Bachelor of Science with Honours in Statistics and Decision Science (through Pathway 2)

School of Science and Technology Programmes Department of Electronic Engineering and Computer Science Bachelor of Science with Honours in Statistics and Decision Science (through Pathway 2)

Bachelor of Science with Honours in Statistics and Decision Science (through Pathway 2)
Programme description
Programme requirements
Related programmes
Enquiries

Programme description

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.

TOP

Programme requirements

Programme-specific entry requirement:

A recognized Higher Diploma or Associate Degree (or equivalent) in a relevant area related to science or engineering from a local tertiary institution recognized by the University for the purpose.

 

Students pursuing this programme must successfully complete 90 credits as follows:
(a)

50 credits from the following courses, of which 20 credits should be from Higher level courses MATH S350 and MATH S346.

Course code
(Click the course
code for details)

Course titleCreditsLevel
MATH S215Linear Algebra5Middle
MATH S221Mathematical Methods10Middle
MATH S249Practical Modern Statistics10Middle
MATH S280Statistical Methods for Decision Analysis10Middle
MATH S346Linear Statistical Modelling10Higher
MATH S350Applied Probability Models for Decision Making10Higher
STAT S242Statistics in Society10Middle
(b)

15 credits from courses:

Course code
(Click the course
code for details)

Course titleCreditsLevel
MATH S365Graphs, Networks and Design10Higher
MATH S373Optimization Methods in Decision Making10Higher
MATH S390Quantitative Models for Financial Risk5Higher
SCI S330Scientific Research Methods5Higher
STAT S347Mathematical Statistics10Higher
(c)

10 credits from courses:

Course code
(Click the course
code for details)

Course titleCreditsLevel
ECON A305Money and Banking10Higher
ECON A314 Econometrics and Forecasting5Higher
ECON A316International Finance5Higher
ENVR S335Environmental Control, Monitoring and Modeling10Higher
FIN B386Financial Decision Making5Higher
MATH S333Advanced Mathematical Methods5Higher
(d)

15 credits from the following courses which have not taken to fulfill (a) to (c) above.

Course code
(Click the course
code for details)

Course titleCreditsLevel
ACT B211Introduction to Accounting I5Middle
ACT B212Introduction to Accounting II5Middle
COMP S201Computing Fundamentals with Java10Middle
ECON A231Introduction to Microeconomics5Middle
ECON A232Introduction to Macroeconomics5Middle
ENVR S237Environmental Control and Public Health10Middle
FIN B280Introduction to Financial Management5Middle
MATH S215Linear Algebra5Middle
MATH S216Mathematical Analysis5Middle
MATH S221Mathematical Methods10Middle
MATH S249Practical Modern Statistics10Middle
MATH S280Statistical Methods for Decision Analysis10Middle
STAT S242Statistics in Society10Middle
ECON A305Money and Banking10Higher
ECON A314 Econometrics and Forecasting5Higher
ECON A316International Finance5Higher
ENVR S335Environmental Control, Monitoring and Modeling10Higher
FIN B386Financial Decision Making5Higher
MATH S365Graphs, Networks and Design10Higher
MATH S373Optimization Methods in Decision Making10Higher
MATH S390Quantitative Models for Financial Risk5Higher
SCI S330Scientific Research Methods5Higher
MATH S333Advanced Mathematical Methods5Higher
STAT S347Mathematical Statistics10Higher

 

Students are required to complete 90 credits but they may opt to graduate with the Bachelor of Science in Statistics and Decision Science [BSCSDS2] (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 SocietyMATH S280 Statistical Methods for Decision AnalysisMATH 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 SocietyMATH S280 Statistical Methods for Decision AnalysisMATH S249 Practical Modern StatisticsMATH S346 Linear Statistical ModellingMATH S350 Applied Probability Models for Decision MakingSTAT 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.

 

Related programmes

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)

 

 

Enquiries

For enquiries about the programmes, please contact:

Dr Tony Chan 陳滿棠博士
Tel: 3120 2612

Email: tmtchan@ouhk.edu.hk

School of Science & Technology website

 
TOP
Jonathan Chiu
Marketing Director
3DP Technology Limited

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.

Krutz Cheuk
Biomedical Engineer
Hong Kong Sanatorium & Hospital

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
Software and Hardware Engineer
Innovation Team Company Limited

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 CodeTitleCredits
 ELEC S201FBasic Electronics5
 IT S290FHuman Computer Interaction & User Experience Design5
 STAT S251FStatistical Data Analysis5
 Course CodeTitleCredits
 COMPS333FAdvanced Programming and AI Algorithms5
 COMPS362FConcurrent and Network Programming5
 COMPS363FDistributed Systems and Parallel Computing5
 COMPS380FWeb Applications: Design and Development5
 COMPS381FServer-side Technologies and Cloud Computing5
 COMPS382FData Mining and Analytics5
 COMPS390FCreative Programming for Games5
 COMPS413FApplication Design and Development for Mobile Devices5
 COMPS492FMachine Learning5
 ELECS305FComputer Networking5
 ELECS363FAdvanced Computer Design5
 ELECS425FComputer and Network Security5