This statistic depicts the average daily census in registered hospitals in the United States in 2019, categorized by the number of beds. During this year, the average daily census totaled ****** people for hospitals with ** to ** beds.
This dataset provides modeled predictions of PM2.5 levels from the EPA's Downscaler model. Data are at the census tract level for 2016-2020. These data are used by the CDC's National Environmental Public Health Tracking Network to generate air quality measures. Census tract-level datasets contain estimates of the mean predicted concentration and associated standard error. Please refer to the metadata attachment for more information. Learn more about outdoor air quality on the Tracking Network's website: https://ephtracking.cdc.gov/showAirLanding.action. By using these data, you signify your agreement to comply with the following requirements: 1. Use the data for statistical reporting and analysis only. 2. Do not attempt to learn the identity of any person included in the data and do not combine these data with other data for the purpose of matching records to identify individuals. 3. Do not disclose of or make use of the identity of any person or establishment discovered inadvertently and report the discovery to: trackingsupport@cdc.gov. 4. Do not imply or state, either in written or oral form, that interpretations based on the data are those of the original data sources and CDC unless the data user and data source are formally collaborating. 5. Acknowledge, in all reports or presentations based on these data, the original source of the data and CDC. 6. Suggested citation: Centers for Disease Control and Prevention. National Environmental Public Health Tracking Network. Web. Accessed: insert date. www.cdc.gov/ephtracking.
This dataset provides modeled predictions of ozone levels from the EPA's Downscaler model. Data are at the census tract level for 2011-2014. These data are used by the CDC's National Environmental Public Health Tracking Network to generate air quality measures. Census tract-level datasets contain estimates of the mean predicted concentration and associated standard error. Please refer to the metadata attachment for more information.
Learn more about outdoor air quality on the Tracking Network's website: https://ephtracking.cdc.gov/showAirLanding.action.
By using these data, you signify your agreement to comply with the following requirements: 1. Use the data for statistical reporting and analysis only. 2. Do not attempt to learn the identity of any person included in the data and do not combine these data with other data for the purpose of matching records to identify individuals. 3. Do not disclose of or make use of the identity of any person or establishment discovered inadvertently and report the discovery to: trackingsupport@cdc.gov. 4. Do not imply or state, either in written or oral form, that interpretations based on the data are those of the original data sources and CDC unless the data user and data source are formally collaborating.
This dataset is historical. For recent data, we recommend using https://chicagotraffictracker.com. -- Average Daily Traffic (ADT) counts are analogous to a census count of vehicles on city streets. These counts provide a close approximation to the actual number of vehicles passing through a given _location on an average weekday. Since it is not possible to count every vehicle on every city street, sample counts are taken along larger streets to get an estimate of traffic on half-mile or one-mile street segments. ADT counts are used by city planners, transportation engineers, real-estate developers, marketers and many others for myriad planning and operational purposes. Data Owner: Transportation. Time Period: 2006. Frequency: A citywide count is taken approximately every 10 years. A limited number of traffic counts will be taken and added to the list periodically. Related Applications: Traffic Information Interactive Map (http://webapps.cityofchicago.org/traffic/).
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Graph and download economic data for Estimate, Median Age by Sex, Total Population (5-year estimate) in Day County, SD (B01002001E046037) from 2009 to 2023 about Day County, SD; SD; age; 5-year; median; and USA.
A file containing the average daily census for county for each year displayed (e.g., daily counts are averaged and then divided by the number of days reported for that year). The population report categorizes inmates by type of offender and includes: Sentenced, Civil, Federal, Technical Parole Violators, State Readies and Other Unsentenced.
A file containing the average daily census for county for each year displayed (e.g., daily counts are averaged and then divided by the number of days reported for that year). The population report categorizes inmates by type of offender and includes: Sentenced, Civil, Federal, Technical Parole Violators, State Readies and Other Unsentenced.
CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automatically
This file details average daily census figures based on daily counts submitted by each jail to the State Commission of Correction. New York City jail population figures have been reported to the state since 2016, while data for the Non-New York City region and each county outside of the five boroughs are shown annually from 1997 onward. Data are presented in the following categories: Census, Boarded Out, Boarded In, In House, Sentenced, Civil, Federal, Technical Parole Violators, State Readies and Other Unsentenced.
Attribution 3.0 (CC BY 3.0)https://creativecommons.org/licenses/by/3.0/
License information was derived automatically
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset presents the distribution of median household income among distinct age brackets of householders in Day town. 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 Day town. 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 Day town, where there exist only two delineated age groups, the median household income is $67,750 for householders within the 65 years and over age group, compared to $37,083 for the 45 to 64 years age group.
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:
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 Day town median household income by age. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset presents the mean household income for each of the five quintiles in Day County, SD, as reported by the U.S. Census Bureau. The dataset highlights the variation in mean household income across quintiles, offering valuable insights into income distribution and inequality.
Key observations
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Income Levels:
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 Day County median household income. You can refer the same here
NOTE: This dataset has been retired and marked as historical-only.
This dataset is a companion to the COVID-19 Daily Cases and Deaths dataset (https://data.cityofchicago.org/d/naz8-j4nc). The major difference in this dataset is that the case, death, and hospitalization corresponding rates per 100,000 population are not those for the single date indicated. They are rolling averages for the seven-day period ending on that date. This rolling average is used to account for fluctuations that may occur in the data, such as fewer cases being reported on weekends, and small numbers. The intent is to give a more representative view of the ongoing COVID-19 experience, less affected by what is essentially noise in the data.
All rates are per 100,000 population in the indicated group, or Chicago, as a whole, for “Total” columns.
Only Chicago residents are included based on the home address as provided by the medical provider.
Cases with a positive molecular (PCR) or antigen test are included in this dataset. Cases are counted based on the date the test specimen was collected. Deaths among cases are aggregated by day of death. Hospitalizations are reported by date of first hospital admission. Demographic data are based on what is reported by medical providers or collected by CDPH during follow-up investigation.
Denominators are from the U.S. Census Bureau American Community Survey 1-year estimate for 2018 and can be seen in the Citywide, 2018 row of the Chicago Population Counts dataset (https://data.cityofchicago.org/d/85cm-7uqa).
All data are provisional and subject to change. Information is updated as additional details are received and it is, in fact, very common for recent dates to be incomplete and to be updated as time goes on. At any given time, this dataset reflects cases and deaths currently known to CDPH.
Numbers in this dataset may differ from other public sources due to definitions of COVID-19-related cases and deaths, sources used, how cases and deaths are associated to a specific date, and similar factors.
Data Source: Illinois National Electronic Disease Surveillance System, Cook County Medical Examiner’s Office, U.S. Census Bureau American Community Survey
Annual average daily traffic is the total volume for the year divided by 365 days. The traffic count year is from October 1st through September 30th. Very few locations in California are actually counted continuously. Traffic Counting is generally performed by electronic counting instruments moved from location throughout the State in a program of continuous traffic count sampling. The resulting counts are adjusted to an estimate of annual average daily traffic by compensating for seasonal influence, weekly variation and other variables which may be present. Annual ADT is necessary for presenting a statewide picture of traffic flow, evaluating traffic trends, computing accident rates. planning and designing highways and other purposes.Traffic Census Program Page
This dataset explores the USDA summer food service program participation by state for fiscal years 2003-2007. *Average daily attendance is reported for July only, the peak month of national program activity. Unlike participation data in the National School Lunch and School Breakfast Programs, average daily attendance is not adjusted for absenteeism. Data are subject to revision.
This dataset explores the child and adult care food program average daily attendance by state for the fiscal years 2003 - 2007.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset presents the mean household income for each of the five quintiles in Day, Wisconsin, as reported by the U.S. Census Bureau. The dataset highlights the variation in mean household income across quintiles, offering valuable insights into income distribution and inequality.
Key observations
https://i.neilsberg.com/ch/day-wi-mean-household-income-by-quintiles.jpeg" alt="Mean household income by quintiles in Day, Wisconsin (in 2022 inflation-adjusted dollars))">
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.
Income Levels:
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 Day town median household income. You can refer the same here
A file containing the average daily census for county for each year displayed (e.g., daily counts are averaged and then divided by the number of days reported for that year). The population report categorizes inmates by type of offender and includes: Sentenced, Civil, Federal, Technical Parole Violators, State Readies and Other Unsentenced.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset presents the distribution of median household income among distinct age brackets of householders in Day town. 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 Day town. 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 Day town, the median household income stands at $125,972 for householders within the 45 to 64 years age group, followed by $108,438 for the 25 to 44 years age group. Notably, householders within the 65 years and over age group, had the lowest median household income at $50,714.
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:
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 Day town median household income by age. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset presents median household incomes for various household sizes in Day Township, Michigan, 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
https://i.neilsberg.com/ch/day-township-mi-median-household-income-by-household-size.jpeg" alt="Day Township, Michigan median household income, by household size (in 2022 inflation-adjusted dollars)">
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.
Household Sizes:
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 Day township median household income. You can refer the same here
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Graph and download economic data for Mean Commuting Time for Workers (5-year estimate) in Day County, SD (B080ACS046037) from 2009 to 2023 about Day County, SD; commuting time; SD; workers; average; 5-year; and USA.
This statistic depicts the average daily census in registered hospitals in the United States in 2019, categorized by the number of beds. During this year, the average daily census totaled ****** people for hospitals with ** to ** beds.