Abstract copyright UK Data Service and data collection copyright owner.

The Great Britain Historical Database has been assembled as part of the ongoing Great Britain Historical GIS Project. The project aims to trace the emergence of the north-south divide in Britain and to provide a synoptic view of the human geography of Britain at sub-county scales. Further information about the project is available on A Vision of Britain webpages, where users can browse the database's documentation system online.

Main Topics:

Parish level statistics for England, Wales and Scotland taken from the 1801, 1811, 1851, 1891, 1911, 1931 and 1951 censuses.

Parish level statistics for England and Wales taken from the 1831 and 1871 censuses.

Parish level statistics for England taken from the 1821 and 1841 censuses.

Parish level statistics for Scotland taken from the 1881 census.

Please note: this study does not include information on named individuals and would therefore not be useful for personal family history research.

Estimates of London's population between 1801 and 2001 (persons present 1801 to 1991 and residents for 2001 onwards) derived from historic Census data.

Sources: years to 1971 - Greater London Council Research Memorandum 413, The Changing Population of the London Boroughs; 1981 Census Small Area Statistics, Table 1; 1991 Census Small Area Statistics, Table 1. Figure for Year-1939 is a mid-year estimate for the year 1939. Figure for Year-2001 onwards is the number of residents because the number of persons present is not available from 2001. Note that totals for Greater London may not match due to rounding errors. Figures are estimates to the nearest thousand.

Abstract copyright UK Data Service and data collection copyright owner. The aim of this study was to analyse the data collected from the statistics of the 1801-1841 Censuses for a group of parishes in the area of Harwich, Tendring Hundred, Essex. Main Topics: The file consists of a dictionary and a set of data collected from the statistics of the 1801-1841 Censuses. The statistics are held in the Census Room of the Public Records Office. Excluded from the data are the returns for merchant seamen in British-registered ships who were separately enumerated. Please note: this study does not include information on named individuals and would therefore not be useful for personal family history research. No sampling (total universe) Compilation or synthesis of existing material

An appreciation of historical landuse and its effects is crucial when interpreting the structure, composition, and spatial characteristics of modern forests. The Harvard Forest has compiled many different historical data sources in an ongoing effort to understand how anthropogenic disturbances have shaped our modern landscapes. Estimates of town land use and land cover were gathered from a variety of sources, including tax valuations (1801-1860) and state agricultural census records (1865-1905). Data prior to 1801 rarely cover the entire state and are excluded from these datasets. Data on forest structure are available for several time periods, including 1885 and 1895 (Agricultural Censuses) and 1916-1920s (State Forester’s reports).

The Census in the UK has been conducted every 10 years since 1801. Over this time there have been numerous changes to the administrative boundaries, such as the amalgamation and deletion of wards and parishes, or the creation of new ones. These occur for a range of reasons, but usually to better distribute the population for administrative purposes. Without knowledge about boundary changes it can be difficult to understand changes observed in populations, or make comparisons of areas over time. For example, moving a parish boundary may cause a population to increase on paper, within a given parish, but only because part of the population of a neighbouring parish has been incorporated, and not because a sudden influx of new residents. The Research and Performance team have tried to keep a record of the changes to parishes over time, and the estimated populations as published by each Census, since 1801. This way we are better able to explain apparent changes to the populations estimated by each Census. You will find the most up to date versions of these records on our Open Data portal.

Every ten years since 1801 the nation has set aside one day for the census - a count of all people and households. It is the most complete source of information about the population that we have. The latest census was held on Sunday 27 March 2011.

Every effort is made to include everyone, and that is why the census is so important. It is the only survey which provides a detailed picture of the entire population, and is unique because it covers everyone at the same time and asks the same core questions everywhere. This makes it easy to compare different parts of the country.

The information the census provides allows central and local government, health authorities and many other organisations to target their resources more effectively and to plan housing, education, health and transport services for years to come.

In England and Wales, the census is planned and carried out by the Office for National Statistics. Elsewhere in the UK, responsibility lies with the National Records of Scotland and the Northern Ireland Statistics and Research Agency.

All 2011 Census data for ‘Welsh’ records are defined as those: - Currently resident in Wales - With a second address in Wales - With a previous Years Address in Wales - With a term-time address in Wales - Who work in Wales (but live in England) - In Armed Forces Establishments in Wales - Who are visitors in Wales - Who are Welsh language speakers (including those who live and work outside of Wales).

The ONS have three processes for checking and resolving duplicate responses so that the main census data should simply be one record for each person:

1. The ONS resolve duplicates coming in for the same postcode using a process called Resolve Multiple Responses (RMR). For instance, if two people both fill in a form for their whole household, or someone from a household also submits an individual response unknown to the main submission. They have rules for checking they are duplicates, and rules for which to keep.

2. The ONS also do an over coverage check on a sample basis for duplicates across the rest of the country, and then factor the findings into their coverage estimation calculations. This sampling focuses on the types of population which are more likely to be duplicated (people who have indicated they have a second residence on the census, students aged 18-25, armed forces personnel, children, adults enumerated at a communal establishment, etc.) but also samples from the remaining population.

3. The ONS ask parents to fill in basic demographic information for any children who are away studying, and when they get to the question on their term-time address, if they answer that the term-time address is elsewhere, we then use that to filter those out-of-term students out of the main database. Then when that student does respond actually at their term-time address, they only include them there.

Variables RELAT06, RELAT11, RELAT16, RELAT21, RELAT26 are not available in the data

Abstract copyright UK Data Service and data collection copyright owner. This data collection uses Census returns to construct a consistent time series of population for urban centres in England and Wales 1801-1911. This allows the urban development and structure of England and Wales to be analysed, and provides a resource to other researchers seeking to make ready comparisons of other information with urban development across the nineteenth century. It has been derived from the work of three previous researchers: (1) Chris Law (1967) originally prepared it; (2) Brian Robson (1973) developed the data further and transcribed Law’s data and preserved it, and also added information on some smaller settlements for years before they became ‘urban’ under Law’s criteria; (3) Jack Langton (2000) undertook a different study for the 17th century to 1841 using the same basic methods and definitions as Law-Robson for 1801 and 1841 and corrected various errors and omissions in the Law-Robson material; he also disaggregated the Law-Robson data for the period to 1841 to reflect the fact that many places had not coalesced into large towns by this date. The database here combines these three sources. It was prepared by Bob Bennett (2011) for a study of local economies and chamber of commerce business representation.

About this dataset

Context

The dataset tabulates the Montgomery County 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 Montgomery County. The dataset can be utilized to understand the population distribution of Montgomery County by age. For example, using this dataset, we can identify the largest age group in Montgomery County.

Key observations

The largest age group in Montgomery County, TN was for the group of age 25-29 years with a population of 21,275 (9.84%), according to the 2021 American Community Survey. At the same time, the smallest age group in Montgomery County, TN was the 85+ years with a population of 1,801 (0.83%). Source: U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 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 Montgomery County is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of Montgomery County total population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Montgomery County Population by Age. You can refer the same here

[ARCHIVED] Community Counts data is retained for archival purposes only, such as research, reference and record-keeping. This data has not been maintained or updated. Users looking for the latest information should refer to Statistics Canada’s Census Program (https://www12.statcan.gc.ca/census-recensement/index-eng.cfm?MM=1) for the latest data, including detailed results about Nova Scotia. This table reports household living arrangements. This data is sourced from the Census of Population. Geographies available: provinces, counties, communities, municipalities, district health authorities, community health boards, economic regions, police districts, school boards, municipal electoral districts, provincial electoral districts, federal electoral districts, regional development authorities, watersheds

In 1801 the population of France was estimated to be just under 20 million people, the number of women was 14 million, whereas the number of men was 13.3 million. The gap then widens in 1821 to 0.9 million, which is most likely a result of the Napoleonic Wars, and it then narrows during the rest of the century, shrinking to just 0.04 million in 1866.

Throughout the time shown in the graph the numbers of men and women seem to follow similar trends, however the period between 1911 and 1946 shows how drastically the numbers of men were affected by both World Wars. Between 1911 and 1921 the number of men dropped by 0.8 million, whereas the number of women grew by 0.4 million. The male population does grow again during the interwar years, however both populations drop between 1931 and 1946 due to the Second World War, with the number of males decreasing by just under one million and the number of females by 0.4 million. This graph does not show how many died in France during the wars, as the numbers would also be influenced by the birth and natural death rate, but it does give an insight into the long term affects it had on the population.

From 1946 onwards the population of France does grow steadily, and at a much faster rate than it did in the 19th century. The population grows from just under 40 million in 1946, to 65.7 million in 2020, with 31.2 and 33.2 million men and women respectively. This increase in growth comes as a result of an increased fertility rate as well as an increased rate of migration into the country. While the difference in the number of men and women did decrease after the war, reaching its lowest point of 1.1 million in 1975, the gap has widened again to over two million in 2020.

About this dataset

Context

The dataset tabulates the Cumberland County 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 Cumberland County. The dataset can be utilized to understand the population distribution of Cumberland County by age. For example, using this dataset, we can identify the largest age group in Cumberland County.

Key observations

The largest age group in Cumberland County, TN was for the group of age 65 to 69 years years with a population of 6,016 (9.62%), according to the ACS 2019-2023 5-Year Estimates. At the same time, the smallest age group in Cumberland County, TN was the 85 years and over years with a population of 1,801 (2.88%). 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 Cumberland County is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of Cumberland County total population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Cumberland County Population by Age. You can refer the same here

About this dataset

Context

The dataset presents the the household distribution across 16 income brackets among four distinct age groups in Easton: Under 25 years, 25-44 years, 45-64 years, and over 65 years. The dataset highlights the variation in household income, offering valuable insights into economic trends and disparities within different age categories, aiding in data analysis and decision-making..

Key observations

• Upon closer examination of the distribution of households among age brackets, it reveals that there are 124(1.77%) households where the householder is under 25 years old, 1,801(25.68%) households with a householder aged between 25 and 44 years, 2,502(35.67%) households with a householder aged between 45 and 64 years, and 2,587(36.88%) households where the householder is over 65 years old.
• The age group of 25 to 44 years exhibits the highest median household income, while the largest number of households falls within the 65 years and over bracket. This distribution hints at economic disparities within the town of Easton, showcasing varying income levels among different age demographics.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Income brackets:

• Less than $10,000
• $10,000 to $14,999
• $15,000 to $19,999
• $20,000 to $24,999
• $25,000 to $29,999
• $30,000 to $34,999
• $35,000 to $39,999
• $40,000 to $44,999
• $45,000 to $49,999
• $50,000 to $59,999
• $60,000 to $74,999
• $75,000 to $99,999
• $100,000 to $124,999
• $125,000 to $149,999
• $150,000 to $199,999
• $200,000 or more

Variables / Data Columns

• Household Income: This column showcases 16 income brackets ranging from Under $10,000 to $200,000+ ( As mentioned above).
• Under 25 years: The count of households led by a head of household under 25 years old with income within a specified income bracket.
• 25 to 44 years: The count of households led by a head of household 25 to 44 years old with income within a specified income bracket.
• 45 to 64 years: The count of households led by a head of household 45 to 64 years old with income within a specified income bracket.
• 65 years and over: The count of households led by a head of household 65 years and over old with income within a specified income bracket.

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 Easton median household income by age. You can refer the same here

About this dataset

Context

The dataset presents the the household distribution across 16 income brackets among four distinct age groups in Kingsville: Under 25 years, 25-44 years, 45-64 years, and over 65 years. The dataset highlights the variation in household income, offering valuable insights into economic trends and disparities within different age categories, aiding in data analysis and decision-making..

Key observations

• Upon closer examination of the distribution of households among age brackets, it reveals that there are 1,551(16.02%) households where the householder is under 25 years old, 3,865(39.91%) households with a householder aged between 25 and 44 years, 2,467(25.48%) households with a householder aged between 45 and 64 years, and 1,801(18.60%) households where the householder is over 65 years old.
• The age group of 45 to 64 years exhibits the highest median household income, while the largest number of households falls within the 25 to 44 years bracket. This distribution hints at economic disparities within the city of Kingsville, showcasing varying income levels among different age demographics.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Income brackets:

• Less than $10,000
• $10,000 to $14,999
• $15,000 to $19,999
• $20,000 to $24,999
• $25,000 to $29,999
• $30,000 to $34,999
• $35,000 to $39,999
• $40,000 to $44,999
• $45,000 to $49,999
• $50,000 to $59,999
• $60,000 to $74,999
• $75,000 to $99,999
• $100,000 to $124,999
• $125,000 to $149,999
• $150,000 to $199,999
• $200,000 or more

Variables / Data Columns

• Household Income: This column showcases 16 income brackets ranging from Under $10,000 to $200,000+ ( As mentioned above).
• Under 25 years: The count of households led by a head of household under 25 years old with income within a specified income bracket.
• 25 to 44 years: The count of households led by a head of household 25 to 44 years old with income within a specified income bracket.
• 45 to 64 years: The count of households led by a head of household 45 to 64 years old with income within a specified income bracket.
• 65 years and over: The count of households led by a head of household 65 years and over old with income within a specified income bracket.

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 Kingsville median household income by age. You can refer the same here

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.

Abstract copyright UK Data Service and data collection copyright owner.

This machine-readable version of John Williams' Digest of Welsh Historical Statistics is the result of a collaboration between the Statistical Directorate of the National Assembly for Wales, the History Data Service and the Centre for Data Digitisation and Analysis at Queen's University Belfast.
John Williams' Digest of Welsh Historical Statistics is intended to provide a service for those working on the history of modern Wales. It arises from a belief that the quantitative element is a necessary and important part of the historical record; from an awareness that it was an aspect that was particularly inaccessible for scholars of Welsh history; and from a conviction that some encouragement in the use of quantitative material was necessary. It is modelled on the two volumes dedicated to British historical statistics: Mitchell, B.R. and Deane, P. (1962) Abstract of British historical statistics and Mitchell, B.R. and Jones, H.G. (1971) Second abstract of British historical statistics.
Main Topics:
The main tables are:


Total population and intercensal change by sex by county, 1801-1971
Number of females per 1000 males by county, 1801-1971
Age and marital condition by sex, 1841-1971
Area/acreage by county, 1841-1971
Population of Registration Counties as constituted at the time of each Census, 1841-1911
Comparative area and population of Registration, Ancient and Administrative Counties, 1891
Parish Register returns of baptisms, burials and marriages, 1700-1840
Estimated mid-year population by sex, 1841-1974
Estimated mid-year population totals by county, 1903-1974
Number of deaths by sex, crude death-rates and infant mortality, 1838-1974
Number of births and birth-rates, 1839-1974
Number of marriages and rate per 1000 population, 1839-1974
Population of towns, 1801-1971
Net migration and natural increase, number and per cent for each, inter-censal period, by county, 1841-1971
Number born in Wales and living in United States, 1850-1970
Number of Welsh speakers by sex, by county and county borough, 1891-1971
Welsh speakers as a percentage of total population over three years of age, by county and county borough, 1891-1971
Welsh-speaking population by age, 1901-1971

Please note: this study does not include information on named individuals and would therefore not be useful for personal family history research.

About this dataset

Context

The dataset tabulates the Battle Ground 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 Battle Ground. The dataset can be utilized to understand the population distribution of Battle Ground by age. For example, using this dataset, we can identify the largest age group in Battle Ground.

Key observations

The largest age group in Battle Ground, WA was for the group of age 15-19 years with a population of 1,801 (8.77%), according to the 2021 American Community Survey. At the same time, the smallest age group in Battle Ground, WA was the 85+ years with a population of 138 (0.67%). Source: U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 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 Battle Ground is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of Battle Ground 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 Battle Ground Population by Age. You can refer the same here

About this dataset

Context

The dataset presents the the household distribution across 16 income brackets among four distinct age groups in Hutchinson County: Under 25 years, 25-44 years, 45-64 years, and over 65 years. The dataset highlights the variation in household income, offering valuable insights into economic trends and disparities within different age categories, aiding in data analysis and decision-making..

Key observations

• Upon closer examination of the distribution of households among age brackets, it reveals that there are 176(2.62%) households where the householder is under 25 years old, 1,801(26.84%) households with a householder aged between 25 and 44 years, 2,498(37.22%) households with a householder aged between 45 and 64 years, and 2,236(33.32%) households where the householder is over 65 years old.
• The age group of 25 to 44 years exhibits the highest median household income, while the largest number of households falls within the 45 to 64 years bracket. This distribution hints at economic disparities within the county of Hutchinson County, showcasing varying income levels among different age demographics.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.

Income brackets:

• Less than $10,000
• $10,000 to $14,999
• $15,000 to $19,999
• $20,000 to $24,999
• $25,000 to $29,999
• $30,000 to $34,999
• $35,000 to $39,999
• $40,000 to $44,999
• $45,000 to $49,999
• $50,000 to $59,999
• $60,000 to $74,999
• $75,000 to $99,999
• $100,000 to $124,999
• $125,000 to $149,999
• $150,000 to $199,999
• $200,000 or more

Variables / Data Columns

• Household Income: This column showcases 16 income brackets ranging from Under $10,000 to $200,000+ ( As mentioned above).
• Under 25 years: The count of households led by a head of household under 25 years old with income within a specified income bracket.
• 25 to 44 years: The count of households led by a head of household 25 to 44 years old with income within a specified income bracket.
• 45 to 64 years: The count of households led by a head of household 45 to 64 years old with income within a specified income bracket.
• 65 years and over: The count of households led by a head of household 65 years and over old with income within a specified income bracket.

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 Hutchinson County median household income by age. You can refer the same here

In 1800, the population of the region of present-day India was approximately 169 million. The population would grow gradually throughout the 19th century, rising to over 240 million by 1900. Population growth would begin to increase in the 1920s, as a result of falling mortality rates, due to improvements in health, sanitation and infrastructure. However, the population of India would see it’s largest rate of growth in the years following the country’s independence from the British Empire in 1948, where the population would rise from 358 million to over one billion by the turn of the century, making India the second country to pass the billion person milestone. While the rate of growth has slowed somewhat as India begins a demographics shift, the country’s population has continued to grow dramatically throughout the 21st century, and in 2020, India is estimated to have a population of just under 1.4 billion, well over a billion more people than one century previously. Today, approximately 18% of the Earth’s population lives in India, and it is estimated that India will overtake China to become the most populous country in the world within the next five years.

About this dataset

Context

The dataset presents the the household distribution across 16 income brackets among four distinct age groups in North Reading town: Under 25 years, 25-44 years, 45-64 years, and over 65 years. The dataset highlights the variation in household income, offering valuable insights into economic trends and disparities within different age categories, aiding in data analysis and decision-making..

Key observations

• Upon closer examination of the distribution of households among age brackets, it reveals that there are 32(0.55%) households where the householder is under 25 years old, 1,801(30.80%) households with a householder aged between 25 and 44 years, 2,818(48.19%) households with a householder aged between 45 and 64 years, and 1,197(20.47%) households where the householder is over 65 years old.
• In North Reading town, the age group of 45 to 64 years stands out with both the highest median income and the maximum share of households. This alignment suggests a financially stable demographic, indicating an established community with stable careers and higher incomes.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Income brackets:

• Less than $10,000
• $10,000 to $14,999
• $15,000 to $19,999
• $20,000 to $24,999
• $25,000 to $29,999
• $30,000 to $34,999
• $35,000 to $39,999
• $40,000 to $44,999
• $45,000 to $49,999
• $50,000 to $59,999
• $60,000 to $74,999
• $75,000 to $99,999
• $100,000 to $124,999
• $125,000 to $149,999
• $150,000 to $199,999
• $200,000 or more

Variables / Data Columns

• Household Income: This column showcases 16 income brackets ranging from Under $10,000 to $200,000+ ( As mentioned above).
• Under 25 years: The count of households led by a head of household under 25 years old with income within a specified income bracket.
• 25 to 44 years: The count of households led by a head of household 25 to 44 years old with income within a specified income bracket.
• 45 to 64 years: The count of households led by a head of household 45 to 64 years old with income within a specified income bracket.
• 65 years and over: The count of households led by a head of household 65 years and over old with income within a specified income bracket.

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 North Reading town median household income by age. You can refer the same here