Course overview
The aim of the course is to delve deeply into sophisticated statistical concepts and methodologies, empowering students with advanced theoretical knowledge and analytical skills essential for tackling complex statistical problems. Through rigorous exploration of topics such as exponential families and statistical decision theory, the students will develop a nuanced understanding of the theoretical foundations of statistical inference as well as develop a comprehensive understanding of optimal decision-making strategies in uncertain environments. Additionally, students will investigate key theorems and their applications in statistical estimation. Through theoretical exploration, students will gain the expertise needed to navigate and contribute to cutting-edge research in advanced statistical theory and methodology.
- Classical Statistical Theory
- Bayes And Decision Theory
- Advanced Topics
Course learning outcomes
- Propose statistical methodologies appropriate for the problem at hand
- Discern the assumptions which underpin validity of a particular method
- Apply the main theoretical results to a variety of situations
- Apply principles of statistical decision theory to a variety of problems
- Communicate results clearly