• Offered by Rsch Sch of Finance, Actuarial Studies & App Stats
  • ANU College ANU College of Business and Economics
  • Classification Advanced
  • Course subject Statistics
  • Areas of interest Statistics
  • Academic career PGRD
  • Course convener
    • Dr Anton Westveld
  • Mode of delivery In Person
  • Co-taught Course
  • Offered in First Semester 2016
    See Future Offerings

This course introduces students to the basic theory behind the development and assessment of statistical analysis techniques in the areas of point and interval estimation and hypothesis testing.

Topics include: Point estimation methods, including method of moments and maximum likelihood; Bias and variance; Mean-squared error and the Cramer-Rao inequality; Sufficiency, completeness and exponential families; the Rao-Blackwell theorem and uniformly minimum variance unbiased estimators; Bayesian estimation methods; Resampling estimation methods, including the jackknife and the bootstrap; Confidence interval construction methods, including likelihood-based intervals, inversion methods, intervals based on pivots and simple resampling-based percentile intervals; Highest posterior density and Bayesian credibility regions; Likelihood ratio tests and the Neymann-Pearson lemma; Power calculations and uniformly most powerful tests; Rank-based non-parametric tests, including the sign-test and Wilcoxon tests.

Learning Outcomes

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

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

  • explain in detail the notion of a parametric model and point estimation of the parameters of those models.
  • explain in detail and demonstrate approaches to include a measure of accuracy for estimation procedures and our confidence in them by examining the area of interval estimation.
  • demonstrate the plausibility of pre-specified ideas about the parameters of the model by examining the area of hypothesis testing.
  • explain in detail and demonstrate the use of non-parametric statistical methods, wherein estimation and analysis techniques are developed that are not heavily dependent on the specifications of an underlying parametric model.
  • demonstrate computational skills to implement various statistical inferential approaches.

Other Information

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

Indicative Assessment

  • Tutorial Question - 5%
  • Presentation/Project - 15%
  • Mid-Semester Exam - 20% or 0%, redeemable in favour of the final
  • Compulsory Final Exam - 60% or 80%

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10 hours per week.

Requisite and Incompatibility

To enrol in this course you must have completed STAT2001/STAT6039

Assumed Knowledge




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:
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.

6.00 0.12500
Domestic fee paying students
Year Fee
2016 $3480
International fee paying students
Year Fee
2016 $4638
Note: Please note that fee information is for current year only.

Offerings, Dates and Class Summary Links

ANU utilises MyTimetable to enable students to view the timetable for their enrolled courses, browse, then self-allocate to small teaching activities / tutorials so they can better plan their time. Find out more on the Timetable webpage.

The list of offerings for future years is indicative only.
Class summaries, if available, can be accessed by clicking on the View link for the relevant class number.

First Semester

Class number Class start date Last day to enrol Census date Class end date Mode Of Delivery Class Summary
3516 15 Feb 2016 26 Feb 2016 31 Mar 2016 27 May 2016 In Person N/A

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