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The University of Sheffield

Sheffield , England ,United Kingdom

MSc Statistics with Financial Mathematics

Course description

Accredited by the Royal Statistical Society

The course is about applying probabilistic, statistical and mathematical techniques in the finance industry. Graduates with skills in these areas are in demand. It’s based on the MSc Statistics with additional training in the concepts, models and tools of modern mathematical finance.

Campus Information

Main (Western Bank) campus

The University of Sheffield is not a campus university, though most of its buildings are located in fairly close proximity to each other. The centre of the University's presence lies one mile to the west of Sheffield city centre, where there is a mile-long collection of buildings belonging almost entirely to the University.


  • Sep

Application Processing Time in Days: 30

Application Process

More Information Required
30 Days
Possible Interview Call from Institution
10 Days
Provisional/Unconditional Offer
10 Days
Visa Process
35 Days

Minimum English Language Requirements

English Level Description IELTS (1.0 -9.0) TOEFL IBT (0-120) TOEFL CBT (0-300) PTE (10-90)
Expert 9 120 297-300 86-90
Very Good 8.5 115-119 280-293 83-86
Very Good 8 110-114 270-280 79-83
Good 7.5 102-109 253-267 73-79
Good 7 94-101 240-253 65-73
Competent 6.5 79-93 213-233 58-65
Competent 6 60-78 170-210 50-58
Modest 5.5 46-59 133-210 43-50
Modest 5 35-45 107-133 36-43
Limited 4 32-34 97-103 30-36
Extremely Limited < 4 < 31 < 93 < 30

PSW Opportunity

  • Post Study Work Permit of 2 years

Admission Requirement / Eligibility Criteria

We ask for a 2:1 honours degree, or equivalent, with substantial mathematical and statistical components. In particular, you should have studied the following topics and performed well in assessments on them (for example, a score of at least 60 per cent).

  • Mathematical Methods for Statistics: ideas and techniques from real analysis and linear algebra, including multiple integration, differentiation, matrix algebra, the theory of quadratic forms.
  • Probability and Probability Distributions: the laws of probability and of conditional probability, the concepts of random variables and random vectors and their distributions, the methodology for calculating with them; laws of large numbers and central limit phenomena.
  • Basic Statistics: statistical inference, rational decision-making under uncertainty, and how they may be applied in a wide range of practical circumstances; relevant software, for example, R.