Advanced Methods Training

The WRDTP is committed to providing training in advanced methods, and it does so across three areas: quantitative methods, qualitative methods, and data analytics. Across these different methods areas, we offer training courses that will help students enhance their understanding of the social world, and explore important research questions that could not be robustly considered otherwise.

Advanced Quantitative Methods

Quantitative data is increasingly prevalent and is widely used by researchers in academia, the public sector, and commercial organisations to understand various aspects of society and the economy. As a result, there is a need for methods that can help analyse this data robustly and effectively. The AQM group focuses on such methods, particularly those that focus on complex data forms that are key to advancing the exploration of core questions in the social sciences. We support students funded under the AQM Scholarships, but the training and resources offered go beyond this, benefitting other students intending to use quantitative methods as part of their PhD.

 Methods training and development:

The AQM methods group provides training in a range of different methods for analysing quantitative data to answer research questions about society. The training provided here will go beyond the basic quantitative methods that are often taught in “Introductory Quantitative Methods” modules in social science bachelors and masters programmes. For instance, the methods used might deal with complex data structures, consider how to identify causal effects (as opposed to simpler associations), or consider spatial and temporal variability.

Advanced Qualitative Methods

Qualitative methods seek to unveil nuance, complexity, and the rich tapestry of life. Widely used by researchers across the social sciences qualitative methods focus on generating data from conversations with people about their beliefs, experiences, attitudes, behaviour, and interactions; observations of people or participation alongside them, embedded in social life; or studying how the world looks, sounds, and even smells and tastes. The AQualM group focus on methods such as interviews, focus groups, ethnography, visual work, and creative approaches, alongside the myriad ways these methods are being innovated globally. Data analysis tools and techniques, and how researchers can take qualitative data to explain lived experiences, inequalities, and people’s ideas and behaviours, are also central to creating compelling stories of how the world works and how it can be improved.

Methods training and development:

The AQualM group provide training in qualitative methods and approaches for intermediate and advanced methodologists. We offer events in common methods, such as interviews and focus groups, including contemporary innovations and applications in the digital world, as well as more specialised subjects, like storytelling methods and archival work. Vital to our work is a focus on ethics: qualitative researchers must put ethical considerations at the heart of their work, and so practical analysis of the lived ethical dilemmas of data collection, and how research can be a positive, participatory experience for individuals, feature throughout our training.

Advanced Data Analytics

In recent years, there has been a vast increase in the data available to companies, governments, and researchers. Often this data contains important information about the way people and society works; however it will often have not been collected for the purpose of social science analysis. These datasets may include administrative data, unstructured commercial data (such as loyalty card databases), data created through digital interactions between people and/or organisations (e.g. social media data), and interactions with urban environments (such as transport footfall data or phone tracking data).These data are often underutilised in the social sciences, whilst being information rich. They are often large (often described as “Big Data”) and sometimes are not representative of broader populations. This means that they are often suitable for answering different research questions, and require different techniques from more traditional datasets that are used more regularly in the social sciences (such as representative surveys). We support students funded specifically under the ADA Scholarships, but the training and resources offered go beyond this, likely with relevance to many students intending to use unconventional data sources as part of their PhD.

Methods training and development:

The ADA group provides training in the sorts of methods that are suitable for research using data sources that are perhaps not usually used for social research, as outlined above. This might include approaches such as Machine learning, Artificial Intelligence, and particular methods of data visualisation.