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Mathematics and Statistics (4 years)

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About this course


Course option

4years

Full-time | 2024

Subjects

Mathematics

Statistics

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.

The first year 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 and third year the focus on statistics increases.

During the final year you complete a double-module project. This can be 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.

**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)

Together with a further 20 credits.

The first-year Mathematics modules expand and develop topics that may be familiar from A level (or equivalent), smoothing the transition to university study. Fundamental statistical methodologies are developed from first principles in the Statistics and Probability modules, providing a mathematical language and coherent conceptual framework with which to structure subsequent developments. Other modules equip you with the essential mathematical tools needed for further study.

**Year 2**

In the second year, you will take four compulsory modules (60 credits):

-Analysis in Many Variables (20)

-Statistical Inference (20)

-Data Science and Statistical Computing (10)

-Statistical Modelling (10)

Together with a further 60 credits which can be chosen from a wide range.

The four compulsory modules will furnish you with the central mathematical, inferential, modelling, and computational tools needed for modern statistics and machine learning, as well as looking at important surrounding issues such as data governance. Further modules allow you to broaden or deepen your knowledge of particular topics or techniques.

**Year 3**

In the third year, you choose from a range of modules on topics central to modern statistics and machine.

**Year 4**

In the fourth year, you take a 40-credit capstone project module, tackling a theoretical area or an applied problem in particular depth. Subject to availability, this may be performed in collaboration with a company or other organisation. For the remaining 80 credits, you choose from a range of modules focusing on topics of current research interest.

**Placement Year**

You may be able to take a work placement. Find out more: https://www.dur.ac.uk/study/ug/studyoptions/

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
Examples of optional modules:
Advanced Statistical Modelling
Bayesian Computation and Modelling
Decision Theory
Machine Learning and Neural Networks
Mathematical Finance
Stochastic Processes.
Year 4
Core modules:
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.
Examples of optional modules:
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.

Assessment methods

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.

The Uni


Course locations:

College allocation pending

Durham City

Department:

Mathematical Sciences

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What students say


We've crunched the numbers to see if overall student satisfaction here is high, medium or low compared to students studying this subject(s) at other universities.

75%
Mathematics

How do students rate their degree experience?

The stats below relate to the general subject area/s at this university, not this specific course. We show this where there isn’t enough data about the course, or where this is the most detailed info available to us.

Mathematics

Teaching and learning

76%
Staff make the subject interesting
87%
Staff are good at explaining things
78%
Ideas and concepts are explored in-depth
66%
Opportunities to apply what I've learned

Assessment and feedback

Feedback on work has been timely
Feedback on work has been helpful
Staff are contactable when needed
Good advice available when making study choices

Resources and organisation

71%
Library resources
78%
IT resources
81%
Course specific equipment and facilities
76%
Course is well organised and has run smoothly

Student voice

Staff value students' opinions
Feel part of a community on my course

Who studies this subject and how do they get on?

91%
UK students
9%
International students
72%
Male students
28%
Female students
80%
2:1 or above
8%
First year drop out rate

Most popular A-Levels studied (and grade achieved)

A*
A*
A*

Statistics

Sorry, no information to show

This is usually because there were too few respondents in the data we receive to be able to provide results about the subject at this university.


Who studies this subject and how do they get on?

91%
UK students
9%
International students
72%
Male students
28%
Female students
80%
2:1 or above
8%
First year drop out rate

Most popular A-Levels studied (and grade achieved)

A*
A*
A*

After graduation


The stats in this section relate to the general subject area/s at this university – not this specific course. We show this where there isn't enough data about the course, or where this is the most detailed info available to us.

Mathematics

What are graduates doing after six months?

This is what graduates told us they were doing (and earning), shortly after completing their course. We've crunched the numbers to show you if these immediate prospects are high, medium or low, compared to those studying this subject/s at other universities.

£28,000
high
Average annual salary
96%
med
Employed or in further education
75%
med
Employed in a role where degree was essential or beneficial

Top job areas of graduates

42%
Business, research and administrative professionals
13%
Business, finance and related associate professionals
13%
Information technology and telecommunications professionals

Want to feel needed? This is one of the most flexible degrees of all and with so much of modern work being based on data, there are options everywhere for maths graduates. With all that training in handling figures, it's hardly surprising that a lot of maths graduates go into well-paid jobs in the IT or finance industries, and last year, a maths graduate in London could expect a very respectable average starting salary of £27k. And we're always short of teachers in maths, so that is an excellent option for anyone wanting to help the next generation. And if you want a research job, you'll want a doctorate — and a really good maths doctorate will get you all sorts of interest from academia and finance — and might secure some of the highest salaries going for new leavers from university.

Statistics

What are graduates doing after six months?

This is what graduates told us they were doing (and earning), shortly after completing their course. We've crunched the numbers to show you if these immediate prospects are high, medium or low, compared to those studying this subject/s at other universities.

£28,000
high
Average annual salary
96%
med
Employed or in further education

Top job areas of graduates

42%
Business, research and administrative professionals
13%
Business, finance and related associate professionals
13%
Information technology and telecommunications professionals

The business and research sectors worry that the UK hasn't got enough people with good statistics skills, and as stats are at the heart of so much of the economy, and we only have a few hundred graduates a year in the discipline, this type of degree can be very useful and versatile. The finance industry is very popular with this group, and they're far more likely to be working in London than most other graduates. And who can blame them — statistics graduates starting work in London were earning an average of nearly £29k just six months after leaving university. There is also demand from the Scottish finance sector in Edinburgh and Glasgow - particularly in banking and insurance. But a good statistician can find work almost anywhere that data can be analysed - which, in an online world, is almost anywhere - and many industries struggle to find enough statisticians to fulfil demand, so stay flexible and you can find a variety of options.

What about your long term prospects?

Looking further ahead, below is a rough guide for what graduates went on to earn.

Mathematics

The graph shows median earnings of graduates who achieved a degree in this subject area one, three and five years after graduating from here.

£27k

£27k

£36k

£36k

£45k

£45k

Note: this data only looks at employees (and not those who are self-employed or also studying) and covers a broad sample of graduates and the various paths they've taken, which might not always be a direct result of their degree.

Statistics

The graph shows median earnings of graduates who achieved a degree in this subject area one, three and five years after graduating from here.

£27k

£27k

£36k

£36k

£45k

£45k

Note: this data only looks at employees (and not those who are self-employed or also studying) and covers a broad sample of graduates and the various paths they've taken, which might not always be a direct result of their degree.

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UCAS Points: 160-168
Higher entry requirements
University of Leeds | Leeds
Mathematics and Statistics
MMath (Hons) 3 Years Full-time 2024
UCAS Points: 136-186

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This information comes from the National Student Survey, an annual student survey of final-year students. You can use this to see how satisfied students studying this subject area at this university, are (not the individual course).

This is the percentage of final-year students at this university who were "definitely" or "mostly" satisfied with their course. We've analysed this figure against other universities so you can see whether this is high, medium or low.

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This information is from the Higher Education Statistics Agency (HESA), for undergraduate students only.

You can use this to get an idea of who you might share a lecture with and how they progressed in this subject, here. It's also worth comparing typical A-level subjects and grades students achieved with the current course entry requirements; similarities or differences here could indicate how flexible (or not) a university might be.

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Post-six month graduation stats:

This is from the Destinations of Leavers from Higher Education Survey, based on responses from graduates who studied the same subject area here.

It offers a snapshot of what grads went on to do six months later, what they were earning on average, and whether they felt their degree helped them obtain a 'graduate role'. We calculate a mean rating to indicate if this is high, medium or low compared to other universities.

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Graduate field commentary:

The Higher Education Careers Services Unit have provided some further context for all graduates in this subject area, including details that numbers alone might not show

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The Longitudinal Educational Outcomes dataset combines HRMC earnings data with student records from the Higher Education Statistics Agency.

While there are lots of factors at play when it comes to your future earnings, use this as a rough timeline of what graduates in this subject area were earning on average one, three and five years later. Can you see a steady increase in salary, or did grads need some experience under their belt before seeing a nice bump up in their pay packet?

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