Sobre este curso

Oxford University
  • Data de início

    2020 - 2021
  • Fees

    £0
  • Study mode

    Full-Time
  • Ucas Code

  • Campus

    Oxford University
  • Qualification

    Master of Science
Sumário

O melhor curso na melhor universidade para você

The information provided on this page was correct at the time of publication (November 2019). 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 The MSc in Statistical Science is a twelve-month full-time taught masterâ??s degree running from October to September each academic year. The MSc has a particular focus on modern computationally-intensive theory and methods. 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. 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. You will be assessed on your performance in two written examinations around May, through your work in the assessed practical problems set during the year, and by the quality and depth of your dissertation. 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. PGDip 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. 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.

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