Statistics

The Oxford Degree in Statistics offers an outstanding opportunity for students to develop a comprehensive understanding of statistical theory, methodology, and application. Designed for individuals with a strong background in mathematics and an interest in data analysis, this program provides rigorous training in both classical and modern statistical techniques. Students will explore a wide range of topics, including probability theory, statistical inference, regression analysis, experimental design, Bayesian methods, and machine learning. The curriculum combines intensive coursework, practical data analysis projects, and independent research, allowing students to apply statistical methods to real-world problems across various disciplines such as medicine, economics, social sciences, and natural sciences.

At Oxford, students benefit from close interactions with leading experts in the field, access to cutting-edge research facilities, and participation in a vibrant academic community. The program emphasizes both theoretical understanding and practical skills, preparing graduates for careers in academia, industry, government agencies, or as data scientists. Throughout their studies, students will engage with a diverse array of software tools and programming languages, including R and Python, to perform complex data analyses efficiently.

The degree typically spans one year for full-time students, with part-time options available for working professionals. Admission requirements include a strong foundation in mathematics, demonstrated through prior coursework or examinations, along with a keen interest in statistical research. Successful students will graduate with a high level of expertise in statistical reasoning and a versatile skill set that is highly valued in today’s data-driven world. Joining this program at Oxford not only provides a gateway to advanced statistical knowledge but also offers an enriching experience within one of the world’s leading academic institutions.

You will be assigned a named supervisor or supervisors, who will have overall responsibility for the direction of your work on behalf of the department. You will have the opportunity to interact with fellow students and other members of your research groups, and more widely across the department. Typically, as a research student, you should expect to have meetings with your supervisor or a member of the supervisory team with a frequency of at least once every two weeks averaged across the year. The regularity of these meetings may be subject to variations according to the time of the year, and the stage that you are at in your research programme.

There are formal assessments of progress on the research project at around 12 to 15 months and at around 30 to 36 months. These assessments involve the submission of written work and oral examination.

The final thesis is normally submitted for examination during the fourth year and is followed by the viva examination.  

You will be expected to acquire transferable skills as part of your training, and to undertake a total of 100 hours broadening training outside your specialist area. Part of that broadening training is obtained through APTS, the Academy for PhD Training in Statistics; this is a joint venture with a group of leading university statistics departments which runs four weeks of appropriate courses a year. You will give a research presentation or prepare a research poster each year in the department.

Applicants are normally expected to be predicted or have achieved a first-class or strong upper second-class undergraduate degree with honours (or equivalent international qualifications), as a minimum, in an appropriate subject. You will need a strong background in mathematics or statistics.

For applicants with a degree from the USA, the minimum GPA sought is 3.6 out of 4.0.

However, entrance is very competitive and most successful applicants have a first-class degree or the equivalent.

If you hold non-UK qualifications and wish to check how your qualifications match these requirements, you can contact the National Recognition Information Centre for the United Kingdom (UK NARIC).

No Graduate Record Examination (GRE) or GMAT scores are sought.

• Official transcript(s)
• CV/résumé
• Research proposal: Up to two pages
• References/letters of recommendation:Three overall, generally academic

ENGLISH LANGUAGE REQUIREMENTS

Higher level

The University of Oxford offers a range of financial support options for students enrolled in its Statistics programs. Funding opportunities typically include scholarships, grants, bursaries, and loans designed to assist both domestic and international students in financing their studies. For postgraduate students, the university provides various scholarships based on academic merit, financial need, and specific eligibility criteria such as nationality or field of study. These include prestigious awards like the Rhodes Scholarship, Clarendon Fund, and departmental-specific scholarships. Undergraduate students may benefit from government loans and bursaries, as well as Oxford-specific scholarships that do not need to be repaid. Additionally, external funding from governmental agencies, charitable foundations, and industry sponsors is often available for eligible students pursuing degrees in statistics and related fields. The university also offers work opportunities, such as Teaching Assistantships and research positions, which provide income and practical experience. Students are encouraged to explore the dedicated scholarship database on the Oxford website and contact the university's financial aid office for personalized guidance. Moreover, the university's flexible funding options aim to reduce financial barriers and enable talented students from diverse backgrounds to access top-tier education. In summary, Oxford’s financing studies encompass a comprehensive array of financial aid programs designed to support students throughout their academic journey, ensuring that lack of funds does not hinder access to its prestigious statistics programs.

The MSc in Mathematical and Computational Finance at the University of Oxford is a rigorous postgraduate degree designed to prepare students for careers in the financial industry, particularly in roles requiring advanced quantitative and computational skills. The program provides a comprehensive curriculum that combines theoretical mathematics, computational techniques, and practical applications in finance. Students examine topics such as stochastic calculus, financial derivatives, risk management, and numerical methods, equipping them with the essential tools to analyze and model complex financial systems.

The program emphasizes the integration of mathematical theory with computational practice, ensuring that graduates are capable of implementing sophisticated models using modern programming languages and software. Faculty members are leading experts in their fields, many of whom are actively involved in cutting-edge research and industry collaborations. This academic environment fosters an interdisciplinary approach, blending finance, mathematics, and computer science to address real-world problems in markets and investment strategies.

Students are expected to undertake a mixture of lectures, seminars, and practical workshops, alongside individual and group projects. These activities are designed to develop both theoretical understanding and applied skills, preparing graduates for roles such as quantitative analysts, risk managers, financial engineers, or data scientists in various financial institutions, hedge funds, or consulting firms.

The program duration is typically one year full-time, with some opportunities for part-time study. It is highly competitive, admitting students from diverse academic backgrounds, including mathematics, physics, engineering, and economics. The admissions process evaluates applicants based on their academic record, relevant experience, and motivation for pursuing advanced studies in finance.

Graduates of the MSc in Mathematical and Computational Finance have access to Oxford’s extensive alumni network and industry connections, which can facilitate internships, employment opportunities, and further research. The university’s reputation for academic excellence and its strategic location in the heart of London’s financial district enhance the program’s prestige and attractiveness to prospective students seeking a career in financial services and related sectors. Overall, the program aims to produce well-rounded, highly skilled professionals capable of contributing to innovation and advancement in the field of finance through rigorous analysis and computational expertise.