About this dataset

Context

The dataset tabulates the German town population distribution across 18 age groups. It lists the population in each age group along with the percentage population relative of the total population for German town. The dataset can be utilized to understand the population distribution of German town by age. For example, using this dataset, we can identify the largest age group in German town.

Key observations

The largest age group in German, New York was for the group of age 50 to 54 years years with a population of 32 (13.17%), according to the ACS 2019-2023 5-Year Estimates. At the same time, the smallest age group in German, New York was the 85 years and over years with a population of 1 (0.41%). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates

Content

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

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group in consideration
• Population: The population for the specific age group in the German town is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of German town 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 German town Population by Age. You can refer the same here

In 1800, the region of Germany was not a single, unified nation, but a collection of decentralized, independent states, bound together as part of the Holy Roman Empire. This empire was dissolved, however, in 1806, during the Revolutionary and Napoleonic eras in Europe, and the German Confederation was established in 1815. Napoleonic reforms led to the abolition of serfdom, extension of voting rights to property-owners, and an overall increase in living standards. The population grew throughout the remainder of the century, as improvements in sanitation and medicine (namely, mandatory vaccination policies) saw child mortality rates fall in later decades. As Germany industrialized and the economy grew, so too did the argument for nationhood; calls for pan-Germanism (the unification of all German-speaking lands) grew more popular among the lower classes in the mid-1800s, especially following the revolutions of 1948-49. In contrast, industrialization and poor harvests also saw high unemployment in rural regions, which led to waves of mass migration, particularly to the U.S.. In 1886, the Austro-Prussian War united northern Germany under a new Confederation, while the remaining German states (excluding Austria and Switzerland) joined following the Franco-Prussian War in 1871; this established the German Empire, under the Prussian leadership of Emperor Wilhelm I and Chancellor Otto von Bismarck. 1871 to 1945 - Unification to the Second World War The first decades of unification saw Germany rise to become one of Europe's strongest and most advanced nations, and challenge other world powers on an international scale, establishing colonies in Africa and the Pacific. These endeavors were cut short, however, when the Austro-Hungarian heir apparent was assassinated in Sarajevo; Germany promised a "blank check" of support for Austria's retaliation, who subsequently declared war on Serbia and set the First World War in motion. Viewed as the strongest of the Central Powers, Germany mobilized over 11 million men throughout the war, and its army fought in all theaters. As the war progressed, both the military and civilian populations grew increasingly weakened due to malnutrition, as Germany's resources became stretched. By the war's end in 1918, Germany suffered over 2 million civilian and military deaths due to conflict, and several hundred thousand more during the accompanying influenza pandemic. Mass displacement and the restructuring of Europe's borders through the Treaty of Versailles saw the population drop by several million more.

Reparations and economic mismanagement also financially crippled Germany and led to bitter indignation among many Germans in the interwar period; something that was exploited by Adolf Hitler on his rise to power. Reckless printing of money caused hyperinflation in 1923, when the currency became so worthless that basic items were priced at trillions of Marks; the introduction of the Rentenmark then stabilized the economy before the Great Depression of 1929 sent it back into dramatic decline. When Hitler became Chancellor of Germany in 1933, the Nazi government disregarded the Treaty of Versailles' restrictions and Germany rose once more to become an emerging superpower. Hitler's desire for territorial expansion into eastern Europe and the creation of an ethnically-homogenous German empire then led to the invasion of Poland in 1939, which is considered the beginning of the Second World War in Europe. Again, almost every aspect of German life contributed to the war effort, and more than 13 million men were mobilized. After six years of war, and over seven million German deaths, the Axis powers were defeated and Germany was divided into four zones administered by France, the Soviet Union, the UK, and the U.S.. Mass displacement, shifting borders, and the relocation of peoples based on ethnicity also greatly affected the population during this time. 1945 to 2020 - Partition and Reunification In the late 1940s, cold war tensions led to two distinct states emerging in Germany; the Soviet-controlled east became the communist German Democratic Republic (DDR), and the three western zones merged to form the democratic Federal Republic of Germany. Additionally, Berlin was split in a similar fashion, although its location deep inside DDR territory created series of problems and opportunities for the those on either side. Life quickly changed depending on which side of the border one lived. Within a decade, rapid economic recovery saw West Germany become western Europe's strongest economy and a key international player. In the east, living standards were much lower, although unemployment was almost non-existent; internationally, East Germany was the strongest economy in the Eastern Bloc (after the USSR), though it eventually fell behind the West by the 1970s. The restriction of movement between the two states also led to labor shortages in t...

Extent to which informed and ideas about the USA. Contacts with Americans and trips to the United States.

Topics: Knowledge of English; knowledge and reading American newspapers, books and films; concepts of respondent about the American school system, family life, way of life, press, radio and television, agriculture, the political, cultural, religious life, the social problems, social services, the relationship employer-employee, the economy, industry and technology; judgement on Americans and reasons for a possible change in attitude to Americans; position on the international policy of the USA; trips of respondent to the USA; evaluation of the influence of a trip to the USA on one´s own attitude to the USA; personal contacts with travelers to America; contacts with Americans since the end of the war; knowledge of experiences with the German-American exchange program; adjustment of prejudices through contact with an ´Exchangee´; evaluation of employment with American employers; personal difficulties of respondent; listening to the broadcast ´Voice of America´; trips to the America House.

Demography: age (classified); sex; marital status; religious denomination; school education; occupation; employment; household income; party preference; party membership; state; refugee status; present and past offices held.

Interviewer rating: social class and willingness of respondent to cooperate; number of contact attempts; city size.

About this dataset

Context

The dataset tabulates the German township population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of German township across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2023, the population of German township was 4,485, a 1.23% decrease year-by-year from 2022. Previously, in 2022, German township population was 4,541, a decline of 1.43% compared to a population of 4,607 in 2021. Over the last 20 plus years, between 2000 and 2023, population of German township decreased by 1,149. In this period, the peak population was 5,634 in the year 2000. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2023

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2023)
• Population: The population for the specific year for the German township is shown in this column.
• Year on Year Change: This column displays the change in German township population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. 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 German township Population by Year. You can refer the same here

Between 1820 and 1957, more than six million people emigrated from Germany to the United States. The period with the highest levels of migration came during the 1850s and the 1880s, and over 250 thousand documented migrants came to the US from Germany in 1882 alone. The reasons for these mass migrations were not linked to individual events, but were because of the improved access to trans-Atlantic travel, poor economic opportunities at home (particularly for farmers, who struggled with the rapid industrialization of Germany), and to escape religious persecution in Europe. The periods with the lowest levels of migration from Germany were between 1915 and 1945, and were likely caused by the First and Second World Wars, and also the Great Depression.

About this dataset

Context

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

Key observations

The percent distribution of German Valley population by race (across all racial categories recognized by the U.S. Census Bureau): 97.80% are white, 0.66% are Asian, 0.88% are some other race and 0.66% 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 German Valley
• Population: The population of the racial category (excluding ethnicity) in the German Valley is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of German Valley 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 German Valley Population by Race & Ethnicity. You can refer the same here

About this dataset

Context

The dataset tabulates the data for the German, New York population pyramid, which represents the German town population distribution across age and gender, using estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. It lists the male and female population for each age group, along with the total population for those age groups. Higher numbers at the bottom of the table suggest population growth, whereas higher numbers at the top indicate declining birth rates. Furthermore, the dataset can be utilized to understand the youth dependency ratio, old-age dependency ratio, total dependency ratio, and potential support ratio.

Key observations

• Youth dependency ratio, which is the number of children aged 0-14 per 100 persons aged 15-64, for German, New York, is 11.9.
• Old-age dependency ratio, which is the number of persons aged 65 or over per 100 persons aged 15-64, for German, New York, is 40.0.
• Total dependency ratio for German, New York is 51.9.
• Potential support ratio, which is the number of youth (working age population) per elderly, for German, New York is 2.5.

Content

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

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group for the German town population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the German town for the selected age group is shown in the following column.
• Population (Female): The female population in the German town for the selected age group is shown in the following column.
• Total Population: The total population of the German town for the selected age group is shown in the following column.

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 German town Population by Age. You can refer the same here

There are more women than men in Germany, although the number of men has been slowly increasing in recent years, especially since 2015. In 2023, there were around 41.8 million males and 42.9 million females in Germany. Births and deaths Globally, the death rate had been slowly decreasing until 2019 but there was a sharp spike in 2020 and 2021, which can be attributed to the COVID-19 pandemic. The general decline, however, is probably due to medical advancements which mean that many diseases are now treatable or curable, that were not 50 years ago. The birth rate has also been decreasing across the world, but it is lowest in Europe and North America. Future challenges There are a number of challenges facing the German population in the future. Some of the most pressing ones are the growing urban population and especially its ageing structure in combination with slow birth rates, which will put increased pressure on the pension system. Because of this trend, old age security and pensions are already today in the top ten most pressing political issues in Germany.

In the past four centuries, the population of the United States has grown from a recorded 350 people around the Jamestown colony of Virginia in 1610, to an estimated 331 million people in 2020. The pre-colonization populations of the indigenous peoples of the Americas have proven difficult for historians to estimate, as their numbers decreased rapidly following the introduction of European diseases (namely smallpox, plague and influenza). Native Americans were also omitted from most censuses conducted before the twentieth century, therefore the actual population of what we now know as the United States would have been much higher than the official census data from before 1800, but it is unclear by how much. Population growth in the colonies throughout the eighteenth century has primarily been attributed to migration from the British Isles and the Transatlantic slave trade; however it is also difficult to assert the ethnic-makeup of the population in these years as accurate migration records were not kept until after the 1820s, at which point the importation of slaves had also been illegalized. Nineteenth century In the year 1800, it is estimated that the population across the present-day United States was around six million people, with the population in the 16 admitted states numbering at 5.3 million. Migration to the United States began to happen on a large scale in the mid-nineteenth century, with the first major waves coming from Ireland, Britain and Germany. In some aspects, this wave of mass migration balanced out the demographic impacts of the American Civil War, which was the deadliest war in U.S. history with approximately 620 thousand fatalities between 1861 and 1865. The civil war also resulted in the emancipation of around four million slaves across the south; many of whose ancestors would take part in the Great Northern Migration in the early 1900s, which saw around six million black Americans migrate away from the south in one of the largest demographic shifts in U.S. history. By the end of the nineteenth century, improvements in transport technology and increasing economic opportunities saw migration to the United States increase further, particularly from southern and Eastern Europe, and in the first decade of the 1900s the number of migrants to the U.S. exceeded one million people in some years. Twentieth and twenty-first century The U.S. population has grown steadily throughout the past 120 years, reaching one hundred million in the 1910s, two hundred million in the 1960s, and three hundred million in 2007. In the past century, the U.S. established itself as a global superpower, with the world's largest economy (by nominal GDP) and most powerful military. Involvement in foreign wars has resulted in over 620,000 further U.S. fatalities since the Civil War, and migration fell drastically during the World Wars and Great Depression; however the population continuously grew in these years as the total fertility rate remained above two births per woman, and life expectancy increased (except during the Spanish Flu pandemic of 1918).

Since the Second World War, Latin America has replaced Europe as the most common point of origin for migrants, with Hispanic populations growing rapidly across the south and border states. Because of this, the proportion of non-Hispanic whites, which has been the most dominant ethnicity in the U.S. since records began, has dropped more rapidly in recent decades. Ethnic minorities also have a much higher birth rate than non-Hispanic whites, further contributing to this decline, and the share of non-Hispanic whites is expected to fall below fifty percent of the U.S. population by the mid-2000s. In 2020, the United States has the third-largest population in the world (after China and India), and the population is expected to reach four hundred million in the 2050s.

About this dataset

Context

The dataset tabulates the German Flatts town population distribution across 18 age groups. It lists the population in each age group along with the percentage population relative of the total population for German Flatts town. The dataset can be utilized to understand the population distribution of German Flatts town by age. For example, using this dataset, we can identify the largest age group in German Flatts town.

Key observations

The largest age group in German Flatts, New York was for the group of age 60 to 64 years years with a population of 1,003 (8.23%), according to the ACS 2019-2023 5-Year Estimates. At the same time, the smallest age group in German Flatts, New York was the 85 years and over years with a population of 273 (2.24%). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates

Content

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

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group in consideration
• Population: The population for the specific age group in the German Flatts town is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of German Flatts town 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 German Flatts town Population by Age. You can refer the same here

The largest number of immigrants in Germany were from Ukraine, as of 2023. The top three origin countries were rounded up by Romania and Turkey. Immigrants are defined as having left a country, which may be their home country, to permanently reside in another. Upon arriving, immigrants do not hold the citizenship of the country they move to. Immigration in the EU All three aforementioned countries are members of the European Union, which means their citizens have freedom of movement between EU member states. In practice, this means that citizens of any EU member country may relocate between them to live and work there. Unrestricted by visas or residence permits, the search for university courses, jobs, retirement options, and places to live seems to be defined by an enormous amount of choice. However, even in this freedom of movement scheme, immigration may be hampered by bureaucratic hurdles or financial challenges. Prosperity with a question mark While Germany continues to be an attractive destination for foreigners both in and outside the European Union, as well as asylum applicants, it remains to be seen how current events might influence these patterns, whether the number of immigrants arriving from certain countries will shift. Europe’s largest economy is suffering. Climbing inflation levels in the last few months, as well as remaining difficulties from the ongoing coronavirus (COVID-19) pandemic are affecting global economic development. Ultimately, future immigrants may face the fact of moving from one struggling economy to another.

About this dataset

Context

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

Key observations

Of the Non-Hispanic population in German Valley, the largest racial group is White alone with a population of 445 (98.23% 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 German Valley
• Population: The population of the racial category (for Non-Hispanic) in the German Valley is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of German Valley 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 German Valley Population by Race & Ethnicity. You can refer the same here

In 2023, around 1.93 million people immigrated to Germany. Numbers fluctuated during the time period covered in the graph at hand, peaking in 2015 during the high point of Europe’s refugee crisis. Significantly lower figures in 2020 may be attributed to the first year of the coronavirus (COVID-19) pandemic, and subsequent restrictions implemented by the German government on entering the country, in order to control the spread of the disease. Immigration to Germany “Immigrant” is a term used from the point of view of the receiving country, or the country being migrated to by a person. While reasons for and circumstances leading to an immigrant entering a foreign country may vary, they often include love, include seeking residence, employment, family reunions, or applying for asylum. Various countries are represented among foreigners living in Germany, though currently the leading three by numbers are Turkey, Ukraine, and Syria. Around 5.2 million immigrants living in Germany do not need a residence permit due to having EU citizenship, and therefore being allowed freedom of movement based on EU law. Another 2.64 million immigrants were granted an unlimited permit to stay in Germany. The near future Germany remains a popular choice for immigrants, even in currently challenging economic and political times. Welfare benefits, healthcare, and various support initiatives for those moving to or arriving in the country are on the list of selling points, though in practice, difficulties may be encountered depending on individual situations and laws in different German federal states. While the unemployment rate among foreigners living in Germany had gone up in 2020, it dropped again in the following years, but increased once more in 2023 and 2024 to over 16 percent. The country is Europe’s largest economy, housing many global players in various industries, which continues to attract jobseekers, despite these very industries facing struggles of their own brought on both by the ongoing coronavirus pandemic and geopolitical events in Europe.

At the end of the Revolutionary Period in United States history, the majority of white settlers in the United States of America had English heritage. The Thirteen Colonies, which claimed independence in 1776, was part of the British Empire until this point - English settlers and their descendants made up over 60 percent of the population by 1790. The English were the ethnic majority (among whites) in all states except Pennsylvania, which had a similarly-sized German population, while New York had a sizeable Dutch population as it was a former Dutch colony. The second-largest group was the Irish, where those from both the island's north and south made up a combined 10 percent of the population, followed by the Scottish and Germans at over eight percent each. Outside of the United States, the French and Spanish territories that would later be incorporated into the Union were majority French and Spanish - despite their large size they were relatively sparsely populated. The composition of the U.S. population would change drastically throughout the 19th century due largely to waves of migration from Europe.

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, the decennial census is the official source of population totals for April 1st of each decennial year. In between censuses, the Census Bureau's Population Estimates Program produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units and the group quarters population for states and counties..Since the 5-year data do not benefit from data quality filtering, comparisons are only made for populations of 5,000 or more..Information about the American Community Survey (ACS) can be found on the ACS website. Supporting documentation including code lists, subject definitions, data accuracy, and statistical testing, and a full list of ACS tables and table shells (without estimates) can be found on the Technical Documentation section of the ACS website.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2019-2023 American Community Survey 5-Year Estimates.ACS data generally reflect the geographic boundaries of legal and statistical areas as of January 1 of the estimate year. For more information, see Geography Boundaries by Year..Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..Users must consider potential differences in geographic boundaries, questionnaire content or coding, or other methodological issues when comparing ACS data from different years. Statistically significant differences shown in ACS Comparison Profiles, or in data users' own analysis, may be the result of these differences and thus might not necessarily reflect changes to the social, economic, housing, or demographic characteristics being compared. For more information, see Comparing ACS Data..Ancestry listed in this table refers to the total number of people who responded with a particular ancestry; for example, the estimate given for German represents the number of people who listed German as either their first or second ancestry. This table lists only the largest ancestry groups; see the Detailed Tables for more categories. Race and Hispanic origin groups are not included in this table because data for those groups come from the Race and Hispanic origin questions rather than the ancestry question (see Demographic Table)..Data for year of entry of the native population reflect the year of entry into the U.S. by people who were born in Puerto Rico or U.S. Island Areas or born outside the U.S. to a U.S. citizen parent and who subsequently moved to the U.S..Methodological changes to citizenship edits may have affected citizenship data for those born in American Samoa. Users should be aware of these changes when using 2018 data or multi-year data containing data from 2018. For more information, see: American Samoa Citizenship User Note..The category "with a broadband Internet subscription" refers to those who said "Yes" to at least one of the following types of Internet subscriptions: Broadband such as cable, fiber optic, or DSL; a cellular data plan; satellite; a fixed wireless subscription; or other non-dial up subscription types..An Internet "subscription" refers to a type of service that someone pays for to access the Internet such as a cellular data plan, broadband such as cable, fiber optic or DSL, or other type of service. This will normally refer to a service that someone is billed for directly for Internet alone or sometimes as part of a bundle.."With a computer" includes those who said "Yes" to at least one of the following types of computers: Desktop or laptop; smartphone; tablet or other portable wireless computer; or some other type of computer..Caution should be used when comparing data for computer and Internet use before and after 2016. Changes in 2016 to the questions involving the wording as well as the response options resulted in changed response patterns in the data. Most noticeable are increases in overall computer ownership or use, the total of Internet subscriptions, satellite subscriptions, and cellular data plans for a smartphone or other mobile device. For more detailed information a...

This statistic shows the number of people in Germany who travelled to Central or South America on vacation in the last 12 months from 2019 to 2023. In 2023, around 450,000 Germans travelled to these destinations. Numbers had decreased in recent years.The Allensbach Market and Advertising Media Analysis (Allensbacher Markt- und Werbeträgeranalyse or AWA in German) determines attitudes, consumer habits and media usage of the population in Germany on a broad statistical basis.

In 1938, the year before the outbreak of the Second world War, the countries with the largest populations were China, the Soviet Union, and the United States, although the United Kingdom had the largest overall population when it's colonies, dominions, and metropole are combined. Alongside France, these were the five Allied "Great Powers" that emerged victorious from the Second World War. The Axis Powers in the war were led by Germany and Japan in their respective theaters, and their smaller populations were decisive factors in their defeat. Manpower as a resource In the context of the Second World War, a country or territory's population played a vital role in its ability to wage war on such a large scale. Not only were armies able to call upon their people to fight in the war and replenish their forces, but war economies were also dependent on their workforce being able to meet the agricultural, manufacturing, and logistical demands of the war. For the Axis powers, invasions and the annexation of territories were often motivated by the fact that it granted access to valuable resources that would further their own war effort - millions of people living in occupied territories were then forced to gather these resources, or forcibly transported to work in manufacturing in other Axis territories. Similarly, colonial powers were able to use resources taken from their territories to supply their armies, however this often had devastating consequences for the regions from which food was redirected, contributing to numerous food shortages and famines across Africa, Asia, and Europe. Men from annexed or colonized territories were also used in the armies of the war's Great Powers, and in the Axis armies especially. This meant that soldiers often fought alongside their former-enemies. Aftermath The Second World War was the costliest in human history, resulting in the deaths of between 70 and 85 million people. Due to the turmoil and destruction of the war, accurate records for death tolls generally do not exist, therefore pre-war populations (in combination with other statistics), are used to estimate death tolls. The Soviet Union is believed to have lost the largest amount of people during the war, suffering approximately 24 million fatalities by 1945, followed by China at around 20 million people. The Soviet death toll is equal to approximately 14 percent of its pre-war population - the countries with the highest relative death tolls in the war are found in Eastern Europe, due to the intensity of the conflict and the systematic genocide committed in the region during the war.

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, the decennial census is the official source of population totals for April 1st of each decennial year. In between censuses, the Census Bureau's Population Estimates Program produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units for states and counties..Information about the American Community Survey (ACS) can be found on the ACS website. Supporting documentation including code lists, subject definitions, data accuracy, and statistical testing, and a full list of ACS tables and table shells (without estimates) can be found on the Technical Documentation section of the ACS website.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2018-2022 American Community Survey 5-Year Estimates.Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..Ancestry listed in this table refers to the total number of people who responded with a particular ancestry; for example, the estimate given for German represents the number of people who listed German as either their first or second ancestry. This table lists only the largest ancestry groups; see the Detailed Tables for more categories. Race and Hispanic origin groups are not included in this table because data for those groups come from the Race and Hispanic origin questions rather than the ancestry question (see Demographic Table)..Methodological changes to citizenship edits may have affected citizenship data for those born in American Samoa. Users should be aware of these changes when using 2018 data or multi-year data containing data from 2018. For more information, see: American Samoa Citizenship User Note..The Census Bureau introduced a new set of disability questions in the 2008 ACS questionnaire. Accordingly, comparisons of disability data from 2008 or later with data from prior years are not recommended. For more information on these questions and their evaluation in the 2006 ACS Content Test, see the Evaluation Report Covering Disability..The category "with a broadband Internet subscription" refers to those who said "Yes" to at least one of the following types of Internet subscriptions: Broadband such as cable, fiber optic, or DSL; a cellular data plan; satellite; a fixed wireless subscription; or other non-dial up subscription types..An Internet "subscription" refers to a type of service that someone pays for to access the Internet such as a cellular data plan, broadband such as cable, fiber optic or DSL, or other type of service. This will normally refer to a service that someone is billed for directly for Internet alone or sometimes as part of a bundle..With a computer includes those who said "Yes" to at least one of the following types of computers: Desktop or laptop; smartphone; tablet or other portable wireless computer; or some other type of computer..The "children of the householder" and "own children of the householder" concepts are combined in these estimates. For more information, please see the following User Note..The 2018-2022 American Community Survey (ACS) data generally reflect the March 2020 Office of Management and Budget (OMB) delineations of metropolitan and micropolitan statistical areas. In certain instances, the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB delineation lists due to differences in the effective dates of the geographic entities..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on 2020 Census data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution. For a 5-year median estimate, the margin of error associated with a median was...

About this dataset

Context

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

Key observations

The percent distribution of German township population by race (across all racial categories recognized by the U.S. Census Bureau): 85.47% are white, 8.17% are Black or African American, 0.48% are Asian, 0.22% are some other race and 5.67% 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 German township
• Population: The population of the racial category (excluding ethnicity) in the German township is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of German township 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 German township Population by Race & Ethnicity. You can refer the same here

It is estimated that the Second World War was responsible for the deaths of approximately 3.76 percent of the world's population between 1939 and 1945. In 2022, where the world's population reached eight billion, this would be equal to the death of around 300 million people.

The region that experienced the largest loss of life relative to its population was the South Seas Mandate - these were former-German territories given to the Empire of Japan through the Treaty of Versailles following WWI, and they make up much of the present-day countries of the Marshall Islands, Micronesia, the Northern Mariana Islands (U.S. territory), and Palau. Due to the location and strategic importance of these islands, they were used by the Japanese as launching pads for their attacks on Pearl Harbor and in the South Pacific, while they were also taken as part of the Allies' island-hopping strategy in their counteroffensive against Japan. This came at a heavy cost for the local populations, a large share of whom were Japanese settlers who had moved there in the 1920s and 1930s. Exact figures for both pre-war populations and wartime losses fluctuate by source, however civilian losses in these islands were extremely high as the Japanese defenses resorted to more extreme measures in the war's final phase.