Queen Mary University of London | Open Day | 12 June 2026
12 Jun 2026, 09:00
London
Combine expertise in economics and advanced mathematical techniques to find solutions to real-world situations.
Fascinated by data? Interested in what’s going on in the world around you? This degree combines economics, statistics, and mathematics to prepare you for roles where you’ll apply quantitative techniques to real-world challenges.
The programme is jointly delivered by the School of Economics and Finance and the School of Mathematical Science, so you’ll learn from experts across both fields. Many of our teaching staff also have practical experience and work closely with industry organisations including HM Treasury, the Debt Management Office, and the Bank of England.
Analyse real-time data
Kick off your studies by exploring key areas in each subject, like macroeconomics and quantitative analysis. Then zone in on statistical methods, modelling and econometrics. With our extensive choice of optional modules, you can also explore hot topics in the sector such as cryptography, generative AI, or big data.
As well as theory, you’ll perfect your practical skills in our Bloomberg trading room. Here you’ll use the same kit used by industry practitioners. All of the skills you learn will be invaluable, whatever field of economics you decide to work in
YEAR 1
Personal and Career Development Plan 1
Applied Probability & Statistics
Macroeconomics 1
Mathematical Methods in Economics and Finance
Microeconomics 1
Principles of Economics
Sets, Functions and Numbers
Vectors and Matrices
Disclaimer
The programme structure shown is for prospective/new students and may vary for existing students.
Please note that all modules are subject to change.
Assessment typically includes a combination of coursework (presentations, assignments, essay report writing, in-class tests, research and project work) and/or examinations in January and May/June.
The following entry points are available for this course:
Queen Mary University of London: English Language Requirements https://www.qmul.ac.uk/international-students/englishlanguagerequirements/undergraduate-and-postgraduate-programmes/
Our Standard contextual offer: Grades ABB at A-Level (grade A in Mathematics required)
Our Enhanced contextual offer: Grades BBB at A-Level (including Mathematics)
Please note that General Studies and Critical Thinking are excluded from any A-Level offer and cannot be considered.
More information on our contextual offer criteria can be found on our contexualised admissions page below.
This section shows the range of grades students (with UK A-Levels or Pearson BTEC Level 3 National Extended Diplomas) who received offers were previously accepted with (learn more). It is designed to support your research but does not guarantee whether you will or won't get a place. Admissions teams consider various factors, including interviews, subject requirements, and entrance tests. Check all course entry requirements for eligibility.
We are unable to show previous accepted grades for this course. This could be because the course is new, it's a postgraduate course, there isn't enough historical data, or the provider has opted out of sharing their entry grades data for this course - learn more.
| Location | Fee | Year |
|---|---|---|
| England | £9535* | Year 1 |
| Northern Ireland | £9535* | Year 1 |
| Scotland | £9535* | Year 1 |
| Wales | £9535* | Year 1 |
* This is a provisional fee and subject to change.
Tuition fee status depends on a number of criteria and varies according to where in the UK you will study. For further guidance on the criteria for home or overseas tuition fees, please refer to the UKCISA website.
Please visit and search for your chosen course on our A-Z course finder at http://search.qmul.ac.uk/s/search.html?collection=queenmary-coursefinder-undergraduate&query=&sort=title - here you will find further details on fees and funding.
Please also visit our A-Z course finder to view the amount of fee you would need to pay if you are an International fee paying student.
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Email:admissions@qmul.ac.uk
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