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Unit of study_
STAT3023: Statistical Inference
2024 unit information
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
Managing faculty or University school:
Mathematics and Statistics Academic Operations
| Code | STAT3023 |
|---|---|
| Academic unit | Mathematics and Statistics Academic Operations |
| Credit points | 6 |
|
Prerequisites:
?
|
STAT2X11 |
|---|---|
|
Corequisites:
?
|
None |
| Prohibitions:
?
|
STAT3913 or STAT3013 or STAT3923 |
| Assumed knowledge:
?
|
DATA2X02 or STAT2X12 |
At the completion of this unit, you should be able to:
- LO1. deduce the (limiting) distribution of sums of random variables using moment-generating functions
- LO2. derive the distribution of a transformation of two (or more) continuous random variables
- LO3. derive marginal and conditional distributions associated with certain multivariate distributions
- LO4. classify many common distributions as belonging to an exponential family
- LO5. derive and implement maximum likelihood methods in various estimation and testing problems
- LO6. formulate and solve various inferential problems in a decision theory framework
- LO7. derive and apply optimal procedures in various problems, including Bayes rules, minimax rules, minimum variance unbiased estimators and most powerful tests.
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 |
Outline unavailable
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Modes of attendance (MoA)
This refers to the Mode of attendance (MoA) for the unit as it appears when you’re selecting your units in Sydney Student. Find more information about modes of attendance on our website.
