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Description
This module aims to introduce the statistical package R with particular application to statistical modelling and a selection of computational techniques. It is intended for students registered on the Masters degree programmes offered by the Department of Statistical Science (including the CSML and MASS programmes).听For these students, the academic prerequisites for this module are met either through earlier compulsory study within (UG) or successful admission to (PGT) their current programme.
Intended Learning Outcomes
- be able to use the statistical package R to input, edit and manipulate data, produce appropriate graphics and implement statistical methods taught in other modules;
- be familiar with some basic principles of programming, and be able to carry out simple programming in R with application to a variety of computational and numerical techniques.
Applications - The generic programming skills acquired in this module are applicable across a wide variety of scientific disciplines as well as in the IT sector. More specifically, the R programming environment is gaining popularity among many research communities as well as in specialised areas of business and industry, such as finance and reinsurance, where non-routine statistical analyses are increasingly required.
Indicative Content - Using R: expressions, assignments, objects, vectors, arrays and matrices, lists and data frames, functions, control structures, graphics. Efficiency considerations. Statistical modelling in R (in collaboration with STAT0028 and STAT0029): linear, generalised linear and non-linear modelling. Unsupervised learning: dimension reduction and clustering. Computational techniques: function minimisation (in particular for mle鈥檚 and in non-linear modelling), quadrature, simulation (general methods, Monte Carlo).
Key Texts - Available from .
Module deliveries for 2024/25 academic year
Last updated
This module description was last updated on 8th April 2024.
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