Program Overview

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MSc in Statistical Science

The MSc in Statistical Science is a taught course offering advanced training in statistical inference, machine learning, and computational methods, with a final dissertation based on independent research.

About the Course

The MSc in Statistical Science will aim to train you to solve real-world statistical problems. When completing the course, you should be able to choose an appropriate statistical method to solve a given problem of data analysis, implement the analysis on a computer and communicate your results clearly and succinctly.

Course Structure

An overview of the course structure is provided below. Details of the compulsory and optional elements of the course are provided in the Course components section.

• The MSc offers a broad high-level training in applied and computational statistics, statistical machine learning, and the fundamental principles of statistical inference.
• Training is delivered through mathematically demanding lectures and problems classes, hands-on practical sessions in the computer laboratory, report writing and dissertation supervision.
• You will have around three months to work on your dissertation with guidance from your supervisor, offering you a substantial opportunity for self-directed study and research.
• You will take a mixture of core courses and optional courses. The core courses are compulsory and involve practical components that students must complete.
• The core and option modules may vary from year to year.

Attendance

The course is full-time and requires attendance in Oxford. Full-time students are subject to the University's Residence requirements.

• You will attend nine units worth of courses (with one unit corresponding to a 16-hour lecture course or equivalent) in addition to writing a dissertation.
• Depending on how the courses you take split between terms, you can expect to attend four or five (or, in exceptional cases, three or six) courses per term.
• Most courses have one-hour lectures per week supplemented by four classes (or the equivalent) per term, though for some courses there are associated practical sessions instead of, or in addition to, lectures or classes.

Resources to Support Your Study

As a graduate student, you will have access to the University's wide range of resources including libraries, museums, galleries, digital resources and IT services.

• The Bodleian Libraries is the largest library system in the UK. It includes the main Bodleian Library and libraries across Oxford, including major research libraries and faculty, department and institute libraries.
• The University's IT Services is available to all students to support with core university IT systems and tools, as well as many other services and facilities.
• The principal computing resource for the MSc in Statistical Science is the IT teaching suite in the department of Statistics.

Supervision

Students are allocated a departmental supervisor and will typically meet with their supervisor up to four times a term, usually in groups. This supervision is limited as the course is mostly taught through lectures and classes.

• Students are also allocated a dissertation supervisor and will typically meet with their dissertation supervisor up to six times during the course of the project.
• The allocation of graduate supervision for this course is the responsibility of the Department of Statistics and it is not always possible to accommodate the preferences of incoming graduate students to work with a particular member of staff.

Assessment

You will be assessed on your performance in a number of written examinations in May/June, through practical coursework set during the year, and by the quality and depth of your dissertation (done mostly over the period June to early September).

Graduate Destinations

Graduates of the MSc find employment in financial, economic, governmental, scientific and industrial areas. The MSc can also be a useful stepping stone for doctoral studies, with around a third of students on the course taking this route.

Course Components

Compulsory Study

Core Courses

The core courses for entry in are:

• Applied Statistics
• Foundations of Statistical Inference
• Statistical Programming
• Computational Statistics
• Statistical Machine Learning You will be required to take all of the core courses.

Dissertation

The dissertation is undertaken under the guidance of a supervisor and will typically involve investigating and writing in a particular area of statistical science, without the requirement (while not excluding the possibility) of obtaining original results.

Options

To provide an indication of the optional courses that are typically offered, the following were available to students admitted for entry in:

• Stochastic Models in Mathematical Genetics
• Probability and Statistics for Network Analysis
• Advanced Topics in Statistical Machine Learning
• Advanced Simulation Methods
• Graphical Models
• Bayes Methods
• Algorithmic Foundations of Learning
• Climate Statistics

Entry Requirements

Proven and Potential Academic Excellence

The requirements described below are specific to this course and apply only in the year of entry that is shown.

• As a minimum, applicants should hold or be predicted to achieve the following UK qualifications or their equivalent:
  • a first-class undergraduate degree with honours in a degree course with advanced mathematical and statistical content
• For applicants with a degree from the USA, the minimum overall GPA that is normally required to meet the undergraduate-level requirement is 3.7 out of 4.0

English Language Proficiency

This course requires proficiency in English at the University's higher level. If your first language is not English, you may need to provide evidence that you meet this requirement.

• The minimum scores required to meet the University's higher level are detailed in the table below:
  • IELTS Academic: 7.5
  • TOEFL iBT: 110
  • C1 Advanced: 191
  • C2 Proficiency: 191
  • Oxford Test of English Advanced: 165

Funding

For entry in the academic year, the collegiate University expects to offer over 1,100 full or partial graduate scholarships across a wide range of graduate courses.

• If you apply by the January deadline shown on this page and receive a course offer, your application will then be considered for Oxford scholarships
• Most scholarships are awarded on the basis of academic merit and/or potential

Costs

Annual Course Fees

The fees for this course are charged on an annual basis.

• Home: Ł18,970
• Overseas: Ł43,730

Additional Costs

There are no compulsory elements of this course that entail additional costs beyond fees and living costs.

Living Costs

In addition to your course fees and any additional course-specific costs, you will need to ensure that you have adequate funds to support your living costs for the duration of your course.

• The range of likely living costs for a single, full-time student is between Ł1,405 and Ł2,105 for each month spent in Oxford

College Preference

Students enrolled on this course will belong to both a department/faculty and a college.

• The following colleges accept students on the MSc in Statistical Science:
  • Brasenose College
  • Christ Church
  • Corpus Christi College
  • Exeter College
  • Green Templeton College
  • Jesus College
  • Keble College
  • Kellogg College
  • Lady Margaret Hall
  • Linacre College
  • Lincoln College
  • Magdalen College
  • Mansfield College
  • New College
  • Oriel College
  • Reuben College
  • St Anne's College
  • St Catherine's College
  • St Cross College
  • St Edmund Hall
  • St Hugh's College
  • St Peter's College
  • Somerville College
  • University College
  • Wadham College
  • Wolfson College
  • Worcester College
  • Wycliffe Hall

How to Apply

Our guide to getting started provides general advice on how to prepare for and start your application.

• You can start or return to an application using the relevant link below
• As you complete the form, please refer to the requirements above and consult our Application Guide for advice

Application Fee Waivers

An application fee of Ł75 is payable for each application to this course.

• Application fee waivers are available for the following applicants who meet the eligibility criteria:
  • applicants from low-income countries
  • refugees and displaced persons
  • UK applicants from low-income backgrounds
  • applicants who applied for our Graduate Access Programmes in the past two years and met the eligibility criteria

Completing Your Application

You should refer to the information below when completing the application form, paying attention to the specific requirements for the supporting documents.

• Three overall referees, at least two of which must be academic
• Official transcript(s)
• CV/résumé
• Personal statement: A maximum of 1,000 words

After You've Submitted Your Application

Your application (including the supporting documents outlined above) will be assessed against the entry requirements detailed on this course page.

• You can find out more about our shortlisting and selection process in our detailed guide to what happens next
• Find out how to manage your application after submission, using our Applicant Self-Service tool

Admission Status

Open to applications for entry in

Deadlines

12:00 midday UK time on:

• Friday 14 November 2025: Applications more likely to receive earlier decisions
• Wednesday 28 January 2026: Latest deadline for most Oxford scholarships, Final application deadline for entry in

Key Facts

• Course code: TM_SA2
• Expected length: 12 months
• Places in: c. 60
• Applications/year: 599
• Expected start: 5 October 2026
• English language: Higher level required