Statistical Inference (STAT3013)


In this course we will study basic topics in modern statistical inference. This will include traditional concepts of mathematical statistics: likelihood estimation, method of moments, properties of estimators, exponential families, decision-theory approach to hypothesis testing, likelihood ratio test as well as more recent approaches such as Bayes estimation, Empirical Bayes and nonparametric estimation. During the computer classes (using R software package) we will illustrate the various estimation techniques and give an introduction to computationally intensive methods like Monte Carlo, Gibbs sampling and EM-algorithm.

Further unit of study information


Three 1 hour lectures, one 1 hour tutorial and one 1 hour computer laboratory per week.


One 2 hour exam, assignments and/or quizzes, and computer practical reports (100%)

Faculty/department permission required?


Unit of study rules

Prerequisites and assumed knowledge

(STAT2011 or STAT2911) and (STAT2012 or STAT2912), (STAT2011 or STAT2911) and (STAT2012 or STAT2912), (STAT2011 or STAT2911) and (STAT2012 or STAT2912)


STAT3901, STAT3001, STAT3913, STAT3901, STAT3001, STAT3913, STAT3901, STAT3001, STAT3913

Study this unit outside a degree

Non-award/non-degree study

If you wish to undertake one or more units of study (subjects) for your own interest but not towards a degree, you may enrol in single units as a non-award student.

Cross-institutional study

If you are from another Australian tertiary institution you may be permitted to underake cross-institutional study in one or more units of study at the University of Sydney.