also available in 2018
A Level Requirements
see all requirements
see all requirements
Full time 3 Year(s)
The MORSE scheme at Lancaster is specifically designed for numerate students wishing to pursue careers in industry, commerce, finance and the public sector. It provides knowledge and key skills in areas that are in great demand and emphasises the application of those ideas in the real world.
The programme equips you with competencies in a variety of quantitative and analytical subjects. Creating strong foundations in mathematics, operations research, statistics and economics in the first year of study, the programme then allows you to tailor your personal programme, whether this is by developing your knowledge in all areas or specialising in those topics that you see as most relevant to your future career. These might be in pure mathematics, statistics, business analytics, economics or management topics. Taught by our world-class Departments of Mathematics and Statistics, Economics, and Management Science the programme offers a wide range of choice for students, all of which focus on applying mathematical knowledge and theory in a practical context.
A Level AAA
Subject Requirement A level Mathematics grade A
GCSE Mathematics grade B or 6, English Language grade C or 4
IELTS 6.5 overall with at least 5.5 in each component. For other English language qualifications we accept, please see our English language requirements webpages.
International Baccalaureate 35 points overall with 16 points from the best 3 Higher Level subjects including 6 in Mathematics HL
BTEC Considered alongside A level Mathematics grade A
We welcome applications from students with a range of alternative UK and international qualifications, including combinations of qualification. Further guidance on admission to the University, including other qualifications that we accept, frequently asked questions and information on applying, can be found on our general admissions webpages.
Contact Admissions Team + 44 (0) 1524 592028 or via email@example.com
Many of Lancaster's degree programmes are flexible, offering students the opportunity to cover a wide selection of subject areas to complement their main specialism. You will be able to study a range of modules, some examples of which are listed below.
Students are provided with an understanding of functions, limits, and series, and knowledge of the basic techniques of differentiation and integration. Examples of functions and their graphs are presented, as are techniques for building new functions from old. Then the notion of a limit is considered along with the main tools of calculus and Taylor Series. Students will also learn how to add, multiply and divide polynomials, and will learn about rational functions and their partial fractions.
The exponential function is defined by means of a power series which is subsequently extended to the complex exponential function of an imaginary variable, so that students understand the connection between analysis, trigonometry and geometry. The trigonometric and hyperbolic functions are introduced in parallel with analogous power series so that students understand the role of functional identities. Such functional identities are later used to simplify integrals and to parametrise geometrical curves.
This module extends the theory of calculus from functions of a single real variable to functions of two real variables. Students will learn more about the notions of differentiation and integration and how they extend from functions defined on a line to functions defined on the plane. They will see how partial derivatives can help to understand surfaces, while repeated integrals enable them to calculate volumes. The module will also investigate complex polynomials and use De Moivre’s theorem to calculate complex roots.
In mathematical models, it is common to use functions of several variables. For example, the speed of an airliner can depend upon the air pressure, temperature and wind direction. To study functions of several variables, rates of change are introduced with respect to several quantities. How to find maxima and minima will be explained. Applications include the method of least squares. Finally, various methods for solving differential equations of one variable will be investigated.
Management science is used in all major organisations in industry, commerce, finance and government. Its application might involve well-defined problems, such as reducing the cost of a complex goods distribution network, or more nebulous problems, such as improving patient care in hospital. Techniques based on mathematics and statistics can be extremely powerful in helping to solve these organisational problems.
Five such techniques will be introduced:
The module emphasises not only how to apply techniques, but also when (and when not) to apply them. There is a stress on practical examples of using the techniques.
You will work on two challenging case studies based on real problems. These provide the opportunity to apply concepts and techniques of problem solving, making recommendations and reporting results. To take this module you must also be taking one of MSCI 101, 100 or MNGT130.
Introducing the theory of matrices together with some basic applications, students will learn essential techniques such as arithmetic rules, row operations and computation of determinants by expansion about a row or a column.
The second part of the module covers a notable range of applications of matrices, such as solving systems of simultaneous linear equations, linear transformations, characteristic eigenvectors and eigenvalues.
The student will learn how to express a linear transformation of the real euclidean space using a matrix, from which they will be able to determine whether it is singular or not and obtain its characteristic equation and eigenspaces.
Providing a thorough introduction to the discipline of Economics, this module is divided into two parts. The first part covers microeconomic analysis, including the theory of demand, costs and pricing under various forms of industrial organisation, and welfare economics. Many applications of theoretical models are examined. The second part focuses on macroeconomic analysis, including national income analysis, monetary theory, business cycles, inflation, unemployment, and the great macroeconomic debates.
Probability theory is the study of chance phenomena, the concepts of which are fundamental to the study of statistics. This module will introduce students to some simple combinatorics, set theory and the axioms of probability.
Students will become aware of the different probability models used to characterise the outcomes of experiments that involve a chance or random component. The module covers ideas associated with the axioms of probability, conditional probability, independence, discrete random variables and their distributions, expectation and probability models.
To enable students to achieve a solid understanding of the broad role that statistical thinking plays in addressing scientific problems, the module begins with a brief overview of statistics in science and society. It then moves on to the selection of appropriate probability models to describe systematic and random variations of discrete and continuous real data sets. Students will learn to implement statistical techniques and to draw clear and informative conclusions.
The module will be supported by the statistical software package ‘R’, which forms the basis of weekly lab sessions. Students will develop a strategic understanding of statistics and the use of associated software, which will underpin the skills needed for all subsequent statistical modules of the degree.
This module is designed to give you an introduction to probability and statistics and to make you familiar with some useful computer tools.
The statistical topics covered are sampling, introductory data analysis and presentation, probability, the use of some important probability distributions, regression analysis and random variables. The computing side of the module uses Excel for presentation and analysis of data.
Available to students taking degrees in the departments of Accounting and Finance, Economics, Management Science and Mathematics, and to incoming exchange students with college-level Mathematics.
Information for this module is currently unavailable.
This module covers the skills needed to improve business process by modelling and simulation.
Computer simulation methods are among the most commonly used approaches within operational research and management science. This module teaches you the skills required to apply simulation successfully to help improve the running of a business, and it shows how companies can find good solutions by predicting the effects of changes before implementing them.
Modern simulation packages are a valuable aid in building a simulation model, and this module uses the Witness simulation package, which is widely used commercially. However, without the proper approach, the results of a simulation project can be incorrect or misleading. This module looks at each task required in a simulation project. It emphasises the practical application of simulation, with a good understanding of how a simulation model works being an essential part of this.
This module is designed to extend the knowledge of macroeconomics principles you acquired in Year 1.
classical and Keynesian views
the role of money
real balance and wealth effects
government budgetary constraints
monetary policy in the UK
models of exchange rate determination
Although the main focus of the module is on macroeconomic theory, this is taught within the context of current events in the international macroeconomic environment. You are encouraged to use your knowledge of macroeconomic theory to gain a better understanding of current macroeconomic events and issues.
This module explores the decision-making of economic agents (consumers and firms), and also examines how different market mechanisms operate to allocate resources. The topics it covers include utility maximisation, profit maximisation, cost minimisation, and introduction to market structures.
The module requires algebra, elementary calculus, logical thinking and problem solving ability, and is normally taken in conjunction with Intermediate Microeconomics II (ECON221).
Students will be provided with the foundational results and language of linear algebra, which they will be able to build upon in the second half of Year Two, and the more specialised Year Three modules. This module will give students the opportunity to study vector spaces, together with their structure-preserving maps and their relationship to matrices.
They will consider the effect of changing bases on the matrix representing one of these maps, and will examine how to choose bases so that this matrix is as simple as possible. Part of their study will also involve looking at the concepts of length and angle with regard to vector spaces.
This module describes a variety of optimisation algorithms and how business problems can be modelled using these techniques.
Optimisation is one of the primary techniques associated with management science/operational research. Linear programming models are used routinely in many industries, including petroleum refining and the food industry. Integer linear programming models are increasingly being used in practice for complex scheduling problems such as those that arise in the airline industry where such models have saved large amounts of money. Skills in formulating and solving applied optimisation problems are valuable for anybody interested in a career in operational research or business modelling and consultancy.
This module is designed to enable you to apply optimisation techniques to business problems.
Four main topics are covered:
Specially-structured linear programs
Integer and mixed-integer programming
Heuristics for large-scale problems
Probability provides the theoretical basis for statistics and is of interest in its own right.
Basic concepts from the first year probability module will be revisited and extended to these to encompass continuous random variables, with students investigating several important continuous probability distributions. Commonly used distributions are introduced and key properties proved, and examples from a variety of applications will be used to illustrate theoretical ideas.
Students will then focus on transformations of random variables and groups of two or more random variables, leading to two theoretical results about the behaviour of averages of large numbers of random variables which have important practical consequences in statistics.
Statistics is the science of understanding patterns of population behaviour from data. In the module, this topic will be approached by specifying a statistical model for the data. Statistical models usually include a number of unknown parameters, which need to be estimated.
The focus will be on likelihood-based parameter estimation to demonstrate how statistical models can be used to draw conclusions from observations and experimental data, and linear regression techniques within the statistical modelling framework will also be considered.
Students will come to recognise the role, and limitations, of the linear model for understanding, exploring and making inferences concerning the relationships between variables and making predictions.
This module helps you to explore the connections between economic theory and econometric and statistical methods as applied to issues of global significance.
The areas it covers include:
the economics of food security
the economics of crime, including cybercrime and the effects of deterrents and policing on crime
the transatlantic financial crisis: its causes, consequences and the future of macroeconomics poverty and inequality
The overall objective of this module is to introduce you to some of the key communication and technical skills needed in project work and to give you the opportunity to practise those skills in a progressive way.
Via a group simulated consultancy study, it covers some of the key communication and technical skills needed in project work, such as teamwork, interviewing for information, oral presentations and writing a management report.
This module focuses on the role of governments within the economy, looking at the extent to which they can intervene in markets and in other areas such as climate change. It builds your skills in evaluating the effectiveness of economic policies, and provides insights into the difficulties of decision-making in collective-choice environments.
Over the course of this module, you will enhance your knowledge and understanding of how to specify economic problems in the confines of a game-theoretic model and to solve those problems using appropriate mathematical techniques. The module aims to build your capacity for logical and structured problem analysis.
Operations management is the core managerial discipline in all kinds of operation – from private-sector manufacturing through to public-sector services. It is about the human capacity to organise all the operations that underpin the modern world: transportation, the generation of energy, retailing, the production of goods, the provision of medical and educational services, and so on.
The module will introduce students to key concepts and themes of Operations Management such as operations strategy and performance objectives, operations design (e.g. layout, facility location and capacity), inventory planning and control, project management, quality management and supply chain management. These topics will be approached using a combination of qualitative and simple quantitative methods.
By the end of the course students should be able to:
Enterprise resource planning systems (ERPs) and integration solutions are essential to every modern enterprise, and this module gives you hands-on experience of SAP, a widely used enterprise technology. The module develops your understanding of how information technologies can help companies to achieve their strategic objectives, and introduces you to techniques and tools that can be used to evaluate the performance of business processes, diagnosing where problems lie and how processes can be improved.
After introductory sessions which look at the pervasive use of IT by business and at quantitative and qualitative business process analysis, you then work in small teams to compete in running a virtual dairy company, using SAP GUI as your ERP technology.
This module provides an introduction to the use and impact of IT, communication and integrated technology systems on business organisations. It considers the impacts of IT systems upon the business procedures, the services delivered to customers and the working life of those in the organisation.
From a taxonomy of the different forms of IT system we move to examining the strategic planning and delivery of new systems, the risks to the business, the business advantages to be gained by successful implementations and consider current issues facing business organisations. The course provides the business foundation for other more specialised or technical topics in information systems.
Designed as a complete introduction to the theory and practice of managing business projects, this module introduces project management methods in a way which links to the life cycle of a typical project – from the early project identification and definition stages, through project execution and control, to issues of implementation and change.
The coverage of the early stages of the project cycle uses methods emerging from the systems movement and stresses the strategic relevance of project management.
The operational management of the project is covered by introducing techniques for planning, scheduling and controlling projects. Attention is also given to the people management aspects of this process, especially to leadership, team-working, motivation and direction.
Introducing you to the main concepts and techniques in the management of operational risk and the management of quality, this module deals with both the technical and broader social analysis of these disciplines.
Its purpose is to give you an understanding of these concepts within the general subject of operations management. It will treat the concepts analytically, but as grounded in the practical problems faced by both manufacturing and service operations.
Topics in quality management range from statistical process control to total quality management, while those in risk management range from quantitative risk assessment to high reliability organisations. The module will also look at both subjects as social constructions, and examine the implications of taking such a viewpoint.
This module helps you to understand general modelling concepts and their role in management analysis; how analytical techniques can add value to management decisions and the role that data issues (quality, errors) can play in decision-making.
You will learn how Excel models can support research and investigations. You will also learn how to use a wide range of Excel functions to handle and filter data of different types, produce effective charts and data summaries, and understand how Excel models can be applied to a wide range of management decisions.
This module examines the principles and practices of supply chain management, and examines supply chain and logistics management in relatively high-volume industries such as retailing. It also looks critically at supply chain management, as just one manifestation of the more general issue of trans-organisational operations management.
Most of the time will be spent considering inter-organisational relationships from various perspectives, but you will also need to understand how they relate to matters within the organisation. For example, adopting Just-in-Time supply requires Just-in-Time approaches to be adopted within the firm, and vice versa.
Statistical inference is the theory of the extraction of information about the unknown parameters of an underlying probability distribution from observed data. Consequently, statistical inference underpins all practical statistical applications.
This module reinforces the likelihood approach taken in second year Statistics for single parameter statistical models, and extends this to problems where the probability for the data depends on more than one unknown parameter.
Students will also consider the issue of model choice: in situations where there are multiple models under consideration for the same data, how do we make a justified choice of which model is the 'best'?
The approach taken in this module is just one approach to statistical inference: a contrasting approach is covered in the Bayesian Inference module.
Many organisational recruiters have identified particular skills and knowledge they want to see from a prospective employee. Top in the priorities are spreadsheet modelling, problem structuring, statistics, and project management. This highly practical module equips you with an advanced set of spreadsheet modelling skills, including advanced functions and programming using Visual Basic for Applications (VBA) that can be used to produce a wide range of effective decision-support models.
You will learn general concepts about spreadsheet modelling using VBA and a wide range of modelling skills which are highly relevant to management. These include structured programming, program documentation, program verification, user interface design, and general investigative modelling – including applications involving optimisation, forecasting and simulation.
Bayesian statistics provides a mechanism for making decisions in the presence of uncertainty. Using Bayes’ theorem, knowledge or rational beliefs are updated as fresh observations are collected. The purpose of the data collection exercise is expressed through a utility function, which is specific to the client or user. It defines what is to be gained or lost through taking particular actions in the current environment. Actions are continually made or not made depending on the expectation of this utility function at any point in time.
Bayesians admit probability as the sole measure of uncertainty. Thus Bayesian reasoning is based on a firm axiomatic system. In addition, since most people have an intuitive notion about probability, Bayesian analysis is readily communicated.
This module introduces you to various current techniques for forecasting future customer demand, including a range of predictive models that develop your knowledge of the best ways of forecasting in problem situations.
The aim is to ensure that you have the skills needed to develop a validated quantitative set of forecasts using both extrapolative and causal forecasting methods, and that you can apply a simple forecasting method to support demand and revenue management.
You will also learn to identify and exploit opportunities for revenue optimisation in different business contexts. You review the main methodologies used in each of these areas, discuss legal issues associated with different pricing strategies, and survey current practices in different industries. Most of the topics covered are either directly or indirectly related to pricing issues faced by firms operating in environments where they enjoy some degree of market power.
This module introduces the analytical techniques of business data mining used in customer relationship management, including direct marketing for up- and cross-selling, and credit scoring for mortgages and credit cards.
It enhances your modelling skills on synthetic and empirical data by showing you simple statistical methods and introducing novel methods from artificial intelligence and machine learning. Although understanding basic statistics may give you a better appreciation of the working of models in regression and classification tasks, the module focuses on applying algorithms on real datasets using software, and making real predictions.
The module also includes workshops in which you learn how to use the SAS Enterprise Miner software for data mining (a software skill much sought after in the job market) and apply it to real datasets in a real-world scenario.
In this module we look at how to study business operations, analyse the situation and develop appropriate information systems designs. The same techniques can be of value whether you develop them further and become an information systems professional or use them in general management or consultancy. There is an emphasis on practical application and extensive use of class exercises.
The techniques taught in this module are widely employed by analysts in the fields of information systems and general business consultancy, and the ability to analyse information requirements and design efficient and effective information systems to meet those requirements is increasingly recognised and valued by employers as an important management skill.
This module develops your understanding of advanced material in the field of economic growth as well as the problems of economic development. There is particular reference to the application of theoretical material to the development experience and policy-making in developing and emerging economies.
The innovative nature of the Internet, ecommerce, mobile technologies, multimedia and e-business is changing the way organisations compete, co-operate and deliver services across all private and public sectors.
This module looks at maximising the benefits of the Internet and organising a business in the globalised economy. It examines the use of information systems in organisations and electronic transactions with customers and businesses. It looks beyond the extraordinary growth in ecommerce – only one part of the e-business revolution –and the high level of dotcom failures to examine the continuing changes in the digital economy.
This module formally introduces students to the discipline of financial mathematics, providing them with an understanding of some of the maths that is used in the financial and business sectors.
Students will begin to encounter financial terminology and will study both European and American option pricing. The module will cover these in relation to discrete and continuous financial models, which include binomial, finite market and Black-Scholes models.
Students will also explore mathematical topics, some of which may be familiar, specifically in relation to finance. These include:
Throughout the module, students will learn key financial maths skills, such as constructing binomial tree models; determining associated risk-neutral probability; performing calculations with the Black-Scholes formula; and proving various steps in the derivation of the Black-Scholes formula. They will also be able to describe basic concepts of investment strategy analysis, and perform price calculations for stocks with and without dividend payments.
In addition, to these subject specific skills and knowledge, students will gain an appreciation for how mathematics can be used to model the real-world; improve their written and oral communication skills; and develop their critical thinking.
This applied module is designed as an introduction to the economics of health and health care, and helps to develop your awareness of the main policy issues in this field. It provides a comprehensive set of economic tools for critically appraising fundamental issues in the economics of health while offering a broad overview of the UK National Health Service and other health care systems around the world. The emphasis is on the use and interpretation of microeconomic models and the latest empirical evidence.
This module focuses on firm behaviour and competition, using theoretical (especially game theoretic) and empirical models. It also explores the relationship between industry structure and firm conduct, together with aspects of firm behaviour such as advertising, R&D and mergers.
There have been a number of innovative developments in Operations Management that have sought to organise resources in a significantly new manner in order to make a big step change in performance. This module discusses these key innovative developments in detail, including those that have led to extensive modernisation both in the manufacturing and service sectors.
There will be an emphasis on the importance of successful innovation in the current competitive environment, and the key role of Operations Management in sustaining a competitive advantage and bringing about service improvements.
This module develops your understanding of advanced material in the field of international business. There is particular emphasis on analysing the strategic economic and financial behaviour of multinational firms in the global economy. The module also considers the role and effects of government intervention on firms and multinational firms and how they adapt.
This module develops your understanding of concepts and theories of international trade and factor flows, with particular reference to the way in which such material can inform policy-making.
You will gain knowledge and understanding of international trade theory, and learn to apply this theory to the analysis of present-day policy issues in international economics.
Focusing on the microeconomics of labour and personnel, this module covers topics such as the economics of migration, wage determination, job search and labour market discrimination.
There is a particular emphasis on principal agent problems in human resources and the design of incentives within firms.
Economics theory is used to analyse the operation of labour markers and assess the empirical evidence. Areas covered include:
The aim is to introduce students to the study designs and statistical methods commonly used in health investigations, such as measuring disease, causality and confounding.
Students will develop a firm understanding of the key analytical methods and procedures used in studies of disease aetiology, appreciate the effect of censoring in the statistical analyses, and use appropriate statistical techniques for time to event data.
They will look at both observational and experimental designs and consider various health outcomes, studying a number of published articles to gain an understanding of the problems they are investigating as well as the mathematical and statistical concepts underpinning inference.
This module examines the essential characteristics of a money economy, and the topics covered include:
Interest rate determination
Monetary and labour market disequilibria
The national debt and monetary disequilibrium (fiscal monetarism)
Monetary and international payments disequilibria
Rational expectations (RE) solutions and applications to stabilisation policy
Market efficiency and the application of RE to bubbles and to exchange rates
The central bank and inflation bias
Using the classical problem of data classification as a running example, this module covers mathematical representation and visualisation of multivariate data; dimensionality reduction; linear discriminant analysis; and Support Vector Machines. While studying these theoretical aspects, students will also gain experience of applying them using R.
An appreciation for multivariate statistical analysis will be developed during the module, as will an ability to represent and visualise high-dimensional data. Students will also gain the ability to evaluate larger statistical models, apply statistical computer packages to analyse large data sets, and extract and evaluate meaning from data.
Central to this module is the Crossbay Contracting Game, a management game designed by the module convenor and his colleagues at HCS Ltd.
Three (health service) organisations are involved in a contract negotiation, and you will be part of the management team of one of these organisations. The contract concerns funding requirements for core activities over the coming financial year.
The main aim is to reach an agreement that is satisfactory to all three parties – but you must of course ensure that your own organisation is likely to come out of it well. Much of your time will be spent analysing the emerging situation and negotiating with the other parties.
Alongside this 'management' task there is also a modelling task. Teams are provided with a decision support system they can use to analyse the emerging situation and help them decide which strategies are cost-effective for their organisation.
This module is concerned with understanding the role of government in the economy. Among the topics covered are the characteristics of public goods, basic characteristics of a tax system under both classical and political economy approaches, and the effects of globalisation and its effects on modern tax systems. The module also explores how economic models can be used to understand current affairs.
This module looks at how theoretical and empirical methods can be applied to the growing field of sports economics.
It helps you to understand the particular characteristics of labour and product markets in professional sports, and what implications these have for economic analysis. You will also learn more about how theoretical and empirical work in the economics of sport can be used to inform policy issues, including competitive structures in sports leagues, free agency and player mobility, and the financing of professional sport. You will also gain insights into how betting markets function and why people gamble on sports.
The concept of generalised linear models (GLMs), which have a range of applications in the biomedical, natural and social sciences, and can be used to relate a response variable to one or more explanatory variables, will be explored. The response variable may be classified as quantitative (continuous or discrete, i.e. countable) or categorical (two categories, i.e. binary, or more than categories, i.e. ordinal or nominal).
Students will come to understand the effect of censoring in the statistical analyses and will use appropriate statistical techniques for lifetime data. They will also become familiar with the programme R, which they will have the opportunity to use in weekly workshops.
Important examples of stochastic processes, and how these processes can be analysed, will be the focus of this module.
As an introduction to stochastic processes, students will look at the random walk process. Historically this is an important process, and was initially motivated as a model for how the wealth of a gambler varies over time (initial analyses focused on whether there are betting strategies for a gambler that would ensure they won).
The focus will then be on the most important class of stochastic processes, Markov processes (of which the random walk is a simple example). Students will discover how to analyse Markov processes, and how they are used to model queues and populations.
Issues and problems in the complex world of management do not necessarily arise in a well-structured form. People often do not know what they want or what is possible. They may also disagree about what they are trying to achieve and the means for arriving at their goals. Much thinking needs to be done in order to define an appropriate framework within which a useful analysis or project can be carried out.
Various approaches have been developed in recent years to assist in this task, often referred to as problem-structuring methods (PSMs). These very practically oriented methodologies typically involve the management team to help facilitate the structuring of complex situations. They place emphasis on dialogue to think through strategic problems, identify the salient issues, formulate goals and negotiate action plans. This module introduces you to several PSMs and some of the process skills needed to use them.
Modern statistics is characterised by computer-intensive methods for data analysis and development of new theory for their justification. In this module students will become familiar with topics from classical statistics as well as some from emerging areas.
Time series data will be explored through a wide variety of sequences of observations arising in environmental, economic, engineering and scientific contexts. Time series and volatility modelling will also be studied, and the techniques for the analysis of such data will be discussed, with emphasis on financial application.
Another area the module will focus on is some of the techniques developed for the analysis of multivariates, such as principal components analysis and cluster analysis.
Lastly,students will spend time looking at Change-Point Methods, which include traditional as well as some recently developed techniques for the detection of change in trend and variance.
Lancaster University offers a range of programmes, some of which follow a structured study programme, and others which offer the chance for you to devise a more flexible programme. We divide academic study into two sections - Part 1 (Year 1) and Part 2 (Year 2, 3 and sometimes 4). For most programmes Part 1 requires you to study 120 credits spread over at least three modules which, depending upon your programme, will be drawn from one, two or three different academic subjects. A higher degree of specialisation then develops in subsequent years. For more information about our teaching methods at Lancaster visit our Teaching and Learning section.
Information contained on the website with respect to modules is correct at the time of publication, but changes may be necessary, for example as a result of student feedback, Professional Statutory and Regulatory Bodies' (PSRB) requirements, staff changes, and new research.
Lancaster University is dedicated to ensuring you not only gain a highly reputable degree, you also graduate with the relevant life and work based skills. We are unique in that every student is eligible to participate in The Lancaster Award which offers you the opportunity to complete key activities such as work experience, employability awareness, career development, campus community and social development. Visit our Employability section for full details.
Lancaster Management School has an award winning careers team to provide a dedicated careers and placement service offering a range of innovative services for management school students. Our high reputation means we attract a wide range of leading global employers to campus offering you the opportunity to interact with graduate recruiters from day 1 of your degree.
We set our fees on an annual basis and the 2019/20 entry fees have not yet been set.
As a guide, our fees in 2018 were:
Some science and medicine courses have higher fees for students from
the Channel Islands and the Isle of Man. You can find more details here:
For full details of the University's financial support packages including eligibility criteria, please visit our fees and funding page
Students also need to consider further costs which may include books, stationery, printing, photocopying, binding and general subsistence on trips and visits. Following graduation it may be necessary to take out subscriptions to professional bodies and to buy business attire for job interviews.
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