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Unit of study_

STAT5610: Advanced Inference

2024 unit information

The great power of the discipline of Statistics is the possibility to make inferences concerning a large population based on optimally learning from increasingly large and complex data. Critical to successful inference is a deep understanding of the theory when the number of samples and the number of observed features is large and require complex statistical methods to be analysed correctly. In this unit you will learn how to integrate concepts from a diverse suite of specialities in mathematics and statistics such as optimisation, functional approximations and complex analysis to make inferences for highly complicated data. In particular, this unit explores advanced topics in statistical methodology examining both theoretical foundations and details of implementation to applications. The unit is made up of distinct modules that may include (but are not restricted to) asymptotic theory for statistics and econometrics, theory and algorithms for statistical learning with big data, and introduction to optimal semiparametric optimality.

Unit details and rules

Managing faculty or University school:

Science

Study level Postgraduate
Academic unit Mathematics and Statistics Academic Operations
Credit points 6
Prerequisites:
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None
Corequisites:
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None
Prohibitions:
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None
Assumed knowledge:
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Strong background in probability theory and statistical modelling. Please consult with the coordinator for further information

At the completion of this unit, you should be able to:

  • LO1. Demonstrate a coherent and advanced understanding of key concepts in statistical methodology.
  • LO2. Apply fundamental principles and results in statistics to solve given problems.
  • LO3. Distinguish and compare the properties of different types of statistical models and statistical methods applicable to them.
  • LO4. ​Identify assumptions required for various statistical methods to be valid and devise methods for testing these assumptions.
  • LO5. ​Devise statistical solutions to complex problems.
  • LO6. Compose correct proofs of unfamiliar general results in statistical methodology.
  • LO7. Compose correct proofs of unfamiliar general results in statistical methodology

Unit availability

This section lists the session, attendance modes and locations the unit is available in. There is a unit outline for each of the unit availabilities, which gives you information about the unit including assessment details and a schedule of weekly activities.

The outline is published 2 weeks before the first day of teaching. You can look at previous outlines for a guide to the details of a unit.

Session MoA ?  Location Outline ? 
Semester 2 2024
Normal day Camperdown/Darlington, Sydney
Session MoA ?  Location Outline ? 
Semester 2 2020
Normal day Camperdown/Darlington, Sydney
Semester 2 2022
Normal day Camperdown/Darlington, Sydney
Semester 2 2022
Normal day Remote

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Modes of attendance (MoA)

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Important enrolment information

Additional advice

This unit is only available in even years.