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Statistics with Finance MSc

Key information

Qualification type

MSc - Master of Science

Subject areas

Statistics Finance / Accounting (General)

Course type


Course Summary

This course is accredited by the Royal Statistical Society (RSS) and is excellent preparation for careers in any field requiring a strong statistical background. This programme trains students for careers using statistics in the financial services industry. You study the statistical modelling underpinning much modern financial engineering combined with a deep understanding of core statistical concepts. The programme includes modelling of financial time series, risk and multivariate techniques. Statistics at Kent provides: a programme that gives you the opportunity to develop practical, mathematical and computing skills in statistics, while working on challenging and important problems relevant to a broad range of potential employers; teaching and supervision by staff who are research-active, with established reputations and who are accessible, supportive and genuinely interested in your work; advanced and accessible computing and other facilities; a congenial work atmosphere with pleasant surroundings, where you can socialise and discuss issues with a community of other students.

Students often go into careers as professional statisticians in industry, government, research and teaching but our programmes also prepare you for careers in other fields requiring a strong statistical background. You have the opportunity to attend careers talks from professional statisticians working in industry and to attend networking meetings with employers. Recent graduates have started careers in diverse areas such as the pharmaceutical industry, financial services and sports betting.

Different course options

Full time | Canterbury Campus | 1 year | SEP-19

Study mode

Full time


1 year

Start date



This course introduces (and revises for some students) the essentials of probability and inference which provide the backbone for later modules. Syllabus: Probability: axioms, marginal, joint and conditional distributions, Bayes theorem, important distributions, generating functions and various models of convergence. Classical Inference: Sampling distributions. Point estimation: consistency, Cramer-Rao inequality, efficiency, sufficiency, minimum variance unbiased estimators. Likelihood. Methods of estimation. Hypothesis tests: maximum likelihood-ratio test, Wald and score tests, profile and test-based confidence intervals. Modified likelihood and estimating equations: marginal, conditional, pseudo- and quasi-likelihood, estimating equations.

Tuition fees

UK fees
Course fees for UK / EU students

For this course (per year)


Average for all Postgrad courses (per year)


International fees
Course fees for non-UK / EU students

For this course (per year)


Average for all Postgrad courses (per year)


Entry requirements

Students need to have a minimum of 2.2, with a substantial amount of mathematics at university level. Prior experience of finance is not required. All applicants are considered on an individual basis and additional qualifications, and professional qualifications and experience will also be taken into account when considering applications.