The Division of Statistics provides M.Phil./Ph.D. programmes in Statistics under the Faculty of Science of The Chinese University of Hong Kong. The objectives are to extend the frontiers of research in various fields of statistics and applied statistics, including but not limited to Finance and Econometrics, Asymptotic Theory, Time Series, Biostatistics and Bioinformatics, Latent Variable Models/Structural Equation Models, Multiple Comparisons, Spectral Density Estimation, and Statistical Computing.
In addition to the general qualifications required for admission to the M.Phil.-Ph.D. Programme, applicants should have a good honours degree in a related field. All applicants must also fulfil the "English Language Proficiency Requirement" as stipulated by the Graduate School before being considered for admission. For further details, please visit the Graduate School website at http://www.gs.cuhk.edu.hk/
Programme of Study
Students are required to complete a minimum of 42 units for graduation, including a minimum of 18 units of lecture courses and 24 units of thesis research courses. Below is the breakdown for the suggested study scheme:
(a) Lecture courses: (Both full-time and part-time)
- Required courses: STAT5010, STAT5020, STAT5030
- Any three courses taken from: STAT5005, STAT5040, STAT5050, STAT5060, STAT6040, STAT6050, STAT6060
(b) Thesis research/monitoring courses:
- Full-time students [First to Second Year of Attendance]: STAT8006 in each term
- Part-time students [First to Third Year of Attendance]: STAT8003 in each term
- Continuing students [for both full-time and part-time]: STAT8003 in each term
In addition to the 24 units of lecture courses, students are required to take thesis research course every term till they graduate. The requirements are enumerated as follows:
(a) Pre-candidacy requirements
The "candidacy requirement" composes of three major parts, namely, coursework requirement, candidacy examination, and thesis proposal (and oral defense). Students must complete and fulfill all three parts within the "maximum period for fulfilling candidacy requirements":
(b) Candidacy/Qualifying Examinations
(i) Lecture courses: (Both full-time and part-time)
- Required courses: STAT5005, STAT5010, STAT5020, STAT5030
- Any four courses taken from: STAT5040, STAT5050, STAT5060, STAT6040, STAT6050, STAT6060 or other relevant courses of 5000-level or above approved by the programme (at most one of the four courses can be non-STAT course taken outside of the department) (For full-time students – First to Second Year of Attendance; For part-time students – First to Third Year of Attendance)
(ii) Thesis research/monitoring courses:
- Full-time students[First to Second Year of Attendance]: STAT8006 in each term
- Part-time students[First to Third Year of Attendance]: STAT8003 in each term
Students are required to take and pass a written examination by the end of the first year from entry. A second attempt is allowed, but it must be taken before the end of the third term from first entry. If the students fail the second time, they should be discontinued from the studies. The written examination materials include: STAT5005, STAT5010, STAT5020 and STAT5030.
(c) Requirements for Ph.D. candidates
Thesis research/monitoring courses:
- Full-time students: STAT8012 in each term
- Part-time students: STAT8006 in each term
- Continuing students (both full-time and part-time ): STAT8003 in each term
Additional requirements for both M.Phil. and Ph.D. in Statistics Programmes students
For students entering either M.Phil. or Ph.D. in Statistics programme, they are also required to meet following additional requirements:
- Students must fulfill the Term Assessment Requirement of the Graduate School. For details, please refer to Section 13.0 “Unsatisfactory Performance and Discontinuation of Studies” of the General Regulations Governing Postgraduate Studies which can be accessed from the Graduate School Homepage: http://www.cuhk.edu.hk/gss.
- A student must achieve a minimum grade of C- in each of the courses taken in order to fulfill the graduation requirements, unless special approval is granted by the Faculty Board.
- Students are required to submit a research thesis and pass an oral examination for graduation.
- Complete an Improving Postgraduate Learning (IPL) module on “Observing Intellectual Property and Copyright Law during Research”. This will be an online module and relevant information can be accessed from the website: http://www.cuhk.edu.hk/clear/prodev/ipl.html.
Application Procedure and Enquiries
Applicants can submit applications via the Internet through Online application. Paper application forms are also obtainable at the Graduate School Office,7th Floor, Yasumoto International Academic Park, The Chinese University of Hong Kong, Shatin, N.T.)
Completed application forms and required support documents should be returned to the relevant divisions, as specified in the "Notes for Applicants" of the application form. All supporting documents, including transcripts from the universities attended by the applicants and confidential recommendations from two referees, must reach the relevant divisions before the application deadline.
Applicants who apply via the Internet: Online application, should quote the "Application No." generated for their applications when they send the hardcopies of their supporting documents to the Graduate Divisions. For the list of required support documents, please refer to the Graduate School Homepage http://www.gs.cuhk.edu.hk/page/ApplicationforAdmission
For applicants who apply for Ph.D. programme through the Hong Kong Ph.D. Fellowship Scheme (HKPFS), which carries a lot of benefits, the application deadline is 1 December for joining us in the next August. Please visit http://www.rgc.edu.hk/hkphd for further information.
For applicants who apply for M.Phil./Ph.D. programme directly with CUHK (i.e. non-HKPFS applicants), the application deadline is 31 December for joining us in the next August.
General enquiries can be submitted to
Ms Esther Tam
Tel: (852) 3943-7931
Fax: (852) 2603-5188
Fields of Specialisation
- Asymptotic Theory
- Statistical Computing and Machine Learning
- Big Data Analytics
- Latent Variable Models
- Time Series and Econometrics
- Actuarial Science and Risk Management
- Biostatistics and Bioinformatics
- Other Interdisciplinary Research