Computational Statistical Methods (STAT5003)


The objectives of this unit of study are to develop an understanding of modern computationally intensive methods for statistical inference, exploratory data analysis and data mining. Advanced computational methods for statistics will be introduced, including univariate, multivariate and combinatorial optimisation methods and simulation methods, such as Gibbs sampling, the Bootstrap, Monte Carlo and the Jackknife approach. In addition, the unit will demonstrate how to apply the above techniques effectively for use on large data sets in practice. Finally, this unit will show how to make inferences about populations of interest in data mining problems.

Our courses that offer this unit of study

Further unit of study information


Two lectures and one tutorial per week.


2 hour examination (60%), assignments (20%), quizzes (20%)


Computational Statistics, Geof H. Givens, Jennifer A. Hoeting, Wiley (2005)

Faculty/department permission required?


Unit of study rules



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.