| Programme Title |
Bachelor of Statistics (Professional Core in Decision Analytics) [BStat(DA)] |
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Offered to students admitted to Year 1 in |
2025
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Objectives:
The Professional Core in Decision Analytics aims to equip students with skills and expertise in leveraging and managing big data in real time. It enables students to examine, translate and classify data, uncover hidden patterns and unknown correlations, and most importantly, pinpoint precisely the most critical areas and implications suggested by data. Adopting a coordinated approach to teaching across three disciplinary fields, namely statistics, mathematics and computer science, with the assistance of statistically guided AI techniques, it provides students with solid training in making digitised information a strategic part of critical decision-making and resource allocation at high levels of clarity and accuracy. Built upon a synergy between data science and statistical reasoning, it also strives to enrich artificial intelligence with a strong touch of human intelligence. Decision Analytics students are trained with both rigorous statistical concepts and computational skills in data analytics. They are educated with problem-solving skills to provide optimized solutions to real life problems based on big data.
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Learning Outcomes:
By the end of this programme, students should be able to:
| PLO 1 : |
apprehend the concepts of decision analytics and its underlying theory in relation to a broad range of related disciplinary academic or professional areas
(by means of coursework, tutorial classes and/or project-based learning in the curriculum) |
| PLO 2 : |
identify and adopt appropriate analytical techniques and tools to extract and classify critical information from structured or unstructured data
(by means of coursework, tutorial classes and/or project-based learning in the curriculum) |
| PLO 3 : |
be proficient with the design and implementation of advanced modelling techniques and database management, and offer effective recommendations for analytic initiatives and solutions
(by means of coursework, tutorial classes and/or project-based learning in the curriculum) |
| PLO 4 : |
evaluate the quality of information from different sources in support of critical decision making, process streamlining and the optimization of resources, and appraise the related ethical issues
(by means of coursework, tutorial classes and/or project-based learning in the curriculum) |
| PLO 5 : |
communicate to people effectively and efficiently with professionalism and accuracy using interactive and dynamic tools to translate technical information and present collaborative and strategic ideas
(by means of coursework, tutorial classes, project-based and/or capstone learning in the curriculum) |
| PLO 6 : |
gain insights into current advances in decision analytics and confidence to solve real-life problems through either project or industrial training
(by means of coursework, tutorial classes, project-based and/or capstone learning in the curriculum) |
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Impermissible Combinations:
Major in Computer Science
Major in Decision Analytics
Major in Risk Management
Major in Statistics
Minor in Computer Science
Minor in Risk Management
Minor in Statistics
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Required courses (120 credits)
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Notes:
1. If the same courses are listed as disciplinary core in both the programme and a second major undertaken by a student, the student must make up the number of credits by taking replacement course(s) stipulated by the second major. Double counting of credits is not permissible.
2. Students should have level 2 or above in HKDSE Mathematics Extended Module 1 or 2 or equivalent to take this Professional Core. Students who do not fulfill this requirement are advised to first take MATH1011 University Mathematics I.
3. Students may consider taking the following courses if they wish to pursue a more focused study in the following areas:
a. Biomedical Analytics
SDST3021 Modern Biostatistics
SDST3607 Statistics in Clinical Medicine and Bio-Medical Research
SDST3608 Statistical Genetics
SDST3620 Modern Nonparametric Statistics
SDST3621 Statistical Data Analysis
SDST4022 Omics Data Analysis
SDST4023 Medical Image Analysis
SDST4602 Multivariate Data Analysis
b. Financial and Risk Analytics
SDST3621 Statistical Data Analysis
SDST4601 Time-Series Analysis
Plus advanced level courses listed for the Professional Core in Risk Management
c. Operational Analytics
COMP3251 Algorithm Design
MATH3901 Operations Research I
MATH4902 Operations Research II
SDST3606 Business Logistics
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Remarks:
Important! Ultimate responsibility rests with students to ensure that the required pre-requisites and co-requisites of selected courses are fulfilled. Students must take and pass all required courses in the
selected Professional Core
in order to satisfy the degree graduation requirements.
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