- Code STAT8056
- Unit Value 6 units
- Offered by Rsch Sch of Finance, Actuarial Studies & App Stats
- ANU College ANU College of Business and Economics
- Course subject Statistics
- Areas of interest Statistics, Mathematics
- Academic career PGRD
- Prof Alan Welsh
- Mode of delivery In Person
Second Semester 2015
See Future Offerings
This course is intended to follow on from Statistical Inference (STAT3013/8027) by providing a more advanced treatment of large sample approximation theory and some of its applications to statistical inference. The focus will be on developing a deeper theoretical understanding of some of the important statistical methods by developing the underlying theory. The objectives will be to achieve a deep understanding of particular statistical methods and to learn to use some advanced tools for analyzing and developing statistical methods.
Upon successful completion, students will have the knowledge and skills to:
On completion of this course students should have an understanding of and be able to apply the techniques outlined in the course description.
See the course outline on the College courses page. Outlines are uploaded as they become available.
2 Assignments (15% each), final examination (70%)
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10 hours per week. (2 1-hour lectures, 1 1-hour tutorial plus additional outside study time)
Requisite and Incompatibility
Tuition fees are for the academic year indicated at the top of the page.
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- Student Contribution Band:
- Unit value:
- 6 units
If you are an undergraduate student and have been offered a Commonwealth supported place, your fees are set by the Australian Government for each course. At ANU 1 EFTSL is 48 units (normally 8 x 6-unit courses). You can find your student contribution amount for each course at Fees. Where there is a unit range displayed for this course, not all unit options below may be available.
Offerings, Dates and Class Summary Links
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Class summaries, if available, can be accessed by clicking on the View link for the relevant class number.
|Class start date
|Last day to enrol
|Class end date
|Mode Of Delivery
|20 Jul 2015
|07 Aug 2015
|31 Aug 2015
|30 Oct 2015