MSc Statistics and Operational Research

Structure and course options for the Statistics and Operational Research MSc programme.

You will take 120 credits of courses in total during Semesters 1 and 2, followed by a 60 credit dissertation which you complete over the summer. The courses you take will be dependent on the availability of courses each year which may be subject to change as the curriculum develops to reflect a modern degree programme. 

 

Compulsory courses cover the core skills of Statistics and Operational Research, with most compulsory courses being studied in Semester 1. All courses are worth 10 credits, unless otherwise indicated.

Semester 1 compulsory courses have previously included:

  • Bayesian Theory
  • Fundamentals of Operational Research
  • Fundamentals of Optimization
  • Generalised Regression Models
  • Methodology, Modelling and Consulting Skills
  • Statistical Programming

Semester 2 compulsory courses have previously included:

  • Simulation
  • Statistical Research Skills

You will have the opportunity to tailor your degree by selecting from a broad range of optional courses. All courses are worth 10 credits, unless otherwise indicated.

Semester 1 optional courses have previously included:

  • Python Programming
  • Statistical Methodology
  • Stochastic Modelling
  • Theory of Statistical Inference

Semester 2 optional courses have previously included:

  • Bayesian Data Analysis
  • Biostatistics
  • Credit Scoring
  • Incomplete Data Analysis
  • Integer and Combinatorial Optimization
  • Large Scale Optimization for Data Science
  • Machine Learning in Python
  • Methods for Causal Inference*
  • Multivariate Data Analysis
  • Nonlinear Optimization
  • Operational Research in the Energy Industry
  • Optimization Methods in Finance
  • Optimization Under Uncertainty
  • Risk and Logistics
  • Targeted Causal Learning
  • Time Series
  • Topics in Applied Operational Research

*delivered by the School of Informatics


Your MSc dissertation provides the opportunity to undertake a research project within one of the UK’s top statistics groups and to work with internationally leading academics on topics such as Bayesian statistics, environmental statistics, machine learning, smoothing, statistical ecology, epidemiology,  extreme value statistics, spatial statistics, operational research and optimisation.


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