Applied Statistics (MSc)

The MSc Applied Statistics delivers rigorous training in statistical methodologies, enabling the analysis of extensive datasets and the resolution of real-world issues. A robust foundation in probability, statistics, and data science is established, allowing for the application of contemporary techniques to practical challenges. Through compulsory modules, core topics such as statistical computing, data science, and fundamental theory are covered, forming the basis for advanced specialisation. Areas of focus include generalised linear models, Bayesian and likelihood inference, statistical computing with R and Python, compute-intensive methods, and the analysis of complex survey data. Further study encompasses longitudinal and multilevel data modelling, along with data science foundations and supervised machine learning.

Participants join one of the largest communities of statisticians globally, benefiting from world-class teaching and research. Academic staff collaborate with diverse organisations, including the United Nations, the World Bank, and various government departments. This research directly informs the course content, incorporating findings on survey design, sampling, small-area estimation, and the analysis of integrated survey, administrative, and geospatial data, as well as 'big data'. Consequently, upon completion, the expertise required to address complex data challenges across academia, industry, and government sectors is secured.