On Monday 20 and Tuesday 21 March 2017 Warwick Q-Step Centre hosted its annual Methods Spring Camp. This is the second event in the Spring Camp Series and this year’s theme was “forecasting”.
Participants, including both undergraduate and postgraduate students, came together to focus on the methodological challenges related to forecasting political, economic, and social events. On both days there was lively debate and discussion, and participants were able to gain hands-on experience of forecasting real-world events. The event was extremely well-attended by staff and students from a range of disciplines across the University, all of whom had an interest in forecasting using quantitative methods. As well as staff and students from Warwick Q-Step Centre, we were pleased to welcome those from departments across the University including Warwick Business School, Economics, Sociology, Politics, Maths and Statistics, and Engineering.
On Day 1 we were delighted to welcome a range of expert guest speakers who gave presentations on various forecasting topics including the economy, intra-state conflict, and political elections. This provided an excellent opportunity for students to engage with the wider University community and to discuss topical issues with academics from Warwick, WBS, UCL and Oxford.
On Day 2 participants had the opportunity to gain hands-on experience in forecasting by taking part in an interactive workshop on Machine Learning and Forecasting. Given by Elio Amicarelli, a PhD student in the Department of Political Science at UCL, the workshop focused on understanding the theory and practice of forecasting. Participants learned how to use statistical software such as ‘R’ to generate and assess forecasts of social and political events.
Spring Camp 2017 Presentations
View the presentations from this year’s event below.
Dr Andreas Murr (Warwick):
Professor James Mitchell (WBS):
Dr Nils Metternich (UCL):
Dr Stephen Fisher (Oxford):
Spring Camp 2017 Photo Gallery
View a selection of photos from the 2017 event below: