MSc in EBHC Medical Statistics
This is a course for health professionals who wish to strengthen their statistical skills and ability to analyse data. Students will gain the confidence in carrying out the methods that are widely used in medical statistics, and interpreting the results for the practice of evidence-based health care.
The Programme is delivered in partnership with Oxford's Nuffield Department of Primary Care Health Sciences, one of the world's most important academic centres for primary care, and leaders in world-class research and training for over 20 years. It is also supported by the Centre for Evidence-Based Medicine. Find out more about the history of the centre and the Evidence-Based Health Care Programme here.
This course is designed for doctors, nurses, pharmacists, midwives and other healthcare professionals, seeking to consolidate their understanding and ability in medical statistics. Core modules introduce the students to methods for observational and clinical trials research. Optional modules offer the students skills in growth areas such as systematic review, meta-analysis, and big data epidemiology, or specialist areas such as statistical computing, diagnosis and screening research and others. Teaching is tailored to non-statisticians and delivered by an experienced team of tutors from University of Oxford who bridge the disciplines of medical statistics and evidence-based health care.
This programme guides students through core and optional modules and a dissertation to a qualification in the application of medical statistics to evidence-based health care. Compared to the main EBHC programme, this will suit those with basic statistical understanding who seek training who now seek deeper understanding on a broader base of statistical methods.
Watch the following video for more information about the course:
Our Student Spotlights feature students' experiences both on and after their courses, and highlight the day-to-day life of study on the Evidence-Based Healthcare programmes.
- Programme details
- Course aims
- Oxford college affiliation
- Who should apply
- Fees and funding
- When to apply
- How to apply and contact details
The MSc in EBHC Medical Statistics is a part-time course.
There are two compulsory modules, four option modules (two must be from group 1 and then either one from group 1 and one from group 2, or two more from group 2) and a dissertation.
Optional modules in Medical Statistics (group 1)
- Big Data Epidemiology
- Statistical Computing for Health Care Research
- Clinical Prediction Rules
Optional modules in EBHC (group 2)
- Introduction to Study Design and Research Methods
- Systematic Reviews or Complex Reviews
- Evidence-based Diagnosis and Screening
The majority of modules are run over either an eight, or fifteen-week learning cycle. Most modules are either delivered fully online or in a blended format, however, some modules are only delivered with a blended format that includes a 5-day attendance in Oxford, and some are only run entirely online. In any given year, not all delivery formats for a module may be available.
Blended format: an initial period of self-directed study is spent on introductory activities using a Virtual Learning Environment (VLE). This is followed by a week spent in Oxford for supported face-to-face teaching, and then a further period of Post-Oxford activities (a mixture of self-directed and supported distance learning also delivered through the VLE). The final week of each module is for self-directed personal study, shortly followed by the assignment submission.
Fully online format: These are delivered through the VLE with the first week allocated to self-directed introductory activities. There is then either:
- a number of units to work through which are released week by week. Each unit includes a mixture of supported and self-directed learning with discussion forums, tasks and activities. Students then have five weeks of self-directed personal study with use of a revision forum and the requirement to submit an assignment electronically the following week. Courses usually run over a 15-week period.
- an intensive week of 5 consecutive days of synchronous and asynchronous teaching sessions, and then a further period of activities (A mixture of self-directed and supported distance learning also delivered through the VLE). The final week of each module is for self-directed personal study, shortly followed by the assignment submission. Courses usually run over an 8-week period.
Part-time attendance details
As a part-time student, you will be required to attend a minimum of two modules (one of which must be a compulsory module) ‘in person’ in Oxford. Each ‘in person’ module requires you to attend a week (five days) in Oxford for supported face-to-face teaching. Your other four modules can be made up of a mix of ‘in-person’, or fully online modules. For additional note: All students are required to attend a minimum of one module in each academic year on course. This can either be ‘in person’ or fully online.
Assessment for each module will be based on a written assignment, which shall not be of more than 4,000 words. Students for the MSc will also be required to complete a dissertation on a topic chosen in consultation with a supervisor and the Course Director. The dissertation should not normally exceed 15,000 words.
To complete the MSc students must:
- Attend and complete 2 compulsory and 4 option modules
- Complete a dissertation on a topic chosen in consultation with a supervisor and the Course Director. The dissertation should normally not exceed 15,000 words.
- Attend a viva voce examination at the end of the course of studies at the discretion of the examiners
The course aims to give healthcare professionals high competence in the concepts, methods, terminology and interpretation of medical statistics; and hence, enhance their ability to carry out their own research and to interpret published evidence.
- Gain competence in execution and interpretation of core statistical techniques used by medical statisticians (outside the context of clinical trials), particularly those used in multivariable analyses: multiple linear regression, logistic regression, and survival modelling; statistical analysis plans and statistical reporting.
- Gain competence in execution and interpretation of core statistical techniques used by medical statisticians in clinical trials.
- Gain competence in execution and interpretation of four other areas, selected by the student from the following options: meta-analysis; systematic review; big data epidemiology; statistical computing; diagnosis and screening; study design and research methods.
- Gain hands-on experience, supervised by a senior member of our medical statistics team, of the analysis or meta-analysis of healthcare data, in order to address a question in evidence-based health care.
Oxford college affiliation
As a matriculated postgraduate degree student, you will become a member of one of the University’s famous interdisciplinary colleges, enabling you to encounter new perspectives in your field or learn more about many other different subjects from fellow college members.
The collegiate system makes studying at Oxford a truly special experience. Oxford colleges are small, intimate communities, where you could find yourself absorbed in fascinating conversations with students and academics from a variety of disciplines at college seminars, dinners, and informal occasions.
To find out more about Oxford University colleges, please consult the University's Graduate Admissions website.
Who should apply
To be eligible for the course you should:
- be a graduate or have successfully completed a professional training course
- have professional work experience in the health service or a health-related field
- be able to combine intensive classroom learning with the application of the principles and practices of evidence-based health care within the work place
- have a good working knowledge of email, internet, word processing and Windows applications (for communications with course members, course team and administration)
- show evidence of the ability to commit time to study and an employer's commitment to make time available to study, complete course work and attend course and university events and modules.
Applicants for the MSc in Evidence-Based Health Care (Medical Statistics) are also required to meet the following additional entry requirements:
- competence in basic statistics: concepts of p-values, confidence intervals, hypothesis tests;
- a high level of computer literacy. Programming experience is not required but readiness to learn to use statistics packages through command line rather than mouse-and-menu interface is essential.
For the full Selection Criteria please refer to the Graduate Admissions and Funding website.
Fees and funding
Fee rates for the academic year 2023-24*
*Rates for 2024/25 to be confirmed
These rates (in pounds sterling) are for students joining in the 2023-24 academic year and will increase annually.
The annual award fee is due for every academic year (or part-year) attended; module or dissertation fees are due in advance as invoiced. Fees must be paid in accordance with the Terms and Conditions for the programme.
- Annual award fee: £7,695
- Module fees: £2,340 (per taught module)
- Dissertation fee: £7,020 (equivalent to 3 module fees)
Illustration for full programme (completing in three years, with six taught modules and a dissertation):
- 3 annual award fees: £23,085*
- plus 6 module fees: £14,040*
- plus dissertation fee: £7,020*
- The fee rates listed are for the academic year shown, and you should be aware that these rates will increase annually.
- The Illustration is based on the fee rates for the academic year shown; however, fee rates for attendance in future years will increase, so students attending for more than one year should expect the total to be higher than is shown in the Illustration. The exact amount will depend on the fee rates set annually, and upon the years you are in attendance; these are normally published well before the start of each academic year, but for your own budgetary purposes you may wish to estimate a 8% annual increase on fee rates.
- Funding: Eligible applications completed before the January deadline will automatically be considered for a Clarendon Fund Scholarship.
Details of funding opportunities, including grants, bursaries, loans, scholarships and benefit information are available on our Fees and Funding page.
When to apply
We strongly recommend that you apply by the January or March deadlines. After the March deadline, the course will only stay open for that year's entry if places are still available.
Remember that it can take a number of weeks to obtain all of the documents you need and prepare a competitive application. You should also allow your referees plenty of time to submit your references. We therefore recommend you apply as soon as possible.
How to apply
Applications for this course should be made via the University of Oxford Graduate Admissions website. This website includes further information about this course and a guide to applying.
Early application for the programme is advised. Applications which have not been fully completed before the application deadline cannot be considered, so please ensure any applications are received by us in good time so that we may advise of missing or incorrectly completed elements. Shortlisted applicants will be invited to telephone interview, and asked to provide evidence of their funding for the programme.
Applications open on 1st September 2022 for entry in October 2023. To see if this course is still open for applications for admission please visit the University of Oxford Graduate Admissions website. Courses with a green admission status are open for applications, amber means the course will be closing at 12 noon on the following Friday and red means it has closed to new applications.
For further information on applying, please refer to the Application Guide. Please read our Terms and Conditions before submitting your application. If you would like to discuss your application or any part of the application process before applying please contact:
Frazer Mackenzie (Course Manager)
Tel: +44 (0)1865 270453 - Email: email@example.com