About this dataset

Context

The dataset tabulates the Au Train township population by year. The dataset can be utilized to understand the population trend of Au Train township.

Content

The dataset constitues the following datasets

• Au Train Township, Michigan Population Dataset: Yearly Figures, Population Change, and Percent Change Analysis

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/.

About this dataset

Context

The dataset tabulates the Au Train township Hispanic or Latino population. It includes the distribution of the Hispanic or Latino population, of Au Train 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 Au Train township.

Key observations

Among the Hispanic population in Au Train township, regardless of the race, the largest group is of Mexican origin, with a population of 27 (79.41% 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 Au Train township
• Population: The population of the specific origin for Hispanic or Latino population in the Au Train township is shown in this column.
• % of Total Hispanic Population: This column displays the percentage distribution of each Hispanic origin as a proportion of Au Train 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 Au Train township Population by Race & Ethnicity. You can refer the same here

Comprehensive population and demographic data for Tain (149) Village

About this dataset

Context

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

Key observations

Largest age group (population): Male # 60-64 years (63) | Female # 60-64 years (102). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

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

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Scope of gender :

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

Variables / Data Columns

• Age Group: This column displays the age group for the Au Train township population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Au Train township is shown in the following column.
• Population (Female): The female population in the Au Train 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 Au Train 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 Au Train township Population by Gender. You can refer the same here

About this dataset

Context

The dataset tabulates the Au Train township population by age cohorts (Children: Under 18 years; Working population: 18-64 years; Senior population: 65 years or more). It lists the population in each age cohort group along with its percentage relative to the total population of Au Train township. The dataset can be utilized to understand the population distribution across children, working population and senior population for dependency ratio, housing requirements, ageing, migration patterns etc.

Key observations

The largest age group was 18 to 64 years with a poulation of 685 (58.90% of the total population). 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 cohorts:

• Under 18 years
• 18 to 64 years
• 65 years and over

Variables / Data Columns

• Age Group: This column displays the age cohort for the Au Train township population analysis. Total expected values are 3 groups ( Children, Working Population and Senior Population).
• Population: The population for the age cohort in Au Train township is shown in the following column.
• Percent of Total Population: The population as a percent of total population of the Au Train township is shown in the following column.

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 Au Train township Population by Age. You can refer the same here

Abstract

The Kintampo north and south districts (previously simply referred to as the Kintampo district) are two of the 19 districts currently in the Brong Ahafo Region of Ghana. The Kintampo HDSS area (constituting of Kintampo North Municipality and Kintampo south district), has a surface area of 7,162 square kilometers. It is bounded to the north by the Black Volta, west by the Wenchi and Tain districts, in the East by the Atebubu District and to the south by Techiman and south-east by the Nkoranza north and south districts respectively.

The main indigenous ethnic groups are of the Bono, and the Mo origin. There is however a large permanent immigrant population from the northern Regions of Ghana (Dagarbas, Dagombas and Konkombas) who are mostly farmers. A few Dangbes and Ewes who are mainly fishermen are settled along the banks of the Black Volta. Settlements are mainly concentrated along the main trunk road linking the district capitals (Kintampo/Jema) to northern Region. There are 24 public health facilities made up of 15 Community-based Health Planning and Services (CHPS) compounds, 7 health centre and 2 hospitals. The hospitals are located at the district capitals. In the private sector, there are 3 private clinics and 3 private maternity homes In April 2010, The Kintampo HDSS established a satellite HDSS (Ahafo Mining Area Health and Demographic Surveillance System, AMAHDSS) in Tano North and Asutifi Districts of the Newmont Ghana Gold mining concession area. It is to monitor population and health dynamics in a mining area. It is the first HDSS in a mining area.

Geographic coverage

The Kintampo north and south districts (previously simply referred to as the Kintampo district) are two of the 19 districts currently in the Brong Ahafo Region of Ghana. The Kintampo HDSS area (constituting of Kintampo North Municipality and Kintampo south district), has a surface area of 7,162 square kilometers. It is bounded to the north by the Black Volta, west by the Wenchi and Tain districts, in the East by the Atebubu District and to the south by Techiman and south-east by the Nkoranza north and south districts respectively.

Analysis unit

Individual

Universe

The survey covered all resident population

Kind of data

Event history data

Frequency of data collection

Round 1 to Round 12: 2 times a year Round 13 to Round 22: 3 times a year

Sampling procedure

This dataset is not based on a sample, but contains information from the complete demographic surveillance area.

Sampling deviation

Not Applicable

Mode of data collection

Proxy Respondent [proxy]

Response rate

Response rate is 99% on an average over the years in all rounds

Sampling error estimates

Not Applicable

Data appraisal

CentreId MetricTable QMetric Illegal Legal Total Metric RunDate GH021 MicroDataCleaned Starts 254483 2017-05-17 12:26
GH021 MicroDataCleaned Transitions 0 700506 700506 0 2017-05-17 12:26
GH021 MicroDataCleaned Ends 254483 2017-05-17 12:26
GH021 MicroDataCleaned SexValues 32 700474 700506 0 2017-05-17 12:27
GH021 MicroDataCleaned DoBValues 32 700474 700506 0 2017-05-17 12:27

Tain. name, office head of government, Mayor, image, Area, date founded, Elevation, Country, administrative division, continent, latitude, waterbody, longitude, Website, population, Demonym

This statistics illustrates the share of population that intend to travel by train after the coronavirus lockdown in Spain in May 2020. As of that date, over half of the surveyed population believed that they would not use railway travel unless the health crisis is officially over. Approximately 30 percent of those surveyed stated they will not travel by train until there is a vaccine against COVID-19.

Demographic characteristics of the patients enrolled.

1. Total length of railways worldwide exceeds 1 million kilometres and recent railway development directly impacts wildlife because of animal-train collisions. Few studies, however, have analysed factors driving ungulate-train collisions. 2. We analysed over 3500 ungulate-train collisions including roe deer, red deer, wild boar, and moose collected in 2012-2015 in Poland. We compared train traffic characteristics (e.g. traffic intensity, speed, rail curvature), land-use and habitat characteristics (e.g. share of forests and build-up areas) and local ungulate population densities at collision sites and random sites distributed along the rail network. 3. Forest coverage generally increased, while urban areas decreased ungulate collision risk. Local density of ungulate species was strongly positively related to the relative collision risk in all four ungulate species, but above certain densities, the risk levelled off for all four species. 4. Train speed and train traffic intensity were positively associated with elevated collision risk in all four species, but the latter in a non-linear manner reached an asymptote at the level of ca. 10 trains per day. Rail curvature also increased probability of collisions with roe deer and red deer and possibly also wild boar. 5. Mortality rate of ungulates on railways in Poland is estimated to be 0.13-0.42% of annual hunting bags of studied species assuming that only one individual is killed at each occasion and ignoring undetected collisions. These values are expected to increase in near future due to increasing train speed in Central European countries. 6. Synthesis and applications. Ungulate-train collisions spots are characterised by surrounding forest, rail curvature, high train speed, and a moderate to high train traffic intensity. To reduce collision risk in a cost-effective way, we suggest to prioritise mitigation actions at sections of the railway characterized by those factors, e.g. by fencing and various warning devices. Due to nonlinear correlation between collision risk and population density, reducing density of ungulates will most likely reduce collision risk only marginally, and only in regions of low population densities where collision risk is relatively low anyway.

Around 44 percent of Germans never travel by long-distance train, while 40 percent of the population do travel by long-distance train but less than once per month. A small proportion of the population of 0.9 percent use long-distance trains daily.

There were 11.86 million people who participated in pilates training in the United States in 2023, denoting an increase of 15 percent versus the previous year. This marked the highest annual figure for pilates participants in the U.S. since 2010.

About this dataset

Context

The dataset tabulates the Au Train township population by race and ethnicity. The dataset can be utilized to understand the racial distribution of Au Train township.

Content

The dataset will have the following datasets when applicable

Please note that in case when either of Hispanic or Non-Hispanic population doesnt exist, the respective dataset will not be available (as there will not be a population subset applicable for the same)

• Au Train Township, Michigan Population Breakdown by Race
• Au Train Township, Michigan Non-Hispanic Population Breakdown by Race
• Au Train Township, Michigan Hispanic or Latino Population Distribution by Their Ancestries

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/.

Deficit of functional clinical refractionists required in Kenya based on different practitioner–population ratios.

Cette statistique représente une répartition des villes desservies par le service train apte à grande vitesse (TAGV) en France en 2016, selon la population. On peut y constater, qu'entre le 13 décembre 2015 et le 10 décembre 2016, les villes ayant une population supérieure à 50.000 habitants représentaient 32 % du total des villes qui ont été desservie par le train apte à grande vitesse en France.

About this dataset

Context

The dataset presents the median household incomes over the past decade across various racial categories identified by the U.S. Census Bureau in Au Train township. It portrays the median household income of the head of household across racial categories (excluding ethnicity) as identified by the Census Bureau. It also showcases the annual income trends, between 2013 and 2023, providing insights into the economic shifts within diverse racial communities.The dataset can be utilized to gain insights into income disparities and variations across racial categories, aiding in data analysis and decision-making..

Key observations

• White: In Au Train township, the median household income for the households where the householder is White increased by $14,977(28.63%), between 2013 and 2023. The median household income, in 2023 inflation-adjusted dollars, was $52,315 in 2013 and $67,292 in 2023.
• Black or African American: As per the U.S. Census Bureau population data, in Au Train township, there are no households where the householder is Black or African American; hence, the median household income for the Black or African American population is not applicable.
• Refer to the research insights for more key observations on American Indian and Alaska Native, Asian, Native Hawaiian and Other Pacific Islander, Some other race and Two or more races (multiracial) households

Content

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

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race of the head of household: This column presents the self-identified race of the household head, encompassing all relevant racial categories (excluding ethnicity) applicable in Au Train township.
• 2010: 2010 median household income
• 2011: 2011 median household income
• 2012: 2012 median household income
• 2013: 2013 median household income
• 2014: 2014 median household income
• 2015: 2015 median household income
• 2016: 2016 median household income
• 2017: 2017 median household income
• 2018: 2018 median household income
• 2019: 2019 median household income
• 2020: 2020 median household income
• 2021: 2021 median household income
• 2022: 2022 median household income
• 2023: 2023 median household income
• Please note: All incomes have been adjusted for inflation and are presented in 2023-inflation-adjusted dollars.

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 Au Train township median household income by race. You can refer the same here

About this dataset

Context

The dataset presents the the household distribution across 16 income brackets among four distinct age groups in Au Train township: Under 25 years, 25-44 years, 45-64 years, and over 65 years. The dataset highlights the variation in household income, offering valuable insights into economic trends and disparities within different age categories, aiding in data analysis and decision-making..

Key observations

• Upon closer examination of the distribution of households among age brackets, it reveals that there are 0 households where the householder is under 25 years old, 90(21.74%) households with a householder aged between 25 and 44 years, 171(41.30%) households with a householder aged between 45 and 64 years, and 153(36.96%) households where the householder is over 65 years old.
• The age group of 25 to 44 years exhibits the highest median household income, while the largest number of households falls within the 45 to 64 years bracket. This distribution hints at economic disparities within the township of Au Train township, showcasing varying income levels among different age demographics.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.

Income brackets:

• Less than $10,000
• $10,000 to $14,999
• $15,000 to $19,999
• $20,000 to $24,999
• $25,000 to $29,999
• $30,000 to $34,999
• $35,000 to $39,999
• $40,000 to $44,999
• $45,000 to $49,999
• $50,000 to $59,999
• $60,000 to $74,999
• $75,000 to $99,999
• $100,000 to $124,999
• $125,000 to $149,999
• $150,000 to $199,999
• $200,000 or more

Variables / Data Columns

• Household Income: This column showcases 16 income brackets ranging from Under $10,000 to $200,000+ ( As mentioned above).
• Under 25 years: The count of households led by a head of household under 25 years old with income within a specified income bracket.
• 25 to 44 years: The count of households led by a head of household 25 to 44 years old with income within a specified income bracket.
• 45 to 64 years: The count of households led by a head of household 45 to 64 years old with income within a specified income bracket.
• 65 years and over: The count of households led by a head of household 65 years and over old with income within a specified income bracket.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Au Train township median household income by age. You can refer the same here