About the course
The Postgraduate Diploma in Statistical Science is a nine-month taught course, running from October each academic year. It is similar to the MSc in Statistical Science but there is no dissertation. The course has a particular focus on modern computationally-intensive theory and methods.
The PGDip aims 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.
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.
You will be assessed on your performance in two written examinations around May, and through your submitted reports in assessed practical problems set during the year.
The Department of Statistics has made some changes to the content and delivery of the course and the revised programme ran for the first time in 2016-17. There is now more emphasis on computational statistics and statistical machine learning, more opportunity for students to take courses from the MMath in Mathematics and Statistics degree, and enhanced class support. The assessment structure remains the same as in previous years. The course is now known as the PGDip in Statistical Science (previously the PGDip in Applied Statistics) to better reflect its content.
Students take four, or exceptionally five, courses each term. Three courses each term are core courses and students must complete the practical sessions in these courses.
The options available will vary from year to year. The core courses available each year may also vary. In 2017-18 the core courses are:
- Applied Statistics
- Foundations of Statistical Inference
- Statistical Programming
- Computational Statistics
- Statistical Machine Learning
- Bayes Methods.
In 2017-18 the options are:
- Stochastic Models in Mathematical Genetics
- Probability and Statistics for Network Analysis
- Graphical Models
- Advanced Topics in Statistical Machine Learning
- Advanced Simulation Methods
- Actuarial Science.
Graduates find employment in financial, economic, governmental, scientific and industrial areas.
Changes to the course
The University will seek to deliver this course in accordance with the description set out in this course page. However, there may be situations in which it is desirable or necessary for the University to make changes in course provision, either before or after registration. For further information, please see our page on changes to courses.
Entry requirements for entry in 2018-19
Within equal opportunities principles and legislation, applications will be assessed in the light of an applicant’s ability to meet the following entry requirements:
1. Academic ability
Proven and potential academic excellence
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 a degree course with advanced mathematical and statistical content.
However, entrance to the course is very competitive and most successful applicants have a first-class degree or the equivalent.
For applicants with a degree from the USA, the minimum GPA sought is 3.6 out of 4.0.
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.
Other appropriate indicators will include:
You will be required to supply supporting documents with your application, including references and an official transcript. See 'How to apply' for instructions on the documents you will need and how these will be assessed.
Performance at interview(s)
Interviews are not normally held as part of the admissions process.
When held, interviews may be in person, or by telephone or by Skype, normally with two interviewers. Interviews are used only when the department needs to gather more information to fully assess an application before deciding whether to make an offer of a place.
Publications are not required.
2. English language requirement
Applicants whose first language is not English are usually required to provide evidence of proficiency in English at the higher level required by the University.
3. Availability of supervision, teaching, facilities and places
The following factors will govern whether candidates can be offered places:
- The ability of the Department of Statistics to provide the appropriate supervision, research opportunities, teaching and facilities for your chosen area of work.
- Minimum and maximum limits to the numbers of students who may be admitted to Oxford's research and taught programmes.
The provision of supervision, where required, is subject to the following points:
- The allocation of graduate supervision 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.
- Under exceptional circumstances a supervisor may be found outside the Department of Statistics.
Where possible your academic supervisor will not change for the duration of your course. However, it may be necessary to assign a new academic supervisor during the course of study or before registration for reasons which might include sabbatical leave, maternity leave or change in employment.
4. Disability, health conditions and specific learning difficulties
Students are selected for admission without regard to gender, marital or civil partnership status, disability, race, nationality, ethnic origin, religion or belief, sexual orientation, age or social background.
Decisions on admission are based solely on the individual academic merits of each candidate and the application of the entry requirements appropriate to the course.
Further information on how these matters are supported during the admissions process is available in our guidance for applicants with disabilities.
All recommendations to admit a student involve the judgment of at least two members of academic staff with relevant experience and expertise, and additionally must be approved by the Director of Graduate Studies or Admissions Committee (or equivalent departmental persons or bodies).
Admissions panels or committees will always include at least one member of academic staff who has undertaken appropriate training.
6. Other information
Whether you have yet secured funding is not taken into consideration in the decision to make an initial offer of a place, but please note that the initial offer of a place will not be confirmed until you have completed a Financial Declaration.
This is an exciting time for the Department of Statistics. In 2016, the department moved to occupy a newly-refurbished building in the centre of Oxford.
The principal computing resource for the Postgraduate Diploma in Statistical Science is the IT teaching suite. You will be able to use this to run software packages such as R, MATLAB and Python, as well as to prepare documents and reports. The IT teaching suite provides students with an excellent environment for training in computational statistics and statistical programming, as well as being a quiet place to work outside lectures. The building has other newly refurbished spaces for study and collaborative learning, including the library and the large open social area, both on the ground floor.
You will also have access to the Radcliffe Science Library and other University libraries, and the centrally-provided electronic resources.
There are over 1,100 full graduate scholarships available across the University, and these cover your course and college fees and provide a grant for living costs. If you apply by the relevant January deadline and fulfil the eligibility criteria you will be automatically considered. Over two thirds of Oxford scholarships require nothing more than the standard course application. Use the Fees, funding and scholarship search to find out which scholarships you are eligible for and if they require an additional application, full details of which are provided.
For students applying to programmes within the MPLS Division at Oxford, Research Council and other funding opportunities available, subject to eligibility. These opportunities are included in the Fees, funding and scholarship search.
Annual fees for entry in 2018-19
Total annual fees
The fees shown above are the annual tuition and college fees for this course for entry in the stated academic year; for courses lasting longer than one year, please be aware that fees will usually increase annually. For details, please see our guidance on likely increases to fees and charges.
Tuition and college fees are payable each year for the duration of your fee liability (your fee liability is the length of time for which you are required to pay tuition and college fees).
For more information about tuition fees, college fees and fee liability, please see the Fees section of this website. EU applicants should refer to our dedicated webpage for details of the implications of the UK’s plans to leave the European Union.
There are no compulsory elements of this course that entail additional costs beyond fees and living costs. However, as part of your course requirements, you may need to choose a dissertation, a project or a thesis topic. Please note that, depending on your choice of topic and the research required to complete it, you may incur additional expenses, such as travel expenses, research expenses, and field trips. You will need to meet these additional costs, although you may be able to apply for small grants from your department and/or college to help you cover some of these expenses.
In addition to your tuition and college fees, you will need to ensure that you have adequate funds to support your living costs for the duration of your course.
For the 2018-19 academic year, the range of likely living costs is between c. £1,015 and £1,555 for each month spent in Oxford. Full information, including a breakdown of likely living costs in Oxford for items such as food, accommodation and study costs, is available on our Living costs page.
How to apply
You are not expected to make contact with an academic member of staff before you apply.
The set of documents you should send with your application to this course comprises the following:
Your transcripts should give detailed information of the individual grades received in your university-level qualifications to date. You should only upload official documents issued by your institution and any transcript not in English should be accompanied by a certified translation.
More information about the transcript requirement is available in the Application Guide.
A CV/résumé is compulsory for all applications. Most applicants choose to submit a document of one to two pages highlighting their academic achievements and any relevant professional experience.
Up to two pages
Your statement should be written in English and should give your reasons for applying. In particular you should explain why you are interested in studying applied statistics, computational statistics and statistical methodology. The statement should summarise your background as it relates to applying for the PGDip in Statistical Science.
This will be assessed for:
- evidence of motivation for and understanding of the proposed area of study
- your reasons for applying.
References/letters of recommendation:
Three overall, generally academic
Whilst you must register three referees, the department may start the assessment of your application if two of the three references are submitted by the course deadline and your application is otherwise complete. Please note that you may still be required to ensure your third referee supplies a reference for consideration.
Academic references are strongly encouraged, though a professional reference is acceptable in the exceptional case that the referee is able to offer comparable information on your background and suitability for the course to an academic referee.
Your references will support intellectual ability, academic achievement, motivation and commitment.