Statistical Computing for Health Care Research


Complement your statistical skills with expert methods in R

The course aims to give students confidence in a high-level professional statistics package in order to use advanced methods that complement the statistical techniques taught on our other modules. Students begin with essential programming skills and progress towards computer-intensive statistical methods such as simulation, bootstrap , optimisation and machine learning methods. Led by Dr Jason Oke, senior statistician in the NDPCHS statistics group, an experienced teaching team guide students from the basics to advanced topics in R. 

This course is delivered and assessed wholly online over an intensive 8 weeks.

The last date for receipt of complete applications is 5pm Friday 11th April 2025. Regrettably, late applications cannot be accepted.

The overall aims of this module are to enable students:

  • To gain confidence in one high-level professional statistics package, and complement the techniques learnt on other modules with advanced techniques such as bootstrap resampling

Intended learning outcomes are:

  • Learn fundamental programming techniques such as loops, resampling, Monte-Carlo simulation and use them to solve analytical problems in medical sciences.
  • To develop the ability to complement the techniques learnt on other modules with computer-intensive machine learning type techniques such as random forests and neural networks.

Students should leave the course with confidence that in the future they could manage challenging analytical problems with state-of-the-art R packages; use simulation to evaluate statistical power, or check model assumptions; use bootstrap and permutation methods to calculate confidence intervals and p-values in non-standard situations and utilise machine learning methods to classification and prediction problems. 


Description Costs
Short Course in Health Sciences £3175.00
Students enrolled on MSc in EBHC (Medical Statistics) £2570.00


Details of funding opportunities, including grants, bursaries, loans, scholarships and benefit information are available on our financial assistance page.


If you are an employee of the University of Oxford and have a valid University staff card you may be eligible to receive a 10% discount on the full stand-alone fee. To take advantage of this offer please submit a scan/photocopy of your staff card along with your application. Your card should be valid for a further six months after attending the course.


Dr Richard Stevens

Module Co-ordinator

Richard Stevens is Course Director of the MSc in EBHC Medical Statistics, Deputy Director of the Statistics Group at the Centre for Evidence-Based Medicine, Oxford and an Associate Professor.

Assessment methods

  • Each unit includes exercises to consolidate understanding
  • The assessment consists of statistical problems in health research designed to give insight into real statistical problems in healthcare and to test ability to apply and understand correct statistical analysis.

Academic Credit

Applicants may take this course for academic credit. The University of Oxford Department for Continuing Education offers Credit Accumulation and Transfer Scheme (CATS) points for this course. Participants attending at least 80% of the taught course and successfully completing assessed assignments are eligible to earn credit equivalent to 20 CATS points which may be counted towards a postgraduate qualification.

Applicants can choose not to take the course for academic credit and will therefore not be eligible to undertake the academic assignment offered to students taking the course for credit. Applicants cannot receive CATS (Credit Accumulation and Transfer Scheme) points or equivalence. Credit cannot be attributed retrospectively. CATS accreditation is required if you wish for the course to count towards a further qualification in the future.

A Certificate of Completion is issued at the end of the course.

Applicants registered to attend ‘not for credit’ who subsequently wish to register for academic credit and complete the assignment are required to submit additional information, which must be received one calendar month in advance of the course start date. Please contact us for more details.

Please contact if you have any questions.


This course requires you to complete the application form and to attach a copy of your CV. If you are applying to take this course for academic credit you will also be required to provide a reference. Please note that if you are not applying to take the course for academic credit then you do not need to submit a reference.

Please ensure you read the guidance notes which appear when you click on the symbols as you progress through the application form, as any errors resulting from failure to do so may delay your application.

Selection criteria

Admissions Criteria:
To apply 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.
  • 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.
  • Have familiarity with basic statistical concepts (p-value; mean, standard deviation, standard error, confidence interval, normal distribution) and the essential methods used by medical statisticians such as linear, logistic regression and Cox regression.
  • Be able to demonstrate English Language proficiency at the University’s higher level

IT requirements

Please ensure that you have access to a computer that meets the specifications detailed on our technical support page.