Understanding and addressing social challenges through applied statistical methods, data science and creative microsimulation.
12th May 2025 | 5 days

This module provides unique, cutting-edge training in applied statistical methods and data science. It builds on examples of online delivery elsewhere, along with models and methods developed within the module teaching team to provide you with unique experience in using statistical evidence to inform policymaking. This applied element is particularly important given the abstract and highly theoretical nature of much teaching in quantitative methods. Formative assessment will enable you to develop a 3,000-word report on a chosen policy area with complementary code and microsimulation output to be uploaded to an osf.io repository following feedback from the module teaching team.

We particularly encourage you to attend if you are a student from other Doctoral Training Programmes (e.g. North West Social Science Doctoral Training Partnership) or an academic at a UK and or non UK university and if you work in the public sector (Local Authorities, Civil Service, government, etc.) or third sector (think tanks, charities, unions, etc.).

Unit 1: Key concepts: an introduction to statistics and data science 

This unit enables students with some prior knowledge of quantitative methods to understand the key concepts around which to conduct statistical analysis and to engage in relevant forms of data science, specifically with regard to coding. In order to prepare you for the rest of the module and assessment, you will work with recent data on income and health, to understand the relationships as well as how we go about quantitative data science. 

Unit 2: Understanding coding 

This unit introduces basic data scientific principles and coding through a series of practical examples. You will explore general principles of coding using any platform, before working through a series of practical examples to understand the nature of analyses produced. 

Unit 3: Building your own tax-transfer model  

This unit enables you to develop you own tax-transfer model. This forms the basis for the analysis within the end of module report. You will use Python to create your own model and populate it with a dataset that will be provided in advance of the module’s start date. You will then begin to work through basic impacts from changes in taxes and benefits with a view to understanding and illustrating their impacts on poverty. 

Unit 4: Understanding advanced models  

This unit uses the cutting-edge Landman Tax-Transfer Model to understand and explore complex forms of economic microsimulation and to assess the strengths and weaknesses of different survey datasets. You will learn how to model specific impacts accurately and understand the economic context for analysis of innovative policies to address poverty and inequality. 

Unit 5: Persuading the politicians: how to deploy evidence to influence policy 

This unit sets out the putative commitment to evidence-based policy and unpicks the way in which specific forms of evidence seem to matter in different contexts. You will work through a series of examples of evidence regarding economic, health and electoral outcomes to frame the evidence produced in your own microsimulation to persuade relevant stakeholders. You will explore ways of presenting evidence for different stakeholders, such as civil servants, third sector bodies and academics. 

Each unit will contain a mixture of lectures, supervised practice sessions, group discussions and independent report development.