About this dataset

Context

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

Key observations

With a zero Hispanic population, Moores Hill is 100% Non-Hispanic. Among the Non-Hispanic population, the largest racial group is White alone with a population of 752 (97.41% 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 Moores Hill
• Population: The population of the racial category (for Non-Hispanic) in the Moores Hill is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Moores Hill 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 Moores Hill Population by Race & Ethnicity. You can refer the same here

About this dataset

Context

The dataset tabulates the population of Charles Mix County by race. It includes the population of Charles Mix County across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of Charles Mix County across relevant racial categories.

Key observations

The percent distribution of Charles Mix County population by race (across all racial categories recognized by the U.S. Census Bureau): 63.99% are white, 0.13% are Black or African American, 28.18% are American Indian and Alaska Native, 0.52% are Asian, 0.05% are Native Hawaiian and other Pacific Islander, 0.45% are some other race and 6.68% are multiracial.

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

The data consist of transcripts of interviews with 19 individuals from Brazil and 5 individuals from Colombia, who are all involved in Black and Indigenous activist organisations or in state agencies that are charged with promoting anti-racism and/or human rights. Each transcript begins with a paragraph giving contextual informationLatin America has often been held up as a region where racism is less of a problem than in regions such as the United States or Europe. Because most people are 'mestizos' (mixed race) and mixture is often seen as the essence of national identity, clear racial boundaries are blurred, resulting in comparatively low levels of racial segregation and a traditionally low public profile for issues of race. In Europe and the United States, the racial mixture and interaction across racial boundaries, which are typical of Latin America and are becoming more visible elsewhere, are heralded by some observers as leading towards a 'post-racial' reality, where anti-racism and multiculturalism - seen in this view as divisive policies that accentuate social differences - become unnecessary. Critics point out that mixture is not an antidote to racial inequality and racism in Latin America: they all coexist. This severely qualifies claims that mixture can lead to a 'post-racial' era. This project will investigate anti-racist practices and ideologies in Bolivia, Brazil, Colombia and Mexico. The project will contribute to conceptualising and addressing problems of racism, racial inequality and anti-racism in the region. We also propose that Latin America presents new opportunities for thinking about racism and anti-racism in a 'post-racial' world. Understanding how racism and anti-racism are conceived and practised in Latin America - in contexts in which mixture is pervasive - can help us to understand how to think about racism and anti-racism in other regions of the world, where notions of race have been changing in some respects towards Latin American patterns. It is also crucial to show the variety of ways in which mixture operates and co-exists with racism in Latin America - a region that is far from homogeneous. Research teams in each country, working with a range of organisations concerned with racism and discrimination, will explore how the organisations conceptualise and address key problems, which are becoming more salient in other regions, which confront similar scenarios. First, how to practice anti-racism when most people are mixed and when they may deny the importance of race and racism and themselves be both victims and the perpetrators of racism. Second, how to conceptualise and practice anti-racism when 'culture' seems to be the dominant discourse for talking about difference, but when physical difference (skin colour, hair type, etc.) remain powerful but often unacknowledged signs that move people to discriminate. Third, how to understand racism and combat it when race and class coincide to a great extent and make it easy to deny that race and racism are important factors. Fourth, how to make sure anti-racism addresses gender difference effectively, in a context in which mixture between white men and non-white women has been seen as the founding act of the nation. Fifth, how to pursue anti-racism when it is often claimed that there is little overt racist violence and that this is evidence of racial tolerance. We will explore how these elements structure - and may constrain - ideas about (anti-)racism within institutions, organisations and everyday practice. Our project will work with organisations in Bolivia, Brazil, Colombia and Mexico - countries that capture a good range of the region's diversity - to explore how racism and anti-racism are conceptualised and addressed in state and non-state circles, in legislation and the media, and in a variety of campaigns and projects. We aim to strengthen anti-racist practice in Latin America by feeding back our findings and by helping build networks; and to provide useful insights for understanding racism and anti-racism within and outside the region. The project carried out research in four countries, Brazil, Colombia, Ecuador and Mexico. We started by scoping out a broad range of organizations and individuals who were working in a direct or indirect fashion to challenge racism and racial inequality. We then selected seventeen case studies (over a third of which were Indigenous), with which we worked in depth, while also touching on about twenty other cases in a less intensive way. The cases were selected in order to include both Black and Indigenous organisations and cases, and to include a range of cases from government bodies to grassroots activist movements, plus some legal processes in which a variety of actors and organizations were involved. Our methods were mainly ethnography and interviews, undertaken principally by the four postdoctoral researchers, each of whom worked in one country. Some interviews were done with the assistance of a research assistant hired in the country. The interviews were conducted mostly in 2017, with some in 2018, in localities appropriate to the case study, such as an organization’s offices, an individual’s residence, or an agreed neutral location (e.g. a café, a village square, a classroom). Some interviews were informal conservations, but most were at least semi-structured. Common interview guides were not used, as each interview was specific to the case in question. Many interviews were audio-recorded (some were video-recorded) and selected interviews were transcribed in full or in part. Files with the original audio recordings and the transcripts are stored on a secure server in the University of Manchester. The files uploaded here are a selection of the transcribed interviews.

This dataset includes the race of applicants for Insurance Affordability Programs (IAPs) who reported their race as American Indian and/or Alaska Native, Asian Indian, Black or African American, Chinese, Cambodian, Filipino, Guamanian or Chamorro, Hmong, Japanese, Korean, Laotian, Mixed Race, Native Hawaiian, Other, Other Asian, Other Pacific Islander, Samoan, Vietnamese, or White by reporting period. The race data is from the California Healthcare Eligibility, Enrollment and Retention System (CalHEERS) and includes data from applications submitted directly to CalHEERS, to Covered California, and to County Human Services Agencies through the Statewide Automated Welfare System (SAWS) eHIT interface. Please note the reporting category Other Asian option on the CalHEERS application was removed in September 2017. This dataset is part of public reporting requirements set forth by the California Welfare and Institutions Code 14102.5.

This dataset includes the race of eligible individuals who selected and enrolled in a Covered California Qualified Health Plan (QHP) and identified their race as American Indian and/or Alaska Native, Asian Indian, Black or African American, Chinese, Filipino, Guamanian or Chamorro, Japanese, Korean, Mixed Race, Native Hawaiian, Other, Other Asian, Other Pacific Islander, Samoan, Vietnamese, or White, by reporting period. Covered California reported data is from the California Healthcare Eligibility, Enrollment and Retention System (CalHEERS) and includes those who selected and enrolled in a QHP, and paid their first premium. This dataset is part of public reporting requirements set forth by the California Welfare and Institutions Code 14102.5.

Matthew Hunt's article, "African American, Hispanic, and White Beliefs about Black/White Inequality, 1977–2004" (ASR 2007), uses the General Social Survey to examine whether blacks, Hispanics and whites hold different beliefs about the causes of black-white inequality and whether these beliefs change over time. Based on his analyses, Hunt argues that whites privilege agency explanations relative to blacks and Hispanics while blacks focus more on discrimination and mixed structural-agency explanations compared to whites and Hispanics. Our analyses explore whether Hunt's conclusions change based on two improvements: (1) we use multiple imputation to address high levels of missing data instead of Hunt's approach of listwise deletion and (2) we expand the data set to include more recent years to examine whether events that occurred post 2008 (for instance, the recession and successful presidential candidacy of Barak Obama, a black man) influenced beliefs about black-white inequality. We find that Hunt’s conclusions are robust to multiple imputation. However, when we include more recent years in our data set and measure the effect of post-2008 years, we find that blacks are more likely to choose an agency explanation while whites are less likely to reference agency and mixed explanation.

About this dataset

Context

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

Key observations

Of the Non-Hispanic population in Charles Mix County, the largest racial group is White alone with a population of 5,922 (65.57% 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 Charles Mix County
• Population: The population of the racial category (for Non-Hispanic) in the Charles Mix County is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Charles Mix County 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 Charles Mix County Population by Race & Ethnicity. You can refer the same here

This dataset is about book subjects. It has 5 rows and is filtered where the books is Interracial encounters : reciprocal representations in African American and Asian American literatures, 1896-1937. It features 10 columns including number of authors, number of books, earliest publication date, and latest publication date.

This dataset is about book subjects. It has 7 rows and is filtered where the books is One nation, one blood : interracial marriage in American fiction, scandal, and law, 1820-1870. It features 10 columns including number of authors, number of books, earliest publication date, and latest publication date.

About this dataset

Context

The dataset tabulates the population of Combined Locks by race. It includes the population of Combined Locks across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of Combined Locks across relevant racial categories.

Key observations

The percent distribution of Combined Locks population by race (across all racial categories recognized by the U.S. Census Bureau): 87.67% are white, 4.51% are Black or African American, 3.85% are some other race and 3.96% are multiracial.

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

This dataset includes the ethnicity of eligible individuals who selected and enrolled in a Covered California Qualified Health Plan (QHP) and identified their ethnicity as Hispanic with the ethnic origin as Mexican/Mexican American/Chicano, Other, Mixed, Puerto Rican, or Cuban, Hispanic with ethnic origin not reported, not Hispanic, or ethnicity not reported, by reporting period. Covered California reported data is from the California Healthcare Eligibility, Enrollment and Retention System (CalHEERS) and includes those who selected and enrolled in a QHP, and paid their first premium. This dataset is part of public reporting requirements set forth by the California Welfare and Institutions Code 14102.5.

aHAART initiated during acute/early or chronic HIV-1 infection as defined in Methods.bW, white, non-Hispanic; H, Hispanic; AA, African-American; As, Asian; M, mixed race.cTime after infection before achieving the most proximally documented period of sustained suppression of viremia to

About this dataset

Context

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

Key observations

Of the Non-Hispanic population in Combined Locks, the largest racial group is White alone with a population of 3,185 (91.84% 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 Combined Locks
• Population: The population of the racial category (for Non-Hispanic) in the Combined Locks is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Combined Locks 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 Combined Locks Population by Race & Ethnicity. You can refer the same here

About this dataset

Context

This list ranks the 7 cities in the Charles Mix County, SD by Multi-Racial Some Other Race (SOR) population, as estimated by the United States Census Bureau. It also highlights population changes in each cities over the past five years.

Content

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

• 2019-2023 American Community Survey 5-Year Estimates
• 2018-2022 American Community Survey 5-Year Estimates
• 2017-2021 American Community Survey 5-Year Estimates
• 2016-2020 American Community Survey 5-Year Estimates
• 2015-2019 American Community Survey 5-Year Estimates

Variables / Data Columns

• Rank by Multi-Racial Other Race Population: This column displays the rank of cities in the Charles Mix County, SD by their Multi-Racial Some Other Race (SOR) population, using the most recent ACS data available.
• cities: The cities for which the rank is shown in the previous column.
• Multi-Racial Other Race Population: The Multi-Racial Other Race population of the cities is shown in this column.
• % of Total cities Population: This shows what percentage of the total cities population identifies as Multi-Racial Other Race. Please note that the sum of all percentages may not equal one due to rounding of values.
• % of Total Charles Mix County Multi-Racial Other Race Population: This tells us how much of the entire Charles Mix County, SD Multi-Racial Other Race population lives in that cities. Please note that the sum of all percentages may not equal one due to rounding of values.
• 5 Year Rank Trend: TThis column displays the rank trend across the last 5 years.

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/.

About this dataset

Context

The dataset presents the median household income across different racial categories in Charles Mix County. 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 Charles Mix County population by race & ethnicity, the population is predominantly White. This particular racial category constitutes the majority, accounting for 63.99% of the total residents in Charles Mix County. Notably, the median household income for White households is $70,474. Interestingly, White is both the largest group and the one with the highest median household income, which stands at $70,474.

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 Charles Mix County.
• 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 Charles Mix County median household income by race. You can refer the same here

About this dataset

Context

The dataset presents the median household incomes over the past decade across various racial categories identified by the U.S. Census Bureau in Charles Mix County. 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 2011 and 2021, 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

• White: In Charles Mix County, the median household income for the households where the householder is White increased by $7,697(13.80%), between 2011 and 2021. The median household income, in 2022 inflation-adjusted dollars, was $55,776 in 2011 and $63,473 in 2021.
• Black or African American: Even though there is a population where the householder is Black or African American, there was no median household income reported by the U.S. Census Bureau for both 2011 and 2021.
• Refer to the research insights for more key observations on American Indian and Alaska Native, Asian, Native Hawaiian and Other Pacific Islander, Some other race and Two or more races (multiracial) households

https://i.neilsberg.com/ch/charles-mix-county-sd-median-household-income-by-race-trends.jpeg" alt="Charles Mix County, SD median household income trends across races (2011-2021, in 2022 inflation-adjusted dollars)">

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 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 Charles Mix County.
• 2010: 2010 median household income
• 2011: 2011 median household income
• 2012: 2012 median household income
• 2013: 2013 median household income
• 2014: 2014 median household income
• 2015: 2015 median household income
• 2016: 2016 median household income
• 2017: 2017 median household income
• 2018: 2018 median household income
• 2019: 2019 median household income
• 2020: 2020 median household income
• 2021: 2021 median household income
• 2022: 2022 median household income
• Please note: 2020 1-Year ACS estimates data was not reported by Census Bureau due to impact on survey collection and analysis during COVID-19, thus for large cities (population 65,000 and above) median household income data is not available.
• Please note: All incomes have been adjusted for inflation and are presented 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/.

Recommended for further research

This dataset is a part of the main dataset for Charles Mix County median household income by race. You can refer the same here

About this dataset

Context

The dataset presents the median household income across different racial categories in Combined Locks. 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 Combined Locks population by race & ethnicity, the population is predominantly White. This particular racial category constitutes the majority, accounting for 87.67% of the total residents in Combined Locks. Notably, the median household income for White households is $92,375. Interestingly, White is both the largest group and the one with the highest median household income, which stands at $92,375.

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 Combined Locks.
• 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 Combined Locks median household income by race. You can refer the same here

About this dataset

Context

The dataset presents the median household incomes over the past decade across various racial categories identified by the U.S. Census Bureau in Combined Locks. 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

• White: In Combined Locks, the median household income for the households where the householder is White increased by $1,084(1.19%), between 2013 and 2023. The median household income, in 2023 inflation-adjusted dollars, was $91,291 in 2013 and $92,375 in 2023.
• Black or African American: Even though there is a population where the householder is Black or African American, there was no median household income reported by the U.S. Census Bureau for both 2013 and 2023.
• Refer to the research insights for more key observations on American Indian and Alaska Native, Asian, Native Hawaiian and Other Pacific Islander, Some other race and Two or more races (multiracial) households

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 Combined Locks.
• 2010: 2010 median household income
• 2011: 2011 median household income
• 2012: 2012 median household income
• 2013: 2013 median household income
• 2014: 2014 median household income
• 2015: 2015 median household income
• 2016: 2016 median household income
• 2017: 2017 median household income
• 2018: 2018 median household income
• 2019: 2019 median household income
• 2020: 2020 median household income
• 2021: 2021 median household income
• 2022: 2022 median household income
• 2023: 2023 median household income
• Please note: All incomes have been adjusted for inflation and are 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 Combined Locks median household income by race. You can refer the same here

About this dataset

Context

The dataset tabulates the population of Charles Mix County by gender, including both male and female populations. This dataset can be utilized to understand the population distribution of Charles Mix County across both sexes and to determine which sex constitutes the majority.

Key observations

There is a slight majority of male population, with 50.49% of total population being male. Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

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

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. No further analysis is done on the data reported from the Census Bureau.

Variables / Data Columns

• Gender: This column displays the Gender (Male / Female)
• Population: The population of the gender in the Charles Mix County is shown in this column.
• % of Total Population: This column displays the percentage distribution of each gender as a proportion of Charles Mix County total 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 Charles Mix County Population by Race & Ethnicity. You can refer the same here