About this dataset

Context

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

Key observations

The largest age group in East Side Township, Minnesota was for the group of age 60 to 64 years years with a population of 108 (16.49%), according to the ACS 2018-2022 5-Year Estimates. At the same time, the smallest age group in East Side Township, Minnesota was the 10 to 14 years years with a population of 9 (1.37%). 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 East Side township is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of East Side township 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 East Side township Population by Age. You can refer the same here

VITAL SIGNS INDICATOR Population (LU1)

FULL MEASURE NAME
Population estimates

LAST UPDATED
February 2023

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 SOURCE
California Department of Finance: Population and Housing Estimates - http://www.dof.ca.gov/Forecasting/Demographics/Estimates/
Table E-6: County Population Estimates (1960-1970)
Table E-4: Population Estimates for Counties and State (1970-2021)
Table E-8: Historical Population and Housing Estimates (1990-2010)
Table E-5: Population and Housing Estimates (2010-2021)

Bay Area Jurisdiction Centroids (2020) - https://data.bayareametro.gov/Boundaries/Bay-Area-Jurisdiction-Centroids-2020-/56ar-t6bs
Computed using 2020 US Census TIGER boundaries

U.S. Census Bureau: Decennial Census Population Estimates - http://www.s4.brown.edu/us2010/index.htm- via Longitudinal Tract Database Spatial Structures in the Social Sciences, Brown University
1970-2020

U.S. Census Bureau: American Community Survey (5-year rolling average; tract) - https://data.census.gov/
2011-2021
Form B01003

Priority Development Areas (Plan Bay Area 2050) - https://opendata.mtc.ca.gov/datasets/MTC::priority-development-areas-plan-bay-area-2050/about

CONTACT INFORMATION
vitalsigns.info@bayareametro.gov

METHODOLOGY NOTES (across all datasets for this indicator)
All historical data reported for Census geographies (metropolitan areas, county, city and tract) use current legal boundaries and names. 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 December 2022.

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 (1970-2020) and the American Community Survey (2011-2021 5-year rolling average). Estimates of population density for tracts use gross acres as the denominator.

Population estimates for Bay Area tracts and PDAs are from the decennial Census (1970-2020) and the American Community Survey (2011-2021 5-year rolling average). Population estimates for PDAs are allocated from tract-level Census population counts using an area ratio. For example, if a quarter of a Census tract lies with in a PDA, a quarter of its population will be allocated to that PDA. Estimates of population density for PDAs use gross acres as the denominator. Note that the population densities between PDAs reported in previous iterations of Vital Signs are mostly not comparable due to minor differences and an updated set of PDAs (previous iterations reported Plan Bay Area 2040 PDAs, whereas current iterations report Plan Bay Area 2050 PDAs).

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

About this dataset

Context

The dataset tabulates the East Side township Hispanic or Latino population. It includes the distribution of the Hispanic or Latino population, of East Side township, by their ancestries, as identified by the Census Bureau. The dataset can be utilized to understand the origin of the Hispanic or Latino population of East Side township.

Key observations

Among the Hispanic population in East Side township, regardless of the race, the largest group is of Other Hispanic or Latino origin, with a population of 5 (71.43% of the total Hispanic population).

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Origin for Hispanic or Latino population include:

• Mexican
• Puerto Rican
• Cuban
• Other Hispanic or Latino

Variables / Data Columns

• Origin: This column displays the origin for Hispanic or Latino population for the East Side township
• Population: The population of the specific origin for Hispanic or Latino population in the East Side township is shown in this column.
• % of Total Hispanic Population: This column displays the percentage distribution of each Hispanic origin as a proportion of East Side township total Hispanic or Latino 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 East Side township Population by Race & Ethnicity. You can refer the same here

Based on graph in "Orange roughy (Hoplostethus atlanticus) eastern zone stock assessment incorporating data up to 2014. Report to the Australian Fisheries Management Authority. CSIRO, Hobart". Data provided by AFMA / CSIRO, for more information see http://www.afma.gov.au/wp-content/uploads/2014/03/SESSF-CSIRO-Orange-Roughy-Eastern-Assessment-Final-2014.pdf\r \r Data used to produce figure MAR28, SoE2016. See;\r https://soe.environment.gov.au/theme/marine-environment/topic/2016/state-and-trends-marine-biodiversity-species-groups#figure-mar28-spawning-biomass-of-the-east-coast-population-of-orange-roughy-1980%E2%80%932015--118736

This dataset includes county population estimates for the total population through July 1, 2023 (Vintage 2023 population estimates) and the July 1, 2024 through July 1, 2060 population projections (Vintage 2024 Population Projections). The July 1, 2023 population estimates are the latest certified population estimates for counties. Regional identifiers are also provided in order to show changes for MSAs, broad regions (not official), and Councils of Governments regional planning areas.

In Tasmania, SCUBA surveys of seahorses populations were conducted. Intensive surveys were conducted in 2000 to 2004 in the Derwent River around Hobart (submonthly & then monthly) and twice yearly surveys from 2004/5 on east coast and Derwent River, until 2007. Mark-recapture studies were done to estimate population size, and life history parameters.

About this dataset

Context

The dataset tabulates the East Haddam town population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of East Haddam town across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2021, the population of East Haddam town was 8,965, a 0.52% increase year-by-year from 2020. Previously, in 2020, East Haddam town population was 8,919, a decline of 0.98% compared to a population of 9,007 in 2019. Over the last 20 plus years, between 2000 and 2021, population of East Haddam town increased by 581. In this period, the peak population was 9,180 in the year 2011. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).

https://i.neilsberg.com/ch/population-of-east-haddam-ct-population-by-year-2000-2021.jpeg" alt="East Haddam town population by year">

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2021

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2021)
• Population: The population for the specific year for the East Haddam town is shown in this column.
• Year on Year Change: This column displays the change in East Haddam town population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. 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 East Haddam town Population by Year. You can refer the same here

Greenland is the world’s largest island, located between the Arctic and Atlantic Oceans. Most of the country is covered by ice. It is the least densely populated country in the world. The population fluctuated slightly in the past few years. As of 2022, Greenland counted over 56,000 inhabitants. Among these, around 30,000 were men and roughly 27,000 were female inhabitants.

 Danish citizenship
Until 1953, Greenland was a Danish colony. It is still part of the Kingdom of Denmark but it has its own extensive local government and is not part of the European Union (unlike Denmark). Due to being part of Denmark, the vast majority of the inhabitants have Danish citizenship, amounting to approximately 55,000 in 2022.

Municipalities
Greenland is organized in five administrative divisions. The capital Nuuk is in Kommuneqarfik Sermersooq, a municipality stretching from the west to the east coast of Greenland. In 2022, nearly 23,000 inhabitants lived in this municipality, making this Greenland’s most populated municipality.

This dataset is about cities in South-Eastern Asia. It has 4,705 rows. It features 2 columns including population.

Ivory Coast CI: Population: as % of Total: Female: Aged 15-64 data was reported at 54.459 % in 2017. This records an increase from the previous number of 54.291 % for 2016. Ivory Coast CI: Population: as % of Total: Female: Aged 15-64 data is updated yearly, averaging 51.774 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 54.459 % in 2017 and a record low of 49.675 % in 1982. Ivory Coast CI: Population: as % of Total: Female: Aged 15-64 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Ivory Coast – Table CI.World Bank: Population and Urbanization Statistics. Female population between the ages 15 to 64 as a percentage of the total female population. Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship.; ; World Bank staff estimates based on age/sex distributions of United Nations Population Division's World Population Prospects: 2017 Revision.; Weighted average; Relevance to gender indicator: Knowing how many girls, adolescents and women there are in a population helps a country in determining its provision of services.

Ivory Coast CI: International Migrant Stock: % of Population data was reported at 9.583 % in 2015. This records a decrease from the previous number of 10.407 % for 2010. Ivory Coast CI: International Migrant Stock: % of Population data is updated yearly, averaging 11.581 % from Dec 1990 (Median) to 2015, with 6 observations. The data reached an all-time high of 14.930 % in 1990 and a record low of 9.583 % in 2015. Ivory Coast CI: International Migrant Stock: % of Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Ivory Coast – Table CI.World Bank: Population and Urbanization Statistics. International migrant stock is the number of people born in a country other than that in which they live. It also includes refugees. The data used to estimate the international migrant stock at a particular time are obtained mainly from population censuses. The estimates are derived from the data on foreign-born population--people who have residence in one country but were born in another country. When data on the foreign-born population are not available, data on foreign population--that is, people who are citizens of a country other than the country in which they reside--are used as estimates. After the breakup of the Soviet Union in 1991 people living in one of the newly independent countries who were born in another were classified as international migrants. Estimates of migrant stock in the newly independent states from 1990 on are based on the 1989 census of the Soviet Union. For countries with information on the international migrant stock for at least two points in time, interpolation or extrapolation was used to estimate the international migrant stock on July 1 of the reference years. For countries with only one observation, estimates for the reference years were derived using rates of change in the migrant stock in the years preceding or following the single observation available. A model was used to estimate migrants for countries that had no data.; ; United Nations Population Division, Trends in Total Migrant Stock: 2008 Revision.; Weighted average;

About this dataset

Context

The dataset tabulates the East Pittsburgh population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of East Pittsburgh across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2023, the population of East Pittsburgh was 1,855, a 1.17% decrease year-by-year from 2022. Previously, in 2022, East Pittsburgh population was 1,877, a decline of 1.37% compared to a population of 1,903 in 2021. Over the last 20 plus years, between 2000 and 2023, population of East Pittsburgh decreased by 210. In this period, the peak population was 2,065 in the year 2000. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2023

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2023)
• Population: The population for the specific year for the East Pittsburgh is shown in this column.
• Year on Year Change: This column displays the change in East Pittsburgh population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. 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 East Pittsburgh Population by Year. You can refer the same here

Ivory Coast CI: Net Migration data was reported at 30,000.000 Person in 2017. This records a decrease from the previous number of 60,000.000 Person for 2012. Ivory Coast CI: Net Migration data is updated yearly, averaging 200,000.000 Person from Dec 1962 (Median) to 2017, with 12 observations. The data reached an all-time high of 430,000.000 Person in 1982 and a record low of -370,000.000 Person in 2002. Ivory Coast CI: Net Migration data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Ivory Coast – Table CI.World Bank.WDI: Population and Urbanization Statistics. Net migration is the net total of migrants during the period, that is, the total number of immigrants less the annual number of emigrants, including both citizens and noncitizens. Data are five-year estimates.; ; United Nations Population Division. World Population Prospects: 2017 Revision.; Sum;

Population: FE: Amur Region: Blagoveschensk City: Non Working Age: Age 1 to 6 data was reported at 17.300 Person th in 2019. This records a decrease from the previous number of 17.600 Person th for 2018. Population: FE: Amur Region: Blagoveschensk City: Non Working Age: Age 1 to 6 data is updated yearly, averaging 14.600 Person th from Dec 2003 (Median) to 2019, with 17 observations. The data reached an all-time high of 17.600 Person th in 2018 and a record low of 11.200 Person th in 2003. Population: FE: Amur Region: Blagoveschensk City: Non Working Age: Age 1 to 6 data remains active status in CEIC and is reported by Federal State Statistics Service. The data is categorized under Russia Premium Database’s Demographic and Labour Market – Table RU.GA023: Population: by City: Far East Federal District.

Phylogeographic studies indicate that many marine invertebrates lacking autonomous dispersal ability are able to achieve trans-oceanic colonization by rafting on buoyant macroalgae. However, less is known about the impact of rafting on on-going population-genetic connectivity of intertidal species associated with buoyant macroalgae. We hypothesize that such species will have higher levels of population-genetic connectivity than those exploiting nonbuoyant substrates such as rock. We tested this hypothesis by comparing nuclear multilocus population-genetic structuring in two sister topshell species, which both have a planktonic larval phase but are fairly well segregated by their habitat preference of low-tidal bull-kelp holdfasts versus mid-to-low tidal bare rock. We analyzed population samples from four sympatric sites spanning 372 km of the east coast of southern New Zealand. The sampled region encompasses a 180 km wide habitat discontinuity and is influenced by a stable, northward coastal current. The level of connectivity was high in both species, and neither of them showed significant correlation between genetic and geographic distances. However, a significant negative partial correlation between genetic distance and habitat discontinuity was found in the rock-associated species, and estimates of migrant movement between sites were somewhat different between the two species, with the kelp-associated species more often yielding higher estimates across the habitat discontinuity, whereas the rock-associated species more often exhibited higher estimates between sites interspersed by rock habitats. We conclude that for species with substantial means of autonomous dispersal, the most conspicuous consequence of kelp dwelling may be enhanced long-distance dispersal across habitat discontinuities rather than a general increase of gene flow.

Population: FE: Khabarovsk Territory: Komsomolsk on Amur data was reported at 244.800 Person th in 2019. This records a decrease from the previous number of 246.600 Person th for 2018. Population: FE: Khabarovsk Territory: Komsomolsk on Amur data is updated yearly, averaging 269.800 Person th from Dec 1999 (Median) to 2019, with 21 observations. The data reached an all-time high of 292.500 Person th in 1999 and a record low of 244.800 Person th in 2019. Population: FE: Khabarovsk Territory: Komsomolsk on Amur data remains active status in CEIC and is reported by Federal State Statistics Service. The data is categorized under Russia Premium Database’s Demographic and Labour Market – Table RU.GA023: Population: by City: Far East Federal District.

In this coastal marten landscape connectivity modeling project, we produced a "primary" connectivity model in which modeled habitat cores and a resistance surface were input into Linkage Mapper to produce least-cost paths and corridors that connect habitat cores. We also produced a "secondary" connectivity model in which the habitat cores were replaced with polygons delineating the boundaries of the four extant population areas (USFWS 2018; Fig. 1 of report). This allowed us to examine whether there were additional areas that may represent potentially significant corridors that were not identified in the primary model. This dataset contains the least-cost paths produced by the secondary connectivity model in which extant population areas (EPAs) are used as habitat cores. To provide context on the connectivity modeling process, refer to the metadata record used to describe the development and output of Least-cost paths and corridors in our primary model. This description can be directly applied to the production of our secondary model as well, by replacing any mention of "habitat cores" with "EPAs". This is an abbreviated and incomplete description of the dataset. Please refer to the spatial metadata for a more thorough description of the methods used to produce this dataset, and a discussion of any assumptions or caveats that should be taken into consideration.

Population: SB: Republic of Buryatia: Ulan-Ude data was reported at 439.100 Person th in 2019. This records an increase from the previous number of 435.500 Person th for 2018. Population: SB: Republic of Buryatia: Ulan-Ude data is updated yearly, averaging 393.300 Person th from Dec 1992 (Median) to 2019, with 28 observations. The data reached an all-time high of 439.100 Person th in 2019 and a record low of 340.200 Person th in 2008. Population: SB: Republic of Buryatia: Ulan-Ude data remains active status in CEIC and is reported by Federal State Statistics Service. The data is categorized under Russia Premium Database’s Demographic and Labour Market – Table RU.GA023: Population: by City: Far East Federal District.

About this dataset

Context

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

Key observations

Largest age group (population): Male # 60-64 years (55) | Female # 60-64 years (53). 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

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 East Side township population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the East Side township is shown in the following column.
• Population (Female): The female population in the East Side township 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 East Side township 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 East Side township Population by Gender. You can refer the same here

About this dataset

Context

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

Key observations

The largest age group in East Washington, PA was for the group of age 20 to 24 years years with a population of 201 (12.12%), according to the ACS 2019-2023 5-Year Estimates. At the same time, the smallest age group in East Washington, PA was the 85 years and over years with a population of 19 (1.15%). 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 East Washington is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of East Washington 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 East Washington Population by Age. You can refer the same here