This is a dataset used for the online stats training website (https://www.rensvandeschoot.com/tutorials/) and is based on the data used by van de Schoot, van der Velden, Boom, and Brugman (2010).

The dataset is based on a study that investigates an association between popularity status and antisocial behavior from at-risk adolescents (n = 1491), where gender and ethnic background are moderators under the association. The study distinguished subgroups within the popular status group in terms of overt and covert antisocial behavior.For more information on the sample, instruments, methodology, and research context, we refer the interested readers to van de Schoot, van der Velden, Boom, and Brugman (2010).

Variable name Description

Respnr = Respondents’ number

Dutch = Respondents’ ethnic background (0 = Dutch origin, 1 = non-Dutch origin)

gender = Respondents’ gender (0 = boys, 1 = girls)

sd = Adolescents’ socially desirable answering patterns

covert = Covert antisocial behavior

overt = Overt antisocial behavior

Graph and download economic data for All Employees: Retail Trade: General Merchandise Stores in Delaware (SMU10000004245200001SA) from Jan 1990 to Dec 2022 about DE, retail trade, sales, retail, employment, and USA.

Graph and download economic data for Employed Persons in Delaware (LASST100000000000005) from Jan 1976 to Apr 2025 about DE, household survey, employment, persons, and USA.

The total amount of data created, captured, copied, and consumed globally is forecast to increase rapidly, reaching *** zettabytes in 2024. Over the next five years up to 2028, global data creation is projected to grow to more than *** zettabytes. In 2020, the amount of data created and replicated reached a new high. The growth was higher than previously expected, caused by the increased demand due to the COVID-19 pandemic, as more people worked and learned from home and used home entertainment options more often. Storage capacity also growing Only a small percentage of this newly created data is kept though, as just * percent of the data produced and consumed in 2020 was saved and retained into 2021. In line with the strong growth of the data volume, the installed base of storage capacity is forecast to increase, growing at a compound annual growth rate of **** percent over the forecast period from 2020 to 2025. In 2020, the installed base of storage capacity reached *** zettabytes.

Obtener información sobre transmisión de derechos de la propiedadVariables de estudio: Número de transmisiones de derechos de la propiedad sobre fincas rústicas y urbanasLa url de acceso se dirige al menú de la operación desde donde se pueden visualizar como html y descargar las diferentes tablas que componen la publicación. La descarga se puede realizar en formato pc-axis, excel y CSV

Hydrographic and Impairment Statistics (HIS) is a National Park Service (NPS) Water Resources Division (WRD) project established to track certain goals created in response to the Government Performance and Results Act of 1993 (GPRA). One water resources management goal established by the Department of the Interior under GRPA requires NPS to track the percent of its managed surface waters that are meeting Clean Water Act (CWA) water quality standards. This goal requires an accurate inventory that spatially quantifies the surface water hydrography that each bureau manages and a procedure to determine and track which waterbodies are or are not meeting water quality standards as outlined by Section 303(d) of the CWA. This project helps meet this DOI GRPA goal by inventorying and monitoring in a geographic information system for the NPS: (1) CWA 303(d) quality impaired waters and causes; and (2) hydrographic statistics based on the United States Geological Survey (USGS) National Hydrography Dataset (NHD). Hydrographic and 303(d) impairment statistics were evaluated based on a combination of 1:24,000 (NHD) and finer scale data (frequently provided by state GIS layers).

This statistic shows the number of logged-in Reddit users in the United States from 2017 to 2025. In 2020, it was reported that ** million users accessed their account on the social news aggregation website. This figure is projected to rise to ** million users in 2025.

About this dataset

Context

The dataset tabulates the population of Hartly by gender, including both male and female populations. This dataset can be utilized to understand the population distribution of Hartly across both sexes and to determine which sex constitutes the majority.

Key observations

There is a considerable majority of male population, with 69.38% of total population being male. 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.

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. No further analysis is done on the data reported from the Census Bureau.

Variables / Data Columns

• Gender: This column displays the Gender (Male / Female)
• Population: The population of the gender in the Hartly is shown in this column.
• % of Total Population: This column displays the percentage distribution of each gender as a proportion of Hartly 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 Hartly Population by Race & Ethnicity. You can refer the same here

Financial overview and grant giving statistics of Delaware Statewide Programs Association

Contains csv data of cell features used for the analysis in the publication: "A novel MYH9 variant leads to atypical Epstein-Fechtner syndrome by altering non-muscle myosin IIA mediated contractile processes". These csv files contain call relevant cell features per patient and cell type. Files should be titled: For controls: + + .csv For patients: + + + + .csv Metadata containing sex and age is also available in files: “controls_metadata.csv” and “patients_metadata.csv” Summary statistic is also included in this public dataset. For controls: “controls_summary_statistics.csv” For patients: “patients_summary_statistics.csv” Summary statistic files are created using publicly available code: code: https://github.com/SaraKaliman/dc-data-novel-MYH9-variant/blob/main/Step1_summary_statistics.ipynb Group analysis included t-test, U-test and effect size for t-test and can be found in the file: “summary_statistical_group_analysis.csv” file. Main figure in the article and statistical analysis are done using publicly available code: https://github.com/SaraKaliman/dc-data-novel-MYH9-variant/blob/main/Step2_group_comparison.ipynb Single scalar rtdc files is included only due to limitation of DCOR datasets to rtdc files.

About this dataset

Context

The dataset tabulates the population of Selbyville by gender, including both male and female populations. This dataset can be utilized to understand the population distribution of Selbyville across both sexes and to determine which sex constitutes the majority.

Key observations

There is a slight majority of male population, with 50.45% of total population being male. 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.

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. No further analysis is done on the data reported from the Census Bureau.

Variables / Data Columns

• Gender: This column displays the Gender (Male / Female)
• Population: The population of the gender in the Selbyville is shown in this column.
• % of Total Population: This column displays the percentage distribution of each gender as a proportion of Selbyville 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 Selbyville Population by Race & Ethnicity. You can refer the same here

Data from various sources are updated in the Statistical Information System of the City of Cologne. The annual statistical yearbook publishes these in tabular, graphic and cartographic form at the level of the city districts and districts. Furthermore, definitions and calculation bases are explained. Small-scale statistics at the level of the 86 districts can be obtained from the Cologne district information become. All levels of the local area structure are presented in this publication explained.

This statistical data catalogue supplements the range of small-scale data. Selected structural data can be called up here in compact tabular form at the level of the 570 statistical districts or the 86 districts. The two overviews provide information about which data is available and from which source it originates. The data itself is provided annually.

Notes:

• Data sources are indicated in the summary tables. When using the data, the data license Germany - attribution - version 2.0 must be observed.
• Some values ​​cannot be given to protect statistical confidentiality. For the data sets of the Federal Employment Agency, these are values ​​from 1 to < 10, for all further data records values ​​from 1 to < 5. This is marked in the data by a * .
• The differentiation of population figures by gender is currently made according to female and male residents. The case numbers of those who define themselves as non-binary/diverse are so low at a small-scale level that they cannot be reported for reasons of statistical confidentiality.
• The determination of residents with a migration background is carried out by combination various characteristics from the resident registration procedure. The data are to be interpreted as estimates. The statistical yearbook of the city of Cologne provides further details.
• The information on households comes from the household generation process. This is a statistical procedure in which residents within an address are assigned to a household as far as possible by querying certain criteria. If the procedure does not identify any connections, the allocation to single-person households takes place. The statistical yearbook of the city of Cologne provides further details.
• The data set pupils* at general schools (spatial location by place of residence) is available from 2013.
• The number of the statistical quarter or district is a spatial location and can be linked to the geodata (see related resource below).

Germany DE: Educational Attainment: Doctoral or Equivalent: Population 25+ Years: Female: % Cumulative data was reported at 1.264 % in 2022. This records an increase from the previous number of 1.189 % for 2021. Germany DE: Educational Attainment: Doctoral or Equivalent: Population 25+ Years: Female: % Cumulative data is updated yearly, averaging 0.840 % from Dec 2010 (Median) to 2022, with 13 observations. The data reached an all-time high of 1.264 % in 2022 and a record low of 0.000 % in 2013. Germany DE: Educational Attainment: Doctoral or Equivalent: Population 25+ Years: Female: % Cumulative data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Germany – Table DE.World Bank.WDI: Social: Education Statistics. The percentage of population ages 25 and over that attained or completed Doctoral or equivalent.;UNESCO Institute for Statistics (UIS). UIS.Stat Bulk Data Download Service. Accessed April 5, 2025. https://apiportal.uis.unesco.org/bdds.;;

Statistics on GTAA and Wikidata

Yearly and monthly growth charts for sports betting in Delaware , including handle, revenue, and growth metrics

Germany DE: Educational Attainment: At Least Completed Primary: Population 25+ Years: Total: % Cumulative data was reported at 98.997 % in 2022. This records a decrease from the previous number of 99.002 % for 2021. Germany DE: Educational Attainment: At Least Completed Primary: Population 25+ Years: Total: % Cumulative data is updated yearly, averaging 100.000 % from Dec 2004 (Median) to 2022, with 19 observations. The data reached an all-time high of 100.000 % in 2020 and a record low of 98.997 % in 2022. Germany DE: Educational Attainment: At Least Completed Primary: Population 25+ Years: Total: % Cumulative data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Germany – Table DE.World Bank.WDI: Social: Education Statistics. The percentage of population ages 25 and over that attained or completed primary education.;UNESCO Institute for Statistics (UIS). UIS.Stat Bulk Data Download Service. Accessed April 5, 2025. https://apiportal.uis.unesco.org/bdds.;;

Germany DE: Primary Education: Pupils data was reported at 3,078,700.000 Person in 2022. This records an increase from the previous number of 3,038,181.000 Person for 2021. Germany DE: Primary Education: Pupils data is updated yearly, averaging 3,304,561.500 Person from Dec 1991 (Median) to 2022, with 32 observations. The data reached an all-time high of 3,865,724.000 Person in 1998 and a record low of 2,862,690.000 Person in 2014. Germany DE: Primary Education: Pupils data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Germany – Table DE.World Bank.WDI: Social: Education Statistics. Primary education pupils is the total number of pupils enrolled at primary level in public and private schools.;UNESCO Institute for Statistics (UIS). UIS.Stat Bulk Data Download Service. Accessed April 5, 2025. https://apiportal.uis.unesco.org/bdds.;Sum;

Germany DE: Educational Attainment: At Least Completed Lower Secondary: Population 25+ Years: Male: % Cumulative data was reported at 94.346 % in 2022. This records an increase from the previous number of 93.938 % for 2021. Germany DE: Educational Attainment: At Least Completed Lower Secondary: Population 25+ Years: Male: % Cumulative data is updated yearly, averaging 97.010 % from Dec 2004 (Median) to 2022, with 19 observations. The data reached an all-time high of 97.960 % in 2004 and a record low of 93.938 % in 2021. Germany DE: Educational Attainment: At Least Completed Lower Secondary: Population 25+ Years: Male: % Cumulative data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Germany – Table DE.World Bank.WDI: Social: Education Statistics. The percentage of population ages 25 and over that attained or completed lower secondary education.;UNESCO Institute for Statistics (UIS). UIS.Stat Bulk Data Download Service. Accessed April 5, 2025. https://apiportal.uis.unesco.org/bdds.;;

The statistic shows the sales value of Mexican food at grocery stores during the week of Cinco de Mayo in the United States in 2016. In the week ending May 7, 2016, tortilla chip sales generated approximately ** million U.S. dollars.

Analysis of ‘Access statistics from moers.de for May 2013 ’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from http://data.europa.eu/88u/dataset/33cdca92-c9c8-4823-9c1f-785f5ae25941 on 16 January 2022.

--- Dataset description provided by original source is as follows ---

The Zip file contains the following CSV files:

• Visitors per year_1.csv
• Visitors per month — individual period_1.csv
• Visitors per month_1.csv
• Visitors per hour_1.csv
• Visitors per day_1.csv
• Visitors_1.csv
• Browser main versions by operating system_1.csv
• Browser by operating system subversions_1.csv
• Browser subversions_1.csv
• Access pages_1.csv
• Statement of origin_1.csv
• Use per domain_1.csv
• PAGE Impression per page_1.csv
• Search word statistics Phrasen by search engine_1.csv
• Search word statistics Phrasen_1.csv
• Search word statistics words_1.csv

--- Original source retains full ownership of the source dataset ---