The Decennial Census provides population estimates and demographic information on residents of the United States.

The Census Summary Files contain detailed tables on responses to the decennial census. Data tables in Summary File 1 provide information on population and housing characteristics, including cross-tabulations of age, sex, households, families, relationship to householder, housing units, detailed race and Hispanic or Latino origin groups, and group quarters for the total population. Summary File 2 contains data tables on population and housing characteristics as reported by housing unit.

Researchers at NYU Langone Health can find guidance for the use and analysis of Census Bureau data on the Population Health Data Hub (listed under "Other Resources"), which is accessible only through the intranet portal with a valid Kerberos ID (KID).

Data from: American Community Survey, 5-year Series

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, the decennial census is the official source of population totals for April 1st of each decennial year. In between censuses, the Census Bureau's Population Estimates Program produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units and the group quarters population for states and counties..Information about the American Community Survey (ACS) can be found on the ACS website. Supporting documentation including code lists, subject definitions, data accuracy, and statistical testing, and a full list of ACS tables and table shells (without estimates) can be found on the Technical Documentation section of the ACS website.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2023 American Community Survey 1-Year Estimates.ACS data generally reflect the geographic boundaries of legal and statistical areas as of January 1 of the estimate year. For more information, see Geography Boundaries by Year..Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..Users must consider potential differences in geographic boundaries, questionnaire content or coding, or other methodological issues when comparing ACS data from different years. Statistically significant differences shown in ACS Comparison Profiles, or in data users' own analysis, may be the result of these differences and thus might not necessarily reflect changes to the social, economic, housing, or demographic characteristics being compared. For more information, see Comparing ACS Data..The 12 selected states are Connecticut, Maine, Massachusetts, Michigan, Minnesota, New Hampshire, New Jersey, New York, Pennsylvania, Rhode Island, Vermont, and Wisconsin..Workers include members of the Armed Forces and civilians who were at work last week..When information is missing or inconsistent, the Census Bureau logically assigns an acceptable value using the response to a related question or questions. If a logical assignment is not possible, data are filled using a statistical process called allocation, which uses a similar individual or household to provide a donor value. The "Allocated" section is the number of respondents who received an allocated value for a particular subject..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on 2020 Census data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution. For a 5-year median estimate, the margin of error associated with a median was larger than the median itself.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (X) The estimate or margin of error is not applicable or not available.median- The median falls in the lowest interval of an open-ended distribution (for example "2,500-")median+ The median falls in the highest interval of an open-ended distribution (for example "250,000+").** The margin of error could not be computed because there were an insufficient number of sample observations.*** The margin of error could not be computed because the median falls in the lowest interval or highest interval of an open-ended distribution.***** A margin of error is not appropriate because the corresponding estimate is controlled to an independent population or housing estimate. Effectively, the corresponding estimate has no sampling error and the margin of error may be treated as zero.

Users can download data or view data tables on topics related to the labor force of the United States. Background Current Population Survey is a joint effort between the Bureau of Labor Statistics and the Census Bureau. It provides information and data on the labor force of the United States, such as: employment, unemployment, earnings, hours of work, school enrollment, health, employee benefits and income. The CPS is conducted monthly and has a sample of approximately 50,000 households. It is representative of the non-institutionalized US population. The sample provides estimates for the nation as a whole and serves as part of model-based estimates for individual states and other geographic areas. User Functionality Users can download data sets or view data tables on their topic of interest. Data can be organized by a variety of demographic variables, including: sex, age, race, marital status and educational attainment. Data is available on a national or state level. Data Notes The CPS is conducted monthly and has a sample of approximately 50,000 households. It is representative of the non-institutionalized US population. The sample provides estimates for th e nation as a whole and serves as part of model-based estimates for individual states and other geographic areas.

Provides data on the number of children that women aged 15-50 have ever had, year of first birth, mother's age at first birth, and marital status at first birth.

Data from: American Community Survey, 5-year Series

The estimated median household income and estimated median family income are two separate measures: every family is a household, but not every household is a family. According to the U.S. Census Bureau definitions of the terms, a family “includes a householder and one or more people living in the same household who are related to the householder by birth, marriage, or adoption,”[1] while a household “includes all the people who occupy a housing unit,” including households of just one person[2]. When evaluated together, the estimated median household income and estimated median family income provide a thorough picture of household-level economics in Champaign County.

Both estimated median household income and estimated median family income were higher in 2023 than in 2005. The changes in estimated median household income and estimated median family income between 2022 and 2023 were not statistically significant. Estimated median family income is consistently higher than estimated median household income, largely due to the definitions of each term, and the types of household that are measured and are not measured in each category.

Median income data was sourced from the U.S. Census Bureau’s American Community Survey (ACS) 1-Year Estimates, which are released annually.

As with any datasets that are estimates rather than exact counts, it is important to take into account the margins of error (listed in the column beside each figure) when drawing conclusions from the data.

Due to the impact of the COVID-19 pandemic, instead of providing the standard 1-year data products, the Census Bureau released experimental estimates from the 1-year data. This includes a limited number of data tables for the nation, states, and the District of Columbia. The Census Bureau states that the 2020 ACS 1-year experimental tables use an experimental estimation methodology and should not be compared with other ACS data. For these reasons, and because data is not available for Champaign County, no data for 2020 is included in this Indicator.

For interested data users, the 2020 ACS 1-Year Experimental data release includes datasets on Median Household Income in the Past 12 Months (in 2020 Inflation-Adjusted Dollars) and Median Family Income in the Past 12 Months (in 2020 Inflation-Adjusted Dollars).

[1] U.S. Census Bureau. (Date unknown). Glossary. “Family Household.” (Accessed 19 April 2016).

[2] U.S. Census Bureau. (Date unknown). Glossary. “Household.” (Accessed 19 April 2016).

Sources: U.S. Census Bureau; American Community Survey, 2023 American Community Survey 1-Year Estimates, Table S1903; generated by CCRPC staff; using data.census.gov; (17 October 2024).; U.S. Census Bureau; American Community Survey, 2022 American Community Survey 1-Year Estimates, Table S1903; generated by CCRPC staff; using data.census.gov; (18 September 2023).; U.S. Census Bureau; American Community Survey, 2021 American Community Survey 1-Year Estimates, Table S1903; generated by CCRPC staff; using data.census.gov; (3 October 2022).; U.S. Census Bureau; American Community Survey, 2019 American Community Survey 1-Year Estimates, Table S1903; generated by CCRPC staff; using data.census.gov; (7 June 2021).; U.S. Census Bureau; American Community Survey, 2018 American Community Survey 1-Year Estimates, Table S1903; generated by CCRPC staff; using data.census.gov; (7 June 2021).;U.S. Census Bureau; American Community Survey, 2017 American Community Survey 1-Year Estimates, Table S1903; generated by CCRPC staff; using American FactFinder; (13 September 2018).; U.S. Census Bureau; American Community Survey, 2016 American Community Survey 1-Year Estimates, Table S1903; generated by CCRPC staff; using American FactFinder; (14 September 2017).; U.S. Census Bureau; American Community Survey, 2015 American Community Survey 1-Year Estimates, Table S1903; generated by CCRPC staff; using American FactFinder; (19 September 2016).; U.S. Census Bureau; American Community Survey, 2014 American Community Survey 1-Year Estimates, Table S1903; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2013 American Community Survey 1-Year Estimates, Table S1903; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2012 American Community Survey 1-Year Estimates, Table S1903; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2011 American Community Survey 1-Year Estimates, Table S1903; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2010 American Community Survey 1-Year Estimates, Table S1903; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2009 American Community Survey 1-Year Estimates, Table S1903; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2008 American Community Survey 1-Year Estimates, Table S1903; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2007 American Community Survey 1-Year Estimates, Table S1903; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2006 American Community Survey 1-Year Estimates, Table S1903; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2005 American Community Survey 1-Year Estimates, Table S1903; generated by CCRPC staff; using American FactFinder; (16 March 2016).

This layer shows demographic context for emergency response efforts. This is shown by tract, county, and state boundaries. This service is updated annually to contain the most currently released American Community Survey (ACS) 5-year data, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis.

U.S. Census Bureau QuickFacts statistics for Reagan County, Texas. QuickFacts data are derived from: Population Estimates, American Community Survey, Census of Population and Housing, Current Population Survey, Small Area Health Insurance Estimates, Small Area Income and Poverty Estimates, State and County Housing Unit Estimates, County Business Patterns, Nonemployer Statistics, Economic Census, Survey of Business Owners, Building Permits.

This layer shows median earnings by occupational group. This is shown by tract, county, and state boundaries. This service is updated annually to contain the most currently released American Community Survey (ACS) 5-year data, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. Only full-time year-round workers included. Median earnings is based on earnings in past 12 months of survey. Occupation Groups based on Bureau of Labor Statistics (BLS)' Standard Occupation Classification (SOC).

The SNAP participation rate shows how many households in Champaign County receive SNAP benefits, as a percentage of the total number of households in the county. The SNAP participation rate can serve as an indicator of poverty and need in the area, as income-based thresholds establish SNAP eligibility. However, not every household in poverty receives SNAP benefits, as can be determined by comparing the poverty rate between 2005 and 2023 and the percentage of households receiving SNAP benefits between 2005 and 2023.

The number of households and the percentage of households receiving SNAP benefits was higher in 2023 than in 2005, but we cannot establish a trend based on year-to-year changes, as in many years these changes are not statistically significant.

SNAP participation data was sourced from the U.S. Census Bureau’s American Community Survey (ACS) 1-Year Estimates, which are released annually.

As with any datasets that are estimates rather than exact counts, it is important to take into account the margins of error (listed in the column beside each figure) when drawing conclusions from the data.

Due to the impact of the COVID-19 pandemic, instead of providing the standard 1-year data products, the Census Bureau released experimental estimates from the 1-year data in 2020. This includes a limited number of data tables for the nation, states, and the District of Columbia. The Census Bureau states that the 2020 ACS 1-year experimental tables use an experimental estimation methodology and should not be compared with other ACS data. For these reasons, and because data is not available for Champaign County, no data for 2020 is included in this Indicator.

For interested data users, the 2020 ACS 1-Year Experimental data release includes a dataset on Receipt of Food Stamps/SNAP in the Past 12 Months by Presence of Children Under 18 Years for Households.

Sources: U.S. Census Bureau; American Community Survey, 2023 American Community Survey 1-Year Estimates, Table S2201; generated by CCRPC staff; using data.census.gov; (17 October 2024).; U.S. Census Bureau; American Community Survey, 2022 American Community Survey 1-Year Estimates, Table S2201; generated by CCRPC staff; using data.census.gov; (26 September 2023).; U.S. Census Bureau; American Community Survey, 2021 American Community Survey 1-Year Estimates, Table S2201; generated by CCRPC staff; using data.census.gov; (5 October 2022).; U.S. Census Bureau; American Community Survey, 2019 American Community Survey 1-Year Estimates, Table S2201; generated by CCRPC staff; using data.census.gov; (8 June 2021).; U.S. Census Bureau; American Community Survey, 2018 American Community Survey 1-Year Estimates, Table S2201; generated by CCRPC staff; using data.census.gov; (8 June 2021).; U.S. Census Bureau; American Community Survey, 2017 American Community Survey 1-Year Estimates, Table S2201; generated by CCRPC staff; using American FactFinder; (13 September 2018).; U.S. Census Bureau; American Community Survey, 2016 American Community Survey 1-Year Estimates, Table S2201; generated by CCRPC staff; using American FactFinder; (14 September 2017).; U.S. Census Bureau; American Community Survey, 2015 American Community Survey 1-Year Estimates, Table S2201; generated by CCRPC staff; using American FactFinder; (19 September 2016).; U.S. Census Bureau; American Community Survey, 2014 American Community Survey 1-Year Estimates, Table S2201; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2013 American Community Survey 1-Year Estimates, Table S2201; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2012 American Community Survey 1-Year Estimates, Table S2201; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2011 American Community Survey 1-Year Estimates, Table S2201; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2010 American Community Survey 1-Year Estimates, Table S2201; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2009 American Community Survey 1-Year Estimates, Table S2201; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2008 American Community Survey 1-Year Estimates, Table S2201; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2007 American Community Survey 1-Year Estimates, Table S2201; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2006 American Community Survey 1-Year Estimates, Table S2201; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2005 American Community Survey 1-Year Estimates, Table S2201; generated by CCRPC staff; using American FactFinder; (16 March 2016).

This layer shows demographic context for senior well-being work. This is shown by tract, county, and state boundaries. This service is updated annually to contain the most currently released American Community Survey (ACS) 5-year data, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis.

About this dataset

Context

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

Key observations

The largest age group in Nome Census Area, AK was for the group of age 10 to 14 years years with a population of 1,058 (10.66%), according to the ACS 2019-2023 5-Year Estimates. At the same time, the smallest age group in Nome Census Area, AK was the 85 years and over years with a population of 45 (0.45%). 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 Nome Census Area is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of Nome Census Area 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 Nome Census Area Population by Age. You can refer the same here

Household Pulse Survey (HPS): HPS is a rapid-response survey of adults ages ≥18 years led by the U.S. Census Bureau, in partnership with seven other federal statistical agencies, to measure household experiences during the COVID-19 pandemic. Detailed information on probability sampling using the U.S. Census Bureau’s Master Address File, questionnaires, response rates, and bias assessment is available on the Census Bureau website (https://www.census.gov/data/experimental-data-products/household-pulse-survey.html).

Data from adults age ≥18 years are collected by 20-minute online survey from randomly sampled households stratified by state and the top 15 metropolitan statistical areas (MSAs). Data are weighted to represent total persons age 18 and older living within households and to mitigate possible bias that can result from non-responses and incomplete survey frame. Data from adults age ≥18 years are collected by 20-minute online survey from randomly sampled households stratified by state and the top 15 metropolitan statistical areas (MSAs). For more information on this survey, see https://www.census.gov/programs-surveys/household-pulse-survey.html.

Data are weighted to represent total persons age 18 and older living within households and to mitigate possible bias that can result from non-responses and incomplete survey frame. Responses in the Household Pulse Survey (https://www.census.gov/programs-surveys/household-pulse-survey.html) are self-reported. Estimates of vaccination coverage may differ from vaccine administration data reported at COVID-19 Vaccinations in the United States (https://covid.cdc.gov/covid-data-tracker/#vaccinations).

This commuter mode share data shows the estimated percentages of commuters in Champaign County who traveled to work using each of the following modes: drove alone in an automobile; carpooled; took public transportation; walked; biked; went by motorcycle, taxi, or other means; and worked at home. Commuter mode share data can illustrate the use of and demand for transit services and active transportation facilities, as well as for automobile-focused transportation projects.

Driving alone in an automobile is by far the most prevalent means of getting to work in Champaign County, accounting for over 69 percent of all work trips in 2023. This is the same rate as 2019, and the first increase since 2017, both years being before the COVID-19 pandemic began.

The percentage of workers who commuted by all other means to a workplace outside the home also decreased from 2019 to 2021, most of these modes reaching a record low since this data first started being tracked in 2005. The percentage of people carpooling to work in 2023 was lower than every year except 2016 since this data first started being tracked in 2005. The percentage of people walking to work increased from 2022 to 2023, but this increase is not statistically significant.

Meanwhile, the percentage of people in Champaign County who worked at home more than quadrupled from 2019 to 2021, reaching a record high over 18 percent. It is a safe assumption that this can be attributed to the increase of employers allowing employees to work at home when the COVID-19 pandemic began in 2020.

The work from home figure decreased to 11.2 percent in 2023, but which is the first statistically significant decrease since the pandemic began. However, this figure is still about 2.5 times higher than 2019, even with the COVID-19 emergency ending in 2023.

Commuter mode share data was sourced from the U.S. Census Bureau’s American Community Survey (ACS) 1-Year Estimates, which are released annually.

As with any datasets that are estimates rather than exact counts, it is important to take into account the margins of error (listed in the column beside each figure) when drawing conclusions from the data.

Due to the impact of the COVID-19 pandemic, instead of providing the standard 1-year data products, the Census Bureau released experimental estimates from the 1-year data in 2020. This includes a limited number of data tables for the nation, states, and the District of Columbia. The Census Bureau states that the 2020 ACS 1-year experimental tables use an experimental estimation methodology and should not be compared with other ACS data. For these reasons, and because data is not available for Champaign County, no data for 2020 is included in this Indicator.

For interested data users, the 2020 ACS 1-Year Experimental data release includes a dataset on Means of Transportation to Work.

Sources: U.S. Census Bureau; American Community Survey, 2023 American Community Survey 1-Year Estimates, Table S0801; generated by CCRPC staff; using data.census.gov; (18 September 2024).; U.S. Census Bureau; American Community Survey, 2022 American Community Survey 1-Year Estimates, Table S0801; generated by CCRPC staff; using data.census.gov; (10 October 2023).; U.S. Census Bureau; American Community Survey, 2021 American Community Survey 1-Year Estimates, Table S0801; generated by CCRPC staff; using data.census.gov; (14 October 2022).; U.S. Census Bureau; American Community Survey, 2019 American Community Survey 1-Year Estimates, Table S0801; generated by CCRPC staff; using data.census.gov; (26 March 2021).; U.S. Census Bureau; American Community Survey, 2018 American Community Survey 1-Year Estimates, Table S0801; generated by CCRPC staff; using data.census.gov; (26 March 2021).; U.S. Census Bureau; American Community Survey, 2017 American Community Survey 1-Year Estimates, Table S0801; generated by CCRPC staff; using American FactFinder; (13 September 2018).; U.S. Census Bureau; American Community Survey, 2016 American Community Survey 1-Year Estimates, Table S0801; generated by CCRPC staff; using American FactFinder; (14 September 2017).; U.S. Census Bureau; American Community Survey, 2015 American Community Survey 1-Year Estimates, Table S0801; generated by CCRPC staff; using American FactFinder; (19 September 2016).; U.S. Census Bureau; American Community Survey, 2014 American Community Survey 1-Year Estimates, Table S0801; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2013 American Community Survey 1-Year Estimates, Table S0801; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2012 American Community Survey 1-Year Estimates, Table S0801; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2011 American Community Survey 1-Year Estimates, Table S0801; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2010 American Community Survey 1-Year Estimates, Table S0801; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2009 American Community Survey 1-Year Estimates, Table S0801; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2008 American Community Survey 1-Year Estimates, Table S0801; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2007 American Community Survey 1-Year Estimates, Table S0801; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2006 American Community Survey 1-Year Estimates, Table S0801; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2005 American Community Survey 1-Year Estimates, Table S0801; generated by CCRPC staff; using American FactFinder; (16 March 2016).

About this dataset

Context

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

Key observations

The largest age group in Sun, LA was for the group of age 30-34 years with a population of 73 (12.46%), according to the 2021 American Community Survey. At the same time, the smallest age group in Sun, LA was the 35-39 years with a population of 0 (0.00%). 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 Sun is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of Sun 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 Sun Population by Age. You can refer the same here

About this dataset

Context

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

Key observations

The largest age group in Colonial Beach, VA was for the group of age 70-74 years with a population of 487 (12.69%), according to the 2021 American Community Survey. At the same time, the smallest age group in Colonial Beach, VA was the 75-79 years with a population of 46 (1.20%). 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 Colonial Beach is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of Colonial Beach 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 Colonial Beach Population by Age. You can refer the same here

About this dataset

Context

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

Key observations

The largest age group in Sweet Home, OR was for the group of age 60-64 years with a population of 833 (8.57%), according to the 2021 American Community Survey. At the same time, the smallest age group in Sweet Home, OR was the 80-84 years with a population of 210 (2.16%). 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 Sweet Home is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of Sweet Home 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 Sweet Home Population by Age. You can refer the same here

About this dataset

Context

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

Key observations

The largest age group in Protection, KS was for the group of age 35-39 years with a population of 66 (14.73%), according to the 2021 American Community Survey. At the same time, the smallest age group in Protection, KS was the 25-29 years with a population of 0 (0.00%). 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 Protection is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of Protection 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 Protection Population by Age. You can refer the same here

U.S. Census Bureau QuickFacts statistics for Campbell city, California. QuickFacts data are derived from: Population Estimates, American Community Survey, Census of Population and Housing, Current Population Survey, Small Area Health Insurance Estimates, Small Area Income and Poverty Estimates, State and County Housing Unit Estimates, County Business Patterns, Nonemployer Statistics, Economic Census, Survey of Business Owners, Building Permits.