https://en.wikipedia.org/wiki/Public_domainhttps://en.wikipedia.org/wiki/Public_domain
The Colleges and Universities feature class/shapefile is composed of all Post Secondary Education facilities as defined by the Integrated Post Secondary Education System (IPEDS, http://nces.ed.gov/ipeds/), National Center for Education Statistics (NCES, https://nces.ed.gov/), US Department of Education for the 2018-2019 school year. Included are Doctoral/Research Universities, Masters Colleges and Universities, Baccalaureate Colleges, Associates Colleges, Theological seminaries, Medical Schools and other health care professions, Schools of engineering and technology, business and management, art, music, design, Law schools, Teachers colleges, Tribal colleges, and other specialized institutions. Overall, this data layer covers all 50 states, as well as Puerto Rico and other assorted U.S. territories. This feature class contains all MEDS/MEDS+ as approved by the National Geospatial-Intelligence Agency (NGA) Homeland Security Infrastructure Program (HSIP) Team. Complete field and attribute information is available in the ”Entities and Attributes” metadata section. Geographical coverage is depicted in the thumbnail above and detailed in the "Place Keyword" section of the metadata. This feature class does not have a relationship class but is related to Supplemental Colleges. Colleges and Universities that are not included in the NCES IPEDS data are added to the Supplemental Colleges feature class when found. This release includes the addition of 175 new records, the removal of 468 no longer reported by NCES, and modifications to the spatial location and/or attribution of 6682 records.
This dataset provides information for Academic Years 2017-2021 which included: By College and VCCS System:
1) Annual Headcount and FTEs 2) Gender (categories are: Female & Male; Unknown may be inferred) 3) Ethnicity (categories are: American Indian & Alaskan Native, Asian, Black & African-American, Native Hawaiian & Pacific Islander, Hispanic, Two or More Races, Unknown/Not Specified, and White) 4) Age (categories are: 17 and Under, 18-19, 20-21, 22-24, 25-29, 30-34, 35-39, 40-49, 50-64, & 65 and Over) 5) 18-Month Outcomes for Dual-Enrolled High School Grads by Year (categories are: Total Grads, Continued in any Higher Ed program, Employed with no Higher Ed, and Unknown) 6) 18-Month Outcomes for VCCS Graduates by Year (categories are: Total Grads, Continued at VCCS, Transferred to a 4yr college, Employed with no Higher Ed, and Unknown)
For Fiscal Years 2018-2021, by Service Area and VCCS System:
1) Fast Forward Credentialers Employed by Fiscal Year (categories are: Total Distinct Students, Employed within 6 Months, Employed within 12 Months, and Employed within 18 Months)
Notes:
1) Headcounts are Unduplicated student counts.
2) One FTE represents 30 credit hours of classes taken by a student over an academic year and is calculated on an annual basis by taking the total credit hours taught divided by 30.
3) 2017 Fiscal Year Fast Forward data was not included as it was considered incomplete- the Fast Forward program began in 2017 and did not encompass all areas for the entire year.
4) In Workforce (Fast Forward data) the service region for the Richmond Metro Area is called CCWA (Community College Workforce Alliance) and combines data for Brightpoint and J Sargeant Reynolds.
4a) Therefore, there are no Reynolds data entries for Fast Forward variables. All CCWA data is listed under Brightpoint for this portion of the data set.
5) 18-Month Outcomes for Fast Forward Credentialers are cumulative (6 months to 12 months to 18 months)
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This dataset tracks annual american indian student percentage from 2009 to 2024 for community colleges in the state of Vermont
This dataset contains locations and attributes of University and College, created as part of the DC Geographic Information System (DC GIS) for the Office of the Chief Technology Officer (OCTO) and participating D.C. government agencies. Information provided by OCTO, EMA, and other sources identified as University Areas and DC GIS staff geo-processed the data. This layer does not represent university areas contained in the campus plans from the DC Office of Zoning.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This dataset tracks annual american indian student percentage from 2007 to 2024 for community colleges in the state of North Dakota
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 College Corner. 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 College Corner. 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 College Corner, where there exist only two delineated age groups, the median household income is $68,125 for householders within the 45 to 64 years age group, compared to $52,917 for the 65 years and over 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 College Corner 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 tabulates the College Corner 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 College Corner. The dataset can be utilized to understand the population distribution of College Corner by age. For example, using this dataset, we can identify the largest age group in College Corner.
Key observations
The largest age group in College Corner, OH was for the group of age 30 to 34 years years with a population of 37 (11.31%), according to the ACS 2019-2023 5-Year Estimates. At the same time, the smallest age group in College Corner, OH was the 80 to 84 years years with a population of 2 (0.61%). 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 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 College Corner Population 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 tabulates the College Park 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 College Park. The dataset can be utilized to understand the population distribution of College Park by age. For example, using this dataset, we can identify the largest age group in College Park.
Key observations
The largest age group in College Park, MD was for the group of age 20 to 24 years years with a population of 9,287 (27%), according to the ACS 2019-2023 5-Year Estimates. At the same time, the smallest age group in College Park, MD was the 85 years and over years with a population of 225 (0.65%). 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 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 College Park Population 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 tabulates the North College Hill 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 North College Hill. The dataset can be utilized to understand the population distribution of North College Hill by age. For example, using this dataset, we can identify the largest age group in North College Hill.
Key observations
The largest age group in North College Hill, OH was for the group of age 5-9 years with a population of 1,102 (11.47%), according to the 2021 American Community Survey. At the same time, the smallest age group in North College Hill, OH was the 80-84 years with a population of 68 (0.71%). 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 North College Hill Population 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
This dataset tracks annual american indian student percentage from 2008 to 2023 for community colleges in the state of New Mexico
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the College Station 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 College Station. The dataset can be utilized to understand the population distribution of College Station by age. For example, using this dataset, we can identify the largest age group in College Station.
Key observations
The largest age group in College Station, TX was for the group of age 20 to 24 years years with a population of 32,962 (26.96%), according to the ACS 2019-2023 5-Year Estimates. At the same time, the smallest age group in College Station, TX was the 85 years and over years with a population of 764 (0.62%). 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 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 College Station Population 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
This dataset tracks annual american indian student percentage from 2008 to 2023 for community colleges in the state of Utah
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 Rutherford College. Based on the latest 2018-2022 5-Year Estimates from the American Community Survey, it displays how income varies among householders of different ages in Rutherford College. 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 2022
In terms of income distribution across age cohorts, in Rutherford College, the median household income stands at $76,191 for householders within the 45 to 64 years age group, followed by $64,477 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 $24,164.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 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 Rutherford College 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
This dataset tracks annual american indian student percentage from 2014 to 2024 for community colleges in the state of Mississippi
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset presents the median household incomes over the past decade across various racial categories identified by the U.S. Census Bureau in State College. It portrays the median household income of the head of household across racial categories (excluding ethnicity) as identified by the Census Bureau. It also showcases the annual income trends, between 2013 and 2023, providing insights into the economic shifts within diverse racial communities.The dataset can be utilized to gain insights into income disparities and variations across racial categories, aiding in data analysis and decision-making..
Key observations
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Racial categories include:
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 State College median household income by race. 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
This dataset tracks annual american indian student percentage from 2008 to 2024 for community colleges in the state of Missouri
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This dataset tracks annual american indian student percentage from 2012 to 2024 for Iowa Western Community College vs. Iowa
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This dataset tracks annual american indian student percentage from 2009 to 2023 for Treasure Valley Community College vs. Oregon
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This dataset tracks annual american indian student percentage from 2018 to 2024 for Holmes Community College vs. Mississippi
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This dataset tracks annual american indian student percentage from 2008 to 2024 for community colleges in the state of Kansas
https://en.wikipedia.org/wiki/Public_domainhttps://en.wikipedia.org/wiki/Public_domain
The Colleges and Universities feature class/shapefile is composed of all Post Secondary Education facilities as defined by the Integrated Post Secondary Education System (IPEDS, http://nces.ed.gov/ipeds/), National Center for Education Statistics (NCES, https://nces.ed.gov/), US Department of Education for the 2018-2019 school year. Included are Doctoral/Research Universities, Masters Colleges and Universities, Baccalaureate Colleges, Associates Colleges, Theological seminaries, Medical Schools and other health care professions, Schools of engineering and technology, business and management, art, music, design, Law schools, Teachers colleges, Tribal colleges, and other specialized institutions. Overall, this data layer covers all 50 states, as well as Puerto Rico and other assorted U.S. territories. This feature class contains all MEDS/MEDS+ as approved by the National Geospatial-Intelligence Agency (NGA) Homeland Security Infrastructure Program (HSIP) Team. Complete field and attribute information is available in the ”Entities and Attributes” metadata section. Geographical coverage is depicted in the thumbnail above and detailed in the "Place Keyword" section of the metadata. This feature class does not have a relationship class but is related to Supplemental Colleges. Colleges and Universities that are not included in the NCES IPEDS data are added to the Supplemental Colleges feature class when found. This release includes the addition of 175 new records, the removal of 468 no longer reported by NCES, and modifications to the spatial location and/or attribution of 6682 records.