BSc (Hons) in Mathematics and Statistics
Programme Director: Dr. J. Fan
Bulletin 17/18 and before
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:

to give students a solid foundation in fundamental mathematics and statistics upon which to build their understanding of mathematical applications;

to provide a broadbased applied mathematics and statistics education;

to integrate computing literacy throughout students' studies because computers are indispensable tools for solving mathematical and statistical problems;

to foster in students an eagerness to solve scientific, industrial and commercial problems of concern to the local community and beyond, and

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.

to provide an environment for students to understand, learn, and master the basic modelling and technical knowledge in the major areas of statistics and actuarial science;

to incorporate the underlying theory, principles, and techniques of statistical models to solve problems in insurance, finance and other industries and professions.

to provide an environment for students to understand, learn, and master the basic modelling and technical knowledge in the major areas of financial risk management;

to incorporate the underlying theory, principles, and techniques of applied mathematics and statistics to solve financial risk management problems.

to provide an environment for students to understand, learn, and master the basic modelling and technical knowledge in the major areas of operations research.

to strength students' ability in quantitative analysis and in making statistically sound interpretations, based on the solid knowledge in mathematics and statistics;

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.

to give students a thorough knowledge of numerical methods, numerical analysis, and modelling for practical computing in a broad range of disciplines and applications;
 to provide students rigorous research and analytical skills to evaluate research techniques, methodologies, and to interpret results in their own field and research.

For students seriously considering a career in teaching, they may apply, at the end of Year 2, to join this integrated 5year programme, the suggested study plan of which can be found here.
 Successful graduates from this 5year programme will receive both the BSc (Hons) in Mathematics and Statistics and the Diploma in Education.
Common Year 1 Science Core Courses:  16 units  
BIOL1005 Introduction to Biology  3 units  
CHEM1005 Introduction to Chemistry  3 units  
COMP1005 Essence of Computing  3 units  
MATH1005 Calculus I or MATH1006 Advanced Calculus I  3 units  
PHYS1005 Introduction to Physics and Energy Science  3 units  
SCIE1005 Integrated Science Laboratory  1 unit  
After completing the first year, students in Science Faculty may select BSc in Mathematics and Statistics as their major if they receive * a grade C in MATH1005 Calculus or, * a grade D in MATH1006 Advanced Calculus I. First priority will be given to those students who have achieved a grade of at least B in MATH1005 or at least C in MATH1006. 

Major Requirements for Graduation: 
45 units  
Core Courses (3 units each):  33 units  
MATH2205 Multivariate Calculus  3 units  
MATH2206 Probability & Statistics  3 units  
MATH2207 Linear Algebra  3 units  
MATH2215 Mathematical Analysis or MATH2217 Advanced Calculus II  3 units  
MATH2216 Statistical Methods and Theory  3 units  
MATH3205 Linear Programming and Integer Programming  3 units  
MATH3206 Numerical Methods I  3 units  
MATH3405 Ordinary Differential Equations  3 units  
MATH3805 Regression Analysis  3 units  
MATH3806 Multivariate Statistical Methods  3 units  
MATH4998 Mathematical Science Project I  3 units  
12 units of Major Electives, at least 3 units in Level 4, can be fulfilled with any MATH3XXXX and MATH4XXXX. Job practicum (MATH 34957) cannot be used to fulfil the Major Electives 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:
 Actuarial Statistics (collaborated with Simon Fraser University);
 Financial Risk Management (collaborated with School of Business);
 Operations Research;
 Quantitative Data Analysis;
 Scientific Computing.
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).
For students pursuing one concentration, the allocation of the 129 units for graduation is as follows.

For students pursuing two concentrations, the allocation of the 129 units for graduation is as follows.

The lists of courses for the concentrations are as follows.
Actuarial Statistics  
Core course:  
MATH3837 Actuarial Mathematics  
3 courses from SFU:  
MATH4685, MATH4686, MATH4687 Special Topics in Actuarial Statistics I, II, III*  
MATH3837 Actuarial Mathematics  
MATH4827 Actuarial Mathematics II*  
MATH4835 Property and Casualty Insurance*  
MATH4836 Theory of Pension*  
3 courses from HKBU:  
MATH3826 Markov Chain and Queuing Theory  
MATH4205 Topics in Probability Theory & Stochastic Processes  
MATH4817 Stochastic Models  
MATH4825 Survival Analysis  
MATH4826 Time Series and Forecasting  
Financial Risk Management (choose all 7 courses)  
MATH4205 Topics in Probability Theory and Stochastic Processes  
MATH4216 Mathematical Finance  
MATH4826 Time Series and Forecasting  
MATH4837 Risk and Portfolio Management  
FINE3006 Introduction to Futures and Options Markets  
FINE3007 Fixed Income Securities  
FINE4006 Financial Risk Management  
Operations Research (choose any 7 courses)  
MATH3425 Graph Theory  
MATH3427 Real Analysis  
MATH3605 Numerical Methods II  
MATH3625 Iterative Methods  
MATH3807 Simulation  
MATH3817 Dynamic Programming and Stochastic Programming  
MATH3826 Markov Chain and Queuing Theory  
MATH3827 Logistics, Inventory Models and Networks  
MATH3836 Data Mining  
MATH4615 Introduction to Numerical Linear Algebra  
MATH4815 Interior Point Methods for Convex Optimization  
MATH4816 Optimization Theory and Techniques  
MATH4826 Time Series and Forecasting  
MATH4865, MATH4866, MATH4867 Special Topics in Operations Research I, II, III  
Quantitative Data Analysis (choose any 7 courses)  
MATH3416 Complex Analysis  
MATH3427 Real Analysis  
MATH3605 Numerical Methods II  
MATH3815 Statistical Design and Analysis of Experiments  
MATH3816 Statistical Analysis of Sample Surveys  
MATH3826 Markov Chain and Queuing Theory  
MATH3836 Data Mining  
MATH4205 Topics in Probability Theory and Stochastic Processes  
MATH4615 Introduction to Numerical Linear Algebra  
MATH4805 Applied Nonparametric Statistics  
MATH4807 Categorical Data Analysis  
MATH4817 Stochastic Models  
MATH4825 Survival Analysis  
MATH4826 Time Series and Forecasting  
MATH4875, MATH4876, MATH4877 Special Topics in Statistics I, II, III  
Scientific Computing (choose any 7 courses)  
MATH3407 Advanced Linear Algebra  
MATH3415 Vector Calculus  
MATH3416 Complex Analysis  
MATH3427 Real Analysis  
MATH3605 Numerical Methods II  
MATH3606 Partial Differential Equations  
MATH3615 Introduction to Imaging Science  
MATH3616 Numerical Methods for Differential Equations  
MATH3625 Iterative Methods  
MATH4606 Functional Analysis  
MATH4615 Introduction to Numerical Linear Algebra  
MATH4815 Interior Point Methods for Convex Optimization  
MATH4816 Optimization Theory and Techniques  
MATH4817 Stochastic Models  
MATH4665, MATH4666, MATH4667 Special Topics in Applied Mathematics I, II, III  
