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 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.

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.

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.

About this dataset

Context

The dataset tabulates the Non-Hispanic population of Blue Earth City township by race. It includes the distribution of the Non-Hispanic population of Blue Earth City township 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 City township across relevant racial categories.

Key observations

Of the Non-Hispanic population in Blue Earth City township, the largest racial group is White alone with a population of 462 (99.35% 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 Blue Earth City township
• Population: The population of the racial category (for Non-Hispanic) in the Blue Earth City township is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Blue Earth City township 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 City township Population by Race & Ethnicity. You can refer the same here

About this dataset

Context

The dataset tabulates the Non-Hispanic population of White Earth township by race. It includes the distribution of the Non-Hispanic population of White Earth township 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 township across relevant racial categories.

Key observations

Of the Non-Hispanic population in White Earth township, the largest racial group is American Indian and Alaska Native alone with a population of 437 (50.11% 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 White Earth township
• Population: The population of the racial category (for Non-Hispanic) in the White Earth township is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of White Earth township 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 township Population by Race & Ethnicity. You can refer the same here

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 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

About this dataset

Context

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

Key observations

Of the Non-Hispanic population in Lincoln township, the largest racial group is White alone with a population of 188 (99.47% 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 Lincoln township
• Population: The population of the racial category (for Non-Hispanic) in the Lincoln township is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Lincoln township 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 Lincoln township Population by Race & Ethnicity. You can refer the same here

(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.

Source: SINGAPORE DEPARTMENT OF STATISTICS

Data Last Updated: 29/03/2016

Update Frequency: 10 years

Survey period: Census of Population 2000

Adapted from: https://tablebuilder.singstat.gov.sg/table/CT/8876

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.

In 2023, 17.9 percent of Black people living in the United States were living below the poverty line, compared to 7.7 percent of white people. That year, the total poverty rate in the U.S. across all races and ethnicities was 11.1 percent. Poverty in the United States Single people in the United States making less than 12,880 U.S. dollars a year and families of four making less than 26,500 U.S. dollars a year are considered to be below the poverty line. Women and children are more likely to suffer from poverty, due to women staying home more often than men to take care of children, and women suffering from the gender wage gap. Not only are women and children more likely to be affected, racial minorities are as well due to the discrimination they face. Poverty data Despite being one of the wealthiest nations in the world, the United States had the third highest poverty rate out of all OECD countries in 2019. However, the United States' poverty rate has been fluctuating since 1990, but has been decreasing since 2014. The average median household income in the U.S. has remained somewhat consistent since 1990, but has recently increased since 2014 until a slight decrease in 2020, potentially due to the pandemic. The state that had the highest number of people living below the poverty line in 2020 was California.

Malaysia HIBAS: Main Source of Income: Current Transfers: Others data was reported at 8.100 % in 2016. This records an increase from the previous number of 6.920 % for 2014. Malaysia HIBAS: Main Source of Income: Current Transfers: Others data is updated yearly, averaging 7.500 % from Dec 2012 (Median) to 2016, with 3 observations. The data reached an all-time high of 8.100 % in 2016 and a record low of 6.920 % in 2014. Malaysia HIBAS: Main Source of Income: Current Transfers: Others data remains active status in CEIC and is reported by Department of Statistics. The data is categorized under Global Database’s Malaysia – Table MY.H028: Household Income and Basic Amenities Survey: Main Source of Income: by Ethnic Group.

Malaysia HIBAS: Main Source of Income: Property and Investment: Bumiputera data was reported at 11.500 % in 2016. This records an increase from the previous number of 10.300 % for 2014. Malaysia HIBAS: Main Source of Income: Property and Investment: Bumiputera data is updated yearly, averaging 10.300 % from Dec 2012 (Median) to 2016, with 3 observations. The data reached an all-time high of 11.500 % in 2016 and a record low of 8.900 % in 2012. Malaysia HIBAS: Main Source of Income: Property and Investment: Bumiputera data remains active status in CEIC and is reported by Department of Statistics. The data is categorized under Global Database’s Malaysia – Table MY.H028: Household Income and Basic Amenities Survey: Main Source of Income: by Ethnic Group.

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.

Data extraction of allele, genotype, haplotypes, and acetylator status from all articles included in this systematic review.

With a population of over 1.4 billion and 56 ethnic groups, China is the largest country in the world in terms of population. Han is the main ethnic group of China (93%). To provide genetic data of Y chromosomal STRs from Anshan City, Northeast of China, for the first time, which will serve as a reference database for forensic and population studies. We report data of 20 Y-chromosomal short tandem repeats (YSTRs) genotyped with the Goldeneye® 20Y kit in 270 Han individuals residing in Anshan City of China. A total of 170 alleles were observed on 20 Y-STRs. The gene diversities varied from 0.3460 (DYS391) to 0.9692 (DYS385). Overall haplotype diversity was almost 1 with 261 unique haplotypes, while the discrimination capacity (DC) was 0.9814. Pairwise Rst and Fst genetic analyses, MDS plot, N-J tree and PCA showed the genetic structure of Anshan Han population was significantly different from other minority groups like Tibetans and Kazakhs. Results of this study showed that Goldeneye® 20Y system loci have strong discriminatory power in the Anshan Han population of China which makes this kit suitable for forensic applications in this ethnic group.

Abstract

The World Values Survey (www.worldvaluessurvey.org) is a global network of social scientists studying changing values and their impact on social and political life, led by an international team of scholars, with the WVS association and secretariat headquartered in Stockholm, Sweden.

The survey, which started in 1981, seeks to use the most rigorous, high-quality research designs in each country. The WVS consists of nationally representative surveys conducted in almost 100 countries which contain almost 90 percent of the world’s population, using a common questionnaire. The WVS is the largest non-commercial, cross-national, time series investigation of human beliefs and values ever executed, currently including interviews with almost 400,000 respondents. Moreover the WVS is the only academic study covering the full range of global variations, from very poor to very rich countries, in all of the world’s major cultural zones.

The WVS seeks to help scientists and policy makers understand changes in the beliefs, values and motivations of people throughout the world. Thousands of political scientists, sociologists, social psychologists, anthropologists and economists have used these data to analyze such topics as economic development, democratization, religion, gender equality, social capital, and subjective well-being. These data have also been widely used by government officials, journalists and students, and groups at the World Bank have analyzed the linkages between cultural factors and economic development.

Geographic coverage

National.

Analysis unit

Household Individual

Universe

National Population, Both sexes,18 and more years.

Kind of data

Sample survey data [ssd]

Sampling procedure

Sample size: 1512

Stratified, random sample of Singapore citizens Lower age cutoff was set at 15. No clusters were used. Substitution was used when the person no longer lives in the address stated or when the case is not contactable after 3 tries. Sample was stratified by ethnicity at the sample design, and stratified by age after completion of fieldwork.

Remarks about sampling:

1. The majority group was undersampled, and minority ethnic groups oversampled,
2. The questionnaire was slightly modified; however, item numbering remains similar to the WVS master questionnaire.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaire was translated by a specialist translator. It wasn't back translated to english but was pre-tested. The pre-test cases were selected to reflect as far as possible the profile of the population. One pre-test involving 39 cases. The following WVS questions were excluded: V12, V37- 38, V137-140, V147-162, V163, V168-173, V177-181-190, V200-203, V220-222, V243 Reason(s) not included: Not applicable to the Singapore context. Some questions are politically sensitive. Moreover, the questionnaire was rather long, so most non-core questions were omitted, where possible.

Response rate

Response rate is 79%, and non-response rate is 21%. Total number of starting names/addresses: 2610 - Addresses which could not be traced at all: 183 - Addresses established as empty, demolished or containing no private dwellings: 26 - No contact with selected person: 341 - Refusal at selected address: 379 - Personal refusal by selected respondent: 379 - Full productive interview: 1512 - Partial productive interview: 21

Sampling error estimates

Estimated error: 2.6

Abstract

The World Values Survey (www.worldvaluessurvey.org) is a global network of social scientists studying changing values and their impact on social and political life, led by an international team of scholars, with the WVS association and secretariat headquartered in Stockholm, Sweden. The survey, which started in 1981, seeks to use the most rigorous, high-quality research designs in each country. The WVS consists of nationally representative surveys conducted in almost 100 countries which contain almost 90 percent of the world’s population, using a common questionnaire. The WVS is the largest non-commercial, cross-national, time series investigation of human beliefs and values ever executed, currently including interviews with almost 400,000 respondents. Moreover the WVS is the only academic study covering the full range of global variations, from very poor to very rich countries, in all of the world’s major cultural zones. The WVS seeks to help scientists and policy makers understand changes in the beliefs, values and motivations of people throughout the world. Thousands of political scientists, sociologists, social psychologists, anthropologists and economists have used these data to analyze such topics as economic development, democratization, religion, gender equality, social capital, and subjective well-being. These data have also been widely used by government officials, journalists and students, and groups at the World Bank have analyzed the linkages between cultural factors and economic development.

Geographic coverage

This survey covers Croatia.

Analysis unit

• Household
• Individual

Universe

The WVS for Croatia covers national population, aged 18 years and over, for both sexes.

Kind of data

Sample survey data [ssd]

Sampling procedure

For the purpose of this survey research the design of stratified random sampling was applied. First, the territory of the Republic of Croatia was divided into 7 distinct geographic regions or sets of regions, and these were: 1. Istra; 2. Rijeka and surrounding; 3. Dalmacija; 4. Slavonija and Podravina; 5. Zagreb, Zagorje and Prigorje; 6. Medimurje and Moslavina; 7. Zumberak, Kordun, Banija and Lika.

Each of the regions covers various number of small, medium, and large cities/settlements (small with less than 2000 inhabitants; medium with 2000-30.000; and large with more than 30.000 inhabitants). So, two-way stratification: by region, and by size of cities/settlements, was used. By the data from the Census 91 outside of ex-occupied regions of The Republic of Croatia there live 4.390.651 of inhabitants. The geographic distribution of all the inhabitants is supposed to be know from the Census. The people live in 5979 cities/settlements of Croatia: 1.703.962 of them live in large cities, 967.621 live in medium size cities/settlements, and the rest of 1.719.068 live in small ones. It is obvious that 39% of inhabitants live in large, 22% in medium, and 39% in small cities. In each region the number of inhabitants, as well as the number of cities of a certain size varies, and the distribution of inhabitants by size of city for many reasons differs a lot. But, the population to be sampled for this survey consists only of adult persons (older than 18) and is of the size N=3.590.366. There is the assumption that the geographic distribution of adult persons is the same as the distribution of all the persons. The planned fixed size of the entire stratified sample was N=1200 of adult persons, for what the proportionate allocation of units, according to the Census data, was constructed. The cities were sampled at random using random digit generator with probabilities proportionate to the size (the measure of size being the number of inhabitants) to ensure that in the further stage of the sampling procedure every person has got the same probability of selection. The number of cities sampled was determined considering the relevant traveling costs. It was decided that every large city (with more than 30.000 inhabitants) has to be included in the sample by imperative. In the regions without such cities, the same rule for the medium size of city/settlement was applied.

Mode of data collection

Face-to-face [f2f]

Research instrument

The WVS questionnaire was in Croatian. Some special variable labels have been included, such as: V56 neighbors: Muslims and V149 Institution: The European Union. Special categories labels are V203/V204 Geographical affinity. Country Specific Variables are: V210 a V212 Political Parties. The variable 206 born in this country is also different. The sample was designed to be representative of the entire adult population, i.e. 18 years and older, of your country. The lower age cut-off for the sample was 18 and there was not any upper age cut-off for the sample. The ethnic group of the respondent was not asked in the interview. In the cases of Eastern Europe Countries where the ethnic group is missing the language chosen for interview is the only indicator available to control the ethnic composition of the samples. Nevertheless, native language indicated in the cesus of 1989 and language chosen for interview are not exactly the same, since the first is rather differentiated whereas for the last the alternatives to choose between where only the national language or Russian.

Response rate

The interviewers contacted 1495 persons and 306 of them refused to participate in the survey. The refusal rate was 20.4%, which is an approximately usual rate in such kind of survey in Croatia.

Sampling error estimates

+/- 2,9%