Oxford Spring School in Advanced Research Methods
Date:
27/03/2017 - 31/03/2017
Organised by:
University of Oxford
Presenter:
Professor Elias Dinas
Professor Ezequiel González-Ocantos
Professor Andrea Ruggeri
Level:
Intermediate (some prior knowledge)
Contact:
Margo Kirk, Oxford Spring School Administrator
springschool@politics.ox.ac.uk
+44 1865 278703
Map:
View in Google Maps (OX1 3UQ)
Venue:
Department of Politics and International Relations
Manor Road Building
Manor Road
Oxford
OX1 3UQ
Description:
The Oxford Spring School in Advanced Research Methods offers graduate students and researchers from universities across the UK and abroad a unique venue to learn cutting-edge methods in quantitative and qualitative methods in the social sciences, with a variety of advanced courses which place the different data analysis techniques within broader disciplinary trends towards mixed-methods research designs.
Funding
We are delighted to be able to offer five full bursaries and six half bursaries. Offers will be made on merit.
Course Options
Course options include a choice between sets of increasingly popular and influential methods/techniques in the discipline:
· Social Network Analysis
· Causal Inference
Other options will be:
· Process Tracing
· Forecasting
· Spatial Analysis
· Data Visualisation
Participants will be able to take a total of up to three different methods courses in one week, as well as a masterclass session on how to publish their research in peer-reviewed journals. Tutors will emphasise the mixed-methods philosophy underlying these courses, and the use of these techniques in different types of research designs.
Registration deadline: Monday 16 January 2017
Cost:
£650
Website and registration:
http://www.politics.ox.ac.uk/spring-school/oxford-spring-school-in-advanced-research-methods.html
Region:
South East
Keywords:
Explanatory Research and Causal analysis, Mixed Methods, Statistical Theory and Methods of Inference, Spatial Data Analysis, Forecasting, Social Network Analysis, R, Data Visualisation
Related publications and presentations:
Explanatory Research and Causal analysis
Mixed Methods
Statistical Theory and Methods of Inference
Spatial Data Analysis
Forecasting
Social Network Analysis
R
Data Visualisation