The trend-based projections include a range of variants based on different assumptions about future levels of migration. The projections are produced for all local authorities in England & Wales. The datasets include summary workbooks with population and summary components of change as well as zip archives with the full detailed outputs from the models, including components of change by single year of age and sex. The most recent set of trend-based population projections currently available are the 2022-based projections (August 2024). Additional documentation, including updated information about methodologies and assumptions will be published in the coming days. For more information about these projections, see the accompanying blog post. The 2022-based projections comprise three variants based on different periods of past migration patterns and assumed levels of future fertility rates. Trend-based projections don't explicitly account for future housing delivery. For most local planning purposes we generally recommend the use of housing-led projections These projections are based on modelled back series of population estimates produced by the GLA and available here * 14 July 2023 - following a minor update to the modelled population estimates series, we have made available an additional version of the projections based on these updated inputs. At this time we have no plans to update or replace the outputs and documentation published in January 2023. However, we recommend users looking to use the projections in analysis or as inputs to onward modelling consider using these updated outputs. Documentation page Back to projections homepage

At the April 2023 meeting of the Population Statistics User Group, the GLA Demography team presented an overview of currently available sources of population estimates for the previous decade, namely:

• The original ONS mid-year population estimates (including rolled-forward estimates for 2021)
• Experimental outputs from the ONS's Dynamic Population Model
• The modelled population backseries produced by the GLA to act as inputs to our 2021-based interim population projections

The slides from the presentation are published here together with packages of comparison plots for all local authority districts and regions in England to allow users to easily view some of the key differences between the sources for their own areas.

The plots also include comparisons of the Dynamic Population Model's provisional 2022 estimates of births with the modelled estimates of recent births produced by the GLA.

About this dataset

Context

The dataset tabulates the data for the Atlantis, FL population pyramid, which represents the Atlantis population distribution across age and gender, using estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. It lists the male and female population for each age group, along with the total population for those age groups. Higher numbers at the bottom of the table suggest population growth, whereas higher numbers at the top indicate declining birth rates. Furthermore, the dataset can be utilized to understand the youth dependency ratio, old-age dependency ratio, total dependency ratio, and potential support ratio.

Key observations

• Youth dependency ratio, which is the number of children aged 0-14 per 100 persons aged 15-64, for Atlantis, FL, is 18.2.
• Old-age dependency ratio, which is the number of persons aged 65 or over per 100 persons aged 15-64, for Atlantis, FL, is 94.9.
• Total dependency ratio for Atlantis, FL is 113.2.
• Potential support ratio, which is the number of youth (working age population) per elderly, for Atlantis, FL is 1.1.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group for the Atlantis population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Atlantis for the selected age group is shown in the following column.
• Population (Female): The female population in the Atlantis for the selected age group is shown in the following column.
• Total Population: The total population of the Atlantis for the selected age group is shown in the following column.

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.

Inspiration

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/.

Recommended for further research

This dataset is a part of the main dataset for Atlantis Population by Age. You can refer the same here

Introduction

Blogging Statistics: Blogging remains a pivotal element in digital content strategies, with over 600 million blogs among 1.9 billion websites globally. WordPress alone powers more than 43% of all websites, hosting over 60 million blogs and facilitating approximately 70 million new posts each month. In the United States, the blogging community has expanded to over 32.7 million active bloggers as of 2022. Globally, bloggers publish around 3 billion posts annually, equating to over 8.2 million posts daily.

The influence of blogs is substantial, with 77% of internet users regularly reading blog content. Incorporating relevant images can enhance blog views by 94%, and posts with seven or more images are 2.3 times more likely to yield strong results. Furthermore, 70% of consumers prefer learning about companies through articles rather than advertisements, highlighting the trust and engagement blogs foster.

For businesses, blogging offers significant advantages: companies with active blogs experience 55% more website visitors and generate 67% more monthly leads compared to those without. These statistics underscore blogging's role as a cost-effective and impactful tool for enhancing brand visibility and driving audience engagement.

With internet access, anyone can start a blog and reach a global audience through social media. In this article, we'll explore blogging statistics in more detail.

As of November 2023, nearly 17 percent of female internet users in the United States and around 16 percent of male users went online to publish blog posts or upload self-made video content. Overall, approximately 17 percent of the U.S. online population reported publishing original content on the internet.

Analysis of ‘🎦 Academy Awards Demographics’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/yamqwe/academy-awards-demographicse on 13 February 2022.

--- Dataset description provided by original source is as follows ---

About this dataset

A data set concerning the race, religion, age, and other demographic details of all Oscar winners since 1928 in the following categories: * Best * Actor

• Best Actress
• Best Supporting Actor
• Best Supporting Actress
• Best Director For further information on this data set, please read our resulting blog post For further information on this data set, please read our resulting blog post.

Source: https://www.crowdflower.com/data-for-everyone/

This dataset was created by CrowdFlower and contains around 400 samples along with Birthplace:confidence, Sexual Orientation Gold, technical information and other features such as: - Date Of Birth - Religion - and more.

How to use this dataset

• Analyze Year Of Award Gold in relation to Trusted Judgments
• Study the influence of Sexual Orientation on Date Of Birth:confidence
• More datasets

Acknowledgements

If you use this dataset in your research, please credit CrowdFlower

Start A New Notebook!

--- Original source retains full ownership of the source dataset ---

The contents of the dataset are related to the demographics of companies in the province of Trento.

The data, which come from various sources, were drawn up by the Labour Market and Policy Studies Office for the preparation of the Annual Employment Report in the province of Trento, available as content open to the URL: https://www.agenzialavoro.tn.it/Open-Data/Other-content-available

The dataset, including the resources in PDF format, is also available on the Open Data Catalogue of the Employment Agency at the URL: https://www.agenzialavoro.tn.it/Open-Data/I-dataset-available/Economics-and-finance/Economics-structure/Demography-of-businesses/Year-2016

The “time coverage” metadata refers to the time interval taken into account by the Historical Series that are identified in the file name with the suffix _ST.

The data released in CSV format are: Machine Readable, identified in the file name with the suffix _MR and validated with the Good Tables library. https://okfnlabs.org/blog/2015/02/20/introducing-goodtables.html

ATTRIBUTION: data compiled by the Office for Labour Market and Policy Studies on CCIAA – Movimprese data.

The housing-led projections reconcile future population growth with available housing supply by incorporating a housing supply trajectory. The housing-led projections are recommended for most local planning purposes, and the 10-year variant can be considered the default variant. Users in London local authorities are able to request bespoke projections based on alternative housing scenarios through the GLA Population Projection Service. The most recent set of projections are the 2022-based round (August 2024) which comprise three variants based on different migration and fertility assumptions. All 2022-based projections are based on a common scenario of assumed future housing delivery that is derived from capacity identified in the 2017 Strategic Housing Land Availability Assessment. These projections are based on modelled back series of population estimates produced by the GLA and available here. Additional documentation, including updated information about methodologies and assumptions will be published in the coming days. For more information about these projections, see the accompanying blog post. The housing-led projections include projections for London Boroughs and London wards (2022 boundaries). The release also includes components of change (births, deaths and migration data). Documentation page Back to projections homepage

On 28 June 2022 ONS released the first results from the 2011 Census of England and Wales comprising for each local authority the estimated population at census day (21 March 2021) and the number of households. Population estimates are by five-year age band and sex. Estimates of responses rates for each local authority were also published. Read our blog post which describes how the census data relates to other population estimates and some of the pitfalls to avoid when interpreting the numbers.

The population of the world, allocated to 1 arcsecond blocks. This refines CIESIN’s Gridded Population of the World project, using machine learning models on high-resolution worldwide Digital Globe satellite imagery. More information.

There is also a tiled version of this dataset that may be easier to use if you are interested in many countries.

The contents of the dataset relate to the population living in the province of Trento. The dataset, including resources in PDF format, is also available on the Employment Agency’s Open Data Portal at the URL: https://www.agenzialavoro.tn.it/Open-Data/I-dataset-available/Historical-Series/Demography Data are grouped by year and gender. Data are expressed in absolute values. The metadata ‘time coverage’ refers to the time interval taken into account by the Historical Series which is identified in the file name with the suffix _ST. Time coverage refers to 31 December of each year. The dataset is updated to 31 December each year with the addition of a new time series. The data released in CSV format are: Machine Readable, identified in the file name with the suffix _MR and validated with the Good Tables library. https://okfnlabs.org/blog/2015/02/20/introducing-goodtables.html ATTRIBUTION: data processed by the Office for the Study of Policies and the Labour Market on ISTAT data.

This dataset contains data from the P.L. 94-171 2020 Census Redistricting Program. The 2020 Census Redistricting Data Program provides states the opportunity to delineate voting districts and to suggest census block boundaries for use in the 2020 Census redistricting data tabulations (Public Law 94-171 Redistricting Data File). In addition, the Redistricting Data Program will periodically collect state legislative and congressional district boundaries if they are changed by the states. The program is also responsible for the effective delivery of the 2020 Census P.L. 94-171 Redistricting Data statutorily required by one year from Census Day. The program ensures continued dialogue with the states in regard to 2020 Census planning, thereby allowing states ample time for their planning, response, and participation. The U.S. Census Bureau will deliver the Public Law 94-171 redistricting data to all states by Sept. 30, 2021. COVID-19-related delays and prioritizing the delivery of the apportionment results delayed the Census Bureau’s original plan to deliver the redistricting data to the states by April 1, 2021.

Data in this dataset contains information on population, diversity, race, ethnicity, housing, household, vacancy rate for 2020 for various geographies (county, MCD, Philadelphia Planning Districts (referred to as county planning areas [CPAs] internally, Census designated places, tracts, block groups, and blocks)

For more information on the 2020 Census, visit https://www.census.gov/programs-surveys/decennial-census/about/rdo/summary-files.html

PLEASE NOTE: 2020 Decennial Census data has had noise injected into it because of the Census's new Disclosure Avoidance System (DAS). This can mean that population counts and characteristics, especially when they are particularly small, may not exactly correspond to the data as collected. As such, caution should be exercised when examining areas with small counts. Ron Jarmin, acting director of the Census Bureau posted a discussion of the redistricting data, which outlines what to expect with the new DAS. For more details on accuracy you can read it here: https://www.census.gov/newsroom/blogs/director/2021/07/redistricting-data.html

The population of the world, allocated to 1 arcsecond blocks. This refines CIESIN’s Gridded Population of the World project, using machine learning models on high-resolution worldwide Digital Globe satellite imagery. More information.

There is also a tiled version of this dataset that may be easier to use if you are interested in many countries.

The population of the world, allocated to 1 arcsecond blocks. This refines CIESIN’s Gridded Population of the World project, using machine learning models on high-resolution worldwide Digital Globe satellite imagery. More information.

There is also a tiled version of this dataset that may be easier to use if you are interested in many countries.

In May 2024, three percent of the Polish population had an online blog, a vlog (video blog), or a website. This was a decrease of two percent as compared to the year 2012.

This dataset contains administrative polygons grouped by country (admin-0) with the following subdivisions according to Who's On First placetypes:
- macroregion (admin-1 including region)
- region (admin-2 including state, province, department, governorate)
- macrocounty (admin-3 including arrondissement)
- county (admin-4 including prefecture, sub-prefecture, regency, canton, commune)
- localadmin (admin-5 including municipality, local government area, unitary authority, commune, suburb)

The dataset also contains human settlement points and polygons for:
- localities (city, town, and village)
- neighbourhoods (borough, macrohood, neighbourhood, microhood)

The dataset covers activities carried out by Who's On First (WOF) since 2015. Global administrative boundaries and human settlements are aggregated and standardized from hundreds of sources and available with an open CC-BY license. Who's On First data is updated on an as-need basis for individual places with annual sprints focused on improving specific countries or placetypes. Please refer to the README.md file for complete data source metadata. Refer to our blog post for explanation of field names.

Data corrections can be proposed using Write Field, an web app for making quick data edits. You’ll need a Github.com account to login and propose edits, which are then reviewed by the Who's On First community using the Github pull request process. Approved changes are available for download within 24-hours. Please contact WOF admin about bulk edits.

Version/Sprint 4 (November 2020) Privacy Loss Budget 4.0Census 2020 brings a new era of disclosure avoidance with the implementation of differential privacy. Differential privacy is a “formal privacy” approach that provides proven mathematical privacy assurances by adding uncertainty or “noise” to the released data. This technique determines the amount of noise necessary to balance privacy loss and accuracy via mathematical formulas. To better prepare data users for this shift, the Census Bureau has released 2010 Demonstration Data Products that provide the public with a sneak peek at what the 2010 raw data would look like after being pushed through the differential privacy system that is under development.The Census Bureau continues to improve the disclosure avoidance system and are actively soliciting feedback. We strongly suggest you run you highest priority workflows using both the original Census 2010 SF1 and Census 2010 with differential privacy applied. If you have concerns, please let the Census Bureau know by sending an email to 2020DAS@census.gov. As additional versions of the demonstration data are released the data will be published in the Living Atlas so that you can ensure your priority use cases are minimally impacted. These layers contain select critical variables for both the original Census 2010 SF1 and Census 2010 with differential privacy applied. This version of the demonstration products was released on 11-16-2020. Persons Per Household and Occupancy Rates were calculated using the housing unit, household, and household population variables. Fields with a “dp_” prefix indicate values from the differentially privatized data, and the “sf_” prefix indicates values from the original SF1 release.Data are shown in Census 2010 boundaries for the following geographies:· States· Counties· County Subdivisions· Tracts· Block Groups· Places· Congressional Districts 110th-112th (CD)· American Indian Areas (AIA)Census Geography are 2010 TIGER/Line ShapefilesTabulated data was obtained from IPUMS NHGIS. David Van Riper, Tracy Kugler, and Jonathan Schroeder. IPUMS NHGIS Privacy-Protected 2010 Census Demonstration Data, version 20201116 [Database]. Minneapolis, MN: IPUMS. 2020.https://www.nhgis.org/privacy-protected-demonstration-dataVisit the Census Bureau’s website to learn more about the implementation and ongoing development of the differential privacy system for future Census Bureau data releases. Read this Esri blog for more information on how Esri is helping data users prepare for the impacts of differential privacy.

The population of the world, allocated to 1 arcsecond blocks. This refines CIESIN’s Gridded Population of the World project, using machine learning models on high-resolution worldwide Digital Globe satellite imagery. More information.

There is also a tiled version of this dataset that may be easier to use if you are interested in many countries.

The population of the world, allocated to 1 arcsecond blocks. This refines CIESIN’s Gridded Population of the World project, using machine learning models on high-resolution worldwide Digital Globe satellite imagery. More information.

There is also a tiled version of this dataset that may be easier to use if you are interested in many countries.

In a matter of days we have used my customizable software package to grow O.T.I.'s Facebook page likes from 10k to almost 18k likes. From the graph presented in the updated pdf, you can clearly see the impact our training phase had on the advertising performance, showcasing how the software package's suggestions increased/decreased page engagement.

Once the training phase was completed a sharp increase in page likes, fan enagement, and shares was observed. An increase in external online traffic at the website and blog, as well as offline traffic was also observed.

We will be putting together a full report on this software once we have completed our investigation.

It is versatile, and our results suggest that it can be customized to any page producing any content. We have used similar generic engines, powered by neural networks, to locate patterns in other areas of science (reaction prediction software). The key to our work is a series of custom neural networks. A group to locate patterns, and another series of groups for additional pattern analysis once key parameters have been identified.

This software package has significant commercial value and utilizes novel concepts in computer science/probability that will not be described publicly for proprietary reasons.