34 datasets found
  1. Share of U.S. e-mail users 2023, by ethnicity

    • statista.com
    Updated Sep 11, 2024
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    Statista (2024). Share of U.S. e-mail users 2023, by ethnicity [Dataset]. https://www.statista.com/statistics/628376/us-email-usage-reach-by-ethnicity/
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    Dataset updated
    Sep 11, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Nov 2023
    Area covered
    United States
    Description

    In November 2023, over 91 percent of the African American digital population accessed emails. By comparison, approximately 93.8 percent of the white population had access and used this form of online communication, while 93.7 percent of Asian Americans in the country did the same as of the last measured period.

  2. Share of U.S. e-mail users 2023, by age group

    • statista.com
    Updated Sep 11, 2024
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    Statista (2024). Share of U.S. e-mail users 2023, by age group [Dataset]. https://www.statista.com/statistics/271501/us-email-usage-reach-by-age/
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    Dataset updated
    Sep 11, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Nov 2023
    Area covered
    United States
    Description

    In November 2023, 95 percent of internet users aged between 25 and 44 years in the United States reported using emails. Email usage interested over 93 percent of the country's population aged between 15 and 24 years, while around 86.5 percent of internet users aged 65 and above reported using this communication method.

  3. d

    ACS 5-Year Economic Characteristics DC Census Tract

    • opdatahub.dc.gov
    • opendata.dc.gov
    • +3more
    Updated Feb 28, 2025
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    City of Washington, DC (2025). ACS 5-Year Economic Characteristics DC Census Tract [Dataset]. https://opdatahub.dc.gov/datasets/a53c0f02804a484b87027ce3ef3ff38b
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    Dataset updated
    Feb 28, 2025
    Dataset authored and provided by
    City of Washington, DC
    License

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

    Area covered
    Description

    Employment, Commuting, Occupation, Income, Health Insurance, Poverty, and more. This service is updated annually with American Community Survey (ACS) 5-year data. Contact: District of Columbia, Office of Planning. Email: planning@dc.gov. Geography: Census Tracts. Current Vintage: 2019-2023. ACS Table(s): DP03. Data downloaded from: Census Bureau's API for American Community Survey. Date of API call: January 2, 2025. National Figures: data.census.gov. Please cite the Census and ACS when using this data. Data Note from the Census: Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables. Data Processing Notes: This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Boundaries come from the US Census TIGER geodatabases. Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines clipped for cartographic purposes. For census tracts, the water cutouts are derived from a subset of the 2020 AWATER (Area Water) boundaries offered by TIGER. For state and county boundaries, the water and coastlines are derived from the coastlines of the 500k TIGER Cartographic Boundary Shapefiles. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters). Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page. Data processed using R statistical package and ArcGIS Desktop. Margin of Error was not included in this layer but is available from the Census Bureau. Contact the Office of Planning for more information about obtaining Margin of Error values.

  4. Indicators of Reduced Access to Care Due to the Coronavirus Pandemic During...

    • catalog.data.gov
    • healthdata.gov
    • +2more
    Updated Feb 4, 2025
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    Centers for Disease Control and Prevention (2025). Indicators of Reduced Access to Care Due to the Coronavirus Pandemic During Last 4 Weeks [Dataset]. https://catalog.data.gov/dataset/indicators-of-reduced-access-to-care-due-to-the-coronavirus-pandemic-during-last-4-weeks
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    Dataset updated
    Feb 4, 2025
    Dataset provided by
    Centers for Disease Control and Preventionhttp://www.cdc.gov/
    Description

    The U.S. Census Bureau, in collaboration with five federal agencies, launched the Household Pulse Survey to produce data on the social and economic impacts of Covid-19 on American households. The Household Pulse Survey was designed to gauge the impact of the pandemic on employment status, consumer spending, food security, housing, education disruptions, and dimensions of physical and mental wellness. The survey was designed to meet the goal of accurate and timely weekly estimates. It was conducted by an internet questionnaire, with invitations to participate sent by email and text message. The sample frame is the Census Bureau Master Address File Data. Housing units linked to one or more email addresses or cell phone numbers were randomly selected to participate, and one respondent from each housing unit was selected to respond for him or herself. Estimates are weighted to adjust for nonresponse and to match Census Bureau estimates of the population by age, sex, race and ethnicity, and educational attainment. All estimates shown meet the NCHS Data Presentation Standards for Proportions.

  5. w

    census.masters@gmail.com - Reverse Whois Lookup

    • whoisdatacenter.com
    csv
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    AllHeart Web Inc, census.masters@gmail.com - Reverse Whois Lookup [Dataset]. https://whoisdatacenter.com/email/census.masters@gmail.com/
    Explore at:
    csvAvailable download formats
    Dataset authored and provided by
    AllHeart Web Inc
    License

    https://whoisdatacenter.com/terms-of-use/https://whoisdatacenter.com/terms-of-use/

    Time period covered
    Mar 15, 1985 - Mar 20, 2025
    Description

    Explore historical ownership and registration records by performing a reverse Whois lookup for the email address census.masters@gmail.com..

  6. c

    ACS 5-Year Demographic Characteristics DC Census Tract

    • s.cnmilf.com
    • datasets.ai
    • +1more
    Updated Feb 4, 2025
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    City of Washington, DC (2025). ACS 5-Year Demographic Characteristics DC Census Tract [Dataset]. https://s.cnmilf.com/user74170196/https/catalog.data.gov/dataset/acs-5-year-demographic-characteristics-dc-census-tract
    Explore at:
    Dataset updated
    Feb 4, 2025
    Dataset provided by
    City of Washington, DC
    Area covered
    Washington
    Description

    Age, Sex, Race, Ethnicity, Total Housing Units, and Voting Age Population. This service is updated annually with American Community Survey (ACS) 5-year data. Contact: District of Columbia, Office of Planning. Email: planning@dc.gov. Geography: Census Tracts. Current Vintage: 2018-2022. ACS Table(s): DP05. Data downloaded from: Census Bureau's API for American Community Survey. Date of API call: January 2, 2024. National Figures: data.census.gov. Please cite the Census and ACS when using this data. Data Note from the Census: Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables. Data Processing Notes: This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Boundaries come from the US Census TIGER geodatabases. Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines clipped for cartographic purposes. For census tracts, the water cutouts are derived from a subset of the 2020 AWATER (Area Water) boundaries offered by TIGER. For state and county boundaries, the water and coastlines are derived from the coastlines of the 500k TIGER Cartographic Boundary Shapefiles. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters). Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page. Data processed using R statistical package and ArcGIS Desktop. Margin of Error was not included in this layer but is available from the Census Bureau. Contact the Office of Planning for more information about obtaining Margin of Error values.

  7. d

    ACS 5-Year Housing Characteristics DC Census Tract

    • catalog.data.gov
    • hub.arcgis.com
    Updated Feb 4, 2025
    + more versions
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    City of Washington, DC (2025). ACS 5-Year Housing Characteristics DC Census Tract [Dataset]. https://catalog.data.gov/dataset/acs-5-year-housing-characteristics-dc-census-tract
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    Dataset updated
    Feb 4, 2025
    Dataset provided by
    City of Washington, DC
    Area covered
    Washington
    Description

    Occupancy status, Units, Rooms, Year built, Owner/Renter (Tenure), Mortgage/Rent costs, and more. This service is updated annually with American Community Survey (ACS) 5-year data. Contact: District of Columbia, Office of Planning. Email: planning@dc.gov. Geography: Census Tracts. Current Vintage: 2018-2022. ACS Table(s): DP04. Data downloaded from: Census Bureau's API for American Community Survey. Date of API call: January 2, 2024. National Figures: data.census.gov. Please cite the Census and ACS when using this data. Data Note from the Census: Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables. Data Processing Notes: This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Boundaries come from the US Census TIGER geodatabases. Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines clipped for cartographic purposes. For census tracts, the water cutouts are derived from a subset of the 2020 AWATER (Area Water) boundaries offered by TIGER. For state and county boundaries, the water and coastlines are derived from the coastlines of the 500k TIGER Cartographic Boundary Shapefiles. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters). Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page. Data processed using R statistical package and ArcGIS Desktop. Margin of Error was not included in this layer but is available from the Census Bureau. Contact the Office of Planning for more information about obtaining Margin of Error values.

  8. p

    Population and Housing Census 2011 - Samoa

    • microdata.pacificdata.org
    Updated Jul 1, 2019
    + more versions
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    Samoa Bureau of Statistics (2019). Population and Housing Census 2011 - Samoa [Dataset]. https://microdata.pacificdata.org/index.php/catalog/250
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    Dataset updated
    Jul 1, 2019
    Dataset authored and provided by
    Samoa Bureau of Statistics
    Time period covered
    2011
    Area covered
    Samoa
    Description

    Abstract

    The 2011 Population and Housing Census of Samoa was taken on the midnight of November the 7th 2011. It counted every person in the country on that night and collected a wide range of social, economic and demographic information about each individual and their housing status.

    The information were used to develop statistical indicators to support national plannning and policy-making and also to monitor MDG indicators and all other related conventions. This included population growth rates, educational attainment, employment rates, fertility rates, mortality rates, internal movements, household access to water supply, electricity, sanitation, and many other information. The full report is available at SBS website: http://www.sbs.gov.ws under the section on Population statistics and demography.

    Geographic coverage

    National coverage Regions Districts Village Enumeration areas

    Analysis unit

    Private households Institutional households Individuals Women 15-49 Housing/Buildings

    Universe

    The PHC 2011 covered all de facto household members, institutional households such as boarding schools, hospitals, prison inmates and expatriates residing in Samoa for more than 3 months. The PHC excluded all tourists visiting Samoa during the enumeration period and all Samoans residing overseas.

    Kind of data

    Census/enumeration data [cen]

    Sampling procedure

    Not applicable to a complete enumeration census.

    Mode of data collection

    Face-to-face [f2f]

    Research instrument

    Users' consultation seminars were conducted for three consecutive days (June 8th -10th, 2010) with financial support provided by the office of UNFPA in Suva via the Samoa Parliamentary Group for Population Development (SPGPD) annual programs. For the first time in census history, the SPGPD or members of parliament have become the target group of users to get involved in any census questionnaire consultations.

    All government ministries and non-governmental organizations were invited to the consultation seminars and each was asked to make a presentation of data needs for consideration in the final census 2011 questionnaire. To avoid re-inventing the wheel in the compilation of the list of census questions for census 2011, the questionnaire from the census 2006 was reprinted and distributed to all participants and presenters to select questions that they would consider again for the census 2011 in addition to their new data needs. Users were also advised that any new question would need good justifications of how it links to national interests.

    At the end of the three days seminar, all new questions were compiled for final selection by Samoa Bureau of Statistics. Not all the users' data needs have been included in the final 2011 census questionnaire due mainly to the cost involved and limited time for census enumeration. Therefore, the final selection of questions was purely based on the linkage of the data being requested to the list of statistical indicators in the 'Strategy for the Development of Samoa 2008-2012' (SDS) and the 'Millennium Development Goals' (MDGs) 2015. All data requests outside of the two frameworks were put aside to be integrated in other more appropriate survey activities by the bureau.

    From July 2010-December 2010, the questionnaire was formatted using the In-Design CS4 software. It is important to note that the PHC 2011 was the first ever census using the scanning technology to process data from the census questionnaires as a replacement of the usual manual data entry process. The scanning was pilot tested in April 2011, before it was finally used for final census enumeration.

    The questionnaire was designed using A3 paper size.

    The Population questionnaire was administered in each household, which collected various information on household members including age, sex, citizenship, disability, orphanhood, marital status, residence (birth, usual, previous), religion, education and employment.

    In the Population questionnaire, a special section was administered in each household for women age 15-49, which also asked information on their children ever born still living, died or living somewhere else. Mothers of children under one year were also asked whether their last born children were still living at the time of the census.

    The Housing questionnaire was also administered in each household which collected information on the types of building the household lived, floor materials, wall materials, roof materials, land tenure, house tenure, water supply, drinking water, lighting, cooking fuel, toilet facility, telephone, computer, internet, refrigerator, radio, television and others.

    Cleaning operations

    Data editing was done in several stages. 1. Office manual editing and coding 2. Automatic scanning data entry edits 3. Visual verification questionnaire edits 3. Structure checking and completeness 4. Structure checks of the CSPro data files Editing program can be enquired at the Division of IT and Data Processing at email address: info.stats@sbs.gov.ws

    Sampling error estimates

    The census is a full-coverage of the population, therefore it is not a sample where sampling errors can be estimated.

    Data appraisal

    There was no post-enumeration in the census 2011. One of the normal practices by the bureau to validate the total population counts from all villages, districts and regions of Samoa in any census is the manual count of the population in all areas during the on-going census enumeration.That information is collected by the enumerators and field supervisors during the enumeration using the Enumerators and Supervisors control forms. At the end of the enumeration, the control forms which mainly contained the number of males and females per enumeration area will be collected and compiled by the Census and Survey division as the first preliminary count of the census. In the census 2011, the preliminary population counts were compiled and launched as the 'Village Directory 2011' report after 4 weeks from end of the enumeration period.

    The significance of the Village Directory report is it helps to provide a qiuick overall picture of the population growth and population distribution in all villages of the country relative to previous censuses. Most important of all is that the preliminary count will provide the basis for a decision whether a post-enumeration is warrant or otherwise. If the preliminary country is close to the projected population then the post-enumeration is assumed not worth the cost because it is expensive and it will delay all other census processes. In the census 2011, the preliminary count arrived at 186,340 which was more than the projected population of 184,032 as depicted in the Statistical Abstract 2009. Therefore the decision was made that post-enumeration was not worth it.

  9. a

    TC Census2020 BG

    • tcdata-tompkinscounty.opendata.arcgis.com
    • hub.arcgis.com
    Updated Feb 1, 2023
    + more versions
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    Tompkins County Mapping Portal (2023). TC Census2020 BG [Dataset]. https://tcdata-tompkinscounty.opendata.arcgis.com/datasets/tc-census2020-bg-1
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    Dataset updated
    Feb 1, 2023
    Dataset authored and provided by
    Tompkins County Mapping Portal
    Area covered
    Description

    Census Bureau ContactsCall Center: 301-763-INFO (4636) or 800-923-8282 or ask.census.govTDD: TTY users can dial 1-800-877-8339 to use the Federal Relay ServiceNews media: 301-763-3030 or 877-861-2010 or pio@census.govSubscribe now to receive Census Bureau releases and information via e-mail or SMS.Mailing Address: Via U.S. Postal Service (USPS): U.S. Census Bureau 4600 Silver Hill Road Washington, DC 20233

  10. Telemedicine Use in the Last 4 Weeks

    • data.virginia.gov
    csv, json, rdf, xsl
    Updated Apr 14, 2023
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    Telemedicine Use in the Last 4 Weeks [Dataset]. https://data.virginia.gov/dataset/telemedicine-use-in-the-last-4-weeks
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    xsl, csv, rdf, jsonAvailable download formats
    Dataset updated
    Apr 14, 2023
    Dataset provided by
    Centers for Disease Control and Preventionhttp://www.cdc.gov/
    Description

    To rapidly monitor recent changes in the use of telemedicine, the National Center for Health Statistics (NCHS) and the Health Resources and Services Administration’s Maternal and Child Health Bureau (HRSA MCHB) partnered with the Census Bureau on an experimental data system called the Household Pulse Survey. This 20-minute online survey was designed to complement the ability of the federal statistical system to rapidly respond and provide relevant information about the impact of the coronavirus pandemic in the U.S.

    The U.S. Census Bureau, in collaboration with five federal agencies, launched the Household Pulse Survey to produce data on the social and economic impacts of the COVID-19 pandemic on American households. The Household Pulse Survey was designed to gauge the impact of the pandemic on employment status, consumer spending, food security, housing, education disruptions, and dimensions of physical and mental wellness.

    The survey was designed to meet the goal of accurate and timely estimates. It was conducted by an internet questionnaire, with invitations to participate sent by email and text message. The sample frame is the Census Bureau Master Address File Data. Housing units linked to one or more email addresses or cell phone numbers were randomly selected to participate, and one respondent from each housing unit was selected to respond for him or herself. Estimates are weighted to adjust for nonresponse and to match Census Bureau estimates of the population by age, sex, race and ethnicity, and educational attainment. All estimates shown meet the NCHS Data Presentation Standards for Proportions.

  11. Indicators of Anxiety or Depression Based on Reported Frequency of Symptoms...

    • s.cnmilf.com
    • healthdata.gov
    • +2more
    Updated Feb 4, 2025
    + more versions
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    Centers for Disease Control and Prevention (2025). Indicators of Anxiety or Depression Based on Reported Frequency of Symptoms During Last 7 Days [Dataset]. https://s.cnmilf.com/user74170196/https/catalog.data.gov/dataset/indicators-of-anxiety-or-depression-based-on-reported-frequency-of-symptoms-during-last-7-
    Explore at:
    Dataset updated
    Feb 4, 2025
    Dataset provided by
    Centers for Disease Control and Preventionhttp://www.cdc.gov/
    Description

    The U.S. Census Bureau, in collaboration with five federal agencies, launched the Household Pulse Survey to produce data on the social and economic impacts of Covid-19 on American households. The Household Pulse Survey was designed to gauge the impact of the pandemic on employment status, consumer spending, food security, housing, education disruptions, and dimensions of physical and mental wellness. The survey was designed to meet the goal of accurate and timely weekly estimates. It was conducted by an internet questionnaire, with invitations to participate sent by email and text message. The sample frame is the Census Bureau Master Address File Data. Housing units linked to one or more email addresses or cell phone numbers were randomly selected to participate, and one respondent from each housing unit was selected to respond for him or herself. Estimates are weighted to adjust for nonresponse and to match Census Bureau estimates of the population by age, sex, race and ethnicity, and educational attainment. All estimates shown meet the NCHS Data Presentation Standards for Proportions,

  12. Mental Health Care in the Last 4 Weeks

    • healthdata.gov
    • data.virginia.gov
    • +3more
    application/rdfxml +5
    Updated Feb 25, 2021
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    data.cdc.gov (2021). Mental Health Care in the Last 4 Weeks [Dataset]. https://healthdata.gov/dataset/Mental-Health-Care-in-the-Last-4-Weeks/kfr8-6xqg
    Explore at:
    application/rdfxml, tsv, csv, xml, application/rssxml, jsonAvailable download formats
    Dataset updated
    Feb 25, 2021
    Dataset provided by
    data.cdc.gov
    Description

    The U.S. Census Bureau, in collaboration with five federal agencies, launched the Household Pulse Survey to produce data on the social and economic impacts of Covid-19 on American households. The Household Pulse Survey was designed to gauge the impact of the pandemic on employment status, consumer spending, food security, housing, education disruptions, and dimensions of physical and mental wellness.

    The survey was designed to meet the goal of accurate and timely weekly estimates. It was conducted by an internet questionnaire, with invitations to participate sent by email and text message. The sample frame is the Census Bureau Master Address File Data. Housing units linked to one or more email addresses or cell phone numbers were randomly selected to participate, and one respondent from each housing unit was selected to respond for him or herself. Estimates are weighted to adjust for nonresponse and to match Census Bureau estimates of the population by age, gender, race and ethnicity, and educational attainment. All estimates shown meet the NCHS Data Presentation Standards for Proportions.

  13. D

    Indicators of Health Insurance Coverage at the Time of Interview

    • data.cdc.gov
    • healthdata.gov
    • +2more
    application/rdfxml +5
    Updated Oct 4, 2024
    + more versions
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    NCHS/DHIS (2024). Indicators of Health Insurance Coverage at the Time of Interview [Dataset]. https://data.cdc.gov/w/jb9g-gnvr/tdwk-ruhb?cur=l9_88DmmwnF
    Explore at:
    application/rdfxml, json, application/rssxml, csv, tsv, xmlAvailable download formats
    Dataset updated
    Oct 4, 2024
    Dataset authored and provided by
    NCHS/DHIS
    License

    https://www.usa.gov/government-workshttps://www.usa.gov/government-works

    Description

    The U.S. Census Bureau, in collaboration with five federal agencies, launched the Household Pulse Survey to produce data on the social and economic impacts of Covid-19 on American households. The Household Pulse Survey was designed to gauge the impact of the pandemic on employment status, consumer spending, food security, housing, education disruptions, and dimensions of physical and mental wellness.

    The survey was designed to meet the goal of accurate and timely weekly estimates. It was conducted by an internet questionnaire, with invitations to participate sent by email and text message. The sample frame is the Census Bureau Master Address File Data. Housing units linked to one or more email addresses or cell phone numbers were randomly selected to participate, and one respondent from each housing unit was selected to respond for him or herself. Estimates are weighted to adjust for nonresponse and to match Census Bureau estimates of the population by age, sex, race and ethnicity, and educational attainment. All estimates shown meet the NCHS Data Presentation Standards for Proportions.

  14. g

    ACS 5-Year Economic Characteristics DC Census Tract | gimi9.com

    • gimi9.com
    Updated Jun 22, 2022
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    (2022). ACS 5-Year Economic Characteristics DC Census Tract | gimi9.com [Dataset]. https://www.gimi9.com/dataset/data-gov_acs-5-year-economic-characteristics-dc-census-tract/
    Explore at:
    Dataset updated
    Jun 22, 2022
    License

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

    Area covered
    Washington
    Description

    Employment, Commuting, Occupation, Income, Health Insurance, Poverty, and more. This service is updated annually with American Community Survey (ACS) 5-year data. Contact: District of Columbia, Office of Planning. Email: planning@dc.gov. Geography: Census Tracts. Current Vintage: 2018-2022. ACS Table(s): DP03. Data downloaded from: Census Bureau's API for American Community Survey. Date of API call: January 2, 2024. National Figures: data.census.gov. Please cite the Census and ACS when using this data. Data Note from the Census: Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables. Data Processing Notes: This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Boundaries come from the US Census TIGER geodatabases. Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines clipped for cartographic purposes. For census tracts, the water cutouts are derived from a subset of the 2020 AWATER (Area Water) boundaries offered by TIGER. For state and county boundaries, the water and coastlines are derived from the coastlines of the 500k TIGER Cartographic Boundary Shapefiles. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters). Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page. Data processed using R statistical package and ArcGIS Desktop. Margin of Error was not included in this layer but is available from the Census Bureau. Contact the Office of Planning for more information about obtaining Margin of Error values.

  15. d

    ACS 5-Year Economic Characteristics of DC Census Tracts 2016-2020

    • opdatahub.dc.gov
    Updated May 12, 2022
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    City of Washington, DC (2022). ACS 5-Year Economic Characteristics of DC Census Tracts 2016-2020 [Dataset]. https://opdatahub.dc.gov/datasets/acs-5-year-economic-characteristics-of-dc-census-tracts-2016-2020
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    Dataset updated
    May 12, 2022
    Dataset authored and provided by
    City of Washington, DC
    Area covered
    Description

    Employment, Commuting, Occupation, Income, Health Insurance, Poverty, and more. This service is updated annually with American Community Survey (ACS) 5-year data. Contact: District of Columbia, Office of Planning. Email: planning@dc.gov. Geography: Census Tracts. Current Vintage: 2016-2020. ACS Table(s): DP03. Data downloaded from: Census Bureau's API for American Community Survey. Date of API call: April 8, 2022. National Figures: data.census.gov. Please cite the Census and ACS when using this data. Data Note from the Census: Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables. Data Processing Notes: This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Boundaries come from the US Census TIGER geodatabases. Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines clipped for cartographic purposes. For census tracts, the water cutouts are derived from a subset of the 2020 AWATER (Area Water) boundaries offered by TIGER. For state and county boundaries, the water and coastlines are derived from the coastlines of the 500k TIGER Cartographic Boundary Shapefiles. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters). Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page. Data processed using R statistical package and ArcGIS Desktop. Margin of Error was not included in this layer but is available from the Census Bureau. Contact the Office of Planning for more information about obtaining Margin of Error values.

  16. a

    ACS 5-Year Economic Characteristics DC Census Tract

    • arc-gis-hub-home-arcgishub.hub.arcgis.com
    Updated Mar 29, 2024
    + more versions
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    City of Washington, DC (2024). ACS 5-Year Economic Characteristics DC Census Tract [Dataset]. https://arc-gis-hub-home-arcgishub.hub.arcgis.com/datasets/a53c0f02804a484b87027ce3ef3ff38b
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    Dataset updated
    Mar 29, 2024
    Dataset authored and provided by
    City of Washington, DC
    License

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

    Area covered
    Description

    Employment, Commuting, Occupation, Income, Health Insurance, Poverty, and more. This service is updated annually with American Community Survey (ACS) 5-year data. Contact: District of Columbia, Office of Planning. Email: planning@dc.gov. Geography: Census Tracts. Current Vintage: 2018-2022. ACS Table(s): DP03. Data downloaded from: Census Bureau's API for American Community Survey. Date of API call: January 2, 2024. National Figures: data.census.gov. Please cite the Census and ACS when using this data. Data Note from the Census: Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables. Data Processing Notes: This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Boundaries come from the US Census TIGER geodatabases. Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines clipped for cartographic purposes. For census tracts, the water cutouts are derived from a subset of the 2020 AWATER (Area Water) boundaries offered by TIGER. For state and county boundaries, the water and coastlines are derived from the coastlines of the 500k TIGER Cartographic Boundary Shapefiles. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters). Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page. Data processed using R statistical package and ArcGIS Desktop. Margin of Error was not included in this layer but is available from the Census Bureau. Contact the Office of Planning for more information about obtaining Margin of Error values.

  17. d

    Social Characteristics of DC Census Tracts 2018-2022 5-Year ACS

    • catalog.data.gov
    Updated Apr 30, 2024
    + more versions
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    City of Washington, DC (2024). Social Characteristics of DC Census Tracts 2018-2022 5-Year ACS [Dataset]. https://catalog.data.gov/dataset/social-characteristics-of-dc-census-tracts-2018-2022-5-year-acs
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    Dataset updated
    Apr 30, 2024
    Dataset provided by
    City of Washington, DC
    Description

    Household type, Education, Disability, Language, Computer/Internet Use, and more. This service is updated annually with American Community Survey (ACS) 5-year data. Contact: District of Columbia, Office of Planning. Email: planning@dc.govGeography: Census TractsCurrent Vintage: 2018-2022ACS Table(s): DP02Data downloaded from: Census Bureau's API for American Community Survey Date of API call: January 2, 2024National Figures: data.census.gov The United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. Please cite the Census and ACS when using this data. Data Note from the Census:Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables. Data Processing Notes:This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Click here to learn more about ACS data releases.Boundaries come from the US Census TIGER geodatabases. Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines clipped for cartographic purposes. For census tracts, the water cutouts are derived from a subset of the 2010 AWATER (Area Water) boundaries offered by TIGER. For state and county boundaries, the water and coastlines are derived from the coastlines of the 500k TIGER Cartographic Boundary Shapefiles. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters). Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.Data processed using R statistical package and ArcGIS Desktop.Margin of Error was not included in this layer but is available from the Census Bureau. Contact the Office of Planning for more information about obtaining Margin of Error values.

  18. Telemedicine Use in the Last 4 Weeks

    • healthdata.gov
    • s.cnmilf.com
    • +2more
    application/rdfxml +5
    Updated May 6, 2021
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    data.cdc.gov (2021). Telemedicine Use in the Last 4 Weeks [Dataset]. https://healthdata.gov/w/jnr3-qn3j/_variation_?cur=cvNEOqytqdN&from=root
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    csv, tsv, json, application/rssxml, xml, application/rdfxmlAvailable download formats
    Dataset updated
    May 6, 2021
    Dataset provided by
    data.cdc.gov
    Description

    To rapidly monitor recent changes in the use of telemedicine, the National Center for Health Statistics (NCHS) and the Health Resources and Services Administration’s Maternal and Child Health Bureau (HRSA MCHB) partnered with the Census Bureau on an experimental data system called the Household Pulse Survey. This 20-minute online survey was designed to complement the ability of the federal statistical system to rapidly respond and provide relevant information about the impact of the coronavirus pandemic in the U.S.

    The U.S. Census Bureau, in collaboration with five federal agencies, launched the Household Pulse Survey to produce data on the social and economic impacts of the COVID-19 pandemic on American households. The Household Pulse Survey was designed to gauge the impact of the pandemic on employment status, consumer spending, food security, housing, education disruptions, and dimensions of physical and mental wellness.

    The survey was designed to meet the goal of accurate and timely estimates. It was conducted by an internet questionnaire, with invitations to participate sent by email and text message. The sample frame is the Census Bureau Master Address File Data. Housing units linked to one or more email addresses or cell phone numbers were randomly selected to participate, and one respondent from each housing unit was selected to respond for him or herself. Estimates are weighted to adjust for nonresponse and to match Census Bureau estimates of the population by age, sex, race and ethnicity, and educational attainment. All estimates shown meet the NCHS Data Presentation Standards for Proportions.

  19. d

    ACS 5-Year Economic Characteristics of DC Census Tracts 2017-2021

    • opdatahub.dc.gov
    Updated Feb 1, 2023
    + more versions
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    City of Washington, DC (2023). ACS 5-Year Economic Characteristics of DC Census Tracts 2017-2021 [Dataset]. https://opdatahub.dc.gov/datasets/acs-5-year-economic-characteristics-of-dc-census-tracts-2017-2021
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    Dataset updated
    Feb 1, 2023
    Dataset authored and provided by
    City of Washington, DC
    License

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

    Area covered
    Description

    Employment, Commuting, Occupation, Income, Health Insurance, Poverty, and more. This service is updated annually with American Community Survey (ACS) 5-year data. Contact:District of Columbia, Office of Planning. Email: planning@dc.gov. Geography: Census Tracts. Current Vintage: 2017-2021. ACS Table(s): DP03. Data downloaded from: Census Bureau's API for American Community Survey. Date of API call: December 12, 2022. National Figures: data.census.gov. Please cite the Census and ACS when using this data. Data Note from the Census: Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables. Data Processing Notes: This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Boundaries come from the US Census TIGER geodatabases. Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines clipped for cartographic purposes. For census tracts, the water cutouts are derived from a subset of the 2020 AWATER (Area Water) boundaries offered by TIGER. For state and county boundaries, the water and coastlines are derived from the coastlines of the 500k TIGER Cartographic Boundary Shapefiles. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters). Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page. Data processed using R statistical package and ArcGIS Desktop. Margin of Error was not included in this layer but is available from the Census Bureau. Contact the Office of Planning for more information about obtaining Margin of Error values.

  20. Share of U.S. e-mail users 2023, by gender

    • statista.com
    Updated Sep 11, 2024
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    Share of U.S. e-mail users 2023, by gender [Dataset]. https://www.statista.com/statistics/628372/us-email-usage-reach-by-gender/
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    Dataset updated
    Sep 11, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Nov 2023
    Area covered
    United States
    Description

    As of November 2023, approximately 93.3 percent of women in the United States were using emails as a form of online communication. By comparison, the number of male internet users doing the same was approximately 91.5 percent of the total as of the last measured period.

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Statista (2024). Share of U.S. e-mail users 2023, by ethnicity [Dataset]. https://www.statista.com/statistics/628376/us-email-usage-reach-by-ethnicity/
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Share of U.S. e-mail users 2023, by ethnicity

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Dataset updated
Sep 11, 2024
Dataset authored and provided by
Statistahttp://statista.com/
Time period covered
Nov 2023
Area covered
United States
Description

In November 2023, over 91 percent of the African American digital population accessed emails. By comparison, approximately 93.8 percent of the white population had access and used this form of online communication, while 93.7 percent of Asian Americans in the country did the same as of the last measured period.

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