All data in Population and Demographic Census Data, grouped by reporting segment. For data grouped by overall segment, see Overall Segments for Population and Demographic Census Data.

This profile is designed to accompany the Joint Strategic Needs Assessment (JSNA) chapter on Demographics, which looks at segmenting the borough’s population by their most significant health and social care need. This supplement looks at adults (aged 18 and over) instead of the overall population, because the health and social care need segments covered in this section are more common in adults.

A shapefile representing greater sage-grouse (hereafter sage-grouse) space use and lek abundance in the Bi-State Distinct Population Segment (DPS) of California and Nevada. These data were derived by combining a kernel density estimation of sage-grouse lek abundance combined with another raster representing distance to lek. The 85 percent isopleth was then used to define "high space-use."

About this dataset

Context

The dataset tabulates the data for the Jersey City, NJ population pyramid, which represents the Jersey City 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 Jersey City, NJ, is 24.4.
• Old-age dependency ratio, which is the number of persons aged 65 or over per 100 persons aged 15-64, for Jersey City, NJ, is 16.5.
• Total dependency ratio for Jersey City, NJ is 40.9.
• Potential support ratio, which is the number of youth (working age population) per elderly, for Jersey City, NJ is 6.1.

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 Jersey City population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Jersey City for the selected age group is shown in the following column.
• Population (Female): The female population in the Jersey City for the selected age group is shown in the following column.
• Total Population: The total population of the Jersey City 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 Jersey City Population by Age. You can refer the same here

How does your organization use this dataset? What other NYSERDA or energy-related datasets would you like to see on Open NY? Let us know by emailing OpenNY@nyserda.ny.gov. The Low- to Moderate-Income (LMI) New York State (NYS) Census Population Analysis dataset is resultant from the LMI market database designed by APPRISE as part of the NYSERDA LMI Market Characterization Study (https://www.nyserda.ny.gov/lmi-tool). All data are derived from the U.S. Census Bureau’s American Community Survey (ACS) 1-year Public Use Microdata Sample (PUMS) files for 2013, 2014, and 2015. Each row in the LMI dataset is an individual record for a household that responded to the survey and each column is a variable of interest for analyzing the low- to moderate-income population. The LMI dataset includes: county/county group, households with elderly, households with children, economic development region, income groups, percent of poverty level, low- to moderate-income groups, household type, non-elderly disabled indicator, race/ethnicity, linguistic isolation, housing unit type, owner-renter status, main heating fuel type, home energy payment method, housing vintage, LMI study region, LMI population segment, mortgage indicator, time in home, head of household education level, head of household age, and household weight. The LMI NYS Census Population Analysis dataset is intended for users who want to explore the underlying data that supports the LMI Analysis Tool. The majority of those interested in LMI statistics and generating custom charts should use the interactive LMI Analysis Tool at https://www.nyserda.ny.gov/lmi-tool. This underlying LMI dataset is intended for users with experience working with survey data files and producing weighted survey estimates using statistical software packages (such as SAS, SPSS, or Stata).

About this dataset

Context

The dataset tabulates the population of Section by race. It includes the population of Section across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of Section across relevant racial categories.

Key observations

The percent distribution of Section population by race (across all racial categories recognized by the U.S. Census Bureau): 89.78% are white, 1.80% are American Indian and Alaska Native, 0.30% are Asian, 6.21% are some other race and 1.90% are multiracial.

Content

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

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race: This column displays the racial categories (excluding ethnicity) for the Section
• Population: The population of the racial category (excluding ethnicity) in the Section is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Section total population. Please note that the sum of all percentages may not equal one due to rounding of values.

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 Section Population by Race & Ethnicity. You can refer the same here

The global market size of Population Health Management Platforms is $XX million in 2018 with XX CAGR from 2014 to 2018, and it is expected to reach $XX million by the end of 2024 with a CAGR of XX% from 2019 to 2024.
Global Population Health Management Platforms Market Report 2019 - Market Size, Share, Price, Trend and Forecast is a professional and in-depth study on the current state of the global Population Health Management Platforms industry. The key insights of the report:
1.The report provides key statistics on the market status of the Population Health Management Platforms manufacturers and is a valuable source of guidance and direction for companies and individuals interested in the industry.
2.The report provides a basic overview of the industry including its definition, applications and manufacturing technology.
3.The report presents the company profile, product specifications, capacity, production value, and 2013-2018 market shares for key vendors.
4.The total market is further divided by company, by country, and by application/type for the competitive landscape analysis.
5.The report estimates 2019-2024 market development trends of Population Health Management Platforms industry.
6.Analysis of upstream raw materials, downstream demand, and current market dynamics is also carried out
7.The report makes some important proposals for a new project of Population Health Management Platforms Industry before evaluating its feasibility.
There are 4 key segments covered in this report: competitor segment, product type segment, end use/application segment and geography segment.
For competitor segment, the report includes global key players of Population Health Management Platforms as well as some small players.
The information for each competitor includes:
* Company Profile
* Main Business Information
* SWOT Analysis
* Sales, Revenue, Price and Gross Margin
* Market Share

For product type segment, this report listed main product type of Population Health Management Platforms market
* Product Type I
* Product Type II
* Product Type III

For end use/application segment, this report focuses on the status and outlook for key applications. End users sre also listed.
* Application I
* Application II
* Application III

For geography segment, regional supply, application-wise and type-wise demand, major players, price is presented from 2013 to 2023. This report covers following regions:
* North America
* South America
* Asia & Pacific
* Europe
* MEA (Middle East and Africa)
The key countries in each region are taken into consideration as well, such as United States, China, Japan, India, Korea, ASEAN, Germany, France, UK, Italy, Spain, CIS, and Brazil etc.

Reasons to Purchase this Report:
* Analyzing the outlook of the market with the recent trends and SWOT analysis
* Market dynamics scenario, along with growth opportunities of the market in the years to come
* Market segmentation analysis including qualitative and quantitative research incorporating the impact of economic and non-economic aspects
* Regional and country level analysis integrating the demand and supply forces that are influencing the growth of the market.
* Market value (USD Million) and volume (Units Million) data for each segment and sub-segment
* Competitive landscape involving the market share of major players, along with the new projects and strategies adopted by players in the past five years
* Comprehensive company profiles covering the product offerings, key financial information, recent developments, SWOT analysis, and strategies employed by the major market players
* 1-year analyst support, along with the data support in excel format.
We also can offer customized report to fulfill special requirements of our clients. Regional and Countries report can be provided as well.

Concept: Total of branches from the banking segment divided by the country's adult population estimation for the year, calculated by IBGE, and multiplied by ten thousand

Snapshot img

Population Health Management Market Size and Forecast 2025-2029

The population health management market size estimates the market to reach by USD 19.40 billion, at a CAGR of 10.7% between 2024 and 2029. North America is expected to account for 68% of the growth contribution to the global market during this period. In 2019 the software segment was valued at USD 16.04 billion and has demonstrated steady growth since then.

    Report Coverage


    Details




    Base year


    2024




    Historic period

    2019-2023



    Forecast period


    2025-2029



    Market structure
    Fragmented



    Market growth 2025-2029


    USD 19.40 billion






The market is experiencing significant growth, driven by the increasing adoption of healthcare IT and the rising focus on personalized medicine. Healthcare providers are recognizing the value of population health management platforms in improving patient outcomes and reducing costs. The implementation of these systems enables proactive care management, disease prevention, and population health analysis. However, the market faces challenges as well. The cost of installing population health management platforms can be a significant barrier for smaller healthcare organizations. Additionally, ensuring data security and interoperability across various systems remains a major concern.
Effective data management and integration are essential for population health management to deliver its full potential. Companies seeking to capitalize on market opportunities must address these challenges and provide cost-effective, secure, and interoperable solutions. By focusing on these areas, they can help healthcare providers optimize their population health management initiatives and improve patient care.

What will be the Size of the Population Health Management Market during the forecast period?

Explore in-depth regional segment analysis with market size data - historical 2019-2023 and forecasts 2025-2029 - in the full report.
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The market continues to evolve, driven by advancements in technology and a growing focus on value-based care. Risk adjustment models, which help account for the variability in health risks among patient populations, are increasingly being adopted to improve care coordination and health outcome measures. For instance, a leading healthcare organization implemented risk stratification models, resulting in a 20% reduction in hospital readmissions. Remote patient monitoring, public health surveillance, and disease outbreak response are crucial applications of population health management. These technologies enable real-time health data collection, allowing for early intervention and improved health equity initiatives. Chronic disease management, a significant focus area, benefits from electronic health records, care coordination models, and health information exchange.

Value-based care programs, predictive modeling healthcare, and telehealth platforms are transforming the landscape of healthcare delivery. Healthcare data analytics, interoperability standards, and population health dashboards facilitate data-driven decision-making, enhancing health intervention efficacy. Behavioral health integration and preventive health services are gaining prominence, with health literacy programs and clinical decision support tools supporting personalized medicine strategies. The market is expected to grow at a robust rate, with industry growth estimates reaching 15% annually. This growth is fueled by the ongoing need for healthcare cost reduction, quality improvement initiatives, and the integration of technology into healthcare delivery.

How is this Population Health Management Industry segmented?

The population health management industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

Component

  Software
  Services


End-user

  Large enterprises
  SMEs


Delivery Mode

  On-Premise
  Cloud-Based
  Web-Based


End-Use

  Providers
  Payers
  Employer Groups
  Government Bodies


Geography

  North America

    US
    Canada


  Europe

    France
    Germany
    Italy
    UK


  APAC

    China
    India
    Japan
    South Korea


  Rest of World (ROW)

By Component Insights

The software segment is estimated to witness significant growth during the forecast period.

The market's software segment is experiencing significant growth and innovation, driven by various components that enhance healthcare organizations' capacity to manage and enhance the health outcomes of diverse populations. Population health management platforms aggregate and integrate data from multiple sources, includin

Summary Tape File (STF) 1 consists of four sets of computer-readable data files containing detailed tabulations of the nation's population and housing characteristics produced from the 1980 Census. This series is comprised of STF 1A, STF 1B, STF 1C, and STF 1D. All files in the STF 1 series are identical, containing 321 substantive data variables organized in the form of 59 "tables," as well as standard geographic identification variables. All of the data items contained in the STF 1 files were tabulated from the "complete count" or "100-percent" questions included on the 1980 Census questionnaire. All four groups of files within the STF 1 series have identical record formats and technical characteristics and differ only in the types of geographical areas for which the summarized data items are presented. STF 1A provides summaries for state or state equivalent, county or county equivalent, minor civil division/census county division (MCD/CCD), place or place segment within MCD/CCD or remainder of MCD/CCD, census tract or block numbering area (BNA) or untracted segment within place, place segment or remainder or MCD/CCD, and block group (BG) or BG segment or enumeration district (ED). This file contains 57 data files, one for each state, the District of Columbia, Puerto Rico, and the United States possessions, which include American Samoa, Guam, Northern Mariana Islands, the Trust Territory of the Pacific Islands, and the Virgin Islands. The information on the United States possessions is similar but not identical to the other data and is documented in a separate codebook. Puerto Rico is also documented by a separate codebook.

Saint Martin population density for 400m H3 hexagons.

Built from Kontur Population: Global Population Density for 400m H3 Hexagons Vector H3 hexagons with population counts at 400m resolution.

Fixed up fusion of GHSL, Facebook, Microsoft Buildings, Copernicus Global Land Service Land Cover, Land Information New Zealand, and OpenStreetMap data.

Constrained estimates, total number of people per grid-cell. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The units are number of people per pixel. The mapping approach is Random Forest-based dasymetric redistribution.

More information can be found in the Release Statement

The difference between constrained and unconstrained is explained on this page: https://www.worldpop.org/methods/top_down_constrained_vs_unconstrained

Snapshot img

US Senior Living Market Size 2025-2029

The senior living market in US size is forecast to increase by USD 30.58 billion at a CAGR of 5.9% between 2024 and 2029.

The senior living market is experiencing significant growth due to various driving factors. One of the primary factors is the aging population, as the number of seniors continues to increase, the demand for services is also rising. Another key trend is the integration of technology into senior living facilities, which enhances the quality of care and improves the overall living experience for seniors. Innovations in artificial intelligence, data analytics, predictive modeling, and personalized care plans are disrupting traditional care models and improving overall financial sustainability through cost containment and value-based care. However, affordability remains a challenge for many seniors and their families, as the cost of services can be prohibitive. This report provides a comprehensive analysis of these factors and more, offering insights into the current state and future direction of the market.

What will be the Size of the Market During the Forecast Period?

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The market encompasses a range of services designed to address the unique needs of an aging population, including long-term care, end-of-life care, palliative care, hospice care, respite care, adult day care, home health services, geriatric care, and various forms of cognitive and behavioral health support. This market is driven by demographic trends, with the global population of individuals aged 65 and above projected to reach 1.5 billion by 2050. 


Key challenges in this market include addressing cognitive decline, social isolation, fall prevention, medication management, nutritional support, mobility assistance, personal care assistance, continence management, and other aspects of daily living. Additionally, there is a growing focus on quality of life, resident satisfaction, staffing ratios, caregiver training, technology adoption, and regulatory compliance. The aging services network is evolving to provide a continuum of care, from independent living to palliative care, with a focus on evidence-based practices, industry best practices, and regulatory compliance.

How is this market segmented, and which is the largest segment?

The market research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments. Service TypeAssisted livingIndependent livingCCRCAge GroupAge 85 and olderAge 66-84Age 65 and underBy TypeMedical ServicesNon-Medical ServicesDistribution ChannelDirect SalesAgency ReferralsOnline PlatformsEnd-UserBaby BoomersSilent GenerationGen XGeographyUS

By Service Type Insights

The assisted living segment is estimated to witness significant growth during the forecast period. Assisted living communities cater to seniors who require assistance with daily activities but do not necessitate full-time nursing care. These residences offer a combination of personalized care, social engagement, and medical support in a secure and comfortable setting. The market is experiencing growth due to the expanding aging population, rising life expectancy, and a preference for home-like environments over traditional nursing homes. Personalized care services are a defining feature of assisted living. Residents receive aid with activities of daily living, such as bathing, dressing, grooming, medication management, and mobility assistance, based on their individual needs.
Trained staff members are available 24/7 to ensure the safety and well-being of residents. Memory care communities are a specialized segment within assisted living, designed for seniors with Alzheimer's disease and other forms of dementia. These facilities provide secure environments and specialized care techniques to address the unique needs of these residents. Independent living communities offer seniors the opportunity to live in a social, active environment while maintaining their independence. These communities provide housing solutions with minimal support services, such as meal preparation and housekeeping. Nursing care homes and skilled nursing facilities offer comprehensive care for seniors with chronic health conditions and complex care needs.

Get a glance at the market report of share of various segments Request Free Sample

Market Dynamics

Our researchers analyzed the data with 2024 as the base year, along with the key drivers, trends, and challenges. A holistic analysis of drivers will help companies refine their marketing strategies to gain a competitive advantage.

What are the key market drivers leading to the rise in adoption of US Senior Living Market?

An aging population is the key driver of the market. The market in the US is experiencing significant grow

In 2021, the share of the Mexican population who identified themselves to be part of the LGBTQ community accounted for *** percent by taking into consideration their sexual preference, gender identity or both.

Abstract (en): Summary File 4 (SF 4) from the United States 2000 Census contains the sample data, which is the information compiled from the questions asked of a sample of all people and housing units. Population items include basic population totals: urban and rural, households and families, marital status, grandparents as caregivers, language and ability to speak English, ancestry, place of birth, citizenship status, year of entry, migration, place of work, journey to work (commuting), school enrollment and educational attainment, veteran status, disability, employment status, industry, occupation, class of worker, income, and poverty status. Housing items include basic housing totals: urban and rural, number of rooms, number of bedrooms, year moved into unit, household size and occupants per room, units in structure, year structure built, heating fuel, telephone service, plumbing and kitchen facilities, vehicles available, value of home, monthly rent, and shelter costs. In Summary File 4, the sample data are presented in 213 population tables (matrices) and 110 housing tables, identified with "PCT" and "HCT" respectively. Each table is iterated for 336 population groups: the total population, 132 race groups, 78 American Indian and Alaska Native tribe categories (reflecting 39 individual tribes), 39 Hispanic or Latino groups, and 86 ancestry groups. The presentation of SF4 tables for any of the 336 population groups is subject to a population threshold. That is, if there are fewer than 100 people (100-percent count) in a specific population group in a specific geographic area, and there are fewer than 50 unweighted cases, their population and housing characteristics data are not available for that geographic area in SF4. For the ancestry iterations, only the 50 unweighted cases test can be performed. See Appendix H: Characteristic Iterations, for a complete list of characteristic iterations. ICPSR data undergo a confidentiality review and are altered when necessary to limit the risk of disclosure. ICPSR also routinely creates ready-to-go data files along with setups in the major statistical software formats as well as standard codebooks to accompany the data. In addition to these procedures, ICPSR performed the following processing steps for this data collection: Created variable labels and/or value labels.. All persons in housing units in the District of Columbia in 2000. 2013-05-25 Multiple Census data file segments were repackaged for distribution into a single zip archive per dataset. No changes were made to the data or documentation.2006-01-12 All files were removed from dataset 342 and flagged as study-level files, so that they will accompany all downloads.2006-01-12 All files were removed from dataset 341 and flagged as study-level files, so that they will accompany all downloads.2006-01-12 All files were removed from dataset 340 and flagged as study-level files, so that they will accompany all downloads.2006-01-12 All files were removed from dataset 339 and flagged as study-level files, so that they will accompany all downloads.2006-01-12 All files were removed from dataset 338 and flagged as study-level files, so that they will accompany all downloads. Because of the number of files per state in Summary File 4, ICPSR has given each state its own ICPSR study number in the range ICPSR 13512-13563. The study number for the national file is 13570. Data for each state are being released as they become available.The data are provided in 38 segments (files) per iteration. These segments are PCT1-PCT4, PCT5-PCT16, PCT17-PCT34, PCT35-PCT37, PCT38-PCT45, PCT46-PCT49, PCT50-PCT61, PCT62-PCT67, PCT68-PCT71, PCT72-PCT76, PCT77-PCT78, PCT79-PCT81, PCT82-PCT84, PCT85-PCT86 (partial), PCT86 (partial), PCT87-PCT103, PCT104-PCT120, PCT121-PCT131, PCT132-PCT137, PCT138-PCT143, PCT144, PCT145-PCT150, PCT151-PCT156, PCT157-PCT162, PCT163-PCT208, PCT209-PCT213, HCT1-HCT9, HCT10-HCT18, HCT19-HCT22, HCT23-HCT25, HCT26-HCT29, HCT30-HCT39, HCT40-HCT55, HCT56-HCT61, HCT62-HCT70, HCT71-HCT81, HCT82-HCT86, and HCT87-HCT110. The iterations are Parts 1-336, the Geographic Header File is Part 337. The Geographic Header File is in fixed-format ASCII and the table files are in comma-delimited ASCII format. A merged iteration will have 7,963 variables.For Parts 251-336, the part names contain numbers within parentheses that refer to the Ancestry Code List (page G1 of the codebook).

Network screening analysis data of urban road segments in Pennsylvania completed in 2024; includes roadways inside of urban area boundaries with a population of more than 5,000 people. Data can be filtered by county, planning partner and engineering district.Notes from the PennDOT HSNS Video https://www.youtube.com/watch?v=liXTnqxZjCgNetwork screening analysis can be used for safety analysis and decision making to decrease frequency and severity of crashes in Pennsylvania.Network screening is a method from the Highway Safety Manual (HSM) that compares expected crash frequencies and crash severities to historical crash data based on Part C of HSM. It helps evaluate facilities and identify and prioritize locations that are likely to respond to safety improvement investments. FHWA states that employing traditional networking screening with systemic safety analysis can be an agency’s first step toward a comprehensive safety management program. The network screening is the first step in the Roadway Safety Management Process (Part B of the HSM) and it considers crash history, roadway factors and traffic characteristics.Roadway Safety Management Process (Part B of the HSM) Steps Network Screening Diagnosis Select Countermeasures Economic Appraisal Prioritize Projects Safety effectiveness evaluationRoadway safety management process parallels the method by which PennDOT selects and evaluates projects for Federal Highway Safety Improvement Program.SPF: safety performance functionPositive/high excess cost locations are good candidates for safety improvements.Urban: sites within urban boundaries (Census) where population is more than 5,000 people.Rural: sites outside of urban boundaries (Census) where population is less than 5,000 people.Crashes within 250 feet of an intersection are assigned to the intersection for analysis.

About this dataset

Context

The dataset tabulates the Chevy Chase Section Three 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 Chevy Chase Section Three. The dataset can be utilized to understand the population distribution of Chevy Chase Section Three by age. For example, using this dataset, we can identify the largest age group in Chevy Chase Section Three.

Key observations

The largest age group in Chevy Chase Section Three, MD was for the group of age 10 to 14 years years with a population of 180 (17.54%), according to the ACS 2018-2022 5-Year Estimates. At the same time, the smallest age group in Chevy Chase Section Three, MD was the 20 to 24 years years with a population of 14 (1.36%). Source: U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 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 in consideration
• Population: The population for the specific age group in the Chevy Chase Section Three is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of Chevy Chase Section Three total population. Please note that the sum of all percentages may not equal one due to rounding of values.

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 Chevy Chase Section Three Population by Age. You can refer the same here

Economically Active Population Survey: Population 16 years of age and over by sex, study segment to 2 digits and level of education attained. National. Population 16 years of age and over by level of education attained, studies segment to 2 digits and sex.

Concept: Total of branches from the banking segment divided by the region's adult population estimation for the year, calculated by IBGE, and multiplied by ten thousand

Concept: Total of electronic service outposts (PAE) from the banking segment, divided by the region's adult population estimation for the year, calculated by IBGE, and multiplied by ten thousand