Program Overview

---

Introduction to the Postgraduate Diploma in Statistical Science

The Postgraduate Diploma in Statistical Science (PGDip) is a taught course offering intensive training in applied statistics, statistical inference, machine learning, and computational methods, without a dissertation. The PGDip aims to train students to solve real-world statistical problems.

Course Structure

The course 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, and report writing. Students take a mixture of core courses and optional courses. The core courses are compulsory and involve practical components that students must complete.

Attendance

The course is full-time and requires attendance in Oxford. Full-time students are subject to the University's Residence requirements. Students will attend nine units worth of courses, with one unit corresponding to a 16-hour lecture course or equivalent.

Resources to Support 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, and the University's IT Services is available to support students with core university IT systems and tools.

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.

Assessment

You will be assessed on your performance in a number of written examinations in May/June, and through practical coursework set during the year.

Graduate Destinations

Graduates find employment in financial, economic, governmental, scientific, and industrial areas.

Course Components

Compulsory Study

The core courses for entry are:

• Applied Statistics
• Foundations of Statistical Inference
• Statistical Programming
• Computational Statistics
• Statistical Machine Learning

Options

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

• 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. You can use the guidance to help evaluate whether your application is likely to be competitive.

Degree-Level Qualifications

As a minimum, applicants should hold or be predicted to achieve the following UK qualifications or their equivalent:

• A first-class undergraduate degree with honors in a degree course with advanced mathematical and statistical content.

Other Qualifications, Evidence of Excellence, and Relevant Experience

Successful applicants will be expected to have a good understanding of basic parts of mathematics, probability, and statistics.

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.

References

You will need to register three referees who can give an informed view of your academic ability and suitability for the course.

Supporting Documents

You will be required to supply supporting documents with your application.

Performance at Interview

Interviews are not normally held as part of the admissions process.

Funding and Costs

Annual Course Fees

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

Fees for the Academic Year

• Home: Ł17,910
• Overseas: Ł40,710

What Do Course Fees Cover?

Course fees cover your teaching, as well as other academic services and facilities provided to support your studies.

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.

College Preference

Students enrolled on this course will belong to both a department/faculty and a college. The following colleges accept students on the PGDip in Statistical Science:

• Hertford College
• Jesus College
• St Anne's College
• St Catherine's College
• St Peter's College
• Somerville College
• Worcester College
• Wycliffe Hall

How to Apply

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

Referees

Three overall, at least two of which must be academic.

Official Transcript(s)

Your transcripts should give detailed information of the individual grades received in your university-level qualifications to date.

CV/Résumé

A CV/résumé is compulsory for this course.

Personal Statement

A maximum of 1,000 words, explaining your motivation for applying for the course at Oxford and your relevant experience and education.

Admission Status and Deadlines

The course is open to applications for entry, with deadlines as follows:

• 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.