Master of Statistics
University of Wollongong
About
The Master of Statistics is designed for candidates holding a Bachelor degree with a minor (or major) in mathematics or statistics, to upgrade statistical skills, and to educate the candidate to undertake advanced statistical work in industry, commerce or government, including the ability to communicate effectively with others.
This program is also designed to prepare students for further postgraduate research degrees in statistics.
Structure
The full degree will normally occupy four (4) sessions of full-time study or eight (8) sessions of part-time study, and requires satisfactory completion of at least 96 credit points, as set out in the suggested course program below. All candidates (including those who receive recognition of prior learning) must complete at least 48 credit points of 900 level subjects.
Candidates who accrue 48 credit points towards the Master of Statistics and who cannot or do not wish to continue may be eligible to receive a Graduate Certificate in Mathematical Studies. Please discuss options with the Academic Program Director of the Master of Statistics.
Students must choose a program of study that suits their entry level. The final program of study is subject to the approval of the Academic Program Director of the Master of Statistics.
Year 1
| Subject Code | Subject Name | Credit Points | Session(s) |
|---|---|---|---|
| MATH907 | Research Methods** | 6 | Autumn |
Plus:
| Subject Code | Subject Name |
|---|---|
| Four subjects selected from the list of Preparation subjects or Foundation subjects below* | 24 |
Plus:
| Subject Code | Subject Name |
|---|---|
| Three subjects selected from the list of Foundation subjects below** | 18 |
Year 2
| Subject Code | Subject Name | Credit Points | Session(s) |
|---|---|---|---|
| STAT991 | Project | 12 | Annual, Spring 2020/Autumn 2021 |
| STAT933 | Advanced Topics in Statistics*** | 24 | Annual, Spring 2020/Autumn 2021 |
Plus:
| Subject Code | Subject Name |
|---|---|
| One 900-level MATH/STAT/INFO/CSCI subject from the list below. Ask the Academic Program Director for possible additional 900-level subjects on offer. | 6 |
Plus:
| Subject Code | Subject Name |
|---|---|
| One subject selected from the list of Foundation Subjects, or any 6-credit-point 900 level subject | 6 |
It is possible to take 900-level subjects from other disciplines with the approval of the Academic Program Director of the Master of Statistics.
* Students who have completed an appropriate combination of subjects in an approved mathematics or statistics major may be exempt from one or more of these subjects. Please apply to the Academic Program Director of the Master of Statistics.
** Students who have an approved Honours degree in mathematics or statistics may be exempt from some of these subjects. Please apply to the Academic Program Director of the Master of Statistics.
*** Before enrolling in this subject, it is essential that candidates consult with the Academic Program Director of the Master of Statistics
| Subject Code | Subject Name | Credit Points | Session(s) |
|---|---|---|---|
| MTH8201 | Multivariate and Vector Calculus | 6 | Autumn |
| MTH8202 | Differential Equations. Analysis and Application | 6 | Autumn |
| MTH8203 | Linear Algebra and Groups | 6 | Spring |
| MTH8204 | Complex Variables and Group Theory | 6 | Not available in 2020 |
| MTH8212 | Mathematical Modelling | 6 | Spring |
| MTH8222 | Real Analysis | 6 | Autumn |
| Subject Code | Subject Name | Credit Points | Session(s) |
|---|---|---|---|
| INFO812 | Mathematics for Cryptography | 6 | Autumn |
| MATH805 | Partial Differential Equations (Enhanced) | 6 | Autumn |
| MATH812 | Advanced Applied Mathematical Modelling (Enhanced) | 6 | Spring |
| MATH813 | Case Studies in Applied Mathematics (Enhanced) | 6 | Spring |
| MATH817 | Financial Mathematics (Enhanced) | 6 | Autumn |
| MATH818 | Optimisation and Applications (Enhanced) | 6 | Spring |
| MATH821 | Numerical Analysis (Enhanced) | 6 | Not available in 2020 |
| MATH822 | Algebra (Enhanced) | 6 | Spring |
| MATH823 | Topology (Enhanced) | 6 | Not available in 2020 |
| MATH824 | Calculus of Variations & Elementary Differential Geometry (Enhanced) | 6 | Not available in 2020 |
| MATH825 | Wavelets (Enhanced) | 6 | Not available in 2020 |
| STAT804 | Stochastic Methods in Statistical Analysis (Enhanced) | 6 | Spring |
| Subject Code | Subject Name | Credit Points | Session(s) |
|---|---|---|---|
| CSCI933 | Machine Learning Algorithms and Applications | 6 | Autumn |
| INFO911 | Data Mining and Knowledge Discovery | 6 | Autumn |
| INFO912 | Mathematics for Cryptography | 6 | Autumn |
| MATH942 | Numerical Methods in Finance | 6 | Spring |
| STAT981 | Advanced Topics in Statistics A | 6 | Autumn, Spring |
| STAT982 | Advanced Topics in Statistics B | 6 | Autumn, Spring |
Note: The content of the subjects STAT971, STAT933, STAT981 and STAT982 may vary each year. A list of topics that will be covered within the above subjects in a particular year will be available from the Academic Program Director of the Master of Statistics before the beginning of each session. These topics include those offered by UOW staff, those from the Australian Mathematical Sciences Institute Summer and Winter graduate schools and classes available remotely, via the access grid room. Potential topics include Modern Inference, Advanced Data Analysis, Survey Design and Analysis, Statistical Consulting, and Experimental Design.
Academic advice should be sought prior to enrolment as the availability of subjects may vary each year.
Learning outcomes
Course Learning Outcomes are statements of learning achievement that are expressed in terms of what the learner is expected to know, understand and be able to do upon completion of a course. Students graduating from this course will be able:
CLO Description 1 To demonstrate advanced and integrated understanding of a complex body of knowledge in statistics. 2 To demonstrate expert, specialised cognitive and technical skills in statistics. 3 To independently analyse, critically reflect on and synthesise complex information, problems and theories. 4 To interpret and transmit statistical knowledge, skills and ideas to specialist and non-specialist audiences. 5 To apply knowledge and skills ethically to demonstrate autonomy and expert judgement as a statistician.
Institution
