Canadian census data from 1891.

This dataset is about books. It has 1 row and is filtered where the book is 1891 census of Lincolnshire index of surnames. Vol.12, Caistor registration district part one RG12/2612-2619. It features 7 columns including author, publication date, language, and book publisher.

Abstract copyright UK Data Service and data collection copyright owner.

The paper Udny Yule read to the Royal Statistical Society at the end of the nineteenth century (Yule, 1899) was a landmark in social statistics. He applied multiple regression analysis to a question of social policy, namely reforms to the 19th century system of poverty alleviation in England. To do this, Yule created a dataset from administrative and Census data. Yule’s original dataset was not preserved, but because his data were drawn from public sources, it is possible to reconstruct it, albeit with some slight differences from the original. This report provides a description of how the dataset was reconstructed and how it varies from the one used in the 1899 paper.

Abstract copyright UK Data Service and data collection copyright owner.

The aim of this project was to investigate the working population of Downham, an agricultural fen parish in north Cambridgeshire, using information derived from the census enumerators' books for 1851 and 1891. This project originated as part of the course of study for Open University Course DA301 (Studying family and community history: nineteenth and twentieth centuries).
Main Topics:

The data consist of a partial transcription of the 1851 and 1891 census enumerators' books for Downham, Cambridgeshire.
The variables are: enumeration district; folio number; schedule number; address; surname; relationship to head of household; marital status; gender; age; occupation; employment status (1891 only); place of birth; birth county or country; disabilities (1891 only).

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

This dataset contains Adjustment Weights for the 1891-1911 England and Wales censuses and corresponds to Supplementary material for the paper "The Population of Non-corporate Business Proprietors in England and Wales 1891-1911", by Bennett, Robert J., Montebruno, Piero, Smith, Harry J. as an outcome of the ESRC project ES/M010953: Drivers of Entrepreneurship and Small Businesses PI Prof. Robert J. Bennett.

The material consists of three raw text files

1. 1891 Employment status & Weights
2. 1901 Employment status & Weights
3. 1911 Employment status & Weights

Each file has the three following variables:

1. newRecID: the ID for I-CEM2 as in Higgs, Edward and Schürer, Kevin (University of Essex) (2014) The Integrated Census Microdata (I-CeM) UKDA, SN-7481; K. Schürer, E. Higgs, A.M. Reid, E.M Garrett, Integrated Census Microdata, 1851-1911, version V. 2 (I-CeM.2), (2016) [data collection] UK Data Service SN: 7481

2. Employment status: 1 Worker 2 Employer 3 Own-account

3. Weights: the inverse of the probability of giving an answer to the Employment Status question of the censuses by Sex and Relationship to the head of the family.

A detailed explanation of how these weights were calculated and how to use them in the context of data analysis of this censuses can be found in the accompanying working paper, Montebruno, Piero (2018) ‘Adjustment Weights 1891-1911: Weights to adjust entrepreneurs taking account of non-response and misallocation bias in Censuses 1891-1911’, Working Paper 11: ESRC project ES/M010953: ‘Drivers of Entrepreneurship and Small Businesses’, University of Cambridge, Department of Geography and Cambridge Group for the History of Population and Social Structure.

The files can be opened by any text editor, database management system (Access) or statistical package (Stata, SPSS)

This dataset should be cited as Adjustment Weights 1891-1911, "The Population of Non-corporate Business Proprietors in England and Wales 1891-1911", by Bennett, Robert J., Montebruno, Piero, Smith, Harry J. Please cite using its DOI.

This data collection contains information about average population 1891-1900 and number of married couples, live births, illegitimate births, deaths, emigrants and immigrants during the period 1891 to 1900.

This data collection contains information about average population 1891-1900 and number of married couples, live births, illegitimate births, deaths, emigrants and immigrants during the period 1891 to 1900.

This dataset contains RecID from I-CeM Adjustment Weights for the 1891-1911 England and Wales censuses and corresponds to Supplementary material for the paper "The Population of Non-corporate Business Proprietors in England and Wales 1891-1911", by Bennett, Robert J., Montebruno, Piero, Smith, Harry J. as an outcome of the ESRC project ES/M010953: Drivers of Entrepreneurship and Small Businesses PI Prof. Robert J. Bennett. The material consists of three raw text files 1. 1891 Employment status & Weights 2. 1901 Employment status & Weights 3. 1911 Employment status & Weights Each file has the three following variables: 1. RecID: the ID for I-CEM2 as in Higgs, Edward and Schürer, Kevin (University of Essex) (2014) The Integrated Census Microdata (I-CeM) UKDA, SN-7481; K. Schürer, E. Higgs, A.M. Reid, E.M Garrett, Integrated Census Microdata, 1851-1911, version V. 2 (I-CeM.2), (2016) [data collection] UK Data Service SN: 7481 2. Employment status: 1 Worker 2 Employer 3 Own-account 3. Weights: the inverse of the probability of giving an answer to the Employment Status question of the censuses by Sex and Relationship to the head of the family. A detailed explanation of how these weights were calculated and how to use them in the context of data analysis of this censuses can be found in the accompanying working paper, Montebruno, Piero (2018) ‘Adjustment Weights 1891-1911: Weights to adjust entrepreneurs taking account of non-response and misallocation bias in Censuses 1891-1911’, Working Paper 11: ESRC project ES/M010953: ‘Drivers of Entrepreneurship and Small Businesses’, University of Cambridge, Department of Geography and Cambridge Group for the History of Population and Social Structure. The files can be opened by any text editor, database management system (Access) or statistical package (Stata, SPSS) This dataset should be cited as Adjustment Weights 1891-1911, "The Population of Non-corporate Business Proprietors in England and Wales 1891-1911", by Bennett, Robert J., Montebruno, Piero, Smith, Harry J. Please cite using its DOI.

This dataset contains the codes for the decisions in England and Wales made for each Sub-Occode to assign each individual identified by RecID to a status of employer or own account entrepreneur. (worker RecIDs are given in a separate download). This is method EMPSTATUS_IND as outlined in the BBCE User Guide. The method is given in full in WP 9.2. The codes are: SubOccode - SubOccode code Ent_rou_01 - Estimate of number of entrepreneurs based on the rounded 1891 data using a cut-off of 0.1 … Ent_rou_08 - Estimate of number of entrepreneurs based on the rounded 1891 data using a cut-off of 0.8 Ent_r01aE_Wo - Estimate of number of entrepreneurs based on the rounded 1891 data using a cut-off of 0.1, after the extracted entrepreneurs are imposed … Ent_r08aE_Wo - Estimate of number of entrepreneurs based on the rounded 1891 data using a cut-off of 0.8, after the extracted entrepreneurs are imposed Decision - Code indicating the option used. 12 codes exist: 1-0.1 cut-off; 15-0.15 cut-off; 2-0.2 cut-off; 25-0.25 cut-off; 3-0.3 cut-off; 35-0.35 cut-off; 4-0.4 cut-off; 45-0.45 cut-off; 5-0.5 cut-off; 6-0.6 cut-off; 7-0.7 cut-off; 8-0.8 cut-off

This dataset contains Adjustment Weights for the 1891-1901 Scottish censuses and corresponds to Supplementary material for the paper "The Population of Non-corporate Business Proprietors in England and Wales 1891-1911", by Bennett, Robert J., Montebruno, Piero, Smith, Harry J. as an outcome of the ESRC project ES/M010953: Drivers of Entrepreneurship and Small Businesses PI Prof. Robert J. Bennett. The material consists of two raw text files 1. 1891 Employment status & Weights 2. 1901 Employment status & Weights. Each file has the three following variables: 1. RecID: the ID for I-CEM as in Higgs, Edward and Schürer, Kevin (University of Essex) (2014) The Integrated Census Microdata (I-CeM) UKDA, SN-7481 [data collection] UK Data Service SN: 7481 2. Employment status: 1 Worker 2 Employer 3 Own-account 3. Weights: the inverse of the probability of giving an answer to the Employment Status question of the censuses by Sex and Relationship to the head of the family. A detailed explanation of how these weights were calculated and how to use them in the context of data analysis of this censuses can be found in the accompanying working paper, Montebruno, Piero (2018) ‘Adjustment Weights 1891-1911: Weights to adjust entrepreneurs taking account of non-response and misallocation bias in Censuses 1891-1911’, Working Paper 11: ESRC project ES/M010953: ‘Drivers of Entrepreneurship and Small Businesses’, University of Cambridge, Department of Geography and Cambridge Group for the History of Population and Social Structure. The files can be opened by any text editor, database management system (Access) or statistical package (Stata, SPSS). This dataset should be cited as 'Adjustment Weights 1891-1911, used for "WP 20: Preparing Scottish census data in I-CeM for the British Business Census of Entrepreneurs (BBCE) Harry Smith, Carry van Lieshout, Piero Montebruno, and Bob Bennett"' Please cite using its DOI.

This download goves updated with RecID Adjustment Weights for the 1891-1911 England and Wales censuses and corresponds to Supplementary material for the paper "The Population of Non-corporate Business Proprietors in England and Wales 1891-1911", by Bennett, Robert J., Montebruno, Piero, Smith, Harry J. as an outcome of the ESRC project ES/M010953: Drivers of Entrepreneurship and Small Businesses PI Prof. Robert J. Bennett. The material consists of three raw text files 1. 1891 Employment status & Weights 2. 1901 Employment status & Weights 3. 1911 Employment status & Weights Each file has the three following variables: 1. RecID: the ID for I-CEM2 as in Higgs, Edward and Schürer, Kevin (University of Essex) (2014) The Integrated Census Microdata (I-CeM) UKDA, SN-7481; K. Schürer, E. Higgs, A.M. Reid, E.M Garrett, Integrated Census Microdata, 1851-1911, version V. 2 (I-CeM.2), (2016) [data collection] UK Data Service SN: 7481 2. Employment status: 1 Worker 2 Employer 3 Own-account 3. Weights: the inverse of the probability of giving an answer to the Employment Status question of the censuses by Sex and Relationship to the head of the family. A detailed explanation of how these weights were calculated and how to use them in the context of data analysis of this censuses can be found in the accompanying working paper, Montebruno, Piero (2018) ‘Adjustment Weights 1891-1911: Weights to adjust entrepreneurs taking account of non-response and misallocation bias in Censuses 1891-1911’, Working Paper 11: ESRC project ES/M010953: ‘Drivers of Entrepreneurship and Small Businesses’, University of Cambridge, Department of Geography and Cambridge Group for the History of Population and Social Structure. The files can be opened by any text editor, database management system (Access) or statistical package (Stata, SPSS) This dataset should be cited as Adjustment Weights 1891-1911, "The Population of Non-corporate Business Proprietors in England and Wales 1891-1911", by Bennett, Robert J., Montebruno, Piero, Smith, Harry J. Please cite using its DOI.

This aggregate-level dataset links poor relief data recorded on 1 January 1891 with several variables from corresponding 1891 census data, all at the level of the registration district (RD). Specifically, the numbers of men and women receiving indoor and outdoor relief in the ‘non-able-bodied’ category (taken as a proxy of the numbers of older-age men and women on relief) are accompanied with a series of socio-economic variables calculated from census data on the population aged 60 years and over (our definition of ‘old age’).

Thus, the dataset fulfils two objectives:

1. To start reconciling poor relief data from the House of Commons Parliamentary Papers archive with transcribed Integrated Census Microdata (I-CeM) available at the UK Data Service (UKDS).

2. To capture geographical variations in the proportion of older-age men and women on poor relief as well as in several household, occupational and migratory compositions recorded in the census, consulting data from 1891 as a pilot study in anticipation of an extended project covering all censuses from 1851-1911.

   The study of old age in history has generally had a narrow focus on welfare needs. Specific studies of the extreme poverty, or pauperism, of older people in late nineteenth-century London by Victorian contemporary Charles Booth (1840-1916) have remained remarkably influential for historical research on old age (Booth, 1894; Boyer and Schmidle, 2009). Old age is also examined through institutional care, particularly workhouse accommodation (Lievers, 2009; Ritch, 2014), while the subgroup of the elderly population that were not poor has been underexplored. However, my PhD thesis shows that pauperism was not a universal experience of old age between 1851 and 1911. Using transcribed census data for five selected counties in England and Wales, I find that pauperism was contingent upon many socio-economic factors recorded in census datasets, such as the occupational structure of older people, their living arrangements and their capacity to voluntarily retire from work based on their savings, land and capital. I find that, in some districts of the northern counties of Cheshire and the Yorkshire West Riding, the proportion of men described in the census as 'retired' and the proportion of women 'living on their own means' was greater than the respective proportions of men and women on welfare. For elderly men in particular, there were regional differences in agrarian work, where those in northern England are more likely to run smallholding 'family farms' whereas, in southern England, elderly men generally participate as agricultural labourers. I find that these differences play an important part in the likelihood of becoming pauperised, and adds to the idea of a north-south divide in old age pauperism (King, 2000). Furthermore, pauperism was predicated on the events and circumstances of people throughout their life histories and approaching their old age.

My fellowship will enable me to expand upon these findings through limited additional research that stresses an examination of the experiences of all older people in England and Wales. Old age has to be assessed more widely in relation to regional and geographical characteristics. In this way, we refine Booth's London-centric focus on the relationship between poverty and old age. My fellowship will achieve these objectives by systematically tracing the diversity of old age experiences. A pilot study will link welfare data recorded on 1 January 1891 from the House of Commons Parliamentary Papers archive with the socio-economic indicators contained in the 1891 census conducted on 5 April, all incorporated at the level of c. 650 registration districts in England and Wales. I will also visit record offices to extract data on the names of older people recorded as receiving welfare in materials related to the New Poor Law, thereby expanding on the PhD's examination of the life histories of older people.

With the key findings from my PhD presented above, I will spend my time addressing a wider audience on my research. As I will argue in blogs and webinars addressed to Age UK, the International Longevity Centre UK and History and Policy, a monolithic narrative of old age as associated with welfare dependency and gradual decline has been constructed since Booth's research in the late nineteenth century. This narrative has remained fixed through the growth of our ageing population, and the development of both old age pensions and the modern welfare state. My research alternatively uses historical censuses that reveal the economic productivity of older people in a manner that is not satisfactorily captured in present day discourse. I will also receive training on how to address my PhD to local schools, through the presentation of maps that present variations in the proportions of older people receiving welfare, and in the application of transcribed census data.

About this dataset

Context

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

Key observations

The largest age group in Clarke County, AL was for the group of age 55-59 years with a population of 1,891 (8.10%), according to the 2021 American Community Survey. At the same time, the smallest age group in Clarke County, AL was the 85+ years with a population of 554 (2.37%). 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 Clarke County is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of Clarke 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 Clarke County Population by Age. You can refer the same here

This data set shows the population trajectory for Sri Lanka (Ceylon) before, during, and after the influenza pandemic of 1918-19. Data covers the population estimates of all districts computed including data from the 1946 census as well as estimates of non-plantation districts computed including data from the 1946 census.

The dataset contains the historical series of the census population for the years from 1881 to 2011, broken down by age and gender. The 1891 and 1941 censuses were not carried out, the former for organizational and financial reasons and the latter for war reasons. The data refer to the borders of the time. For further information, it is possible to consult the Istat website http://seriestoriche.istat.it/ This dataset was released by the municipality of Milan.

About this dataset

Context

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

Key observations

The largest age group in Arlington Heights, IL was for the group of age 55-59 years with a population of 5,813 (7.52%), according to the 2021 American Community Survey. At the same time, the smallest age group in Arlington Heights, IL was the 80-84 years with a population of 1,891 (2.45%). 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 Arlington Heights is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of Arlington Heights 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 Arlington Heights Population by Age. You can refer the same here

Abstract copyright UK Data Service and data collection copyright owner.

The aims of the project were as follows :
to collect and process information from the data relating to the Welsh language in the 1891 Census Enumerators' Returns in 20 selected communities in Wales;
to create computer-readable data files on the language ability of around 90,000 individuals, i.e. five per cent of the population;
to undertake a quantitative analysis of the socio-economic structure of Welsh/English language ability on the basis of the above data;
to develop a classification of occupations in order to explore links between economic activity and the process of language change;
to write a volume on the basis of the above in order to deepen our socio-cultural understanding of a society in which nearly a million people spoke Welsh and over half a million were monoglot Welsh.
Main Topics:

The dataset contains 35 files, each of which consists of a 100 per cent sample of the enumeration district in twenty communities selected from the 178 sub-registration districts in Wales, i.e. 90,000 individuals or five per cent of the total population of wales in 1891. Two specific datafiles were created for each district.
Variables in the first file identify : the individual person, enumeration district, schedule number, first name, surname, relation to head of household, marital status, gender, age, occupation, employment status, occupation code, country/county of birth, birthplace and language spoken.
Variables in the second file identify : the enumeration district, schedule number, whether a Welsh-language schedule was used, number of persons in the household, number of rooms and address.

About this dataset

Context

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

Key observations

The largest age group in Aroostook County, ME was for the group of age 55-59 years with a population of 5,612 (8.34%), according to the 2021 American Community Survey. At the same time, the smallest age group in Aroostook County, ME was the 80-84 years with a population of 1,891 (2.81%). 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 Aroostook County is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of Aroostook 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 Aroostook County Population by Age. You can refer the same here

The UNI-CEN Digital Boundary File Series facilitates the mapping of UNI-CEN census data tables. Boundaries are provided in multiple formats for different use cases: Esri Shapefile (SHP), geoJson, and File Geodatabase (FGDB). SHP and FGDB files are provided in two projections: NAD83 CSRS for print cartography and WGS84 for web applications. The geoJson version is provided in WGS84 only. The UNI-CEN Standardized Census Data Tables are readily merged to these boundary files. For more information about file sources, the methods used to create them, and how to use them, consult the documentation at https://borealisdata.ca/dataverse/unicen_docs. For more information about the project, visit https://observatory.uwo.ca/unicen.

About this dataset

Context

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

Key observations

The largest age group in Churchill County, NV was for the group of age 65 to 69 years years with a population of 1,891 (7.38%), according to the ACS 2019-2023 5-Year Estimates. At the same time, the smallest age group in Churchill County, NV was the 80 to 84 years years with a population of 525 (2.05%). 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 Churchill County is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of Churchill 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 Churchill County Population by Age. You can refer the same here