This graph shows the population of the U.S. by race and ethnic group from 2000 to 2023. In 2023, there were around 21.39 million people of Asian origin living in the United States. A ranking of the most spoken languages across the world can be accessed here. U.S. populationCurrently, the white population makes up the vast majority of the United States’ population, accounting for some 252.07 million people in 2023. This ethnicity group contributes to the highest share of the population in every region, but is especially noticeable in the Midwestern region. The Black or African American resident population totaled 45.76 million people in the same year. The overall population in the United States is expected to increase annually from 2022, with the 320.92 million people in 2015 expected to rise to 341.69 million people by 2027. Thus, population densities have also increased, totaling 36.3 inhabitants per square kilometer as of 2021. Despite being one of the most populous countries in the world, following China and India, the United States is not even among the top 150 most densely populated countries due to its large land mass. Monaco is the most densely populated country in the world and has a population density of 24,621.5 inhabitants per square kilometer as of 2021. As population numbers in the U.S. continues to grow, the Hispanic population has also seen a similar trend from 35.7 million inhabitants in the country in 2000 to some 62.65 million inhabitants in 2021. This growing population group is a significant source of population growth in the country due to both high immigration and birth rates. The United States is one of the most racially diverse countries in the world.

This map shows the percentage of people who identify as something other than non-Hispanic white throughout the US according to the most current American Community Survey. The pattern is shown by states, counties, and Census tracts. Zoom or search for anywhere in the US to see a local pattern. Click on an area to learn more. Filter to your area and save a new version of the map to use for your own mapping purposes.The Arcade expression used was: 100 - B03002_calc_pctNHWhiteE, which is simply 100 minus the percent of population who identifies as non-Hispanic white. The data is from the U.S. Census Bureau's American Community Survey (ACS). The figures in this map update automatically annually when the newest estimates are released by ACS. For more detailed metadata, visit the ArcGIS Living Atlas Layer: ACS Race and Hispanic Origin Variables - Boundaries.The data on race were derived from answers to the question on race that was asked of individuals in the United States. The Census Bureau collects racial data in accordance with guidelines provided by the U.S. Office of Management and Budget (OMB), and these data are based on self-identification. The racial categories included in the census questionnaire generally reflect a social definition of race recognized in this country and not an attempt to define race biologically, anthropologically, or genetically. The categories represent a social-political construct designed for collecting data on the race and ethnicity of broad population groups in this country, and are not anthropologically or scientifically based. Learn more here.Other maps of interest:American Indian or Alaska Native Population in the US (Current ACS)Asian Population in the US (Current ACS)Black or African American Population in the US (Current ACS)Hawaiian or Other Pacific Islander Population in the US (Current ACS)Hispanic or Latino Population in the US (Current ACS) (some people prefer Latinx)Population who are Some Other Race in the US (Current ACS)Population who are Two or More Races in the US (Current ACS) (some people prefer mixed race or multiracial)White Population in the US (Current ACS)Race in the US by Dot DensityWhat is the most common race/ethnicity?

About this dataset

Context

The dataset tabulates the Earth Hispanic or Latino population. It includes the distribution of the Hispanic or Latino population, of Earth, by their ancestries, as identified by the Census Bureau. The dataset can be utilized to understand the origin of the Hispanic or Latino population of Earth.

Key observations

Among the Hispanic population in Earth, regardless of the race, the largest group is of Mexican origin, with a population of 588 (94.84% of the total 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.

Origin for Hispanic or Latino population include:

• Mexican
• Puerto Rican
• Cuban
• Other Hispanic or Latino

Variables / Data Columns

• Origin: This column displays the origin for Hispanic or Latino population for the Earth
• Population: The population of the specific origin for Hispanic or Latino population in the Earth is shown in this column.
• % of Total Hispanic Population: This column displays the percentage distribution of each Hispanic origin as a proportion of Earth total Hispanic or Latino 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 Earth Population by Race & Ethnicity. You can refer the same here

Anti-Black or African American attacks were the most common form of racist hate crime in the United States in 2023, with 3,027 cases. Anti-White hate crimes were the next most common form of race-based hate crime in that year, with 831 incidents.

The statistic shows the share of U.S. population, by race and Hispanic origin, in 2016 and a projection for 2060. As of 2016, about 17.79 percent of the U.S. population was of Hispanic origin. Race and ethnicity in the U.S. For decades, America was a melting pot of the racial and ethnical diversity of its population. The number of people of different ethnic groups in the United States has been growing steadily over the last decade, as has the population in total. For example, 35.81 million Black or African Americans were counted in the U.S. in 2000, while 43.5 million Black or African Americans were counted in 2017.

The median annual family income in the United States in 2017 earned by Black families was about 50,870 U.S. dollars, while the average family income earned by the Asian population was about 92,784 U.S. dollars. This is more than 15,000 U.S. dollars higher than the U.S. average family income, which was 75,938 U.S. dollars.

The unemployment rate varies by ethnicity as well. In 2018, about 6.5 percent of the Black or African American population in the United States were unemployed. In contrast to that, only three percent of the population with Asian origin was unemployed.

In the fiscal year of 2019, 21.39 percent of active-duty enlisted women were of Hispanic origin. The total number of active duty military personnel in 2019 amounted to 1.3 million people.

Ethnicities in the United States The United States is known around the world for the diversity of its population. The Census recognizes six different racial and ethnic categories: White American, Native American and Alaska Native, Asian American, Black or African American, Native Hawaiian and Other Pacific Islander. People of Hispanic or Latino origin are classified as a racially diverse ethnicity.

The largest part of the population, about 61.3 percent, is composed of White Americans. The largest minority in the country are Hispanics with a share of 17.8 percent of the population, followed by Black or African Americans with 13.3 percent. Life in the U.S. and ethnicity However, life in the United States seems to be rather different depending on the race or ethnicity that you belong to. For instance: In 2019, native Hawaiians and other Pacific Islanders had the highest birth rate of 58 per 1,000 women, while the birth rae of white alone, non Hispanic women was 49 children per 1,000 women.

The Black population living in the United States has the highest poverty rate with of all Census races and ethnicities in the United States. About 19.5 percent of the Black population was living with an income lower than the 2020 poverty threshold. The Asian population has the smallest poverty rate in the United States, with about 8.1 percent living in poverty.

The median annual family income in the United States in 2020 earned by Black families was about 57,476 U.S. dollars, while the average family income earned by the Asian population was about 109,448 U.S. dollars. This is more than 25,000 U.S. dollars higher than the U.S. average family income, which was 84,008 U.S. dollars.

This map is designed to work in the new ArcGIS Online Map Viewer. Open in Map Viewer to view map. What does this map show?This map shows the population in the US by race. The map shows this pattern nationwide for states, counties, and tracts. Open the map in the new ArcGIS Online Map Viewer Beta to see the dot density pattern. What is dot density?The density is visualized by randomly placing one dot per a given value for the desired attribute. Unlike choropleth visualizations, dot density can be mapped using total counts since the size of the polygon plays a significant role in the perceived density of the attribute.Where is the data from?The data in this map comes from the most current American Community Survey (ACS) from the U.S. Census Bureau. Table B03002. The layer being used if updated with the most current data each year when the Census releases new estimates. The layer can be found in ArcGIS Living Atlas of the World: ACS Race and Hispanic Origin Variables - Boundaries.What questions does this map answer?Where do people of different races live?Do people of a similar race live close to people of their own race?Which cities have a diverse range of different races? Less diverse?

The graph illustrates the number of victims of race-based hate crimes in the United States in 2023. The x-axis lists various ethnic groups, while the y-axis represents the corresponding number of victims. The data reveals that Anti-Black hate crimes were the most prevalent, with 3224 victims, followed by Anti-Hispanic and Anti-Asian crimes with 861and 430 victims respectively. Other categories include Anti-Other Race (418), Anti-American Indian (112), Anti-Arab (154), and Anti-Native Pacific (15). The data indicates a significant disparity in the number of victims across different ethnic groups, with Anti-Black hate crimes being the most prominent.

This statistic shows the share of ethnic groups in Australia in the total population. 33 percent of the total population of Australia are english.

Australia’s population

Australia’s ethnic diversity can be attributed to their history and location. The country’s colonization from Europeans is a significant reason for the majority of its population being Caucasian. Additionally, being that Australia is one of the most developed countries closest to Eastern Asia; its Asian population comes as no surprise.

Australia is one of the world’s most developed countries, often earning recognition as one of the world’s economical leaders. With a more recent economic boom, Australia has become an attractive country for students and workers alike, who seek an opportunity to improve their lifestyle. Over the past decade, Australia’s population has slowly increased and is expected to continue to do so over the next several years. A beautiful landscape, many work opportunities and a high quality of life helped play a role in the country’s development. In 2011, Australia was considered to have one of the highest life expectancies in the world, with the average Australian living to approximately 82 years of age.

From an employment standpoint, Australia has maintained a rather low employment rate compared to many other developed countries. After experiencing a significant jump in unemployment in 2009, primarily due to the world economic crisis, Australia has been able to remain stable and slightly increase employment year-over-year.

About this dataset

Context

The dataset presents the median household income across different racial categories in Blue Earth 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 Blue Earth County population by race & ethnicity, the population is predominantly White. This particular racial category constitutes the majority, accounting for 88.78% of the total residents in Blue Earth County. Notably, the median household income for White households is $69,941. Interestingly, despite the White population being the most populous, it is worth noting that Two or More Races households actually reports the highest median household income, with a median income of $102,936. This reveals that, while Whites may be the most numerous in Blue Earth County, Two or More Races households experience greater economic prosperity in terms of median household income.

https://i.neilsberg.com/ch/blue-earth-county-mn-median-household-income-by-race.jpeg" alt="Blue Earth County median household income diversity across racial categories">

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2022 1-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 Blue Earth County.
• Median household income: Median household income, adjusting for inflation, 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 Blue Earth County median household income by race. You can refer the same here

Diversity in Tech Statistics: In today's tech-driven world, discussions about diversity in the technology sector have gained significant traction. Recent statistics shed light on the disparities and opportunities within this industry. According to data from various sources, including reports from leading tech companies and diversity advocacy groups, the lack of diversity remains a prominent issue. For example, studies reveal that only 25% of computing jobs in the United States are held by women, while Black and Hispanic individuals make up just 9% of the tech workforce combined. Additionally, research indicates that LGBTQ+ individuals are underrepresented in tech, with only 2.3% of tech workers identifying as LGBTQ+. Despite these challenges, there are promising signs of progress. Companies are increasingly recognizing the importance of diversity and inclusion initiatives, with some allocating significant resources to address these issues. For instance, tech giants like Google and Microsoft have committed millions of USD to diversity programs aimed at recruiting and retaining underrepresented talent. As discussions surrounding diversity in tech continue to evolve, understanding the statistical landscape is crucial in fostering meaningful change and creating a more inclusive industry for all. Editor’s Choice In 2021, 7.9% of the US labor force was employed in technology. Women hold only 26.7% of tech employment, while men hold 73.3% of these positions. White Americans hold 62.5% of the positions in the US tech sector. Asian Americans account for 20% of jobs, Latinx Americans 8%, and Black Americans 7%. 83.3% of tech executives in the US are white. Black Americans comprised 14% of the population in 2019 but held only 7% of tech employment. For the same position, at the same business, and with the same experience, women in tech are typically paid 3% less than men. The high-tech sector employs more men (64% against 52%), Asian Americans (14% compared to 5.8%), and white people (68.5% versus 63.5%) compared to other industries. The tech industry is urged to prioritize inclusion when hiring, mentoring, and retaining employees to bridge the digital skills gap. Black professionals only account for 4% of all tech workers despite being 13% of the US workforce. Hispanic professionals hold just 8% of all STEM jobs despite being 17% of the national workforce. Only 22% of workers in tech are ethnic minorities. Gender diversity in tech is low, with just 26% of jobs in computer-related sectors occupied by women. Companies with diverse teams have higher profitability, with those in the top quartile for gender diversity being 25% more likely to have above-average profitability. Every month, the tech industry adds about 9,600 jobs to the U.S. economy. Between May 2009 and May 2015, over 800,000 net STEM jobs were added to the U.S. economy. STEM jobs are expected to grow by another 8.9% between 2015 and 2024. The percentage of black and Hispanic employees at major tech companies is very low, making up just one to three percent of the tech workforce. Tech hiring relies heavily on poaching and incentives, creating an unsustainable ecosystem ripe for disruption. Recruiters have a significant role in disrupting the hiring process to support diversity and inclusion. You May Also Like To Read Outsourcing Statistics Digital Transformation Statistics Internet of Things Statistics Computer Vision Statistics

According to the Wikipedia, an ultramarathon, also called ultra distance or ultra running, is any footrace longer than the traditional marathon length of 42.195 kilometres (26 mi 385 yd). Various distances are raced competitively, from the shortest common ultramarathon of 31 miles (50 km) to over 200 miles (320 km). 50k and 100k are both World Athletics record distances, but some 100 miles (160 km) races are among the oldest and most prestigious events, especially in North America.}

The data in this file is a large collection of ultra-marathon race records registered between 1798 and 2022 (a period of well over two centuries) being therefore a formidable long term sample. All data was obtained from public websites.

Despite the original data being of public domain, the race records, which originally contained the athlete´s names, have been anonymized to comply with data protection laws and to preserve the athlete´s privacy. However, a column Athlete ID has been created with a numerical ID representing each unique runner (so if Antonio Fernández participated in 5 races over different years, then the corresponding race records now hold his unique Athlete ID instead of his name). This way I have preserved valuable information.

The dataset contains 7,461,226 ultra-marathon race records from 1,641,168 unique athletes.

The following columns (with data types) are included:

• Year of event (int64)
• Event dates (object)
• Event name (object)
• Event distance/length (object)
• Event number of finishers (int64)
• Athlete performance (object)
• Athlete club (object)
• Athlete country (object)
• Athlete year of birth (float64)
• Athlete gender (object)
• Athlete age category (object)
• Athlete average speed (object)
• Athlete ID (int64)

The Event name column include country location information that can be derived to a new column, and similarly seasonal information can be found in the Event dates column beyond the Year of event (these can be extracted with a bit of processing).

The Event distance/length column describes the type of race, covering the most popular UM race distances and lengths, and some other specific modalities (multi-day, etc.):

• Distances: 50km, 100km, 50mi, 100mi
• Lengths: 6h, 12h, 24h, 48h, 72h, 6d, 10d

Additionally, there is information of age, gender and speed (in km/h) in other columns.

About this dataset

Context

The dataset presents the median household income across different racial categories in White Earth township. 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 White Earth township population by race & ethnicity, the population is predominantly American Indian and Alaska Native. This particular racial category constitutes the majority, accounting for 46% of the total residents in White Earth township. Notably, the median household income for American Indian and Alaska Native households is $17,375. Interestingly, despite the American Indian and Alaska Native population being the most populous, it is worth noting that Two or More Races households actually reports the highest median household income, with a median income of $88,036. This reveals that, while American Indian and Alaska Natives may be the most numerous in White Earth township, Two or More Races households experience greater economic prosperity in terms of median household income.

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 White Earth township.
• 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 White Earth township 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 Globe. 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 Globe population by race & ethnicity, the population is predominantly White. This particular racial category constitutes the majority, accounting for 58.09% of the total residents in Globe. Notably, the median household income for White households is $65,261. Interestingly, despite the White population being the most populous, it is worth noting that Some Other Race households actually reports the highest median household income, with a median income of $98,333. This reveals that, while Whites may be the most numerous in Globe, Some Other Race households experience greater economic prosperity in terms of median household income.

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

Nigeria has hundreds of ethnic groups that are usually divided and defined primarily by language. The country hosts more ethnic groups than any other African nation, ranking among the most ethnically-complex states in the world. Most of these ethnic groups are small and localized, with only a few playing a central role in Nigerian society. The major people groups of Nigeria are: Hausa, Fulani, Yoruba, and Igbo (Ibo).The advent of colonial rule in Nigeria brought the various ethnic groups increasingly into contact with one another. This integrative process was facilitated by the construction of connective infrastructure. This increasing development set in motion a process that led to greater contact and competition among the various ethnic groups for dominance and economic advantage. The Nigerian government has worked out tentative power-sharing arrangements to help ensure that its many ethnic groups have some say in society. However, cities remain largely segregated along ethno-religious lines and confrontation between ethnic groups is common. Often, ethnic clashes in one part of the country can set off a chain of reprisal riots and attacks in other parts of the country.Most major ethnic groups have seen the formation of ethnic-exclusive militias to protect alleged group interests and perpetrate violence against other ethnic groups. These vigilante groups continue to act with impunity for lack of stringent law enforcement in much of the state. These continued attacks and tensions among ethnic groups threaten to destabilize an already unsteady country.Hausa - Northern Nigeria is dominated by this ethnic group and is often considered unified with the Fulani through intermarriage of acculturation, generating the Hausa-Fulani as a single ethnic entity. The Hausa were predominately traders throughout the Sahara and Sahel regions but have become more concentrated in rural areas as farmers and herders. They are predominately Muslim with some of the smaller sub-groups such as the Maguzawa practicing indigenous faiths. Their religion is a key component to ethnic identity and continues to shape their role in modern Nigerian society and politics. The Hausa and Fulani were instrumental in establishing and maintaining Sharia in 11 of the country’s northern states.Fulani –The Fulani are an ethnic group of Muslims located in northern Nigeria that have often assimilated into the Hausa culture. At one point nomadic herders, they arrived in the Hausa states sometime in the early 13th century. Many have intermarried with the Hausa and have mostly adopted those customs and language, although some Fulani choose to stay "pure" by retaining a nomadic lifestyle, their own language, and cultural autonomy. The Fulani are most distinctively known for a dispute that developed between them and the local King of Gobir, which developed into a jihad ending with a Fulani conquest of the Hausa states in the early 1800s.Yoruba – The Yoruba are Christian/Muslims living in southwestern Nigeria united by their common belief that Ife is their place of origin and the Oni of Ife is their spiritual leader. Their mythology holds that "Oduduwa" created the earth and that royal houses of the Yoruba kingdoms can trace their ancestry back to "Oduduwa.” Yoruba society is organized into kingdoms, the greatest of which was called Oyo. The Oyo Empire collapsed in 1830, when Afonja, broke away from the rest of the Yoruba culture and lost his empire to the Fulani. This event occurred in close temporal proximity to the Fulani Jihad, but was not associated with it. As Islam and Christianity spread to Yorubaland over the past few centuries, the group embraced both faiths alongside its many traditional and animist beliefs. This blend and acceptance of religion survives in modern society and has mitigated some religious conflict in places where Yoruba form the majority.Igbo (Ibo) – The Igbo are the main ethnic group living in southeastern Nigeria. They have represented some of the staunchest opponents to the establishment of Sharia in the North where some minority Igbo populations exist. As opposed to Hausa-Fulani and Yoruba cultures, the Igbo were traditionally decentralized and non-hierarchical, making them more receptive to European conversion efforts.Under British colonial rule, many Igbo served in government and military roles and were later key players in the 1960 Nigerian independence movement. In January 1966, Igbo leader General Ironsi established a military coup in Nigeria to try and unify a fragmented, newly-independent Nigeria. The northern section of the country believed there was an Igbo conspiracy with the establishment of the new government. In July 1966, a counter-attack was staged by northern military officers in response to the constitution of another new government. Chaos ensued and about 50,000 Igbo were killed in northern Nigeria. To put an end to chaos and upheaval, groups in eastern Nigeria declared themselves as an independent sovereign state known as “Biafra" on 30 May 1967. The Igbo secessionist movement in Biafra led to a 30-month war (Biafran War) with the Nigerian government, in which hundreds of thousands of Igbo starved to death. After the war, Igbo were reintegrated into Nigerian society, but in a more marginalized role. Despite lingering ethnic tension, they now play an important part in southeastern Nigeria's oil trade.

ISO3 - International Organization for Standardization 3-digit country code

PEOPLEGP_1 - People group level one

PEOPLEGP_2 - People group level two

PEOPLEGP_3 - People group level three

ALT_NAME - Alternate names or spellings for people groups

SOURCE_DT - Primary source creation date

SOURCE - Primary source

Collection

This shapefile created by using Anthromapper consists of ethnic layers that have been primarily based on the 1959 Murdock map of Africa with an addition of the Anaang people group based on a general location provided by Ethnologue. Geographical terrain features, combined with a watershed model, were also used to predict the likely extent of ethnic and linguistic influence. The HGIS data and metadata were supplemented with anthropological information from peer-reviewed journals and published books. The interpretation of ethnic names often produces multiple spellings of the same people groups; therefore similarly spelled or phonetic titles may be referencing the same group.

The data included herein have not been derived from a registered survey and should be considered approximate unless otherwise defined. While rigorous steps have been taken to ensure the quality of each dataset, DigitalGlobe Analytics is not responsible for the accuracy and completeness of data compiled from outside sources.

Sources (HGIS)

Anthromapper. DigitalGlobe Analytics, March 2013.

Murdock, George Peter. Tribal Map of Africa from Africa: Its Peoples and Their Culture History. New York: McGraw-Hill Book Co., January 1959.

Interactive Murdock Map available at - http://worldmap.harvard.edu/africamap.

Ethnologue, “Anaang.” Last modified April 2013. Accessed April 2013. http://www.ethnologue.com

People Groups, “Nigeria.” Last modified April 2013. Accessed April 2013. http://peoplegroups.org.

Joshua Project, “Nigeria”. Last modified March 2013. Accessed April 2013. http://www.joshuaproject.net.

Sources (Metadata)

Walker, Andrew. United States Institute of Peace, "What is Boko Haram?." Last modified 2012. Accessed April 9, 2013. http://www.usip.org.

Buhayar, Noah. PBS, "Oil and Politics in Nigeria." Last modified 2007. Accessed April 8, 2013. www.pbs.org.

Bascom, William. Urbanization Among the Yoruba. Culture and Societies of Africa. Edited by Simon and Phoebe Ottenberg. New York: Random House, 1960.

Greenberg, Joseph H. Some Aspects of Negro-Mohammedan Culture Contact Among the Hausa. Culture and Societies of Africa. Edited by Simon and Phoebe Ottenberg. New York: Random House, 1960.

Levinson, David. Ethnic Groups Worldwide: A Ready Reference Handbook. Santa Barbara: Greenwood, 1998.

Ehwarieme, William. "Between the Devil and the Deep Blue Sea: The Displacement of Ethnicity by Corruption in Nigeria's Electoral Politics." Journal of Third World Studies. 26. no. 2 (2011): 181-206.

Paden, John. Religion and Political Culture in Kano. University of California Press: Berkeley and Los Angeles, 1973.

Suberu, Rotimi. Federalism and Ethnic Conflict in Nigeria. Washington D.C.: United States Institute of Peace, 2001.

Joshua Project, “Nigeria”. Last modified April 2013. Accessed April 2013. http://www.joshuaproject.net.

In 2023, Black adults had the highest obesity rates of any race or ethnicity in the United States, followed by American Indians/Alaska Natives and Hispanics. As of that time, around 42 percent of all Black adults were obese. Asians/Pacific Islanders had by far the lowest obesity rates. Obesity in the United States Obesity is a present and growing problem in the United States. An astonishing 33 percent of the adult population in the U.S. is now considered obese. Obesity rates can vary substantially by state, with around 41 percent of the adult population in West Virginia reportedly obese, compared to 25 percent of adults in Colorado. The states with the highest rates of obesity include West Virginia, Mississippi, and Arkansas. Diabetes Being overweight and obese can lead to a number of health problems, including heart disease, cancer, and diabetes. Being overweight or obese is one of the most common causes of type 2 diabetes, a condition in which the body does not use insulin properly, causing blood sugar levels to rise. It is estimated that just over eight percent of adults in the U.S. have been diagnosed with diabetes. Diabetes is now the eighth leading cause of death in the United States, accounting for three percent of all deaths.

BackgroundThe IRONMAN® (IM) triathlon is a popular multi-sport, where age group athletes often strive to qualify for the IM World Championship in Hawaii. The aim of the present study was to investigate the location of the fastest IM racecourses for age group IM triathletes. This knowledge will help IM age group triathletes find the best racecourse, considering their strengths and weaknesses, to qualify.ObjectiveTo determine the fastest IM racecourse for age group IM triathletes using descriptive and predictive statistical methods.MethodsWe collected and analyzed 677,702 age group IM finishers’ records from 228 countries participating in 444 IM competitions held between 2002 and 2022 across 66 event locations. Locations were ranked by average race speed (performance), and countries were sorted by number of records in the sample (participation). A predictive model was built with race finish time as the predicted variable and the triathlete’s gender, age group, country of origin, event location, average air, and water temperatures in each location as predictors. The model was trained with 75% of the available data and was validated against the remaining 25%. Several model interpretability tools were used to explore how each predictor contributed to the model’s predictive power, from which we intended to infer whether one or more predictors were more important than the others.ResultsThe average race speed ranking showed IM Vitoria-Gasteiz (1 race only), IM Copenhagen (8 races), IM Hawaii (18 races), IM Tallinn (4 races) and IM Regensburg (2 races) in the first five positions. The XG Boost Regressor model analysis indicated that the IM Hawaii course was the fastest race course and that male athletes aged 35 years and younger were the fastest. Most of the finishers were competing in IM triathlons held in the US, such as IM Wisconsin, IM Florida, IM Lake Placid, IM Arizona, and IM Hawaii, where the IM World Championship took place. However, the fastest average times were achieved in IM Vitoria-Gasteiz, IM Copenhagen, IM Hawaii, IM Tallin, IM Regensburg, IM Brazil Florianopolis, IM Barcelona, or IM Austria with the absolutely fastest race time in IM Hawaii. Most of the successful IM finishers originated from the US, followed by athletes from the UK, Canada, Australia, Germany, and France. The best mean IM race times were achieved by athletes from Austria, Germany, Belgium, Switzerland, Finland, and Denmark. Regarding environmental conditions, the best IM race times were achieved at an air temperature of ∼27°C and a water temperature of ∼24°C.ConclusionsIM age group athletes who intend to qualify for IM World Championship in IM Hawaii are encouraged to participate in IM Austria, IM Copenhagen, IM Brazil Florianopolis, and/or IM Barcelona in order to achieve a fast race time to qualify for the IM World Championship in IM Hawaii where the top race times were achieved. Most likely these races offer the best ambient temperatures for a fast race time.

This statistic shows the population of the United States in the final census year before the American Civil War, shown by race and gender. From the data we can see that there were almost 27 million white people, 4.5 million black people, and eighty thousand classed as 'other'. The proportions of men to women were different for each category, with roughly 700 thousand more white men than women, over 100 thousand more black women than men, and almost three times as many men than women in the 'other' category. The reason for the higher male numbers in the white and other categories is because men migrated to the US at a higher rate than women, while there is no concrete explanation for the statistic regarding black people.

About this dataset

Context

The dataset presents the median household income across different racial categories in Earth. 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 Earth population by race & ethnicity, the population is predominantly White. This particular racial category constitutes the majority, accounting for 60.83% of the total residents in Earth. Notably, the median household income for White households is $45,987. Interestingly, White is both the largest group and the one with the highest median household income, which stands at $45,987.

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

College Completion Dataset

Graduation Rates, Race, Efficiency Measures and More

By Jonathan Ortiz [source]

About this dataset

This College Completion dataset provides an invaluable insight into the success and progress of college students in the United States. It contains graduation rates, race and other data to offer a comprehensive view of college completion in America. The data is sourced from two primary sources – the National Center for Education Statistics (NCES)’ Integrated Postsecondary Education System (IPEDS) and Voluntary System of Accountability’s Student Success and Progress rate.

At four-year institutions, the graduation figures come from IPEDS for first-time, full-time degree seeking students at the undergraduate level, who entered college six years earlier at four-year institutions or three years earlier at two-year institutions. Furthermore, colleges report how many students completed their program within 100 percent and 150 percent of normal time which corresponds with graduation within four years or six year respectively. Students reported as being of two or more races are included in totals but not shown separately

When analyzing race and ethnicity data NCES have classified student demographics since 2009 into seven categories; White non-Hispanic; Black non Hispanic; American Indian/ Alaskan native ; Asian/ Pacific Islander ; Unknown race or ethnicity ; Non resident with two new categorize Native Hawaiian or Other Pacific Islander combined with Asian plus students belonging to several races. Also worth noting is that different classifications for graduate data stemming from 2008 could be due to variations in time frame examined & groupings used by particular colleges – those who can’t be identified from National Student Clearinghouse records won’t be subjected to penalty by these locations .

When it comes down to efficiency measures parameters like “Awards per 100 Full Time Undergraduate Students which includes all undergraduate completions reported by a particular institution including associate degrees & certificates less than 4 year programme will assist us here while we also take into consideration measures like expenditure categories , Pell grant percentage , endowment values , average student aid amounts & full time faculty members contributing outstandingly towards instructional research / public service initiatives .

When trying to quantify outcomes back up Median Estimated SAT score metric helps us when it is derived either on 25th percentile basis / 75th percentile basis with all these factors further qualified by identifying required criteria meeting 90% threshold when incoming students are considered for relevance . Last but not least , Average Student Aid equalizes amount granted by institution dividing same over total sum received against what was allotted that particular year .

All this analysis gives an opportunity get a holistic overview about performance , potential deficits &

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How to use the dataset

This dataset contains data on student success, graduation rates, race and gender demographics, an efficiency measure to compare colleges across states and more. It is a great source of information to help you better understand college completion and student success in the United States.

In this guide we’ll explain how to use the data so that you can find out the best colleges for students with certain characteristics or focus on your target completion rate. We’ll also provide some useful tips for getting the most out of this dataset when seeking guidance on which institutions offer the highest graduation rates or have a good reputation for success in terms of completing programs within normal timeframes.

Before getting into specifics about interpreting this dataset, it is important that you understand that each row represents information about a particular institution – such as its state affiliation, level (two-year vs four-year), control (public vs private), name and website. Each column contains various demographic information such as rate of awarding degrees compared to other institutions in its sector; race/ethnicity Makeup; full-time faculty percentage; median SAT score among first-time students; awards/grants comparison versus national average/state average - all applicable depending on institution location — and more!

When using this dataset, our suggestion is that you begin by forming a hypothesis or research question concerning student completion at a given school based upon observable characteristics like financ...