This data collection contains population and per capita income estimates for over 39,000 governmental entities in the United States, recorded for selected years from 1969 to 1975. These estimates were developed to provide updates of the data elements in federal revenue sharing allocations under the state and local Fiscal Assistance Act of 1972. Estimates recorded in the data file are for July 1 of the respective years, while per capita income refers to the entire year. Data items included are population in 1970 as recorded in the decennial census of that year, population estimates for 1973 and 1975, and per capita money income estimates for 1969, 1972, and 1974.

A nice clean panel of basic demographic information for every US county from 1969 to 2023. Variables include total population, percent white, percent black, percent male, percent children (age 0-17), and percent seniors (age 65+). This is a cleaned and reshaped version of the CDC SEER data available here: https://seer.cancer.gov/popdata/download.html

This data collection provides information on income and population estimates for the United States in the period 1969-1973. Variables include the total population in 1970, estimated population in 1973, per capita income for 1969, and estimated total money income for 1973. Data are recorded for each of the 38,529 governments (counties, townships, minor civil divisions, etc.) eligible for participation in the Federal Revenue Sharing Program. These data were prepared as part of the Bureau of the Census's Federal-State Cooperative Program for Local Population Estimates.

Data from National Cancer instituted, better described at https://seer.cancer.gov/popdata/download.html

This data is adjusted such that Hurricane Katrina displaced victims in 2005 have their own cfips code.

United States US: Population: Male: Ages 70-74: % of Male Population data was reported at 3.553 % in 2017. This records an increase from the previous number of 3.377 % for 2016. United States US: Population: Male: Ages 70-74: % of Male Population data is updated yearly, averaging 2.712 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 3.553 % in 2017 and a record low of 2.264 % in 1969. United States US: Population: Male: Ages 70-74: % of Male Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s USA – Table US.World Bank: Population and Urbanization Statistics. Male population between the ages 70 to 74 as a percentage of the total male population.; ; World Bank staff estimates based on age/sex distributions of United Nations Population Division's World Population Prospects: 2017 Revision.; ;

United States US: Population: Female: Ages 10-14: % of Female Population data was reported at 6.249 % in 2017. This records a decrease from the previous number of 6.258 % for 2016. United States US: Population: Female: Ages 10-14: % of Female Population data is updated yearly, averaging 7.054 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 9.665 % in 1969 and a record low of 6.249 % in 2017. United States US: Population: Female: Ages 10-14: % of Female Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s USA – Table US.World Bank: Population and Urbanization Statistics. Female population between the ages 10 to 14 as a percentage of the total female population.; ; World Bank staff estimates based on age/sex distributions of United Nations Population Division's World Population Prospects: 2017 Revision.; ;

VITAL SIGNS INDICATOR Population (LU1)

FULL MEASURE NAME Population estimates

LAST UPDATED October 2019

DESCRIPTION Population is a measurement of the number of residents that live in a given geographical area, be it a neighborhood, city, county or region.

DATA SOURCES U.S Census Bureau: Decennial Census No link available (1960-1990) http://factfinder.census.gov (2000-2010)

California Department of Finance: Population and Housing Estimates Table E-6: County Population Estimates (1961-1969) Table E-4: Population Estimates for Counties and State (1971-1989) Table E-8: Historical Population and Housing Estimates (2001-2018) Table E-5: Population and Housing Estimates (2011-2019) http://www.dof.ca.gov/Forecasting/Demographics/Estimates/

U.S. Census Bureau: Decennial Census - via Longitudinal Tract Database Spatial Structures in the Social Sciences, Brown University Population Estimates (1970 - 2010) http://www.s4.brown.edu/us2010/index.htm

U.S. Census Bureau: American Community Survey 5-Year Population Estimates (2011-2017) http://factfinder.census.gov

U.S. Census Bureau: Intercensal Estimates Estimates of the Intercensal Population of Counties (1970-1979) Intercensal Estimates of the Resident Population (1980-1989) Population Estimates (1990-1999) Annual Estimates of the Population (2000-2009) Annual Estimates of the Population (2010-2017) No link available (1970-1989) http://www.census.gov/popest/data/metro/totals/1990s/tables/MA-99-03b.txt http://www.census.gov/popest/data/historical/2000s/vintage_2009/metro.html https://www.census.gov/data/datasets/time-series/demo/popest/2010s-total-metro-and-micro-statistical-areas.html

CONTACT INFORMATION vitalsigns.info@bayareametro.gov

METHODOLOGY NOTES (across all datasets for this indicator) All legal boundaries and names for Census geography (metropolitan statistical area, county, city, and tract) are as of January 1, 2010, released beginning November 30, 2010, by the U.S. Census Bureau. A Priority Development Area (PDA) is a locally-designated area with frequent transit service, where a jurisdiction has decided to concentrate most of its housing and jobs growth for development in the foreseeable future. PDA boundaries are current as of August 2019. For more information on PDA designation see http://gis.abag.ca.gov/website/PDAShowcase/.

Population estimates for Bay Area counties and cities are from the California Department of Finance, which are as of January 1st of each year. Population estimates for non-Bay Area regions are from the U.S. Census Bureau. Decennial Census years reflect population as of April 1st of each year whereas population estimates for intercensal estimates are as of July 1st of each year. Population estimates for Bay Area tracts are from the decennial Census (1970 -2010) and the American Community Survey (2008-2012 5-year rolling average; 2010-2014 5-year rolling average; 2013-2017 5-year rolling average). Estimates of population density for tracts use gross acres as the denominator.

Population estimates for Bay Area PDAs are from the decennial Census (1970 - 2010) and the American Community Survey (2006-2010 5 year rolling average; 2010-2014 5-year rolling average; 2013-2017 5-year rolling average). Population estimates for PDAs are derived from Census population counts at the tract level for 1970-1990 and at the block group level for 2000-2017. Population from either tracts or block groups are allocated to a PDA using an area ratio. For example, if a quarter of a Census block group lies with in a PDA, a quarter of its population will be allocated to that PDA. Tract-to-PDA and block group-to-PDA area ratios are calculated using gross acres. Estimates of population density for PDAs use gross acres as the denominator.

Annual population estimates for metropolitan areas outside the Bay Area are from the Census and are benchmarked to each decennial Census. The annual estimates in the 1990s were not updated to match the 2000 benchmark.

The following is a list of cities and towns by geographical area: Big Three: San Jose, San Francisco, Oakland Bayside: Alameda, Albany, Atherton, Belmont, Belvedere, Berkeley, Brisbane, Burlingame, Campbell, Colma, Corte Madera, Cupertino, Daly City, East Palo Alto, El Cerrito, Emeryville, Fairfax, Foster City, Fremont, Hayward, Hercules, Hillsborough, Larkspur, Los Altos, Los Altos Hills, Los Gatos, Menlo Park, Mill Valley, Millbrae, Milpitas, Monte Sereno, Mountain View, Newark, Pacifica, Palo Alto, Piedmont, Pinole, Portola Valley, Redwood City, Richmond, Ross, San Anselmo, San Bruno, San Carlos, San Leandro, San Mateo, San Pablo, San Rafael, Santa Clara, Saratoga, Sausalito, South San Francisco, Sunnyvale, Tiburon, Union City, Vallejo, Woodside Inland, Delta and Coastal: American Canyon, Antioch, Benicia, Brentwood, Calistoga, Clayton, Cloverdale, Concord, Cotati, Danville, Dixon, Dublin, Fairfield, Gilroy, Half Moon Bay, Healdsburg, Lafayette, Livermore, Martinez, Moraga, Morgan Hill, Napa, Novato, Oakley, Orinda, Petaluma, Pittsburg, Pleasant Hill, Pleasanton, Rio Vista, Rohnert Park, San Ramon, Santa Rosa, Sebastopol, Sonoma, St. Helena, Suisun City, Vacaville, Walnut Creek, Windsor, Yountville Unincorporated: all unincorporated towns

According to the data, support for marijuana legalization has increased from 12 percent of respondents in 1969 to a record-high of 70 percent of respondents in 2023. This statistic depicts the percentage of U.S. adults that supported marijuana legalization from 1969 to 2023.

United States US: Rural Population data was reported at 58,440,535.000 Person in 2017. This records a decrease from the previous number of 58,659,368.000 Person for 2016. United States US: Rural Population data is updated yearly, averaging 59,251,956.500 Person from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 61,656,881.000 Person in 1990 and a record low of 54,047,876.000 Person in 1969. United States US: Rural Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United States – Table US.World Bank.WDI: Population and Urbanization Statistics. Rural population refers to people living in rural areas as defined by national statistical offices. It is calculated as the difference between total population and urban population. Aggregation of urban and rural population may not add up to total population because of different country coverages.; ; World Bank staff estimates based on the United Nations Population Division's World Urbanization Prospects: 2018 Revision.; Sum;

About this dataset

Context

The dataset tabulates the population of Mount Pleasant town by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Mount Pleasant town. The dataset can be utilized to understand the population distribution of Mount Pleasant town by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Mount Pleasant town. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for Mount Pleasant town.

Key observations

Largest age group (population): Male # 15-19 years (1,891) | Female # 50-54 years (1,969). 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

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis.

Variables / Data Columns

• Age Group: This column displays the age group for the Mount Pleasant town population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Mount Pleasant town is shown in the following column.
• Population (Female): The female population in the Mount Pleasant town is shown in the following column.
• Gender Ratio: Also known as the sex ratio, this column displays the number of males per 100 females in Mount Pleasant town for each age group.

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 Mount Pleasant town Population by Gender. You can refer the same here

About this dataset

Context

The dataset tabulates the population of Hillsdale County by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Hillsdale County. The dataset can be utilized to understand the population distribution of Hillsdale County by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Hillsdale County. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for Hillsdale County.

Key observations

Largest age group (population): Male # 55-59 years (1,804) | Female # 60-64 years (1,969). 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

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis.

Variables / Data Columns

• Age Group: This column displays the age group for the Hillsdale County population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Hillsdale County is shown in the following column.
• Population (Female): The female population in the Hillsdale County is shown in the following column.
• Gender Ratio: Also known as the sex ratio, this column displays the number of males per 100 females in Hillsdale County for each age group.

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 Hillsdale County Population by Gender. You can refer the same here

About this dataset

Context

The dataset tabulates the population of Arcata by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Arcata. The dataset can be utilized to understand the population distribution of Arcata by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Arcata. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for Arcata.

Key observations

Largest age group (population): Male # 20-24 years (1,918) | Female # 20-24 years (1,969). 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

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis.

Variables / Data Columns

• Age Group: This column displays the age group for the Arcata population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Arcata is shown in the following column.
• Population (Female): The female population in the Arcata is shown in the following column.
• Gender Ratio: Also known as the sex ratio, this column displays the number of males per 100 females in Arcata for each age group.

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 Arcata Population by Gender. You can refer the same here

About this dataset

Context

The dataset tabulates the population of Elyria by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Elyria. The dataset can be utilized to understand the population distribution of Elyria by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Elyria. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for Elyria.

Key observations

Largest age group (population): Male # 30-34 years (2,123) | Female # 30-34 years (1,969). 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

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis.

Variables / Data Columns

• Age Group: This column displays the age group for the Elyria population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Elyria is shown in the following column.
• Population (Female): The female population in the Elyria is shown in the following column.
• Gender Ratio: Also known as the sex ratio, this column displays the number of males per 100 females in Elyria for each age group.

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 Elyria Population by Gender. You can refer the same here

This replication package provides code for the data analysis reported in “Newly Available Individual-level U.S. Tax Data from 1969-1994”. All data analysis was conducted in the Integrated Research Environment of the Federal Statistical Research Data Center (FSRDCs). The source data included IRS Form 1040 files, Current Population Survey data, and decennial Census data. The code provided with this documentation includes redacted variable names, dataset names, and dataset paths, since that information is protected by Title 13 and Title 26 of the U.S. Code. All results and replication code have been reviewed to ensure that no confidential information is disclosed. Researchers who would like to replicate or review this analysis within the FSRDCs should take the following steps: (1) Propose an FSRDC project that includes the following datasets: IRS Form 1040 from 1969, 1974, 1979, 1984, 1989, 1994, 1999; Current Population Survey ASEC from 1973, 1985, 1991, 1995, 2000; Current Population Survey PIK crosswalks from1973, 1985, 1991, 1995, 2000; Decennial Census data and PIK crosswalks from 1940, 2000; and (2) Request access to CES Technical Note “Replication Documentation for 'Newly Available Individual-level U.S. Tax Data from 1969-1994' by contacting an FSRDC Administrator or CES.Technical.Notes.List@census.gov. The technical note contains the same code provided here, but with unredacted information on variable names, dataset names, and dataset paths.

About this dataset

Context

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

Key observations

The largest age group in Lino Lakes, MN was for the group of age 55 to 59 years years with a population of 1,969 (9.15%), according to the ACS 2018-2022 5-Year Estimates. At the same time, the smallest age group in Lino Lakes, MN was the 85 years and over years with a population of 144 (0.67%). 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 Lino Lakes is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of Lino Lakes 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 Lino Lakes Population by Age. You can refer the same here

About this dataset

Context

The dataset tabulates the population of Clatsop County by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Clatsop County. The dataset can be utilized to understand the population distribution of Clatsop County by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Clatsop County. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for Clatsop County.

Key observations

Largest age group (population): Male # 60-64 years (1,744) | Female # 60-64 years (1,969). 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

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis.

Variables / Data Columns

• Age Group: This column displays the age group for the Clatsop County population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Clatsop County is shown in the following column.
• Population (Female): The female population in the Clatsop County is shown in the following column.
• Gender Ratio: Also known as the sex ratio, this column displays the number of males per 100 females in Clatsop County for each age group.

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 Clatsop County Population by Gender. You can refer the same here

Although the founding fathers declared American independence in 1776, and the subsequent Revolutionary War ended in 1783, individual states did not officially join the union until 1787. The first states to ratify the U.S. Constitution were Delaware, Pennsylvania and New Jersey, in December 1787, and they were joined by the remainder of the thirteen ex-British colonies by 1790. Another three states joined before the turn of the nineteenth century, and there were 45 states by 1900. The final states, Alaska and Hawaii, were admitted to the union in 1959, almost 172 years after the first colonies became federal states. Secession in the American Civil War The issues of slavery and territorial expansion in the mid nineteenth century eventually led to the American Civil War, which lasted from 1861 until 1865. As the U.S. expanded westwards, a moral and economic argument developed about the legality of slavery in these new states; northern states were generally opposed to the expansion of slavery, whereas the southern states (who were economically dependent on slavery) saw this lack of extension as a stepping stone towards nationwide abolition. In 1861, eleven southern states seceded from the Union, and formed the Confederate States of America. When President Lincoln refused to relinquish federal property in the south, the Confederacy attacked, setting in motion the American Civil War. After four years, the Union emerged victorious, and the Confederate States of America was disbanded, and each individual state was readmitted to Congress gradually, between 1866 and 1870. Expansion of other territories Along with the fifty U.S. states, there is one federal district (Washington D.C., the capital city), and fourteen overseas territories, five of which with a resident population (American Samoa, Guam, the Northern Mariana Islands, Puerto Rico, and the U.S. Virgin Islands). In 2019, President Trump inquired about the U.S. purchasing the territory of Greenland from Denmark, and, although Denmark's response indicated that this would be unlikely, this does suggest that the US may be open to further expansion of it's states and territories in the future. There is also a movement to make Washington D.C. the 51st state to be admitted to the union, as citizens of the nation's capital (over 700,000 people) do not have voting representation in the houses of Congress nor control over many local affairs; as of 2020, the U.S. public appears to be divided on the issue, and politicians are split along party lines, as D.C. votes overwhelmingly for the Democratic nominee in presidential elections.

The certainty and promptness of punishment have long been hypothesized to be important variables in deterring crime. This data collection evaluates whether sentencing reforms to enhance certainty of punishment and speedy trial laws to enhance promptness of punishment affected crime rates, prison admissions, and prison populations. Variables include state, year, crime reports, economic conditions, population (including age structure), prison population, prison releases, and prison admissions. The unit of observation is the state by the year.

Graph and download economic data for Average Hours of Work Per Week, Nonagricultural Employment, Household Survey for United States (M08304USM310NNBR) from Jun 1941 to Dec 1969 about nonagriculture, hours, household survey, employment, and USA.

About this dataset

Context

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

Key observations

The largest age group in Lilburn, GA was for the group of age 5 to 9 years years with a population of 1,969 (13.36%), according to the ACS 2018-2022 5-Year Estimates. At the same time, the smallest age group in Lilburn, GA was the 85 years and over years with a population of 166 (1.13%). 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 Lilburn is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of Lilburn 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 Lilburn Population by Age. You can refer the same here