In today's data-rich world more and more people from diverse fields are needing to perform statistical analyses and indeed more and more tools for doing so are becoming available; it is relatively easy to point and click and obtain some statistical analysis of your data. But how do you know if any particular analysis is indeed appropriate? Is there another procedure or workflow which would be more suitable? Is there such a thing as the best possible approach in a given situation? All of these questions (and more) are addressed in this unit. You will study the foundational core of modern statistical inference, including classical and cutting-edge theory and methods of mathematical statistics with a particular focus on various notions of optimality. The first part of the unit covers various aspects of distribution theory which are necessary for the second part which deals with optimal procedures in estimation and testing. The framework of statistical decision theory is used to unify many of the concepts. You will apply the methods learnt to real-world problems in laboratory sessions. By completing this unit you will develop the necessary skills to confidently choose the best statistical analysis to use in many situations.
Unit details and rules
Academic unit | Mathematics and Statistics Academic Operations |
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Credit points | 6 |
Prerequisites
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|
STAT2X11 |
Corequisites
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|
None |
Prohibitions
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|
STAT3913 or STAT3013 or STAT3923 |
Assumed knowledge
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|
DATA2X02 or STAT2X12 |
Available to study abroad and exchange students | Yes |
Teaching staff
Coordinator | Michael Stewart, michael.stewart@sydney.edu.au |
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Lecturer(s) | Rachel Wang, rachel.wang@sydney.edu.au |
Michael Stewart, michael.stewart@sydney.edu.au |