BSc (Hons) Mathematics and Statistics Bachelor's degree at West London

This module aims to provide a basic knowledge of how to summarise, analyse and interpret data, provide an overview of sampling and experimentation in the mathematical sciences and engineering field, and deliver an introduction to modelling a linear relationship between variables.

The Personalised Learning module is intended to equip you with the study skills needed to successfully progress onto level 4, the first year of undergraduate study. Tutor group sessions are an integral part of the module, where you will consolidate your learning and frame it in the context of your subject area. The module will focus on various aspects of study skills, such as those skills related to reading and writing, learning approaches, problem-solving techniques, critical thinking, research

The module provides you with a strong mathematical grounding to prepare you to undertake further mathematics throughout the course. The module will start by covering essential basis of numbers, the application of algebraic and trigonometric principles, application of differential calculus and complex numbers.

This module will enable you to read critically, present an argument and distinguish between the quality and suitability of materials. It will prepare you to use and evaluate a range of evidence sources throughout your degree.

The aim of this module is to extend your knowledge of matrices, vectors and systems of linear equations and to introduce the abstract concepts of vector spaces, linear maps and inner products.

This module provides you with the basic mathematical concepts and techniques of discrete structures. It includes the study of mathematical logic, sets, relations and functions. The module will develop your skills in expressing problems in mathematical language, using mathematical techniques to find solutions to problems and communicating mathematical ideas clearly and succinctly.

On this module you will learn how to program computers and other devices using a modern programming language. Module topics include: algorithm development fundamentals of computer programming control structures input/output functions structuring of data introduction to object-oriented programming. The module is introductory in nature and assumes no prior programming knowledge. The module includes weekly computing practical.

This module is an introduction to probability theory and statistical methods. The module leads to a deeper understanding of probability distributions, random variables and their role in sampling. Tools such as hypothesis testing are presented and a basic introduction to the statistical software SPSS is provided.

This module introduces you to the most important techniques in Calculus. In particular, the module leads to a deeper understanding of the concepts of differentiation and integration. Tools and techniques for differentiation and integration will be presented in detail.

Real analysis deals with numbers along the one dimensional number line, while complex analysis deals with numbers in two dimensions. This module will introduce you to the rigorous development of both real and complex analysis and will help to develop your skills in deductive reasoning.

The aim of this module is to give you knowledge and techniques for working with vectors and vector fields. You'll extend your understanding of calculus and will be introduced to the concept of multivariable calculus as well as calculus of vectors.

On this module, you will extend your knowledge of the fundamental mathematical methods used in engineering. The module includes study of Laplace transforms, Fourier analysis, ordinary differential equations, introduction to partial differential equations and complex variables. In addition, the module will develop your skills in expressing problems in mathematical language, using mathematical techniques to find solutions to problems and communicating mathematical ideas clearly and succinctly.

This module aims to introduce you to the numerical techniques required to solve different mathematical problems motivated by the engineering and the science sector.

This module aims to develop understanding and proficiency in statistical modelling by introducing you to the normal theory linear model. It will provide you with the ability to formulate and apply these models in a range of practical settings, to carry out associated inference appreciating how this relates to the general likelihood inferential framework, and to perform appropriate model selection and model checking procedures.

This module aims to study both the qualitative and quantitative aspects of ordinary and linear partial differential equations.

The module aims to develop an understanding of the elements of non-linear differential equations and dynamical systems. The aim of this module is to expose you to qualitative and quantitative methods for dynamical systems, including nonlinear ordinary differential equations, maps and chaos. The phenomena studied occur in many physical systems of interest.

The module aims to introduce you to stochastic processes and their applications.

The module aims to introduce you to linear programming, the Simplex Method and the Transportation Algorithm. The module will enable you to solve linear programming problems as primal problems or using duality. The module includes an introductory theory for nonlinear programming problems by demonstrating the application of Lagrange Multiplier Theory as well as tackling optimisation problems.

You will investigate a topic of interest and prepare a project proposal. You will then present your ideas to the School for approval and, once this has been approved, you will begin a detailed literature review of your chosen field. You will choose and follow a suitable development methodology leading to an implementation which you will evaluate.