For entry in Academic Year 2024 to 2025
Year 1 modules
You must study the following modules :

Design of Experiments
When planning experiments, it is essential that the data collected are as relevant and informative as possible. The statistical principles for the design of experiments include the choice of optimal or good treatments sets and appropriate replication of t...

Generalised Linear Models
This module aims to introduce students to a wide range of statistical models grouped by the unifying theory of Generalized Linear Models: Linear, Logistic, Multinomial, Cumulative Ordinal and Poisson regression, as well as Log-linear models are presented,...

Likelihood and Bayesian Inference
This module develops methods for conducting inference about parametric statistical models. The techniques studied are general and applicable to a wide range of statistical models, including simple models for identically distributed responses and regressio...

Statistical Computing
This module consists of lecturers and associated practical sessions. The first part will focus on basic statistical programming in R. The second part will provide an introduction to some modern computational statistical methods and their implementation in...

Statistical Consultancy
This module focuses on statistical and demographic consulting.

Statistical Seminar Series I
Statistical Seminar Series II
Statistics Project
The Statistics Project gives MSc students to conduct an in-depth study, either of a particular advanced statistical methodology, or of the application of one or more methods to real applied problems. The aim is to develop skills of organising work, identi...

Survival Models
This module introduces some of the fundamental ideas and issues of lifetime and time-to-event data analysis, as used in actuarial practice, biomedical research and demography Co-Requisite: MATH6122

You must also choose from the following modules :

Clinical Trials
This module provides an introduction to the statistical challenges arising in planning and conducting clinical trials. The main topics will cover: Clinical Trials of Parallel or cross-over design; Randomization, Treatment Comparison and Confidence Interv...

Epidemiological Methods
This module introduces students to the main concepts involved in epidemiological analyses. The main epidemiological study designs are introduced and two lectures focus on methods used to analyse case-control studies whilst another two focus on cohort stu...

Flexible Regression
This module will introduce and develop flexible statistical modelling methods that allow for general and complex forms of data to be modelled, extending ideas already encountered in earlier modules on linear and/or generalised linear modelling. The two ma...

Forecasting
The module will introduce students to time series models and associated forecasting methods.

Introduction to Python
This module aims to teach students the fundamentals of writing structured computer programs, applicable using any high level programming language. However, students will be shown the special features of Python that makes this language especially useful fo...

Machine Learning
The purpose of the module will be to introduce students to the fundamentals of machine learning, i.e. computational methods for statistical learning, prediction and decision-making using data. The basic principles of predictive modelling will be outlined,...

Statistical Genetics
Statistical genetics has played a pivotal role in the discovery of genes that cause disease in humans. This module introduces the basic concepts and terms in genetics and demonstrates the use of statistical models to identify disease genes in humans.