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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 United States 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 United States. The dataset can be utilized to understand the population distribution of United States by age. For example, using this dataset, we can identify the largest age group in United States.
Key observations
The largest age group in United States was for the group of age 25-29 years with a population of 22,854,328 (6.93%), according to the 2021 American Community Survey. At the same time, the smallest age group in United States was the 80-84 years with a population of 5,932,196 (1.80%). 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 United States Population by Age. You can refer the same here
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TwitterMIT Licensehttps://opensource.org/licenses/MIT
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The dataset, "Heart Attack in Youth vs. Adults in America", contains 500,000 synthetic records detailing health, lifestyle, and demographic factors contributing to heart attack risks among youth and adults in the United States. This dataset can help researchers and data enthusiasts analyze patterns, predict risk levels, and understand disparities between age groups and regions in terms of heart health.
Insights Beginners, Intermediate, and Advanced Users Can Derive:
For Beginners:
Descriptive Statistics:
Calculate average cholesterol levels or blood pressure for youth vs. adults. Determine the distribution of heart attack risk levels across different states or demographics.
Data Visualization:
Visualize the distribution of obesity indices across age groups. Plot the survival rates based on risk levels.
For Intermediate Users:
Exploratory Data Analysis (EDA):
Investigate the correlation between lifestyle factors (e.g., dietary habits, smoking history) and heart attack risk levels. Compare access to healthcare between low-income and high-income groups.
Predictive Modeling:
Build a logistic regression or decision tree model to predict high-risk individuals. Use clustering techniques to group individuals based on heart attack risks.
For Advanced Users:
Deep Analysis and Insights:
Perform a time series analysis on hospital visits and prior heart attacks. Use advanced ML algorithms (e.g., Gradient Boosting, Neural Networks) for risk prediction and survival rate forecasting.
Feature Engineering:
Create new features, such as BMI categories or healthcare accessibility indices. Analyze the interaction effects between physical activity, obesity index, and smoking history.
Explainable AI:
Use SHAP (SHapley Additive exPlanations) to understand model predictions. Identify biases in predictions related to ethnicity or access to healthcare.
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TwitterBy US Open Data Portal, data.gov [source]
This dataset contains the age-standardized stroke mortality rate in the United States from 2013 to 2015, by state/territory, county, gender and race/ethnicity. The data source is the highly respected National Vital Statistics System. The rates are reported as a 3-year average and have been age-standardized. Moreover, county rates are spatially smoothed for further accuracy. The interactive map of heart disease and stroke produced by this dataset provides invaluable information about the geographic disparities in stroke mortality across America at different scales - county, state/territory and national. By using the adjustable filter settings provided in this interactive map, you can quickly explore demographic details such as gender (Male/Female) or race/ethnicity (e.g Non-Hispanic White). Conquer your fear of unknown with evidence! Investigate these locations now to inform meaningful action plans for greater public health resilience in America and find out if strokes remain a threat to our millions of citizens every day! Updated regularly since 2020-02-26, so check it out now!
For more datasets, click here.
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The US Age-Standardized Stroke Mortality Rates (2013-2015) by State/County/Gender/Race dataset provides valuable insights into stroke mortality rates among adults ages 35 and over in the USA between 2013 and 2015. This dataset contains age-standardized data from the National Vital Statistics System at the state, county, gender, and race level. Use this guide to learn how best use this dataset for your purposes!
Understand the Data
This dataset provides information about stroke mortality rates among adult Americans aged 35+. The data is collected from 2013 to 2015 in three year averages. Even though it is possible to view county level data, spatial smoothing techniques have been applied here. The following columns of data are provided: - Year – The year of the data collection - LocationAbbr – The abbreviation of location where the data was collected
- LocationDesc – A description of this location
- GeographicLevel – Geographic level of granularity where these numbers are recorded * DataSource - source of these statistics * Class - class or group into which these stats fall * Topic - overall topic on which we have stats * Data_Value - age standardized value associated with each row * Data_Value_Unit - units associated with each value * Stratification1– First stratification defined for a given row * Stratification2– Second stratification defined for a given rowAdditionally, several other footnotes fields such as ‘Data_value_Type’; ‘Data_Value_Footnote _Symbol’; ‘StratificationCategory1’ & ‘StratificatoinCategory2’ etc may be present accordingly .## Exploring Correlations
Now that you understand what individual columns mean it should take no time to analyze correlations within different categories using standard statistical methods like linear regressions or boxplots etc. If you want to compare different regions , then you can use
LocationAbbrcolumn with locations reduced geographical levels such asStateorRegion. Alternatively if one wants comparisons across genders then they can refer column labelledStratifacation1alongwith their desired values within this
- Creating a visualization to show the relationship between stroke mortality and specific variations in race/ethnicity, gender, and geography.
- Comparing two or more states based on their average stroke mortality rate over time.
- Building a predictive model that disregards temporal biases to anticipate further changes in stroke mortality for certain communities or entire states across the US
If you use this dataset in your research, please credit the original authors. Data Source
Unknown License - Please check the dataset description for more information.
File: csv-1.csv | Column name | Description | |:--...
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Graph and download economic data for Infra-Annual Labor Statistics: Working-Age Population Total: From 15 to 64 Years for United States (LFWA64TTUSM647S) from Jan 1977 to Aug 2025 about working-age, 15 to 64 years, population, and USA.
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TwitterBackground Investigating the validity of the self-reported values of weight allows for the proper assessment of studies using questionnaire-derived data. The study examined the accuracy of gender-specific self-reported weight in a sample of adults. The effects of age, education, race and ethnicity, income, general health and medical status on the degree of discrepancy (the difference between self-reported weight and measured weight) are similarly considered. Methods The analysis used data from the US Third National Health and Nutrition Examination Survey. Self-reported and measured weights were abstracted and analyzed according to sex, age, measured weight, self-reported weight, and body mass index (BMI). A proportional odds model was applied. Results The weight discrepancy was positively associated with age, and negatively associated with measured weight and BMI. Ordered logistic regression modeling showed age, race-ethnicity, education, and BMI to be associated with the degree of discrepancy in both sexes. In men, additional predictors were consumption of more than 100 cigarettes and the desire to change weight. In women, marital status, income, activity level, and the number of months since the last doctor's visit were important. Conclusions Predictors of the degree of weight discrepancy are gender-specific, and require careful consideration when examined.
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TwitterBy US Open Data Portal, data.gov [source]
This dataset contains stroke mortality data among US adults (35+) by state/territory and county. Learn more about the health of people within your own state or region, across genders and ethnicities. Reliable statistics even for small counties can be seen, thanks to 3-year averages, age-standardization, and spatial smoothing. Data sources such as the National Vital Statistics System give you all the data you need to get a detailed sense of your population's total cardiovascular health. With interactive maps created from this data also provided covering heart disease risks, death rates and hospital bed availability across each location in America, you can now gain a powerful perspective on how effective healthcare initiatives are making an impact in those who live there. Study up on the real cardiovascular conditions plaguing those around us today to make a real change in public health!
For more datasets, click here.
- 🚨 Your notebook can be here! 🚨!
This dataset contains stroke mortality data among US adults (35+) by state/territory and county. This data can be useful in helping identify areas where stroke mortality is high, and interventions to reduce mortality should be taken into account.
To access the dataset, you need to download it from Kaggle. The dataset consists of 18 columns including year, location description, geographic level, source of data, class of data values provided, topic of discussion with regard to stroke mortality rates (age-standardized), labels for stratification categories and stratifications used within the given age group when performing this analysis. The last 3 columns consist of geographical coordinates for each location (Y_lat & X_lon) as well as an overall georeferenced column (Georeferenced Column).
Once you have downloaded the dataset there are a few ways you can go about using it:
- You can perform a descriptive analysis on any particular column using methods such as summary statistics or distributions graphs;
- You can create your own maps or other visual representation based on the latitude/longitude columns;
- You could look at differences between states and counties/areas within states by subsetting out certain areas;
- Using statistical testing methods you could create inferential analyses that may lead to insights on why some areas seem more prone to higher levels of stroke mortality than others
- Track county-level stroke mortality trends among US adults (35+) over time.
- Identify regions of higher stroke mortality risk and use that information to inform targeted, preventative health policies and interventions.
- Analyze differences in stroke mortality rates by gender, race/ethnicity, or geographic location to identify potential disparities in care access or outcomes for certain demographic groups
If you use this dataset in your research, please credit the original authors. Data Source
Unknown License - Please check the dataset description for more information.
File: csv-1.csv | Column name | Description | |:-------------------------------|:---------------------------------------------------------| | Year | Year of the data. (Integer) | | LocationAbbr | Abbreviation of the state or territory. (String) | | LocationDesc | Name of the state or territory. (String) | | GeographicLevel | Level of geographic detail. (String) | | DataSource | Source of the data. (String) | | Class | Classification of the data. (String) | | Topic | Topic of the data. (String) | | Data_Value | Numeric value associated with the topic. (Float) | | Data_Value_Unit | Unit used to express the data value. (String) | | Data_Value_Type | Type of data value. (String) | | Data_Value_Footnote_Symbol | Symbol associated with the data value footnote. (String) | | StratificationCategory1 | First category of stratification. (String) | | Stratification1 | First stratifica...
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TwitterThis dataset documents rates and trends in local hypertension-related cardiovascular disease (CVD) death rates. Specifically, this report presents county (or county equivalent) estimates of hypertension-related CVD death rates in 2000-2019 and trends during two intervals (2000-2010, 2010-2019) by age group (ages 35–64 years, ages 65 years and older), race/ethnicity (non-Hispanic American Indian/Alaska Native, non-Hispanic Asian/Pacific Islander, non-Hispanic Black, Hispanic, non-Hispanic White), and sex (female, male). The rates and trends were estimated using a Bayesian spatiotemporal model and a smoothed over space, time, and demographic group. Rates are age-standardized in 10-year age groups using the 2010 US population. Data source: National Vital Statistics System.
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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 Boston population by age cohorts (Children: Under 18 years; Working population: 18-64 years; Senior population: 65 years or more). It lists the population in each age cohort group along with its percentage relative to the total population of Boston. The dataset can be utilized to understand the population distribution across children, working population and senior population for dependency ratio, housing requirements, ageing, migration patterns etc.
Key observations
The largest age group was 18 - 64 years with a poulation of 487,505 (72.46% of the total population). 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 cohorts:
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 Boston Population by Age. You can refer the same here
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TwitterAs of June 2024, 99 percent of adults in the United States between 18 and 49 years were internet users, making it the age group with the highest level of internet penetration in the country. A further share of 97 percent of adults using the internet were between 18 and 29 years old. Mobile internet usage Mobile internet usage continues to surge in the United States, with 96.2 percent of internet users accessing the web via phones as of the third quarter of 2023. In April 2024, YouTube's mobile app led with a 74 percent audience reach, while TikTok topped weekly engagement among social apps. Mobile apps and privacy Mobile apps became an essential part of mobile users, this high usage raised new concerns about data privacy. By June 2023, three in four internet users supported data localization to protect their information. Additionally, As of September 2024, 13.5 percent of paid iOS apps stated that they collected user data, with 88 percent of this data used to enhance app functionality.
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TwitterA survey carried out in 2021 revealed how important having more control over personal data is to adults in the United States. A third of respondents said this was extremely important to them, another third said it was very important, and roughly ** percent said it was moderately important. Just *** percent said having more control over personal data and how it is shared was not at all important to them. Most Americans worry about falling victim to cybercrime When asked in a 2020 survey to name crimes they were most afraid of, the majority of American respondents claimed to be more worried about cybercrimes than having their home broken into or car stolen. The top two concerns were having personal financial information stolen by hackers, and being the victim of identity theft. This is unsurprising, considering the rise in data breaches and exposed records over the past decade. In the United States alone, *** billion data breaches were reported in 2017 - the highest figure to date. It is likely that this figure was somewhat impacted by the infamous Yahoo! data breach scandal that year, where * billion user accounts worldwide were compromised. This has been recognized as one of the largest breaches of its kind in history. IT security market on the rise As a direct result of increasing security demands and rising concerns, more companies than ever before are investing in cyber security, both in the form of services and technology. The information security technology market is booming, and as a result worldwide spend is predicted to hit nearly *** billion U.S. dollars by 2024, a ** billion dollar increase from one year prior.
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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 Norwood Young America population by age cohorts (Children: Under 18 years; Working population: 18-64 years; Senior population: 65 years or more). It lists the population in each age cohort group along with its percentage relative to the total population of Norwood Young America. The dataset can be utilized to understand the population distribution across children, working population and senior population for dependency ratio, housing requirements, ageing, migration patterns etc.
Key observations
The largest age group was 18 - 64 years with a poulation of 2,370 (61.75% of the total population). 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 cohorts:
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 Norwood Young America Population by Age. You can refer the same here
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Context
The dataset tabulates the Many population by age cohorts (Children: Under 18 years; Working population: 18-64 years; Senior population: 65 years or more). It lists the population in each age cohort group along with its percentage relative to the total population of Many. The dataset can be utilized to understand the population distribution across children, working population and senior population for dependency ratio, housing requirements, ageing, migration patterns etc.
Key observations
The largest age group was 18 - 64 years with a poulation of 1,395 (59.69% of the total population). 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 cohorts:
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 Many Population by Age. You can refer the same here
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Context
The dataset tabulates the Florida City population by age cohorts (Children: Under 18 years; Working population: 18-64 years; Senior population: 65 years or more). It lists the population in each age cohort group along with its percentage relative to the total population of Florida City. The dataset can be utilized to understand the population distribution across children, working population and senior population for dependency ratio, housing requirements, ageing, migration patterns etc.
Key observations
The largest age group was 18 to 64 years with a poulation of 7,199 (56.28% of the total population). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Age cohorts:
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 Florida City Population by Age. You can refer the same here
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Context
The dataset tabulates the American Fork population by age cohorts (Children: Under 18 years; Working population: 18-64 years; Senior population: 65 years or more). It lists the population in each age cohort group along with its percentage relative to the total population of American Fork. The dataset can be utilized to understand the population distribution across children, working population and senior population for dependency ratio, housing requirements, ageing, migration patterns etc.
Key observations
The largest age group was 18 to 64 years with a poulation of 21,078 (59.69% of the total population). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Age cohorts:
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 American Fork Population by Age. You can refer the same here
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Context
The dataset tabulates the Azusa population by age cohorts (Children: Under 18 years; Working population: 18-64 years; Senior population: 65 years or more). It lists the population in each age cohort group along with its percentage relative to the total population of Azusa. The dataset can be utilized to understand the population distribution across children, working population and senior population for dependency ratio, housing requirements, ageing, migration patterns etc.
Key observations
The largest age group was 18 to 64 years with a poulation of 33,154 (67.22% of the total population). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Age cohorts:
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 Azusa Population by Age. You can refer the same here
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License information was derived automatically
Context
The dataset tabulates the American Falls population by age cohorts (Children: Under 18 years; Working population: 18-64 years; Senior population: 65 years or more). It lists the population in each age cohort group along with its percentage relative to the total population of American Falls. The dataset can be utilized to understand the population distribution across children, working population and senior population for dependency ratio, housing requirements, ageing, migration patterns etc.
Key observations
The largest age group was 18 - 64 years with a poulation of 2,510 (55.40% of the total population). 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 cohorts:
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 American Falls Population by Age. You can refer the same here
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License information was derived automatically
Context
The dataset tabulates the Florida population by age cohorts (Children: Under 18 years; Working population: 18-64 years; Senior population: 65 years or more). It lists the population in each age cohort group along with its percentage relative to the total population of Florida. The dataset can be utilized to understand the population distribution across children, working population and senior population for dependency ratio, housing requirements, ageing, migration patterns etc.
Key observations
The largest age group was 18 to 64 years with a poulation of 12.99 million (59.25% of the total population). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Age cohorts:
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 Florida Population by Age. You can refer the same here
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License information was derived automatically
Context
The dataset tabulates the California population by age cohorts (Children: Under 18 years; Working population: 18-64 years; Senior population: 65 years or more). It lists the population in each age cohort group along with its percentage relative to the total population of California. The dataset can be utilized to understand the population distribution across children, working population and senior population for dependency ratio, housing requirements, ageing, migration patterns etc.
Key observations
The largest age group was 18 to 64 years with a poulation of 2,646 (58.50% of the total population). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Age cohorts:
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 California Population by Age. You can refer the same here
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Context
The dataset tabulates the Black population by age cohorts (Children: Under 18 years; Working population: 18-64 years; Senior population: 65 years or more). It lists the population in each age cohort group along with its percentage relative to the total population of Black. The dataset can be utilized to understand the population distribution across children, working population and senior population for dependency ratio, housing requirements, ageing, migration patterns etc.
Key observations
The largest age group was 18 to 64 years with a poulation of 214 (46.32% of the total population). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Age cohorts:
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 Black Population by Age. You can refer the same here
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Context
The dataset tabulates the Palm Beach population by age cohorts (Children: Under 18 years; Working population: 18-64 years; Senior population: 65 years or more). It lists the population in each age cohort group along with its percentage relative to the total population of Palm Beach. The dataset can be utilized to understand the population distribution across children, working population and senior population for dependency ratio, housing requirements, ageing, migration patterns etc.
Key observations
The largest age group was 65 years and over with a poulation of 5,735 (62.11% of the total population). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Age cohorts:
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 Palm Beach Population by Age. You can refer the same here
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Context
The dataset tabulates the United States 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 United States. The dataset can be utilized to understand the population distribution of United States by age. For example, using this dataset, we can identify the largest age group in United States.
Key observations
The largest age group in United States was for the group of age 25-29 years with a population of 22,854,328 (6.93%), according to the 2021 American Community Survey. At the same time, the smallest age group in United States was the 80-84 years with a population of 5,932,196 (1.80%). 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 United States Population by Age. You can refer the same here