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Rsch Sch of Finance, Actuarial Studies & App Stats · ANU College of Business and Economics
Statistical Learning is a course designed for students who need to carry out statistical analysis, or “learning”, from real data. Emphasis will be placed on the development of statistical concepts and statistical computing. The content will be motivated by problem-solving in many diverse areas of application. This course will cover a range of topics in statistical learning including linear and non-linear regression, classification techniques, resampling methods (e.g., the bootstrap), regularisation methods, tree based methods and unsupervised learning techniques (e.g. principle components analysis and clustering).
The research-based assessment will consist of a nested project.
Learning outcomes 1, 2, 3, 4, 5, 6, 7
The other assessment may include, but is not restricted to assignments, projects, presentations and other assessment tasks as appropriate.
Learning outcomes 1, 2, 3, 4, 5, 6, 7
Students are expected to commit 130 hours of work in completing this course. This includes time spent in scheduled classes and self-directed study time.
Information about the prescribed textbook will be available via the class summary.