- Students are to follow the requirements of the Handbook for the year they commenced the course.
However, the subject links below do not contain the subject information for the current year. You can view current subject information through the new Course Handbook.
Master of Statistics | 2018
Testamur Title of Degree: | Master of Statistics |
Abbreviation: | MStat |
UOW Course Code: | 427 |
CRICOS Code: | 083830G |
Total Credit Points: | 96 |
Duration: | 2 years full-time or part-time equivalent |
Home Faculty: | Faculty of Engineering & Information Sciences |
Intake Session(s): | Autumn/Spring |
Delivery Mode: | On-campus (Face-to-face) |
Delivery Campus: | Wollongong |
Overview
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.
Entry Requirements and Credit Arrangements
Information on academic and English language requirements, as well as eligibility for credit for prior learning, is available from the Course Finder.
Course 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 to demonstrate:
| CLO | Description | ||||||
|---|---|---|---|---|---|---|---|
| 1 | Demonstrate advanced and integrated understanding of a complex body of knowledge in statistics. | ||||||
| 2 | Expert, specialised cognitive and technical skills in statistics to independently analyse, critically reflect on and synthesise complex information, problems and theories. | ||||||
| 3 | Interpret and transmit statistical knowledge, skills and ideas to specialist and non-specialist audiences. | ||||||
| 4 | Apply knowledge and skills ethically to demonstrate autonomy and expert judgement as a statistician. | ||||||
Course 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 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 Diploma in Mathematics. Please discuss options with the Coordinator 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 Coordinator of the Master of Statistics.
| Subject Code | Subject Name | Credit Points | Session(s) |
|---|---|---|---|
| Year 1 | |||
| MATH907 | Research Methods** | 6 | Autumn |
| Plus: | |||
| Four subjects selected from the list of Preparation subjects or Foundation subjects below* | 24 | ||
| Plus: | |||
| Three subjects selected from the list of Foundation subjects below** | 18 | ||
| Year 2 | |||
| STAT991 | Project | 12 | Annual, Spring 2018/Autumn 2019 |
| STAT933 | Advanced Topics in Statistics | 24 | Annual, Spring 2018/Autumn 2019 |
| Plus: | |||
| One 6- credit-point 900 level MATH/STAT/INFO/CSCI subject (see the list below). Ask degree coordinator for possible additional 900-level subjects on offer. | 6 | ||
| Plus: | |||
| One subject selected from the list of Foundation Subjects, or any 6-credit-point 900 level subject | 6 | ||
| * 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 Coordinator 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 Coordinator of the Master of Statistics. | |||
Foundation Subjects
| Subject Code | Subject Name | Credit Points | Session(s) |
|---|---|---|---|
| INFO812 | Mathematics for Cryptography | 6 | Autumn |
| MATH802 | Differential Equations 3 (Enhanced) | 6 | Autumn |
| MATH805 | Partial Differential Equations (Enhanced) | 6 | Spring |
| MATH817 | Financial Calculus (Enhanced) | 6 | Autumn |
| MATH818 | Operations Research (Enhanced) | 6 | Spring |
| MATH821 | Numerical Analysis (Enhanced) | 6 | Spring |
| STAT804 | Applied Probability and Financial Risk (Enhanced) | 6 | Autumn |
| STAT832 | Linear and Generalised Linear Models (Enhanced) | 6 | Spring |
| STAT833 | Statistical Inference Enhanced | 6 | Spring |
| STAT835 | Sample Surveys and Experimental Design (Enhanced) | 6 | Autumn |
| STAT971 | Preliminary Topics in Statistics A | 6 | Autumn, Spring |
| STAT972 | Preliminary Topics in Statistics B | 6 | Autumn, Spring |
Preparation Subjects
| Subject Code | Subject Name | Credit Points | Session(s) |
|---|---|---|---|
| MTH8201 | Multivariate and Vector Calculus | 6 | Autumn |
| MTH8202 | Differential Equations 2 | 6 | Spring |
| MTH8203 | Linear Algebra | 6 | Autumn |
| MTH8204 | Complex Variables and Group Theory | 6 | Spring |
| MTH8231 | Probability and Random Variables | 6 | Autumn |
| MTH8232 | Estimation and Hypothesis Testing | 6 | Spring |
| MTH8302 | Differential Equations 3 | 6 | Autumn |
| MTH8305 | Partial Differential Equations | 6 | Spring |
| MTH8317 | Financial Calculus | 6 | Autumn |
| MTH8318 | Operations Research | 6 | Spring |
| MTH8321 | Numerical Analysis | 6 | Spring |
| MTH8304 | Applied Probability and Financial Risk | 6 | Autumn |
| MTH8332 | Linear and Generalised Linear Models | 6 | Spring |
| MTH8333 | Statistical Inference | 6 | Spring |
| MTH8335 | Sample Surveys and Experimental Design | 6 | Autumn |
900-Level MATH/STAT/INFO/CSCI Subjects
| 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 |
| STAT920 | Stochastic Methods in Finance | 6 | Autumn |
| STAT981 | Advanced Topics in Statistics A | 6 | Autumn |
| STAT982 | Advanced Topics in Statistics B | 6 | Autumn, Spring |
Note: The content of the subjects STAT971, STAT972, 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 Coordinator 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.
Professional Recognition/Accreditation
Graduates of the Master of Statistics with a relevant undergraduate degree and 4-6 years' work experience are eligible to apply for membership as an Accredited Statistician with the Statistical Society of Australia.
Other Information
Students who satisfactorily complete the Master of Statistics degree are eligible to apply for entry to the Master of Philosophy.
Students who complete the Master of Statistics with a weighted average mark of 70 or higher are eligible to apply for entry to the Doctor of Philosophy.
For further information please email: eis@uow.edu.au or Academic Program Director