About this dataset

Context

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

Key observations

The largest age group in Miles, TX was for the group of age 15 to 19 years years with a population of 152 (12.99%), according to the ACS 2019-2023 5-Year Estimates. At the same time, the smallest age group in Miles, TX was the 85 years and over years with a population of 5 (0.43%). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates

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 in consideration
• Population: The population for the specific age group in the Miles is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of Miles 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 Miles Population by Age. You can refer the same here

**This data set was last updated 3:30 PM ET Monday, January 4, 2021. The last date of data in this dataset is December 31, 2020. **

Overview

Data shows that mobility declined nationally since states and localities began shelter-in-place strategies to stem the spread of COVID-19. The numbers began climbing as more people ventured out and traveled further from their homes, but in parallel with the rise of COVID-19 cases in July, travel declined again.

This distribution contains county level data for vehicle miles traveled (VMT) from StreetLight Data, Inc, updated three times a week. This data offers a detailed look at estimates of how much people are moving around in each county.

Data available has a two day lag - the most recent data is from two days prior to the update date. Going forward, this dataset will be updated by AP at 3:30pm ET on Monday, Wednesday and Friday each week.

This data has been made available to members of AP’s Data Distribution Program. To inquire about access for your organization - publishers, researchers, corporations, etc. - please click Request Access in the upper right corner of the page or email kromano@ap.org. Be sure to include your contact information and use case.

Findings

• Nationally, data shows that vehicle travel in the US has doubled compared to the seven-day period ending April 13, which was the lowest VMT since the COVID-19 crisis began. In early December, travel reached a low not seen since May, with a small rise leading up to the Christmas holiday.
• Average vehicle miles traveled continues to be below what would be expected without a pandemic - down 38% compared to January 2020. September 4 reported the largest single day estimate of vehicle miles traveled since March 14.
• New Jersey, Michigan and New York are among the states with the largest relative uptick in travel at this point of the pandemic - they report almost two times the miles traveled compared to their lowest seven-day period. However, travel in New Jersey and New York is still much lower than expected without a pandemic. Other states such as New Mexico, Vermont and West Virginia have rebounded the least. ## About This Data The county level data is provided by StreetLight Data, Inc, a transportation analysis firm that measures travel patterns across the U.S.. The data is from their Vehicle Miles Traveled (VMT) Monitor which uses anonymized and aggregated data from smartphones and other GPS-enabled devices to provide county-by-county VMT metrics for more than 3,100 counties. The VMT Monitor provides an estimate of total vehicle miles travelled by residents of each county, each day since the COVID-19 crisis began (March 1, 2020), as well as a change from the baseline average daily VMT calculated for January 2020. Additional columns are calculations by AP.

Included Data

01_vmt_nation.csv - Data summarized to provide a nationwide look at vehicle miles traveled. Includes single day VMT across counties, daily percent change compared to January and seven day rolling averages to smooth out the trend lines over time.

02_vmt_state.csv - Data summarized to provide a statewide look at vehicle miles traveled. Includes single day VMT across counties, daily percent change compared to January and seven day rolling averages to smooth out the trend lines over time.

03_vmt_county.csv - Data providing a county level look at vehicle miles traveled. Includes VMT estimate, percent change compared to January and seven day rolling averages to smooth out the trend lines over time.

Additional Data Queries

* Filter for specific state - filters 02_vmt_state.csv daily data for specific state.

* Filter counties by state - filters 03_vmt_county.csv daily data for counties in specific state.

* Filter for specific county - filters 03_vmt_county.csv daily data for specific county.

Interactive

The AP has designed an interactive map to show percent change in vehicle miles traveled by county since each counties lowest point during the pandemic:

@(https://interactives.ap.org/vmt-map/)

Interactive Embed Code

Using the Data

This data can help put your county's mobility in context with your state and over time. The data set contains different measures of change - daily comparisons and seven day rolling averages. The rolling average allows for a smoother trend line for comparison across counties and states. To get the full picture, there are also two available baselines - vehicle miles traveled in January 2020 (pre-pandemic) and vehicle miles traveled at each geography's low point during the pandemic.

Caveats

• The data from StreetLight Data, Inc does not include data for some low-population counties with low VMT (<5,000 miles/day in their baseline month of January 2020). In our analyses, we only include the 2,779 counties that have daily data for the entire period (March 1, 2020 to current).
• In some cases, a lack of decline in mobility from March to April can indicate that movement in the county is essential to keeping the larger economy going or that residents need to drive further to reach essentials businesses like grocery stores compared to other counties.
• The VMT includes both passenger and commercial miles, so truck traffic is included. However, the proxy is based on the "total number of trip starts and ends for all devices whose most frequent location is in this county". It does not count the VMT of trucks cutting through a county.
• For those instances where travel begins in one county and ends in another, the county where the miles are recorded is always the vehicle’s home county. ###### Contact reporter Angeliki Kastanis at akastanis@ap.org.

About this dataset

Context

The dataset tabulates the Miles population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Miles across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2022, the population of Miles was 908, a 1.57% increase year-by-year from 2021. Previously, in 2021, Miles population was 894, an increase of 1.94% compared to a population of 877 in 2020. Over the last 20 plus years, between 2000 and 2022, population of Miles increased by 57. In this period, the peak population was 908 in the year 2022. The numbers suggest that the population has not reached its peak yet and is showing a trend of further growth. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2022

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2022)
• Population: The population for the specific year for the Miles is shown in this column.
• Year on Year Change: This column displays the change in Miles population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. 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 Miles Population by Year. You can refer the same here

About this dataset

Context

The dataset tabulates the population of Miles by gender, including both male and female populations. This dataset can be utilized to understand the population distribution of Miles across both sexes and to determine which sex constitutes the majority.

Key observations

There is a slight majority of male population, with 52.81% of total population being male. Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

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

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis. No further analysis is done on the data reported from the Census Bureau.

Variables / Data Columns

• Gender: This column displays the Gender (Male / Female)
• Population: The population of the gender in the Miles is shown in this column.
• % of Total Population: This column displays the percentage distribution of each gender as a proportion of Miles 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 Miles Population by Race & Ethnicity. You can refer the same here

Graph and download economic data for Moving 12-Month Total Vehicle Miles Traveled (M12MTVUSM227NFWA) from Dec 1970 to Jun 2025 about miles, travel, vehicles, and USA.

These data represent the centerline and measured increments at hundredths, tenths and whole miles, along the centerline of the Colorado River beginning at Glen Canyon Dam near Page, Arizona and terminating near the inflow s of Lake Mead in the Grand Canyon region of Arizona, USA. The centerline was digitized using Color Infra-Red (CIR) orthophotography collected in March 2000 as source information and a LiDAR-derived river shoreline representing 8,000 cubic feet per second (CFS)as the defined extent of the river. Every effort was made to follow the main flow of the river while keeping the line approximately equidistant from both shorelines. The centerline feature class has been created to more accurately map locations along the Colorado River downstream of the Glen Canyon Dam. River miles and river kilometers were developed from measurements along this line. The incremental point feature classes were derived from the centerline of the Colorado River datasets. Specifically, the points were generated from nodes extracted from the centerline endpoints of the tenth mile line feature class. The Grand Canyon Monitoring and Research Center (GCMRC) river mileage was cross-checked with commercially available river guides and always fell within one mile of the guides, usually corresponding within a half mile. Additionally, these data were subjected to internal review by GCMRC scientists and commercial boatmen with decades of river travel experience on the Colorado River. River Mile 0 was measured from the USGS concrete gage and cableway at Lees Ferry, Arizona -- as per the Colorado River Compact of 1922 -- with negative river mile numbers used in Glen Canyon and positive river mile numbers downstream in Marble and Grand Canyons. These data were updated in March 2015 using newer ortho-rectified imagery collected in May of 2009 and 2013, both at approximately 8,000 CFS. Due to extended drought conditions that have persisted in the U.S. Southwest, lake levels have dropped dramatically, especially at Lake Mead. A stretch of the Colorado River corridor that was part of Lake Mead in year 2000 has returned to a flowing river once again, and with a different channel that has not previously existed. All changes to the original centerline are downstream of River Mile 260 which is just upstream of Quartermaster Canyon in western Grand Canyon. New river miles and river kilometers were developed from this updated centerline.

The NCHS National Post-acute and Long-term Care Study (NPALS) collects data on post-acute and long-term care providers every two years. The goal is to monitor post-acute and long-term care settings with reliable, accurate, relevant, and timely statistical information to support and inform policy, research, and practice. These data tables provide an overview of the geographic, organizational, staffing, service provision, and user characteristics of paid, regulated long-term and post-acute care providers in the United States. The settings include adult day services centers, home health agencies, hospices, inpatient rehabilitation facilities, long-term care hospitals, and nursing homes.

WIND Toolkit Long-term Ensemble Dataset (WTK-LED), an updated version of the meteorological WIND Toolkit, is a meteorological dataset providing high-resolution time series, including interannual variability and model uncertainty of wind speed at every modeling grid point to indicate ranges of possible wind speeds. The data were produced using the Weather Research and Forecasting Model (WRF). The vertical grid used in WTK-LED includes many vertical layers in the atmospheric boundary layer to provide information of atmospheric quantities across the rotor layer of utility scale and distributed wind turbines. The WTK-LED includes: (1) Numerical simulations of wind speed and other meteorological variables covering the contiguous United States (CONUS) and Alaska, with high-resolution (5-minute [min], 2-kilometer [km]) data for 3 years (2018-2020): WTK-LED CONUS, WTK-LED Alaska. (2) Climate simulations from Argonne National Laboratory covering North America, including Alaska, Canada, and most of Mexico and the Caribbean islands. These simulations complement the new WTK-LED to offer a 4-km, hourly dataset covering 20 years (2001-2020): WTK-LED Climate. (3) Specific long-term, high-resolution offshore simulations have been conducted separately for the U.S. coasts, Hawaii, and the Great Lakes, leading to the 2023 National Offshore Wind dataset: NOW-23. The data for Hawaii include land-based data and are part of WTK-LED Hawaii. Because the accuracy of simulations from a mesoscale model, such as WRF, varies depending on the location and weather situation, and can reach up to several m/s for wind speed, we provide simulated wind speed uncertainty estimates to the community to be used in conjunction with the deterministic model simulations. This dataset was developed to satisfy a wide group of stakeholders across various wind energy disciplines, including but not limited to stakeholders in the distributed and utility scale wind industry, the new emerging airborne wind energy field, grid integration, power systems modeling, environmental modeling, and researchers in academia, and to close some of the gaps that current public datasets have. Based on our validation results to date, we suggest use cases and applications for each dataset of the WTK-LED as shown in "WTK-LED Use Cases" resource below.

About this dataset

Context

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

Key observations

The percent distribution of Miles population by race (across all racial categories recognized by the U.S. Census Bureau): 94.47% are white, 0.75% are some other race and 4.77% are multiracial.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 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 Miles
• Population: The population of the racial category (excluding ethnicity) in the Miles is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Miles 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 Miles Population by Race & Ethnicity. You can refer the same here

These data were compiled to examine how climate change affects biocrust recovery from both physical and climate-induced disturbance. Objective(s) of our study were to uncover the trajectory of biological soil crust communities and soil stability following distrubance and under warming. These data represent biological soil crust surveys under 5 treatments at three sites. These data were collected at three sites: Arches National Park, Canyonlands National Park and Castle Valley. Data collection for a physical disturbance experiment where annual human-trampling occurred at the sites in Arches and Canyonlands began in 1996 and was concluded in 2018. Data collection for a 13-year full-factorial in situ climate manipulation experiment (undisturbed control, warming, altered precipitation, warming + altered precipitation) in Castle Valley began in 2005 and was concluded in 2018. These data were collected by U.S. Geological Survey technicians using field surveys of biological soil crusts and soil stability. These data can be used to track biological soil crust communities and soil stability through time under climate manipulation and physical disturbance treatments.

Rangelands have immense inherent spatial and temporal variability, yet assessments of land condition and trends are often assessed relative to the condition of a limited number of representative points. Ecological Potential (EP) data are spatially comprehensive, quantitative, and needed as a baseline for comparison of current rangeland vegetation conditions, trends, and management targets. We define EP as the potential fractional cover of vegetation components bare ground, herbaceous, litter, shrub, and sagebrush represented in the least disturbed and most productive portion of the western U.S. This dataset enables: 1) setting realistic expectations for restoration and management targets at 30-meter resolution, 2) better understanding of the extent of vegetation departure from potential and 3) improved spatial understanding of vegetation composition and productivity variation. We produce EP maps across rangelands in the Western U.S. by training regression tree models in ecologically intact sites. The independent variables in these models include digital soils, topography data, six bimonthly composites of the 90th percentile of NDVI, and the associated spectral bands from the 1985-2018 Landsat archive. The study area encompasses all or part of 17 states and a vast range of biophysical conditions, vegetation conditions, and disturbance history. The region is 3,006,071 km2, of which 2,060,962 km2 was rangeland.

Foreign purchases and sales of long term domestic and foreign securities by type. Data column titles correspond to column titles in Treasury Bulletin Table CM-VI-4, excluding CM-VI-4 columns (1) and (8). Refer to CNTRYCDS.TXT file for "Cntry Code" identification. All amounts in millions of dollars.

Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline data along open-ocean sandy shores of the conterminous United States and parts of Alaska and Hawaii under the National Assessment of Shoreline Change project. There is no widely accepted standard for analyzing shoreline change. Existing shoreline data measurements and rate calculation methods vary from study to study and prevent combining results into state-wide or regional assessments. The impetus behind the National Assessment project was to develop a standardized method of measuring changes in shoreline position that is consistent from coast to coast. The goal was to facilitate the process of periodically and systematically updating the results in an internally consistent manner.

About this dataset

Context

The dataset presents median household incomes for various household sizes in Miles, TX, as reported by the U.S. Census Bureau. The dataset highlights the variation in median household income with the size of the family unit, offering valuable insights into economic trends and disparities within different household sizes, aiding in data analysis and decision-making.

Key observations

• Of the 7 household sizes (1 person to 7-or-more person households) reported by the census bureau, Miles did not include 5, 6, or 7-person households. Across the different household sizes in Miles the mean income is $63,859, and the standard deviation is $26,447. The coefficient of variation (CV) is 41.41%. This high CV indicates high relative variability, suggesting that the incomes vary significantly across different sizes of households.
• In the most recent year, 2021, The smallest household size for which the bureau reported a median household income was 1-person households, with an income of $37,607. It then further increased to $100,370 for 4-person households, the largest household size for which the bureau reported a median household income.

https://i.neilsberg.com/ch/miles-tx-median-household-income-by-household-size.jpeg" alt="Miles, TX median household income, by household size (in 2022 inflation-adjusted dollars)">

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Household Sizes:

• 1-person households
• 2-person households
• 3-person households
• 4-person households
• 5-person households
• 6-person households
• 7-or-more-person households

Variables / Data Columns

• Household Size: This column showcases 7 household sizes ranging from 1-person households to 7-or-more-person households (As mentioned above).
• Median Household Income: Median household income, in 2022 inflation-adjusted dollars for the specific household size.

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 Miles median household income. You can refer the same here

About this dataset

Context

The dataset tabulates the Miles City population by gender and age. The dataset can be utilized to understand the gender distribution and demographics of Miles City.

Content

The dataset constitues the following two datasets across these two themes

• Miles City, MT Population Breakdown by Gender
• Miles City, MT Population Breakdown by Gender and Age

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/.

About this dataset

Context

The dataset tabulates the Miles population by gender and age. The dataset can be utilized to understand the gender distribution and demographics of Miles.

Content

The dataset constitues the following two datasets across these two themes

• Miles, TX Population Breakdown by Gender
• Miles, TX Population Breakdown by Gender and Age

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/.

About this dataset

Context

The dataset presents the distribution of median household income among distinct age brackets of householders in Miles. Based on the latest 2019-2023 5-Year Estimates from the American Community Survey, it displays how income varies among householders of different ages in Miles. It showcases how household incomes typically rise as the head of the household gets older. The dataset can be utilized to gain insights into age-based household income trends and explore the variations in incomes across households.

Key observations: Insights from 2023

In terms of income distribution across age cohorts, in Miles, the median household income stands at $130,682 for householders within the 25 to 44 years age group, followed by $78,750 for the 45 to 64 years age group. Notably, householders within the 65 years and over age group, had the lowest median household income at $58,750.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.

Age groups classifications include:

• Under 25 years
• 25 to 44 years
• 45 to 64 years
• 65 years and over

Variables / Data Columns

• Age Of The Head Of Household: This column presents the age of the head of household
• Median Household Income: Median household income, in 2023 inflation-adjusted dollars for the specific age group

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 Miles median household income by age. You can refer the same here

About this dataset

Context

The dataset tabulates the data for the Miles, IA population pyramid, which represents the Miles population distribution across age and gender, using estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 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 Miles, IA, is 25.9.
• Old-age dependency ratio, which is the number of persons aged 65 or over per 100 persons aged 15-64, for Miles, IA, is 40.6.
• Total dependency ratio for Miles, IA is 66.5.
• Potential support ratio, which is the number of youth (working age population) per elderly, for Miles, IA is 2.5.

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

About this dataset

Context

The dataset presents the distribution of median household income among distinct age brackets of householders in Miles. Based on the latest 2017-2021 5-Year Estimates from the American Community Survey, it displays how income varies among householders of different ages in Miles. It showcases how household incomes typically rise as the head of the household gets older. The dataset can be utilized to gain insights into age-based household income trends and explore the variations in incomes across households.

Key observations: Insights from 2021

In terms of income distribution across age cohorts, in Miles, householders within the 25 to 44 years age group have the highest median household income at $65,869, followed by those in the 45 to 64 years age group with an income of $65,080. Meanwhile householders within the under 25 years age group report the second lowest median household income of $54,721. Notably, householders within the 65 years and over age group, had the lowest median household income at $37,832.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2022-inflation-adjusted dollars.

Age groups classifications include:

• Under 25 years
• 25 to 44 years
• 45 to 64 years
• 65 years and over

Variables / Data Columns

• Age Of The Head Of Household: This column presents the age of the head of household
• Median Household Income: Median household income, in 2022 inflation-adjusted dollars for the specific age group

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 Miles median household income by age. You can refer the same here

About this dataset

Context

The dataset tabulates the data for the Long Grove, IA population pyramid, which represents the Long Grove 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 Long Grove, IA, is 31.0.
• Old-age dependency ratio, which is the number of persons aged 65 or over per 100 persons aged 15-64, for Long Grove, IA, is 48.9.
• Total dependency ratio for Long Grove, IA is 79.9.
• Potential support ratio, which is the number of youth (working age population) per elderly, for Long Grove, IA is 2.0.

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