BSc (Hons) in Mathematics and Statistics

Programme Director: Prof L. Liao

Bulletin 22/23

 

Aims and Objectives

The B.Sc. programme is designed to provide students with an education that prepares them for careers as practicing mathematicians and/or statisticians. In order to accomplish this aim in the Hong Kong context, certain objectives have been incorporated into the curriculum as follows:

  1. to give students a solid foundation in fundamental mathematics and statistics upon which to build their understanding of mathematical applications;
  2. to provide a broad-based applied mathematics and statistics education;
  3. to integrate computing literacy throughout students' studies because computers are indispensable tools for solving mathematical and statistical problems;
  4. to foster in students an eagerness to solve scientific, industrial and commercial problems of concern to the local community and beyond, and
  5. to teach students how to formulate suitable mathematical and statistical models for solving these problems.

The optional concentrations provide great flexibility to students. Students can choose the programme without concentration, one or even two concentrations according to their interest and career goal. These concentrations are designed to deliver some more specific objectives.

Concentration in Applied Statistics
  1. To strengthen students' ability in quantitative analysis and in making statistically sound interpretations, based on the solid knowledge of mathematics and statistics;
  2. To incorporate the underlying theory, principles, and techniques of applied mathematics and statistics with scientific computation tools and statistical and computing software packages to solve practical problems.
Concentration in Data Science
  1. To combine mathematics, statistics, and computing into an integrated curriculum, providing students the rigorous theoretical background of data science methods and techniques necessary for success in data-related fields in addition to just know how to implement them;
  2. To synthesize the analytical skills and mathematical knowledge to analyze data, draw conclusions, and make decisions in real-life situation.

Common Year 1 Science Core Courses:
BIOL1005 Introduction to Biology
CHEM1005 Introduction to Chemistry
COMP1005 Essence of Computing*
MATH1025 Understanding Mathematics and Statistics*
PHYS1005 Introduction to Green Energy
SCIE1005 Integrated Science Laboratory
 
*Required courses for students taking MATH & STAT as major
 
After completing the first year, students in Science Faculty may select BSc in Mathematics and Statistics as their major if they receive
(a) cGPA 2.0; and
(b) Grade C in MATH1025 Understanding Mathematics and Statistics
 
At most one of BIOL1005, CHEM1005 and PHYS1005 can be replaced by a 3-unit Major elective course.

Major Requirements for Graduation:

Core Courses (3 units each):
MATH1005 Calculus I
MATH2225 Calculus II
MATH2205 Multivariate Calculus
MATH2206 Probability & Statistics
MATH2207 Linear Algebra I
MATH2215 Mathematical Analysis
MATH2216 Statistical Methods and Theory
MATH3205 Operations Research I
MATH3206 Scientific Computing I
MATH3405 Differential Equations I
MATH3805 Regression Analysis
MATH3806 Multivariate Statistical Methods
MATH4998 Mathematical Science Project I
 

12 units of Major Electives, at least 3 units in Level 4, can be fulfilled with any MATH3XXX and MATH4XXX excluding MATH3495/3496/3497 Job practicum, MATH3095/3096 Summer Research. The GE capstone GCAP3005 or GCAP3017 can be double-counted towards the major elective requirements, and the outstanding 3 units have to be made up by taking any 3-unit letter-grade MATH1xxx or MATH2xxx courses. However, none of these two courses can be counted towards the concentration requirement.

 

Concentrations

The additional graduation option of BSc (Hons) in Mathematics and Statistics with Concentration is available. The Department of Mathematics offers the following concentrations:

  1. Applied Statistics;
  2. Date Science.

Students can make use of the Major Electives and Free Electives to pursue a concentration within the department by completing seven required courses (or 21 units).

It is possible for students to make use of the remaining Free Electives to pursue a second concentration by completing another seven required courses (or 21 units) in the second concentration. Courses may not be doubled counted towards multiple concentration requirements. Students are welcome to seek advice from academic advisor of the corresponding concentration if assistance is needed.

For students pursuing one concentration, the allocation of the 128 units for graduation is as follows.

University Core13 units  
General Education18 units  
Common Year 1 Science Core16 units  
Major Core 39 units   
Major Electives12 units Concentration (Optional)
Free Electives9 units
Free Electives21 units  
  128 units  

 

For students pursuing two concentrations, the allocation of the 128 units for graduation is as follows.

University Core13 units  
General Education18 units  
Common Year 1 Science Core16 units  
Major Core 39 units  
Major Electives12 units Concentration 1 (Optional)
Free Electives9 units
Free Electives21 unitsConcentration 2 (Optional)
  128 units  

 

The lists of courses for the concentrations are as follows. Note that neither GCAP3005 nor GCAP3017 will be counted towards the concentration requirement.

Data Science (total 7 courses)
Group A: All of:
MATH3836 Data Mining
MATH4225 Foundation of Big Data and Learning
 
Group B: At least 6 units from:**
MATH4226 Introduction to Deep Learning
MATH4227 Programming for Data Science
MATH4815 Interior Point Methods for Convex Optimization
MATH4816 Optimization Theory and Techniques
 
Group C: At least 3 units from:**
MATH3427 Real Analysis
MATH3605 Numerical Methods II
MATH3615 Introduction to Imaging Science
MATH3626 Computational Statistics for Data Science
MATH3826 Operations Research II
MATH4615 Numerical Linear Algebra
MATH4807 Categorical Data Analysis
MATH4826 Time Series and Forecasting
MATH4875, 4876, 4877 Special Topics in Statistics I, II, III

 

** Students should take MATH4225 and MATH3836 as core courses; at least 6 units from Group B; and the remaining units from either Group B or Group C.

The GE capstone GCAP3005 or GCAP3017 cannot be double-counted towards the concentration requirement.

 

Applied Statistics (retitled from Quantitative Data Analysis) (choose any 7 courses)
MATH3416 Complex Analysis
MATH3427 Real Analysis
MATH3605 Numerical Methods II
MATH3626 Computational Statistics for Data Science
MATH3815 Statistical Design and Analysis of Experiments
MATH3816 Statistical Analysis of Sample Surveys
MATH3825 Life Insurance and Life Contingencies
MATH3826 Operations Research II
MATH3836 Data Mining
MATH4205 Topics in Probability Theory and Stochastic Processes
MATH4615 Numerical Linear Algebra
MATH4805 Applied Nonparametric Statistics
MATH4807 Categorical Data Analysis
MATH4817 Stochastic Models
MATH4825 Survival Analysis
MATH4826 Time Series and Forecasting
MATH4875, 4876, 4877 Special Topics in Statistics I, II, III