The United States Census Bureau has conducted surveys of manufacturing activity since 1810 with fluctuating frequency. Between 1919 and 1939 the Census of Manufactures (CM) was conducted biennially. This data collection consists of individual-plant data from the Census of Manufactures for 1929, 1931, 1933, and 1935, the only years in this span for which original returns are available. The records of the Cotton Goods Industry have been coded to produce an electronic dataset to provide the basis for microeconomic evidence for the study of the Great Depression. The dataset contains observations on: basic information about the plants (e.g. name, location, owner, etc.), products made and materials used, operation and working hours, employment, wages and salaries, costs and amount of materials used, value of products and processing tax (1933 and 1935), machinery, and power used.

This dataset contains data on population by sex and age on the basis of the results of the Census Data of Latvia, which was carried out on 12 February 1935. Dataset "Latvian Population by Sex and Age in 1935 Census Data" was published implementing project "Historical Sociology of Modern Restorations: a Cross-Time Comparative Study of Post-Communist Transformation in the Baltic States" from 2018 to 2022. Project leader is prof. Zenonas Norkus. Project is funded by the European Social Fund according to the activity "Improvement of researchers' qualification by implementing world-class R&D projects' of Measure No. 09.3.3-LMT-K-712".

This dataset is comprised of selected Division level census counts for the dominion of Newfoundland, Canada derived from the published census reports of 1911, 1935 and 1945. It forms part of a larger project entitled 'The Orange Order in the 20th century: A study in social change'. This wider study explores the relative impact of techno-economic, cultural and institutional factors on Orange Order membership and political influence in twentieth century Scotland, Canada and Northern Ireland Please note: this study does not include information on named individuals and would therefore not be useful for personal family history research. Purposive selection/case studies Transcription of existing materials Compilation or synthesis of existing material

PERIOD: Population census on Oct. 1, 1935. SOURCE: [Survey by the Statistics Bureau, Imperial Cabinet].

The Providence City Archives is pleased to announce the completion of a project to scan the Providence House Directories. These directories were published between 1895 and 1935 and are an invaluable resource for those conducting house research, neighborhood demographic change, and occupancy patterns. Basic entries in the more than 20,000 pages of information are organized by street (unlike the city directories). Individual name listings for each address in many cases indicate occupation and whether the resident is a boarder or owner of the property. Additional directory sections include information on parks, businesses, churches, clubs, theaters, cemeteries, places of amusement and basic census data. The scanned listings allow for key word searches.

The 4th Population Census. In order to clarify the state of Japan’s population and households, the population census has been conducted in Japan almost every five years.More details on the "Population Census of Japan" overall including other years can be found here: https://d-infra.ier.hit-u.ac.jp/Japanese/statistical-yb/b001.html. 　　　　　This is the first census based on persons' place of usual residence.

PERIOD: Population census on Oct. 1, 1935. SOURCE: [Survey by the Statistics Bureau, Imperial Cabinet].

These data are sourced from transcriptions of the original establishment-level schedules from the United States Census of Manufactures taken in 1929, 1931, 1933, and 1935. This dataset combines industries currently archived by ICPSR with new transcriptions. In total, twenty-five industries are included representing some 20 percent of manufacturing output. In addition to information transcribed verbatim from Census schedules, the dataset includes establishment identifiers constructed to link establishments across the censuses.

The twenty-five industries included are Agricultural Implements, Aviation, Beverages, Blast Furnaces, Bone Black, Cement, Cigars and cigarettes, Concrete, Glass, manufactured Ice, Ice cream, Linoleum, Macaroni, Malt, Matches, Motor Vehicles, Petroleum Refining, Planing-mill products, Radio, Rubber tires, Soap, Steel works, Cane Sugar, Refining Sugar.

PERIOD: Population census on Oct. 1, 1935. SOURCE: [Survey by the Statistics Bureau, Imperial Cabinet].

Abstract

The Home Owners’ Loan Corporation (HOLC) was a U.S. federal agency that graded mortgage investment risk of neighborhoods across the U.S. between 1935 and 1940. HOLC residential security maps standardized neighborhood risk appraisal methods that included race and ethnicity, pioneering the institutional logic of residential “redlining.”

Methodology

The Mapping Inequality Project digitized the HOLC mortgage security risk maps from the 1930s. We overlaid the HOLC maps with 2010 and 2020 census tracts for 142 cities across the U.S. using ArcGIS and determined the proportion of HOLC residential security grades contained within the boundaries. We assigned a numerical value to each HOLC risk category as follows: 1 for “A” grade, 2 for “B” grade, 3 for “C” grade, and 4 for “D” grade. We calculated a historic redlining score from the summed proportion of HOLC residential security grades multiplied by a weighting factor based on area within each census tract. A higher score means greater redlining of the census tract. Continuous historic redlining score, assessing the degree of “redlining,” as well as 4 equal interval divisions of redlining, can be linked to existing data sources by census tract identifier allowing for one form of structural racism in the housing market to be assessed with a variety of outcomes.

The 2010 files are set to census 2010 tract boundaries. The 2020 files use the new census 2020 tract boundaries, reflecting the increase in the number of tracts from 12,888 in 2010, to 13,488 in 2020. Use the 2010 HRS with decennial census 2010 or ACS 2010-2019 data. As of publication (10/15/2020) decennial census 2020 data for the P1 (population) and H1 (housing) files are available from census.

Population Census: Male: Age 70 to 74 Years data was reported at 3,582,440.000 Person in 2015. This records an increase from the previous number of 3,225,503.000 Person for 2010. Population Census: Male: Age 70 to 74 Years data is updated yearly, averaging 881,724.000 Person from Dec 1920 (Median) to 2015, with 20 observations. The data reached an all-time high of 3,582,440.000 Person in 2015 and a record low of 394,223.000 Person in 1935. Population Census: Male: Age 70 to 74 Years data remains active status in CEIC and is reported by Statistical Bureau. The data is categorized under Global Database’s Japan – Table JP.G002: Population: Annual.

About this dataset

Context

The dataset presents the the household distribution across 16 income brackets among four distinct age groups in Santa Fe Springs: 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 51(0.89%) households where the householder is under 25 years old, 1,935(33.95%) households with a householder aged between 25 and 44 years, 2,041(35.81%) households with a householder aged between 45 and 64 years, and 1,673(29.35%) 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 city of Santa Fe Springs, 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 Santa Fe Springs median household income by age. You can refer the same here

About this dataset

Context

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

Key observations

The largest age group in Toa Baja Municipio, PR was for the group of age 25 to 29 years years with a population of 5,185 (7.01%), according to the ACS 2019-2023 5-Year Estimates. At the same time, the smallest age group in Toa Baja Municipio, PR was the 85 years and over years with a population of 1,935 (2.62%). 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 Toa Baja Municipio is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of Toa Baja Municipio 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 Toa Baja Municipio Population by Age. You can refer the same here

PERIOD: Population census on Oct. 1, 1935. SOURCE: [Survey by the Statistics Bureau, Imperial Cabinet].

Abstract

For 156 years (1840 - 1996), the U.S. Department of Commerce, Bureau of the Census was responsible for collecting census of agriculture data. The 1997 Appropriations Act contained a provision that transferred the responsibility for the census of agriculture from the Bureau of the Census to the U.S. Department of Agriculture (USDA), National Agricultural Statistics Service (NASS). The 2007 Census of Agriculture is the 27th Federal census of agriculture and the third conducted by NASS. The first agriculture census was taken in 1840 as part of the sixth decennial census of population. The agriculture census continued to be taken as part of the decennial census through 1950. A separate middecade census of agriculture was conducted in 1925, 1935, and 1945. From 1954 to 1974, the census was taken for the years ending in 4 and 9. In 1976, Congress authorized the census of agriculture to be taken for 1978 and 1982 to adjust the data reference year so that it coincided with other economic censuses. This adjustment in timing established the agriculture census on a 5-year cycle collecting data for years ending in 2 and 7. Agriculture census data are used to:

• Evaluate, change, promote, and formulate farm and rural policies and programs that help agricultural producers; • Study historical trends, assess current conditions, and plan for the future; • Formulate market strategies, provide more efficient production and distribution systems, and locate facilities for agricultural communities; • Make energy projections and forecast needs for agricultural producers and their communities; • Develop new and improved methods to increase agricultural production and profitability; • Allocate local and national funds for farm programs, e.g. extension service projects, agricultural research, soil conservation programs, and land-grant colleges and universities; • Plan for operations during drought and emergency outbreaks of diseases or infestations of pests. • Analyze and report on the current state of food, fuel, feed, and fiber production in the United States.

American Samoa is one of the territories collectively referred as the "US Outlying areas". The 2008 American Samoa Census of Agriculture was conducted by personal interviews of all farm operations on the list of commercial farms, and supplemented by an area sample of the remaining households. The purpose of the area sample was to efficiently accountfor farms not on the commercialfarmlist and provide an accurate measure of the agricultural activity in American Samoa.

Geographic coverage

National coverage

Analysis unit

Households

Universe

The statistical unit for the CA 2008 was the farm, an operating unit defined as any place from which USD 1 000 or more of agricultural products were produced and sold, or normally would have been sold, during the census year.

Kind of data

Census/enumeration data [cen]

Sampling procedure

i. Methodological modality for conducting the census The classical approach was used in the CA 2008.

ii. sample design The design of the sample for the 2008 Census of Agriculture made use of materials and information available from the American Samoa Department of Commerce. These included detailed maps of all the islands in the territory, up-to-date map-spotting (location on a map) of all households in the territory, a system of numbering each household to provide it a unique identifier, and identification of householdswhich were on the list of commercial farms. The households that were on the list of commercial farms were excluded from the universe used to select the area sample. A random sample of the remaining households was selected, using the available maps with the household identification information. It was determined that a 20 percent sample would be optimal. A serpentine selection methodology, starting at a point determined by the generation of a random number, was used to select the area sample.

Mode of data collection

Face-to-face paper [f2f]

Research instrument

One questionnaire was used which collected information on:

• Land owned
• Field crops
• Fruit
• Root crops
• Cattle and calves
• Poultry
• Aquaculture
• Expenditure
• Production expenses
• Machinery, equipment and buildings
• Household characteristics

Cleaning operations

1. DATA PROCESSING AND ARCHIVING The completed forms were scanned and Optical Mark Recognition (OMR) was used to retrieve categorical responses and to identify the other answer zones in which some type of mark was present. The edit system determined the best value to impute for reported responses that were deemed unreasonable and for required responses that were absent. The complex edit ensured the full internal consistency of the record. After tabulation and review of the aggregates, a comprehensive disclosure review was conducted. Cell suppression was used to protect the cells that were determined to be sensitive to a disclosure of information.

2. CENSUS DATA QUALITY NASS conducted an extensive program to follow-up all non-response. NASS also used capture-recapture methodology to adjust for under-coverage, non-response, and misclassification. To implement capture-recapture methods, two independent surveys were required --the 2012 Census of Agriculture (based on the Census Mail List) and the 2012 June Agricultural Survey (based on the area frame). Historically, NASS has been careful to maintain the independence of these two surveys.

Data appraisal

The complete data series from the 2008 Census of Agriculture is available from the NASS website free of charge in multiple formats, including Quick Stats 2.0 - an online database to retrieve customized tables with Census data at the national, state and county levels. The 2012 Census of Agriculture provides information on a range of topics, including agricultural practices, conservation, organic production, as well as traditional and specialty crops.

About this dataset

Context

The dataset presents the the household distribution across 16 income brackets among four distinct age groups in Ogemaw 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 186(2.07%) households where the householder is under 25 years old, 1,935(21.50%) households with a householder aged between 25 and 44 years, 3,557(39.53%) households with a householder aged between 45 and 64 years, and 3,321(36.90%) 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 Ogemaw 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) 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 Ogemaw County median household income by age. You can refer the same here

About this dataset

Context

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

Key observations

The largest age group in Norcross, GA was for the group of age 30 to 34 years years with a population of 1,935 (11.04%), according to the ACS 2018-2022 5-Year Estimates. At the same time, the smallest age group in Norcross, GA was the 80 to 84 years years with a population of 168 (0.96%). Source: U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 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 Norcross is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of Norcross 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 Norcross Population by Age. You can refer the same here

Abstract

The 1999 Census of Population and Housing (CPH) of the Republic of Marshall Islands (RMI)) is the tenth census conducted since 1920 and the second since RMI gained independence. The first population census in Marshall Islands was conducted in 1920, after which censuses were conducted every five years up to 1935 when World War II disrupted this pattern. The first census after World War II was in 1958, followed by censuses in 1967, 1973, 1980 and 1988.

The objectives of this census were to provide government planners, policy makers, the private sector and the international donor community with social and economic data and to fulfill the data requirements of the upcoming negotiation of the Compact of Free Association. Data on the size, composition and distribution of the population as well as the structural characteristics and available facilities of housing units were obtained.

Geographic coverage

National coverage.

Analysis unit

Household and Individual.

Universe

All de jure household members were covered.

Kind of data

Census/enumeration data [cen]

Sampling procedure

Not applicable as it is a census.

Sampling deviation

Not applicable as it is a census.

Mode of data collection

Face-to-face [f2f]

Research instrument

Two types of questionnaires were drafted -- (1) CPH Form 2 gathers information on the demographic, social and economic characteristics of the population as well as the characteristics of the building and housing units, and (2) CPH Form 3 gathers information on people residing in institutional living quarters These questionnaires were reviewed several times by NCSC. OPS and CTC pre-tested the questionnaires at the end of March. Revisions were made on the basis of the pre-test and the revised questionnaires were reviewed again by the NCSC. After the questionnaires in English version were approved by NCSC, they were translated into Marshallese to facilitate the training of enumerators and supervisors. The English version of the questionnaires, however, was used in the actual enumeration with questions asked in Marshallese. The enumerators and supervisors kept a copy of the questionnaires in Marshallese for reference. Control forms such as listing sheets that will be used to generate preliminary counts were also prepared by CTC. These forms were designed to record the major step of the census operations.

Cleaning operations

The questionnaires were separated by type of form and folioed by EA. Each folio was checked for completeness. The questionnaires underwent two stages of processing -- manual processing and machine processing. Manual processing involved the verification of geographic identification, review of the entries for completeness, consistency and acceptability of responses and coding of selected items. Data editing, verification of questionnaire and/or callbacks were performed in iteration until all the data editing rules have been fulfilled or when there are no more reject listing on the particular questionnaire. Some data records had to be edited four times. This means that four iterations of the steps mentioned above had to be done before the records or questionnaires could be declared without error. Twenty-four people were involved in the data processing process.These are the ADB Data Processing Consultant, a national data processing specialist from OPS, 9 manual processors, 5 keyers for data entries, 1 keyer for field editing, 6 data processors and 1 keyer for updating of the data files.

Sampling error estimates

Not applicable as this is a census.

Data appraisal

The preliminary population counts by atoll and by sex and atoll were generated based on the listing sheet in the first week of August 1999. These were compared to the 1988 and 1980 censuses. The comparison indicated that the average annual population growth rate between 1988 and 1999 was lower than expected. The possible undercount in the 1999 census was investigated. The CTC proposed a plan to revisit the major atolls of Majuro and Kwajalein that the NCSC discussed and approved.

About this dataset

Context

The dataset presents the the household distribution across 16 income brackets among four distinct age groups in Collier 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 1,935(1.20%) households where the householder is under 25 years old, 30,660(19.06%) households with a householder aged between 25 and 44 years, 50,877(31.63%) households with a householder aged between 45 and 64 years, and 77,395(48.11%) 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 65 years and over bracket. This distribution hints at economic disparities within the county of Collier 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) 2019-2023 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 Collier County median household income by age. You can refer the same here

PERIOD: Population Census on Oct. 1, 1935. SOURCE: [Surveys by the Statistics Bureau, Imperial Cabinet and government offices, overseas territories of Japan].