Introducing your course
Find out what it's like to study Economics and Mathematics at Lancaster University Management School.
10th for in Mathematics
The Guardian University Guide (2024)
11th for Research Quality for Economics
The Times and Sunday Times Good University Guide (2024)
14th for Mathematics
The Times and Sunday Times Good University Guide (2024)
BSc Economics and Mathematics (Industry) focuses on the mathematical and statistical methods employed in economics, alongside studies in mathematics theory. Whether your goal is to use economics in finance or policy, this programme is flexible enough to allow you to pursue either.
As a student who is comfortable and fluent in mathematics, BSc Economics and Mathematics (Industry) provides you with the analytic skills and intellectual toolbox to help answer some of the most pressing economics questions.
You will learn how to interpret data, understand (and quantify) the decisions made by individuals, organisations, and governments and evaluate economic policies.
You will cover the fundamentals of economic theory and practice, and as your degree progresses and you discover more about both the subject and yourself, you have the opportunity to flex this programme in ways that speak to your changing interests and strengths. This might lead you to choose modules in:
Amongst many other specialisations. This leads to a degree unique to you, where you have played a major part in building the degree you want.
Alongside your economics studies, you will study the principles, methods and concepts of mathematics. Modules cover a wide range of topics, from calculus, probability and statistics to logic, proofs and theorems.
This programme uses your mathematical skills and knowledge to explore the core principles of macro- and micro-economics and game theory, amongst other areas of the discipline.
Your third year is spent in industry. You’ll be supported in securing a placement, with past students joining companies such as IBM, Lloyds Bank, Microsoft, PwC and the Bank of England. Roles on offer range from project management and logistics to investment, business development and risk. Most placements are in the UK, but there are some options overseas.
What separates Lancaster from the crowd is the flexible nature of our Economics degree programmes. In your final year, you can choose a large number of your modules, focusing on your areas of interest to build a degree unique to you.
You do not need an A level in Economics to enrol in this course.
The University will use all reasonable effort to support you to find a suitable placement for your studies. While a placement role may not be available in a field or organisation that is directly related to your academic studies or career aspirations, all placement roles offer valuable experience of working at a graduate level and gaining a range of professional skills.
If you are unsuccessful in securing a suitable placement for your third year, you will be able to transfer to the equivalent non-placement degree scheme and would continue with your studies at Lancaster, finishing your degree after your third year. The University offers a range of shorter placement and internship opportunities for which you would be welcome to apply.
BSc Economics and Mathematics (Industry) offers a grounding in the fundamentals of economics alongside your mathematical knowledge. The most powerful aspect of economics is that it teaches a way of thinking which can then be applied to a specific field. If you want to be a government economist advising on tax or social/welfare costs, you need specific knowledge and skills. The same is true for a career in finance. You need specific finance models – how much to invest here, or advise clients to invest there. But the mode of thinking is the same for both: it is the critical, disciplined way of thinking that you will get from an Economics degree at Lancaster University. Economics opens up the world because the critical and analytical thinking skills that it inculcates are applicable to whatever your passion, be they politics, finance, the trading floor, or working for an NGO, all use the same skills.
As a graduate of Lancaster you’ll enjoy excellent employment prospects. Your qualification in Economics and Mathematics, along with your problem-solving skills, analytical abilities and organisational expertise, will make you highly desirable to employers.
Former graduates have been taken on as professional economists and economic advisers by the Bank of England, the Civil Service, management consultancies and diverse companies in a wide range of areas.
Your skills are also easily transferable to various roles such as marketing, management, advertising and consultancy.
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 University 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 one of your degree.
A level AAB
Required subjects A level Mathematics or Further Mathematics grade A
GCSE 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 web pages.
International Baccalaureate 35 points overall with 16 points from the best 3 Higher Level subjects, including 6 in HL Mathematics (either analysis and approaches or applications and interpretations)
BTEC May be considered alongside A level Mathematics or Further Mathematics at grade A
We welcome applications from students with a range of alternative UK and international qualifications, including combinations of qualifications. 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 web pages.
Contact Admissions Team + 44 (0) 1524 592028 or via ugadmissions@lancaster.ac.uk
Lancaster University offers a range of programmes, some of which follow a structured study programme, and some which offer the chance for you to devise a more flexible programme to complement your main specialism.
Information contained on the website with respect to modules is correct at the time of publication, and the University will make every reasonable effort to offer modules as advertised. In some cases changes may be necessary and may result in some combinations being unavailable, for example as a result of student feedback, timetabling, Professional Statutory and Regulatory Bodies' (PSRB) requirements, staff changes and new research. Not all optional modules are available every year.
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.
Each year, students receive specific training by the Management School Careers Team, to prepare them for the graduate labour market. In the first year, the focus is on growing the student’s awareness of labour market dynamics and his or her professional aspirations and inclinations. The second year focuses on goal setting, action planning, and the development of a personalised career plan. The third year focuses on one-to-one sessions with career advisors. The Career Team is based in the Management School, organises events with employers and alumni, and coaches students on how to best perform in the graduate job market through seminars, surgeries, mock interviews and one-to-one advice.
This full-year module provides the foundation for your future study in Economics. It is divided into three parts. The first part provides a thorough introduction to Microeconomics (including the theory of demand, costs and pricing under various forms of market structure, and welfare economics). The second part provides a thorough introduction to Macroeconomics (including national income analysis, monetary theory, business cycles, inflation, unemployment, and the great macroeconomic debates).
The third part of the module, taught in parallel with the first two parts, shows how the key Micro- and Macroeconomics ideas can help us understand the world around us. In this part, we will use economic experiments to answer various questions, such as whether economists are selfish. We will analyse whether a sugar tax is a good idea, automation and the minimum wage, the structure, conduct and performance of big technology firms, and use the skills we have learned to analyse inequality, Brexit, and Covid-19. We will also discuss the distinction between transitory inflation and stagflation, central banks’ changing objectives, cryptocurrencies and the financial markets, fiscal and monetary policy responses to the pandemic, the Great Depression and the Great Recession, quantitative easing, currency crises, and the Euro debt crisis. Economics A is taught in conjunction with modules (ECON103 or MATH100, depending on the degree) which provide the quantitative foundations for further study in Economics.
This course extends ideas of MATH101 from functions of a single real variable to functions of two real variables. The notions of differentiation and integration are extended from functions defined on a line to functions defined on the plane. Partial derivatives help us to understand surfaces, while repeated integrals enable us to calculate volumes.
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 and temperature, and the direction of the wind. To study functions of several variables, we introduce rates of change with respect to several quantities. We learn how to find maxima and minima. Applications include the method of least squares. Finally, we investigate various methods for solving differential equations of one variable.
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.
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.
Each year, students receive specific training by the Management School Careers Team, to prepare them for the graduate labour market. In the first year the focus is on growing the student’s awareness of labour market dynamics and his or her professional aspirations and inclinations. The second year focuses on goal setting, action planning, and developing a personalised career plan. The third year focuses on one-to-one sessions with career advisors. The Career Team is based in the Management School, organises events with employers and alumni, and coaches students on how to best perform in the graduate job market through seminars, surgeries, mock interviews and one-to-one advice.
Students will gain a solid understanding of computation and computer programming within the context of maths and statistics. This module expands on five key areas:
Under these headings, students will study a range of complex mathematical concepts, such as: data structures, fixed-point iteration, higher dimensions, first and second derivatives, non-parametric bootstraps, and modified Euler methods.
Throughout the module, students will gain an understanding of general programming and algorithms. They will develop a good level of IT skills and familiarity with computer tools that support mathematical computation.
Over the course of this module, students will have the opportunity to put their knowledge and skills into practice. Workshops, based in dedicated computing labs, allow them to gain relatable, practical experience of computational mathematics.
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.
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.
The course provides students with general knowledge and understanding concerning social research and particular methods and methodologies that lie within the positivist and interpretivist paradigms. It is primarily aimed at students from across the management school that are planning to undertake an industrial placement and/or a dissertation in their final year of study. This module helps to prepare you to undertake your own research with a view to highlighting different research approaches and techniques that are used in the production of knowledge.
The module provides an insight into the various ways research can be undertaken and the implications of different approaches. We will examine the conceptual and practical complexities of undertaking research in practice. Initially you will be introduced to research methods and that are most commonly employed in business and management research. The module will then examine the methodological approaches and paradigms that are linked with these methods and the assumptions that underpin positivistic and interpretivist approaches. The final part of the module explores how this understanding can be used in writing your research proposal and dissertation.
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 uses the tools of economics to study various macroeconomic variables (inflation, consumption, output, unemployment) and particularly their short-run and long-run dynamics. It covers topics related to fiscal policy and the sustainability of public debt in the intermediate run. In addition, students will study unemployment and labour market dynamics and more in general economic stability in the short run.
The module requires algebra, elementary calculus, logical thinking and general problem-solving ability.
This module first explores some of the key insights of New Keynesian economics, particularly that the monetary policy effectively influences output in the short-run but not in the long run. We will examine the crucial role of how the public formulates expectations for the economy’s stability, e.g. expectations about inflation and the importance of credible monetary policy. The second part of the module will cover topics explaining the “mysteries” of long-run economic growth. For example, how did we arrive at the vast degree of disparity between countries we observe today? This module covers topics like exogenous and endogenous growth, optimal growth, and dualism.
Note that this module is available only to students majoring in Economics.
Markets consist of individual buyers and sellers, each facing choices. A buyer must decide what, and how much, to purchase. A seller must decide how much to produce, how to produce it, and what price to charge. But how are these choices made? In this course, we will explore this question formally, with the aid of economic models. The topics include consumer choice, profit maximization and cost minimization. The module requires a basic knowledge of algebra and calculus.
By the end of the course, you will improve your logical thinking and problem-solving abilities.
This module builds on learning gained in Intermediate Microeconomics 1 (ECON220), developing on the theories and concepts covered as well as focusing on a range of new topics.
Topics include:
analysis of monopoly behaviour and regulation
price and quantity setting in duopoly markets
introduction to game theory and strategic behaviour by firms
auctions (including a study of eBay)
general equilibrium and welfare economics
The module is normally taken in conjunction with ECON220.
The objective of the course is to train students to use macroeconomic models to understand real-world economic phenomena. The students will learn how to interpret macroeconomic data and understand the implications of economic policies. The course will put emphasis on major issues related to economic growth, the causes of economic fluctuations, and the effectiveness of economic policy. We will investigate the link between financial openness and economic growth, and we will explain why emerging countries experience capital outflows. We will study the impact of the exchange rate regime on the effectiveness of fiscal policy, we will rationalise the increase of current account deficits in Europe after the beginning of the nineties, and we will analyse the cause(s) of cross-country differences in hours worked.
The module requires basic knowledge of basic calculus, logical thinking and problem-solving skills.
This module provides the tools necessary to produce the rigorous economic analyses that form the core of both microeconomics and macroeconomics.
During the first part of the course, the attention is on the dynamic analysis of systems, which is key to understanding how economic variables change over time, especially in response to shifts in government economic policy.
The second part of the course studies constrained optimization which is central to understanding how households and firms make their consumption and production decisions when faced with limited budgets. Throughout the whole course, we focus our analysis on concrete examples and intuition, with an emphasis on how to frame economic problems using the mathematical tools you will acquire in the course.
We will require you to apply the concepts learned in class, and to translate informal problems into formal language.
Various topics of interest to prospective managers are covered within this module, including production and demand, competition and strategic behaviour, advertising and distribution, capital budgeting and inventories, the foreign exchange market, the economics of the multinational enterprise and the politics of corporate economics. The module provides knowledge of aspects of microeconomics relevant to general management, and also emphasises techniques and tools of analysis alongside relevant theory.
The module is designed to as an introduction to aspects of the firm and its environment which are of particular relevance to management. The topics selected aim to bridge the gap between the traditional approach to managerial economics and the more modern study of the organisation.
In your first year you'll apply for placements in business or industry, and will take a module to prepare you for the placement year. The whole of your third year will then be spent working in a paid placement, supported by the Careers team. Near the end of the placement, you'll submit a proposal for your dissertation topic, inspired by your experiences during the placement year, which you'll complete in fourth year under the supervision of an academic tutor.
This module equips students with experience of working within a business environment. You are expected to acquire not only knowledge of business problems and practices, but also experience of interpersonal relationships within a business context. The dissertation is undertaken during the work placement year.
Each year, students receive specific training by the Management School Careers Team, to prepare them for the graduate labour market. In the first year the focus is on growing the student’s awareness of labour market dynamics and his or her professional aspirations and inclinations. The second year focuses on goal setting, action planning, and developing a personalised career plan. The third year focuses on one-to-one sessions with career advisors. The Career Team is based in the Management School, organises events with employers and alumni, and coaches students on how to best perform in the graduate job market through seminars, surgeries, mock interviews and one-to-one advice.
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 course is just one approach to statistical inference: a contrasting approach is covered in the Bayesian Inference module.
The course introduces state-of-the-art methods used in current macroeconomics research to understand short-run business cycle and inflation dynamics, as well as economic stabilisation policies.
We will develop a broad and deep knowledge of modern Dynamic Stochastic General Equilibrium (DSGE) macroeconomic models that employ microeconomic foundations and rational expectations. These models will be solved using advanced analytical and numerical-computational approaches. More specifically, we will use the DSGE neoclassical Real Business Cycle and New Keynesian frameworks to understand the different sources of aggregate economic fluctuations, and to examine the positive and normative roles of fiscal and monetary policies.
Finally, the course examines contemporary issues such as inflationary shocks, government debt financing through distortionary taxation, optimal (un)conventional monetary and fiscal policies in a zero interest rate-liquidity trap environment, and financial frictions.
This module explores how the theoretical and mathematical tools of advanced microeconomic theory can be used to understand and model individual and strategic decision making. Topics it covers include advanced concepts of decision making of the main economic agents (consumers and firms), as well as specialised topics on game theory. The module requires algebra and calculus, along with logical thinking and problem-solving ability.
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.
Behavioural Economics is the interface between economics and psychology. It is one of the fastest-growing fields in economics, and since the past decade, it is regarded as a standard tool for policymaking. The course will survey the empirical tools used by behavioural economists and in particular lab and field experiments. We will explore behavioural biases affecting economic and financial decision making, and the role of trust and cooperation in teamwork. We will discuss models and experimental results explaining how we make decisions in various contexts such as choice under uncertainty, intertemporal choice or decision making in a social framework.
This course focuses on the economics of growth and development, both from a theoretical and empirical perspective. Using examples from developing countries, it explores wide-ranging, policy-relevant topics such as investments in health, education and infrastructure, microeconomics of credit markets, corruption and other determinants of economic development.
This module introduces up-to-date quantitative econometric methods used in applied research/empirical work. We will discuss various economic applications, including “returns to schooling” and “the effect of minimum wages on employment”. The module will also provide students with the data analytical skills necessary to conduct applied research in economics/policy analysis using popular statistical software, STATA. Key topics include linear regression, instrumental variables, causal inferences, binary choice models, panel data, time series modelling, and forecasting.
This module helps you improve your strategic thinking. Over the course of this module, you will learn how to use ‘games’ to model strategic situations in the real world, and how to analyse and find out solutions to these games in situations in which players are intelligent and rational. Games including “normal form games”, “extensive form games”, “Bayesian games”, “repetitive games”, and “games with correlation device” will be introduced. Opportunities for playing games with the lecturer and other students will also be provided. The module requires a basic knowledge of algebra, calculus, and economics.
This applied module is an introduction to the economics of health and health care and will 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’s 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 builds on basic microeconomics concepts to explore competition between firms and the evolution of market structure. It focuses on understanding the way firms make decisions and the effects of those decisions on market outcomes like prices, quantities, the type of products offered, and social welfare. The module first introduces basic concepts in Industrial Organisation to study imperfect competition and the determinants of market power. It then proceeds to analyse important topics in competition policy, such as cartels and merger policy.
The module requires an understanding of intermediate microeconomics (especially production/cost theory), basic concepts of game theory, and basic calculus.
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 policymaking. Topics covered include the Ricardian model, the Heckscher-Ohlin model, international trade under imperfect competition, outsourcing and offshoring, trade models based on heterogeneous firms and multinational firms, and trade policy under perfect and imperfect competition. Throughout the module we emphasise the applicability of the models learned, and their relevance to real-world events. Examples include the relationship between labour productivity and wages, opinions toward free trade, and the impact of immigration.
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:
This course aims at training ambitious economists to formal mathematical methods used in economic modelling and beyond. These techniques are necessary for students interested in pursuing postgraduate studies in Economics or working in analytically demanding jobs in the private sector. The course will cover material that usually is outside the scope of the regular mathematics education for economists, like decisions over time.
By the end of this course, students should have a good knowledge and understanding of these relevant mathematical techniques.
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.
Policymakers at Central Banks lie in a unique position to influence economic activity. This module examines the role of monetary policy in influencing the expectations and behaviour of agents in the economy and the implications this has for outcomes such as inflation, GDP and household welfare. Students will focus on applications of monetary theory to central banks problems and the recent objectives of the Bank of England Monetary Policy Committee. Topics include Central Bank independence, inflation targeting and the zero lower bound on interest rates, money creation and quantitative easing, and the macroeconomics of pandemics.
This module presents an overview of the interactions between the government, firms, and citizens, using a mix of theory and empirical work. Sometimes, markets are not efficient, and government intervention is necessary. Sometimes, markets are efficient, but equity concerns create the need for government. There is often a tension between the socially optimal policy and the outcome of the democratic process.
Some questions we study in this module:
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.
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.
Our annual tuition fee is set for a 12-month session, starting in the October of your year of study.
Our Undergraduate Tuition Fees for 2024/25 are:
Home | International |
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£9,250 | £26,575 |
There may be extra costs related to your course for items such as books, stationery, printing, photocopying, binding and general subsistence on trips and visits. Following graduation, you may need to pay a subscription to a professional body for some chosen careers.
Specific additional costs for studying at Lancaster are listed below.
Lancaster is proud to be one of only a handful of UK universities to have a collegiate system. Every student belongs to a college, and all students pay a small college membership fee which supports the running of college events and activities. Students on some distance-learning courses are not liable to pay a college fee.
For students starting in 2023 and 2024, the fee is £40 for undergraduates and research students and £15 for students on one-year courses. Fees for students starting in 2025 have not yet been set.
To support your studies, you will also require access to a computer, along with reliable internet access. You will be able to access a range of software and services from a Windows, Mac, Chromebook or Linux device. For certain degree programmes, you may need a specific device, or we may provide you with a laptop and appropriate software - details of which will be available on relevant programme pages. A dedicated IT support helpdesk is available in the event of any problems.
The University provides limited financial support to assist students who do not have the required IT equipment or broadband support in place.
In addition to travel and accommodation costs, while you are studying abroad, you will need to have a passport and, depending on the country, there may be other costs such as travel documents (e.g. VISA or work permit) and any tests and vaccines that are required at the time of travel. Some countries may require proof of funds.
In addition to possible commuting costs during your placement, you may need to buy clothing that is suitable for your workplace and you may have accommodation costs. Depending on the employer and your job, you may have other costs such as copies of personal documents required by your employer for example.
The fee that you pay will depend on whether you are considered to be a home or international student. Read more about how we assign your fee status.
Fees are set by the UK Government annually, and subsequent years' fees may be subject to increases. Read more about fees in subsequent years.
You will be automatically considered for our main scholarships and bursaries when you apply, so there's nothing extra that you need to do.
You may be eligible for the following funding opportunities, depending on your fee status:
Unfortunately no scholarships and bursaries match your selection, but there are more listed on scholarships and bursaries page.
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We also have other, more specialised scholarships and bursaries - such as those for students from specific countries.
Browse Lancaster University's scholarships and bursaries.
The information on this site relates primarily to 2024/2025 entry to the University and every effort has been taken to ensure the information is correct at the time of publication.
The University will use all reasonable effort to deliver the courses as described, but the University reserves the right to make changes to advertised courses. In exceptional circumstances that are beyond the University’s reasonable control (Force Majeure Events), we may need to amend the programmes and provision advertised. In this event, the University will take reasonable steps to minimise the disruption to your studies. If a course is withdrawn or if there are any fundamental changes to your course, we will give you reasonable notice and you will be entitled to request that you are considered for an alternative course or withdraw your application. You are advised to revisit our website for up-to-date course information before you submit your application.
More information on limits to the University’s liability can be found in our legal information.
We believe in the importance of a strong and productive partnership between our students and staff. In order to ensure your time at Lancaster is a positive experience we have worked with the Students’ Union to articulate this relationship and the standards to which the University and its students aspire. View our Charter and other policies.
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