MSc - Statistical Data Science

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Organisation
University of Kent
Start - End
12 Sep
Study Options
Full Time
Fee
GBP 9300 - 9300
Fee International
GBP 17400 - 17400

The MSc in Statistical Data Science is accredited by the Royal Statistical Society (RSS) and is excellent preparation for careers in any field requiring a strong statistical background.

The programme, which has recently been updated, trains professional statisticians for posts in industry, government, research and teaching. It provides a suitable preparation for careers in other fields requiring a strong statistical background. Core modules give a thorough grounding in modern statistical methods and there is the opportunity to choose additional topics to study.

Statistical Data Science at Kent provides:

  • a programme that gives you the opportunity to develop practical, mathematical and computing skills in statistics, while working on challenging and important problems relevant to a broad range of potential employers
  • teaching and supervision by staff who are research-active, with established reputations and who are accessible, supportive and genuinely interested in your work
  • advanced and accessible computing and other facilities
  • a congenial work atmosphere with pleasant surroundings, where you can socialise and discuss issues with a community of other students.

About the School of Mathematics, Statistics and Actuarial Science (SMSAS)

The School has a strong reputation for world-class research and a well-established system of support and training, with a high level of contact between staff and research students. Postgraduate students develop analytical, communication and research skills. Developing computational skills and applying them to mathematical problems forms a significant part of the postgraduate training in the School. We encourage all postgraduate statistics students to take part in statistics seminars and to help in tutorial classes.

The Statistics Group is forward-thinking, with varied research, and received high rankings in the Research Excellence Framework (REF) 2014 for research power and quality.

Accreditation

Course structure

Duration: 1 year full-time

You undertake a substantial project in statistics, supervised by an experienced researcher. Some projects are focused on the analysis of particular complex data sets while others are more concerned with generic methodology.

You gain experience of analysing real data problems through practical classes and exercises. The programme includes training in the computer language R.

Modules

The following modules are indicative of those offered on this programme. This list is based on the current curriculum and may change year to year in response to new curriculum developments and innovation. Most programmes will require you to study a combination of compulsory and optional modules. You may also have the option to take modules from other programmes so that you may customise your programme and explore other subject areas that interest you.

Compulsory modules currently include

  • MA867 - Project (60 credits)
  • MA881 - Probability and Classical Inference (15 credits)
  • MA882 - Advanced Regression Modelling (15 credits)
  • MA883 - Bayesian Statistics (15 credits)
  • MA884 - Principles of Data Collection (15 credits)
  • MA942 - Data Science with R (15 credits)

Teaching and assessment

Assessment is through coursework involving: complex theoretical questions, analysis of real-world data using appropriate computing packages over a range of areas of application; written unseen examinations; dissertation.

Programme aims

This programme aims to:

  • To give students the depth of technical appreciation and skills appropriate to masters' level students in Statistics.
  • To equip students with a comprehensive and systematic understanding of theoretical and practical Statistics.
  • To develop students’ capacity for rigorous reasoning and precise expression.
  • To develop students’ capabilities to formulate and solve problems relevant to Statistics.
  • To develop in students appreciation of recent developments in Statistics, and of the links between the theory of Statistics and their practical application.
  • To develop in students a logical, mathematical approach to solving problems.
  • To develop in students an enhanced capacity for independent thought and work.
  • To ensure students are competent in the use of information technology, and are familiar with computers, together with the relevant software.
  • To provide students with opportunities to study advanced topics in Statistics, engage in research at some level, and develop communication and personal skills.
  • To provide successful students with the depth of knowledge of the subject sufficient to enter a career as a professional statistician.
  • To provide successful students with eligibility for exemptions from examinations of the Royal Statistical Society.

Learn More

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