Minor Requirements

Minor Title Minor in Statistics
Offered to students admitted to Year 1 in 2025
Objectives:

The curriculum of the Minor in Statistics is structured specifically to cater for the general need of non-statistical disciplines and provide basic training in statistical methodologies and their applications to practical problems. It aims to provide students with a strong and rigorous sense of quantitative reasoning that has become an indispensable skill in nearly all disciplines.
Learning Outcomes:
By the end of this programme, students should be able to:
PLO 1 :

acquire basic statistical knowledge alongside their major disciplines, with emphases on correct applications of statistical methods and insightful interpretations of statistical findings (by means of coursework, tutorial classes and project-based learning in the curriculum)
PLO 2 :

equip with computational skills essential to conducting complete data analyses (by means of coursework, tutorial classes, project-based learning and presentation opportunities in the curriculum)
PLO 3 :

participate proactively in large-scale, multi-disciplinary studies, determine objective findings, and provide guidance on all aspects of data collection and analyses (by means of coursework, tutorial classes and project-based learning in the curriculum)
Impermissible Combinations:

Bachelor of Statistics
Major in Decision Analytics
Major in Risk Management
Major in Statistics
Minor in Risk Management
Required courses (48 credits)
1. Introductory level courses (24 credits)
Disciplinary Electives (24 credits)
At least 24 credits selected from the following courses:
MATH1013 University Mathematics II (6)
MATH2014 Multivariable Calculus and Linear Algebra (6)
SDST1018 Foundations of Data Science (6)
SDST1600 Statistics: Ideas and Concepts (6)
SDST2601 Probability and Statistics I (6)
SDST2602 Probability and Statistics II (6)
SDST2604 Introduction to R/Python Programming and Elementary Data Analysis (6)
2. Advanced level courses (24 credits)
Disciplinary Electives (24 credits)
At least 24 credits selected from the following courses:
SDST3021 Modern Biostatistics (6)
SDST3600 Linear Statistical Analysis (6)
SDST3602 Statistical Inference (6)
SDST3603 Stochastic Processes (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)
SDST3612 Statistical Machine Learning (6)
SDST3613 Marketing Analytics (6)
SDST3617 Sample Survey Methods (6)
SDST3620 Modern Nonparametric Statistics (6)
SDST3621 Statistical Data Analysis (6)
SDST3655 Survival Analysis (6)
SDST4601 Time-Series Analysis (6)
SDST4602 Multivariate Data Analysis (6)
SDST4610 Bayesian Learning (6)
SDST4611 High-Dimensional Statistical Learning (6)
SDST4613 Causal Inference (6)
 
Note:

If the same courses are listed as disciplinary core in both this minor and the primary major (or programme/professional core) undertaken by a student, the student must make up the number of credits by taking replacement course(s) stipulated by the minor. Double counting of credits is not permissible.
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 curriculum of the declared minor in order to satisfy the requirements of the minor.