Quantitative

Designed for the applied users of R, this master-class will show you how to access spatial data from a number of sources, match this with geographic shape files, analyse spatial patterns, link these data to information from surveys, and create interactive maps to highlight important findings.

The aim of this course is to provide students with an accessible introduction to the fundamentals of quantitative political science research.

This masterclass introduces students to choice models, discusses and contrasts the family of available model structures, and covers both estimation on data and the use of models to produce outputs for policy. 

This master-class has two objectives – to teach the design principles required to make plots that really have an impact on the reader, and to teach the practical skills required to create these plots within the R software package.

Survival analysis is used to find out the time it takes for an event of interest to occur (e.g., death, birth, recidivism). This course is designed as an introduction to survival analysis.

This course covers enough of the statistical material for the intelligent use of multivariate statistical techniques. The approach is informal and applied rather than emphasising algebraic manipulation or proofs.

A step-by-step, interactive introduction to Python for participants with no experience with this software package. 

This masterclass offers a step-by-step, interactive introduction to R and RStudio for participants with no experience with these software packages.

This short webinar demonstrates the set up and execution of an evaluation questionnaire. It shows how to use LimeSurvey for the first time, and gives some hints at the advanced functionality available for more experienced users.

This is an online, self paced introduction to core concepts, methods and tools in computational social science focusing on three themes: (1) networks as data; (2) text as data; (3) prediction and simulation.

This course offers hands-on training in R programming for quantitative political analysis, paired with practical and responsible techniques for using AI assistants to write, debug, and verify data analysis code. 

This course introduces the principles of survey design and standard practices in the field, with particular emphasis on measuring political attitudes, public opinion and electoral behaviour.

Whether you're looking to add AI to your research toolkit or just curious about what deep learning can do, this masterclass will give you the foundation you need to start experimenting with confidence.

This 5-day course aims to provide you with the understanding and experience to undertake a basic research project in the social or health sciences using Stata as the statistical tool.

This masterclass introduces students to choice models, discusses and contrasts the family of available model structures, and also talks about the data requirements, model estimation, and the use of models to produce outputs for policy. 

This course provides an overview of the fundamentals of SEM. As well as the statistical theory, an overview of the many applications and capabilities of SEM is given.

This course is designed as an introduction to mixed effects modelling. These models involve data arising from longitudinal studies or studies where the data exhibits some form of hierarchy, and sometimes referred to as multilevel modelling.

An introduction to Large Language Models (LLMs) in the context of social sciences, offering hands-on, practical experience - no coding expertise or advanced maths skills required.
 

Designed for mixed methods and qualitative researchers, this course covers data collection and research design, visualisation and basic analytic methods used in social network research.

How to set up, conduct and export your data for a web based survey in the freely available Limesurvey web survey software system.

This course provides an overview of Longitudinal Data Analysis. As well as the statistical theory, an overview of the many applications and capabilities of LDA is given.

This 5-day intermediate course will help you choose from a range of statistical procedures to analyse your data. It aims to provide participants with an ability to understand, run and interpret these procedures.   

A 5-day introductory unit in statistical methods with the emphasis on statistical techniques applicable to the social sciences, although these introductory techniques are also relevant to the health sciences.

A hands-on introduction to applied choice modelling using the open-source Apollo software for the estimation of choice models. 

We will explore the key features and different types of mixed method design; critically analyse the benefits and challenges associated with the design and implementation of each design type; and the analysis and write-up of mixed method studies.

This 3-day course is designed to cover the fundamental principles of Structural Equation Modeling (SEM) and introduce the AMOS and/or Mplus software packages to estimate structural equation models.

This course is designed as an advanced course in Structural Equation Modeling (SEM) for existing AMOS and/or Mplus users. 

This course covers enough of the statistical material for the intelligent use of multivariate statistical techniques. The approach is informal and applied rather than emphasising algebraic manipulation or proofs.

This course will help build participants’ ability to work with data in R and undertake rigorous statistical analysis, including spatial analysis and linear regression, creating publication-standard graphs of the results. 

An introduction to supervised machine learning techniques for data science, providing an interactive step-by-step guide to running some of the standard statistical regression and classification machine learning models that every data scientist should know. 

Collecting survey data can be expensive and time-consuming; therefore it is appropriate to ensure that usable and reliable data are collected. This 2-day course is designed to prepare participants to build hard copy or internet surveys to meet a variety of needs.

Designed as an applied introduction to SEM using Stata, this course aims to provide participants with a sound understanding of when to use SEM and how to assess and report their models.

An introduction to linear and non-linear predictive models, providing an interactive step-by-step guide to running these models, and key diagnostics using the R software platform.

Designed as an applied introduction to SEM using Stata, this course aims to provide participants with a sound understanding of when to use SEM and how to assess and report their models

Taught by an instructor with real-world experience as a campaign consultant, survey researcher and data scientist, this 2-day masterclass will focus on teaching you about survey design.

Multivariate analysis of variance (MANOVA) is an extension of analysis of variance (ANOVA) to deal with two or more continuous outcomes or dependent variables. This technique is used to determine whether multiple levels of independent variables on their own or in combination with one another have an effect on the outcome variables.

A course for participants who have experience in qualitative or quantitative research and who are interested in applying QCA in their current or future studies.