Note: This course is not available in 2026.
Course overview
- Description
The Master of Statistics is designed for students with a solid mathematical background (multivariable calculus, linear algebra and probability theory), who are seeking to specialise in Statistics and Data Analysis. The program includes units focusing on the theory behind the methods, and units focusing on data modelling and applied statistics. The compulsory research component provides experience in solving problems for those aspiring to a career in data analysis or further research in Statistics. Students will have the opportunity to apply data analysis methods across a range of areas, including finance, healthcare, environmental science, engineering, and medical and biological sciences.
- Course title
- Master of Statistics (coursework and dissertation)
- Award abbreviation
- MStats
- Course code
- 60610
- Course type
- Master's degree by coursework and dissertation
- Status
- Not available in 2026
- Administered by
- Physics, Mathematics and Computing
Course details
- Intake periods
- Beginning of year and mid-year
- Attendance type
- Full- or part-time
- Credit points required
- 96
A standard full-time load is 24 points per semester. - Standard course duration
- 1.5 years full-time (or equivalent part-time) comprising 72 points of taught units and 24 points of admission credit, as recognised and granted by the School
- Maximum course duration
- 2.0 years full-time (or equivalent part-time) comprising up to 96 points of taught study (see Rule 5 for further information)
- Time limit
- 5.0 years
- Delivery mode
- Internal
- Locations offered
- UWA (Perth)
- Domestic fee type
- Commonwealth supported and/or HECS-HELP
- Available to international students
- Not available to international students on student visas. Available to international students on other visas if visa conditions allow (see https://www.immi.gov.au). For information on international student fees see 'Student Procedures: Fees'. (Enquiries: https://www.uwa.edu.au/askuwa)
- Course Coordinator(s)
- Associate Professor Adriano Polpo de Campos
- Fees
- Visit the fees calculator.
Prospective students should see the Future Students website for details on admission requirements, intake periods, fees, availability to international students, careers information etc.
No study plans found for this course. Check your chosen major, see study plans or contact your student advising office for more information.
Specialisations
Course structure
Key to availability of units:
- S1
- Semester 1
- S2
- Semester 2
- SS
- summer teaching period
- N/A
- not available in 2026 – may be available in 2027 or 2028
- *
- to be advised
All Students to complete the following totalling 72 points:
a) 48 points from Group A or 30 points from Group A and 18 points from either Group B or C; and
b) 24 points of core (STAT5001
Students who have not complemented the units listed below must complete 24 points of conversion units, comprising: STAT3061 (6 points) and STAT3062 (6 points); MATH2064 (6 points) as a numerical methods for data analysis unit; and 6 points selected from CITS1401, CITS1501, or CITS2401 to develop programming skills required for modern data analysis.
| Availability | Unit code | Unitname | Unit requirements | Contact hours |
|---|---|---|---|---|
| S1, S2 | CITS1401 | Computational Thinking with Python | lectures: 2 hours per week; labs: 2 hours per week; workshops: 1 hour per week | |
| S2 | CITS1501 | Introduction to Programming with Python |
| Lectures: 2 hours per week for 12 weeks; Labs: 2 hours per week for 10 weeks from week 1. |
| S1, S2 | CITS2401 | Computer Analysis and Visualisation | lectures: 2 hours per week; labs: 3 hours per week; workshop: 1 hour per week | |
| S1 | MATH2064 | Numerical Methods |
| lectures: 3 hours per week workshops: 2 hours per week |
| S1 | STAT3061 | Random Processes and their Applications | Lectures: 5-hours per fortnight; Labs: 2-hours per fortnight | |
| S1 | STAT3062 | Statistical Science | Lectures: 5-hours per fortnight; Labs: 2-hours per fortnight |
Take all units (24 points):
Note: Research units in Statistics.
| Availability | Unit code | Unitname | Unit requirements | Contact hours |
|---|---|---|---|---|
| N/A | STAT5001 | Masters Research Project in Statistics Part 1 (12 points) |
| Part 1: 3 hours per week (Scientific Communications component) + regular meetings with supervisor; Part 2: regular meetings with supervisor |
| N/A | STAT5002 | Masters Research Project in Statistics Part 2 (12 points) | Part 1: 3 hours per week (Scientific Communications component) + regular meetings with supervisor; Part 2: regular meetings with supervisor |
Take between 30-48 points from this Group.
Note: Fondation units designed to strengthen knowledge and skills in Statistics. Students are advised to consult with their supervisor or program coordinator prior to enrolling in any unit to ensure appropriate unit selection.
Group A
| Availability | Unit code | Unitname | Unit requirements | Contact hours |
|---|---|---|---|---|
| S1 | STAT4064 | Applied Predictive Modelling | Lectures: 2-hours per week; Computer Labs: 2-hours per week | |
| S2 | STAT5061 | Statistical Data Science | Lectures: 2-hours per week; Laboratory: 2-hours per week. | |
| N/A | STAT5401 | Multilevel and Mixed-Effects Modelling |
| Lectures: 2-hours per week; labs: 2-hours per week |
| S2 | STAT5405 | Bayesian Computing and Statistics |
| Lectures: 2-hours per week; Computer Labs: 3-hours per fortnight; Practical Classes: 1-hour per fortnight |
| N/A | STAT5461 | Stochastic Processes | 3 hours per week | |
| N/A | STAT5462 | Statistical Modelling | 3-hours per week | |
| N/A | STAT5463 | Spatial Statistics | lectures: 3 hours per week; practical class: 1 hour per week from week 2 | |
| N/A | STAT5466 | Computational Statistical Methods | 3-hours per week | |
| N/A | STAT5467 | Infectious Disease Modelling |
| 3-hours per week |
Take between 0-18 points from this Group.
Note: Optional units in mathematical modelling. Students are advised to consult with their supervisor or program coordinator prior to enrolling in any unit to ensure appropriate unit selection.
Group B
| Availability | Unit code | Unitname | Unit requirements | Contact hours |
|---|---|---|---|---|
| S1 | MATH4011 | Special Topics in Mathematics 1 |
| 3 hours per week |
| S2 | MATH4012 | Special Topics in Mathematics 2 |
| 3 hours per week |
| S1 | MATH4021 | Applied Dynamical Systems |
| 3 hours per week |
| S2 | MATH4022 | Continuum Mechanics |
| 3 hours per week |
| S2 | MATH4023 | Mathematical Optimisation |
| Lectures: 3-hours per week |
| N/A | MATH4025 | Mathematical Models and Partial Differential Equations |
| 3 hours per week |
| N/A | MATH4027 | Advanced Complex Systems |
| 3 hours per week |
Take between 0-18 points from this Group.
Note: Optional units in computational methods for data analysis. Students are advised to consult with their supervisor or program coordinator prior to enrolling in any unit to ensure appropriate unit selection.
Group C
| Availability | Unit code | Unitname | Unit requirements | Contact hours |
|---|---|---|---|---|
| S2 | CITS4012 | Natural Language Processing |
| Lectures: 2-hours per week; Laboratories: 2-hours per week. |
| S1 | CITS4407 | Open Source Tools and Scripting |
| |
| S2 | CITS5017 | Deep Learning |
| lectures: 2 hours per week; laboratories: 2 hours per week. |
| S2 | CITS5503 | Cloud Computing |
| |
| S2 | CITS5507 | High Performance Computing |
| |
| S1 | CITS5508 | Machine Learning |
| lectures: 2 hours per week; labs: 2 hours per week for 11 weeks from week 2 |
| S1 | PHYS4021 | Quantum Information and Computing |
| Lectures/Workshop: 3 x 45 minutes per week |
| S2 | PHYS4022 | Advanced Quantum Computing |
|
See also the rules for the course and the Student Rules.
Rules
Note: This course is not available in 2026.
Applicability of the Student Rules, policies and procedures
1.(1) The Student Rules apply to students in this course.
(2) The policy, policy statements and guidance documents and student procedures apply, except as otherwise indicated in the rules for this course.
Academic Conduct Essentials and Communication and Research Skills modules
2.(1) A student who enrols in this course for the first time irrespective of whether they have previously been enrolled in another course of the University, must undertake the Academic Conduct Essentials module (the ACE module) and the Communication and Research Skills module (the CARS module).
(2) A student must successfully complete the ACE module within the first teaching period of their enrolment. Failure to complete the module within this timeframe will result in the student's unit results from this teaching period being withheld. These results will continue to be withheld until students avail themselves of a subsequent opportunity to achieve a passing grade in the ACE module. In the event that students complete units in subsequent teaching periods without completing the ACE module, these results will similarly be withheld. Students will not be permitted to submit late review or appeal applications regarding results which have been withheld for this reason and which they were unable to access in the normally permitted review period.
English Language competency requirements
3. To be eligible for consideration for admission to this course an applicant must satisfy the University's English language competence requirement as set out in the University Policy on Admission: Coursework.
Admission requirements
4.(1) To be considered for admission to this course an applicant must have—a bachelor's degree with major in statistics, or an equivalent qualification, as recognised by UWA; and
(2) the equivalent of a UWA weighted average mark of at least 70 per cent; and
(3) an agreement with an academic staff member/s to supervise their research project.
Admission ranking and selection
5. Where relevant, admission will be awarded to the highest ranked applicants or applicants selected based on—
(a) the weighted average mark (WAM)
Articulations and exit awards
6. This course does not form part of an articulated sequence.
Course structure
7.(1) The course consists of units to a total value of 96 points (maximum value) which include conversion units to a value of 24 points.
(2) Units must be selected in accordance with the course structure, as set out in these rules.
Satisfactory progress
8. To make satisfactory progress a student must pass units to a point value greater than half the total value of units in which they remain enrolled after the final date for withdrawal without academic penalty.
9. A student who has not achieved a result of Ungraded Pass (UP) for the Communication and Research Skills module (the CARS module) when their progress status is assessed will not have made satisfactory progress even if they have met the other requirements for satisfactory progress in Rule 8.
Progress status
10.(1) A student who makes satisfactory progress in terms of Rule 8 is assigned the status of 'Good Standing'.
(2) Unless the relevant board determines otherwise because of exceptional circumstances—
(a) a student who does not make satisfactory progress for the first time under Rule 8 is assigned a progress status of 'On Probation';
(b) a student who does not make satisfactory progress for the second time under Rule 8 is assigned a progress status of 'Suspended';
(c) a student who does not make satisfactory progress for the third time under Rule 8 is assigned a progress status of 'Excluded'.
11. A student who does not make satisfactory progress in terms of Rule 9 is assigned the progress status of 'On Probation', unless they have been assigned a progress status of 'Suspended' or 'Excluded' for failure to meet other satisfactory progress requirements in Rule 8.
Award with distinction
12. To be awarded the degree with distinction a student must achieve a course weighted average mark (WAM) of at least 80 per cent which is calculated based on—
(a) all units above Level 3 attempted as part of the course that are awarded a final percentage mark;
(b) all relevant units above Level 3 undertaken in articulating courses of this University that are awarded a final percentage mark;
and
(c) all units above Level 3 completed at this University that are credited to the master's degree course.
Deferrals
13. Applicants are not permitted to defer admission to this course and are expected to commence their course in the offered intake only. Applicants seeking admission to an alternative intake must submit a new application for that intake.