Master of Statistics (2016 Admission)

Theme requirement for part-time study

Commencing in September, the curriculum is composed of a total of '60 credits of courses in either one year for full-time study, or two years for part-time study. The programme offers great flexibilities for students who wish to take a general approach or a specialised theme in Risk Management or Data Analytics. 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.

Risk Management theme

Two compulsory courses (12 credits):

STAT7003 Foundations of statistics
STAT7004 Linear modelling

Students with prior background may replace each course with a more advanced course from the same area:

REPLACE…
STAT6008 Advanced statistical inference
STAT6014 Advanced statistical modelling
STAT7003 Foundations of statistics
STAT7004 Linear modelling WITH
STAT6009 Research methods in statistics
Any other course
STAT7005 Multivariate methods
STAT6014 Advanced statistical modelling

plus at least 24 credits of courses from one of the themes below:

STAT6006 Stochastic calculus with financial applications (6 credits)
STAT6013 Financial data analysis (6 credits)
STAT6015 Advanced quantitative risk management and finance (6 credits)
STAT6017 Operational risk and insurance analytics (6 credits)
STAT8003 Time series forecasting (6 credits)
STAT8007 Statistical methods in economics and finance (6 credits)
STAT8014 Risk management and Basel accords (6 credits)
STAT8015 Actuarial statistics (6 credits)
STAT8017 Data mining techniques (6 credits)
STAT8301 Big data analytics (3 credits)
STAT8303 Quantitative strategies and algorithmic trading (3 credits)

The remaining courses can be selected from other MStat courses

Capstone requirement (6 credits)

STAT8002 Project (6 credits)
STAT8088 Practicum (6 credits)
STAT8089 Capstone project (6 credits)

Data Analytics theme

Two compulsory courses (12 credits):

STAT7003 Foundations of statistics
STAT7004 Linear modelling

Students with prior background may replace each course with a more advanced course from the same area:

REPLACE…
STAT6008 Advanced statistical inference
STAT6014 Advanced statistical modelling
STAT7003 Foundations of statistics
STAT7004 Linear modelling

WITH
STAT6009 Research methods in statistics
Any other course
STAT7005 Multivariate methods
STAT6014 Advanced statistical modelling

plus at least 24 credits of courses from one of the themes below:

STAT6011 Computational statistics (6 credits)
STAT6014 Advanced statistical modelling (for part-time study only) (6 credits)
STAT6016 Spatial data analysis (6 credits)
STAT7005 Multivariate methods (6 credits)
STAT7007 Categorical data analysis (6 credits)
STAT7008 Programming for data science (6 credits)

STAT8003 Time series forecasting (6 credits)
STAT8016 Biostatistics (6 credits)
STAT8017 Data mining techniques (6 credits)
STAT8019 Marketing analytics (6 credits)
STAT8301 Big data analytics (3 credits)
STAT8302 Structural equation modelling (3 credits)

The remaining courses can be selected from other MStat courses

Capstone requirement (6 credits)

STAT8002 Project (6 credits)
STAT8088 Practicum (6 credits)
STAT8089 Capstone project (6 credits)

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.