• 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 UGRD
  • Course convener
    • Prof Alan Welsh
  • Mode of delivery In Person
  • Co-taught Course
  • Offered in Second Semester 2019
    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.

Learning Outcomes

Upon successful completion, students will have the knowledge and skills to:

Upon successful completion of the requirements for this course, students should have the
knowledge and skills to:

• understand and be able to carry out maximum likelihood estimation and inference in simple statistical models with several parameters.  
• be able to apply Taylor series expansions to derive approximate sampling distributions and confidence intervals for transformed estimators.
• understand the basic concepts of robust estimation in statistics, be able to derive influence functions of estimators and use them to evaluate the robustness of estimators.
• understand and explain the different uses of randomisation in statistics.
• understand the basic principles of statistical inference and the issues they raise about how to do statistical inference.

Other Information

See the course outline on the College courses page. Outlines are uploaded as they become available. 

Indicative Assessment

Typical assessment may include, but is not restricted to: assignments and a final exam.

The ANU uses Turnitin to enhance student citation and referencing techniques, and to assess assignment submissions as a component of the University's approach to managing Academic Integrity. While the use of Turnitin is not mandatory, the ANU highly recommends Turnitin is used by both teaching staff and students. For additional information regarding Turnitin please visit the ANU Online website.

Workload

Students are expected to commit at least 10 hours per week to completing the work in this course. This will include at least 3 contact hours per week and up to 7 hours of private study time.

Requisite and Incompatibility

To enrol in this course you must have completed STAT3013.

Majors

Fees

Tuition fees are for the academic year indicated at the top of the page.  

If you are a domestic graduate coursework or international student you will be required to pay tuition fees. Tuition fees are indexed annually. Further information for domestic and international students about tuition and other fees can be found at Fees.

Student Contribution Band:
2
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.

Units EFTSL
6.00 0.12500
Domestic fee paying students
Year Fee
2019 $3840
International fee paying students
Year Fee
2019 $5460
Note: Please note that fee information is for current year only.

Offerings and Dates

The list of offerings for future years is indicative only

Second Semester

Class number Class start date Last day to enrol Census date Class end date Mode Of Delivery Class Summary
8037 22 Jul 2019 29 Jul 2019 31 Aug 2019 25 Oct 2019 In Person View

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