Structure of the MSc in Statistics
Course structure
Our cutting-edge curriculum covers the most relevant and in-demand topics for statisticians in today’s dynamic landscape.
Our program provides unparalleled flexibility, allowing students to tailor their learning to their ambitions through four distinctive options:
- MSc in Statistics
- MSc in Statistics with Data Science
- MSc in Statistics with Finance
- MSc in Statistics with Probability
The choice of degree is made after you start the course, rather than when you apply.
You begin the MSc by taking a Statistics Refresher (pre-term in Welcome Week), and the module Statistical Methods and Practice. The programme then features different core modules depending on the chosen degree:
- for Data Science, the module Theory of Data Science;
- for Finance and Probability, the module Introduction to Advanced Probability.
In Term 2 you take the module Advanced Topics in Statistics & Probability, which provides an introduction to current topics through case studies in Statistics, Data Science, Finance and Probability, exploring potential research topics for your dissertation. Each two-week case study is led by an expert lecturer in the fields and will make use of lectures, presentation, practicals, summary and discussion as appropriate to the area.
Regardless of the chosen degree, all students can choose approximately a third of their modules from any of those offered on the MSc, with the remainder dependent on the chosen degree.
The programme concludes with the Dissertation Project, which you work on under the supervision of a faculty member over the summer with submission in September.
Statistics
The general Statistics degree offers you a free choice of almost all Master's-level modules offered by the Statistics Department. This includes all of the Statistics modules mentioned in the other degrees below, plus
- Medical Statistics
- Designed Experiments
- Statistical Genetics
This degree will suit you if you want an MSc in Statistics, with the maximum degree of flexibility in this subject.
Finance
An MSc in Statistics with Finance will equip you for a career in quantitative finance, where you require a knowledge of the latest mathematical and statistical models, along with insights into their application in modern financial systems. Modules with a particular focus or relevance to finance include:
- Introduction to Mathematical Finance
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Stochastic Methods in Finance
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Statistical Learning and Big Data
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Time Series
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Stochastic Calculus for Finance
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Advanced Trading Strategies
- Risk Theory
Data Science
This choice leads to an MSc in Statistics with Data Science. You should choose this degree if you are interested in working at the forefront of the modern data revolution, at the intersection of Statistics and Computer Science. Statistics modules geared towards this degree include:
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Bayesian Forecasting and Intervention
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Applied Stochastic Processes
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Monte Carlo Methods
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Multivariate Statistics
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Bayesian Statistics and Decision Theory
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Advanced Topics in Data Science
- Machine Learning Frameworks
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Statistical Learning and Big Data
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Statistical Consulting
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Statistical Communication and Visualisation of Data
- Time Series
Subject to availability, you will have access to a varying selection of Computer Science modules with themes such as:
- High Performance Computing
- Agent Based Systems
- Algorithmic Game Theory
- Image and Video Analysis
- Computational Biology
- Natural Language Processing
Probability
If your passion is the theoretical underpinnings of statistical applications, the MSc in Statistics with Probability is for you. This degree features modules from Probability and Applied Probability from the Statistics Department, alongside modules offered by Mathematics. The Statistics modules featured are:
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Applied Stochastic Processes
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Brownian Motion
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Dynamic Stochastic Control
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Monte Carlo Methods
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Stochastic Methods in Finance
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Applications of Stochastic Calculus for Finance
Subject to availability, you will have access to a varying selection of Mathematics modules with themes such as:
- Topics in Rare Events
- Theory of Random Graphs
- Stochastic Analysis
- Statistical Mechanics
- High Dimensional Probability
Further details about all modules will be available on the university course page.
An overview of the relationships between the degrees can be found below.
