About this dataset

Context

The dataset tabulates the Orange County median household income by race. The dataset can be utilized to understand the racial distribution of Orange County income.

Content

The dataset will have the following datasets when applicable

Please note: The 2020 1-Year ACS estimates data was not reported by the Census Bureau due to the impact on survey collection and analysis caused by COVID-19. Consequently, median household income data for 2020 is unavailable for large cities (population 65,000 and above).

• Orange County, IN median household income breakdown by race betwen 2011 and 2021
• Median Household Income by Racial Categories in Orange County, IN (2021, in 2022 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/.

Interested in deeper insights and visual analysis?

Explore our comprehensive data analysis and visual representations for a deeper understanding of Orange County median household income by race. You can refer the same here

US Census 2010 (SF1) population characteristics for Orange County, California, across multiple census geographies: county, county subdivisions, urban areas, census places (cities), block groups, tracts, ZIP code tabulation areas, US Congressional districts (111th), and elementary school districts. The US Census geodemographic data are based on the 2010 TigerLines across multiple census geographies. The spatial geographies were merged with SF1 and SF2 demographic data tables for both Housing and Population characteristics.

About this dataset

Context

The dataset tabulates the Orange County household income by age. The dataset can be utilized to understand the age-based income distribution of Orange County income.

Content

The dataset will have the following datasets when applicable

Please note: The 2020 1-Year ACS estimates data was not reported by the Census Bureau due to the impact on survey collection and analysis caused by COVID-19. Consequently, median household income data for 2020 is unavailable for large cities (population 65,000 and above).

• Orange County, VT annual median income by age groups dataset (in 2022 inflation-adjusted dollars)
• Age-wise distribution of Orange County, VT household incomes: Comparative analysis across 16 income brackets

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/.

Interested in deeper insights and visual analysis?

Explore our comprehensive data analysis and visual representations for a deeper understanding of Orange County income distribution by age. You can refer the same here

US Census 2010 selected population and housing characteristics for Orange County, California, across multiple census geographies: County, County Subdivisions, Census Places (cities), Blocks, Tracts, ZIP code tabulation areas, US Congressional districts (111th), State Assembly and Senate Legislative Districts, Elementary, Secondary and Unified School Districts. The US Census geodemographic data are based on the 2010 TigerLines across multiple census geographies. The spatial geographies were merged with SF1 and SF2 demographic data tables for both Housing and Population characteristics.

U.S. Census Bureau QuickFacts statistics for City of Orange township, Essex County, New Jersey. 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.

About this dataset

Context

The dataset tabulates the Chester town median household income by race. The dataset can be utilized to understand the racial distribution of Chester town income.

Content

The dataset will have the following datasets when applicable

Please note: The 2020 1-Year ACS estimates data was not reported by the Census Bureau due to the impact on survey collection and analysis caused by COVID-19. Consequently, median household income data for 2020 is unavailable for large cities (population 65,000 and above).

• Chester Town, Orange County, New York median household income breakdown by race betwen 2011 and 2021
• Median Household Income by Racial Categories in Chester Town, Orange County, New York (2021, in 2022 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/.

Interested in deeper insights and visual analysis?

Explore our comprehensive data analysis and visual representations for a deeper understanding of Chester town median household income by race. You can refer the same here

A dataset listing California counties by population for 2024.

This statistic shows the 25 largest counties in the United States in 2022, by population. In 2022, about 9.72 million people were estimated to be living in Los Angeles County, California.

Additional information on urbanization in the United States

Urbanization is defined as the process by which cities grow or by which societies become more urban. Rural to urban migration in the United States, and around the world, is often undertaken in the search for employment or to enjoy greater access to services such as healthcare. The largest cities in the United States are steadily growing. Given their size, incremental increases yield considerable numerical gains as seen by New York increasing by 69,777 people in 2011, the most of any city. However in terms of percentage growth, smaller cities outside the main centers are growing the fastest, such as Georgetown city and Leander city in Texas.

Urbanization has increased slowly in the United States, rising from 80.77 percent of the population living in urban areas in 2010 to 82.66 percent in 2020. In 2018, the United States ranked 14th in a ranking of countries based on their degree of urbanization. Unlike fully urbanized countries such as Singapore and Hong Kong, the United States maintains a sizeable agricultural industry. Although technological developments have reduced demands for rural labor, labor in the industry and supporting services are still required.

Land boundaries for Orange County, cities, and unincorporated areas (based on the five supervisorial districts). Contains additional geodemographic data on population and housing from the US Census 2021 American Community Survey (ACS).

Chart and table of population level and growth rate for the Los Angeles metro area from 1950 to 2025. United Nations population projections are also included through the year 2035.

About this dataset

Context

The dataset tabulates the Chester town household income by gender. The dataset can be utilized to understand the gender-based income distribution of Chester town income.

Content

The dataset will have the following datasets when applicable

Please note: The 2020 1-Year ACS estimates data was not reported by the Census Bureau due to the impact on survey collection and analysis caused by COVID-19. Consequently, median household income data for 2020 is unavailable for large cities (population 65,000 and above).

• Chester Town, Orange County, New York annual median income by work experience and sex dataset : Aged 15+, 2010-2022 (in 2022 inflation-adjusted dollars)
• Chester Town, Orange County, New York annual income distribution by work experience and gender dataset (Number of individuals ages 15+ with income, 2021)

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/.

Interested in deeper insights and visual analysis?

Explore our comprehensive data analysis and visual representations for a deeper understanding of Chester town income distribution by gender. You can refer the same here

US Census American Community Survey (ACS) 2013, 5-year estimates of the key population, household, and housing characteristics of Cities/Places geographic level in Orange County, California. The data contains a number of fields showcasing annual estimated values of total population, households and housing units for each city in Orange County, California, along with total and mean annual average changes. The US Census geodemographic data are based on the 2013-2017 TigerLines across multiple geographies. The spatial geographies were merged with ACS data tables. See full documentation at the OCACS project github page (https://github.com/ktalexan/OCACS-Geodemographics).

About this dataset

Context

The dataset tabulates the Greenville town household income by gender. The dataset can be utilized to understand the gender-based income distribution of Greenville town income.

Content

The dataset will have the following datasets when applicable

Please note: The 2020 1-Year ACS estimates data was not reported by the Census Bureau due to the impact on survey collection and analysis caused by COVID-19. Consequently, median household income data for 2020 is unavailable for large cities (population 65,000 and above).

• Greenville Town, Orange County, New York annual median income by work experience and sex dataset : Aged 15+, 2010-2022 (in 2022 inflation-adjusted dollars)
• Greenville Town, Orange County, New York annual income distribution by work experience and gender dataset (Number of individuals ages 15+ with income, 2021)

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/.

Interested in deeper insights and visual analysis?

Explore our comprehensive data analysis and visual representations for a deeper understanding of Greenville town income distribution by gender. You can refer the same here

US Census American Community Survey (ACS) 2013, 5-year estimates of the key demographic characteristics of Cities/Places geographic level in Orange County, California. The data contains 105 fields for the variable groups D01: Sex and age (universe: total population, table X1, 49 fields); D02: Median age by sex and race (universe: total population, table X1, 12 fields); D03: Race (universe: total population, table X2, 8 fields); D04: Race alone or in combination with one or more other races (universe: total population, table X2, 7 fields); D05: Hispanic or Latino and race (universe: total population, table X3, 21 fields), and; D06: Citizen voting age population (universe: citizen, 18 and over, table X5, 8 fields). The US Census geodemographic data are based on the 2013 TigerLines across multiple geographies. The spatial geographies were merged with ACS data tables. See full documentation at the OCACS project GitHub page (https://github.com/ktalexan/OCACS-Geodemographics).

About this dataset

Context

The dataset tabulates the Orange County household income by gender. The dataset can be utilized to understand the gender-based income distribution of Orange County income.

Content

The dataset will have the following datasets when applicable

Please note: The 2020 1-Year ACS estimates data was not reported by the Census Bureau due to the impact on survey collection and analysis caused by COVID-19. Consequently, median household income data for 2020 is unavailable for large cities (population 65,000 and above).

• Orange County, FL annual median income by work experience and sex dataset : Aged 15+, 2010-2022 (in 2022 inflation-adjusted dollars)
• Orange County, FL annual income distribution by work experience and gender dataset (Number of individuals ages 15+ with income, 2022)

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/.

Interested in deeper insights and visual analysis?

Explore our comprehensive data analysis and visual representations for a deeper understanding of Orange County income distribution by gender. You can refer the same here

About this dataset

Context

The dataset tabulates the Greenville town median household income by race. The dataset can be utilized to understand the racial distribution of Greenville town income.

Content

The dataset will have the following datasets when applicable

Please note: The 2020 1-Year ACS estimates data was not reported by the Census Bureau due to the impact on survey collection and analysis caused by COVID-19. Consequently, median household income data for 2020 is unavailable for large cities (population 65,000 and above).

• Greenville Town, Orange County, New York median household income breakdown by race betwen 2011 and 2021
• Median Household Income by Racial Categories in Greenville Town, Orange County, New York (2021, in 2022 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/.

Interested in deeper insights and visual analysis?

Explore our comprehensive data analysis and visual representations for a deeper understanding of Greenville town median household income by race. You can refer the same here

This 1991 survey examines ten years of trends in the Orange County Annual Survey. In asking questions from the 1982 benchmark survey, the focus is on the county's quality of life ratings and local public service ratings. The survey also examines changes over time in attitudes towards traffic congestion and growth, which have been the county's top two policy issues in the past decade. The sample size is 1,002 Orange County adult residents.Online data analysis & additional documentation in Link below. Methods The Orange County Annual Survey was co-directed by Mark Baldassare, a UC Irvine professor of social ecology, and Cheryl Katz, research associate. For the survey, 1,002 adult Orange County residents were interviewed by telephone Sept. 3 to 20. Interviewing was conducted on weekend days and weekday nights, using a computer-generated random sample of telephone numbers. The field work was conducted at the Center for Survey Research at UCI. Of the telephone numbers called, 21 percent resulted in completed interviews and 14 percent were refusals. The completion rate for the survey was 60 percent, consistent with earlier Orange County Annual Surveys. Within a household, respondents were chosen for interview using the Troldahl-Carter method. This method randomly selects a household member from a grid that includes information on the number of adult household members and the number of adult men in the household. Each interview included 93 questions and took an average of 20 minutes to complete.

The interview began with questions about housing, consumer confidence, and general perceptions about Orange County. These were followed by questions on transportation, the quality of life, public service ratings, the environment, and air quality proposals. Later in the interview, we turned to the issues of health care and charity. The conclusion of the survey was devoted to questions about work, commuting, demographics, and politics. For analysis, we statistically weighted the sample to represent the actual regional distribution of Orange County residents, as in previous surveys. The 1990 U.S. Census population figures by city were reviewed for this purpose. The sampling error for this survey is +/-3 percent at the 95 percent confidence level. This means that 95 times out of 100, the results will be within 3 percentage points of what they would be if all adults in Orange County were interviewed. The sampling error for any subgroup would be larger. Sampling error is just one type of error to which surveys are subject. Results may also be affected by question wording, survey timing and survey design.

About this dataset

Context

The dataset tabulates the median household income in Chester town. It can be utilized to understand the trend in median household income and to analyze the income distribution in Chester town by household type, size, and across various income brackets.

Content

The dataset will have the following datasets when applicable

Please note: The 2020 1-Year ACS estimates data was not reported by the Census Bureau due to the impact on survey collection and analysis caused by COVID-19. Consequently, median household income data for 2020 is unavailable for large cities (population 65,000 and above).

• Chester Town, Orange County, New York Median Household Income Trends (2010-2021, in 2022 inflation-adjusted dollars)
• Median Household Income Variation by Family Size in Chester Town, Orange County, New York: Comparative analysis across 7 household sizes
• Income Distribution by Quintile: Mean Household Income in Chester Town, Orange County, New York
• Chester Town, Orange County, New York households by income brackets: family, non-family, and total, in 2022 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/.

Interested in deeper insights and visual analysis?

Explore our comprehensive data analysis and visual representations for a deeper understanding of Chester town median household income. You can refer the same here

A dataset listing Florida counties by population for 2024.

A dataset listing New York counties by population for 2024.