) is a household survey conducted by the U.S. Census Bureau that currently has an annual sample size of about 3.5 million addresses. ACS estimates provides communities with the current information they need to plan investments and services. Information from the survey generates estimates that help determine how more than $400 billion in federal and state funds are distributed annually. Each year the survey produces data that cover the periods of 1-year, 3-year, and 5-year estimates for geographic areas in the United States and Puerto Rico, ranging from neighborhoods to Congressional districts to the entire nation. This table also has a companion table (Same table name with MOE Suffix) with the margin of error (MOE) values for each estimated element. MOE is expressed as a measure value for each estimated element. So a value of 25 and an MOE of 5 means 25 +/- 5 (or statistical certainty between 20 and 30). There are also special cases of MOE. An MOE of -1 means the associated estimates do not have a measured error. An MOE of 0 means that error calculation is not appropriate for the associated value. An MOE of 109 is set whenever an estimate value is 0. The MOEs of aggregated elements and percentages must be calculated. This process means using standard error calculations as described in "American Community Survey Multiyear Accuracy of the Data (3-year 2008-2010 and 5-year 2006-2010)". Also, following Census guidelines, aggregated MOEs do not use more than 1 0-element MOE (109) to prevent over estimation of the error. Due to the complexity of the calculations, some percentage MOEs cannot be calculated (these are set to null in the summary-level MOE tables).

  12. W

    R2 & NE: Tract Level 2006-2010 ACS Languages Spoken Summary

    • cloud.csiss.gmu.edu
    • data.wu.ac.at
    Updated Mar 5, 2021
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    United States (2021). R2 & NE: Tract Level 2006-2010 ACS Languages Spoken Summary [Dataset]. https://cloud.csiss.gmu.edu/uddi/dataset/r2-ne-tract-level-2006-2010-acs-languages-spoken-summary
    Explore at:
    Dataset updated
    Mar 5, 2021
    Dataset provided by
    United States
    Description

    The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line File is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Census tracts are small, relatively permanent statistical subdivisions of a county or equivalent entity, and were defined by local participants as part of the 2010 Census Participant Statistical Areas Program. The Census Bureau delineated the census tracts in situations where no local participant existed or where all the potential participants declined to participate. 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.

    This table contains data on individual languages spoken from the American Community Survey 2006-2010 database for tracts. The American Community Survey (ACS) is a household survey conducted by the U.S. Census Bureau that currently has an annual sample size of about 3.5 million addresses. ACS estimates provides communities with the current information they need to plan investments and services. Information from the survey generates estimates that help determine how more than $400 billion in federal and state funds are distributed annually. Each year the survey produces data that cover the periods of 1-year, 3-year, and 5-year estimates for geographic areas in the United States and Puerto Rico, ranging from neighborhoods to Congressional districts to the entire nation. This table also has a companion table (Same table name with MOE Suffix) with the margin of error (MOE) values for each estimated element. MOE is expressed as a measure value for each estimated element. So a value of 25 and an MOE of 5 means 25 +/- 5 (or statistical certainty between 20 and 30). There are also special cases of MOE. An MOE of -1 means the associated estimates do not have a measured error. An MOE of 0 means that error calculation is not appropriate for the associated value. An MOE of 109 is set whenever an estimate value is 0. The MOEs of aggregated elements and percentages must be calculated. This process means using standard error calculations as described in "American Community Survey Multiyear Accuracy of the Data (3-year 2008-2010 and 5-year 2006-2010)". Also, following Census guidelines, aggregated MOEs do not use more than 1 0-element MOE (109) to prevent over estimation of the error. Due to the complexity of the calculations, some percentage MOEs cannot be calculated (these are set to null in the summary-level MOE tables).

    The name for table 'ACS10LSPTRMOE' was added as a prefix to all field names imported from that table. Be sure to turn off 'Show Field Aliases' to see complete field names in the Attribute Table of this feature layer. This can be done in the 'Table Options' drop-down menu in the Attribute Table or with key sequence '[CTRL]+[SHIFT]+N'. Due to database restrictions, the prefix may have been abbreviated if the field name exceded the maximum allowed characters.

  13. Environmental determinants of fecundity and pup growth in fur seals

    • data.aad.gov.au
    • researchdata.edu.au
    Updated Jun 26, 2001
    + more versions
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    GOLDSWORTHY, SIMON (2001). Environmental determinants of fecundity and pup growth in fur seals [Dataset]. http://doi.org/10.26179/5d2e8725bb2d5
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    Dataset updated
    Jun 26, 2001
    Dataset provided by
    Australian Antarctic Divisionhttps://www.antarctica.gov.au/
    Australian Antarctic Data Centre
    Authors
    GOLDSWORTHY, SIMON
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 1, 1990 - Dec 31, 1999
    Area covered
    Description

    This indicator is no longer maintained, and is considered OBSOLETE.

    INDICATOR DEFINITION The fecundity (pupping rates) of female fur seals and the growth rates of their pups relative to changes in sea surface temperatures (local primary production) in the vicinity of Macquarie Island.

    TYPE OF INDICATOR There are three types of indicators used in this report: 1.Describes the CONDITION of important elements of a system; 2.Show the extent of the major PRESSURES exerted on a system; 3.Determine RESPONSES to either condition or changes in the condition of a system.

    This indicator is one of: CONDITION

    RATIONALE FOR INDICATOR SELECTION A highly negative correlation has been detected between sea surface temperatures in the vicinity of Macquarie Island and fur seal fecundity and pup growth. A dataset of over ten years has shown that autumn sea-surface temperatures are highly negatively correlated with female fecundity in the following breeding season.

    Rather than the reproductive success in terms of fecundity and pup growth being seen simply as a correlate of SST and presumably ocean productivity, the measure is much more than this. What the dataset from the Macquarie Island fur seal populations is rather more unique, in that they indicate how environmental variability effects the reproductive success of animals at annual and lifetime scales. This is especially important as we can now show what impacts environmental/climatic phenomena such as the Antarctic Circumpolar Wave, and global warming will have on fur seals, and how changes in the environment may impact on the viability of populations. In this situation, the data clearly suggest that warmer ocean temperatures significantly effect the reproductive success of fur seals. Sustained warmer temperatures would therefore impose demographic constraints on populations.

    DESIGN AND STRATEGY FOR INDICATOR MONITORING PROGRAM Spatial scale: SST data are obtained from a 1 degree square just north of the island that represents the region in which most females obtain food throughout their lactation period.

    Frequency: Data on the reproductive success of fur seals is to be collected annually.

    Measurement technique: Each breeding season (November-January), the reproductive success of tagged females is monitored, including their pupping success, and the growth rates of their pups.

    RESEARCH ISSUES

    LINKS TO OTHER INDICATORS

  14. d

    R2 & NE: Tract Level 2006-2010 ACS Income Summary.

    • datadiscoverystudio.org
    • data.wu.ac.at
    Updated Jan 13, 2018
    + more versions
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    (2018). R2 & NE: Tract Level 2006-2010 ACS Income Summary. [Dataset]. http://datadiscoverystudio.org/geoportal/rest/metadata/item/83d45d8f71fa467fa31cdb98d680117f/html
    Explore at:
    Dataset updated
    Jan 13, 2018
    Description

    description: The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line File is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Census tracts are small, relatively permanent statistical subdivisions of a county or equivalent entity, and were defined by local participants as part of the 2010 Census Participant Statistical Areas Program. The Census Bureau delineated the census tracts in situations where no local participant existed or where all the potential participants declined to participate. 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.

    This table contains data on household income and poverty status from the American Community Survey 2006-2010 database for tracts. The American Community Survey (ACS) is a household survey conducted by the U.S. Census Bureau that currently has an annual sample size of about 3.5 million addresses. ACS estimates provides communities with the current information they need to plan investments and services. Information from the survey generates estimates that help determine how more than $400 billion in federal and state funds are distributed annually. Each year the survey produces data that cover the periods of 1-year, 3-year, and 5-year estimates for geographic areas in the United States and Puerto Rico, ranging from neighborhoods to Congressional districts to the entire nation. This table also has a companion table (Same table name with MOE Suffix) with the margin of error (MOE) values for each estimated element. MOE is expressed as a measure value for each estimated element. So a value of 25 and an MOE of 5 means 25 +/- 5 (or statistical certainty between 20 and 30). There are also special cases of MOE. An MOE of -1 means the associated estimates do not have a measured error. An MOE of 0 means that error calculation is not appropriate for the associated value. An MOE of 109 is set whenever an estimate value is 0. The MOEs of aggregated elements and percentages must be calculated. This process means using standard error calculations as described in "American Community Survey Multiyear Accuracy of the Data (3-year 2008-2010 and 5-year 2006-2010)". Also, following Census guidelines, aggregated MOEs do not use more than 1 0-element MOE (109) to prevent over estimation of the error. Due to the complexity of the calculations, some percentage MOEs cannot be calculated (these are set to null in the summary-level MOE tables).

    The name for table 'ACS10INCTRMOE' was added as a prefix to all field names imported from that table. Be sure to turn off 'Show Field Aliases' to see complete field names in the Attribute Table of this feature layer. This can be done in the 'Table Options' drop-down menu in the Attribute Table or with key sequence '[CTRL]+[SHIFT]+N'. Due to database restrictions, the prefix may have been abbreviated if the field name exceded the maximum allowed characters.; abstract: The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line File is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Census tracts are small, relatively permanent statistical subdivisions of a county or equivalent entity, and were defined by local participants as part of the 2010 Census Participant Statistical Areas Program. The Census Bureau delineated the census tracts in situations where no local participant existed or where all the potential participants declined to participate. 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.

    This table contains data on household income and poverty status from the American Community Survey 2006-2010 database for tracts. The American Community Survey (ACS) is a household survey conducted by the U.S. Census Bureau that currently has an annual sample size of about 3.5 million addresses. ACS estimates provides communities with the current information they need to plan investments and services. Information from the survey generates estimates that help determine how more than $400 billion in federal and state funds are distributed annually. Each year the survey produces data that cover the periods of 1-year, 3-year, and 5-year estimates for geographic areas in the United States and Puerto Rico, ranging from neighborhoods to Congressional districts to the entire nation. This table also has a companion table (Same table name with MOE Suffix) with the margin of error (MOE) values for each estimated element. MOE is expressed as a measure value for each estimated element. So a value of 25 and an MOE of 5 means 25 +/- 5 (or statistical certainty between 20 and 30). There are also special cases of MOE. An MOE of -1 means the associated estimates do not have a measured error. An MOE of 0 means that error calculation is not appropriate for the associated value. An MOE of 109 is set whenever an estimate value is 0. The MOEs of aggregated elements and percentages must be calculated. This process means using standard error calculations as described in "American Community Survey Multiyear Accuracy of the Data (3-year 2008-2010 and 5-year 2006-2010)". Also,

  15. S

    Meshblock 2025 Clipped

    • datafinder.stats.govt.nz
    csv, dwg, geodatabase +6
    Updated Dec 2, 2024
    + more versions
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    Stats NZ (2024). Meshblock 2025 Clipped [Dataset]. https://datafinder.stats.govt.nz/layer/120976-meshblock-2025-clipped/
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    geodatabase, pdf, kml, csv, geopackage / sqlite, mapinfo mif, shapefile, dwg, mapinfo tabAvailable download formats
    Dataset updated
    Dec 2, 2024
    Dataset provided by
    Statistics New Zealandhttp://www.stats.govt.nz/
    Authors
    Stats NZ
    License

    https://datafinder.stats.govt.nz/license/attribution-4-0-international/https://datafinder.stats.govt.nz/license/attribution-4-0-international/

    Area covered
    Description

    Refer to the current geographies boundaries table for a list of all current geographies and recent updates.

    This dataset is the definitive of the annually released meshblock boundaries as at 1 January 2025 as defined by Stats NZ (the custodian), clipped to the coastline. This clipped version has been created for cartographic purposes and so does not fully represent the official full extent boundaries. This version contains 56,800 meshblocks.

    Stats NZ maintains an annual meshblock pattern for collecting and producing statistical data. This allows data to be compared over time.

    A meshblock is the smallest geographic unit for which statistical data is collected and processed by Stats NZ. A meshblock is a defined geographic area, which can vary in size from part of a city block to a large area of rural land. The optimal size for a meshblock is 30–60 dwellings (containing approximately 60–120 residents).

    Each meshblock borders on another to form a network covering all of New Zealand, including coasts and inlets and extending out to the 200-mile economic zone (EEZ) and is digitised to the 12-mile limit. Meshblocks are added together to build up larger geographic areas such as statistical area 1 (SA1), statistical area 2 (SA2), statistical area 3 (SA3), and urban rural (UR). They are also used to define electoral districts, territorial authorities, and regional councils.

    Meshblock boundaries generally follow road centrelines, cadastral property boundaries, or topographical features such as rivers. Expanses of water in the form of lakes and inlets are defined separately from land.

    Meshblock maintenance

    Meshblock boundaries are amended by:

    1. Splitting – subdividing a meshblock into two or more meshblocks.

    2. Nudging – shifting a boundary to a more appropriate position.

    Reasons for meshblock splits and nudges can include:

    • to maintain meshblock criteria rules.
    • to improve the size balance of meshblocks in areas where there has been population growth
    • to maintain alignment to cadastre and other geographic features.
    • Stats NZ requests for boundary changes so that statistical geography boundaries can be moved
    • external requests for boundary changes so that administrative or electoral boundaries can be moved
    • to separate land and water. Mainland, inland water, islands, inlets, and oceanic are defined separately

    Meshblock changes are made throughout the year. A major release is made at 1 January each year with ad hoc releases available to users at other times.

    While meshblock boundaries are continually under review, 'freezes' on changes to the boundaries are applied periodically. Such 'freezes' are imposed at the time of population censuses and during periods of intense electoral activity, for example, prior and during general and local body elections.

    Meshblock numbering

    Meshblocks are not named and have seven-digit codes.

    When meshblocks are split, each new meshblock is given a new code. The original meshblock codes no longer exist within that version and future versions of the meshblock classification. Meshblock codes do not change when a meshblock boundary is nudged.

    Meshblocks that existed prior to 2015 and have not changed are numbered from 0000100 to 3210003. Meshblocks created from 2015 onwards are numbered from 4000000.

    Digitised and non-digitised meshblocks

    The digital geographic boundaries are defined and maintained by Stats NZ.

    Meshblocks cover the land area of New Zealand, the water area to the 12mile limit, the Chatham Islands, Kermadec Islands, sub-Antarctic islands, offshore oil rigs, and Ross Dependency. The following 16 meshblocks are not held in digitised form.

    Meshblock

    Location (statistical area 2 name)

    • 0016901 /Oceanic Kermadec Islands
    • 0016902 / Kermadec Islands
    • 1588000 / Oceanic Oil Rig Taranaki
    • 3166401 / Oceanic Campbell Island
    • 3166402 / Campbell Island
    • 3166600 / Oceanic Oil Rig Southland
    • 3166710 / Oceanic Auckland Islands
    • 3166711 / Auckland Islands
    • 3195000 / Ross Dependency
    • 3196001 / New Zealand Economic Zone
    • 3196002 / Oceanic Bounty Islands
    • 3196003 / Bounty Islands
    • 3196004 / Oceanic Snares Islands
    • 3196005 / Snares Island
    • 3196006 / Oceanic Antipodes Islands
    • 3196007 / Antipodes Islands

    Clipped Version

    This clipped version has been created for cartographic purposes and so does not fully represent the official full extent boundaries.

    High-definition version

    This high definition (HD) version is the most detailed geometry, suitable for use in GIS for geometric analysis operations and for the computation of areas, centroids and other metrics. The HD version is aligned to the LINZ cadastre.

    Macrons

    Names are provided with and without tohutō/macrons. The column name for those without macrons is suffixed ‘ascii’.

    Digital data

    Digital boundary data became freely available on 1 July 2007.

    Further information

    To download geographic classifications in table formats such as CSV please use Ariā

    For more information please refer to the Statistical standard for geographic areas 2023.

    Contact: geography@stats.govt.nz

  16. Community Development Block Grant Grantee Areas

    • giscommons-countyplanning.opendata.arcgis.com
    • arc-gis-hub-home-arcgishub.hub.arcgis.com
    • +1more
    Updated Jan 12, 2019
    + more versions
    Share
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    Esri U.S. Federal Datasets (2019). Community Development Block Grant Grantee Areas [Dataset]. https://giscommons-countyplanning.opendata.arcgis.com/datasets/fedmaps::community-development-block-grant-grantee-areas
    Explore at:
    Dataset updated
    Jan 12, 2019
    Dataset provided by
    Esrihttp://esri.com/
    Authors
    Esri U.S. Federal Datasets
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Description

    Community Development Block Grant Grantee AreasThis National Geospatial Data Asset (NGDA) dataset, shared as a Department of Housing and Urban Development (HUD) feature layer, displays Community Development Block Grant Grantee Areas. Per HUD, “The Community Development Block Grant (CDBG) program is a flexible program that provides communities with resources to address a wide range of unique community development needs. The CDBG program provides annual grants on a formula basis to local and state governments. The annual CDBG appropriation is allocated between States and local jurisdictions called non-entitlement and entitlement communities respectively. Entitlement communities are comprised of the principal cities of Metropolitan Statistical Areas; metropolitan cities with populations of at least 50,000; and qualified urban counties with a population of 200,000 or more (excluding the populations of entitlement cities). States distribute CDBG funds to non-entitlement localities not qualified as entitlement communities. HUD determines the amount of each grant by using a formula comprised of several measures of community need, including the extent of poverty, population, housing overcrowding, age of housing, and population growth lag in relationship to other metropolitan areas.”Denton, TX (Entitlement Grantee - Metropolitan Cities, Central City), Tarrant, TX (Entitlement Grantee - Urban Counties) & Texas Nonentitlement, TX (State Grantee)Data currency: current federal service (Community Development Block Grant Grantee Areas)NGDAID: 81 (HUD Entitlement Grantee Jurisdiction - National Geospatial Data Asset (NGDA))OGC API Features Link: Not availableFor more information: CDBG: Community Development Block Grant ProgramsSupport Documentation: DD CDBG Grantee Areas (Data Dictionary download)For feedback please contact: Esri_US_Federal_Data@esri.comNGDA Data SetThis data set is part of the NGDA Governmental Units, and Administrative and Statistical Boundaries Theme Community. Per the Federal Geospatial Data Committee (FGDC), this theme is defined as the "boundaries that delineate geographic areas for uses such as governance and the general provision of services (e.g., states, American Indian reservations, counties, cities, towns, etc.), administration and/or for a specific purpose (e.g., congressional districts, school districts, fire districts, Alaska Native Regional Corporations, etc.), and/or provision of statistical data (census tracts, census blocks, metropolitan and micropolitan statistical areas, etc.). Boundaries for these various types of geographic areas are either defined through a documented legal description or through criteria and guidelines. Other boundaries may include international limits, those of federal land ownership, the extent of administrative regions for various federal agencies, as well as the jurisdictional offshore limits of U.S. sovereignty. Boundaries associated solely with natural resources and/or cultural entities are excluded from this theme and are included in the appropriate subject themes." For other NGDA Content: Esri Federal Datasets

  17. w

    R2 & NE: Tract Level 2006-2010 ACS Employment Summary

    • data.wu.ac.at
    tgrshp (compressed)
    Updated Jan 13, 2018
    + more versions
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    U.S. Environmental Protection Agency (2018). R2 & NE: Tract Level 2006-2010 ACS Employment Summary [Dataset]. https://data.wu.ac.at/odso/data_gov/OTFlNDhmN2UtZDY5MS00MTVlLWE5YzItODJlMTUxNGZlNWEz
    Explore at:
    tgrshp (compressed)Available download formats
    Dataset updated
    Jan 13, 2018
    Dataset provided by
    U.S. Environmental Protection Agency
    License

    U.S. Government Workshttps://www.usa.gov/government-works
    License information was derived automatically

    Area covered
    0213f8db6f300fcc466293315bed3556da3a1590
    Description

    The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line File is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Census tracts are small, relatively permanent statistical subdivisions of a county or equivalent entity, and were defined by local participants as part of the 2010 Census Participant Statistical Areas Program. The Census Bureau delineated the census tracts in situations where no local participant existed or where all the potential participants declined to participate. 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.

    This table contains data on employment, commuting time and method, and participation of mothers in the labor force from the American Community Survey 2006-2010 database for states. The American Community Survey (ACS) is a household survey conducted by the U.S. Census Bureau that currently has an annual sample size of about 3.5 million addresses. ACS estimates provides communities with the current information they need to plan investments and services. Information from the survey generates estimates that help determine how more than $400 billion in federal and state funds are distributed annually. Each year the survey produces data that cover the periods of 1-year, 3-year, and 5-year estimates for geographic areas in the United States and Puerto Rico, ranging from neighborhoods to Congressional districts to the entire nation. This table also has a companion table (Same table name with MOE Suffix) with the margin of error (MOE) values for each estimated element. MOE is expressed as a measure value for each estimated element. So a value of 25 and an MOE of 5 means 25 +/- 5 (or statistical certainty between 20 and 30). There are also special cases of MOE. An MOE of -1 means the associated estimates do not have a measured error. An MOE of 0 means that error calculation is not appropriate for the associated value. An MOE of 109 is set whenever an estimate value is 0. The MOEs of aggregated elements and percentages must be calculated. This process means using standard error calculations as described in "American Community Survey Multiyear Accuracy of the Data (3-year 2008-2010 and 5-year 2006-2010)". Also, following Census guidelines, aggregated MOEs do not use more than 1 0-element MOE (109) to prevent over estimation of the error. Due to the complexity of the calculations, some percentage MOEs cannot be calculated (these are set to null in the summary-level MOE tables).

    The name for table 'ACS10EMPTRMOE' was added as a prefix to all field names imported from that table. Be sure to turn off 'Show Field Aliases' to see complete field names in the Attribute Table of this feature layer. This can be done in the 'Table Options' drop-down menu in the Attribute Table or with key sequence '[CTRL]+[SHIFT]+N'. Due to database restrictions, the prefix may have been abbreviated if the field name exceded the maximum allowed characters.

  18. a

    ABS Aboriginal and Torres Strait Islander Peoples (Data by region) SA2...

    • digital.atlas.gov.au
    Updated Dec 11, 2024
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    Digital Atlas of Australia (2024). ABS Aboriginal and Torres Strait Islander Peoples (Data by region) SA2 November 2024 [Dataset]. https://digital.atlas.gov.au/datasets/abs-aboriginal-and-torres-strait-islander-peoples-data-by-region-sa2-november-2024
    Explore at:
    Dataset updated
    Dec 11, 2024
    Dataset authored and provided by
    Digital Atlas of Australia
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Description

    This dataset presents a range of data items sourced from the Australian Bureau of Statistics (ABS). The data is derived from the November 2024 release of Data by region. Individual data items present the latest reference year data available on Data by region. This layer presents data by Statistical Areas Level 2 (SA2), 2021.

    The Aboriginal and Torres Strait Islander Peoples theme is based on groupings of data within Data by region. Concepts, sources and methods for each dataset can be found on the Data by region methodology page.

    Topics in the Aboriginal and Torres Strait Islander Peoples theme include:

    Estimated resident population Language (Census) Engagement in employment, education or training (Census) Labour force status (Census) Unpaid assistance to person with disability (Census) Unpaid childcare (Census) Voluntary work (Census) Tenure type (Census)

    The Closing the Gap topics that are informed by Census data are included in the update:

    Target 5: By 2031, increase the proportion of Aboriginal and Torres Strait Islander people aged 20-24 years attaining Year 12 or an equivalent qualification to 96 per cent. Target 6: By 2031, increase the proportion of Aboriginal and Torres Strait Islander people aged 25-34 years who have completed a tertiary qualification (Certificate III and above) to 70 per cent. Target 7: By 2031, increase the proportion of Aboriginal and Torres Strait Islander youth aged 15-24 years who are in employment, education or training to 67 per cent. Target 8: By 2031, increase the proportion of Aboriginal and Torres Strait Islander people aged 25-64 years who are employed to 62 per cent. Target 9A: By 2031, increase the proportion of Aboriginal and Torres Strait Islander people living in appropriately sized (not overcrowded) housing to 88 per cent.

    When analysing these statistics:

    Time periods, definitions, methodologies, scope, and coverage can differ across collections.
    Some data values have been randomly adjusted or suppressed to avoid the release of confidential data, this means
    
        some small cells have been randomly set to zero
        care should be taken when interpreting cells with small numbers or zeros.
    

    Data and geography references

    Source data publication: Data by region Geographic boundary information: Australian Statistical Geography Standard (ASGS) Edition 3 Further information: Data by region methodology, reference period 2011-24 Source: Australian Bureau of Statistics (ABS)

    Made possible by the Digital Atlas of Australia

    The Digital Atlas of Australia is a key Australian Government initiative being led by Geoscience Australia, highlighted in the Data and Digital Government Strategy. It brings together trusted datasets from across government in an interactive, secure, and easy-to-use geospatial platform. The Australian Bureau of Statistics (ABS) is working in partnership with Geoscience Australia to establish a set of web services to make ABS data available in the Digital Atlas of Australia.

    Contact the Australian Bureau of Statistics

    Email geography@abs.gov.au if you have any questions or feedback about this web service.
    Subscribe to get updates on ABS web services and geospatial products.
    

    Privacy at the Australian Bureau of Statistics Read how the ABS manages personal information - ABS privacy policy.

  19. d

    R2 & NE: Tract Level 2006-2010 ACS Education Summary.

    • datadiscoverystudio.org
    • data.wu.ac.at
    Updated Jan 9, 2018
    + more versions
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    (2018). R2 & NE: Tract Level 2006-2010 ACS Education Summary. [Dataset]. http://datadiscoverystudio.org/geoportal/rest/metadata/item/04a8239a960042b5b4cfa3a2c747cafb/html
    Explore at:
    Dataset updated
    Jan 9, 2018
    Description

    description: The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line File is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Census tracts are small, relatively permanent statistical subdivisions of a county or equivalent entity, and were defined by local participants as part of the 2010 Census Participant Statistical Areas Program. The Census Bureau delineated the census tracts in situations where no local participant existed or where all the potential participants declined to participate. 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.

    This table contains data on educational attainment from the American Community Survey 2006-2010 database for states. The American Community Survey (ACS) is a household survey conducted by the U.S. Census Bureau that currently has an annual sample size of about 3.5 million addresses. ACS estimates provides communities with the current information they need to plan investments and services. Information from the survey generates estimates that help determine how more than $400 billion in federal and state funds are distributed annually. Each year the survey produces data that cover the periods of 1-year, 3-year, and 5-year estimates for geographic areas in the United States and Puerto Rico, ranging from neighborhoods to Congressional districts to the entire nation. This table also has a companion table (Same table name with MOE Suffix) with the margin of error (MOE) values for each estimated element. MOE is expressed as a measure value for each estimated element. So a value of 25 and an MOE of 5 means 25 +/- 5 (or statistical certainty between 20 and 30). There are also special cases of MOE. An MOE of -1 means the associated estimates do not have a measured error. An MOE of 0 means that error calculation is not appropriate for the associated value. An MOE of 109 is set whenever an estimate value is 0. The MOEs of aggregated elements and percentages must be calculated. This process means using standard error calculations as described in "American Community Survey Multiyear Accuracy of the Data (3-year 2008-2010 and 5-year 2006-2010)". Also, following Census guidelines, aggregated MOEs do not use more than 1 0-element MOE (109) to prevent over estimation of the error. Due to the complexity of the calculations, some percentage MOEs cannot be calculated (these are set to null in the summary-level MOE tables).

    The name for table 'ACS10EDUTRMOE' was added as a prefix to all field names imported from that table. Be sure to turn off 'Show Field Aliases' to see complete field names in the Attribute Table of this feature layer. This can be done in the 'Table Options' drop-down menu in the Attribute Table or with key sequence '[CTRL]+[SHIFT]+N'. Due to database restrictions, the prefix may have been abbreviated if the field name exceded the maximum allowed characters.; abstract: The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line File is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Census tracts are small, relatively permanent statistical subdivisions of a county or equivalent entity, and were defined by local participants as part of the 2010 Census Participant Statistical Areas Program. The Census Bureau delineated the census tracts in situations where no local participant existed or where all the potential participants declined to participate. 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.

    This table contains data on educational attainment from the American Community Survey 2006-2010 database for states. The American Community Survey (ACS) is a household survey conducted by the U.S. Census Bureau that currently has an annual sample size of about 3.5 million addresses. ACS estimates provides communities with the current information they need to plan investments and services. Information from the survey generates estimates that help determine how more than $400 billion in federal and state funds are distributed annually. Each year the survey produces data that cover the periods of 1-year, 3-year, and 5-year estimates for geographic areas in the United States and Puerto Rico, ranging from neighborhoods to Congressional districts to the entire nation. This table also has a companion table (Same table name with MOE Suffix) with the margin of error (MOE) values for each estimated element. MOE is expressed as a measure value for each estimated element. So a value of 25 and an MOE of 5 means 25 +/- 5 (or statistical certainty between 20 and 30). There are also special cases of MOE. An MOE of -1 means the associated estimates do not have a measured error. An MOE of 0 means that error calculation is not appropriate for the associated value. An MOE of 109 is set whenever an estimate value is 0. The MOEs of aggregated elements and percentages must be calculated. This process means using standard error calculations as described in "American Community Survey Multiyear Accuracy of the Data (3-year 2008-2010 and 5-year 2006-2010)". Also, following Census guidelines,

  20. w

    R2 & NE: Tract Level 2006-2010 ACS Housing Summary

    • data.wu.ac.at
    • datadiscoverystudio.org
    tgrshp (compressed)
    Updated Jan 13, 2018
    + more versions
    Share
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    U.S. Environmental Protection Agency (2018). R2 & NE: Tract Level 2006-2010 ACS Housing Summary [Dataset]. https://data.wu.ac.at/schema/data_gov/MjcwOTRmYTEtNDg5NS00MTljLTkyNzAtZmJmOGM0ZGE0ZmIx
    Explore at:
    tgrshp (compressed)Available download formats
    Dataset updated
    Jan 13, 2018
    Dataset provided by
    U.S. Environmental Protection Agency
    License

    U.S. Government Workshttps://www.usa.gov/government-works
    License information was derived automatically

    Area covered
    debee69097c2a1eefb5b4129da52a90a4d2087d5
    Description

    The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line File is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Census tracts are small, relatively permanent statistical subdivisions of a county or equivalent entity, and were defined by local participants as part of the 2010 Census Participant Statistical Areas Program. The Census Bureau delineated the census tracts in situations where no local participant existed or where all the potential participants declined to participate. 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.

    This table contains housing data, including building age, value and/or rent, length of occupation, number of units, home heating type, and number of vehicles from the American Community Survey 2006-2010 database for tracts. The American Community Survey (ACS) is a household survey conducted by the U.S. Census Bureau that currently has an annual sample size of about 3.5 million addresses. ACS estimates provides communities with the current information they need to plan investments and services. Information from the survey generates estimates that help determine how more than $400 billion in federal and state funds are distributed annually. Each year the survey produces data that cover the periods of 1-year, 3-year, and 5-year estimates for geographic areas in the United States and Puerto Rico, ranging from neighborhoods to Congressional districts to the entire nation. This table also has a companion table (Same table name with MOE Suffix) with the margin of error (MOE) values for each estimated element. MOE is expressed as a measure value for each estimated element. So a value of 25 and an MOE of 5 means 25 +/- 5 (or statistical certainty between 20 and 30). There are also special cases of MOE. An MOE of -1 means the associated estimates do not have a measured error. An MOE of 0 means that error calculation is not appropriate for the associated value. An MOE of 109 is set whenever an estimate value is 0. The MOEs of aggregated elements and percentages must be calculated. This process means using standard error calculations as described in "American Community Survey Multiyear Accuracy of the Data (3-year 2008-2010 and 5-year 2006-2010)". Also, following Census guidelines, aggregated MOEs do not use more than 1 0-element MOE (109) to prevent over estimation of the error. Due to the complexity of the calculations, some percentage MOEs cannot be calculated (these are set to null in the summary-level MOE tables).

Share
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Link copied
Close
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NSGIC Local Govt | GIS Inventory (2017). Demographic Data - TIGER/Line Shapefile, 2010, 2010 county, Miami-Dade County, FL, 2010 Census Census Tract County-based [Dataset]. https://data.wu.ac.at/schema/data_gov/MzFiNWVlZTgtZThlMS00ZjE5LTg3YzEtZDczMjVmMmYzMTBj

Demographic Data - TIGER/Line Shapefile, 2010, 2010 county, Miami-Dade County, FL, 2010 Census Census Tract County-based

Explore at:
xmlAvailable download formats
Dataset updated
Aug 19, 2017
Dataset provided by
NSGIC Local Govt | GIS Inventory
Area covered
e542f162cd008c18420b5022876ee15bab71f11e
Description

The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line File is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Census tracts are small, relatively permanent statistical subdivisions of a county or equivalent entity, and were defined by local participants as part of the 2010 Census Participant Statistical Areas Program. The Census Bureau delineated the census tracts in situations where no local participant existed or where all the potential participants declined to participate. 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. This census data layer has been imported into the Miami-Dade County ArcSDE infrastructure and re-projected to: Projected Coordinate System: NAD_1983_StatePlane_Florida_East_FIPS_0901_Feet Projection: Transverse_Mercator False_Easting: 656166.66666667 False_Northing: 0.00000000 Central_Meridian: -81.00000000 Scale_Factor: 0.99994118 Latitude_Of_Origin: 24.33333333 Linear Unit: Foot_US The boundaries have been aligned to Miami-Dade County base data where they have been found to NOT be within +/- 10 ft Population figures have been appended to the end of the feature classes attribute table: Pop2010, HU2010, HISPAN, WHITENH, BLACKNH, AMERINDIANNH, ASIANNH, HAWIANNH, OTHERNH, and MULTIRACE. Definitions can be found in the census documentation.

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