School of Mathematics and Statistics
You are viewing this course for 2021-2022 entry.
Degree-level maths is about finding ways to answer big questions. You will look at how mathematicians have tried to answer similar questions in the past. You will also learn how to construct a logical argument with reasoned conclusions.
Your study will include core mathematics, pure mathematics, applied mathematics, and probability and statistics. You can specialise later in your course, and may have the option to switch between our degrees.
You'll have the chance to study scientific programming and simulation, and practical and applied statistics.
For applied mathematics and probability and statistics, you don't need to have prior knowledge of the subject. You'll have plenty of opportunities to focus on your career and skills development too.
The modules listed below are examples from the last academic year. There may be some changes before you start your course. For the very latest module information, check with the department directly.
Choose a year to see modules for a level of study:
UCAS code: G100
- Introduction to Probability and Statistics
The module provides an introduction to the fields of probability and statistics, which form the basis of much of applicable mathematics and operations research. The theory behind probability and statistics will be introduced, along with examples occurring in diverse areas. Some of the computational statistical work may make use of the statistics package R.20 credits
- Mathematics Core 1
The module explores topics in mathematics which will be used throughout many degree programmes. The module will consider techniques for solving equations, special functions, calculus (differentiation and integration), differential equations, Taylor series, complex numbers and finite and infinite series. The course will use mathematical packages, for example MAPLE, as appropriate to illustrate ideas.20 credits
- Mathematics Core II
The module continues the study of core mathematical topics begun in MAS110, which will be used throughout many degree programmes. The module will discuss 2-dimensional co-ordinate geometry, discussing the theory of matrices geometrically and algebraically, and will define and evaluate derivatives and integrals for functions which depend on more than one variable, with an emphasis on functions of two variables. The course will use mathematical packages, for example MAPLE, as appropriate to illustrate ideas.20 credits
- Numbers and Groups
The module provides an introduction to more specialised Pure Mathematics. The first half of the module will consider techniques of proof, and these will be demonstrated within the study of properties of integers and real numbers. The second semester will study symmetries of objects, and develop a theory of symmetries which leads to the more abstract study of groups.20 credits
- Vectors and Mechanics
The module begins with the algebra of vectors, essential for the study of many branches of applied mathematics. The theory is illustrated by many examples, with emphasis on geometry including lines and planes. Vectors are then used to define the velocity and acceleration of a moving particle, thus leading to an introduction to Newtonian particle mechanics. Newton's laws are applied to particle models in areas such as sport, rides at theme parks and oscillation theory.20 credits
- Mathematical Investigation Skills
This module introduces topics which will be useful throughout students time as undergraduates and beyond. These skills fall into two categories: computer literacy and presentation skills. Various computer packages are introduced in other modules; these share some programming capabilities, and one aim of this module is to develop programming techniques to perform mathematical investigations within the context of these mathematical packages. In addition, spreadsheets have substantial scientific capabilities, and Excel is the program of choice within industry. Finally, students will meet the typesetting package LaTeX, preparing reports and presentations into mathematical topics.20 credits
- Advanced Calculus and Linear Algebra
Advanced Calculus and Linear Algebra are basic to most further work in pure and applied mathematics and to much of statistics. This course provides the basic tools and techniques and includes sufficient theory to enable the methods to be used in situations not covered in the course. The material in this course is essential for further study in mathematics and statistics.20 credits
This unit continues the study of abstract algebra begun in MAS114, going further with the study of groups, and introducing the concepts of a ring, which generalises the properties of the integers, and a vector space, which generalises the techniques introduced in linear algebra to many more examples.As well as demonstrating the interest and power of abstraction, this course is vital to further studies in most of pure mathematics, including algebraic geometry and topology, functional analysis and Galois theory.20 credits
This course is a foundation for the rigorous study of continuity and convergence of functions, both in one and in several variables. As well as providing the theoretical underpinnings of calculus, we develop applications of the theory in this course that use the theory, as well as examples that show why the rigour is needed, even if we are focused on applications.The material in this course is vital to further studies in metric spaces, measure theory, parts of probability theory, and functional analysis.20 credits
- Differential Equations
The module aims at developing a core set of advanced mathematical techniques essential to the study of applied mathematics. Topics include the qualitative analysis of ordinary differential equations, solutions of second order linear ordinary differential equations with variable coefficients, first order and second order partial differential equations, the method of characteristics and the method of separation of variables.20 credits
- Statistical Inference and Modelling
This unit develops methods for analysing data, and provides a foundation for further study of probability and statistics at Level 3. It introduces some standard distributions beyond those met in MAS113, and proceeds with study of continuous multivariate distributions, with particular emphasis on the multivariate normal distribution. Transformations of univariate and multivariate continuous distributions are studied, with the derivation of sampling distributions of important summary statistics as applications. The concepts of likelihood and maximum likelihood estimation are developed. Data analysis is studied within the framework of linear models. There will be substantial use of the software package R.20 credits
- Career Development Skills
This unit will equip students with the necessary skills to support them in gaining employment upon graduation. Students will learn how to construct covering letters, CV writing and complete applications to enhance their success when applying for jobs. Skills such as how to communicate mathematics to non-mathematicians and the need for attention to detail will also be introduced.10 credits
- Mathematics and Statistics in Action
This module will demonstrate, in a series of case studies, the use of applied mathematics, probability and statistics in solving a variety of real-world problems. The module will illustrate the process of mathematical and statistical modelling, whereby real-world questions are translated to mathematical and/or statistical questions. Students will see how techniques learned earlier in their degree, as well as simple computer programming, can be used to explore these problems. There will be a mix of individual and group projects, and some projects will involve the use of R or Python, but MAS115 is not a prerequisite.10 credits
- Mechanics and Fluids
This module extends the Newtonian mechanics studied in MAS112. The main topics treated are (i) extensions of the work-energy principle and conservation of energy, (ii) a full treatment of planetary and satellite motion, (iii) the elements of rigid body motion, and (iv) inviscid (frictionless) fluid motions. The course is a prerequisite for students wishing to pursue higher level modules in fluid mechanics.10 credits
- Probability Modelling
The course introduces a number of general models for processes where the state of a system is fluctuating randomly over time. Examples might be the length of a queue, the size of a reproducing population, or the quantity of water in a reservoir. The aim is to familiarize students with an important area of probability modelling.10 credits
- Scientific Computing and Simulation
The module further develops the students' skills in computer programming and independent investigations. The students will learn how to solve algebraic and differential equations using the solvers in Python as well as Python codes developed by themselves. The students will learn basic computing methods and methods to visualize and analyze numerical results, and then apply the knowledge to explore the physical behaviors of model equations.10 credits
- Practical and Applied Statistics
The overall aim of the course is to give students practice in the various stages of dealing with a real problem: objective definition, preliminary examination of data, modelling, analysis, computation, interpretation and communication of results. It could be said that while other courses teach how to do statistics, this teaches how to be a statistician. There will be a series of projects and other exercises directed towards this aim. Projects will be assessed, but other exercises will not.20 credits
- Stochastic Processes and Finance
A stochastic process is a mathematical model for phenomena unfolding dynamically and unpredictably over time. This module studies two classes of stochastic process particularly relevant to financial phenomena: martingales and diffusions. The module develops the properties of these processes and then explores their use in Finance. A key problem considered is that of the pricing of a financial derivative such as an option giving the right to buy or sell a stock at a particular price at a future time. What is such an option worth now? Martingales and stochastic integration are shown to give powerful solutions to such questions.20 credits
- Group Project
This unit will provide students with opportunities to improve their transferable skills by working in groups of (normally) four students to investigate a mathematical project topic. Students will be expected to register for SOM369 in pre-formed groups of four. With the aid of the Library and the internet each group will produce a (single) written account of the group¿s investigations into the topic, and contribute to an oral presentation of their work. Topics will be proposed by members of staff, but groups may propose their own. The module Coordinator will provide guidance about working in groups, and on appropriate techniques for the written and oral presentation of mathematical topics.10 credits
- Undergraduate Ambassadors Scheme in Mathematics
This module provides an opportunity for Level Three students to gain first hand experience of mathematics education through a mentoring scheme with mathematics teachers in local schools. Typically, each student will work with one class for half a day every week for 11 weeks. The classes will vary from key stage 2 to sixth form. Students will be given a range of responsibilities from classroom assistant to the organisation and teaching of self-originated special projects. Only a limited number of places are available and students will be selected on the basis of their commitment and suitability for working in schools.20 credits
- Advanced Operations Research
Mathematical Programming is concerned with the algorithms that deal with constrained optimisation problems. We consider only constraints which are linear, and for which the objective function to be maximised or minimised is also linear. These problems are not continuously differentiable and so they do not fall into the category of problems considered in organisation; special algorithms have to be developed. The module considers not only the solution of such problems but also the important area of post-optimality analysis; i.e. given the solution can one answer questions about the effect of small changes in the parameters of the problem (such as values of the cost coefficients)? Additional topics will include the transportation and assignment problems.10 credits
- Applied Probability
The unit will link probability modelling to Statistics. It will explore a range of models that can be constructed for random phenomena that vary in time or space - the evolution of an animal population, for example, or the number of cancer cases in different regions of the country. It will illustrate how models are built and how they might be applied: how likelihood functions for a model may be derived and used to fit the model to data, and how the result may be used to assess model adequacy. Models examined will build on those studied in MAS27510 credits
- Bayesian Statistics
This unit develops the Bayesian approach to statistical inference. The Bayesian method is fundamentally different in philosophy from conventional frequentist/classical inference, and has been the subject of some controversy in the past. It is, however, becoming increasingly popular in many fields of applied statistics. This course will cover both the foundations of Bayesian statistics, including subjective probability, utility and decision theory, and modern computational tools for practical inference problems, specifically Markov chain Monte Carlo methods and Gibbs sampling. Applied Bayesian methods will be demonstrated in a series of case studies using the software package WinBUGS.10 credits
- Codes and Cryptography
The word `code' is used in two different ways. The ISBN code of a book is designed in such a way that simple errors in recording it will not produce the ISBN of a different book. This is an example of an `error-correcting code' (more accurately, an error-detecting code). On the other hand, we speak of codes which encrypt information - a topic of vital importance to the transmission of sensitive financial information across the internet. These two ideas, here labelled `Codes' and `Cryptography', each depend on elegant pure mathematical ideas: codes on linear algebra and cryptography on number theory. This course explores these topics, including the real-life applications and the mathematics behind them.10 credits
Combinatorics is the mathematics of selections and combinations. For example, given a collection of sets, when is it possible to choose a different element from each of them? That simple question leads to Hall's Theorem, a far-reaching result with applications to counting and pairing problems throughout mathematics.10 credits
- Complex Analysis
It is natural to use complex numbers in algebra, since these are the numbers we need to provide the roots of all polynomials. In fact, it is equally natural to use complex numbers in analysis, and this course introduces the study of complex-valued functions of a complex variable. Complex analysis is a central area of mathematics. It is both widely applicable and very beautiful, with a strong geometrical flavour. This course will consider some of the key theorems in the subject, weaving together complex derivatives and complex line integrals. There will be a strong emphasis on applications. Anyone taking the course will be expected to know the statements of the theorems and be able to use them correctly to solve problems.10 credits
- Continuum Mechanics
Continuum mechanics is concerned with the mechanical behaviour of solids and fluids which change their shape when forces are applied. For example, rubber extends when pulled but behaves elastically returning to its original shape when the forces are removed. Water starts to move when the external pressure is applied. This module aims to introduce the basic kinematic and mechanical ideas needed to model deformable materials and fluids mathematically. They are needed to develop theories which describe elastic solids and fluids like water. In this course, a theory for solids which behave elastically under small deformations is developed. This theory is also used in seismology to discuss wave propagation in the Earth. An introduction in theory of ideal and viscous, incompressible and compressible fluids is given. The theory is used to solve simple problems. In particular, the propagation of sound waves in the air is studied.10 credits
- Differential Geometry
What is differential geometry? In short, it is the study of geometric objects using calculus. In this introductory course, the geometric objects of our concern are curves and surfaces. Besides calculating such familiar quantities as lengths, angles and areas, much of our focus is on how to measure the 'shape' of a geometric object. The story is relatively simple for curves, but naturally becomes more involved for surfaces - and more interesting too. Well-known notions (e.g. straight lines) and results (e.g. sum of angles in a triangle) in Euclidean geometry are to be modified, in certain precise ways, for general surfaces. The course concludes with the celebrated Gauss-Bonnet Theorem, which shows how small- and large-scale behaviours of a surface can impact each other.10 credits
A field is a set where the familiar operations of arithmetic are possible. It often happens, particularly in the theory of equations, that one needs to extend a field by forming a bigger one. The aim of this course is to study the idea of field extension and various problems where it arises. In particular, it is used to answer some classical problems of Greek geometry, asking whether certain geometrical constructions, such as angle trisection or squaring the circle, are possible.10 credits
- Financial Mathematics
The discovery of the Capital Asset Pricing Model by William Sharpe in the 1960's and the Black-Scholes option pricing formula a decade later mark the beginning of a very fruitful interaction between mathematics and finance. The latter obtained new powerful analytical tools while the former saw its knowledge applied in new and surprising ways. (A key result used in the derivation of the Black-Scholes formula, Ito's Lemma, was first applied to guide missiles to their targets; hence the title 'rocket science' applied to financial mathematics). This course describes the mathematical ideas behind these developments together with their application in modern finance.10 credits
- Fluid Mechanics I
The way in which fluids move is of immense practical importance; the most obvious examples of this are air and water, but there are many others such as lubricants in engines - and alcohol! Moreover, the scientific principles and mathematical techniques needed to explain fluid motion are of intrinsic interest. This half-module builds on Level 2 work (MAS271 Methods for Differential Equations; MAS270 Vectors and Fluid Mechanics) and, more particularly, the ground work covered in MAS310 Continuum Mechanics. The first step is to derive the equation (Navier-Stokes equations) governing the motions of most common fluids. These serve as a basis for the remainder of MAS320.10 credits
- Galois Theory
Given a field K (as studied in MAS333/MAS438) one can consider the group G of isomorphisms from K to itself. In the cases of interest, this is a finite group, and there is a tight link (called the Galois correspondence) between the structure of G and the subfields of K. If K is generated over the rationals by the roots of a polynomial f(x), then G can be identified as a group of permutations of the set of roots. One can then use the Galois correspondence to help find formulae for the roots, generalising the standard formula for the roots of a quadratic. It turns out that this works whenever the degree of f(x) is less than five. However, the fifth symmetric group lacks certain group-theoretic properties that lie behind these formulae, so there is no analogous method for solving arbitrary quintic equations. The aim of this course is to explain this theory, which is strikingly rich and elegant.10 credits
- Game Theory
The module will give students the opportunity to apply previously acquired mathematical skills to the study of Game Theory and to some of the applications in Economics.10 credits
- Generalised Linear models
This module introduces the theory and application of generalised linear models. These models can be used to investigate the relationship between some quantity of interest, the “dependent variable”, and one more “explanatory” variables; how the dependent variable changes as the explanatory variables change. The term “generalised” refers to the fact that these models can be used for a wide range of different types of dependent variable: continuous, discrete, categorical, ordinal etc. The application of these models is demonstrated using the programming language R.10 credits
- Graph Theory
.A graph is a simple mathematical structure consisting of a collection of points, some pairs of which are joined by lines. Their basic nature means that they can be used to illustrate a wide range of situations. The aim of this course is to investigate the mathematics of these structures and to use them in a wide range of applications.10 credits
- History of Mathematics
The course aims to introduce the student to the history of mathematics. The topics discussed are Egyptian and Babylonian mathematics, early Greek mathematics, Renaissance mathematics, and the early history of the calculus.10 credits
- Introduction to Relativity
Einstein's theory of relativity is one of the corner stones of our understanding of the universe. This course will introduce some of the ideas of relativity, and the physical consequences of the theory, many of which are highly counter-intuitive. For example, a rapidly moving body will appear to be contracted as seen by an observer at rest. The course will also introduce one of the most famous equations in the whole of mathematics: E=mc2.10 credits
- Knots and Surfaces
The course studies knots, links and surfaces in an elementary way. The key mathematical idea is that of an algebraic invariant: the Jones polynomial for knots, and the Euler characteristic for surfaces. These invariants will be used to classify surfaces, and to give a practical way to place a surface in the classification. Various connections with other sciences will be described.10 credits
- Machine Learning
Machine learning lies at the interface between computer science and statistics. The aims of machine learning are to develop a set of tools for modelling and understanding complex data sets. It is an area developed recently in parallel between statistics and computer science. With the explosion of ¿Big Data¿, statistical machine learning has become important in many fields, such as marketing, finance and business, as well as in science. The module focuses on the problem of training models to learn from training data to classify new examples of data.10 credits
- Mathematical Biology
The unit is concerned with the Mathematical Modelling of the growth and spread of biological populations. These models may be deterministic but the emphasis will be on stochastic models where an element of randomness is present. They range from simple models which assume that there is no competition and individuals are free to live and reproduce independently of each other, to more complicated ones where there is interaction between different individuals, for example because of shortage of food or the presence of an epidemic. Where explicit solutions are not readily obtainable, some attention will be paid to approximations and simulations which give a qualitative picture of the behaviour of a model.10 credits
- Mathematical Methods
This course introduces methods which are useful in many areas of mathematics. The emphasis will mainly be on obtaining approximate solutions to problems which involve a small parameter and cannot easily be solved exactly. These problems will include the evaluation of integrals and the solution of differential equations. Examples of possible applications are: oscillating motions with small nonlinear damping, the effect of other planets on the Earth's orbit around the Sun, boundary layers in fluid flows, electrical capacitance of long thin bodies, central limit theorem correction terms for finite sample size.10 credits
- Mathematical modelling of natural systems
Mathematical modelling enables insight in to a wide range of scientific problems. This module will provide a practical introduction to techniques for modelling natural systems. Students will learn how to construct, analyse and interpret mathematical models, using a combination of differential equations, scientific computing and mathematical reasoning. Students will learn the art of mathematical modelling: translating a scientific problem into a mathematical model, identifying and using appropriate mathematical tools to analyse the model, and finally relating the significance of the mathematical results back to the original problem. Study systems will be drawn from throughout the environmental and life sciences.10 credits
- Measure and Probability
The module will give students an additional opportunity to develop skills in modern analysis as well as providing a rigorous foundation for probability theory. In particular it would form a useful precursor or companion course to the Level 4 courses MAS436 (Functional Analysis) and MAS452 (Stochastic Processes and Finance), the latter of which is fundamentally dependent on measure theoretic ideas10 credits
- Medical Statistics
This course comprises sections on Clinical Trials and Survival Data Analysis. The special ethical and regulatory constraints involved in experimentation on human subjects mean that Clinical Trials have developed their own distinct methodology. Students will, however, recognise many fundamentals from mainstream statistical theory. The course aims to discuss the ethical issues involved and to introduce the specialist methods required. Prediction of survival times or comparisons of survival patterns between different treatments are examples of paramount importance in medical statistics. The aim of this course is to provide a flavour of the statistical methodology developed specifically for such problems, especially with regard to the handling of censored data (eg patients still alive at the close of the study). Most of the statistical analyses can be implemented in standard statistical packages.10 credits
- Metric Spaces
This unit explores ideas of convergence of iterative processes in the more general framework of metric spaces. A metric space is a set with a distance function which is governed by just three simple rules, from which the entire analysis follows. The course follows on from MAS207 `Continuity and Integration', and adapts some of the ideas from that course to the more general setting. The course ends with the Contraction Mapping Theorem, which guarantees the convergence of quite general processes; there are applications to many other areas of mathematics, such as to the solubility of differential equations.10 credits
- Operations Research
Mathematical Programming is the title given to a collection of optimisation algorithms that deal with constrained optimisation problems. Here the problems considered will all involve constraints which are linear, and for which the objective function to be maximised or minimised is also linear. These problems are not continuously differentiable; special algorithms have to be developed. The module considers not only the solution of such problems but also the important area of post-optimality analysis; i.e. given the solution can one answer questions about the effect of small changes in the parameters of the problem (such as values of the cost coefficients)?10 credits
- Optics and Symplectic Geometry
This course is an introduction to some of the areas of pure mathematics which have evolved from the mathematical study of optics. Optics provides a unifying thread, but no prior knowledge of the properties of light is required. Mathematical topics covered include symplectic structures on vector spaces, symplectic maps and matrices, Lagrangian subspaces and characteristic functions and, if time permits, an introduction to the Maslov class and/or Symplectic manifolds. In terms of optics we cover Gaussian, linear and geometrical optics and (if time permits) an introduction to aberration.10 credits
- Quantum Theory
The development of quantum theory revolutionized both physics and mathematics during the 20th century. The theory has applications in many technological advances, including: lasers, super-conductors, modern medical imaging techniques, transistors and quantum computers. This course introduces the basics of the theory and brings together many aspects of mathematics: for example, probability, matrices and complex numbers. Only first year mechanics is assumed, and other mathematical concepts will be introduced as they are needed.10 credits
- Sampling Theory and Design of Experiments
The results of sample surveys through opinion polls are commonplace in newspapers and on television. The objective of the Sampling Theory section of the module is to introduce several different methods for obtaining samples from finite populations. Experiments which aim to discover improved conditions are commonplace in industry, agriculture, etc. The purpose of experimental design is to maximise the information on what is of interest with the minimum use of resources. The aim of the Design section is to introduce some of the more important design concepts.10 credits
- Time Series
Time series are observations made in time, for which the time aspect is potentially important for understanding and use. The course aims to give an introduction to modern methods of time series analysis and forecasting as applied in economics, engineering and the natural, medical and social sciences. The emphasis will be on practical techniques for data analysis, though appropriate stochastic models for time series will be introduced as necessary to give a firm basis for practical modelling. Appropriate computer packages will be used to implement the methods.10 credits
- Topics in Number Theory
This module aims to investigate some of the properties of the natural numbers 1,2,3,... Topics covered include linear and quadratic congruences, Fermat's Little Theorem, the RSA cryptosystem, the Law of Quadratic Reciprocity, perfect numbers, Mersenne primes, Fermat's Last Theorem, continued fractions, and Pell's equation.10 credits
Studying wave phenomena has had a great impact on Applied Mathematics. This module looks at some important wave motions with a view to understanding them by developing from first principles the key mathematical tools. We begin with waves on strings (e.g. a piano or violin), developing the concept of standing and progressive waves, and normal modes. Fourier series are used to solve problems relating to waves on strings and membranes. Sound waves and water waves are considered. The concepts of dispersion and group velocity are introduced. The course concludes with consideration of 'traffic waves' as the simplest example of nonlinear waves.10 credits
The content of our courses is reviewed annually to make sure it's up-to-date and relevant. Individual modules are occasionally updated or withdrawn. This is in response to discoveries through our world-leading research; funding changes; professional accreditation requirements; student or employer feedback; outcomes of reviews; and variations in staff or student numbers. In the event of any change we'll consult and inform students in good time and take reasonable steps to minimise disruption.
Learning and assessment
You'll learn through lectures, problems classes in small groups and research projects. Some modules also include programming classes.
With Access Sheffield, you could qualify for additional consideration or an alternative offer - find out if you're eligible
The A Level entry requirements for this course are:
including A in Maths
The A Level entry requirements for this course are:
including A in Maths
A Levels + additional qualifications | ABB, including A in Maths + B in a relevant EPQ; ABB, including A in Maths + B in Further Maths ABB, including A in Maths + B in a relevant EPQ; ABB, including A in Maths + B in Further Maths
International Baccalaureate | 34, 6 in Higher Level Mathematics (Analysis and Approaches) 33 with 6 in Higher Level Mathematics
BTEC | DDD with Distinctions in Maths units DDD with Distinctions in Maths units
Scottish Highers + 1 Advanced Higher | AAABB + A in Maths AAABB + A in Maths
Welsh Baccalaureate + 2 A Levels | B + AA, including Maths B + AB, including A Maths
Access to HE Diploma | 60 credits overall in a relevant subject with Distinctions in 36 Level 3 credits, including Mathematics units, + Merits in 9 Level 3 credits 60 credits overall in a relevant subject with Distinctions in 30 Level 3 credits, including Mathematics units, + Merits in 15 Level 3 credits
Mature students - explore other routes for mature students
You must demonstrate that your English is good enough for you to successfully complete your course. For this course we require: GCSE English Language at grade 4/C; IELTS grade of 6.5 with a minimum of 6.0 in each component; or an alternative acceptable English language qualification
We will give your application additional consideration if you have passed the Sixth Term Examination Paper (STEP) at grade 3 or above or the Test of Mathematics for University Admissions (TMUA) at grade 5 or above
If you have any questions about entry requirements, please contact the department.
School of Mathematics and Statistics
From geometry to probability, our courses cover all aspects of mathematics, pure and applied. With modules in finance, science, engineering and medical applications, we showcase the wide-ranging relevance and importance of mathematics.
Degree-level maths is about finding ways to answer big questions. You'll explore how mathematicians have tried to answer similar questions in the past. You'll also learn how to construct logical arguments with reasoned conclusions.
Your study will include core mathematics, pure mathematics, applied mathematics, and probability and statistics. You can specialise later in your course, and may have the option to switch between our degrees. You'll have the chance to study scientific programming and simulation, and practical and applied statistics. You'll have plenty of opportunities to focus on your career and skills development too.
The School of Mathematics and Statistics is based in the Hicks Building, which is next door to the Students' Union, and just down the road from the library facilities at the Information Commons and the Diamond. The Department of Physics and Astronomy is also based here.
Why choose Sheffield?
The University of Sheffield
A Top 100 university 2021
QS World University Rankings
Top 10% of all UK universities
Research Excellence Framework 2014
No 1 Students' Union in the UK
Whatuni Student Choice Awards 2019, 2018, 2017
No 1 in the north for graduate employment
The Times and Sunday Times Good University Guide 2020
School of Mathematics and Statistics
National Student Survey 2019
School of Mathematics and Statistics
In the age of big data, major companies are increasingly reliant on graduates with numerical skills.
Many of our graduates go on to finance-related careers: accountancy, actuarial work, public finance, insurance. There are lots of other choices too, including: teaching, advertising, software development, operations research, drug development and meteorology.
Employers include PricewaterhouseCoopers, KPMG, Deloitte UK, GCHQ, British Airways and the European Space Agency.
Some of our graduates choose further study in mathematics and related sciences at masters and PhD level.
Fees and funding
The annual fee for your course includes a number of items in addition to your tuition. If an item or activity is classed as a compulsory element for your course, it will normally be included in your tuition fee. There are also other costs which you may need to consider.
Funding your study
Depending on your circumstances, you may qualify for a bursary, scholarship or loan to help fund your study and enhance your learning experience.
Use our Student Funding Calculator to work out what you're eligible for.
University open days
There are four open days every year, usually in June, July, September and October. You can talk to staff and students, tour the campus and see inside the accommodation.
At various times in the year we run online taster sessions to help Year 12 students experience what it is like to study at the University of Sheffield.
If you've received an offer to study with us, we'll invite you to one of our applicant open days, which take place between November and April. These open days have a strong department focus and give you the chance to really explore student life here, even if you've visited us before.
Campus tours run regularly throughout the year, at 1pm every Monday, Wednesday and Friday.
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