Statistics with Data Science MSc

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University of Edinburgh
Start - End
12 Sep
Application Deadline
31 Aug
Study Options
Full Time
Fee International
GBP 26300 - 26300

In this digital and data-rich era the demand for statistics graduates from industry, the public sector and academia is high, yet the pool of such graduates is small. The recent growth of data science has increased the awareness of the importance of statistics, with the analysis of data and interpretation of the results firmly embedded within this newly recognised field.

This programme is designed to train the next generation of statisticians with a focus on the newly recognised field of data science. The syllabus combines rigorous statistical theory with wider hands-on practical experience of applying statistical models to data. In particular the programme includes:

  • classical and Bayesian ideologies
  • computational statistics
  • regression
  • data analysis of a range of models and applications

Graduates will be in high demand. It is anticipated that the majority of students will be employed as statisticians within private and public institutions providing statistical advice/consultancy.

Links with Industry

The School of Mathematics has connections with a wide number of industrial partners, organisations, charities and government departments. As an MSc student in the School you will have opportunities to engage with these external organisations through regular employability events, careers workshops, and our annual analytics challenge (whose recent partners have included Edinburgh Airport and the Data and Marketing Association). You will also have the opportunity to undertake an industry-based consultancy-style dissertation project.

Recent partners for industry-based consultancy projects in the Statistics with Data Science MSc include:

  • Lloyds Banking Group
  • Public Health Scotland


This MSc is accredited by the Royal Statistical Society (RSS). Thus, this programme is recognised by RSS for the purpose of eligibility for the professional award of Graduate Statistician. The accreditation is based on the general depth, breadth, quality and foundation of the programme and its statistical content.

Programme structure

This programme involves two taught semesters of compulsory and option courses followed by your dissertation project.

Compulsory courses have previously included:

  • Bayesian Data Analysis
  • Bayesian Theory
  • Generalised Regression Models
  • Incomplete Data Analysis
  • Statistical Programming
  • Statistical Research Skills

Optional courses have previously included:

  • Biomedical Data Science
  • Biostatistics
  • Credit Scoring
  • Fundamentals of Operational Research
  • Fundamentals of Optimization
  • Large Scale Optimization for Data Science
  • Machine Learning in Python
  • Machine Learning and Pattern Recognition*
  • Python Programming
  • Machine Learning in Python
  • Simulation
  • Probabilistic Modelling and Reasoning*
  • Methods for Causal Inference*
  • Statistical Methodology
  • Stochastic Modelling
  • Time Series
  • Text Technologies for Data Science*

*delivered by the School of Informatics

Dissertation projects

The dissertation will take the form of two consultancy-style case projects in different application areas.

Each consultancy-style project will last 5-6 weeks and will take the form of a consultant-client style where an industrial client will present a problem to your class and each student acts as a consultant addressing a particular aspect of the problem and presenting their conclusions to the client at the end of the 5-6 week period.

Learning outcomes

At the end of this programme you will have:

  • knowledge and understanding of statistical theory and its applications within data science
  • the ability to formulate suitable statistical models for new problems, fit these models to real data and correctly interpret the results
  • the ability to assess the validity of statistical models and their associated limitations
  • practical experience of implementing a range of computational techniques using statistical software R and BUGS/JAGS

Career opportunities

Trained statisticians are in high demand both in public and private institutions. This programme will provide graduates with the necessary statistical skills, able to handle and analyse different forms of data, interpret the results and effectively communicate the conclusions obtained.

Graduates will have a deep knowledge of the underlying statistical principles coupled with practical experience of implementing the statistical techniques using standard software across a range of application areas, ensuring they are ideally placed for a range of different job opportunities.

The degree is also excellent preparation for further study in statistics or data science. Students have gone on to study their PhDs at highly-ranked universities including Oxford and Edinburgh.

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