BSc (Hons) Mathematical Sciences Bachelor's degree at London Metropolitan University

This module introduces methods of analysing data using appropriate statistical software. Descriptive statistics and statistical techniques that are useful to present, analyse and make inferences about data are also introduced. A selection of suitable software (e.g. Excel, SPSS, R) will enable students to analyse data in order to make informed decisions.

This module develops the mathematical and statistical tools that are used in the mathematics of finance. This module introduces the basic terminologies used in finance and develops the mathematical techniques to solve real-life problems in finance. The module will provide an introductory knowledge of Excel, and Excel built functions in financial computing. The application of suitable software (e.g. Excel) will enable students to solve financial problems in order to draw valid conclusions and mak

In this module, we introduce the basic concepts of graph theory, focusing on finite graphs. These include numerical invariants of graphs and methods for calculating them; how to navigate through graphs (including the method that lies behind the resolution of the Königsberg problem discussed above); vertex and edge colourings of graphs and other numerical invariants of graphs; the conditions under which a graph is planar.

This module introduces a range of numerical approximation methods for solving a variety of mathematical problems, including iterative methods for solving nonlinear equations and systems of linear equations. There is also an introductory course on LaTeX, which is a high-quality document preparation system commonly used for writing, editing, and designing mathematical documents and technical reports.

This module develops a range of mathematical techniques including set theory, logic, relations and functions, algebra, differentiation and integration. The techniques provide the foundation for further study of mathematics and related applications in Computer Science, Computer Games Programming, Computer Systems Engineering and Robotics and Electronics and Internet of Things.

This module introduces a mathematical programming package that is commonly used for solving a variety of problems, where there is an expectation of some knowledge of calculus, linear algebra. The application of these techniques, through the medium of mathematical problems enables the student to become proficient in the use of algebraic software which is used in most mathematical related jobs such as working in industry, financial markets, and teaching.

This module develops the skills necessary to support academic study at degree level. It will also develop reflective learning and action planning via the Personal Development Planning (PDP) process. The first term topics will look into history of mathematics, development of modern number system and introduce idea of mathematical proofs. Different proof techniques will be covered using examples from Set Theory and Number Theory.

The module builds on and extends concepts learned in A-Level Mathematics such as complex numbers, vectors, and matrices. This module serves as an introduction to linear algebra methods, which are central in modern mathematics, having found applications in many other sciences and in our everyday life. The module covers basic mathematical techniques of linear algebra such as Systems of linear equations and Gaussian elimination, Matrices and Determinants, and Diagonalisation. The contents covered a

The module extends the students' knowledge of the techniques of calculus and introduces the concept of differential equations. This module aims to give students a thorough understanding of the analytical techniques available to solve first and second order ordinary differential equations.

The module covers basic mathematical techniques of differential and integral calculus. The module builds on and extends concepts learned in A-Level Mathematics. The contents covered and the skills developed are fundamental to the development of mathematical competence. Calculus forms an important foundation for further studies in Mathematics, Finance, Statistics and Engineering.

This module introduces a selected range of Operational Research techniques that are commonly used for solving a variety of small to medium size problems, through the medium of spreadsheet and other suitable software. It also enables the student to investigate real-life problems of business and industrial problems of varied complexity.

This module enables the student to further develop and apply numerical techniques to a range of problems including the solution of ordinary differential equations related to both physical and financial/economic models. The aims are: To enable students to apply approximation techniques to problems of both theoretical and practical importance and understand the cause of and interpret the degree of error involved. To prepare students with the tools necessary for solving a range of problems in situa

The topics covered in the first part of this module is to introduce students to the abstract algebraic structures of groups, which arise from the ideas of symmetries and of vector and matrix calculus respectively. These two primary examples of algebraic structures have applications across science and engineering, and also provide a firm foundation of necessary basic algebraic notions for the student to further their study mathematical study. The aim of the second part of the module is to introdu

The module covers mathematical and statistical modelling techniques that are applied in making decisions in areas of finance. It also enables the student to investigate real-life statistical data. This module introduces important financial concepts and develops statistical modelling techniques. Statistical regression models are applied to financial data (e.g., credit scoring, default time analysis) and mathematical modelling of stock and option prices is investigated. A selection of suitable sof

This module serves as a core module for all maths students (and optional for Data Science students) to do a one-semester project in the broader sense. The feature of the module is summarised as follows. 1. Students will follow their own interest to pursue an individualised study independently under staff supervision. 2. Students taking this module with the same supervisor may study the same subject but the assessments should be individualised. 3. The allocation of supervisors to students should