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This is an advanced course that prepares students for research careers in statistics, which nowadays typically require a combination of applied, methodological and theoretical skills. By considering a variety of statistical topics in depth it introduces students to the technical skills and methods of proof needed to conduct research in modern statistics. Topics covered may include U-statistics, asymptotic distributions of statistics, inference in parametric and nonparametric models, curve estimation, Edgeworth expansions and the bootstrap and sequential methods.
Intended learning outcomes
LO1 A deep understanding of some advanced topics in statistical theory.
LO2 Mastery of the technical skills needed for further research in statistics
LO3 Preparation for a research career in statistics.
LO4 Familiarity with several major texts in mathematical statistics.
- In addition to learning specific skills that will assist students in their future careers in science, they will have the opportunity to develop generic skills that will assist them in any future career path. These include: - problem-solving skills: the ability to engage with unfamiliar problems and identify relevant solution strategies; - analytical skills: the ability to construct and express logical arguments and to work in abstract or general terms to increase the clarity and efficiency of analysis; - collaborative skills: the ability to work in a team; - time-management skills: the ability to meet regular deadlines while balancing competing commitments
Last updated: 2 December 2019