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Probability for Inference (MAST30020)
Undergraduate level 3Points: 12.5On Campus (Parkville)
Overview
Availability | Semester 1 |
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Fees | Look up fees |
This subject introduces a measured-theoretic approach to probability theory and presents its fundamentals concepts and results.
Topics covered include: probability spaces and random variables, expectation, conditional expectation and distributions, elements of multivariate distribution theory, modes of convergence in probability theory, characteristics functions and their application in key limit theorems.
Intended learning outcomes
On completion of this subject, students should be able to:
- Formulate the fundamentals of modern probability theory;
- Interpret univariate and multivariate probability distributions;
- Construct general conditional expectations;
- Describe and compare different modes of convergence of random variables and distributions;
- Evaluate different approaches to proving basic limit theorems of probability theory and their uses in statistical applications.
Generic skills
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: 21 January 2025