COURSE CURRICULUM

The MSc Applied Statistics program provides comprehensive training in advanced statistical theory, data analysis, and computational techniques. Core modules cover key areas such as complex survey data analysis, generalized linear models, likelihood and Bayesian inference, and further topics in statistical modelling, equipping students to handle a wide range of real-world data challenges. The course also includes hands-on learning through modules like statistical computing in R and computationally intensive statistical methods, developing strong programming and analytical skills. Students gain practical experience in designing surveys, assessing data quality, and conducting research with effective communication skills, culminating in an independent dissertation project guided by expert supervision. Optional modules allow students to tailor their studies to specific interests or career goals, with topics including demographic and epidemiological methods, design of experiments, evaluation and monitoring, qualitative and quantitative social science research, statistical genetics, and survival models. Through this combination of theoretical understanding, computational training, and applied research, the program prepares graduates for careers in data analysis, statistics, research, and policy development across diverse fields such as government, healthcare, social science, and industry, as well as for further academic or doctoral study.