BSc Business Statistics


Actuarial Sciences incorporates multi-disciplinary teaching, combining the expertise of the School of Computing Sciences, School of Mathematics, School of Economics and Norwich Business School to give our students a unique opportunity to pursue a stimulating and influential career as an actuary.

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Key facts

Key facts

Business Statistics at UEA allows you to turn your interest in maths, computing and business into a successful career. We focus on preparing and supporting you for a secure, in demand and well-paid career path.

You will be taught by expert academics from the Schools of Computing Sciences, Mathematics, Economics and the Norwich Business School. The vast majority of learning takes place in small groups, providing you with quality contact time with lecturers while learning through first-hand experience.


BSc Business Statistics is a three-year programme aimed at mathematically able students who are interested in pursuing a fulfilling career in business, through the application of statistical techniques.

The course provides you with a thorough knowledge of applied statistics, computing, databases, and a comprehensive understanding of business and its practices. You will benefit from the multidisciplinary nature of the programme, which combines teaching from the School of Computing Sciences, School of Mathematics, School of Economics and the Norwich Business School. Take advantage of our links with insurance giant Aviva, who are based right here in Norwich. That includes opportunities for tuition, work experience and eventually employment.

As well as developing your mathematical, financial and statistical knowledge, you will also complete a significant project in applied statistics, strengthening your understanding of mathematics and business. Successful students also have the opportunity to gain eligibility for up to 4 exemptions from examinations set by the Institute and Faculty of Actuaries.

The first year of the Business Statistics degree programme contains the same modules as the BSc Actuarial Science course. One of the benefits of this is that top students may transfer to the Actuarial Science degree programme after the first year, subject to space.

Course Structure

This three year course will begin by developing your knowledge in areas including mathematics, computing, economics and business. This will continue in your second year, alongside the opportunity to also begin gaining specialist knowledge through optional modules. Specialisation continues within the third year, as you continue to strengthen your mathematical knowledge through the completion of a significant project in applied statistics.

Year 1

The first year programme is made up of compulsory modules, which concentrate on developing your mathematical, computing, business and problem-solving skills. You will be taught across a variety of departments, improving your understanding of business and statistics.

Year 2

Compulsory modules continue to build up your knowledge of statistics, computing, maths and actuarial practices.

Year 3

In your final year you will take both compulsory and optional modules that focus on expanding your advanced knowledge of statistics and mathematics, whilst also allowing for specialisation in maths, business, advanced statistics, and computing. You will also complete a significant statistical project, allowing you to develop your abilities in both applied and theoretical statistics.

Course Modules 2017/8

Students must study the following modules for 120 credits:

Name Code Credits


(a) Complex numbers. (b) Vectors. (c) Differentiation. Taylor and Maclaurin series. (d) Integration: Applications: curve sketching, areas, arc length. (e) First-order, second-order, constant coefficient ordinary differential equations. Reductions of order. Numerical solutions using MAPLE. Partial derivatives, chain rule. (f) Line integrals. Multiple integrals including change of co-ordinates by Jacobians. Green's theorem in the plane. (Students must have A-level Mathematics Grade 'B' or above or equivalent.)




This module provides students with an introduction to core economic theory and principles in a business context. It combines basic microeconomic and macroeconomic theory with cases/applications in a teaching programme designed to provide students with the ability to understand and analyse current and topical economic issues with relevance for business.




This module provides a foundation in the theory and practice of accounting and an introduction to the role, context and language of financial reporting and management accounting. The module assumes no previous study of accounting. It may be taken as a standalone course for those students following a more general management pathway or to provide a foundation to underpin subsequent specialist studies in accounting. This module is for NON-NBS students only.




This module will consist primarily of material leading to exemption from the CT1 Institute and Faculty of Actuaries professional exam (the exemption is jointly awarded based on this module and the Financial Mathematics module in year 2). It will also include an introduction to excel skills for Actuaries as well as some discrete maths material in preparation for later modules.




Probability as a measurement of uncertainty, statistical experiments and Bayes' theorem. Discrete and continuous distributions. Expectation. Applications of probability: Markov chains, reliability theory.




The purpose of this module is to give the student a solid grounding in the essential features of programming using Java programming language. The module is designed to meet the needs of the student who has not previously studied programming.



Students must study the following modules for 120 credits:

Name Code Credits


This is a module designed to give students the opportunity to apply statistical methods in realistic situations. While no advanced knowledge of probability and statistics is required, we expect students to have some background in probability and statistics before taking this module. The aim is to teach the R statistical language and to cover 3 topics: Linear regression, ANOVA, and Survival Analysis.




This module sets out the basic principles of financial management and applies them to the main decisions faced by the financial manager. For example, it explains why the firm's owners would like the manager to increase firm value and shows how managers choose between investments that may pay off at different points of time or have different degrees of risk. Moreover, it discusses how companies raise the necessary funds to pay for these investments and why they might prefer a particular source of finance. Overall, this module presents the tools of modern financial management in a consistent conceptual framework.




(a) Ordinary Differential Equations: solution by reduction of order; variation of parameters for inhomogeneous problems; series solution and the method of Frobenius. Legendre's and Bessel's equations: Legendre polynomials, Bessel functions and their recurrence relations; Fourier series; Partial differential equations (PDEs): heat equation, wave equation, Laplace's equation; solution by separation of variables. (b) Method of characteristics for hyperbolic equations; the characteristic equations; Fourier transform and its use in solving linear PDEs; (c) Dynamical Systems: equilibrium points and their stability; the phase plane; theory and applications.




This module is about the theory and practice of financial accounting and reporting. This includes an examination of current and legal professional requirements as they relate to limited liability companies in the UK. Large UK companies report using International Financial Reporting Standards and therefore international reporting issues are considered.




This module builds on fundamentals of compound interest introduced in Mathematics for Actuaries to show how the key concepts introduced can be used in practical financial applications for Actuarial Science or Business Statistics students.




It introduces the essential concepts of mathematical statistics deriving the necessary distribution theory as required. In consequence in addition to ideas of sampling and central limit theorem, it will cover estimation methods and hypothesis-testing. Some Bayesian ideas will be also introduced.



Students must study the following modules for 60 credits:

Name Code Credits


This module covers two topics in statistical theory: Linear and Generalised Linear models and also includes Stochastic processes. The first two topics consider both the theory and practice of statistical model fitting and students will be expected to analyse real data using R. Stochastic processes including the random walk, Markov chains, Poisson processes, and birth and death processes.




This module will give you experience of independent project work and, via the lecture programme, will provide a primer on the law, ethical and professional behaviour, project management, reporting and other aspects of being a statistician. You will be allocated a supervisor and will be expected to work closely with him or her on a mutually agreed project.



Students will select 60 credits from the following modules:

Name Code Credits


This module is about building on the work done in NBS-5002Y Financial Accounting. It will deepen your understanding of the theory and practice of financial reporting. You look at some technical areas such as group accounts in more depth. The module will develop your technical skills. It is also an opportunity to question the practices of financial reporting; why are some things included and others excluded from the financial statements, in what other ways could transactions be reported, how do we measure transactions and why that way?




This module aims to build a bridge between the theory, application and practice of finance. The module will enable students to analyse simulated and actual financial data and build realistic models to solve problems and support financial decisions. In line with practice, most of the models will be built using Microsoft Excel spreadsheets and data from free online sources or specialized financial databases. Key applications include: time value of money, investment appraisal, firm valuation, equity and bond pricing, descriptive statistics, regression, forecasting, etc. The module will allow students to gain exposure to the application of statistical methods in real contexts through in-class case studies and practice in a PC lab environment. Finally, the students will have the opportunity to experience the excitement of trading financial assets by using state of the art computer-based trading simulation software.




This module provides students with an introduction to core trade theory and principles in a business context. It combines basic microeconomic and macroeconomic principles with cases/applications in a teaching programme designed to help students understand current business and international business issues. What drives cross-border trade flows? Why is free trade better than autarchy and what is the cost of not having it? How does cross-border trade affect economic growth? And what are the most common challenges that firms have to face when operating across borders? The module will provide students with a set of technical tools and way of thinking to answer such questions, among others.




This module deals with the basic and advanced theories, models and techniques that have been developed and used in the financial industry and research for investment management. You will learn how wealth can be allocated optimally across various types of assets in order to meet different investor objectives. Emphasis will be placed on mainstream approaches which assume market efficiency. However, we shall also discuss arguments and evidence related to criticism of these approaches and the usefulness of alternatives, such as Behavioural finance. The module will cover both passive and active investment strategies (e.g. algorithmic trading, technical analysis, fundamental analysis) at a national and global level. Assets analysed will include basic traded stock and debt securities along with more complex derivative assets (e.g. futures, options, swaps) in the context of different investment portfolios ,e.g. hedge funds, ETFs, index trackers, REITs, etc.). The module will also discuss issues related to performance evaluation, risk management and taxes. The material taught will be aligned closely to the curriculum of the Chartered Financial Analyst (CFA) Program and the Chartered Institute for Securities and Investment (CISI).




This module covers the core topics that dominate machine learning research: classification, clustering and reinforcement learning. We describe a variety of classification algorithms (e.g. Neural Networks, Decision Trees and Learning Classifier Systems) and clustering algorithms (e.g. k-NN and PAM) and discuss the practical implications of their application to real world problems. We then introduce reinforcement learning and the Q-learning problem and describe its application to control problems such as maze solving.




This module considers quantitative methods used in business for analysing and solving problems. The emphasis is on practical applications and uses involving Excel and SPSS.




Whilst the University will make every effort to offer the modules listed, changes may sometimes be made arising from the annual monitoring, review and update of modules and regular (five-yearly) review of course programmes. Where this activity leads to significant (but not minor) changes to programmes and their constituent modules, there will normally be prior consultation of students and others. It is also possible that the University may not be able to offer a module for reasons outside of its control, such as the illness of a member of staff or sabbatical leave. Where this is the case, the University will endeavour to inform students.

Entry Requirements

  • A Level ABB including Mathematics or Statistics at grade A
  • International Baccalaureate 32 points including HL Mathematics at 6 and one other HL subject at 5
  • Scottish Advanced Highers ABB (including Maths)
  • Irish Leaving Certificate AABBBB or 2 subjects at H1 and 4 subjects at H2 including Mathematics
  • Access Course Pass the Access to HE Diploma with Distinction in 30 credits at Level 3 and Merit in 15 credits at Level 3, including 12 Level 3 credits in Mathematics
  • BTEC Only accepted alongside A level Mathematics
  • European Baccalaureate 75% overall (including Maths)

Entry Requirement

You are required to have Mathematics and English Language at a minimum of Grade B or Grade 5 or above at GCSE.

General Studies and Critical Thinking are not accepted.

UEA recognises that some students take a mixture of International Baccalaureate IB or International Baccalaureate Career-related Programme IBCP study rather than the full diploma, taking Higher levels in addition to A levels and/or BTEC qualifications. At UEA we do consider a combination of qualifications for entry, provided a minimum of three qualifications are taken at a higher Level. In addition some degree programmes require specific subjects at a higher level.

Students for whom English is a Foreign language

We welcome applications from students from all academic backgrounds. We require evidence of proficiency in English (including writing, speaking, listening and reading):

  • IELTS: 6.5 overall (minimum 6.0 in any component)

We also accept a number of other English language tests. Please click here to see our full list.

INTO University of East Anglia 

If you do not meet the academic and or English requirements for direct entry our partner, INTO University of East Anglia offers guaranteed progression on to this undergraduate degree upon successful completion of a preparation programme. Depending on your interests, and your qualifications you can take a variety of routes to this degree:

International Foundation in General Science FS1

International Foundation in Physical Sciences and Mathematics FS3

International Foundation in Mathematics with Actuarial Science FMA 


The majority of candidates will not be called for an interview and a decision will be made via UCAS Track. However, for some students an interview will be requested. You may be called for an interview to help the School of Study, and you, understand if the course is the right choice for you.  The interview will cover topics such as your current studies, reasons for choosing the course and your personal interests and extra-curricular activities.  Where an interview is required the Admissions Service will contact you directly to arrange a convenient time.

Gap Year

We welcome applications from students who have already taken or intend to take a gap year, believing that a year between school and university can be of substantial benefit. You are advised to indicate your reason for wishing to defer entry and may wish to contact the appropriate Admissions Office directly to discuss this further.

Alternative Qualifications

We encourage you to apply if you have alternative qualifications equivalent to our stated entry requirement. Please contact us for further information.

Fees and Funding

Undergraduate University Fees and Financial Support

Tuition Fees

Information on tuition fees can be found here:

UK students

EU Students

Overseas Students

Scholarships and Bursaries

We are committed to ensuring that costs do not act as a barrier to those aspiring to come to a world leading university and have developed a funding package to reward those with excellent qualifications and assist those from lower income backgrounds. 

The University of East Anglia offers a range of Scholarships; please click the link for eligibility, details of how to apply and closing dates.

How to Apply

Applications need to be made via the Universities Colleges and Admissions Services (UCAS), using the UCAS Apply option.

UCAS Apply is a secure online application system that allows you to apply for full-time Undergraduate courses at universities and colleges in the United Kingdom. It is made up of different sections that you need to complete. Your application does not have to be completed all at once. The system allows you to leave a section partially completed so you can return to it later and add to or edit any information you have entered. Once your application is complete, it must be sent to UCAS so that they can process it and send it to your chosen universities and colleges.

The UCAS code name and number for the University of East Anglia is EANGL E14.

Further Information

If you would like to discuss your individual circumstances with the Admissions Office prior to applying please do contact us:

Undergraduate Admissions Office

Tel: +44 (0)1603 591515

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