HKU HKU Dept of Statistics & Actuarial Science, HKU
   
 

Master of Statistics (2022 Admission)


 Programme Structure

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.

You may refer to the 2022 Regulations and Syllabuses (subject to approval) for details.

 
 

 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)
 
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)

WITH…
STAT6009 Research methods in statistics (6 credits)
or
STAT7005 Multivariate methods (6 credits)
Any other course

Theme-specific elective courses (24 Credits):

Risk Management theme
 
plus 24 credits from:
 
STAT6013 Financial data analysis (6 credits)
STAT6015 Advanced quantitative risk management (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)
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)
STAT8308 Blockchain data analytics (3 credits)

Data Analytics theme
 
plus 24 credits from:
 
STAT6011 Computational statistics (6 credits)
STAT6016 Spatial data analysis (6 credits)
STAT7005 Multivariate methods (6 credits)
STAT7007 Categorical data analysis (3 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)
STAT8021 Big data analytics (6 credits)
STAT8302 Structural equation modelling (3 credits)
STAT8305 Bayesian statistics (3 credits)
STAT8306 Statistical methods for network data (3 credits)

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)
STAT7301 Socio-economic statistics for business and public policies (3 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

Any capstone courses

Capstone requirement (6 credits)
 
plus 6 credits from
 
STAT8002 Project (6 credits)
STAT8017 Data mining techniques (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.

 

 Optional Summer Courses

  • Preparatory course in matrices and calculus for all students who need to rejuvenate their mathematical skills (August, 2022).

  • Review course on basic probability and statistics concepts to solidify students’ conceptual understanding (August, 2022).

  • Workshop in R covering data handling, graphics, mathematical functions and some basic statistical techniques (August, 2022).

  • Workshop in SAS for all the students who need to rejuvenate their skills in data management using SAS (August, 2022).