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TwitterPopulation is the sum of births plus in-migration, and it signifies the total market size possible in the area. This is an important metric for economic developers to measure their economic health and investment attraction. Businesses also use this as a metric for market size when evaluating startup, expansion or relocation decisions.
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TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
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This demographics data package is part of a 3 layer set for Tracts, Block Groups, and Blocks across all of Santa Clara County. A field is present in each to allow filtering for the geometries that are only in The City of San Jose. Each of the data layers contains the most commonly requested demographic fields from the U.S. Census/American Community Survey. Please note these fields are not exactly the same as found in the census tables, the goal was to standardize the field names so that they will always remain the same regardless of if the census changes the field names or range values. San Jose GIS Enterprise staff will update these fields once a year. Please check the field that states the last time it was updated and from what source. Please also note that Tracts has the most data fields, Block Groups slightly less, and Blocks has very few. The finer scaled geometries have less data available from the U.S. Census, so those fields were dropped.
Source: Census 2020
Data is updated every ten years from decennial census.
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Context
The dataset tabulates the New Haven population distribution across 18 age groups. It lists the population in each age group along with the percentage population relative of the total population for New Haven. The dataset can be utilized to understand the population distribution of New Haven by age. For example, using this dataset, we can identify the largest age group in New Haven.
Key observations
The largest age group in New Haven, IL was for the group of age 20-24 years with a population of 105 (25.86%), according to the 2021 American Community Survey. At the same time, the smallest age group in New Haven, IL was the 30-34 years with a population of 0 (0.00%). Source: U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.
Age groups:
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for New Haven Population by Age. You can refer the same here
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Demographic statistical domains – DeSO is a national classification created by Statistics Sweden that came into force in January 2018. DeSO divides Sweden into 5,984 areas with between 700 and 2,700 inhabitants at the start. The division follows the county and municipal boundaries. DeSO does not have names or names but is described by a code with nine unique positions. The first four consist of the county and municipality code and indicate the county and municipality in which the area is located. The fifth position indicates which category the area belongs to A, B or C. A are areas that are mostly outside major population concentrations or agglomerations. B are areas which are mostly in population concentrations or urban agglomerations but which are not a central location. Category C is the area that is mostly located in the municipality's central city. The three subsequent positions consist of a sequential number that sorts the areas geographically. This sorting is based on the categories and starts in the south and continues north. The last position is a reserve that will be used in case a DeSO needs to be split up in the future. A DeSO can only occur in one location.
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TwitterMedical Service Study Areas (MSSAs)As defined by California's Office of Statewide Health Planning and Development (OSHPD) in 2013, "MSSAs are sub-city and sub-county geographical units used to organize and display population, demographic and physician data" (Source). Each census tract in CA is assigned to a given MSSA. The most recent MSSA dataset (2014) was used. Spatial data are available via OSHPD at the California Open Data Portal. This information may be useful in studying health equity.Definitions:Race/Ethnicity: Race/ethnicity is categorized as: All races/ethnicities, Non-Hispanic (NH) White, NH Black, Asian/Pacific Islander, or Hispanic. "All races" includes all of the above, as well as other and unknown race/ethnicity and American Indian/Alaska Native. The latter two groups are not reported separately due to small numbers for many cancer sites.Racial/Ethnic Composition: Distribution of residents' race/ethnicity (e.g., % Hispanic, % non-Hispanic White, % non-Hispanic Black, % non-Hispanic Asian/Pacific Islander). (Source: US Census, 2010.)Rural: Percent of residents who reside in blocks that are designated as rural. (Source: US Census, 2010.)Foreign Born: Percent of residents who were born outside the United States. (Source: American Community Survey, 2008-2012.)Socioeconomic Status (Neighborhood Level): A composite measure of seven indicator variables created by principal component analysis; indicators include: education, blue-collar job, unemployment, household income, poverty, rent, and house value. Quintiles based on state distribution, with quintile 1 being the lowest SES and 5 being the highest. (Source: American Community Survey, 2008-2012.)Spatial extent: CaliforniaSpatial Unit: MSSACreated: n/aUpdated: n/aSource: California Health MapsContact Email: gbacr@ucsf.eduSource Link: https://www.californiahealthmaps.org/?areatype=mssa&address=&sex=Both&site=AllSite&race=&year=05yr&overlays=none&choropleth=Obesity
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TwitterEach year, the Forecasting and Trends Office (FTO) publishes population estimates and future year projections. The population estimates can be used for a variety of planning studies including statewide and regional transportation plan updates, subarea and corridor studies, and funding allocations for various planning agencies.The 2020 population estimates reported are based on the US Census Bureau 2020 Decennial Census. The 2021 population estimates are based on the population estimates developed by the Bureau of Economic and Business Research (BEBR) at the University of Florida. BEBR uses the decennial census count for April 1, 2020, as the starting point for state-level projections. More information is available from BEBR here.This dataset contains boundaries for all 2010 Census Urbanized Areas (UAs) in the State of Florida with 2020 census population and 2021 population estimates. It reports population by both UA and county. For example, Pensacola, FL--AL Urbanized Area is located in three counties: Escambia County, FL, Santa Rosa County, FL, and Baldwin County, AL. This dataset contains three records that report Pensacola, FL—AL UA’s population that live in each county separately. All legal boundaries and names in this dataset are from the US Census Bureau’s TIGER/Line Files (2021).BEBR provides 2021 population estimates for counties in Florida. However, UA boundaries may not coincide with the jurisdictional boundaries of counties and UAs often spread into several counties. To estimate the population for an UA, first the ratio of the subject UA that is contained within a county (or sub-area) to the area of the entire county was determined. That ratio was multiplied by the estimated county population to obtain the population for that sub-area. The population for the entire UA is the sum of all sub-area populations estimated from the counties they are located within.For the 2010 Census, urban areas comprised a “densely settled core of census tracts and/or census blocks that meet minimum population density requirements, along with adjacent territory containing non-residential urban land uses as well as territory with low population density included to link outlying densely settled territory with the densely settled core.” In 2010, the US Census Bureau identified two types of urban areas—UAs and Urban Clusters (UCs). UAs have a population of 50,000 or more people. Note: Pensacola, FL--AL Urbanized Area is the only Urbanized Area in Florida that crosses the state border. 2021 population of Baldwin County, AL used for this estimation is from the US Census annual population estimates (2020-2021). Please see the Data Dictionary for more information on data fields. Data Sources:US Census Bureau 2020 Decennial CensusUS Census Bureau’s TIGER/Line Files (2021)Bureau of Economic and Business Research (BEBR) – Florida Estimates of Population 2021 Data Coverage: StatewideData Time Period: 2020 – 2021 Date of Publication: July 2022 Point of Contact:Dana Reiding, ManagerForecasting and Trends OfficeFlorida Department of TransportationDana.Reiding@dot.state.fl.us605 Suwannee Street, Tallahassee, Florida 32399850-414-4719
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TwitterPublic Domain Mark 1.0https://creativecommons.org/publicdomain/mark/1.0/
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The mean "Center of Population" for each county in 2000, 2010 and 2020, as published by the United State Census Bureau, is shown in this layer..The population center for each county represents the point where a flat and rigid representation of the county would balance if identical weights for each person were placed at their residence. Looking at the movement of the point over time helps convey information about the predominant population trend in the county including areas loosing population or areas gaining population.For each location, the nearest feature from the US Geologic Survey Geographic Names Information System (GNIS) was appended along with the GNIS feature class and county where the point was located.
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TwitterTo provide a snapshot of citywide student enrollment and demographic information across multiple years. Data is collected using multiple data sources, including DOE's Audited Register, biographic data from Automate The Schools (ATS) system and the Location Code Generation and Management System (LCGMS). Data can be used to view citywide demographic and enrollment trends over time. Enrollment counts are based on the October 31 Audited Register for each school year. Please note that October 31 enrollment is not audited for charter schools or Pre-K Early Education Centers(NYCEECs). Charter schools are required to submit enrollment as of BEDS Day the first Wednesday in October to the New York State Education Department of Education. Enrollment counts will exceed operational enrollment counts due the fact that long term absence (LTA) students are excluded for funding purposes.
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TwitterComprehensive demographic dataset for Model, CO, US including population statistics, household income, housing units, education levels, employment data, and transportation with year-over-year changes.
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Twitterhttps://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/
This data file includes city population and geolocation data (lat, long, timezone) for the top 15000 cities of the world. It was originally downloaded in September 2017 from http://www.geonames.org/.
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TwitterComprehensive demographic dataset for Portales, NM, US including population statistics, household income, housing units, education levels, employment data, and transportation with year-over-year changes.
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TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
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Context
The dataset tabulates the Rhode Island population by age. The dataset can be utilized to understand the age distribution and demographics of Rhode Island.
The dataset constitues the following three datasets
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
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TwitterComprehensive demographic dataset for Ama, LA, US including population statistics, household income, housing units, education levels, employment data, and transportation with year-over-year changes.
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TwitterAttribution 3.0 (CC BY 3.0)https://creativecommons.org/licenses/by/3.0/
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Information about persons of concern broken down by sex and age, as well as by location within the country of residence (where such information is available). Such data is available since 2000.
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TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the Aurora population distribution across 18 age groups. It lists the population in each age group along with the percentage population relative of the total population for Aurora. The dataset can be utilized to understand the population distribution of Aurora by age. For example, using this dataset, we can identify the largest age group in Aurora.
Key observations
The largest age group in Aurora, MN was for the group of age 60-64 years with a population of 200 (11.70%), according to the 2021 American Community Survey. At the same time, the smallest age group in Aurora, MN was the 80-84 years with a population of 51 (2.98%). Source: U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.
Age groups:
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for Aurora Population by Age. You can refer the same here
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TwitterComprehensive demographic dataset for Valley, PA, US including population statistics, household income, housing units, education levels, employment data, and transportation with year-over-year changes.
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TwitterComprehensive demographic dataset for Oneida, PA, US including population statistics, household income, housing units, education levels, employment data, and transportation with year-over-year changes.
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TwitterSee our new monthly data page for data from November 2024 onwards.
These official statistics were independently reviewed by the Office for Statistics Regulation in May 2022. They comply with the standards of trustworthiness, quality and value in the https://code.statisticsauthority.gov.uk/">Code of Practice for Statistics and should be labelled ‘accredited official statistics’. Accredited official statistics are called National Statistics in the Statistics and Registration Service Act 2007. Further explanation of accredited official statistics can be found on the https://osr.statisticsauthority.gov.uk/accredited-official-statistics/">Office for Statistics Regulation website.
In response to user feedback, we are testing alternative ways of presenting the monthly data sets as visualisations on the UKHSA data dashboard. The current data sets will continue to be published as normal and users will be consulted prior to any significant changes. We encourage users to review and provide feedback on the new dashboard content.
Monthly counts of total reported, hospital-onset, hospital-onset healthcare associated (HOHA), community-onset healthcare associated (COHA), community-onset and community-onset community associated (COCA) MRSA bacteraemias by NHS organisations.
These documents contain the monthly counts of total reported, hospital-onset and community-onset MRSA bacteraemia by NHS organisations.
The UK Government Web Archive contains MRSA bacteraemia data from previous financial years, including:
data from https://webarchive.nationalarchives.gov.uk/ukgwa/20230510143423/https://www.gov.uk/government/statistics/mrsa-bacteraemia-monthly-data-by-location-of-onset">2022 to 2023
data from https://webarchive.nationalarchives.gov.uk/ukgwa/20220614173109/https://www.gov.uk/government/statistics/mrsa-bacteraemia-monthly-data-by-location-of-onset">2021 to 2022
data from https://webarchive.nationalarchives.gov.uk/20210507180210/https://www.gov.uk/government/statistics/mrsa-bacteraemia-monthly-data-by-location-of-onset">2020 to 2021
data from https://webarchive.nationalarchives.gov.uk/20200506173036/https://www.gov.uk/government/statistics/mrsa-bacteraemia-monthly-data-by-location-of-onset">2019 to 2020
data from https://webarchive.nationalarchives.gov.uk/20190508011104/https://www.gov.uk/government/collections/staphylococcus-aureus-guidance-data-and-analysis">2018 to 2019
data from https://webarchive.nationalarchives.gov.uk/20180510152304/https://www.gov.uk/government/statistics/mrsa-bacteraemia-monthly-data-by-attributed-clinical-commissioning-group">2017 to 2018
data from https://webarchive.nationalarchives.gov.uk/20170515101840tf_/https://www.gov.uk/government/statistics/mrsa-bacteraemia-monthly-data-by-attributed-clinical-commissioning-group">2013 to 2014, up to 2016 to 2017
data from https://webarchive.nationalarchives.gov.uk/20140712114853tf_/http://www.hpa.org.uk/web/HPAweb&HPAwebStandard/HPAweb_C/1254510675444">2013 and earlier
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TwitterThese Economic Estimates are National Statistics providing an estimate of the contribution of DCMS Sectors to the UK economy, measured by the number of businesses.
We have experimented with using a different, more timely data source to calculate this year’s Business Demographics statistics. As a result, they are not comparable with earlier DCMS Sector Business Demographics publications. More information is provided in these published documents and in the “Call for Feedback” section below.
These statistics cover the contributions of the following DCMS sectors to the UK economy;
Users should note that there is overlap between DCMS Sector definitions and that the Telecoms sector sits wholly within the Digital sector. Estimates are not available for the Civil Society sector, because they are not identifiable in the data source used for this release.
The release also includes estimates for the Audio Visual sector, which is not a DCMS Sector but is “adjacent” to it and includes some industries also common to DCMS Sectors.
A definition for each sector is available in the published data tables.
These statistics were first published on 8 December 2022
In this publication we have experimented with using a snapshot of the Inter-Departmental Business Register (IDBR) to generate estimates of DCMS Business Demographics, rather than the Annual Business Survey (ABS) as in previous releases. This has the advantage of being more timely, and commits to most tables included in previous Business Demographics publications. We have used the March 2019, March 2020, March 2021 and March 2022 snapshots from the ONS https://www.ons.gov.uk/businessindustryandtrade/business/activitysizeandlocation/datasets/ukbusinessactivitysizeandlocation">UK business: activity, size and location release rather than raw data from the IDBR.
We are looking for feedback on this approach. We particularly welcome views on:
Please contact evidence@dcms.gov.uk before Thursday 9th February 2023 with any feedback.
Hard copy feedback can be sent to:
DCMS Economic Estimates Team
Department for Digital, Culture, Media & Sport
4th Floor - area 4/34
100 Parliament Street
London
SW1A 2BQ
This release is published in accordance with the Code of Practice for Statistics (2018) produced by the UK Statistics Authority (UKSA). The UKSA has the overall objective of promoting and safeguarding the production and publication of official statistics that serve the public good. It monitors and reports on all official statistics, and promotes good practice in this area.
The accompanying pre-release access document lists ministers and officials who have received privileged early access to this release. In line with best practice, the list has been kept to a minimum and those given access for briefing purposes had a maximum of 24 hours.
Responsible analyst: Eri Hutchinson
For any queries or feedback, please contact evidence@dcms.gov.uk.
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TwitterComprehensive demographic dataset for Red Cross, NC, US including population statistics, household income, housing units, education levels, employment data, and transportation with year-over-year changes.
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TwitterPopulation is the sum of births plus in-migration, and it signifies the total market size possible in the area. This is an important metric for economic developers to measure their economic health and investment attraction. Businesses also use this as a metric for market size when evaluating startup, expansion or relocation decisions.