Skip to main content
Unit of study_

Computational Statistical Methods - STAT5003

Year - 2018

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.

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: Science

Semester 2

30 Jul 2018

Department/School: Mathematics and Statistics Academic Operations
Study Mode: Normal (lecture/lab/tutorial) evening
Census Date: 31 Aug 2018
Unit of study level: Postgraduate
Credit points: 6.0
EFTSL: 0.125
Available for study abroad and exchange: No
Faculty/department permission required? Yes
More details
Unit of Study coordinator: A/Prof Shelton Peiris
HECS Band: 2
Courses that offer this unit

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 undertake cross-institutional study in one or more units of study at the University of Sydney.

To help you understand common terms that we use at the University, we offer an online glossary.