100+ datasets found
  1. d

    Community Survey: 2021 Random Sample Results

    • catalog.data.gov
    • data.bloomington.in.gov
    • +1more
    Updated May 20, 2023
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    data.bloomington.in.gov (2023). Community Survey: 2021 Random Sample Results [Dataset]. https://catalog.data.gov/dataset/community-survey-2021-random-sample-results-69942
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    Dataset updated
    May 20, 2023
    Dataset provided by
    data.bloomington.in.gov
    Description

    A random sample of households were invited to participate in this survey. In the dataset, you will find the respondent level data in each row with the questions in each column. The numbers represent a scale option from the survey, such as 1=Excellent, 2=Good, 3=Fair, 4=Poor. The question stem, response option, and scale information for each field can be found in the var "variable labels" and "value labels" sheets. VERY IMPORTANT NOTE: The scientific survey data were weighted, meaning that the demographic profile of respondents was compared to the demographic profile of adults in Bloomington from US Census data. Statistical adjustments were made to bring the respondent profile into balance with the population profile. This means that some records were given more "weight" and some records were given less weight. The weights that were applied are found in the field "wt". If you do not apply these weights, you will not obtain the same results as can be found in the report delivered to the Bloomington. The easiest way to replicate these results is likely to create pivot tables, and use the sum of the "wt" field rather than a count of responses.

  2. Financial Literacy and Financial Services Survey 2011 - Bosnia and...

    • microdata.unhcr.org
    • catalog.ihsn.org
    • +3more
    Updated May 19, 2021
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    IPSOS (2021). Financial Literacy and Financial Services Survey 2011 - Bosnia and Herzegovina [Dataset]. https://microdata.unhcr.org/index.php/catalog/396
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    Dataset updated
    May 19, 2021
    Dataset authored and provided by
    IPSOShttp://www.ipsos.com/
    Time period covered
    2011
    Area covered
    Bosnia and Herzegovina
    Description

    Abstract

    The survey on financial literacy among the citizens of Bosnia and Herzegovina was conducted within a larger project that aims at creating the Action Plan for Consumer Protection in Financial Services.

    The conclusion about the need for an Action Plan was reached by the representatives of the World Bank, the Federal Ministry of Finance, the Central Bank of Bosnia and Herzegovina, supervisory authorities for entity financial institutions and non-governmental organizations for the protection of consumer rights, based on the Diagnostic Review on Consumer Protection and Financial Literacy in Bosnia and Herzegovina conducted by the World Bank in 2009-2010. This diagnostic review was conducted at the request of the Federal Ministry of Finance, as part of a larger World Bank pilot program to assess consumer protection and financial literacy in developing countries and middle-income countries. The diagnostic review in Bosnia and Herzegovina was the eighth within this project.

    The financial literacy survey, whose results are presented in this report, aims at establishing the basic situation with respect to financial literacy, serving on the one hand as a preparation for the educational activities plan, and on the other as a basis for measuring the efficiency of activities undertaken.

    Geographic coverage

    Data collection was based on a random, nation-wide sample of citizens of Bosnia and Herzegovina aged 18 or older (N = 1036).

    Analysis unit

    Household, individual

    Universe

    Population aged 18 or older

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    SUMMARY

    In Bosnia and Herzegovina, as is well known, there is no completely reliable sample frame or information about universe. The main reasons for such a situation are migrations caused by war and lack of recent census data. The last census dates back to 1991, but since then the size and distribution of population has significantly changed. In such a situation, researchers have to combine all available sources of population data to estimate the present size and structure of the population: estimates by official statistical offices and international organizations, voters? lists, list of polling stations, registries of passport and ID holders, data from large random surveys etc.

    The sample was three-stage stratified: in the first stage by entity, in the second by county/region and in the third by type of settlement (urban/rural). This means that, in the first stage, the total sample size was divided in two parts proportionally to number of inhabitants by entity, while in the second stage the subsample size for each entity was further divided by regions/counties. In the third stage, the subsample for each region/county was divided in two categories according to settlement type (rural/urban).

    Taking into the account the lack of a reliable and complete list of citizens to be used as a sample frame, a multistage sampling method was applied. The list of polling stations was used as a frame for the selection of primary sampling units (PSU). Polling station territories are a good choice for such a procedure since they have been recently updated, for the general elections held in October 2010. The list of polling station territories contains a list of addresses of housing units that are certainly occupied.

    In the second stage, households were used as a secondary sampling unit. Households were selected randomly by a random route technique. In total, 104 PSU were selected with an average of 10 respondents per PSU. The respondent from the selected household was selected randomly using the Trohdal-Bryant scheme.

    In total, 1036 citizens were interviewed with a satisfactory response rate of around 60% (table 1). A higher refusal rate is recorded among middle-age groups (table 2). The theoretical margin of error for a random sample of this size is +/-3.0%.

    Due to refusals, the sample structure deviated from the estimated population structure by gender, age and education level. Deviations were corrected by RIM weighting procedure.

    MORE DETAILED INFORMATION

    IPSOS designed a representative sample of approximately 1.000 residents age 18 and over, proportional to the adult populations of each region, based on age, sex, region and town (settlement) type.

    For this research we designed three-stage stratified representative sample. First we stratify sample at entity level, regional level and then at settlement type level for each region.

    Sample universe:

    Population of B&H -18+; 1991 Census figures and estimated population dynamics, census figures of refugees and IDPs, 1996. Central Election Commision - 2008; CIPS - 2008;

    Sampling frame:

    Polling stations territory (approximate size of census units) within strata defined by regions and type of settlements (urban and rural) Polling stations territories are chosen to be used as primary units because it enables the most reliable sample selection, due to the fact that for these units the most complete data are available (dwelling register - addresses)

    Type of sample:

    Three stage random representative stratified sample

    Definition and number of PSU, SSU, TSU, and sampling points

    • PSU - Polling station territory Definition: Polling stations territories are defined by street(s) name(s) and dwelling numbers; each polling station territory comprises approximately 300 households, with exception of the settlements with less than 300 HH which are defined as one unite. Number of PSUs in sample universe: 4710
    • SSU - Household Definition: One household comprises people living in the same apartment and sharing the expenditure for food
    • TSU - Respondent Definition: Member of the HH , 18+ Number of TSUs in sample universe: = 2.966.766
    • Sampling points Approximately 10 respondents per one PSU, total 104

    Stratification, purpose and method

    • First level strata: Federation of B&H Republika Srpska Brc ko District
    • Second level strata: 10 cantons 2 regions -
    • Third level strata: urban and rural settlements
    • Purpose: Optimisation of the sample plan, and reducing the sampling error
    • Method: The strata are defined by criteria of optimal geographical and cultural uniformity

    • Selection procedure of PSU, SSU, and respondent Stratification, purpose and method

    • PSU Type of sampling of the PSU: Polling station territory chosen with probability proportional to size (PPS) Method of selection: Cumulative (Lachirie method)

    • SSU Type of sampling of the SSU: Sample random sampling without replacement Method of selection: Random walk - Random choice of the starting point

    • TSU - Respondent Type of sampling of respondent: Sample random sampling without replacement Method of selection: TCB (Trohdal-Bryant scheme)

    • Sample size N=1036 respondents

    • Sampling error Marginal error +/-3.0%

    Mode of data collection

    Face-to-face [f2f]

    Research instrument

    The survey was modelled after the identical survey conducted in Romania. The questionnaire used in the Financial Literacy Survey in Romania was localized for Bosnia and Herzegovina, including adaptations to match the Bosnian context and methodological improvements in wording of questions.

    Cleaning operations

    Before data entry, 100% logic and consistency controls are performed first by local supervisors and once later by staff in central office.

    Verification of correct data entry is assured by using BLAISE system for data entry (commercial product of Netherlands statistics), where criteria for logical and consistency control are defined in advance.

    Response rate

    • Nobody at home: 2,8%
    • Eligible person is not home: 2,8%
    • Refusal : 32,79%
    • Given up after a minimum of two visits: 0,82%
    • Other (excluded after control): 0,29%
    • Finished: 60,5%
  3. d

    National Coral Reef Monitoring Program: Stratified Random Surveys (StRS) of...

    • catalog.data.gov
    • s.cnmilf.com
    • +2more
    Updated Feb 1, 2025
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    (Point of Contact) (2025). National Coral Reef Monitoring Program: Stratified Random Surveys (StRS) of Coral Demography (Adult and Juvenile Corals) across the Mariana Archipelago from 2022-05-10 to 2022-06-01 (NCEI Accession 0279491) [Dataset]. https://catalog.data.gov/dataset/national-coral-reef-monitoring-program-stratified-random-surveys-strs-of-coral-demography-adult5
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    Dataset updated
    Feb 1, 2025
    Dataset provided by
    (Point of Contact)
    Area covered
    Mariana Islands
    Description

    The data described here result from benthic coral demographic surveys for two life stages (juveniles, adults) across the Mariana archipelago from 2022-05-10 to 2022-06-01. Juvenile colony surveys include morphology and size. Adult colony surveys record morphology, colony size, partial mortality in two categories - old dead and recent dead, cause of recent dead partial mortality, and non-lesion forming condition (including bleaching and disease). Observations were repeated for internal review, and are denoted with TRANSECTNUM = 2 and REPEAT_SEGMENT_YN = -1. When using observation data for analyses, filter for TRANSECTNUM = 1. A two-stage stratified random sampling (StRS) design was employed to survey the coral reef ecosystems throughout the U.S. Pacific regions. The survey domain encompassed the majority of the mapped area of reef and hard bottom habitats in the 0-30 m depth range. The stratification scheme included island, reef zone, and depth in all regions, as well as habitat structure type in the Main Hawaiian Islands. Sampling effort was allocated based on strata area and sites were randomly located within strata. Sites were surveyed using belt transects to collect juvenile and adult coral colony metrics. These data provide information on juvenile and adult coral abundance (density, proportion occurrence, and total colony abundance), size distribution, partial mortality, prevalence and abundance of recent mortality and cause, prevalence of disease and bleaching, and diversity. The StRS design effectively reduces estimate variance through stratification using environmental covariates and by sampling more sites rather than sampling more transects at a site. Therefore, site-level estimates and site to site comparisons should be used with caution.

  4. c

    National Coral Reef Monitoring Program: Stratified random surveys (StRS) of...

    • s.cnmilf.com
    • cmr.earthdata.nasa.gov
    • +2more
    Updated Feb 1, 2025
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    (Point of Contact) (2025). National Coral Reef Monitoring Program: Stratified random surveys (StRS) of coral demography (adult and juvenile corals) across the Pacific Remote Island Areas [Dataset]. https://s.cnmilf.com/user74170196/https/catalog.data.gov/dataset/national-coral-reef-monitoring-program-stratified-random-surveys-strs-of-coral-demography-adult3
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    Dataset updated
    Feb 1, 2025
    Dataset provided by
    (Point of Contact)
    Description

    Data provided in this collection were gathered around the Pacific Remote Island Areas as part of the ongoing National Coral Reef Monitoring Program (NCRMP) by the NOAA National Marine Fisheries Service (NMFS), Coral Reef Ecosystem Program in the Pacific. The data described here result from benthic coral demographic surveys for two life stages (juveniles, adults) across the Pacific Remote Island Areas. A two-stage stratified random sampling (StRS) design was employed to survey the coral reef ecosystems around the Pacific Remote Island Areas. Sampling effort was allocated based on strata area, and sites were randomly located within strata. The StRS design effectively reduces estimate variance through stratification using environmental covariates and by sampling more sites rather than sampling more transects at a site. Therefore, site-level estimates and site to site comparisons should be used with caution. Sites were surveyed using belt transects to collect juvenile and adult coral colony metrics. These data provide information on juvenile and adult coral abundance (density, proportion occurrence, and total colony abundance), size distribution, partial mortality, prevalence and abundance of recent mortality and cause, prevalence of disease and bleaching, and diversity.

  5. c

    City of Tempe 2023 Community Survey Data

    • s.cnmilf.com
    • performance.tempe.gov
    • +10more
    Updated Apr 12, 2024
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    City of Tempe (2024). City of Tempe 2023 Community Survey Data [Dataset]. https://s.cnmilf.com/user74170196/https/catalog.data.gov/dataset/city-of-tempe-2023-community-survey-data
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    Dataset updated
    Apr 12, 2024
    Dataset provided by
    City of Tempe
    Area covered
    Tempe
    Description

    These data include the individual responses for the City of Tempe Annual Community Survey conducted by ETC Institute. This dataset has two layers and includes both the weighted data and unweighted data. Weighting data is a statistical method in which datasets are adjusted through calculations in order to more accurately represent the population being studied. The weighted data are used in the final published PDF report.These data help determine priorities for the community as part of the City's on-going strategic planning process. Averaged Community Survey results are used as indicators for several city performance measures. The summary data for each performance measure is provided as an open dataset for that measure (separate from this dataset). The performance measures with indicators from the survey include the following (as of 2023):1. Safe and Secure Communities1.04 Fire Services Satisfaction1.06 Crime Reporting1.07 Police Services Satisfaction1.09 Victim of Crime1.10 Worry About Being a Victim1.11 Feeling Safe in City Facilities1.23 Feeling of Safety in Parks2. Strong Community Connections2.02 Customer Service Satisfaction2.04 City Website Satisfaction2.05 Online Services Satisfaction Rate2.15 Feeling Invited to Participate in City Decisions2.21 Satisfaction with Availability of City Information3. Quality of Life3.16 City Recreation, Arts, and Cultural Centers3.17 Community Services Programs3.19 Value of Special Events3.23 Right of Way Landscape Maintenance3.36 Quality of City Services4. Sustainable Growth & DevelopmentNo Performance Measures in this category presently relate directly to the Community Survey5. Financial Stability & VitalityNo Performance Measures in this category presently relate directly to the Community SurveyMethods:The survey is mailed to a random sample of households in the City of Tempe. Follow up emails and texts are also sent to encourage participation. A link to the survey is provided with each communication. To prevent people who do not live in Tempe or who were not selected as part of the random sample from completing the survey, everyone who completed the survey was required to provide their address. These addresses were then matched to those used for the random representative sample. If the respondent’s address did not match, the response was not used. To better understand how services are being delivered across the city, individual results were mapped to determine overall distribution across the city. Additionally, demographic data were used to monitor the distribution of responses to ensure the responding population of each survey is representative of city population. Processing and Limitations:The _location data in this dataset is generalized to the block level to protect privacy. This means that only the first two digits of an address are used to map the _location. When they data are shared with the city only the latitude/longitude of the block level address points are provided. This results in points that overlap. In order to better visualize the data, overlapping points were randomly dispersed to remove overlap. The result of these two adjustments ensure that they are not related to a specific address, but are still close enough to allow insights about service delivery in different areas of the city. The weighted data are used by the ETC Institute, in the final published PDF report.The 2023 Annual Community Survey report is available on data.tempe.gov or by visiting https://www.tempe.gov/government/strategic-management-and-innovation/signature-surveys-research-and-dataThe individual survey questions as well as the definition of the response scale (for example, 1 means “very dissatisfied” and 5 means “very satisfied”) are provided in the data dictionary.Additional InformationSource: Community Attitude SurveyContact (author): Adam SamuelsContact E-Mail (author): Adam_Samuels@tempe.govContact (maintainer): Contact E-Mail (maintainer): Data Source Type: Excel tablePreparation Method: Data received from vendor after report is completedPublish Frequency: AnnualPublish Method: ManualData Dictionary

  6. c

    National Coral Reef Monitoring Program: Stratified random surveys (StRS) of...

    • s.cnmilf.com
    • datasets.ai
    • +2more
    Updated Feb 1, 2025
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    (Point of Contact) (2025). National Coral Reef Monitoring Program: Stratified random surveys (StRS) of reef fish, including benthic estimate data of the Hawaiian Archipelago [Dataset]. https://s.cnmilf.com/user74170196/https/catalog.data.gov/dataset/national-coral-reef-monitoring-program-stratified-random-surveys-strs-of-reef-fish-including-be8
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    Dataset updated
    Feb 1, 2025
    Dataset provided by
    (Point of Contact)
    Area covered
    Hawaii, Hawaiian Islands
    Description

    Reef fish survey data provided in this collection are gathered as part of the NOAA Pacific Islands Fisheries Science Center (PIFSC), Coral Reef Ecosystem Program (CREP) led National Coral Reef Monitoring Program missions around the Hawaiian Archipelago. The stationary point count (SPC) method is used to conduct reef fish surveys in the Hawaiian Archipelago as part of the ongoing NOAA National Coral Reef Monitoring Program (NCRMP). The SPC method used to gather these data catalogs the diversity (species richness), abundance (numeric density) and biomass (fish mass per unit area) of diurnally active reef fish assemblages in shallow-water (less than 30 m) hard-bottom habitats. Visual estimates of benthic cover and topographic complexity are also recorded within this collection, with benthic organisms grouped into broad functional categories (e.g., 'Hard Coral', 'Macroalgae'). A stratified random sampling (StRS) design is employed to survey the coral reef ecosystems throughout the region. The survey _domain encompasses the majority of the mapped area of reef and hard bottom habitats and the stratification includes island, reef zone, habitat structure type, and depth. Sampling effort is allocated based on strata area.

  7. World Bank Enterprise Survey 2023 - Gambia

    • datacatalog.ihsn.org
    • catalog.ihsn.org
    • +1more
    Updated Jan 10, 2025
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    World Bank Group (WBG) (2025). World Bank Enterprise Survey 2023 - Gambia [Dataset]. https://datacatalog.ihsn.org/catalog/12650
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    Dataset updated
    Jan 10, 2025
    Dataset provided by
    World Bank Grouphttp://www.worldbank.org/
    World Bankhttp://worldbank.org/
    Authors
    World Bank Group (WBG)
    Time period covered
    2023
    Area covered
    The Gambia
    Description

    Abstract

    The World Bank Enterprise Survey (WBES) is a firm-level survey of a representative sample of an economy's private sector. The surveys cover a broad range of topics related to the business environment including access to finance, corruption, infrastructure, competition, and performance.

    Geographic coverage

    National coverage

    Analysis unit

    The primary sampling unit of the study is the establishment. An establishment is a physical location where business is carried out and where industrial operations take place or services are provided. A firm may be composed of one or more establishments. For example, a brewery may have several bottling plants and several establishments for distribution. For the purposes of this survey an establishment must make its own financial decisions and have its own financial statements separate from those of the firm. An establishment must also have its own management and control over its payroll.

    Universe

    The universe of inference includes all formal (i.e., registered) private sector businesses (with at least 1% private ownership) and with at least five employees. In terms of sectoral criteria, all manufacturing businesses (ISIC Rev 4. codes 10-33) are eligible; for services businesses, those corresponding to the ISIC Rev 4 codes 41-43, 45-47, 49-53, 55-56, 58, 61-62, 69-75, 79, and 95 are included in the Enterprise Surveys. Cooperatives and collectives are excluded from the Enterprise Surveys. All eligible establishments must be registered with the registration agency. In the case of Gambia, registration was with the Gambia Revenue Authority.

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    The WBES use stratified random sampling, where the population of establishments is first separated into non-overlapping groups, called strata, and then respondents are selected through simple random sampling from each stratum. The detailed methodology is provided in the Sampling Note (https://www.enterprisesurveys.org/content/dam/enterprisesurveys/documents/methodology/Sampling_Note-Consolidated-2-16-22.pdf). Stratified random sampling has several advantages over simple random sampling. In particular, it:

    • produces unbiased estimates of the whole population or universe of inference, as well as at the levels of stratification
    • ensures representativeness by including observations in all of those categories
    • produces more precise estimates for a given sample size or budget allocation, and
    • may reduce implementation costs by splitting the population into convenient subdivisions.

    The WBES typically use three levels of stratification: industry classification, establishment size, and subnational region (used in combination). Starting in 2022, the WBES bases the industry classification on ISIC Rev. 4 (with earlier surveys using ISIC Rev. 3.1). For regional coverage within a country, the WBES has national coverage.

    Note: Refer to Sampling Structure section in "The Gambia 2023 World Bank Enterprise Survey Implementation Report" for detailed methodology on sampling.

    Mode of data collection

    Face-to-face [f2f]

    Research instrument

    The standard WBES questionnaire covers several topics regarding the business environment and business performance. These topics include general firm characteristics, infrastructure, sales and supplies, management practices, competition, innovation, capacity, land and permits, finance, business-government relations, exposure to bribery, labor, and performance. Information about the general structure of the questionnaire is available in the Enterprise Surveys Manual and Guide (https://www.enterprisesurveys.org/content/dam/enterprisesurveys/documents/methodology/Enterprise-Surveys-Manual-and-Guide.pdf).

    The questionnaire implemented in the Gambia 2023 WBES included additional questions tailored for the Business Ready Report covering infrastructure, trade, government regulations, finance, labor, and other topics.

    Response rate

    Overall survey response rate was 67.8%.

  8. d

    National Coral Reef Monitoring Program: Stratified Random Surveys (StRS) of...

    • catalog.data.gov
    • s.cnmilf.com
    • +1more
    Updated Feb 7, 2025
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    (Point of Contact, Custodian) (2025). National Coral Reef Monitoring Program: Stratified Random Surveys (StRS) of Reef Fish, including Benthic Estimate Data of the Hawaiian Archipelago since 2013 [Dataset]. https://catalog.data.gov/dataset/national-coral-reef-monitoring-program-stratified-random-surveys-strs-of-reef-fish-includi-20133
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    Dataset updated
    Feb 7, 2025
    Dataset provided by
    (Point of Contact, Custodian)
    Area covered
    Hawaii, Hawaiian Islands
    Description

    The stationary point count (SPC) method is used to conduct reef fish surveys in the Hawaiian and Mariana Archipelagos, American Samoa, and the Pacific Remote Island Areas as part of the NOAA National Coral Reef Monitoring Program (NCRMP). The SPC method catalogs the diversity (species richness), abundance (numeric density) and biomass (fish mass per unit area) of diurnally active reef fish assemblages in shallow-water (less than 30 m) hard-bottom habitats. Visual estimates of benthic cover and topographic complexity are also recorded, with benthic organisms grouped into broad functional categories (e.g., 'Hard Coral', 'Macroalgae'). A stratified random sampling (StRS) design is employed to survey the coral reef ecosystems throughout the U.S.-Pacific regions. For all regions, the survey domain encompasses the majority of the mapped area of reef and hard bottom habitats and the stratification includes island, reef zone, and depth, with the exception of the Main Hawaiian Islands that includes habitat structure type as well. Sampling effort is allocated based on strata area. Reef fish and benthic estimate data provided in this data set were collected during SPC surveys as part of the NOAA Pacific Islands Fisheries Science Center (PIFSC), Ecosystem Sciences Division (formerly the Coral Reef Ecosystem Division) led NCRMP missions around the Main Hawaiian Islands in 2013, 2016, and 2019, 2024 and the Northwestern Hawaiian Islands in 2016 & 2024. Data collected as part of PapahÄ naumokuÄ kea Marine National Monument funded research cruises in the Northwestern Hawaiian Islands in 2014, 2015, and 2017 are also included as these data are funded separately from but are complementary to the NCRMP-funded data. Additionally, data collected as part of a PIFSC-funded Reef Fish Survey cruise in the Main Hawaiian Islands in 2015 are included as these data are funded separately from but are complementary to the NCRMP-funded data. During the 2015 and cruise, some sites were surveyed using both open-circuit SCUBA (OC) and closed-circuit rebreather (CCR), as part of an ongoing assessment of sources of bias in survey count relating to divers' presence. The CCR data is archived separately.

  9. V

    Resident Survey 2024 Demographics

    • data.virginia.gov
    • data.norfolk.gov
    csv, json, rdf, xsl
    Updated Sep 24, 2024
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    City of Norfolk (2024). Resident Survey 2024 Demographics [Dataset]. https://data.virginia.gov/bs/dataset/groups/resident-survey-2024-demographics
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    json, xsl, csv, rdfAvailable download formats
    Dataset updated
    Sep 24, 2024
    Dataset provided by
    data.norfolk.gov
    Authors
    City of Norfolk
    Description

    The City of Norfolk is committed to using data to inform decisions and allocate resources. An important source of data is input from residents about their priorities and satisfaction with the services we provide. Norfolk last conducted a citywide survey of residents in 2022.

    To provide up-to-date information regarding resident priorities and satisfaction, Norfolk contracted with ETC Institute to conduct a survey of residents. This survey was conducted in May and June 2024; surveys were sent via the U.S. Postal Service, and respondents were given the choice of responding by mail or online. This survey represents a random and statistically valid sample of residents from across the city, including each Ward. ETC Institute monitored responses and followed up to ensure all sections of the city were represented. Additionally, an opportunity was provided for residents not included in the random sample to take the survey and express their views. This dataset includes all random sample survey data including demographic information; it excludes free-form comments to protect privacy. It is grouped by Question Category, Question, Response, Demographic Question, and Demographic Question Response. This dataset will be updated every two years.

  10. Results Monitoring Survey (RMS) - 2022 - South Sudan

    • microdata.unhcr.org
    Updated Mar 18, 2025
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    UNHCR (2025). Results Monitoring Survey (RMS) - 2022 - South Sudan [Dataset]. https://microdata.unhcr.org/index.php/catalog/1063
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    Dataset updated
    Mar 18, 2025
    Dataset provided by
    United Nations High Commissioner for Refugeeshttp://www.unhcr.org/
    Authors
    UNHCR
    Time period covered
    2022 - 2023
    Area covered
    South Sudan
    Description

    Abstract

    The Results-Monitoring Survey (RMS) was conducted by UNHCR South Sudan in the last quarter of 2022 to serve as a pilot tool for measuring country operations' results regarding internally displaced persons (IDPs). Using computer-assisted personal interviews, around 4,634 questionnaires were carried out proportionally across eight states. The target was IDPs in camps and non-camp settings, including hard-to-reach areas. A simple random sampling method was used to allow generalizability and minimize bias. The questionnaire was tailored to the local context while drawing from the standard RMS instrument. Sample sizes were calculated for states and counties based on displacement figures and partner presence. A 95% confidence level and 5% margin of error determined the state samples. The county samples used 90% confidence and 5% margins given the need for greater precision at lower administrative levels. Total target was 5,309 households, allocated proportionally. High response rate (97%) exceeded targets in some counties. The pilot provides baseline data on results indicators to track over time. Key aspects were representative sampling, localized questionnaire, sufficient sample size, and community access enabling quality data for ongoing monitoring.

    Geographic coverage

    Central Equatoria, Eastern Equatoria, Jonglei, Northern Bahr el Ghazal, Unity, Upper Nile, Warrap, Western Equatoria

    Analysis unit

    Household

    Universe

    Internally Displaced Persons (IDPs): The focus was on IDPs both in camps and out of camps, including deep field and hard-to-reach locations across eight states of South Sudan.

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    The sampling procedure for the 2022 South Sudan Results Monitoring Survey by UNHCR involved a simple random sampling approach within a probability sampling framework, ensuring impartiality and representativeness. This method facilitated the generalization of findings to the broader population of internally displaced persons (IDPs) in South Sudan.

    Mode of data collection

    Computer Assisted Personal Interview [capi]

    Research instrument

    Income, food consumption, expenditures, assets, community relations, wellbeing, resilience, mental health, health, accommodation, protection, and education

  11. d

    National Coral Reef Monitoring Program: Stratified random surveys (StRS) of...

    • catalog.data.gov
    • gimi9.com
    • +4more
    Updated Feb 1, 2025
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    (Point of Contact) (2025). National Coral Reef Monitoring Program: Stratified random surveys (StRS) of coral demography (adult and juvenile corals) across the Hawaiian Archipelago [Dataset]. https://catalog.data.gov/dataset/national-coral-reef-monitoring-program-stratified-random-surveys-strs-of-coral-demography-adult
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    Dataset updated
    Feb 1, 2025
    Dataset provided by
    (Point of Contact)
    Area covered
    Hawaii, Hawaiian Islands
    Description

    Data provided in this collection were gathered around Hawaii as part of the ongoing National Coral Reef Monitoring Program (NCRMP) by the NOAA National Marine Fisheries Service (NMFS), Coral Reef Ecosystem Program in the Pacific. The data described here result from benthic coral demographic surveys for two life stages (juveniles, adults) across Hawaii. A two-stage stratified random sampling (StRS) design was employed to survey the coral reef ecosystems around Hawaii. Sampling effort was allocated based on strata area, and sites were randomly located within strata. The StRS design effectively reduces estimate variance through stratification using environmental covariates and by sampling more sites rather than sampling more transects at a site. Therefore, site-level estimates and site to site comparisons should be used with caution. Sites were surveyed using belt transects to collect juvenile and adult coral colony metrics. These data provide information on juvenile and adult coral abundance (density, proportion occurrence, and total colony abundance), size distribution, partial mortality, prevalence and abundance of recent mortality and cause, prevalence of disease and bleaching, and diversity.

  12. Results Monitoring Survey, 2023 Q2 - Peru

    • microdata.unhcr.org
    Updated Dec 5, 2024
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    UNHCR (2024). Results Monitoring Survey, 2023 Q2 - Peru [Dataset]. https://microdata.unhcr.org/index.php/catalog/960
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    Dataset updated
    Dec 5, 2024
    Dataset provided by
    United Nations High Commissioner for Refugeeshttp://www.unhcr.org/
    Authors
    UNHCR
    Time period covered
    2023
    Area covered
    Peru
    Description

    Abstract

    The UNHCR Results Monitoring Surveys (RMS) is a household-level survey on people with and for whom UNHCR works or who benefit from direct or indirect assistance provided by UNHCR, including refugees and asylum seekers, internally displaced persons, returnees, stateless and others of concern. The objective of the survey is to monitor impact and outcome level indicators on education, healthcare, livelihoods, protection concerns, shelter, and water and sanitation. The results contribute to an evidence base for reporting against UNHCR's multi-year strategies to key stakeholders. This RMS took place in Peru from April 2023 to May 2023 at national level.

    Analysis unit

    Household and individual

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    The survey used two different modalities: phone and in-person interviews. The phone survey covered a total of 1,000 households with members registered in proGres during the 6 months prior to data collection, with simple random sampling. Additionally, the operation carried out 200 face-to-face interviews, also with random sampling, in 4 areas of the city of Trujillo, department of La Libertad, where a high presence of Venezuelan population was identified, particularly economically active persons.

    Mode of data collection

    Computer Assisted Personal Interview [capi]

    Research instrument

    The questionnaire contained the following sections: Survey Information , Socio-economic Indicators & Mobility, Information on the well-being of the household, Habitable and affordable housing, Habitable housing and access to basic services, Health Services and Social Protection, Perceptions on safety and gender-based violence.

  13. World Bank Enterprise Survey 2024 - Ireland

    • microdata.worldbank.org
    Updated Mar 18, 2025
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    World Bank Group (WBG) (2025). World Bank Enterprise Survey 2024 - Ireland [Dataset]. https://microdata.worldbank.org/index.php/catalog/6526
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    Dataset updated
    Mar 18, 2025
    Dataset provided by
    World Bank Grouphttp://www.worldbank.org/
    World Bankhttp://worldbank.org/
    Authors
    World Bank Group (WBG)
    Time period covered
    2024
    Area covered
    Ireland
    Description

    Abstract

    The World Bank Enterprise Survey (WBES) is a firm-level survey of a representative sample of an economy's private sector. The surveys cover a broad range of topics related to the business environment including access to finance, corruption, infrastructure, competition, and performance.

    Geographic coverage

    National

    Analysis unit

    The primary sampling unit of the study is the establishment. An establishment is a physical location where business is carried out and where industrial operations take place or services are provided. A firm may be composed of one or more establishments. For example, a brewery may have several bottling plants and several establishments for distribution. For the purposes of this survey an establishment must make its own financial decisions and have its own financial statements separate from those of the firm. An establishment must also have its own management and control over its payroll.

    Universe

    All formal (i.e., registered) private sector businesses (with at least 1% private ownership) and with at least five employees. In terms of sectoral criteria, all manufacturing businesses (ISIC Rev 4. codes 10-33) are eligible; for services businesses, those corresponding to the ISIC Rev 4 codes 41-43, 45-47, 49-53, 55-56, 58, 61-62, 69-75, 79, and 95 are included in the Enterprise Surveys. Cooperatives and collectives are excluded from the Enterprise Surveys. All eligible establishments must be registered with the registration agency. In the case of Ireland, a firm was classified as registered if recorded in the Companies Registration Office.

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    The WBES use stratified random sampling, where the population of establishments is first separated into non-overlapping groups, called strata, and then respondents are selected through simple random sampling from each stratum. The detailed methodology is provided in the Sampling Note (https://www.enterprisesurveys.org/content/dam/enterprisesurveys/documents/methodology/Sampling_Note-Consolidated-2-16-22.pdf). Stratified random sampling has several advantages over simple random sampling. In particular, it:

    • produces unbiased estimates of the whole population or universe of inference, as well as at the levels of stratification
    • ensures representativeness by including observations in all of those categories
    • produces more precise estimates for a given sample size or budget allocation, and
    • may reduce implementation costs by splitting the population into convenient subdivisions.

    The WBES typically use three levels of stratification: industry classification, establishment size, and subnational region (used in combination). Starting in 2022, the WBES bases the industry classification on ISIC Rev. 4 (with earlier surveys using ISIC Rev. 3.1). For regional coverage within a country, the WBES has national coverage.

    Note: Refer to Sampling Structure section in "The Ireland 2024 World Bank Enterprise Survey Implementation Report" for detailed methodology on sampling.

    Mode of data collection

    Face-to-face [f2f]

    Research instrument

    The standard WBES questionnaire covers several topics regarding the business environment and business performance. These topics include general firm characteristics, infrastructure, sales and supplies, trade, management practices, competition, innovation, capacity, land and permits, finance, business-government relations, exposure to bribery, labor, and performance. Information about the general structure of the questionnaire is available in the Enterprise Surveys Manual and Guide (https://www.enterprisesurveys.org/content/dam/enterprisesurveys/documents/methodology/Enterprise-Surveys-Manual-and-Guide.pdf).

    Response rate

    Overall survey response rate was 9.9%.

  14. Afrobarometer Survey 2020 - Gabon

    • microdata.worldbank.org
    Updated Nov 2, 2022
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    Afrobarometer Survey 2020 - Gabon [Dataset]. https://microdata.worldbank.org/index.php/catalog/4746
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    Dataset updated
    Nov 2, 2022
    Dataset provided by
    Institute for Justice and Reconciliationhttp://www.ijr.org.za/
    Ghana Centre for Democratic Development (CDD)
    University of Cape Town (UCT, South Africa)
    Institute for Development Studies (IDS)
    Institute for Empirical Research in Political Economy (IREEP)
    Michigan State University (MSU)
    Time period covered
    2020
    Area covered
    Gabon
    Description

    Abstract

    The Afrobarometer is a comparative series of public attitude surveys that assess African citizen's attitudes to democracy and governance, markets, and civil society, among other topics. The surveys have been undertaken at periodic intervals since 1999. The Afrobarometer's coverage has increased over time. Round 1 (1999-2001) initially covered 7 countries and was later extended to 12 countries. Round 2 (2002-2004) surveyed citizens in 16 countries. Round 3 (2005-2006) 18 countries, Round 4 (2008) 20 countries, Round 5 (2011-2013) 34 countries, Round 6 (2014-2015) 36 countries, and Round 7 (2016-2018) 34 countries. The survey covered 34 countries in Round 8 (2019-2021).

    Geographic coverage

    National coverage

    Analysis unit

    Individual

    Universe

    Citizens aged 18 years and above excluding those living in institutionalized buildings.

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    Afrobarometer uses national probability samples designed to meet the following criteria. Samples are designed to generate a sample that is 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 being selected for an interview. They achieve this by:

    • using random selection methods at every stage of sampling; • sampling at all stages with probability proportionate to population size wherever possible to ensure that larger (i.e., more populated) geographic units have a proportionally greater probability of being chosen into the sample.

    The sampling universe normally includes all citizens age 18 and older. As a standard practice, we exclude people living in institutionalized settings, such as students in dormitories, patients in hospitals, and persons in prisons or nursing homes. Occasionally, we must also exclude people living in areas determined to be inaccessible due to conflict or insecurity. Any such exclusion is noted in the technical information report (TIR) that accompanies each data set.

    Sample size and design Samples usually include either 1,200 or 2,400 cases. A randomly selected sample of n=1200 cases allows inferences to national adult populations with a margin of sampling error of no more than +/-2.8% with a confidence level of 95 percent. With a sample size of n=2400, the margin of error decreases to +/-2.0% at 95 percent confidence level.

    The sample design is a clustered, stratified, multi-stage, area probability sample. Specifically, we first stratify the sample according to the main sub-national unit of government (state, province, region, etc.) and by urban or rural location.

    Area stratification reduces the likelihood that distinctive ethnic or language groups are left out of the sample. Afrobarometer occasionally purposely oversamples certain populations that are politically significant within a country to ensure that the size of the sub-sample is large enough to be analysed. Any oversamples is noted in the TIR.

    Sample stages Samples are drawn in either four or five stages:

    Stage 1: In rural areas only, the first stage is to draw secondary sampling units (SSUs). SSUs are not used in urban areas, and in some countries they are not used in rural areas. See the TIR that accompanies each data set for specific details on the sample in any given country. Stage 2: We randomly select primary sampling units (PSU). Stage 3: We then randomly select sampling start points. Stage 4: Interviewers then randomly select households. Stage 5: Within the household, the interviewer randomly selects an individual respondent. Each interviewer alternates in each household between interviewing a man and interviewing a woman to ensure gender balance in the sample.

    To keep the costs and logistics of fieldwork within manageable limits, eight interviews are clustered within each selected PSU.

    Gabon - Sample size: 1,200 - Sampling Frame: Recensement Général de la Population et des Logements (RGPL) de 2013 réalisée par la Direction Générale de la Statistique et des Etudes Economiques - Sample design: Representative, random, clustered, stratified, multi-stage area probability sample - Stratification: Province, Department, and urban-rural location - Stages: Primary sampling unit (PSU), start points, households, respondents - PSU selection: Probability Proportionate to Population Size (PPPS) - Cluster size: 8 households per PSU - Household selection: Randomly selected start points, followed by walk pattern using 5/10 interval - Respondent selection: Gender quota to be achieved by alternating interviews between men and women; potential respondents (i.e. household members) of the appropriate gender are listed, then the computer chooses the individual random

    Mode of data collection

    Face-to-face [f2f]

    Research instrument

    The Round 8 questionnaire has been developed by the Questionnaire Committee after reviewing the findings and feedback obtained in previous Rounds, and securing input on preferred new topics from a host of donors, analysts, and users of the data.

    The questionnaire consists of three parts: 1. Part 1 captures the steps for selecting households and respondents, and includes the introduction to the respondent and (pp.1-4). This section should be filled in by the Fieldworker. 2. Part 2 covers the core attitudinal and demographic questions that are asked by the Fieldworker and answered by the Respondent (Q1 – Q100). 3. Part 3 includes contextual questions about the setting and atmosphere of the interview, and collects information on the Fieldworker. This section is completed by the Fieldworker (Q101 – Q123).

    Response rate

    Outcome rates: - Contact rate: 99% - Cooperation rate: 92% - Refusal rate: 3% - Response rate: 91%

    Sampling error estimates

    +/- 3% at 95% confidence level

  15. V

    Resident Survey 2022

    • data.virginia.gov
    • data.norfolk.gov
    url
    Updated May 2, 2024
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    City of Norfolk (2024). Resident Survey 2022 [Dataset]. https://data.virginia.gov/dataset/resident-survey-2022
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    urlAvailable download formats
    Dataset updated
    May 2, 2024
    Dataset authored and provided by
    City of Norfolk
    Description

    The City of Norfolk is committed to using data to help inform decisions and allocate resources. One important source of data is input from residents about their priorities and satisfaction with the services we provide. Norfolk last conducted a citywide survey of residents in 2014.

    To provide up-to-date information regarding resident priorities and satisfaction, Norfolk contracted with ETC institute to conduct a survey of residents. This survey was conducted in the fall of 2022; surveys were sent via the U.S. Postal Service and respondents were given the choice of responding by mail, online, or by telephone. This survey represents a random and statistically valid sample of residents from across the city. ETC Institute monitored responses and followed up to ensure all sections of the city were represented. An opportunity was also provided for residents not included in the random sample to take the survey and express their views. This dataset includes all survey data, excluding demographic data to protect privacy. This dataset will be updated every two years.

    For data about this dataset, please click on the below link: https://data.norfolk.gov/Government/Resident-Survey-2022/qure-5p8r/about_data

  16. Household Survey on Information and Communications Technology, 2014 - West...

    • pcbs.gov.ps
    Updated Jan 28, 2020
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    Palestinian Central Bureau of statistics (2020). Household Survey on Information and Communications Technology, 2014 - West Bank and Gaza [Dataset]. https://www.pcbs.gov.ps/PCBS-Metadata-en-v5.2/index.php/catalog/465
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    Dataset updated
    Jan 28, 2020
    Dataset provided by
    Palestinian Central Bureau of Statisticshttp://pcbs.gov.ps/
    Authors
    Palestinian Central Bureau of statistics
    Time period covered
    2014
    Area covered
    Gaza, Gaza Strip, West Bank
    Description

    Abstract

    Within the frame of PCBS' efforts in providing official Palestinian statistics in the different life aspects of Palestinian society and because the wide spread of Computer, Internet and Mobile Phone among the Palestinian people, and the important role they may play in spreading knowledge and culture and contribution in formulating the public opinion, PCBS conducted the Household Survey on Information and Communications Technology, 2014.

    The main objective of this survey is to provide statistical data on Information and Communication Technology in the Palestine in addition to providing data on the following: -

    · Prevalence of computers and access to the Internet. · Study the penetration and purpose of Technology use.

    Geographic coverage

    Palestine (West Bank and Gaza Strip) , type of locality (Urban, Rural, Refugee Camps) and governorate

    Analysis unit

    Household. Person 10 years and over .

    Universe

    All Palestinian households and individuals whose usual place of residence in Palestine with focus on persons aged 10 years and over in year 2014.

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    Sampling Frame The sampling frame consists of a list of enumeration areas adopted in the Population, Housing and Establishments Census of 2007. Each enumeration area has an average size of about 124 households. These were used in the first phase as Preliminary Sampling Units in the process of selecting the survey sample.

    Sample Size The total sample size of the survey was 7,268 households, of which 6,000 responded.

    Sample Design The sample is a stratified clustered systematic random sample. The design comprised three phases:

    Phase I: Random sample of 240 enumeration areas. Phase II: Selection of 25 households from each enumeration area selected in phase one using systematic random selection. Phase III: Selection of an individual (10 years or more) in the field from the selected households; KISH TABLES were used to ensure indiscriminate selection.

    Sample Strata Distribution of the sample was stratified by: 1- Governorate (16 governorates, J1). 2- Type of locality (urban, rural and camps).

    Sampling deviation

    -

    Mode of data collection

    Face-to-face [f2f]

    Research instrument

    The survey questionnaire consists of identification data, quality controls and three main sections: Section I: Data on household members that include identification fields, the characteristics of household members (demographic and social) such as the relationship of individuals to the head of household, sex, date of birth and age.

    Section II: Household data include information regarding computer processing, access to the Internet, and possession of various media and computer equipment. This section includes information on topics related to the use of computer and Internet, as well as supervision by households of their children (5-17 years old) while using the computer and Internet, and protective measures taken by the household in the home.

    Section III: Data on persons (aged 10 years and over) about computer use, access to the Internet and possession of a mobile phone.

    Cleaning operations

    Preparation of Data Entry Program: This stage included preparation of the data entry programs using an ACCESS package and defining data entry control rules to avoid errors, plus validation inquiries to examine the data after it had been captured electronically.

    Data Entry: The data entry process started on 8 May 2014 and ended on 23 June 2014. The data entry took place at the main PCBS office and in field offices using 28 data clerks.

    Editing and Cleaning procedures: Several measures were taken to avoid non-sampling errors. These included editing of questionnaires before data entry to check field errors, using a data entry application that does not allow mistakes during the process of data entry, and then examining the data by using frequency and cross tables. This ensured that data were error free; cleaning and inspection of the anomalous values were conducted to ensure harmony between the different questions on the questionnaire.

    Response rate

    Response Rates= 79%

    Sampling error estimates

    There are many aspects of the concept of data quality; this includes the initial planning of the survey to the dissemination of the results and how well users understand and use the data. There are three components to the quality of statistics: accuracy, comparability, and quality control procedures.

    Checks on data accuracy cover many aspects of the survey and include statistical errors due to the use of a sample, non-statistical errors resulting from field workers or survey tools, and response rates and their effect on estimations. This section includes:

    Statistical Errors Data of this survey may be affected by statistical errors due to the use of a sample and not a complete enumeration. Therefore, certain differences can be expected in comparison with the real values obtained through censuses. Variances were calculated for the most important indicators.

    Variance calculations revealed that there is no problem in disseminating results nationally or regionally (the West Bank, Gaza Strip), but some indicators show high variance by governorate, as noted in the tables of the main report.

    Non-Statistical Errors Non-statistical errors are possible at all stages of the project, during data collection or processing. These are referred to as non-response errors, response errors, interviewing errors and data entry errors. To avoid errors and reduce their effects, strenuous efforts were made to train the field workers intensively. They were trained on how to carry out the interview, what to discuss and what to avoid, and practical and theoretical training took place during the training course. Training manuals were provided for each section of the questionnaire, along with practical exercises in class and instructions on how to approach respondents to reduce refused cases. Data entry staff were trained on the data entry program, which was tested before starting the data entry process.

    Several measures were taken to avoid non-sampling errors. These included editing of questionnaires before data entry to check field errors, using a data entry application that does not allow mistakes during the process of data entry, and then examining the data by using frequency and cross tables. This ensured that data were error free; cleaning and inspection of the anomalous values were conducted to ensure harmony between the different questions on the questionnaire.

    The sources of non-statistical errors can be summarized as: 1. Some of the households were not at home and could not be interviewed, and some households refused to be interviewed. 2. In unique cases, errors occurred due to the way the questions were asked by interviewers and respondents misunderstood some of the questions.

  17. National Coral Reef Monitoring Program: Stratified random surveys (StRS) of...

    • accession.nodc.noaa.gov
    • s.cnmilf.com
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    Updated Apr 3, 2024
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    NOAA Pacific Islands Fisheries Science Center, Ecosystem Sciences Division (2024). National Coral Reef Monitoring Program: Stratified random surveys (StRS) of reef fish, including benthic estimate data of the Pacific Remote Island Areas [Dataset]. http://doi.org/10.7289/v58c9tkb
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    htmlAvailable download formats
    Dataset updated
    Apr 3, 2024
    Dataset provided by
    National Marine Fisheries Servicehttps://www.fisheries.noaa.gov/
    United States Department of Commercehttp://www.commerce.gov/
    National Centers for Environmental Informationhttps://www.ncei.noaa.gov/
    National Oceanic and Atmospheric Administrationhttp://www.noaa.gov/
    Authors
    NOAA Pacific Islands Fisheries Science Center, Ecosystem Sciences Division
    Time period covered
    Mar 16, 2014 - Present
    Area covered
    Pacific Ocean, United States, PRIA, Pacific Ocean, Pacific Ocean, Pacific Ocean, Pacific Ocean, Pacific Ocean, Pacific Ocean, United States
    Description

    Reef fish survey data provided in this collection were gathered as part of the NOAA Pacific Islands Fisheries Science Center (PIFSC), Coral Reef Ecosystem Program (CREP) led National Coral Reef Monitoring Program missions around the Pacific Remote Island Areas.

    The stationary point count (SPC) method is used to conduct reef fish surveys in the Pacific Remote Island Areas as part of the ongoing NOAA National Coral Reef Monitoring Program (NCRMP). The SPC method used to gather these data catalogs the diversity (species richness), abundance (numeric density) and biomass (fish mass per unit area) of diurnally active reef fish assemblages in shallow-water (less than 30 m) hard-bottom habitats. Visual estimates of benthic cover and topographic complexity are also recorded within this collection, with benthic organisms grouped into broad functional categories (e.g., 'Hard Coral', 'Macroalgae'). A stratified random sampling (StRS) design is employed to survey the coral reef ecosystems throughout the region. The survey domain encompasses the majority of the mapped area of reef and hard bottom habitats and the stratification includes island, reef zone, and depth. Sampling effort is allocated based on strata area.

  18. d

    Somerville Happiness Survey Responses

    • catalog.data.gov
    • data.somervillema.gov
    • +2more
    Updated Feb 7, 2025
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    data.somervillema.gov (2025). Somerville Happiness Survey Responses [Dataset]. https://catalog.data.gov/dataset/somerville-happiness-survey-responses-4fe50
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    Dataset updated
    Feb 7, 2025
    Dataset provided by
    data.somervillema.gov
    Description

    Every two years, the City of Somerville sends the Somerville Happiness Survey to a random sample of Somerville residents. The survey asks residents to rate their personal happiness, wellbeing, and satisfaction with City services. This combined dataset includes random-sample survey results from 2011 to 2023, including all 2023 questions with applicable responses from previous years. A data dictionary, exploratory visualization, and survey instruments are attached.

  19. d

    National Coral Reef Monitoring Program: Stratified Random Surveys (StRS) of...

    • catalog.data.gov
    Updated Oct 19, 2024
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    (Point of Contact, Custodian) (2024). National Coral Reef Monitoring Program: Stratified Random Surveys (StRS) of Coral Demography (Adult and Juvenile Corals) across the Hawaiian Archipelago since 2013 [Dataset]. https://catalog.data.gov/dataset/national-coral-reef-monitoring-program-stratified-random-surveys-strs-of-coral-demography-20132
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    Dataset updated
    Oct 19, 2024
    Dataset provided by
    (Point of Contact, Custodian)
    Area covered
    Hawaii, Hawaiian Islands
    Description

    The data described here result from benthic coral demographic surveys within belt transects of specified length and width for two life stages (juveniles and adults) across the Hawaiian archipelago since 2013. The data provide information on adult coral colony counts, morphology, size, partial mortality (old and recent dead), presence and causation of disease and other compromised health conditions, including bleaching. Juvenile colony surveys include morphology and size. Taxonomic identification of adult colonies is to the species level and genus level for juveniles. A two-stage stratified random sampling (StRS) design was employed to survey the coral reef ecosystems of the Hawaiian archipelago in 2013, 2016, and 2017 and starting in 2019 a one-stage StRS design was employed. The survey domain encompassed the majority of the mapped area of reef and hard bottom habitats in the 0–30 m depth range. The stratification scheme included island, reef zone, and depth (i.e., shallow: >0–6 m; mid-depth: >6–18 m; and deep: >18–30 m), habitat structure type, as well as reef zone (i.e., forereef, backreef, lagoon, and protected slope; the latter three only in the Northwestern Hawaiian Islands). Sampling effort allocation was determined based on strata area and sites randomly located within strata. The StRS design effectively reduces estimate variance through stratification using environmental covariates and by sampling more sites rather than more transects per site. Therefore, site-level estimates and site-to-site comparisons should proceed with caution. The data were collected as part of the NOAA Pacific Islands Fisheries Science Center (PIFSC) and Ecosystem Sciences Division (ESD; formerly the Coral Reef Ecosystem Division) led National Coral Reef Monitoring Program (NCRMP) missions around the Main Hawaiian Islands in 2013, 2016 and 2019, and the Northwestern Hawaiian Islands in 2016. Data collected as part of the 2014 and 2015 PapahĠnaumokuĠkea Marine National Monument funded research cruises in the Northwestern Hawaiian Islands are also included. The latter are funded separately but are complementary to the ESD NCRMP-funded data.

  20. General Social Survey Panel Data (2016-2020)

    • thearda.com
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    The Association of Religion Data Archives, General Social Survey Panel Data (2016-2020) [Dataset]. http://doi.org/10.17605/OSF.IO/HACZV
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    Dataset provided by
    Association of Religion Data Archives
    Dataset funded by
    National Science Foundation
    Description

    The General Social Surveys (GSS) have been conducted by the "https://www.norc.org/Pages/default.aspx" Target="_blank">National Opinion Research Center (NORC) annually since 1972, except for the years 1979, 1981, and 1992 (a supplement was added in 1992), and biennially beginning in 1994. The GSS are designed to be part of a program of social indicator research, replicating questionnaire items and wording in order to facilitate time-trend studies. The 2016-2020 GSS consisted of re-interviews of respondents from the 2016 and 2018 Cross-Sectional GSS rounds. All respondents from 2018 were fielded, but a random subsample of the respondents from 2016 were released for the 2020 panel. Cross-sectional responses from 2016 and 2018 are labelled Waves 1A and 1B, respectively, while responses from the 2020 re-interviews are labelled Wave 2.

    The 2016-2020 GSS Wave 2 Panel also includes a collaboration between the General Social Survey (GSS) and the "https://electionstudies.org/" Target="_blank">American National Election Studies (ANES). The 2016-2020 GSS Panel Wave 2 contained a module of items proposed by the ANES team, including attitudinal questions, feelings thermometers for presidential candidates, and plans for voting in the 2020 presidential election. These respondents appear in both the ANES post-election study and the 2016-2020 GSS panel, with their 2020 GSS responses serving as their equivalent pre-election data. Researchers can link the relevant GSS Panel Wave 2 data with ANES post-election data using either ANESID (in the GSS Panel Wave 2 datafile) or V200001 in the ANES 2020 post-election datafile.

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data.bloomington.in.gov (2023). Community Survey: 2021 Random Sample Results [Dataset]. https://catalog.data.gov/dataset/community-survey-2021-random-sample-results-69942

Community Survey: 2021 Random Sample Results

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Dataset updated
May 20, 2023
Dataset provided by
data.bloomington.in.gov
Description

A random sample of households were invited to participate in this survey. In the dataset, you will find the respondent level data in each row with the questions in each column. The numbers represent a scale option from the survey, such as 1=Excellent, 2=Good, 3=Fair, 4=Poor. The question stem, response option, and scale information for each field can be found in the var "variable labels" and "value labels" sheets. VERY IMPORTANT NOTE: The scientific survey data were weighted, meaning that the demographic profile of respondents was compared to the demographic profile of adults in Bloomington from US Census data. Statistical adjustments were made to bring the respondent profile into balance with the population profile. This means that some records were given more "weight" and some records were given less weight. The weights that were applied are found in the field "wt". If you do not apply these weights, you will not obtain the same results as can be found in the report delivered to the Bloomington. The easiest way to replicate these results is likely to create pivot tables, and use the sum of the "wt" field rather than a count of responses.

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