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Royal Statistical Society (RSS) Accreditation

The Royal Statistical SocietyLink opens in a new window (RSS) is one of the premier statistical societies in the world, with a high international reputation. RSS accreditation provides external recognition for our courses’ depth, breadth, quality and statistical content. The opportunity to gain Graduate Statistician (GradStat) status adds further value to your degree qualification and the chance to access further professional development opportunities.

The RSS accredits the Department of Statistics' courses listed below for the period from 2017/18 up to 2022/23:

  • BSc in MORSE*
  • Integrated Masters in MORSE*
  • BSc in Mathematics and Statistics*
  • Integrated Masters in Mathematics and Statistics*
  • BSc in Data Science*
  • Integrated Masters in Data Science*
  • MSc in Statistics

For students entering in 22/23, all programmes are accredited on an unconditional basis; that is, accreditation does not depend on your choice of optional modules. For students entering in 21/22 or earlier, the programmes marked * are accredited on a conditional basis. Graduates from these programmes who wish to apply for Graduate Statistician status with the Society must submit a transcript (their HEAR document) to show that a satisfactory combination of modules has been taken and passed.

The table below sets out the accreditation conditions.

Programmes accredited with conditions (for entrants from 17/18 - 21/22) Modules needing to have been sat and passed
  • BSc in MORSE
  • Integrated Masters in MORSE
  • BSc in Mathematics and Statistics
  • Integrated Masters in Mathematics and Statistics
  • BSc in Data Science
  • Integrated Masters in Data Science

Students will be required to have passed at least one module from those listed in both A) and B) below:

A) Design of Experiments

  • ST221 Linear Statistical Modelling;
  • ST305/ST410 Designed Experiments;
  • ST332/ST409 Medical Statistics;
  • ST344 Professional Practice of Data Analysis;
  • ST404 Applied Statistical Modelling

B) Bayesian methodology

  • ST301/ST413 Bayesian Statistics and Decision Theory;
  • ST337/ST405 Bayesian Forecasting and Intervention;
  • ST404 Applied Statistical Modelling

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