COURSE CURRICULUM

The MSc Statistics program offers a comprehensive curriculum designed to equip students with both theoretical knowledge and practical skills in statistical analysis, data science, and computational methods. Core modules provide in-depth training in generalized linear models, likelihood and Bayesian inference, and computationally intensive statistical methods, giving students the ability to apply modern statistical techniques to real-world problems. Programming and data science skills are developed through modules in Python, R, and fundamentals of data science, alongside statistical computing and machine learning, enabling students to handle, analyse, and interpret complex datasets. Case study modules and the Statistics Project provide opportunities for independent research, allowing students to conduct open-ended investigations and apply advanced methods to applied problems, enhancing problem-solving, project management, and research communication skills. Optional modules allow further specialisation in areas such as clinical trials, design of experiments, epidemiological methods, flexible regression, forecasting, statistical genetics, and survival models, broadening expertise in specific applications of statistics. Through this combination of core, elective, and research-focused modules, students gain the technical, analytical, and practical skills necessary for careers in data science, finance, pharmaceuticals, government, and other industries, or to pursue advanced academic study at the PhD level.