Abstract copyright UK Data Service and data collection copyright owner.

• the number of variables has been reduced
• weighting has been simplified
• a reduced codebook is provided

• socio-demographic variables
• body, weight and blood pressure measurements
• illnesses
• cigarette smoking

Abstract copyright UK Data Service and data collection copyright owner.

The English Housing Survey, 2018-2019: Household Data Teaching Dataset is based on the English Housing Survey, 2018-2019: Household Data (held under SN8669) and constitutes real data which are used by the Department for Communities and Local Government and are behind many headlines. The teaching dataset is a subset which has been subjected to certain simplifications for the purpose of learning and teaching.

The main differences are:

• the number of variables has been reduced
• weighting has been simplified
• a reduced codebook is provided

Further information is available in the study documentation which includes a dataset user guide. Information about other teaching resources and datasets can be found on the UK Data Service teaching resources webpages.

Main Topics:

The main topics covered are:

• housing characteristics
• household characteristics

Vulnerability to anxiety and depressive disorders is affected by risk and resilience factors, such as personality, use of emotion regulation strategies, and affective cognition. Previous research has identified personality constructs best explaining variance in anxiety and depression (Lyon et al, 2020; 2021), however the mediating mechanisms are unknown. This study aimed to investigate the mediating roles of emotion regulation strategies and affective cognition in the relationship between personality constructs and affective disorders. Data were collected from a sample of 276 students and staff at the University of Manchester. Measures included both broad and narrow Big Five personality constructs; COPE Inventory strategies; a dot-probe task to measure attentional biases to emotional information; both a questionnaire and a computerised cognitive to measure interpretation of emotional images; and measures of anxiety and depression.

Abstract copyright UK Data Service and data collection copyright owner.

• the teaching dataset contains data from April-May 2015 only;
  
• the number of variables has been reduced;
  
• a reduced user guide with codebook is provided;
  
• some variables have been recoded due to concerns about statistical disclosure;

• life satisfaction;
  
• emotional states;
  
• employment;
  
• socio-demographics.

This is a carefully curated dataset of patients who have either been diagnosed with Pancreatic Cancer (PC) or are deemed high risk. Sourced from Manchester Foundation Trust systems, the dataset was curated for use in a predictive model.

Abstract copyright UK Data Service and data collection copyright owner.

• SN 8268 - 1971 Census Microdata Individual File for Great Britain: 5% Sample, which contains information on individuals in larger local authorities;
• SN 8269 - 1971 Census Microdata Household File for Great Britain: 0.95% Sample, which links household members together to allow individuals to be understood within their household context. SNs 8268 and 8269 are both available to registered UK Data Service users based in the United Kingdom (see Access section for non-UK access restrictions); and
• SN 8271 - 1971 Census Microdata for Great Britain: 9% Sample: Secure Access, which comprises a larger population sample and so contains sufficient information to constitute personal data, meaning that it is only available to Accredited Researchers, under restrictive Secure Access conditions.

The Health Survey for England, 2000-2001: Small Area Estimation Teaching Dataset was prepared as a resource for those interested in learning introductory small area estimation techniques. It was first presented as part of a workshop entitled 'Introducing small area estimation techniques and applying them to the Health Survey for England using Stata'. The data are accompanied by a guide that includes a practical case study enabling users to derive estimates of disability for districts in the absence of survey estimates. This is achieved using various models that combine information from ESDS government surveys with other aggregate data that are reliably available for sub-national areas. Analysis is undertaken using Stata statistical software; all relevant syntax is provided in the accompanying '.do' files.

The data files included in this teaching resource contain HSE variables and data from the Census and Mid-year population estimates and projections that were developed originally by the National Statistical agencies, as follows:

• The main data file, 'hse_data.dta', is a reduced version of the HSE for 2000 and 2001. In order to combine data from two years of the HSE in a consistent way some changes have been made to the weights in each year. Additionally, some recoding of the limiting long term illness (LLTI), disability and the age variable has also been undertaken.
• File 'practical_1_task_5_data.dta' contains population counts and model mobility disability rates (estimated during practical 1) distinguishing single year of age and sex for the six case study districts.
• File 'practical_2_data.dta' contains the aggregate data required for Practical 2, including age- and sex-specific rates of LLTI (Census) for six UK case study districts, age- and sex-specific rates of mobility disability for England (HSE), and population counts for the six districts.
• File 'pop_data_practical_3.dta' contains population counts for the six districts (by age, sex and LLTI status) required for practical 3

The DIAMET project aimed to better the understanding and prediction of mesoscale structures in synoptic-scale storms. Such structures include fronts, rain bands, secondary cyclones, sting jets etc, and are important because much of the extreme weather we experience (e.g. strong winds, heavy rain) comes from such regions. Weather forecasting models are able to capture some of this activity correctly, but there is much still to learn. By a combination of measurements and modelling, mainly using the Met Office Unified Model (UM), the project worked to better understand how mesoscale processes in cyclones give rise to severe weather and how they can be better represented in models and better forecast.

This dataset contains meteorological data recorded by radiosondes launched in support of the DIAMET campaign. Data are from the Manchester radiosondes launched at Aberystwyth and from Met Office sondes at Albemarle, Camborne, Castor Bay, Herstmonceux, Lerwick and Lochranza.

List of Institutions offering MSc FinTech programs 1 MS Finance (FinTech and Financial Analytics), HK Baptist University, Hong Kong 2 MS Financial Technology, New Jersey City University, USA 3 MSc Financial Technology, HK University of Science & Technology, Hong Kong 4 MSc Financial Technology, Imperial College Business School, UK 5 MSc Financial Technology, University of Birmingham, UK 6 MSc Financial Technology, University of Essex, UK 7 MSc Financial Technology, University of Glasgow, UK 8 MSc Financial Technology, University of Liverpool, UK 9 MSc Financial Technology, University of Strathclyde, UK 10 MSc Financial Technology (FinTech), Nanyang Technological University, Singapore 11 MSc Financial Technology (FinTech), Coventry University, UK 12 MSc Financial Technology (FinTech), Manchester Metropolitan University, UK 13 MSc Financial Technology (FinTech), Teesside University, UK 14 MSc Financial Technology (FinTech), University of Salford, UK 15 MSc Financial Technology (FinTech), University of Stirling, UK 16 MSc Financial Technology (Fintech), University of Exeter, UK 17 MSc Financial Technology (FinTech), University of West England - Bristol, UK 18 MSc Fintech, Risk and Investment Analysis, University of Sussex, UK 19 MSc Fintech with Business Analytics, University of Westminster, UK 20 MSc FinTech and Policy, University of Surrey, UK 21 MSc FinTech and Financial Markets, Nottingham Trent University, UK 22 MSc Fintech, University of Huddersfield, UK

Six subject areas were identified including: • FinTech; • Technology; • Finance; • Analytics; • RegTech; • Others.

Data is organized in three worksheets; 1. Raw data comparing 22 MSc programs 2. Course wise arrangement of all programs 3. MS FinTech structure

Data collected as part of the NERC funded Radioactivity and the Environment (RATE), Long-lived Radionuclides in the Surface Environment (Lo-RISE), research consortium.This data comes from the terrestrial workstream group based at the University of Manchester. The data consists of radionuclide measurements of environmental and biological samples including uranium (238), thorium (232) and radium (226), and soil subsurface and surface biota bioprospecting (plants and AM fungi). The data from this first dataset has been published in the following publication: Davies et al. (2018) Multiple environmental factors influence 238U, 232Th and 226Ra bioaccumulation in arbuscular mycorrhizal-associated plants. Science of the Total Environment 640-641:921-934.

The British Social Attitudes survey (BSA) is the leading survey in Britain for assessing trends and changes in public opinions on social and political measures. Over the past four decades, the survey has become the main source of statistics on key national issues, which makes the survey valuable for policy making, researchers, charity and media.

The British Social Attitudes Open Teaching Dataset: Health Care and Equalities, 2021, is a subsample from the original British Social Attitudes Survey 2021 (available from the UK Data Archive under SN 9072). This open-access teaching dataset has been adapted for teaching and learning with a reduced number of variables, covering attitudes towards health care and equality.

Further information is available in the study documentation, which includes a dataset user guide.

Abstract copyright UK Data Service and data collection copyright owner.

The Quarterly Labour Force Survey July - September 2018: Teaching Dataset is based on the Quarterly Labour Force Survey, July - September 2018 (QLFS JS18; available from the UK Data Archive under SN 8407) and constitutes real data which are used by the government and are behind many headlines. The teaching dataset contains fewer variables and has been subjected to certain simplifications and additions for the purpose of learning and teaching.

The main differences are:

• the number of variables has been reduced;
• extra variables (based on variables from the original QLFS JS18 dataset) have been added, including a weight for which mean=1;
• a reduced codebook is provided.

Further information is available in the study documentation which includes a dataset user guide.

Socio-demographics, employment, housing tenure, education, health.

The UK's Natural Environment Research Council's (NERC) National Centre for Atmospheric Sciences (NCAS) operates a suite of instrumentation to monitor the atmospheric dynamics and composition of the atmosphere. This dataset brings together all the long term routine observations made by NCAS instruments covering surface based instruments as well as remote sensing instruments such as radars and lidars. Some of the instruments may also be deployed elsehwere on field campaigns, for which the data will be available under the associated field campaign dataset. Links are also available to pages describing the instruments from which links to all data from that particular instrument can be found.

The dataset contains the following measurements:

Eastward wind velocity component Northward wind velocity component Upward air velocity Direction the wind is from Signal to noise ratio Altitude of instrument above the ground Longitude of instrument Latitude of instrument Spectral width

Abstract copyright UK Data Service and data collection copyright owner. The 1961 Census Microdata Individual File for Great Britain: 5% Sample dataset was created from existing digital records from the 1961 Census under a project known as Enhancing and Enriching Historic Census Microdata Samples (EEHCM), which was funded by the Economic and Social Research Council with input from the Office for National Statistics and National Records of Scotland. The project ran from 2012-2014 and was led from the UK Data Archive, University of Essex, in collaboration with the Cathie Marsh Institute for Social Research (CMIST) at the University of Manchester and the Census Offices. In addition to the 1961 data, the team worked on files from the 1971 Census and 1981 Census. The original 1961 records preceded current data archival standards and were created before microdata sets for secondary use were anticipated. A process of data recovery and quality checking was necessary to maximise their utility for current researchers, though some imperfections remain (see the User Guide for details). Three other 1961 Census datasets have been created: SN 8273 - 1961 Census Microdata Household File for Great Britain: 0.95% Sample, which links household members together to allow individuals to be understood within their household context, and is available to registered UK Data Service users based in the United Kingdom (see Access section for non-UK access restrictions);SN 8274 - 1961 Census Microdata Teaching Dataset for Great Britain: 1% Sample: Open Access, which can be used as a taster file and is freely available for anyone to download under an Open Government Licence; and SN 8275 - 1961 Census Microdata for Great Britain: 9% Sample: Secure Access, which comprises a larger population sample and so contains sufficient information to constitute personal data, meaning that it is only available to Accredited Researchers, under restrictive Secure Access conditions.

Abstract copyright UK Data Service and data collection copyright owner. The 1961 Census Microdata Household File for Great Britain: 0.95% Sample dataset was created from existing digital records from the 1961 Census under a project known as Enhancing and Enriching Historic Census Microdata Samples (EEHCM), which was funded by the Economic and Social Research Council with input from the Office for National Statistics and National Records of Scotland. The project ran from 2012-2014 and was led from the UK Data Archive, University of Essex, in collaboration with the Cathie Marsh Institute for Social Research (CMIST) at the University of Manchester and the Census Offices. In addition to the 1961 data, the team worked on files from the 1971 Census and 1981 Census. The original 1961 records preceded current data archival standards and were created before microdata sets for secondary use were anticipated. A process of data recovery and quality checking was necessary to maximise their utility for current researchers, though some imperfections remain (see the User Guide for details). Three other 1961 Census datasets have been created: SN 8272 - 1961 Census Microdata Individual File for Great Britain: 5% Sample, which contains information on individuals in larger local authorities, and is available to registered UK Data Service users based in the United Kingdom (see Access section for non-UK access restrictions);SN 8274 - 1961 Census Microdata Teaching Dataset for Great Britain: 1% Sample: Open Access, which can be used as a taster file and is freely available for anyone to download under an Open Government Licence; and SN 8275 - 1961 Census Microdata for Great Britain: 9% Sample: Secure Access, which comprises a larger population sample and so contains sufficient information to constitute personal data, meaning that it is only available to Accredited Researchers, under restrictive Secure Access conditions.

Abstract copyright UK Data Service and data collection copyright owner. Welfare State under Strain, 2014-2015: A Comparative Study of Diversity, Austerity and Public Opinion is a panel study which investigates the dynamics and drivers of public opinion about welfare in Great Britain and the Netherlands. The panel features a series of embedded survey experiments designed to test the impact of diversity, austerity, and various moderators on political attitudes. Identical experiments were conducted in the two countries, enabling examination of how national context mediates the effects of these factors on public opinion. Attitude change over time was also captured by surveying the same voters repeatedly, and the impact of the most powerful source of political information - election campaigns, was captured by timing survey waves before and immediately after European Parliament (2014), national (Britain, 2015) and regional (Netherlands, 2015) elections. The survey was commissioned following an Open Research Area grant awarded jointly by the UK Economic and Social Research Council and NWO Netherlands. The surveys were developed by a team of four based in the Department of Politics and International Relations, University of Manchester and the European Research Centre on Migration and Ethnic Relations, University of Utrecht. Further information is available on the Research Councils UK award page. The first edition of this study contains the British data only, as the Dutch data are not yet available for public release. A future update will include the Dutch dataset and the integrated two country dataset. Main Topics: The questionnaire covered the following topics: political attitudes; general welfare support; austerity measures and economic security; deservingness and welfare chauvinism, interethnic/intergroup attitudes; ideological factors and demographic characteristics. The survey also included a vignette experiment. Active sampling Online (web-based) survey

Abstract copyright UK Data Service and data collection copyright owner.

• the number of variables has been reduced
• a reduced User Guide with codebook is provided
• some variables have been recoded to reduce the level of detail