Programme (Professional Core) Requirements

Programme Title Bachelor of Statistics (Professional Core in Statistics) [BStat(ST)]
Offered to students admitted to Year 1 in 2025
Objectives:

The Professional Core in Statistics focuses on the study of statistics, a scientific discipline characterised by the development and applications of analytical and quantitative tools which involve logical thinking, problem formulation, statistical reasoning and intensive data analyses. The programme aims to equip students with powerful mathematical, analytical and computational skills, which are in great demand in practical areas where data are obtained for the purpose of extracting information in support of evidence-based decision making. It helps students to build a strong background in statistical concepts and theory, and provides broad and solid training in applied statistical methodologies. Indeed, such applications of statistics as an analytical and reasoning tool have been given growing prominence in the modern society. In response to this welcoming trend, the curriculum is constantly revised to meet a steadily rising demand for specialist statisticians, data scientists and quantitative analysts in government, business, finance, industry, as well as in research and teaching in local and overseas institutions.
Learning Outcomes:
By the end of this programme, students should be able to:
PLO 1 :

receive solid training in probability and statistics, gain insight into their underlying theory and be acquainted with their state-of-the-art applications in the modern world (by means of coursework, tutorial classes and/or project-based learning in the curriculum)
PLO 2 :

conduct meticulous data analyses, supported by rigorous statistical reasoning, to make informed decisions in the face of uncertainty that arises in all sorts of institutions and companies, and appraise the related ethical issues (by means of coursework, tutorial classes and/or project-based learning in the curriculum)
PLO 3 :

equip with hands-on experience in data analysis using statistical software, and be competent for data-analytic jobs which require advanced computational skills (by means of coursework, tutorial classes and/or project-based learning in the curriculum)
PLO 4 :

be highly motivated to explore cross-disciplinary applications of statistics in a broad variety of academic or professional areas including, in particular, mathematics, natural sciences, economics, finance, business, risk management, actuarial work, social sciences and engineering (by means of coursework, tutorial classes and/or project-based learning in the curriculum)
PLO 5 :

communicate and collaborate with people effectively on probability and statistical issues (by means of coursework, tutorial classes, project-based and/or capstone learning in the curriculum)
PLO 6 :

through the understanding and application of statistical concepts and techniques, gain confidence to meet challenges posed by increasingly complicated real-life problems encountered in the modern era in a creative and rational manner (by means of coursework, tutorial classes, project-based and/or capstone learning in the curriculum)
Impermissible Combinations:

Major in Decision Analytics
Major in Risk Management
Major in Statistics
Minor in Risk Management
Minor in Statistics
Required courses (120 credits)
1. Introductory level courses (42 credits)
Disciplinary Core Courses (30 credits)
COMP1117 Computer Programming (6)
MATH1013 University Mathematics II (6)
SDST1600 Statistics: Ideas and Concepts (6)
SDST2601 Probability and Statistics I (6)
SDST2602 Probability and Statistics II (6)
Disciplinary Elective Courses (12 credits)
Select either List A or List B:
List A (for general study)
MATH2012 Fundamental Concepts of Mathematics (6)
MATH2014 Multivariable Calculus and Linear Algebra (6)
List B (for advanced study)
MATH2101 Linear Algebra I (6)
MATH2211 Multivariable Calculus (6)
2. Advanced level courses (72 credits)
Disciplinary Core Courses (42 credits)
SDST3600 Linear Statistical Analysis (6)
SDST3602 Statistical Inference (6)
SDST3603 Stochastic Processes (6)
SDST3620 Modern Nonparametric Statistics (6)
SDST3621 Statistical Data Analysis (6)
SDST4602 Multivariate Data Analysis (6)
SDST4610 Bayesian Learning (6)
Disciplinary Electives (36 credits)
Select at least 30 credits from List S1 and List S2, among which at least 6 credits from List S1, and at least 12 credits from List S2
List S1 (mainstream statistical topics)
SDST3612 Statistical Machine Learning (6)
SDST3655 Survival Analysis (6)
SDST4601 Time-Series Analysis (6)
List S2 (statistical applications and other advanced topics)
SDST3021 Modern Biostatistics (6)
SDST3604 Design and Analysis of Experiments (6)
SDST3606 Business Logistics (6)
SDST3607 Statistics in Clinical Medicine and Bio-medical Research (6)
SDST3608 Statistical Genetics (6)
SDST3613 Marketing Analytics (6)
SDST3617 Sample Survey Methods (6)
SDST4611 High-Dimensional Statistical Learning (6)
SDST4613 Causal Inference (6)
SDST7609 Research Methods in Statistics (6)
SDST7610 Advanced Probability (6)
3. Capstone requirement (6 credits)
At least 6 credits selected from the following courses:
SDST3799 Directed Studies in Statistics (6)
SDST4710 Capstone Experience for Statistics Undergraduates (6)
SDST4766 Statistics Internship (6)
SDST4799 Statistics Project (12)
 
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.
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.