BSc (Hons) Mathematics with Finance

Provides students with an understanding of essential finance and accounting terminology and methods to enable them to perform effectively and efficiently within their future workplace. Using practical examples, students will gain confidence to be able to financial modelling skills using Excel.

This module covers the exploratory analysis of datasets (including basic relational database skills to extract data from appropriate sources), the use of probability to handle uncertainty and develops techniques of hypothesis testing and confidence interval construction.

This module will provide the basic mathematical concepts and methods needed to solve a range of problems with scientific, business and statistical applications. You will be introduced to concepts of complex numbers and their application and introduced to methods for solving ordinary first and second order differential equations.

This module provides you with the experience of using pencil-and-paper techniques and mathematical software to solve realistic problems in Linear Algebra.

This module aims to develop programming and problem solving skills to help prepare for work in mathematics and statistics.

This module familiarises you with fundamental skills and mathematical techniques. It provides you with an appreciation of the concept of mathematical proof and give opportunities for practicing different proof techniques. It will also introduce you to mathematical writing. It will give you an appreciation in which historical context and cultures, fundamental mathematical concepts originated.

The aim of this module is to enable you to make evidence-based investment decisions and analyse financial statements and performance in order to ensure sustainability, liquidity and profitability.

This module continues to build on mathematical methods and elements of discrete/finite mathematics which have increasing application in science, engineering and business decision making.

This module covers simple and multiple linear regression, basic one and two-way Analysis of Variance models, and the process of statistical modelling.

This module will extend your knowledge of the use of probability models to introduce the use of simulation models in order to enable you to familiarise yourself with risk techniques through which can assist decision makers in making informed decisions in the face of uncertainty.

This module will familiarises you with the employment market and the expectations of employers, and develops employability skills. The module also develops advanced I.T. skills related to Mathematics and Statistics.

This module will build on differential equation theory that was introduced in Mathematical Methods. You will be introduced to systems of ordinary differential equations (ODEs) and determine how to solve linear autonomous systems of ODEs and to introduce the concepts of asymptotic theory as a tool for analytically approximating the solution of differential equations.

The aim is to provide students with an extended period of work experience at an approved partner that will complement their programme of study at LJMU. This will give students the opportunity to develop professional skills relevant to their programme of study as well as the attitude and behaviours necessary for employment in a diverse and changing environment. This extended placement forms a key part of a sandwich degree. All placements need to be assessed and approved prior to commencement in line with the LJMU Placement Learning Code of Practice. The Code of Practice requires students to conduct themselves in a professional and responsible manner during the placement - failure to do so may lead to the placement being terminated prematurely. Placements are normally for one calendar year on a full-time basis. Split placements of a shorter duration may be permissible. There is an expectation that a minimum of 1200 hours will be spent in the workplace.

The aim is to provide students with an additional year of study at an approved overseas partner that will complement their programme at LJMU. This is an additional year of full-time study at an approved higher education institution. The modules to be studied must be agreed in advance, and must be appropriate for the student's programme of study. Assuming successful completion of this year, mark-bearing credit will be awarded by the Faculty Recognition Group. The grade conversion scale to be used will be made available in advance of the year abroad.

Designed to enable students to make corporate financial decisions in an increasingly volatile international marketplace, in order to increase profitability, maintain liquidity and reduce financial risk.

The aim of this module is to develop and widen your experience of tackling a realistic problem selected from the domain of your programme by carrying out independent research to extend the your ability to communicate the solution to a significant problem.

This module aims to extend your mastery of calculus in application areas such as vectors, complex numbers transforms and series. It will demonstrate the use of functions of a complex variable to evaluate real integrals. It will extend theory introduced in Differential Equations at Level 5 and provide an introductory course on solving Partial Differential Equations (PDEs).

The aim of this module is to examine a wide range of operational research methods and your applicability to real-life problems encountered in business and industry.

This module will teach the application of mathematical models to a variety of problems in biology and medicine. The aims of the module are to introduce mathematical models of biological systems and techniques for analysing them.

This module aims at providing you with a rigorous framework within which you will learn to make personal financial decisions.

This module aims to give you an experience of campus-based work related learning focusing on the role of a statistician in industry and how statistical methods are applied in both manufacturing and business.

This module gives an introduction to Data Science and aims to introduce you to the Data Science field, providing you with a wide range of methods and state-of-the-art technologies that are on demand in the job market.

This module enables you to explore the structure of multidimensional data sets. It will introduce you to inferential procedures using multivariate data. It will explore the structure of data in the form of a time series, and make forecasts of future observations that will arise in the time series.