Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset presents the detailed breakdown of the count of individuals within distinct income brackets, categorizing them by gender (men and women) and employment type - full-time (FT) and part-time (PT), offering valuable insights into the diverse income landscapes within North Carolina. The dataset can be utilized to gain insights into gender-based income distribution within the North Carolina population, 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.
Income brackets:
Variables / Data Columns
Employment type classifications include:
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 Carolina 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 diversity score from 2016 to 2023 for North Carolina Cyber Academy School District vs. North Carolina
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This dataset tracks annual diversity score from 2019 to 2023 for East Carolina Community School District vs. North Carolina
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Despite nearly a century of study, the diversity of marine fungi remains poorly understood. Historical surveys utilizing microscopy or culture-dependent methods suggest that marine fungi are relatively species-poor, predominantly Dikarya, and localized to coastal habitats. However, the use of high-throughput sequencing technologies to characterize microbial communities has challenged traditional concepts of fungal diversity by revealing novel phylotypes from both terrestrial and aquatic habitats. Here, I used ion semiconductor sequencing (Ion Torrent) of the ribosomal large subunit (LSU/28S) to explore fungal diversity from water and sediment samples collected from four habitats in coastal North Carolina. The dominant taxa observed were Ascomycota and Chytridiomycota, though all fungal phyla were represented. Diversity was highest in sand flats and wetland sediments, though benthic sediments harbored the highest proportion of novel sequences. Most sequences assigned to early-diverging fungal groups could not be assigned beyond phylum with statistical support, suggesting they belong to unknown lineages.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This dataset tracks annual diversity score from 2005 to 2023 for Rashkis Elementary School vs. North Carolina and Chapel Hill-Carrboro City Schools School District
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This dataset tracks annual diversity score from 1991 to 2023 for Durham School District vs. North Carolina
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This dataset tracks annual diversity score from 1991 to 2023 for Hertford County Schools School District vs. North Carolina
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This dataset tracks annual diversity score from 2013 to 2023 for Research Triangle High School District vs. North Carolina
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This dataset tracks annual diversity score from 2003 to 2023 for Gray Stone Day School District vs. North Carolina
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This dataset tracks annual diversity score from 1991 to 2023 for North Carolina
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This dataset tracks annual diversity score from 1993 to 2023 for Riverside High School vs. North Carolina and Durham School District
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This dataset tracks annual diversity score from 1999 to 2023 for The Learning Center School District vs. North Carolina
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This dataset tracks annual diversity score from 1991 to 2023 for Person County Schools School District vs. North Carolina
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This dataset tracks annual diversity score from 2002 to 2023 for Greenlee Primary vs. North Carolina and Mitchell County Schools School District
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This dataset tracks annual diversity score from 1991 to 2023 for Pisgah High School vs. North Carolina and Haywood County Schools School District
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This dataset tracks annual diversity score from 2011 to 2023 for Powhatan Elementary School vs. North Carolina and Johnston County School District
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This dataset tracks annual diversity score from 1991 to 2023 for Waccamaw vs. North Carolina and Brunswick County Schools School District
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This dataset tracks annual diversity score from 1991 to 2023 for Montgomery County Schools School District vs. North Carolina
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This dataset tracks annual diversity score from 1991 to 2023 for Orange County Schools School District vs. North Carolina
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This dataset tracks annual diversity score from 1991 to 2023 for Plain View Primary vs. North Carolina and Bladen County Schools School District
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset presents the detailed breakdown of the count of individuals within distinct income brackets, categorizing them by gender (men and women) and employment type - full-time (FT) and part-time (PT), offering valuable insights into the diverse income landscapes within North Carolina. The dataset can be utilized to gain insights into gender-based income distribution within the North Carolina population, 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.
Income brackets:
Variables / Data Columns
Employment type classifications include:
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 Carolina median household income by race. You can refer the same here