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Master of Statistics (2025 Admission)
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 Programme Structure
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Commencing in September, the curriculum is composed of a total of 60 credits of courses covering research methods in statistics, quantitative trading, biostatistics, big data analytics, etc., of which some electives are from the department’s research postgraduate programme. The programme offers great flexibilities for students to specialise in themes of Risk Management, Data Analytics or Financial Statistics. A student may choose to have his/her theme printed on the transcript if he/she has satisfied the requirement of one of the themes. If a student selects an MStat course whose contents are similar to a course (or courses) which he/she has taken in his/her previous study, the Department may not approve the selection in question.
You may refer to the 2024 Regulations and Syllabuses (TBC) for details.
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Curriculum study (applicable for both full-time and part-time modes)
Two compulsory courses (12 credits):
STAT7101 Fundamentals of statistical inference (6 credits)
STAT7102 Advanced statistical modelling (6 credits)
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Students with prior background has to take a more advanced course from the same area as
replacement:
REPLACE…
STAT7101 Fundamentals of statistical inference (6 credits)
STAT7102 Advanced statistical modelling (6 credits)
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WITH…
STAT6009 Research methods in statistics (6 credits)
or
STAT7005 Multivariate methods (6 credits)
Any other course
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Theme-specific elective courses (24 Credits):
Risk Management theme
plus 24 credits from
STAT6015 Advanced quantitative risk management (6 credits)
STAT6017 Operational risk and insurance analytics (6 credits)
STAT7009 Stochastic dependence modelling (6 credits) 
STAT8003 Time series forecasting (6 credits)
STAT8007 Statistical methods in economics and finance (6 credits)
STAT8015 Actuarial statistics (6 credits)
STAT8017 Data mining techniques (6 credits)
STAT8308 Blockchain data analytics (3 credits)
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Data Analytics theme
plus 24 credits from
STAT6011 Computational statistics and Bayesian learning (6 credits)
STAT6016 Spatial data analysis (6 credits)
STAT7005 Multivariate methods (6 credits)
STAT7007 Categorical data analysis (3 credits)
STAT8003 Time series forecasting (6 credits)
STAT8016 Biostatistics (6 credits)
STAT8017 Data mining techniques (6 credits)
STAT8019 Marketing analytics (6 credits)
STAT8021 Big data analytics (6 credits)
STAT8302 Structural equation modelling (3 credits)
STAT8306 Statistical methods for network data (3 credits)
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Financial Statistics theme*
plus 24 credits from
STAT6013 Financial data analysis (6 credits)
STAT7009 Stochastic dependence modelling (6 credits)
STAT8003 Time series forecasting (6 credits)
STAT8007 Statistical methods in economics and finance (6 credits)
STAT8015 Actuarial statistics (6 credits)
STAT8017 Data mining techniques (6 credits)
STAT8020 Quantitative strategies and algorithmic trading (6 credits)
STAT8021 Big data analytics (6 credits)
STAT8309 Monte Carlo Simulation and Finance (3 credits)
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Other elective courses (18 credits)
plus at least 18 credits from
STAT6009 Research methods in statistics (6 credits)
STAT6010 Advanced probability (6 credits)
STAT6019 Current topics in statistics (6 credits)
STAT7006 Design and analysis of sample surveys (6 credits)
STAT7008 Programming for data science (6 credits)
STAT8000 Workshop on spreadsheet modelling and database management (3 credits)
STAT8300 Career development and communication workshop (Non-credit-bearing)
Any theme-specific elective courses
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Capstone requirement (6 credits)
plus 6 credits from
STAT8017 Data mining techniques (6 credits)
STAT8088 Statistical practicum (6 credits)
STAT8089 Capstone project (6 credits)
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Remarks:
- Apart from the two compulsory courses and capstone requirement, candidates may choose not to
follow any theme and may take 42 credits of elective courses in any order, whenever feasible.
- The programme structure will be reviewed from time to time and is subject to change.
- *The proposed new theme is pending the University’s approval.
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Programme Fee (subject to approval)
The full tuition fee is HK$228,000, and it is normally paid by full-time students in 2 installments, and part-time students in 4 installments.
The University allows Occasional Students to enrol in individual courses without registering in any particular programme of study. The tuition fee for occasional students taking MStat courses is HK$3,800 per credit.
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Summer Preparatory Courses
- Preparatory Course on Python is a course provides a quick overview of the Python programming language (August, 2025).
- Preparatory course in matrices and calculus for all students who need to rejuvenate their mathematical skills (August, 2025).
- Review course on basic probability and statistics concepts to solidify students’ conceptual understanding (August, 2025).
- Workshop in R covering data handling, graphics, mathematical functions and some basic statistical techniques (August, 2025).
- Workshop in SAS for all the students who need to rejuvenate their skills in data management using SAS (August, 2025).
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