About this dataset

Context

The dataset presents the median household income across different racial categories in Norfolk. 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 Norfolk population by race & ethnicity, the population is predominantly White. This particular racial category constitutes the majority, accounting for 44% of the total residents in Norfolk. Notably, the median household income for White households is $81,510. Interestingly, White is both the largest group and the one with the highest median household income, which stands at $81,510.

Content

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:

• 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 of the head of household: This column presents the self-identified race of the household head, encompassing all relevant racial categories (excluding ethnicity) applicable in Norfolk.
• Median household income: Median household income, adjusting for inflation, presented in 2023-inflation-adjusted dollars

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 Norfolk median household income by race. You can refer the same here

This dataset tracks annual diversity score from 1993 to 2023 for Norview High School vs. Virginia and Norfolk City School District

Diversity Data Profile for Norfolk-Virginia Beach-Newport News, VA-NC MSA
Metropolitan Quality of Life Data
ref:
http://web.archive.org/web/20150125012537/http://diversitydata-archive.org/Data/Profiles/Show.aspx?loc=909

About this dataset

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 Norfolk town. The dataset can be utilized to gain insights into gender-based income distribution within the Norfolk town population, aiding in data analysis and decision-making..

Key observations

• Employment patterns: Within Norfolk town, among individuals aged 15 years and older with income, there were 3,851 men and 3,206 women in the workforce. Among them, 2,229 men were engaged in full-time, year-round employment, while 1,364 women were in full-time, year-round roles.
• Annual income under $24,999: Of the male population working full-time, 2.78% fell within the income range of under $24,999, while 2.05% of the female population working full-time was represented in the same income bracket.
• Annual income above $100,000: 71.69% of men in full-time roles earned incomes exceeding $100,000, while 53.30% of women in full-time positions earned within this income bracket.
• Refer to the research insights for more key observations on more income brackets ( Annual income under $24,999, Annual income between $25,000 and $49,999, Annual income between $50,000 and $74,999, Annual income between $75,000 and $99,999 and Annual income above $100,000) and employment types (full-time year-round and part-time)

Content

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

Income brackets:

• $1 to $2,499 or loss
• $2,500 to $4,999
• $5,000 to $7,499
• $7,500 to $9,999
• $10,000 to $12,499
• $12,500 to $14,999
• $15,000 to $17,499
• $17,500 to $19,999
• $20,000 to $22,499
• $22,500 to $24,999
• $25,000 to $29,999
• $30,000 to $34,999
• $35,000 to $39,999
• $40,000 to $44,999
• $45,000 to $49,999
• $50,000 to $54,999
• $55,000 to $64,999
• $65,000 to $74,999
• $75,000 to $99,999
• $100,000 or more

Variables / Data Columns

• Income Bracket: This column showcases 20 income brackets ranging from $1 to $100,000+..
• Full-Time Males: The count of males employed full-time year-round and earning within a specified income bracket
• Part-Time Males: The count of males employed part-time and earning within a specified income bracket
• Full-Time Females: The count of females employed full-time year-round and earning within a specified income bracket
• Part-Time Females: The count of females employed part-time and earning within a specified income bracket

Employment type classifications include:

• Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
• Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

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 Norfolk town median household income by race. You can refer the same here

This dataset tracks annual diversity score from 1991 to 2023 for Norfolk County Agricultural vs. Massachusetts and Norfolk County Agricultural School District

This dataset tracks annual diversity score from 1993 to 2023 for Norfolk Highlands Primary vs. Virginia and Chesapeake City School District

This dataset tracks annual diversity score from 1996 to 2023 for Norfolk Middle School vs. Nebraska and Norfolk School District

This dataset tracks annual diversity score from 1991 to 2023 for Norfolk Jr High School vs. Nebraska and Norfolk School District

This dataset tracks annual diversity score from 1991 to 2023 for Norwood-norfolk School vs. New York and Norwood-Norfolk Central School District

This dataset tracks annual diversity score from 1991 to 2023 for Norfolk School District vs. Massachusetts

This dataset tracks annual diversity score from 1993 to 2023 for Booker T Washington High School vs. Virginia and Norfolk City School District

This dataset tracks annual diversity score from 1993 to 2023 for Lake Taylor vs. Virginia and Norfolk City School District

This dataset tracks annual diversity score from 1991 to 2023 for Norfolk Senior High School vs. Nebraska and Norfolk School District

This dataset tracks annual diversity score from 1993 to 2023 for Mary Calcott Elementary School vs. Virginia and Norfolk City School District

This dataset tracks annual diversity score from 1993 to 2023 for Matthew Fontaine Maury High School vs. Virginia and Norfolk City School District

This dataset tracks annual diversity score from 1993 to 2023 for Larchmont Elementary School vs. Virginia and Norfolk City School District

This dataset tracks annual diversity score from 1997 to 2010 for Norfolk Public Montessori School vs. Nebraska and Norfolk Public Schools School District

This dataset tracks annual diversity score from 1993 to 2023 for Ruffner School vs. Virginia and Norfolk City School District

Water body status classification data indicates the quality or status of water bodies across a range of different parameters known as quality elements. This dataset includes the classification history of all water bodies in the North West Norfolk catchment. Data may be flagged as 'Cycle 1' if the classification uses the rules initiated in 2009 when the first cycle of river basin planning began. These data end in 2015. Or the data may be flagged as 'Cycle 2' if the classification uses the latest rules used in the updated river basin plans. These data begin in 2013 and will end in 2021. For surface water bodies status classification is grouped into ecological and chemical status and for groundwater bodies they are grouped into chemical and quantitative status. This data supports the Water Framework Directive river basin management plans that can be found here: https://www.gov.uk/government/collections/river-basin-management-plans-2015 and is available to view interactively here: http://environment.data.gov.uk/catchment-planning/ManagementCatchment/3065 Attribution statement: © Environment Agency copyright and/or database right 2016. All rights reserved.

About this dataset

Context

The dataset tabulates the Non-Hispanic population of Norfolk by race. It includes the distribution of the Non-Hispanic population of Norfolk across various race categories as identified by the Census Bureau. The dataset can be utilized to understand the Non-Hispanic population distribution of Norfolk across relevant racial categories.

Key observations

Of the Non-Hispanic population in Norfolk, the largest racial group is White alone with a population of 97,557 (46.05% of the total Non-Hispanic population).

Content

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:

• 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 (for Non-Hispanic) for the Norfolk
• Population: The population of the racial category (for Non-Hispanic) in the Norfolk is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Norfolk total Non-Hispanic 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 Norfolk Population by Race & Ethnicity. You can refer the same here