Understanding Society, (UK Household Longitudinal Study), which began in 2009, is conducted by the Institute for Social and Economic Research (ISER) at the University of Essex and the survey research organisations Verian Group (formerly Kantar Public) and NatCen. It builds on and incorporates, the British Household Panel Survey (BHPS), which began in 1991.

Understanding Society (UK Household Longitudinal Study), which began in 2009, is conducted by the Institute for Social and Economic Research (ISER) at the University of Essex and the survey research organisations Kantar Public and NatCen. It builds on and incorporates, the British Household Panel Survey (BHPS), which began in 1991.

The Understanding Society COVID-19 Study, 2020-2021 is a regular survey of households in the UK. The aim of the study is to enable research on the socio-economic and health consequences of the COVID-19 pandemic, in the short and long term. The surveys started in April 2020 and took place monthly until July 2020. From September 2020 they took place every other month until March 2021 and the final wave was fielded in September 2021. They complement the annual interviews of the Understanding Society study. The data can be linked to data on the same individuals from previous waves of the annual interviews (SN 6614) using the personal identifier pidp. However, the most recent pre-pandemic (2019) annual interviews for all respondents who have taken part in the COVID-19 Study are included as part of this data release. Please refer to the User Guide for further information on linking in this way and for geographical information options.

Latest edition information

For the eleventh edition (December 2021), revised April, May, June, July, September, November 2020, January 2021 and March 2021 data files for the adult survey have been deposited. These files have been amended to address issues identified during ongoing quality assurance activities. All documentation has been updated to explain the revisions, and users are advised to consult the documentation for details. In addition new data from the September 2021 web survey have been deposited.

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.

Descriptive statistics of the traits in the study population.

List of student's achievement in the learning area of Maths by SA2 and year level.

This dataset is no longer being updated. For more information about Learning Outcomes go to https://www.qed.qld.gov.au/publications/reports/statistics/schooling/learning-outcomes

Employment income (in 2019 and 2020) by detailed major field of study and highest certificate, diploma or degree, including work activity (full time full year, part time full year, or part year).

Historical Employment Statistics 1990 - current. The Current Employment Statistics (CES) more information program provides the most current estimates of nonfarm employment, hours, and earnings data by industry (place of work) for the nation as a whole, all states, and most major metropolitan areas. The CES survey is a federal-state cooperative endeavor in which states develop state and sub-state data using concepts, definitions, and technical procedures prescribed by the Bureau of Labor Statistics (BLS). Estimates produced by the CES program include both full- and part-time jobs. Excluded are self-employment, as well as agricultural and domestic positions. In Connecticut, more than 4,000 employers are surveyed each month to determine the number of the jobs in the State. For more information please visit us at http://www1.ctdol.state.ct.us/lmi/ces/default.asp.

Colleges and universities in the United States are still a popular study destination for Chinese students, with around 277 thousand choosing to take courses there in the 2023/24 academic year. Although numbers were heavily affected by the coronavirus pandemic, China is still the leading source of international students in the U.S. education market, accounting for 24.6 percent of all incoming students. The education exodus Mathematics and computer science courses led the field in terms of what Chinese students were studying in the United States, followed by engineering and business & management programs. The vast majority of Chinese students were self-funded, wth the remainder receiving state-funding to complete their overseas studies. Tuition fees can run into the tens of thousands of U.S. dollars, as foreign students usually pay out-of-state tuition fees. What about the local situation? Although studying abroad attracts many Chinese students, the country itself boasts the largest state-run education system in the world. With modernization of the national tertiary education system being a top priority for the Chinese government, the country has seen a significant increase in the number of local universities over the last decade. Enrolments in these universities exceeded 37 million in 2023, and a record of more than ten million students graduated in the same year, indicating that China's education market is still expanding.

The datasets containing simulation performance results during the current study, in addition to the code to replicate the simulation study in its entirety, are available here. See the README file for a description the Stata do-files, R-script files, tips to run the code, and the performance result dataset dictionaries.

The Public Health Research Database (PHRD) is a linked asset which currently includes Census 2011 data; Mortality Data; Hospital Episode Statistics (HES); GP Extraction Service (GPES) Data for Pandemic Planning and Research data. Researchers may apply for these datasets individually or any combination of the current 4 datasets.

The purpose of this dataset is to enable analysis of deaths involving COVID-19 by multiple factors such as ethnicity, religion, disability and known comorbidities as well as age, sex, socioeconomic and marital status at subnational levels. 2011 Census data for usual residents of England and Wales, who were not known to have died by 1 January 2020, linked to death registrations for deaths registered between 1 January 2020 and 8 March 2021 on NHS number. The data exclude individuals who entered the UK in the year before the Census took place (due to their high propensity to have left the UK prior to the study period), and those over 100 years of age at the time of the Census, even if their death was not linked. The dataset contains all individuals who died (any cause) during the study period, and a 5% simple random sample of those still alive at the end of the study period. For usual residents of England, the dataset also contains comorbidity flags derived from linked Hospital Episode Statistics data from April 2017 to December 2019 and GP Extraction Service Data from 2015-2019.

Abstract copyright UK Data Service and data collection copyright owner. These teaching datasets, comprising a sub-set of a large-scale longitudinal study, the Longitudinal Study of Young People in England (LSYPE), were created as part of the NCRM Developing Statistical Modelling in the Social Sciences: Lancaster-Warwick-Stirling Node Phase 2 project, funded by the Economic and Social Research Council (ESRC). During the project, a web site was created with the aim to provide a web-based training resource about the use of statistical regression methods in educational research. The content is designed to teach users how to perform a variety of regression analyses using SPSS, starting with foundation material in basic statistics and working through to more complex multiple linear, logistic and ordinal regression models. Along with illustrated modules the site contains demonstration videos, interactive quizzes and SPSS exercises and examples that use these LSYPE teaching data. Further information and documentation may be found at the web site, Using Statistical Methods in Education Research. Throughout the site modules users are invited to use the datasets for either following the examples or performing exercises. Prospective users of the data will be directed to register an account in order to download the data. The full LSYPE study is held at the Archive under SN 5545. The teaching datasets include information drawn from Wave 1 of LSYPE, conducted in 2004, with GCSE results matched from Wave 3 (2006). Further information about the NCRM Node project covering this study may be found on the Developing Statistical Modelling in the Social Sciences ESRC award web page. Documentation There is currently no discrete documentation currently available with these teaching datasets; users should consult the web site noted above. Documentation covering the main LSYPE study is available with SN 5545. For the second edition (July 2011), updated versions of the SPSS data files were deposited to resolve minor anomalies. Main Topics: The teaching datasets include variables covering LSYPE respondents' educational test results, academic achievement and school life, and demographic/household characteristics including ethnic group, gender, social class and socio-economic status, computer ownership, private education, and mothers' occupational status and educational background. For details of sampling, see main LSYPE study.

About this dataset

Context

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

Key observations

There is a slight majority of female population, with 52.36% of total population being female. 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.

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 Tillamook is shown in this column.
• % of Total Population: This column displays the percentage distribution of each gender as a proportion of Tillamook 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 Tillamook Population by Gender. You can refer the same here

List of student's achievement in the learning area of English by their year level and country of birth.

*This dataset is no longer being updated. For more information about Learning Outcomes go to https://qed.qld.gov.au/publications/reports/statistics/schooling/learning-outcomes

In 2019, 797,546 animals were used for research in research facilities in the United States. This is an increase from the previous year, when about 780,070 animals were used for research in the country.

About this dataset

Context

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

Key observations

There is a majority of female population, with 53.63% of total population being female. 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 Wilmington is shown in this column.
• % of Total Population: This column displays the percentage distribution of each gender as a proportion of Wilmington 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 Wilmington Population by Race & Ethnicity. You can refer the same here

Background:
The Millennium Cohort Study (MCS) is a large-scale, multi-purpose longitudinal dataset providing information about babies born at the beginning of the 21st century, their progress through life, and the families who are bringing them up, for the four countries of the United Kingdom. The original objectives of the first MCS survey, as laid down in the proposal to the Economic and Social Research Council (ESRC) in March 2000, were:

• to chart the initial conditions of social, economic and health advantages and disadvantages facing children born at the start of the 21st century, capturing information that the research community of the future will require
• to provide a basis for comparing patterns of development with the preceding cohorts (the National Child Development Study, held at the UK Data Archive under GN 33004, and the 1970 Birth Cohort Study, held under GN 33229)
• to collect information on previously neglected topics, such as fathers' involvement in children's care and development
• to focus on parents as the most immediate elements of the children's 'background', charting their experience as mothers and fathers of newborn babies in the year 2000, recording how they (and any other children in the family) adapted to the newcomer, and what their aspirations for her/his future may be
• to emphasise intergenerational links including those back to the parents' own childhood
• to investigate the wider social ecology of the family, including social networks, civic engagement and community facilities and services, splicing in geo-coded data when available

Additional objectives subsequently included for MCS were:

• to provide control cases for the national evaluation of Sure Start (a government programme intended to alleviate child poverty and social exclusion)
• to provide samples of adequate size to analyse and compare the smaller countries of the United Kingdom, and include disadvantaged areas of England

Further information about the MCS can be found on the Centre for Longitudinal Studies web pages.

The content of MCS studies, including questions, topics and variables can be explored via the CLOSER Discovery website.

The first sweep (MCS1) interviewed both mothers and (where resident) fathers (or father-figures) of infants included in the sample when the babies were nine months old, and the second sweep (MCS2) was carried out with the same respondents when the children were three years of age. The third sweep (MCS3) was conducted in 2006, when the children were aged five years old, the fourth sweep (MCS4) in 2008, when they were seven years old, the fifth sweep (MCS5) in 2012-2013, when they were eleven years old, the sixth sweep (MCS6) in 2015, when they were fourteen years old, and the seventh sweep (MCS7) in 2018, when they were seventeen years old. End User Licence versions of MCS studies:
The End User Licence (EUL) versions of MCS1, MCS2, MCS3, MCS4, MCS5, MCS6 and MCS7 are held under UK Data Archive SNs 4683, 5350, 5795, 6411, 7464, 8156 and 8682 respectively. The longitudinal family file is held under SN 8172.

Sub-sample studies:
Some studies based on sub-samples of MCS have also been conducted, including a study of MCS respondent mothers who had received assisted fertility treatment, conducted in 2003 (see EUL SN 5559). Also, birth registration and maternity hospital episodes for the MCS respondents are held as a separate dataset (see EUL SN 5614).


How to access genetic and/or bio-medical sample data from a range of longitudinal surveys:
For information on how to access biomedical data from MCS that are not held at the UKDS, see the CLS Genetic data and biological samples webpage.

Secure Access datasets:
Secure Access versions of the MCS have more restrictive access conditions than versions available under the standard End User Licence or Special Licence (see 'Access data' tab above).

Secure Access versions of the MCS include:

• detailed sensitive variables not available under EUL. These have been grouped thematically and are held under SN 8753 (socio-economic, accommodation and occupational data), SN 8754 (self-reported health, behaviour and fertility), SN 8755 (demographics, language and religion) and SN 8756 (exact participation dates). These files replace previously available studies held under SNs 8456 and 8622-8627
  
• detailed geographical identifier files which are grouped by sweep held under SN 7758 (MCS1), SN 7759 (MCS2), SN 7760 (MCS3), SN 7761 (MCS4), SN 7762 (MCS5 2001 Census Boundaries), SN 7763 (MCS5 2011 Census Boundaries), SN 8231 (MCS6 2001 Census Boundaries), SN 8232 (MCS6 2011 Census Boundaries), SN 8757 (MCS7), SN 8758 (MCS7 2001 Census Boundaries) and SN 8759 (MCS7 2011 Census Boundaries). These files replace previously available files grouped by geography SN 7049 (Ward level), SN 7050 (Lower Super Output Area level), and SN 7051 (Output Area level)
• linked education administrative datasets for Key Stages 1, 2, 4 and 5 held under SN 8481 (England). This replaces previously available datasets for Key Stage 1 (SN 6862) and Key Stage 2 (SN 7712)
  
• linked education administrative datasets for Key Stage 1 held under SN 7414 (Scotland)
• linked education administrative dataset for Key Stages 1, 2, 3 and 4 under SN 9085 (Wales)
  
• linked NHS Patient Episode Database for Wales (PEDW) for MCS1 – MCS5 held under SN 8302
• linked Scottish Medical Records data held under SNs 8709, 8710, 8711, 8712, 8713 and 8714;
• Banded Distances to English Grammar Schools for MCS5 held under SN 8394
• linked Health Administrative Datasets (Hospital Episode Statistics) for England for years 2000-2019 held under SN 9030
• linked Health Administrative Datasets (SAIL) for Wales held under SN 9310
  
• linked Hospital of Birth data held under SN 5724.

The linked education administrative datasets held under SNs 8481,7414 and 9085 may be ordered alongside the MCS detailed geographical identifier files only if sufficient justification is provided in the application. Users are also only allowed access to either 2001 or 2011 of Geographical Identifiers Census Boundaries studies. So for MCS5 either SN 7762 (2001 Census Boundaries) or SN 7763 (2011 Census Boundaries), for the MCS6 users are only allowed either SN 8231 (2001 Census Boundaries) or SN 8232 (2011 Census Boundaries); and the same applies for MCS7 so either SN 8758 (2001 Census Boundaries) or SN 8759 (2011 Census Boundaries).

Researchers applying for access to the Secure Access MCS datasets should indicate on their ESRC Accredited Researcher application form the EUL dataset(s) that they also wish to access (selected from the MCS Series Access web page).

The Millennium Cohort Study: Linked Health Administrative Data (Scottish Medical Records), Scottish Birth Records, 2000-2002: Secure Access includes data files from the NHS Digital Hospital Episode Statistics database for those cohort members who provided consent to health data linkage in the Age 50 sweep, and had ever lived in Scotland. The Scottish Medical Records database contains information about all hospital admissions in Scotland. This study concerns the Scottish Birth Records.

Other datasets are available from the Scottish Medical Records database, these include:

• Child Health Reviews (CHR) held under SN 8709
• Prescribing Information System (PIS) held under SN 8710
• Scottish Immunisation and Recall System

Taiwan Number of Student: Applying for Visa to Study Abroad: Oceania data was reported at 6,313.000 Person in 2017. This records a decrease from the previous number of 7,265.000 Person for 2016. Taiwan Number of Student: Applying for Visa to Study Abroad: Oceania data is updated yearly, averaging 3,397.000 Person from Dec 1998 (Median) to 2017, with 20 observations. The data reached an all-time high of 7,322.000 Person in 2015 and a record low of 2,434.000 Person in 1998. Taiwan Number of Student: Applying for Visa to Study Abroad: Oceania data remains active status in CEIC and is reported by Ministry of Education. The data is categorized under Global Database’s Taiwan – Table TW.G054: Education Statistics.

The National Assessment of Educational Progress, 2009 High School Transcript Study (HSTS 2009), is a study that is part of the National Assessment of Educational Progress (NAEP) program; program data available since 1990 at . HSTS 2009 (https://nces.ed.gov/nationsreportcard/hsts/) is a cross-sectional survey that periodically surveys the curricula being followed in our nation's high schools and the coursetaking patterns of high school students through a collection of transcripts. The study was conducted using survey of school administrative personnel and collection of students' transcripts. For public schools, the HSTS sample was a subsample of the NAEP 2009 twelfth-grade public school sample for the operational mathematics and science assessments. For private schools, the HSTS sample was the NAEP 2009 twelfth-grade private school sample for the operational mathematics and science assessments. The study weighted response rate was 83 percent. HSTS 2009 also offers information on the relationship of student coursetaking patterns to achievement at grade 12 as measured by NAEP. Key statistics produced from HSTS 2009 are information about the types of courses that graduates take, how many credits they earn, their grade point averages, and the relationship between coursetaking patterns and achievement, as measured by NAEP.

The number of postsecondary graduates, by Classification of Instructional Programs (CIP) 2016 - Cannabis groupings (2 and 4 digit series), International Standard Classification of Education (ISCED), institution type and gender.

Most are in Engineering & related fields with 65 people practicing it in Lot 6, PE. Health & related fields is another popular field of expertise, as 25.49% of inhabitants are involved in it. The third group are those who are in Business, Management & Public Administration, with 60 people responding that it is their line of work. STEM (Science, Technology, Engineering, and Math) is expected to be a growing industry, however, Department of Finance confirms that Canada is lagging behind other Organisation for Economic Co-operation and Development (OECD) countries in terms of STEM graduates. Lot 6, PE has 65 people or 25.49% of workers in STEM industries.

Taiwan Number of Student: Applying for Visa to Study Abroad: Africa data was reported at 18.000 Person in 2017. This records a decrease from the previous number of 20.000 Person for 2016. Taiwan Number of Student: Applying for Visa to Study Abroad: Africa data is updated yearly, averaging 21.000 Person from Dec 1998 (Median) to 2017, with 20 observations. The data reached an all-time high of 102.000 Person in 1999 and a record low of 0.000 Person in 2012. Taiwan Number of Student: Applying for Visa to Study Abroad: Africa data remains active status in CEIC and is reported by Ministry of Education. The data is categorized under Global Database’s Taiwan – Table TW.G054: Education Statistics.