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During 2021 we will continue to support students who need to study remotely due to the ongoing impacts of COVID-19 and travel restrictions. Make sure you check the location code when selecting a unit outline or choosing your units of study in Sydney Student. Find out more about what these codes mean. Both remote and on-campus locations have the same learning activities and assessments, however teaching staff may vary. More information about face-to-face teaching and assessment arrangements for each unit will be provided on Canvas.

Unit of study_

STAT5611: Statistical Methodology

The great power of the discipline of Statistics is the possibility to make inferences concerning a large population based on only observing a relatively small sample from it. Of course, this "magic" does not come without a price, we must construct statistical models to approximate these populations and samples from them, develop mathematical tools using probability theory, appreciate the limitations of our methods and, most importantly, understand what assumptions need to be made for such inferences to be valid, and develop ways to check these assumptions. Implementing these methods to possibly complex data structures is also a challenge that must be overcome. 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) advanced survival analysis, extreme value theory and statistical methods in bioinformatics.

Code STAT5611
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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Familiarity with probability theory at 4000 level (e.g., STAT4211 or STAT4214 or equivalent) and with statistical modelling (e.g., STAT4027 or equivalent). 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. Communicate coherent mathematical arguments appropriately to student and expert audiences, both orally and through written work.

Unit outlines

Unit outlines will be available 2 weeks before the first day of teaching for the relevant session.

There are no unit outlines available online for previous years.