Master of Mathematical Sciences (Applied Statistics)

2 Years On Campus Masters Program

University of Wollongong

Program Overview

The Master of Mathematical Sciences (Applied Statistics) at the University of Wollongong (UOW) is a two-year on-campus program designed for graduates with a background in mathematics or statistics who want to develop advanced statistical expertise for real-world applications. Students build professional capabilities in statistical modelling, experimental design, data analysis, probability and statistical inference, while also developing computing, communication, critical-thinking and research skills relevant to government and private-sector careers.

Curriculum Structure

Year 1: Students establish advanced mathematical and statistical foundations through subjects such as MTH8206 Random Variables and Estimation and MTH8207 Statistical Inference and Introduction to Model Building, before progressing into the applied statistics core. They then develop practical statistical capabilities through STAT801 Statistical Methods for Data Science (Enhanced) and STAT804 Stochastic Methods in Statistical Analysis (Enhanced), covering statistical methods, stochastic approaches and data-focused analysis.

Year 2: The second year moves further into professional statistical practice, with STAT832 Generalised Linear Models (Enhanced) and STAT835 Sample Surveys and Experimental Design (Enhanced) developing students' ability to model complex data, design surveys and experiments, and interpret statistical results. Students also undertake statistics-focused investigations and an Advanced Project in the Mathematical Sciences (MTST991 or MTST992), giving them an opportunity to apply their knowledge to an approved applied-statistics problem through substantial work-integrated learning.

Focus Areas:

Applied statistics, statistical modelling, probability, statistical inference, data analysis, experimental design, sample surveys, generalised linear models, research and statistical applications across government and private-sector environments.

Learning Outcomes:

Graduates develop advanced statistical knowledge and technical skills to analyse, critically evaluate and synthesise complex information; independently investigate statistical problems; communicate mathematical and statistical ideas effectively; and apply expert judgement to statistical problems in interdisciplinary contexts.

Professional Alignment (Accreditation):

Accreditation for this newly developed course is currently being sought from the Australian Mathematical Society. The Applied Statistics specialisation is specifically designed to develop the skills and knowledge expected of a professional statistician, including problem-solving, statistical and mathematical modelling, experimental design, data organisation, analysis and interpretation.

Reputation (Employability Rankings):

UOW is ranked 195th globally and 13th in Australia in the QS World University Rankings 2027, placing it among the world's top 200 universities. UOW also reports that its graduates are consistently ranked among the top one per cent in the world by employers, while the latest QILT Employer Satisfaction Survey reported 83% overall employer satisfaction with UOW graduates and 88.5% gained employment within four months of completing their course.

Experiential Learning (Research, Projects, Internships etc.)

The Master of Mathematical Sciences (Applied Statistics) at the University of Wollongong (UOW) is strongly focused on applying statistical knowledge to real-world problems. Students build practical capability in statistical modelling, experimental design, data analysis, statistical inference and interpretation of large datasets, while developing the computing and communication skills expected of professional statisticians. The program also includes an advanced project with directed studies in applied statistics, giving students the opportunity to investigate a substantial statistics problem independently.

Students can also gain workplace exposure through embedded Work Integrated Learning (WIL) in the advanced project subjects, while UOW provides access to specialist statistical software through its Virtual Lab. The combination of applied coursework, statistical computing and project-based investigation makes the learning particularly relevant to careers involving data and statistical analysis:

Applied statistics projects: Students can complete MTST991 and MTST992 – Advanced Project in the Mathematical Sciences, with directed studies specifically in an approved area of applied statistics.
Work Integrated Learning: The advanced project subjects MTST991 and MTST992 contain substantial embedded WIL, allowing students to develop practical skills through project-based work.
Statistical modelling: Students work with topics including estimation and hypothesis testing, linear and generalised models, statistical inference, sample surveys and experimental design.
Data Mining: INFO911 – Data Mining and Knowledge Discovery is available as a preparation subject, giving students exposure to methods for extracting useful information from datasets.
SPSS: UOW's Virtual Lab provides access to SPSS, supporting advanced statistical analysis, machine-learning algorithms, text analysis and big-data integration.
Stata: Students can access Stata, a statistical package designed for exploring, summarising and analysing datasets.
R and RStudio: UOW provides R for data manipulation, calculation and graphical display, along with RStudio, an IDE supporting R and Python workflows.
AmoS: The Virtual Lab provides AmoS for structural equation modelling, including regression, factor analysis, correlation and analysis of variance.
SmartPLS: Students can access SmartPLS, a data-visualisation tool for complex modelling tasks.
Interdisciplinary learning: The degree allows students to apply mathematics and statistics to areas including computer science, business, science and psychology, strengthening their ability to solve problems beyond a single discipline.
Research methods: MATH907 – Research Methods develops the research skills needed to investigate mathematical and statistical problems and is compulsory in the Master of Mathematical Sciences.
UOW research and study facilities: Students can use UOW's academic and digital resources to support statistical research, coursework and project work, including the university's specialist Virtual Lab for statistical software.

Progression & Future Opportunities

The Master of Mathematical Sciences (Applied Statistics) at the University of Wollongong (UOW) can prepare graduates for careers where statistical modelling, data analysis and quantitative problem-solving are central. UOW’s mathematics and statistics career information identifies graduates working in roles such as data analyst, biostatistician, analyst and catastrophe modelling, with employers including SAS, Westpac, Commonwealth Bank, KPMG, Quantium, Microsoft, NSW Health and the Australian Institute of Health and Welfare.

Typical career opportunities include:

Data Analyst
Biostatistician
Statistical Analyst
Catastrophe Modelling Analyst

UOW provides several pathways to help students turn their statistical skills into professional opportunities:

Career support: UOW Careers and Employability offers one-to-one Career Chats, resume and application reviews, interview and job-seeking workshops, CareerHub, the UOW JobBoard and employer events. Students can also participate in Ignite your Future, an online program designed to help final-year students transition into professional roles.
Work experience: Students can access work-integrated learning programs, internships, virtual internships, paid opportunities and volunteering, allowing them to build practical experience alongside their studies.
Graduate employment: UOW reports that 88.5% of graduates gained employment within four months of completing their course, above the national average of 86.9%, according to the QILT Employer Satisfaction Survey 2024 information published by UOW.
Salary outcomes: UOW reported a median full-time salary of AUD $67,800 for recent graduates in its 2022 Graduate Outcomes Survey. This is a university-wide figure rather than a salary specifically for Applied Statistics graduates, so individual salaries will vary by role and experience.
Industry connections: UOW's mathematics and statistics graduate information identifies employers including SAS, Australian Energy Market Operator, Westpac, Commonwealth Bank, KPMG, IMC Financial Markets, Microsoft, Quantium, IAG, NSW Health and the Australian Institute of Health and Welfare, demonstrating the range of industries in which UOW mathematics and statistics graduates have worked.
Professional development: The UOW Mentoring Program connects students one-to-one with experienced professionals who previously studied at UOW, while UOWx helps students build and formally document transferable skills gained through activities outside their degree.
Employer recognition: UOW states that 83% of employers were overall satisfied with UOW graduates in the QILT Employer Satisfaction Survey 2024, supporting the university's reputation for producing graduates with skills valued by employers.
Long-term value: UOW is ranked among the top 200 universities globally for graduate employability in the university's published rankings information, giving the qualification an added employability advantage when graduates pursue careers in Australia or internationally.
Graduate outcomes: UOW's dedicated mathematics and statistics career resource tracks actual graduate destinations and lists roles ranging from Software Design Engineer in Test and Data Analyst to Biostatistician and Transport Planner, helping students see the breadth of careers available from mathematical and statistical study.

Further Academic Progression: Graduates who want to move into advanced statistical research, academia or specialised quantitative research can consider progressing to a research-focused higher degree such as a PhD. UOW's strong research environment and its extensive network of academic and research collaborations can provide a foundation for students who want to develop a long-term research career.