Master of Statistics (MStat)

 Graduate Statistician (GradStat) and Quality Mark of Royal Statistical Society (RSS)

The University of Hong Kong (HKU) has been awarded the status of an Accredited University by the Royal Statistical Society (RSS) since December 2023. The RSS accreditation provides reassurance that the teaching, learning and assessment within the accredited programme is of high quality and meets the needs of students and employers.

Upon completion of the Master of Statistics (MStat) programme at HKU and application to RSS via the standard route, graduates are qualified to become a Graduate Statistician (GradStat) designated by RSS (link).

In addition, the RSS has awarded individual HKU courses with the RSS Quality Mark (link), a recognition that these courses teach good statistical literacy. Students who have passed these courses are deemed to have met the academic requirements of the RSS Data Analyst award (link).

 Courses

• MStat add/drop period:
  September 1 to 14, 2023 (for Semester 1 & Semester 2),
  January 15 to 29, 2024 (for Semester 2 & Summer Semester),
  June 1 to 7, 2024 (Summer Semester)
• Timetable for 2023-24 (Updated on June 4, 2024)
• STAT8088 Practicum (6 credits) (2023-24) (Updated on August 10, 2023)
• STAT8089 Capstone Project (6 credits) (2023-24) (Updated on August 10, 2023)

 Regulations and Syllabuses

• For students admitted in 2023
• For students admitted in 2022
• For students admitted in 2021

 Prizes/Scholarships

• Belt and Road Scholarship in Statistics and Data Science (Taught Postgraduate)*
• Entrance Scholarship for the Master of Statistics
• Lifelong Learning Prizes in Statistics
• Master of Statistics Outstanding Performance Scholarship
• NAG Scholarships in Statistics
• Subject Prize for MStat Courses

List of Awardees (Updated on June 28, 2024)

 Reimbursable Courses by Continuing Education Fund (CEF)*

STAT6013 Financial Data Analysis	(42Z152714)
STAT7008 Programming for Data Science	(42Z153745)
STAT8003 Time Series Forecasting	(42Z153753)
STAT8007 Statistical methods in economics and finance	(42Z153575)
STAT8017 Data mining techniques	(42Z153583)
STAT8019 Marketing Analytics	(42Z12186A)

Three courses in the programme have been included in the list of reimbursable courses under the CEF. All CEF applicants are required to attend at least 70% of the courses before they are eligible for fee reimbursement under the CEF.

*The mother programme (Master of Statistics) of these courses is recognised under the Qualifications Framework (QF Level 6).

 Student Feedback Channels

The University strives to provide quality education and training to students, and feedback from students is valuable for the evaluation of the result of the endeavor. The Student Feedback on Teaching and Learning (SFTL), and Student Learning Experience Questionnaire (SLEQ) allow students to rate and comment on the courses they take near the end of the courses. To further enhance communication between teaching staff and students, the Department also supports the half-yearly Staff-Student Consultative Committee (SSCC) meetings, during which student course representatives and respective teaching staff exchange their views on certain aspects of the courses concerned. All feedback from students are collected anonymously.