Mathematics and Statistics at University of Oxford

Oxford combines Mathematics and Mathematics and Statistics at admissions stage, so the first part of the degree is deliberately broad. The first year covers pure mathematics, applied mathematics, probability, statistics and computation before later route choice.

Read the ranking comparison as a Mathematics subject-table comparison, not as a separate undergraduate ranking for Oxford Mathematics and Statistics; the Times/Sunday Times subject rank was not verified in the audit. Within the partial peer table, Oxford is listed as #2 in the primary Mathematics ranking display, with Cambridge, St Andrews, Imperial, Warwick and UCL used as comparison points.

The course is built for applicants who enjoy moving between rigorous proof and quantitative uncertainty. In practice, it helps to show both: the ability to solve abstract mathematical problems, and the judgement to ask what a statistical model can and cannot justify.

For 2027 entry, Oxford requires TMUA for Mathematics / Mathematics and Statistics. The test is provided by UAT-UK and delivered online by Pearson VUE.

Oxford applicants must take both Paper 1: Applications of Mathematical Knowledge and Paper 2: Mathematical Reasoning. The 2027-entry October sitting is scheduled for 12-16 October 2026; UAT-UK notes that candidates in China, Hong Kong and Macau may take TMUA only on 15 and 16 October 2026.

Registration account creation, access arrangements and bursary requests open on 1 June 2026 at 3pm UK time, and test booking opens on 20 July 2026 at 3pm BST. Booking closes on 28 September 2026 at 6pm BST.

This is a major change for Oxford Mathematics applicants: for 2027 entry, TMUA replaces the previous MAT route. Oxford states there is no published pass mark, and TMUA is considered alongside UCAS information and school background when shortlisting.

For international students, TMUA gives Oxford another common measure across different school systems. In reality, that means preparation needs to be planned early, especially where test-centre availability or local sitting dates are narrower.

A good Mathematics and Statistics personal statement should not try to sound like a miniature research paper. We recommend using two or three examples where you can explain what you investigated, what became difficult, and what changed in your thinking.

For this course, it helps to connect pure mathematical reasoning with probability, statistics or data. A project that compares a simulation with an exact probability argument can be more convincing than a long reading list with no reflection.

Avoid claiming certainty too early. Oxford's structure keeps Mathematics and Mathematics and Statistics joint until after the fourth term, so it is reasonable to show breadth while making clear why statistics and uncertainty interest you; for example, you might explain how a probability model, statistical simulation or critique of a dataset changed your mathematical judgement.

For mathematical breadth:

• What Is Mathematics? by Richard Courant and Herbert Robbins, revised by Ian Stewart, is useful because it is a classic bridge from school mathematics to deeper proof, structure and mathematical taste.
• How to Solve It by George Pólya is useful because it is a guide to mathematical problem-solving habits and heuristic thinking.

For statistics and applied judgement:

• The Art of Statistics by David Spiegelhalter is useful because it builds statistical judgement and data literacy through real-world examples.
• An Introduction to Statistical Learning by Gareth James, Daniela Witten, Trevor Hastie, Robert Tibshirani and Jonathan Taylor is useful because it is a free introduction to modern statistical learning for motivated statistics applicants.
• The Pleasures of Counting by T. W. Körner is useful because it shows how mathematical thinking connects to real problems and applied reasoning.

For visual explanation and public lectures:

• Oxford Mathematics helps with official public lectures, student lectures and research films from the Oxford Mathematical Institute.
• 3Blue1Brown helps with visual explanations for algebra, calculus, linear algebra and probability.
• Numberphile helps with accessible conversations with mathematicians that can spark reading trails.
• StatQuest helps with clear statistical and machine-learning explanations.

For listening and statistical judgement:

• The Numberphile Podcast is worth using because it offers long-form interviews with mathematicians and mathematically minded thinkers.
• More or Less: Behind the Stats is worth using because it develops awareness of how statistics are used and misused in public debate.
• The Joy of Why is worth using because it explores research-level ideas through careful conversations.

For structured online study:

• MIT OpenCourseWare 18.05: Introduction to Probability and Statistics gives you a structured free course for probability and statistics beyond school level.
• MIT OpenCourseWare 18.01SC: Single Variable Calculus gives you a resource useful for strengthening calculus fluency and conceptual understanding.
• Khan Academy Statistics and Probability gives you a broad revision path for core probability and statistics concepts.
• Seeing Theory gives you interactive visual explanations of probability and statistics.
• Essence of Linear Algebra gives you a visual route into vector spaces, transformations and eigenvectors.

29 colleges offer this subject. around 20% of applicants submit an open application. around one third of applicants may be reallocated across Oxford; the Mathematical Institute states around 25-30% of offers for Mathematics-related courses are not with the applicant's first college. of places come through the pool.

Applicants may name a college or submit an open application.

Around 20% of applicants make an open application, and Oxford states tutors have no preference for open or direct applications. The Mathematical Institute states that around 25-30% of offers for Mathematics-related courses are not with the applicant's first college.

College choice should mainly be a living and learning environment decision. All Mathematics students attend the same departmental lectures and sit the same examinations.

Oxford shortlisting considers UCAS information alongside contextual information about school background and factors that may explain achieved or predicted grades. For Mathematics and joint honours, there is no TMUA pass mark; test information is considered with the UCAS application and school background.

Further Mathematics is recommended, and Oxford expects applicants with access to Further Mathematics to take it while recognising cases where it is not available. GCSEs, where taken, are considered as one measure of academic achievement and contextualised with cohort data about the school where they were achieved.

Disruption, disability, care experience, school access to subjects and other educational circumstances should be disclosed through the relevant UCAS, school-reference or Oxford-specific routes.