14Jun
UndergraduateDurham University has participated in the Teaching Excellence Framework.These ratings were awarded in 2023, for four years.
Open days
Course summary
Mathematics and Statistics is a fascinating mix of subjects that will suit those with enquiring minds, strong IT skills and an interest in identifying and analysing patterns in data. The BSc 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. When you choose maths you’ll 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 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. You will be based in a brand-new facility, purpose-built to meet the learning, teaching and study needs of students from the Department. Year 1 begins with a broad-based introduction to pure and applied mathematics, statistics and probability and provides a sound foundation for in-depth study in subsequent years. As you move into the second year the focus on statistics increases. During the final year you complete either the individual project in which you tackle a theoretical area or an applied problem in depth. Alternatively, the internship project is a statistics and machine learning piece of work based on a third-party problem. Both projects can be carried out in collaboration with external organisations to add valuable real-world context to your degree. You can also apply to add a placement year or a year abroad to your degree, increasing the course from three years to four. Year 1 The first year consists of 100 compulsory Mathematics credits:
- Analysis (20)
- Calculus (20)
- Linear Algebra (20)
- Dynamics (10)
- Probability (10)
- Programming (10)
- Statistics (10)
- Discrete Mathematics (20)
- Any other available Sciences, Arts and Social Sciences modules (subject to pre-requisites and timetabling compatibility)
- Analysis in Many Variables (20)
- Statistical Inference (20)
- Data Science and Statistical Computing (10)
- Statistical Modelling (10)
- Advanced Statistical Modelling (20)
- Bayesian Computation and Modelling (20)
- Decision Theory (20)
- Machine Learning and Neural Networks (20)
- Mathematical Finance (20)
- Stochastic Processes (20).
Modules
Year 1 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 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. Examples of optional modules: Algebra Complex Analysis Mathematical Physics Numerical Analysis Elementary Number Theory Geometric Topology Markov Chains Mathematical Modelling Probability Special Relativity and Electromagnetism. Year 3 (Year 4 if undertaking a placement year or year abroad) Core module: 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. Examples of optional modules: Advanced Statistical Modelling Bayesian Computation and Modelling Decision Theory Machine Learning and Neural Networks Mathematical Finance Stochastic Processes.
Assessment method
We use a combination of methods to assess the different modules, which 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.
How to apply
31Jan
This is the deadline for applications to be completed and sent for this course. If the university or college still has places available you can apply after this date, but your application is not guaranteed to be considered.
Application codes
- Course code:
- G111
- Institution code:
- D86
- Campus name:
- Durham City
- Campus code:
- O
Points of entry
The following entry points are available for this course:
- Year 1
Entry requirements
Qualification requirements
UCAS Tariff - Not accepted
A level - A*A*A
Pearson BTEC Level 3 National Extended Diploma (first teaching from September 2016) - D*D*D
Access to HE Diploma
Scottish Higher
Scottish Advanced Higher - AAA
International Baccalaureate Diploma Programme - 38 points
Welsh Baccalaureate - Advanced Skills Challenge Certificate (first teaching September 2015) - Not accepted
Extended Project - Not accepted
Leaving Certificate - Higher Level (Ireland) (first awarded in 2017) - H1, H1, H2, H2, H2
Cambridge International Pre-U Certificate - Principal - D2, D2, D3
OCR Cambridge Technical Extended Diploma - D*DD - DDD
T Level
Contextual Offers: Our contextual offer for this programme is A level A*AB including A*A in Mathematics and Further Mathematics in any order or A*A*C including A*A* in Mathematics and Further Mathematics (or equivalent). To find out if you’re eligible, please visit: https://www.durham.ac.uk/study/undergraduate/how-to-apply/what-happens-to-your-application/contextual-offers/ TMUA: https://studyatdurham.microsoftcrmportals.com/en-US/knowledgebase/article/KA-02546 MAT: https://studyatdurham.microsoftcrmportals.com/en-US/knowledgebase/article/KA-02544 STEP: https://studyatdurham.microsoftcrmportals.com/en-US/knowledgebase/article/KA-02545
Please click the following link to find out more about qualification requirements for this course
English language requirements
Durham University welcomes applications from all students irrespective of background. We encourage the recruitment of academically well-qualified and highly motivated students, who are non-native speakers of English, whose full potential can be realised with a limited amount of English Language training either prior to entry or through pre-sessional and/or in-sessional courses. It is the normal expectation that candidates for admission should be able to demonstrate satisfactory English proficiency before the start of a programme of study, whether via the submission of an appropriate English language qualification or by attendance on an appropriate pre-sessional course. Acceptable evidence and levels required can be viewed by following the link provided.
English language requirements
https://www.durham.ac.uk/study/international/entry-requirements/english-language-requirements/
Student Outcomes
Operated by the Office for Students
Employment after 15 months (Most common jobs)
Go onto work and study
The number of student respondents and response rates can be important in interpreting the data – it is important to note your experience may be different from theirs. This data will be based on the subject area rather than the specific course. Read more about this data on the Discover Uni website.
Fees and funding
Tuition fees
| Republic of Ireland | £9250 | Year 1 |
| Channel Islands | £9250 | Year 1 |
| EU | £27000 | Year 1 |
| England | £9250 | Year 1 |
| Northern Ireland | £9250 | Year 1 |
| Scotland | £9250 | Year 1 |
| Wales | £9250 | Year 1 |
| International | £27000 | Year 1 |
Additional fee information
There may also be additional course costs for things like books (if you want to purchase them), field trips etc.
Provider information
Durham University
The Palatine Centre
Stockton Road
Durham
DH1 3LE