Mathematics and Statistics

Program Overview

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Mathematics and Statistics

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The MMath Mathematics and Statistics degree takes your study of mathematical techniques and statistical principles to a higher level. The course includes an integrated year of Master's-level study and the opportunity to conduct a project in collaboration with an external organisation.

Start Dates

• September 2026
• September 2025

Degree Type

MMath

Course Length

4 years full-time

Location

Durham City

UCAS Code

G114

Typical Offers

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A Level

• AAA
• AA in Mathematics and Further Mathematics or AAA including AA in Mathematics and Further Mathematics and a suitable performance in an accepted mathematics test.

Contextual Offer

• AAC
• AA in Mathematics and Further Mathematics or AAB including AA in Mathematics and Further Mathematics or AAC including AA in Mathematics and Further Mathematics and a suitable performance in an accepted mathematics test.

BTEC Level 3 National Extended Diploma/OCR Cambridge Technical Extended Diploma

• DDD-D*DD
• A level requirements as above.

IB Diploma Score

• 38 with 776 in higher level subjects, including a 7 in Higher Level Mathematics (Analysis & Approaches) or 766 in higher level subjects, including a 7 in Higher Level Mathematics (Analysis & Approaches) and a suitable performance in an accepted mathematics test.

Course Details

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This challenging degree takes your study of Mathematics and Statistics to Master’s level. It is the ideal choice if you are considering postgraduate study or a career that requires high-level numeracy skills or research.

The MMath combines a strong mathematical grounding with the latest developments in statistics and machine learning to provide the foundation you’ll need to step into a data-driven workplace. The first two years follow a similar structure to the BSc. The wider range of modules introduced in Years 3 and 4 explore more sophisticated mathematical and statistical techniques in greater depth.

The course is based in a brand-new facility, purpose-built to meet the learning, teaching and study needs of students from the Department. You will be taught by a team of mathematicians and statisticians with a wealth of experience in industry and research.

The Department is home to a number of research groups with specialisms in both pure and applied mathematics. With many members of the teaching team actively involved in research there are plenty of opportunities to link learning to the latest research in distinctive and creative ways.

Course Structure

Year 1 Modules

Core Modules:

• Analysis: aims to provide an understanding of real and complex number systems, and to develop rigorously the calculus of functions of a single variable from basic principles.
• Calculus: builds on ideas of differentiation and integration in A level mathematics, beginning with functions of a single variable and moving on to functions of several variables. Topics include methods of solving ordinary and partial differential equations, and an introduction to Fourier Series and Fourier transforms.
• Linear Algebra: presents mathematical ideas, techniques in linear algebra and develops geometric intuition and familiarity with vector methods in preparation for more demanding material later in the course.
• Dynamics: develops an understanding of elementary classical Newtonian dynamics as well as an ability to formulate and solve basic problems in dynamics.
• Probability: introduces mathematics ideas on probability in preparation for more specialised material later in the course. The module presents a mathematical subject of key importance to the real-world (applied) that is based on rigorous mathematical foundations (pure).
• Programming: is taught via lectures and practical sessions that introduce basic principles and competence in computer programming. You will also study control structures; floating point arithmetic; and lists, strings and introduction to objects.
• Statistics: introduces frequentist and Bayesian statistics and demonstrates the relevance of these principles and procedures to real problems. This module lays the foundations for all subsequent study of statistics.

Year 2 Modules

Core Modules:

• Analysis in Many Variables: provides an understanding of calculus in more than one dimension, together with an understanding of, and facility with, the methods of vector calculus. It also explores the application of these ideas to a range of forms of integration and to solutions of a range of classical partial differential equations.
• Statistical Inference: introduces the main concepts underlying statistical inference and methods. This module develops the foundations underlying classical statistical techniques, and the basis for the Bayesian approach to statistics. You will also investigate and compare frequentist and Bayesian approaches.
• Data Science and Statistical Computing: equips you with the skills to import, explore, manipulate, model and visualise real data sets using the statistical programming language R. The module introduces the concepts and mathematics behind sampling. It also covers data protection and governance issues when working with data.
• Statistical Modelling: provides a working knowledge of the theory, computation and practice of the linear model. You will cover areas including analysis of variance, model selection, diagnostics and transformation methods.

Optional Modules:

In recent years optional modules have included:

• Algebra
• Complex Analysis
• Mathematical Physics
• Numerical Analysis
• Elementary Number Theory
• Geometric Topology
• Markov Chains
• Mathematical Modelling
• Probability
• Special Relativity and Electromagnetism

Year 3 Modules

Optional Modules:

In recent years optional modules have included:

• Advanced Statistical Modelling
• Bayesian Computation and Modelling
• Decision Theory
• Machine Learning and Neural Networks
• Mathematical Finance
• Stochastic Processes

Year 4 Modules

Core Modules:

• Project: In the final year Project you will investigate a statistical topic of interest or perform an in-depth analysis of a data set using the tools acquired earlier in the course. You then produce a written report and give a short presentation. Subject to availability, you may have the opportunity to perform this project in collaboration with an external organisation. The project develops your research and communication skills which are important for future employment or postgraduate studies.
• Internship Project: The Internship Project gives you the opportunity to conduct a substantial piece of independent statistics and machine learning work in a real-world context working with a third party, and to write up and present this work. This will further your analytical, collaborative and transferable skills, and your knowledge of the practice of statistics and machine learning, as well as advance your abilities in oral or written communication.

Optional Modules:

In recent years optional modules have included:

• Spatio-Temporal Statistics
• Deep Learning and Artificial Intelligence
• Discrete and Continuous Probability
• High-Dimensional Data Analysis
• Non-Parametric Statistics
• Object-Oriented Statistics
• Robust Bayesian Analysis
• Topics in Probability
• Uncertainty Quantification

Additional Pathways

Students can apply to be transferred onto either the with Year Abroad or with Placement pathway. Places on these pathways are in high demand and if you are chosen your studies will extend from three years to four or four to five depending on course.

Learning

Methods of teaching and learning include lectures, tutorials, problem classes, homework problems, written and oral presentations and individual projects. You will also take part in computer practicals, in which you learn how to implement computational methods and how to analyse real data.

For most modules you will attend two lectures a week. Mathematical questions are set in lectures and may form the topic of discussion in tutorials or problem classes. The best way to learn maths is to work through problems, so in addition to independent study we recommend collaborative working with other students.

The final-year project is organised around fortnightly small-group meetings with lecturers. You are free to choose the remaining modules from a range of subjects including statistics, machine learning, and probability, plus a teaching module in which you study how pupils learn in school.

Assessment

We use a combination of methods to assess the different modules, these include written examinations, computer-based examinations, project reports and presentations of project work.

In your final year you also complete an in-depth project which is worth one-third of your final-year marks.

Entry Requirements

A Level Offer

• AAA
• AA in Mathematics and Further Mathematics or AAA including AA in Mathematics and Further Mathematics and a suitable performance in an accepted mathematics test.

Contextual Offer

• AAC
• AA in Mathematics and Further Mathematics or AAB including AA in Mathematics and Further Mathematics or AAC including AA in Mathematics and Further Mathematics and a suitable performance in an accepted mathematics test.

BTEC Level 3 National Extended Diploma/OCR Cambridge Technical Extended Diploma

• DDD-D*DD
• A level requirements as above.

IB Diploma Score

• 38 with 776 in higher level subjects, including a 7 in Higher Level Mathematics (Analysis & Approaches) or 766 in higher level subjects, including a 7 in Higher Level Mathematics (Analysis & Approaches) and a suitable performance in an accepted mathematics test.

Fees and Funding

The fees for this academic year have not been confirmed yet.

The tuition fees shown for home students are for one complete academic year of full-time study and are set according to the academic year of entry. Fees for subsequent years of your course may rise in line with an inflationary uplift as determined by the government.

Career Opportunities

Mathematical Sciences

As well as developing you academically, a Durham University degree will equip you with a range of practical skills including critical thinking, an analytical approach and ability to reason with information, alongside experience in building relationships and leading teams.

A significant number of our students progress to higher level study following their degree. Some remain within their academic field of interest and pursue higher level research, notably at Durham but also other prestigious institutions. Others take a different route and pursue postgraduate programmes or employment in areas from statistics and financial management to conservation and teaching.

Some of the high-profile employers our graduates have gone on to work for include Royal London, Deloitte, CERN, Morgan Stanley and Ocado.

Department Information

Mathematical Sciences

Are you a natural problem-solver? If you relish the challenge of tackling complex problems, then Mathematical Sciences at Durham could be your perfect match.

Mathematical Sciences offers a high-quality education that is taught by subject specialists, informed by the latest research and delivered in a stimulating academic environment. Using distinctive and creative methods, we do all we can to incorporate relevant aspects of the Department’s world-leading research into the undergraduate curriculum.

We offer a range of degrees which give you a choice from a wide spectrum of pure mathematics, applied mathematics (including mathematical physics) and statistics.

The overall aim is to develop you as a member of the community of professional mathematicians. Degrees combine theoretical learning with practicals and mini projects, enabling you to develop your capacity for critical thinking, problem-solving and independent learning, which will equip you with the skills to meet a variety of challenges in the workplace. We seek to develop both the generic and subject-specific skills you need to pursue a range of careers, and to further develop your skills we offer the opportunity to spend a year studying overseas or working in industry.

Rankings

• Top 10 The Complete University Guide 2025

Facilities

The Department lies in the heart of the University on the Upper Mountjoy campus near to the University library and the science and engineering departments. We share our purpose-built £40 million new building with Computer Sciences given the natural synergy between the subjects.