About this dataset

Context

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

Key observations

The largest age group in United States was for the group of age 25-29 years with a population of 22,854,328 (6.93%), according to the 2021 American Community Survey. At the same time, the smallest age group in United States was the 80-84 years with a population of 5,932,196 (1.80%). 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 United States is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of United States 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 United States Population by Age. You can refer the same here

In 2021, there were about **** million children under the age of 18 years old in California -- the most out of any state. In that same year, Texas, Florida, New York, and Illinois rounded out the top five states with the most children under 18.

About this dataset

Context

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

Key observations

The largest age group in North Norwich, New York was for the group of age 55-59 years with a population of 208 (12.90%), according to the 2021 American Community Survey. At the same time, the smallest age group in North Norwich, New York was the 80-84 years with a population of 25 (1.55%). 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 North Norwich town is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of North Norwich town 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 North Norwich town Population by Age. You can refer the same here

In 2021, children between the ages of zero and 17 years old made up 22.2 percent of the total population in the United States. This is down from a peak in 1960, where children made up 36 percent of the total population in the country.

About this dataset

Context

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

Key observations

The largest age group in New Market, MD was for the group of age 5-9 years with a population of 223 (13.95%), according to the 2021 American Community Survey. At the same time, the smallest age group in New Market, MD was the 80-84 years with a population of 7 (0.44%). 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 New Market is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of New Market 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 New Market Population by Age. You can refer the same here

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, it is the Census Bureau's Population Estimates Program that produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units for states and counties..Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Technical Documentation section.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, 2017-2021 American Community Survey 5-Year Estimates.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..The 2017-2021 American Community Survey (ACS) data generally reflect the March 2020 Office of Management and Budget (OMB) delineations of metropolitan and micropolitan statistical areas. In certain instances, the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB delineation lists due to differences in the effective dates of the geographic entities..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2010 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.

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, it is the Census Bureau's Population Estimates Program that produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units for states and counties..Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Technical Documentation section.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, 2017-2021 American Community Survey 5-Year Estimates.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..The age dependency ratio is derived by dividing the combined under-18 and 65-and-over populations by the 18-to-64 population and multiplying by 100..The old-age dependency ratio is derived by dividing the population 65 and over by the 18-to-64 population and multiplying by 100..The child dependency ratio is derived by dividing the population under 18 by the 18-to-64 population and multiplying by 100..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..The 2017-2021 American Community Survey (ACS) data generally reflect the March 2020 Office of Management and Budget (OMB) delineations of metropolitan and micropolitan statistical areas. In certain instances, the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB delineation lists due to differences in the effective dates of the geographic entities..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2010 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.

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, it is the Census Bureau's Population Estimates Program that produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units for states and counties..Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Technical Documentation section.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, 2021 American Community Survey 1-Year Estimates.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..The age dependency ratio is derived by dividing the combined under-18 and 65-and-over populations by the 18-to-64 population and multiplying by 100..The old-age dependency ratio is derived by dividing the population 65 and over by the 18-to-64 population and multiplying by 100..The child dependency ratio is derived by dividing the population under 18 by the 18-to-64 population and multiplying by 100..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..The 2021 American Community Survey (ACS) data generally reflect the March 2020 Office of Management and Budget (OMB) delineations of metropolitan and micropolitan statistical areas. In certain instances the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB delineations due to differences in the effective dates of the geographic entities..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2010 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.

In terms of population size, the sex ratio in the United States favors females, although the gender gap is remaining stable. In 2010, there were around 5.17 million more women, with the difference projected to decrease to around 3 million by 2027.

Gender ratios by U.S. state In the United States, the resident population was estimated to be around 331.89 million in 2021. The gender distribution of the nation has remained steady for several years, with women accounting for approximately 51.1 percent of the population since 2013. Females outnumbered males in the majority of states across the country in 2020, and there were eleven states where the gender ratio favored men.

Metro areas by population National differences between male and female populations can also be analyzed by metropolitan areas. In general, a metropolitan area is a region with a main city at its center and adjacent communities that are all connected by social and economic factors. The largest metro areas in the U.S. are New York, Los Angeles, and Chicago. In 2019, there were more women than men in all three of those areas, but Jackson, Missouri was the metro area with the highest share of female population.

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, it is the Census Bureau's Population Estimates Program that produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units for states and counties..Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Technical Documentation section.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, 2017-2021 American Community Survey 5-Year Estimates.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..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..The 2017-2021 American Community Survey (ACS) data generally reflect the March 2020 Office of Management and Budget (OMB) delineations of metropolitan and micropolitan statistical areas. In certain instances, the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB delineation lists due to differences in the effective dates of the geographic entities..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2010 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.

"Enrollment counts are based on the October 31 Audited Register for the 2017-18 to 2019-20 school years. To account for the delay in the start of the school year, enrollment counts are based on the November 13 Audited Register for 2020-21 and the November 12 Audited Register for 2021-22. * Please note that October 31 (and November 12-13) enrollment is not audited for charter schools or Pre-K Early Education Centers (NYCEECs). Charter schools are required to submit enrollment as of BEDS Day, the first Wednesday in October, to the New York State Department of Education." Enrollment counts in the Demographic Snapshot will likely exceed operational enrollment counts due to the fact that long-term absence (LTA) students are excluded for funding purposes. Data on students with disabilities, English Language Learners, students' povery status, and students' Economic Need Value are as of the June 30 for each school year except in 2021-22. Data on SWDs, ELLs, Poverty, and ENI in the 2021-22 school year are as of March 7, 2022. 3-K and Pre-K enrollment totals include students in both full-day and half-day programs. Four-year-old students enrolled in Family Childcare Centers are categorized as 3K students for the purposes of this report. All schools listed are as of the 2021-22 school year. Schools closed before 2021-22 are not included in the school level tab but are included in the data for citywide, borough, and district. Programs and Pre-K NYC Early Education Centers (NYCEECs) are not included on the school-level tab. Due to missing demographic information in rare cases at the time of the enrollment snapshot, demographic categories do not always add up to citywide totals. Students with disabilities are defined as any child receiving an Individualized Education Program (IEP) as of the end of the school year (or March 7 for 2021-22). NYC DOE "Poverty" counts are based on the number of students with families who have qualified for free or reduced price lunch, or are eligible for Human Resources Administration (HRA) benefits. In previous years, the poverty indicator also included students enrolled in a Universal Meal School (USM), where all students automatically qualified, with the exception of middle schools, D75 schools and Pre-K centers. In 2017-18, all students in NYC schools became eligible for free lunch. In order to better reflect free and reduced price lunch status, the poverty indicator does not include student USM status, and retroactively applies this rule to previous years. "The school’s Economic Need Index is the average of its students’ Economic Need Values. The Economic Need Index (ENI) estimates the percentage of students facing economic hardship. The 2014-15 school year is the first year we provide ENI estimates. The metric is calculated as follows: * The student’s Economic Need Value is 1.0 if: o The student is eligible for public assistance from the NYC Human Resources Administration (HRA); o The student lived in temporary housing in the past four years; or o The student is in high school, has a home language other than English, and entered the NYC DOE for the first time within the last four years. * Otherwise, the student’s Economic Need Value is based on the percentage of families (with school-age children) in the student’s census tract whose income is below the poverty level, as estimated by the American Community Survey 5-Year estimate (2020 ACS estimates were used in calculations for 2021-22 ENI). The student’s Economic Need Value equals this percentage divided by 100. Due to differences in the timing of when student demographic, address and census data were pulled, ENI values may vary, slightly, from the ENI values reported in the School Quality Reports. In previous years, student census tract data was based on students’ addresses at the time of ENI calculation. Beginning in 2018-19, census tract data is based on students’ addresses as of the Audited Register date of the g

About this dataset

Context

The dataset tabulates the population of United States by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for United States. The dataset can be utilized to understand the population distribution of United States by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in United States. 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 United States.

Key observations

Largest age group (population): Male # 25-29 years (11.59 million) | Female # 25-29 years (11.26 million). 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 United States population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the United States is shown in the following column.
• Population (Female): The female population in the United States 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 United States 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 United States Population by Gender. You can refer the same here

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, it is the Census Bureau's Population Estimates Program that produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units for states and counties..Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Technical Documentation section.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, 2017-2021 American Community Survey 5-Year Estimates.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..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..The 2017-2021 American Community Survey (ACS) data generally reflect the March 2020 Office of Management and Budget (OMB) delineations of metropolitan and micropolitan statistical areas. In certain instances, the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB delineation lists due to differences in the effective dates of the geographic entities..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2010 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.

The estimated population of the U.S. was approximately 334.9 million in 2023, and the largest age group was adults aged 30 to 34. There were 11.88 million males in this age category and around 11.64 million females. Which U.S. state has the largest population? The population of the United States continues to increase, and the country is the third most populous in the world behind China and India. The gender distribution has remained consistent for many years, with the number of females narrowly outnumbering males. In terms of where the residents are located, California was the state with the highest population in 2023. The U.S. population by race and ethnicity The United States is well known the world over for having a diverse population. In 2023, the number of Black or African American individuals was estimated to be 45.76 million, which represented an increase of over four million since the 2010 census. The number of Asian residents has increased at a similar rate during the same time period and the Hispanic population in the U.S. has also continued to grow.

About this dataset

Context

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

Key observations

The largest age group in Brownstown, IN was for the group of age 70-74 years with a population of 384 (12.77%), according to the 2021 American Community Survey. At the same time, the smallest age group in Brownstown, IN was the 80-84 years with a population of 82 (2.73%). 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 Brownstown is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of Brownstown 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 Brownstown Population by Age. You can refer the same here

This statistic depicts the age distribution in the United States from 2014 to 2024. In 2024, about 17.32 percent of the U.S. population fell into the 0-14 year category, 64.75 percent into the 15-64 age group and 17.93 percent of the population were over 65 years of age. The increasing population of the United States The United States of America is one of the most populated countries in the world, trailing just behind China and India. A total population count of around 320 million inhabitants and a more-or-less steady population growth over the past decade indicate that the country has steadily improved its living conditions and standards for the population. Leading healthier lifestyles and improved living conditions have resulted in a steady increase of the life expectancy at birth in the United States. Life expectancies of men and women at birth in the United States were at a record high in 2012. Furthermore, a constant fertility rate in recent years and a decrease in the death rate and infant mortality, all due to the improved standard of living and health care conditions, have helped not only the American population to increase but as a result, the share of the population younger than 15 and older than 65 years has also increased in recent years, as can be seen above.

About this dataset

Context

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

Key observations

The largest age group in Luxemburg, WI was for the group of age 5-9 years with a population of 276 (10.44%), according to the 2021 American Community Survey. At the same time, the smallest age group in Luxemburg, WI was the 85+ years with a population of 31 (1.17%). 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 Luxemburg is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of Luxemburg 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 Luxemburg Population by Age. You can refer the same here

About this dataset

Context

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

Key observations

The largest age group in Media, PA was for the group of age 30-34 years with a population of 717 (12.29%), according to the 2021 American Community Survey. At the same time, the smallest age group in Media, PA was the 75-79 years with a population of 120 (2.06%). 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 Media is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of Media 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 Media Population by Age. You can refer the same here

In 2023, the median age of the population of the United States was 39.2 years. While this may seem quite young, the median age in 1960 was even younger, at 29.5 years. The aging population in the United States means that society is going to have to find a way to adapt to the larger numbers of older people. Everything from Social Security to employment to the age of retirement will have to change if the population is expected to age more while having fewer children. The world is getting older It’s not only the United States that is facing this particular demographic dilemma. In 1950, the global median age was 23.6 years. This number is projected to increase to 41.9 years by the year 2100. This means that not only the U.S., but the rest of the world will also have to find ways to adapt to the aging population.

The statistic shows the total population in the United States from 2015 to 2021, with projections up until 2027. In 2021, the total population of the U.S. amounted to approximately 332.18 million inhabitants.

The United States' economy over the last decade

The United States of America is the world’s largest national economy and the second most prominent trader globally, trailing just behind China. The country is also one of the most populated countries in the world, trailing only China and India. The United States' economy prospers primarily due to having a plentiful amount of natural resources and advanced infrastructure to cope with the production of goods and services, as well as the population and workforce to enable high productivity. Efficient productivity led to a slight growth in GDP almost every year over the past decade, despite undergoing several economic hardships towards the late 2000's.

In addition, the United States holds arguably one of the most important financial markets, with the majority of countries around the world having commercial connections with American companies. Dependency on a single market like the United States has however caused several global dilemmas, most evidently seen during the 2008 financial crisis. What initially started off as a bursting of the U.S. housing bubble lead to a worldwide recession and the necessity to reform national economics. The global financial crisis affected the United States most drastically, especially within the unemployment market as well as national debt, which continued to rise due to the United States having to borrow money in order to stimulate its economy.