Statistical Science PgDip

<strong>The information provided on this page was correct at the time of publication (November 2025). For complete and up-to-date information about this course, please visit the relevant University of Oxford course page via www.graduate.ox.ac.uk/ucas.</strong> <br/><br/><strong>PGDip</strong><br/>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.<br/><br/>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. <br/><br/>Course structure<br/>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.<br/><br/>Students take a mixture of core courses and optional courses. The core courses are compulsory and involve practical components that students must complete.<br/><br/><strong>MSc</strong><br/>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.<br/><br/>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.<br/><br/>Course structure<br/>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. <br/><br/>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.<br/><br/>The MSc offers a substantial opportunity for independent study and research in the form of a dissertation. The main period for dissertation work is June to September (though you may do some preparatory work for your dissertation earlier in the year) and during this time students should expect to work hours that are equivalent to full-time working hours, although extra hours may occasionally be needed.<br/><br/>A dissertation gives students the opportunity to develop broader transferable skills in the processes of organising, communicating, and presenting their work, and will equip students well for further research or for a wide variety of other careers. <br/><br/><strong>For the full description with information on course modules, patterns of learning and teaching, supervision etc, please visit the relevant University of Oxford course page via www.graduate.ox.ac.uk/ucas</strong>