The course aims to provide students with some theoretical background and mathematical tools in theoretical statistics to access the literature on biostatistics methodologies and applications. Topics covered include: efficiency of estimators; efficiency of tests; empirical processes; functional delta method; quantile and order statistics; L-statistics; bootstrap; high-dimensional models, gradient descent optimization. Selected topics such as empirical likelihood, U-statistics, counting process methods in survival analysis, functional data analysis, nonparametric estimation, shape-constrained inference, and semiparametric inference and efficiency will also be included.

Examination questions are designed to see how well students have achieved the learning objectives and acquired the requisite techniques for problem-solving.

To pass the course, students are required to obtain a minimum of 40% in continuous assessment and a minimum of 35% in the examination.