COURSE CURRICULUM

The Statistics MSc provides a rigorous and versatile curriculum designed to develop advanced analytical, computational, and problem-solving skills. Core modules such as The Statistician’s Toolkit, Bayesian Statistics and Computational Methods, and Machine Learning build a strong foundation in modern statistical techniques and data-driven modelling. Modules like Sampling Theory and Design of Experiments and Time Series focus on the design, collection, and analysis of data over time, equipping students to handle complex real-world datasets. Medical Statistics introduces the application of statistical methods in healthcare and clinical research, emphasizing evidence-based decision-making. The Dissertation allows students to conduct an independent research project, applying theoretical knowledge to a specific statistical challenge. In addition, students may tailor their learning by selecting up to 30 credits of optional modules, with approval, from areas such as Data Modelling and Machine Intelligence, Optimisation, Economic Evaluation, Epidemiology, and Qualitative Research Design. These options broaden expertise across interdisciplinary applications of statistics in health, economics, and computational science. The course combines theoretical depth with practical relevance, preparing graduates for diverse careers in data analysis, research, finance, healthcare, and technology, or for further academic study in statistics, data science, or quantitative research fields.