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Mathematics, statistics and techniques for decision-making are professional and indispensable tools for many types of problems, and continue to enjoy rapid growth in areas of actuarial science, strategic planning, financial investments and operations research analysis. The degree programmes equip students with a strong undergraduate background in the areas of applied mathematical methods, statistics, data analysis, optimization, stochastic and deterministic modeling, and risk analysis. It prepares students for careers or for further study in many technical fields such as statistical analysis, management science, industrial engineering, biostatistics, strategic planning, financial analysis, education.
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| Students pursuing this programme must successfully complete at least 120 credits as follows: | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| (a) | 20 credits from:
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| (b) | 65 credits of compulsory courses:
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| (c) | 15 credits from courses:
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| (d) | Additional courses, as necessary, from any Foundation, Middle or Higher courses offered by the University, provided that, of the total 120 credits, no more than 40 are gained at Foundation level. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
 Students are required to complete 120 credits but they may opt to graduate with the Diploma in Applied Statistics [DAS] (60 credits) after completing the required number of credits and fulfilling the requirements of the programme regulations. |
Professional recognition The Hong Kong Statistical Society The Hong Kong Statistical Society has granted accreditation to students of the Mathematics and Statistics Programmes of the School of Science and Technology to obtain the Society's Graduate Diploma, Higher Certificate, and Ordinary Certificate. Details are given below. Ordinary Certificate: Students are given accreditation for the Ordinary Certificate if they achieve a pass at grade 3/C+ or above in STAT S242 Statistics in Society and MATH S280 Statistical Methods for Decision Analysis. Higher Certificate: Students are given accreditation for the Higher Certificate if they fulfil either one of the following requirements: (a) Obtain a grade 3/C+ or above in STAT S242 Statistics in Society, MATH S280 Statistical Methods for Decision Analysis, MATH S346 Linear Statistical Modelling and MATH S350 Applied Probability Models for Decision Making. (b) Obtain accreditation for the Hong Kong Statistical Society Ordinary Certificate, and also obtain a grade 3/C+ or above in MATH S346 Linear Statistical Modelling and MATH S350 Applied Probability Models for Decision Making. Entire Graduate Diploma Students are given accreditation for the entire Graduate Diploma if they have passed at grade 3/C+ or above in all six of the following courses: STAT S242 Statistics in Society, MATH S280 Statistical Methods for Decision Analysis, MATH S249 Practical Modern Statistics, MATH S346 Linear Statistical Modelling, MATH S350 Applied Probability Models for Decision Making, STAT S347 Mathematical Statistics. Individual modules of the Graduate Diploma Students are given accreditation for individual modules of the Graduate Diploma if they have passed at grade 3/C+ or above in the following: (a) MATH S280 + MATH S350 accreditation for Module 1 of the Graduate Diploma. (b) MATH S249 + MATH S350 accreditation for Module 3 of the Graduate Diploma. (c) STAT S242 + MATH S346 accreditation for Module 4 of the Graduate Diploma. (d) Individuals who have obtained accreditation for Modules 1, 3 and 4 of the Hong Kong Statistical Society Graduate Diploma and passed STAT S347 at grade C+ or above will fulfill the accreditation requirement of the entire Graduate Diploma. Remark 1: Students who have obtained accreditation for the entire Graduate Diploma are deemed to have fulfilled the requirements of Graduate Statistician membership of the Hong Kong Statistical Society. Remark 2: Among discontinued courses, successful completion of MATH S242 is considered as completion of STAT S242; completion of MATH S245/MATH S246/MATH S248 is considered as completion of MATH S280; completion of MATH S343 is considered as completion of MATH S350; and completion of MATH S345 is considered as completion of MATH S346. |
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Choosing the first courses to get started
Students with no credit exemption are recommended to begin with MATH S121 or MATH S122.
Master of Science in Quantitative Analysis and Computational Mathematics (60 credits)
Master of Science in Quantitative Analysis and Computational Mathematics (through Pathway 1) (40 credits)
Postgraduate Diploma in Quantitative Analysis and Computational Mathematics (40 credits)
Postgraduate Certificate in Quantitative Analysis (20 credits)
Postgraduate Certificate in Computational Mathematics (20 credits)
Bachelor of Science in Mathematical Studies (120 credits)
Bachelor of Science with Honours in Mathematical Studies (160 credits)
Bachelor of Science in Statistics and Decision Science (120 credits)
Bachelor of Science with Honours in Statistics and Decision Science (160 credits)
Diploma in Applied Statistics (60 credits)
For enquiries about the programmes, please contact:
Dr Tony Chan 陳滿棠博士
Tel: 2768 6867
Email: tmtchan@ouhk.edu.hk
School of Science & Technology website
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Jonathan handles all external affairs include business development, patents write up and public relations. He is frequently interviewed by media and is considered a pioneer in 3D printing products.
After graduating from OUHK, Krutz obtained an M.Sc. in Engineering Management from CityU. He is now completing his second master degree, M.Sc. in Biomedical Engineering, at CUHK. Krutz has a wide range of working experience. He has been with Siemens, VTech, and PCCW.
Hugo Leung Wai-yin, who graduated from his four-year programme in 2015, won the Best Paper Award for his ‘intelligent pill-dispenser’ design at the Institute of Electrical and Electronics Engineering’s International Conference on Consumer Electronics – China 2015.
The pill-dispenser alerts patients via sound and LED flashes to pre-set dosage and time intervals. Unlike units currently on the market, Hugo’s design connects to any mobile phone globally. In explaining how it works, he said: ‘There are three layers in the portable pillbox. The lowest level is a controller with various devices which can be connected to mobile phones in remote locations. Patients are alerted by a sound alarm and flashes. Should they fail to follow their prescribed regime, data can be sent via SMS to relatives and friends for follow up.’ The pill-dispenser has four medicine slots, plus a back-up with a LED alert, topped by a 500ml water bottle. It took Hugo three months of research and coding to complete his design, but he feels it was worth all his time and effort.
Hugo’s public examination results were disappointing and he was at a loss about his future before enrolling at the OUHK, which he now realizes was a major turning point in his life. He is grateful for the OUHK’s learning environment, its industry links and the positive guidance and encouragement from his teachers. The University is now exploring the commercial potential of his design with a pharmaceutical company. He hopes that this will benefit the elderly and chronically ill, as well as the society at large.
Soon after completing his studies, Hugo joined an automation technology company as an assistant engineer. He is responsible for the design and development of automation devices. The target is to minimize human labor and increase the quality of products. He is developing products which are used in various sections, including healthcare, manufacturing and consumer electronics.
| Course Code | Title | Credits | |
|---|---|---|---|
| COMP S321F | Advanced Database and Data Warehousing | 5 | |
| COMP S333F | Advanced Programming and AI Algorithms | 5 | |
| COMP S351F | Software Project Management | 5 | |
| COMP S362F | Concurrent and Network Programming | 5 | |
| COMP S363F | Distributed Systems and Parallel Computing | 5 | |
| COMP S382F | Data Mining and Analytics | 5 | |
| COMP S390F | Creative Programming for Games | 5 | |
| COMP S492F | Machine Learning | 5 | |
| ELEC S305F | Computer Networking | 5 | |
| ELEC S348F | IOT Security | 5 | |
| ELEC S371F | Digital Forensics | 5 | |
| ELEC S431F | Blockchain Technologies | 5 | |
| ELEC S425F | Computer and Network Security | 5 |
| Course Code | Title | Credits | |
|---|---|---|---|
| ELEC S201F | Basic Electronics | 5 | |
| IT S290F | Human Computer Interaction & User Experience Design | 5 | |
| STAT S251F | Statistical Data Analysis | 5 |
| Course Code | Title | Credits | |
|---|---|---|---|
| COMPS333F | Advanced Programming and AI Algorithms | 5 | |
| COMPS362F | Concurrent and Network Programming | 5 | |
| COMPS363F | Distributed Systems and Parallel Computing | 5 | |
| COMPS380F | Web Applications: Design and Development | 5 | |
| COMPS381F | Server-side Technologies and Cloud Computing | 5 | |
| COMPS382F | Data Mining and Analytics | 5 | |
| COMPS390F | Creative Programming for Games | 5 | |
| COMPS413F | Application Design and Development for Mobile Devices | 5 | |
| COMPS492F | Machine Learning | 5 | |
| ELECS305F | Computer Networking | 5 | |
| ELECS363F | Advanced Computer Design | 5 | |
| ELECS425F | Computer and Network Security | 5 |
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