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.

In 2011, 87.2 percent of the total population of the United Kingdom were white British. A positive net migration in recent years combined with the resultant international relationships following the wide-reaching former British Empire has contributed to an increasingly diverse population.

Varied ethnic backgrounds

Black British citizens, with African and/or African-Caribbean ancestry, are the largest ethnic minority population, at three percent of the total population. Indian Britons are one of the largest overseas communities of the Indian diaspora and make up 2.3 percent of the total UK population. Pakistani British citizens, who make up almost two percent of the UK population, have one of the highest levels of home ownership in Britain.

Racism in the United Kingdom

Though it has decreased in comparison to the previous century, the UK has seen an increase in racial prejudice during the first decade and a half of this century. Racism and discrimination continues to be part of daily life for Britain’s ethnic minorities, especially in terms of work, housing, and health issues. Moreover, the number of hate crimes motivated by race reported since 2012 has increased, and in 2017/18, there were 3,368 recorded offenses of racially or religiously aggravated assault with injury, almost a thousand more than in 2013/14.

About this dataset

Context

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

Key observations

With a zero Hispanic population, White Earth is 100% Non-Hispanic. Among the Non-Hispanic population, the largest racial group is White alone with a population of 76 (100% of the total Non-Hispanic population).

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 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 White Earth
• Population: The population of the racial category (for Non-Hispanic) in the White Earth is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of White Earth 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 White Earth Population by Race & Ethnicity. You can refer the same here

Prior to the civil war in the 1990’s ethnic tension caused many rivalries between groups. This was common between the Temne, with their allies the Limba, and the Mende, with their allies the Sherbro, Kissi, and Gola groups. Even with this history of ethnic conflict it does not appear to be a significant factor that contributed to the civil war as the war focused on control of diamond mines. With the civil war over for more than a decade the country is relatively peaceful. There are no serious ethnic conflicts or rivalries. Limba – Limba populations are found in other West African countries although 90% reside in Sierra Leone. The majority are Muslim, having been introduced to Islam in the late nineteenth century. This is much later than their neighbors. To prevent too much Westernization, the Limba often send their children to Islamic schools. Mande – The Mande are a large ethnic group in West Africa that is comprised of many smaller groups. The Mande people speak a variety of Mande languages. Most practice agriculture, animal husbandry, and trade. They practice a patrilineal society having the eldest male serve as lineage head. With so many Mande groups spread over West Africa there is much variation among language and culture. Mel – The Mel within Sierra Leone are comprised of the Gola and the Kissi. Similar to other West Africa groups, the Gola participate in secret societies. The most important occurs around the age of puberty and these societies seek to socialize youth with Gola culture. The Kissi are increasingly becoming culturally influenced by the Mende people. Soso - The Soso were introduced to Islam in the seventeenth century and they are now overwhelmingly Sunni Muslim, of the Maliki School. Many still perform ritual ceremonies from indigenous religions. They are often influenced by neighboring groups. Temne – The Temne are one of the largest ethnic groups in the country. While the capital of Freetown is home to many groups, the largest number of people belong to the Temne ethnicity. The majority are Muslim, having been introduced to Islam in the seventeenth century. Some Temne still practice indigenous religions or incorporate them into their practice of Islam. Similar to other groups in the country, the Temne also have secret socieites. The Temne use these socieites to learn about the Temne culture. Although many have convertered to Islam or Christianity, it is common to incorporate indigenous religious beliefs. Attribute Table Field DescriptionsISO3-International Organization for Standardization 3-digit country codeADM0_NAME-Administration level zero identification / namePEOPLEGP_1-People Group level 1PEOPLEGP_2-People Group level 2PEOPLEGP_3-People Group level 3PEOPLEGP_4-People Group level 4PEOPLEGP_5-People Group level 5ALT_NAMES-Alternative names or spellings for a people groupCOMMENTS-Comments or notes regarding the people groupSOURCE_DT-Source one creation dateSOURCE-Source oneSOURCE2_DT-Source two creation dateSOURCE2-Source twoCollectionThis feature class was constructed by referencing and combining information from Murdock’s Map of Africa (1959) with other anthropological literature pertaining to Sierra Leone ethnicity. The information was then processed through DigitalGlobe’s AnthropMapper program to generate more accurate ethnic coverage boundaries. Anthromapper uses geographical terrain features, combined with a watershed model, to predict the likely extent of ethnic and linguistic influence.Metadata and data pertaining to the feature class was collected from the review of Murdock’s Map of Africa (1959) in conjunction with information from anthropological research pertaining to ethnicity in northern Africa. While efforts were made to secure the accuracy of the geographic location of existing ethnicities, many are transient in nature and continue to migrate. Further, it should be stressed that ethnic groups listed represent the prominent people groups in Sierra Leone; however, numerous subgroups may exist below this tier. 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 is not responsible for the accuracy and completeness of data compiled from outside sources.Sources (HGIS)Anthromapper. DigitalGlobe, September 2014.Gonen, Amiram. The Encyclopedia of the Peoples of the World. New York: Henry Holt and Company, 1993.Levinson, David. Encyclopedia of World Cultures: Africa and the Middle East. Boston: G.K. Hall and Co., 1995.Murdock, George Peter. Tribal Map of Africa from Africa: Its Peoples and Their Culture History. New York: McGraw-Hill Book Co., January 1959.Olson, James S. The Peoples of Africa: An Ethnohistorical Dictionary. Westport: Greenworod Press, 1996.The Diagram Group. Encyclopedia African Peoples. London: Diagram Visual Information, 2000.Yakan, Mohamad Z. Almanac of African Peoples and Nations. New Brunswick: Transaction Publishers, 1999.Sources (Metadata)Gonen, Amiram. The Encyclopedia of the Peoples of the World. New York: Henry Holt and Company, 1993.Levinson, David. Encyclopedia of World Cultures: Africa and the Middle East. Boston: G.K. Hall and Co., 1995.Murdock, George Peter. Tribal Map of Africa from Africa: Its Peoples and Their Culture History. New York: McGraw-Hill Book Co., January 1959.Notholt, Stuart A. Fields of Fire: An atlas of ethnic conflict. London: Stuart Notholt Communications Ltd, 2008.Olson, James S. The Peoples of Africa: An Ethnohistorical Dictionary. Westport: Greenworod Press, 1996.The Diagram Group. Encyclopedia African Peoples. London: Diagram Visual Information, 2000.University of Iowa Museum of Art, “Sierra Leone; Gola or Vai peoples, Lansana Ngumoi”. January 2006. Accessed December 2014. http://uima.uiowa.edu.Yakan, Mohamad Z. Almanac of African Peoples and Nations. New Brunswick: Transaction Publishers, 1999.

About this dataset

Context

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

Key observations

The percent distribution of Globe population by race (across all racial categories recognized by the U.S. Census Bureau): 58.09% are white, 2.70% are Black or African American, 5.26% are American Indian and Alaska Native, 2.92% are Asian, 0.12% are Native Hawaiian and other Pacific Islander, 11.37% are some other race and 19.54% 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 Globe
• Population: The population of the racial category (excluding ethnicity) in the Globe is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Globe 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 Globe Population by Race & Ethnicity. You can refer the same here

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.

Context

This dataset is in context of the real world data science work and how the data analyst and data scientist work.

Content

The dataset consists of four columns Year, Level_1(Ethnic group/gender), Level_2(Age group), and population

Acknowledgements

I would sincerely thank GeoIQ for sharing this dataset with me along with tasks. Just having a basic knowledge of Pandas and Numpy and other python data science libraries is not enough. How can you execute tasks and how can you preprocess the data before making any prediction is very important. Most of the datasets in Kaggle are clean and well arranged but this dataset thought me how real world data science and analysis works. Every data science beginner must work on this dataset and try to execute the tasks. It would only give them a good exposer to the real data science world.

Inspiration

1. Identify the largest Ethnic group in Singapore. Their average population growth over the years and what proportion of the total population do they constitute.
2. Identify the largest age group in Singapore. Their average population growth over the years and what proportion of the total population do they constitute.
3. Identify the group (by age, ethnicity and gender) that: a. Has shown the highest growth rate b. Has shown the lowest growth rate c. Has remained the same
4. Plot a graph for population trends

About this dataset

Context

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

Key observations

Of the Non-Hispanic population in Blue Earth County, the largest racial group is White alone with a population of 59,101 (89.37% 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 Blue Earth County
• Population: The population of the racial category (for Non-Hispanic) in the Blue Earth County is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Blue Earth 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 Blue Earth County Population by Race & Ethnicity. You can refer the same here

About this dataset

Context

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

Key observations

Of the Non-Hispanic population in Earth, the largest racial group is White alone with a population of 275 (86.75% 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 Earth
• Population: The population of the racial category (for Non-Hispanic) in the Earth is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Earth 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 Earth Population by Race & Ethnicity. You can refer the same here

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.

(UNCLASSIFIED) There are three main ethnolinguistic groups that made up ethnicity in Liberia; Mel, Mande, and Kru. The ethnic mix of Liberia has contributed to a rich culture as well as ethnic tension. It is common for politics in West Africa to divide along ethnic lines. Ethnic tension along with poor economic and social conditions and political instability were the leading causes for the two recent civil wars in the country. This first began in 1989 when the National Patriotic Front of Liberia, led by Charles Taylor, rose up against the Kran dominant government lead by Samuel Doe. The first civil war ended in 1997 with Charles Taylor formally voted into power. During the civil war Taylor commonly targeted Muslim Mande populations and the Kran for being the two groups most associated with the Doe regime. The opposition to Taylor retaliated by attacking Christian sites. Taylor’s regime was chaotic which led to a second civil war that began in 1999 with full scale war in 2003; a cease fire was signed the same year which ended the civil war. The actions during both civil wars show how politics and ethnicity go hand in hand and can produce ethnoreligious violence. Many in Liberia participate in secret societies known as hale, this is the most controlling and unifying force in Liberian culture with most participants belonging to one or more societies. They are both religious and political in nature and lay out acceptable and unacceptable behavior. There are numerous different hale societies offering regulations on how someone should act in society. The two most important hale societies are the men’s Poro and the female’s Sande, with participants joining at puberty to be taught the ideals of manhood and womanhood. Initiations are secret and performed in the forest. Reports state that initiation into the Sande society often includes female genital mutilation while boys undergo circumcisions in the Poro society. Belonging to either the Poro or Sande society is so important among traditional communities that those who do not join are not considered a member of the village, clan, or tribe. Mande - The Mande people group is the largest ethnicity in Liberia and has multiple subgroups. Agriculture, trade, and animal husbandry are common economic activities among the Mande people. They are patrilineal and the oldest male serves as the lineage head. Class structure is also common among Mande people typically consisting of royal, noble, commoner, artisan, and former slave classes. The largest Mande subgroup are the Kpelle and alone they account for 20.3 percent of the total Liberian population. The Kpelle organize themselves into many chiefdoms each of which are led by a paramount chief. While mass conversion to Christianity happened in the nineteenth century many still practice indigenous belief systems either alone or in combination with Christianity. Mel - The Mel group in Liberia is comprised of the Kissi and the Gola, 4.8 percent and 4.4 percent of the population respectively. Most Kissi are either Christian, animists, or a combination of the two. A small population, roughly 9 percent, is Muslim. Most are subsistence farmers or urban laborers. During the first civil war they were in conflict with the Kran. Kru – The Kru are organized based on patrilineal relationships and divided in many subgroups. As with many other ethnic groups in the region, while many have converted to Christianity there is still a significant portion that still adheres to indigenous beliefs or incorporates them into Christianity. Indigenous beliefs are passed through folklores and proverbs. Attribute Table Field DescriptionsISO3 - International Organization for Standardization 3-digit country code ADM0_NAME - Administration level zero identification / name PEOPLEGP_1 - People Group level 1 PEOPLEGP_2 - People Group level 2 PEOPLEGP_3 - People Group level 3 PEOPLEGP_4 - People Group level 4 PEOPLEGP_5 - People Group level 5 ALT_NAMES - Alternative names or spellings for a people group COMMENTS - Comments or notes regarding the people group SOURCE_DT - Source one creation date SOURCE - Source one SOURCE2_DT - Source two creation date SOURCE2 - Source two CollectionThe feature class was constructed by combining information from Murdock’s Map of Africa (1959) with other anthropological literature pertaining to Liberian ethnicity. The information was then processed through DigitalGlobe’s AnthropMapper program to generate more accurate ethnic coverage boundaries. Anthromapper uses geographical terrain features, combined with a watershed model, to predict the likely extent of ethnic and linguistic influence. 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 is not responsible for the accuracy and completeness of data compiled from outside sources.Sources (HGIS)Anthromapper. DigitalGlobe, September 2014.Gonen, Amiram. The Encyclopedia of the Peoples of the World. New York: Henry Holt and Company, 1993.Levinson, David. Encyclopedia of World Cultures: Africa and the Middle East. Boston: G.K. Hall and Co., 1995.Minority Rights Group International. World Directory of Minorities and Indigenous Peoples, “Liberia Overview.” January 2005. Accessed September 23, 2014. http://www.minorityrights.org/directory.Murdock, George Peter. Tribal Map of Africa from Africa: Its Peoples and Their Culture History. New York: McGraw-Hill Book Co., January 1959.Olson, James S. The Peoples of Africa: An Ethnohistorical Dictionary. Westport: Greenworod Press, 1996.The Diagram Group. Encyclopedia African Peoples. London: Diagram Visual Information, 2000.Yakan, Mohamad Z. Almanac of African Peoples and Nations. New Brunswick: Transaction Publishers, 1999.Sources (Metadata)Central Intelligence Agency. The World FactBook, “Liberia.” June 20, 2014. Accessed September 22, 2014. https://www.cia.gov/index.html.Gonen, Amiram. The Encyclopedia of the Peoples of the World. New York: Henry Holt and Company, 1993.Humanitarian News and Analysis, “Liberia: FGM continues in rural secrecy.” September 24, 2008. Accessed September 23, 2014. http://www.irinnews.org/.Levinson, David. Encyclopedia of World Cultures: Africa and the Middle East. Boston: G.K. Hall and Co., 1995.Olson, James S. The Peoples of Africa: An Ethnohistorical Dictionary. Westport: Greenworod Press, 1996.The Diagram Group. Encyclopedia African Peoples. London: Diagram Visual Information, 2000.Vogel, Health. Blogging without Maps: a Journey through Liberia, “Societies within Society – The Secret Societies of Liberia.” June 16, 2012. Accessed September 23, 2014. http://bloggingwithoutmaps.blogspot.com/.Yakan, Mohamad Z. Almanac of African Peoples and Nations. New Brunswick: Transaction Publishers, 1999.

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

About this dataset

Context

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

Key observations

Of the Non-Hispanic population in Black Earth, the largest racial group is White alone with a population of 1,565 (95.72% 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 Black Earth
• Population: The population of the racial category (for Non-Hispanic) in the Black Earth is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Black Earth 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 Black Earth Population by Race & Ethnicity. You can refer the same here

Vietnam has one of the fastest economic growth rates in the world in recent years. However, ethnic groups in this country may not equally share the benefit of this wealth increase. Using data from household surveys in Vietnam, this paper offers an analysis of the welfare outcomes between ethnic groups in poverty, education, labor market participation, labor earnings, child labor, health, nutrition and social protection. Ethnic minority groups fare significantly worse than ethnic majority groups for most indicators. This paper concludes with some policy recommendations to narrow the ethnic gap.

BackgroundElectronic health records (EHRs) are increasingly used to investigate health inequalities across ethnic groups. While there are some studies showing that the recording of ethnicity in EHR is imperfect, there is no robust evidence on the accuracy between the ethnicity information recorded in various real-world sources and census data.Methods and findingsWe linked primary and secondary care NHS England data sources with Census 2021 data and compared individual-level agreement of ethnicity recording in General Practice Extraction Service (GPES) Data for Pandemic Planning and Research (GDPPR), Hospital Episode Statistics (HES), Ethnic Category Information Asset (ECIA), and Talking Therapies for anxiety and depression (TT) with ethnicity reported in the census. Census ethnicity is self-reported and, therefore, regarded as the most reliable population-level source of ethnicity recording. We further assessed the impact of multiple approaches to assigning a person an ethnic category. The number of people that could be linked to census from ECIA, GDPPR, HES, and TT were 47.4m, 43.5m, 47.8m, and 6.3m, respectively. Across all 4 data sources, the White British category had the highest level of agreement with census (≥96%), followed by the Bangladeshi category (≥93%). Levels of agreement for Pakistani, Indian, and Chinese categories were ≥87%, ≥83%, and ≥80% across all sources. Agreement was lower for Mixed (≤75%) and Other (≤71%) categories across all data sources. The categories with the lowest agreement were Gypsy or Irish Traveller (≤6%), Other Black (≤19%), and Any Other Ethnic Group (≤25%) categories.ConclusionsCertain ethnic categories across all data sources have high discordance with census ethnic categories. These differences may lead to biased estimates of differences in health outcomes between ethnic groups, a critical data point used when making health policy and planning decisions.

About this dataset

Context

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

Key observations

Of the Non-Hispanic population in Black Earth town, the largest racial group is White alone with a population of 392 (97.03% 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 Black Earth town
• Population: The population of the racial category (for Non-Hispanic) in the Black Earth town is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Black Earth town 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 Black Earth town Population by Race & Ethnicity. You can refer the same here

In the middle of 2023, about 60 percent of the global population was living in Asia.The total world population amounted to 8.1 billion people on the planet. In other words 4.7 billion people were living in Asia as of 2023. Global populationDue to medical advances, better living conditions and the increase of agricultural productivity, the world population increased rapidly over the past century, and is expected to continue to grow. After reaching eight billion in 2023, the global population is estimated to pass 10 billion by 2060. Africa expected to drive population increase Most of the future population increase is expected to happen in Africa. The countries with the highest population growth rate in 2024 were mostly African countries. While around 1.47 billion people live on the continent as of 2024, this is forecast to grow to 3.9 billion by 2100. This is underlined by the fact that most of the countries wit the highest population growth rate are found in Africa. The growing population, in combination with climate change, puts increasing pressure on the world's resources.

Veterans by largest Race and Ethnicity categories, by Health and Human Services Service Area.

This indicator provides the provides the percentage of civilian veterans by race/ethnicity group.

Veterans are persons 18 years and over who ever served on active duty. A civilian veteran refers to persons 18 years or older who served on active duty in any military branch or served in the National Guard or military reserves (only those ever called or ordered to active duty were classified as veterans). It does not include persons currently in active duty.

Source: U.S. Census Bureau; 2013-2017 American Community Survey 5-Year Estimates, Table S2101.

Do ethnic majorities and minorities have diverging preferences for fiscal capacity? Do these preferences converge during national emergencies such as interstate war? In this paper, we provide evidence from a natural experiment to demonstrate that politically salient minority-majority divisions undermine the development of fiscal capacity. In addition, we show that the pressure of interstate war is insufficient to supersede differences in support for the expansion of state's capacity for taxation between majority and minority groups. More specifically, we employ a regression discontinuity design using a natural border that separates linguistic groups and municipality outcomes of a popular vote on the introduction of direct taxation at federal level in Switzerland during the First World War. The findings suggest that salient minority-majority divisions have a negative effect on the expansion of states' capacity for taxation even during periods of interstate war.

Dataset from Singapore Department of Statistics. For more information, visit https://data.gov.sg/datasets/d_3de421ca89ff660c9fdc00debbf9764e/view