MORSE (BSc) - Course full
Our MORSE degree balances mathematical theory and its practical applications, with subject specialists from the departments of Mathematics, Statistics, Economics and Warwick Business School teaching core modules.
You will learn through a combination of lectures, small-group tutorials and practical sessions based in the Statistics Department’s well-equipped undergraduate computing laboratory. You can also take modules from outside the Statistics Department, for example from Physics, Philosophy or the Language Centre. We also work with the Institute and Faculty of Actuaries to design modules that can lead to exemptions for some Actuarial Exams.
The first two years of the BSc and MMORSE courses are similar, making it easy to reconsider your preference in the second year. Differences become apparent in the final years. From the third year onwards, our four-year MMORSE gives you the opportunity to specialise in one of the following four areas: Actuarial and Financial Mathematics; Operational Research and Statistics; Econometrics and Mathematical Economics; Statistics with Mathematics, and to complete a supervised research project.
The first two years of the MORSE degrees follow a (mainly) fixed set of courses, laying the foundations of the four main subjects. For part of the first two years, and the whole of the third, students are free to choose from a wide range of topics. Final year students can elect to specialise in one or two of the main subject areas or can continue a balanced programme by selecting topics from all four departments.
Year 1 - The compulsory modules in year 1 concentrate on the underlying mathematical ideas. You also study basic material from economics and OR.
Year 2 - In year 2 the statistics, economics and OR are developed further, and there is a wide range of optional modules. At the end of year 2, you finalise your choice between the 3-year MORSE degree and the 4-year MMORSE (the latter requiring you averaged of least 60% and took the module ST221 on linear statistical modelling).
Final years - The third year includes compulsory modules on advanced probability, statistical modelling, and financial mathematics.
You will learn from a combination of lectures, small-group tutorials and practical sessions based in the Statistics Department’s well-equipped undergraduate computing laboratory. Many core modules are designed specifically with MORSE students in mind. These cover the technical intricacies of theoretical subjects, while emphasising their modern applications.
Core modules are taught by staff from all four partner departments, and involve deriving theorems, optimisation, quantitative reasoning and modelling complex systems. MMORSE students work on their own research project under the guidance of a lecturer or professor.
Overseas and European students forming about one-third of the intake allowing our students to form lifelong, global friendship networks whilst at Warwick.
Class sizes for core modules are around 220 students, though can be higher in some core modules joint with Mathematics degree students. Size of classes for optional modules varies; it can be as large as in core modules but it can be as low as 15 in specific topics in higher years. Support classes usually consist of 15 students.
You will be assessed by a combination of closed and open-book examinations, continuous assessment and project work, depending on your options. The first year counts 10%, the second year 30% and the third year 60% towards the final BSc degree mark.
You may additionally choose to spend an ‘intercalated’ year in an approved industry, business or university between your last two years at Warwick.
A level: A*AA to include A* in Mathematics and A in Further Mathematics or A*A*A + AS Level to include A* in Mathematics and A in AS level Further Mathematics or A*A*A* to include Mathematics or AAA to include Mathematics + 2 in STEP paper
IB: 38 overall to include 7 in Higher Level Mathematics or 38 overall to include 6 in Higher Level Mathematics and 2 in any STEP paper
Additional requirements: You will also need to meet our English Language requirements.
Contextual data and differential offers
Warwick may make differential offers to students in a number of circumstances. These include students participating in the Realising Opportunities programme, or who meet two of the contextual data criteria. Differential offers will be one or two grades below Warwick’s standard offer (to a minimum of BBB).
- Warwick International Foundation Programme (IFP)
All students who successfully complete the Warwick IFP and apply to Warwick through UCAS will receive a guaranteed conditional offer for a related undergraduate programme (selected courses only). For full details of standard offers and conditions visit the IFP website.
- We welcome applications from students with other internationally recognised qualifications. For more information please visit the international entry requirements page.
Taking a gap year
Applications for deferred entry welcomed.
We do not typically interview applicants. Offers are made based on your UCAS form which includes predicted and actual grades, your personal statement and school reference.
Introduction to Quantitative Economics
The focus of this module is mainly on economic theory but "real world" applications of relevant theories will also be examined, subject to time limitations. The module covers aspects of microeconomics and macroeconomics. Microeconomics is concerned with the economic behaviour of individual consumers and producing firms, and their interaction in markets for goods, services and factors of production. Macroeconomics, on the other hand, is concerned with aggregate economic variables or the workings of the national economy as a whole such as Gross Domestic Product, unemployment, inflation and interest rates, and with government economic policies to influence these variables.
Mathematical Programming I
Operational Research is concerned with advanced analytical methods to support decision making, for example for resource allocation, routing or scheduling. A common problem in decision making is finding an optimal solution subject to certain constraints. Mathematical Programming I introduces you to theoretical and practical aspects of linear programming, a mathematical approach to such optimisation problems.
Linear algebra addresses simultaneous linear equations. You will learn about the properties of vector space, linear mapping and its representation by a matrix. Applications include solving simultaneous linear equations, properties of vectors and matrices, properties of determinants and ways of calculating them. You will learn to define and calculate eigenvalues and eigenvectors of a linear map or matrix. You will have an understanding of matrices and vector spaces for later modules to build on.
Analysis is the rigorous study of calculus. In this module there will be considerable emphasis throughout on the need to argue with much greater precision and care than you had to at school. With the support of your fellow students, lecturers and other helpers, you will be encouraged to move on from the situation where the teacher shows you how to solve each kind of problem, to the point where you can develop your own methods for solving problems. By the end of the year you will be able to answer interesting questions like, what do we mean by `infinity'?
Sets and Numbers
It is in its proofs that the strength and richness of mathematics is to be found. University mathematics introduces progressively more abstract ideas and structures, and demands more in the way of proof, until most of your time is occupied with understanding proofs and creating your own. Learning to deal with abstraction and with proofs takes time. This module will bridge the gap between school and university mathematics, taking you from concrete techniques where the emphasis is on calculation, and gradually moving towards abstraction and proof.
Statistical Laboratory 1
If you’re studying ST115 (Introduction to Probability) or ST111/2 (Probability), this course supports your understanding of statistical analysis. You’ll lay foundations for applying mathematical probability, and learn to calculate using probabilities and expectations. You’ll become familiar with the R software package for exploratory data analysis, and gain experience of elementary simulation techniques on real data, and, using visualisations, be able to propose probabilistic models for simple data sets. You’ll also cover sampling technique (standard discrete and continuous distributions – Bernoulli, geometric, Poisson, Gaussian and gamma) and learn generic sampling methods for univariate distributions, preparing you to move on to ST221 (Linear Statistical Modelling).
Introduction to Probability
Following modules MA137 and MA138, this builds your knowledge by introducing key notions of probability and developing your ability to calculate using probabilities and expectations. You’ll experiment with random outcomes through the notion of events and their probability, and look at examples of discrete and continuous probability spaces. You’ll learn counting methods (inclusion–exclusion formula and binomial co-efficients), and study theoretical topics including conditional probability and Bayes’ Theorem. Later, you’ll scrutinise important families of distributions and the distribution of random variables, and the light this shines on the properties of expectations. Finally, you’ll examine mean, variance and co-variance of distribution, through Chebyshev's and Cauchy-Schwartz inequalities.
Want to think like a mathematician? This practical, problem-solving module is for you. Building on your A-level knowledge, you’ll develop a deeper understanding of mathematical concepts and relations, using problem-solving techniques such as visualisation and pattern exploration. Using concrete examples from counting, combinatorics, calculus, geometry and inequalities, you will learn to express mathematical concepts clearly and precisely and enhance your mathematical and logical reasoning and communication skills. By the end of the module, you’ll be able to comprehend, construct, visualise and present a coherent mathematical argument.
The concept of a stochastic (developing randomly over time) process is a useful and surprisingly beautiful mathematical tool in economics, biology, psychology and operations research. In studying the ideas governing sequential stochastic processes, you’ll learn about Markov chains, which use conditional probability for a widely applicable family of random processes; random walks – the building blocks for constructing other processes as well as being important in their own right – and renewal theory, for processes that ‘begin all over again’. Your understanding will extend to notions of behaviour, including transience, recurrence and equilibrium, and you will apply these ideas to problems in probability theory.
Following the algebraic modules MA106 and MA137, you’ll gain expertise in the everyday techniques of probability and statistics essential to your continued study. You’ll gain a grounding in optimisation, convergence, regression and best approximation. By the end of your course, expect to apply multivariate calculus (integration, calculation of under-surface volumes, variable formulae and Fubini’s Theorem) and to use partial derivatives, critical points and extrema, and to understand constrained optimisation. You’ll work on eigenvalues and eigenvectors, diagonalisation, characteristic polynomials, constant co-efficient differential equations, and orthogonal bases and orthonormalisation. You’ll also study convergence and continuity in metric spaces to advance your mathematical thinking.
Mathematical Statistics Part A
If you have already completed ST115, on this module, you’ll have the opportunity to acquire the knowledge you need to study more advanced topics in probability. You’ll study discrete, continuous and multivariate distributions in greater depth, and also learn about Jacobian transformation formula, conditional and multivariate Gaussian distributions, and the related distributions Chi-squared, Student’s and Fisher. In the second part, you’ll move on to more advanced topics, including moment-generating functions for random variables, convergence, and the Law of Large Number and the Central Limit Theorem.
Mathematical Statistics Part B
If you’ve completed Part A, this second-term module is your next step, where you’ll study the major ideas behind statistical inference, with an emphasis on likelihood methods of estimation, repeated sampling, and testing. You’ll learn to apply important models (such as the parametrised statistical model), hypothesis tests, linear models, estimators, and the Chi-squared goodness of fit. You’ll spend time calculating sampling distributions (Fisher’s theorem), and confidence intervals, and understand the principles of data reduction, point estimation and the notion of sufficient statistics. You’ll also become familiar with asymptotic normality and contingency tables, giving you a very firm foundation for your future engagement in advanced mathematical statistics.
Mathematical Economics 1A
This module aims to provide a basic understanding of pure game theory and also introduce You will acquire a sense of the importance of strategic considerations in economic problem solving and will learn that a few simple, intuitive principles, formulated precisely, can go a long way in understanding the fundamental aspects of many economic problems.
Mathematical Programming II
This module builds on the first year module IB104 Mathematical Programming 1. You will learn how to identify the business problems that can be modelled using optimisation techniques and formulate them in a suitable mathematical form. You will then apply optimisation techniques to the solution of the problems using spreadsheets and other appropriate software and learn how to report on the meaning of the optimal solution in a manner suited to a business context.
You can select from a range of modules in year three.
Examples of optional modules/options for current students
Geometry and Motion; Quantum Phenomena; Games, Decisions and Behaviour; Linear Statistical Modelling; Simulation; Introduction to Mathematical Finance; Programming for Data Science; Bayesian Forecasting and Intervention.
Graduates from our MORSE courses have gone on to work for employers including: Acturis, Aldi, BAE Systems, Barclays, BNP Paribas, Hayes, HSBC, Legal and General, RBC Capital Markets, Sainsbury’s and Santander.
They have pursued roles such as: actuaries; business and financial project management professionals; chartered and certified accountants, estimators, valuers and assessors; finance and investment analysts and advisors; investment/merchant bankers; management consultants and business analysts; office managers and statisticians.
Statistics graduates develop a strong range of transferable skills including excellent numerical, problem-solving and analytical abilities. These along with your ability to communicate complex ideas effectively are highly sought after by employers.
A number of students decide to continue in academia, studying for either a Statistics related Masters or PhD. Alternative study routes have included the study of Management Science & Operational Research or the PGCE teaching qualification.
Helping you find the right career
Our department has a dedicated professionally qualified Senior Careers Consultant who works within Student Careers and Skills to help you as an individual. Additionally your Senior Careers Consultant offers impartial advice and guidance together with workshops and events, tailored to our department, throughout the year. Previous examples of workshops and events include:
- Finding experience to boost your CV in Year One and Two
- Careers in Data Science and Artificial Intelligence
- Warwick careers fairs throughout the year
- Interview skills for Statistics students
- Maths and Stats Careers Fair
- Becoming an Actuary Alumni Talk
Find out more about our Careers & Skills Services here.
"Employers want someone to nurture and grow with them."
"MORSE was perfect for me - I wanted to study economics, loved mathematics and found statistics interesting.
I found Warwick stimulating and was surrounded by people who shared my dedication to learning. This really impacted on me and chose to extend the course to the four year version. I gained many skills including coding; I learnt STATA and R as part of the course.
Data analysis is integral to my role as a Financial Conduct Authority economist, and almost every module I studied allowed me to build on these skills."
James Forster - Associate Economist in the Competition & Economics Division of the FCA
Studied 'MORSE' - Graduated 2017
Bachelor of Science (BSc)
3 years full-time
28 September 2020
Location of study
University of Warwick, Coventry
Find out more about fees and funding
Additional course costs
There may be costs associated with other items or services such as academic texts, course notes, and trips associated with your course. Students who choose to complete a work placement will pay reduced tuition fees for their third year.
This information is applicable for 2020 entry.
Given the interval between the publication of courses and enrolment, some of the information may change. It is important to check our website before you apply. Please read our terms and conditions to find out more.
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