In 2023, about 12.7 percent of the population in West Virginia was between the ages of 65 and 74 years old. A further 12.6 percent of the population was between the ages of 45 and 54 years old in that same year.
In 2023, the median household income in West Virginia amounted to 60,410 U.S. dollars. This is an increase from the previous year, when the median household income in the state amounted to 52,460 U.S. dollars. The median household income for the United States may be accessed here.
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Graph and download economic data for Median Household Income in West Virginia (MEHOINUSWVA646N) from 1984 to 2023 about WV, households, median, income, and USA.
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Context
The dataset presents the median household income across different racial categories in West Virginia. It portrays the median household income of the head of household across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to gain insights into economic disparities and trends and explore the variations in median houshold income for diverse racial categories.
Key observations
Based on our analysis of the distribution of West Virginia population by race & ethnicity, the population is predominantly White. This particular racial category constitutes the majority, accounting for 90.90% of the total residents in West Virginia. Notably, the median household income for White households is $58,553. Interestingly, despite the White population being the most populous, it is worth noting that Native Hawaiian and Other Pacific Islander households actually reports the highest median household income, with a median income of $135,156. This reveals that, while Whites may be the most numerous in West Virginia, Native Hawaiian and Other Pacific Islander households experience greater economic prosperity in terms of median household income.
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 West Virginia median household income by race. You can refer the same here
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U.S. Census Bureau QuickFacts statistics for Lewis County, West Virginia. QuickFacts data are derived from: Population Estimates, American Community Survey, Census of Population and Housing, Current Population Survey, Small Area Health Insurance Estimates, Small Area Income and Poverty Estimates, State and County Housing Unit Estimates, County Business Patterns, Nonemployer Statistics, Economic Census, Survey of Business Owners, Building Permits.
In 2023, 16.7 percent of West Virginia's population lived below the poverty line. This was a decrease from the previous year, when about 17.9 percent of the state's population lived below the poverty line. The poverty rate of the United States since 1990 can be accessed 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 population of West Virginia by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for West Virginia. The dataset can be utilized to understand the population distribution of West Virginia by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in West Virginia. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for West Virginia.
Key observations
Largest age group (population): Male # 60-64 years (61,942) | Female # 60-64 years (66,387). 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:
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.
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 West Virginia Population by Gender. You can refer the same here
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License information was derived automatically
U.S. Census Bureau QuickFacts statistics for Morgan County, West Virginia. QuickFacts data are derived from: Population Estimates, American Community Survey, Census of Population and Housing, Current Population Survey, Small Area Health Insurance Estimates, Small Area Income and Poverty Estimates, State and County Housing Unit Estimates, County Business Patterns, Nonemployer Statistics, Economic Census, Survey of Business Owners, Building Permits.
This dataset is a polygon coverage of counties limited to the extent of the Pocahontas No. 3 coal bed resource areas and attributed with statistics on these coal quality parameters: ash yield (percent), sulfur (percent), SO2 (lbs per million Btu), calorific value (Btu/lb), arsenic (ppm) content and mercury (ppm) content. The file has been generalized from detailed geologic coverages found elsewhere in Professional Paper 1625-C. The attributes were generated from public data found in the geochemical dataset found in Chap. H, Appendix 2, Disc 1. Please see the metadata file found in Chap. H, Appendix 3, Disc 1, for more detailed information on the geochemical attributes. The county statistical data used for this data set are found in Tables 6-9 and 21-22 in Chap. H, Disc 1. Additional county geochemical statistics for other parameters are found in Tables 10-20, Chap. H, Disc 1.
In 2023, 3.2 percent of West Virginia residents were Black or African American. A further 90.1 percent of the population were white, and five percent of West Virginia residents were of two or more races in that same year.
The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Census tracts are small, relatively permanent statistical subdivisions of a county or equivalent entity, and were defined by local participants as part of the 2020 Census Participant Statistical Areas Program. The Census Bureau delineated the census tracts in situations where no local participant existed or where all the potential participants declined to participate. The primary purpose of census tracts is to provide a stable set of geographic units for the presentation of census data and comparison back to previous decennial censuses. Census tracts generally have a population size between 1,200 and 8,000 people, with an optimum size of 4,000 people. When first delineated, census tracts were designed to be homogeneous with respect to population characteristics, economic status, and living conditions. The spatial size of census tracts varies widely depending on the density of settlement. Physical changes in street patterns caused by highway construction, new development, and so forth, may require boundary revisions. In addition, census tracts occasionally are split due to population growth, or combined as a result of substantial population decline. Census tract boundaries generally follow visible and identifiable features. They may follow legal boundaries such as minor civil division (MCD) or incorporated place boundaries in some States and situations to allow for census tract-to-governmental unit relationships where the governmental boundaries tend to remain unchanged between censuses. State and county boundaries always are census tract boundaries in the standard census geographic hierarchy. In a few rare instances, a census tract may consist of noncontiguous areas. These noncontiguous areas may occur where the census tracts are coextensive with all or parts of legal entities that are themselves noncontiguous. For the 2010 Census, the census tract code range of 9400 through 9499 was enforced for census tracts that include a majority American Indian population according to Census 2000 data and/or their area was primarily covered by federally recognized American Indian reservations and/or off-reservation trust lands; the code range 9800 through 9899 was enforced for those census tracts that contained little or no population and represented a relatively large special land use area such as a National Park, military installation, or a business/industrial park; and the code range 9900 through 9998 was enforced for those census tracts that contained only water area, no land area.
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Graph and download economic data for Employed Persons in West Virginia (LAUST540000000000005) from Jan 1976 to May 2025 about WV, household survey, employment, persons, and USA.
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License information was derived automatically
Context
The dataset presents the distribution of median household income among distinct age brackets of householders in West Virginia. 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 West Virginia. 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 West Virginia, householders within the 45 to 64 years age group have the highest median household income at $68,993, followed by those in the 25 to 44 years age group with an income of $68,704. Meanwhile householders within the 65 years and over age group report the second lowest median household income of $45,248. Notably, householders within the under 25 years age group, had the lowest median household income at $32,481.
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 West Virginia median household income by age. You can refer the same here
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A dataset listing West Virginia cities by population for 2024.
In 2019 the median annual family income in West Virginia was ****** U.S. dollars, and has been steadily increasing since 2010. Family income is the total income earned by all family members who have been living in the household for at least *** year and are at least 14 years old.
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A dataset listing West Virginia counties by population for 2024.
Employment and unemployment estimates reported from the Local Area Unemployment Statistics (LAUS) program from 2014-2-24
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U.S. Census Bureau QuickFacts statistics for Webster County, West Virginia. QuickFacts data are derived from: Population Estimates, American Community Survey, Census of Population and Housing, Current Population Survey, Small Area Health Insurance Estimates, Small Area Income and Poverty Estimates, State and County Housing Unit Estimates, County Business Patterns, Nonemployer Statistics, Economic Census, Survey of Business Owners, Building Permits.
This dataset is a polygon coverage of counties limited to the extent of the Pond Creek coal zone resource areas and attributed with statistics on these coal quality parameters: ash yield (percent), sulfur (percent), SO2 (lbs per million Btu), calorific value (Btu/lb), arsenic (ppm) content and mercury (ppm) content. The file has been generalized from detailed geologic coverages found elsewhere in Professional Paper 1625-C. The attributes were generated from public data found in geochemical dataset found in Chap. G, Appendix 7, Disc 1. Please see the detailed information on the geochemical attributes. The county statistical data used for this data set are found in Tables 2-5 and 17-18, Chap. G, Disc 1. Additional county geochemical statistics for other parameters are found in Tables 6-16, Chap. G, Disc 1.
CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automatically
U.S. Census Bureau QuickFacts statistics for Teays Valley CDP, West Virginia. QuickFacts data are derived from: Population Estimates, American Community Survey, Census of Population and Housing, Current Population Survey, Small Area Health Insurance Estimates, Small Area Income and Poverty Estimates, State and County Housing Unit Estimates, County Business Patterns, Nonemployer Statistics, Economic Census, Survey of Business Owners, Building Permits.
In 2023, about 12.7 percent of the population in West Virginia was between the ages of 65 and 74 years old. A further 12.6 percent of the population was between the ages of 45 and 54 years old in that same year.