Trainer

Through a series of videos featuring a variety of voices and perspectives and discussing a range of methodologies and theoretical approaches, this course aims to explore the history, practice and people involved in the evolving, highly diverse, and interdisciplinary field of Digital Humanities.

This introductory webinar is for anyone who is involved in the collection of data and is considering making (some of) their data available in accordance with funders’ requirements. More and more funders are requiring that research data be made available after completion of the research project, usually through the archiving of data in a trusted repository. However, research teams often still lack the appropriate skills and knowledge regarding how to properly prepare their data for archiving and sharing. This webinar aims to raise awareness about relevant key data management practices for sharing, specifically regarding data documentation, gaining consent, and data anonymisation. Addressing each of these three topics, it provides a short theoretical introduction, including what FAIR means and how it is implemented, as well as practical illustrations drawing on a large-scale cross-national survey (the European Social Survey). It also provides some practical tips with respect to data archiving, in particular how to choose an appropriate archive or repository.

The ORION Open Science Train-the-Trainer course is intended to guide you in how to facilitate and run training on Open Science. The course covers the theoretical underpinnings of adult education as well as practical methods and techniques to use in training events. From didactics to video creation, from audience profiles to Brainwalking. There are a range of materials, media, and activities intended to strengthen your abilities as a training facilitator, both face-to-face and online.

This is an introductory guide to the main types of data with a time element. The guide is a brief overview of key elements in need of consideration when using these types of data. It also covers data availability and some commonly used methods for studying change over time quantitatively. 

This guide covers the basics of sampling as well as other related topics such as clustering, stratification and weighting. 

This guide explains the main reasons for using weights, how weights work and how to use weighting variables in statistical analysis. 

This guide aims to help researchers utilise extensive survey data available. In particular, this guide is designed to support those starting small research projects, especially students doing dissertations. 

The guide includes materials to read, worksheets for getting started and questions to think about and answer.

This guide will cover how to map census data in QGIS. The example used in this guide creates a choropleth map showing the percentage of males who work in the manufacturing service using the QGIS package. 

This guide aims to show the strength of using Census Microdata for a variety of research purposes, via a worked example taken from real-life research. This guide assumes some familiarity with microdata, mapping and statistical software. 

These quantitative methods e-books and accompanying quizzes are for direct use in teaching students or for self-study. They aim to build skills in quantitative methods and statistical software and use the Living Costs and Food Survey.

Using SPSS, lecturers and students can utilise both the practical and quiz elements of each e-book topic. Topics include examining variables, correlations, regression and multiple regression.

The e-books have been developed through a collaboration of the UK Data Service, National Centre for Research Methods (NCRM), and the Centre for Multi-Level Modelling at the University of Bristol and were created using the StatJR software based on original outputs from the project Using Statistical E-books to teach undergraduate students quantitative methods and statistical software funded by the British Academy.