This dataset is a polygon coverage of counties limited to the extent of the Pond Creek coal bed resource areas and attributed with statistics on the thickness of the Pond Creek coal zone, its elevation, and overburden thickness, in feet. The file has been generalized from detailed geologic coverages found elsewhere in Professional Paper 1625-C.

This statistic displays the top uses of data in talent acquisition in 2017 according to hiring decision makers worldwide. During the survey period, ** percent of respondents stated that data can be used to predict the success of a candidate.

This folder contains 3 .csv files which contain all the observations for the suite of major ion and nutrient constituents for the Heart River Basin. These files contain the water-quality observations for the statistical summary tables in the report cited in this data release (Tatge and others, 2021).The allsiteinfo.table.csv file can be used to cross reference the sites with the main report (Tatge and others, 2021). Tatge, W.S., Nustad, R.A., and Galloway, J.M., 2021, Evaluation of Salinity and Nutrient Conditions in the Heart River Basin, North Dakota, 1970-2020: U.S. Geological Survey Scientific Investigations Report 2021-XXXX, XX p.

About this dataset

Context

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

Key observations

Largest age group (population): Male # 65-69 years (7) | Female # 60-64 years (11). 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 Toco population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Toco is shown in the following column.
• Population (Female): The female population in the Toco 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 Toco 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 Toco Population by Gender. You can refer the same here

IE: Adjusted Net Enrollment Rate: Primary: % of Primary School Age Children data was reported at 99.678 % in 2015. This records an increase from the previous number of 99.236 % for 2014. IE: Adjusted Net Enrollment Rate: Primary: % of Primary School Age Children data is updated yearly, averaging 94.999 % from Dec 1971 (Median) to 2015, with 42 observations. The data reached an all-time high of 99.942 % in 2007 and a record low of 84.722 % in 1986. IE: Adjusted Net Enrollment Rate: Primary: % of Primary School Age Children data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Ireland – Table IE.World Bank.WDI: Education Statistics. Adjusted net enrollment is the number of pupils of the school-age group for primary education, enrolled either in primary or secondary education, expressed as a percentage of the total population in that age group.; ; UNESCO Institute for Statistics; Weighted average; Each economy is classified based on the classification of World Bank Group's fiscal year 2018 (July 1, 2017-June 30, 2018).

KZ: Gender Parity Index (GPI): Secondary School Enrollment: Gross data was reported at 1.009 Ratio in 2017. This records a decrease from the previous number of 1.027 Ratio for 2016. KZ: Gender Parity Index (GPI): Secondary School Enrollment: Gross data is updated yearly, averaging 1.023 Ratio from Dec 1993 (Median) to 2017, with 14 observations. The data reached an all-time high of 1.134 Ratio in 1997 and a record low of 0.996 Ratio in 2006. KZ: Gender Parity Index (GPI): Secondary School Enrollment: Gross data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Kazakhstan – Table KZ.World Bank: Education Statistics. Gender parity index for gross enrollment ratio in secondary education is the ratio of girls to boys enrolled at secondary level in public and private schools.; ; UNESCO Institute for Statistics; Weighted average; Each economy is classified based on the classification of World Bank Group's fiscal year 2018 (July 1, 2017-June 30, 2018).

Discover Disney Animal Kingdom (US) like never before! Get up-to-date stats from June 2024, including waiting times or queue times for all attractions, to plan your route perfectly. Check real-time updates and regional weather data to stay prepared.

The Bath and North East Somerset Council has one of the largest databases in the world on the production and trade of minerals. The dataset contains annual production statistics by mass for more than 70 mineral commodities covering the majority of economically important and internationally-traded minerals, metals and mineral-based materials. For each commodity the annual production statistics are recorded for individual countries, grouped by continent. Import and export statistics are also available for years up to 2002. Maintenance of the database is funded by the Science Budget and output is used by government, private industry and others in support of policy, economic analysis and commercial strategy. As far as possible the production data are compiled from primary, official sources. Quality assurance is maintained by participation in such groups as the International Consultative Group on Non-ferrous Metal Statistics. Individual commodity and country tables are available for sale on request.

The revenue in the footwear market in France was modeled to stand at ************* U.S. dollars in 2024. Between 2018 and 2024, the revenue rose by *********** U.S. dollars, though the increase followed an uneven trajectory rather than a consistent upward trend. The revenue will steadily rise by ************ U.S. dollars over the period from 2024 to 2030, reflecting a clear upward trend.Further information about the methodology, more market segments, and metrics can be found on the dedicated Market Insights page on Footwear.

The statistic presents the leading financial data service companies in the United States in 2015, by revenue. In that year, Visa was ranked second with the revenue of approximately 13.88 billion U.S. dollars.

During the fourth quarter of 2024, data breaches exposed more than a million user data records in the United Kingdom (UK). The figure decreased significantly from nearly 41 million in the quarter prior. Overall, the time between the first quarter of 2022 and the fourth quarter of 2023, saw the lowest number of exposed user data accounts.

In 2024, the number of participants in tennis in the United States peaked at approximately ***** million, denoting an increase of ***** percent over the figure reported in the previous year. This continued the trend of steady growth in participation that started in 2020.

The Trends in International Mathematics and Science Study, 2015 (TIMSS 2015) is a data collection that is part of the Trends in International Mathematics and Science Study (TIMSS) program; program data are available since 1999 at . TIMSS 2015 (https://nces.ed.gov/timss/) is a cross-sectional study that provides international comparative information of the mathematics and science literacy of fourth-, eighth-, and twelfth-grade students and examines factors that may be associated with the acquisition of math and science literacy in students. The study was conducted using direct assessments of students and questionnaires for students, teachers, and school administrators. Fourth-, eighth-, and twelfth-graders in the 2014-15 school year were sampled. Key statistics produced from TIMSS 2015 provide reliable and timely data on the mathematics and science achievement of U.S. students compared to that of students in other countries. Data are expected to be released in 2018.

Demographic statistics of each township and city..

In 2021, 42 percent of healthcare organizations in the European Union were currently using AI technologies for disease diagnosis, while a further 19 percent had plans to employ this technology within the next 3 years. Furthermore, 33 percent of healthcare organizations surveyed planned to use patient monitoring AI tools in the next 3 years How much impact does AI have on saving time in healthcare? An online survey from several European countries concluded that the implementation of AI could free up significant portions of time in healthcare – with nearly half of the hours worked by medical equipment preparers and one-third of the hours of medical assistants. While, according to another survey, physicians in Europe could spend almost ** percent more time with patients instead of administrative tasks with the help of AI. The same held true for nurses, whose time with patients would increase by *** percent thanks to AI, according to estimates. Attitudes and opinions regarding AI in healthcare In 2021, a quarter of respondents surveyed in the European Union reported trusting AI-enabled decisions in patient monitoring, higher than any other AI applications. Meanwhile, only * percent trusted AI-enabled decisions in disease diagnostics, with the majority preferring to combine it with expert judgment from healthcare professionals. Overall, the opinions of EU respondents on the impact of AI in healthcare were positive, with the majority agreeing that the use of AI could result in improvement in the quality of diagnosis decisions and treatment

In 2023, it was estimated to be *** million mobile internet users in Latin America. The number is expected to increase to *** million by 2030. Meanwhile, smartphone penetration rate is projected to increase to ** percent in 2030.

Lebanon Imports from Vietnam of Commodities not specified according to kind was US$4.31 Thousand during 2021, according to the United Nations COMTRADE database on international trade. Lebanon Imports from Vietnam of Commodities not specified according to kind - data, historical chart and statistics - was last updated on August of 2025.

About this dataset

Context

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

Key observations

Largest age group (population): Male # 5-9 years (62) | Female # 50-54 years (83). 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 Van Buren population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Van Buren is shown in the following column.
• Population (Female): The female population in the Van Buren 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 Van Buren 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 Van Buren Population by Gender. You can refer the same here

Data for Figure 3.22 from Chapter 3 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6). Figure 3.22 shows time series of Northern Hemisphere March-April mean snow cover extent (SCE) from observations, CMIP5 and CMIP6 simulations. --------------------------------------------------- How to cite this dataset --------------------------------------------------- When citing this dataset, please include both the data citation below (under 'Citable as') and the following citation for the report component from which the figure originates: Eyring, V., N.P. Gillett, K.M. Achuta Rao, R. Barimalala, M. Barreiro Parrillo, N. Bellouin, C. Cassou, P.J. Durack, Y. Kosaka, S. McGregor, S. Min, O. Morgenstern, and Y. Sun, 2021: Human Influence on the Climate System. In Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Masson-Delmotte, V., P. Zhai, A. Pirani, S.L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M.I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J.B.R. Matthews, T.K. Maycock, T. Waterfield, O. Yelekçi, R. Yu, and B. Zhou (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, pp. 423–552, doi:10.1017/9781009157896.005. --------------------------------------------------- Figure subpanels --------------------------------------------------- There are technically two panels top and bottom (CMIP5 and CMIP6), however, the data is stored in the parent directory. --------------------------------------------------- List of data provided --------------------------------------------------- The data is for the Northern Hemisphere snow cover extent anomalies (SCEA) from models and observations: - The SCEA observational data from GLDAS-NOAH (1948-2012), Brown-NOAA (1923-2017), Mudryk et al 2020 (1968-2017) - The SCEA modelled by CMIP5 historical-rcp45 experiment (1923-2017) - The SCEA modelled by CMIP5 historicalNat experiment (1923-2012) - The SCEA modelled by CMIP6 historical-ssp245 experiment (1923-2017) - The SCEA modelled by CMIP6 hist-nat experiment (1923-2017) - The SCEA modelled by CMIP5 and CMIP6 piControl experiments --------------------------------------------------- Data provided in relation to figure --------------------------------------------------- snow_cover_extent_cmip5_obs.csv is the data for the green and brown lines and shadings in the upper panel and grey lines (1923-2017) snow_cover_extent_cmip6_obs.csv is the data for the green and brown lines and shadings in the lower panel and grey lines (1923-2017) snow_cover_extent_piControl.csv for the blue error bars in the both panels Additional details of data provided in relation to figure in the file header (BADC-CSV file) CMIP5 is the fifth phase of the Coupled Model Intercomparison Project. CMIP6 is the sixth phase of the Coupled Model Intercomparison Project. --------------------------------------------------- Sources of additional information --------------------------------------------------- The following weblinks are provided in the Related Documents section of this catalogue record: - Link to the report component containing the figure (Chapter 3) - Link to the Supplementary Material for Chapter 3, which contains details on the input data used in Table 3.SM.1 - Link to the code for the figure, archived on Zenodo.