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MSc Modules and Assessment

MSc course handbook 2018-2019
Modules

Students on the MSc in Statistics take eight lecture-course modules, two of which are compulsory (core) modules:

Statistical Methods
An Introduction to Statistical Practice

The two core modules above provide a strong foundation in statistical methods, both theoretical and practical, for the rest of the MSc course.

The remaining six modules are chosen from a wide range of options, subject to availability, to suit the interests of individual students. The options include:

Risk Theory

Bayesian Forecasting and Intervention with Advanced Topics

Applied Stochastic Processes with Advanced Topics

Monte Carlo Methods

Medical Statistics with Advanced Topics

Designed Experiments with Advanced Topics

Multivariate Statistics with Advanced Topics

Bayesian Statistics and Decision Theory with Advanced Topics

Advanced Topics in Statistics, not run in 2018-19

Statistical Genetics with Advanced Topics

Financial Time Series

Statistical Frontiers

Data Mining 

Advanced Topics in Data Science

The Introduction to Statistical Practice module includes an initial 'mock exam' intended for students to use as a focus for revision, and as an introduction to the UK style of written examination for those with little or no such experience. It also introduces statistical computing, using one of the modern systems R or S-Plus, through hands-on practical classes on the analysis of real data from a variety of scientific and other disciplines; and develops such skills are report-writing, statistical graphics, etc.

Advanced Topics in Statistics is a module made up of a small number (typically 3) of sub-modules, each sub-module giving a rapid treatment of a specific area of current interest in statistics or probability. The particular topics vary from year to year.

To complete the MSc, a student also undertakes a substantial project under the supervision of a Department member, and writes a dissertation reporting the results. Such projects can be in any of the areas covered by the MSc, including applied statistics, statistical methodology, computational methods, probability etc. subject to the approval of the MSc Tutor.

Assessment

Assessment is initially made for each module separately: some modules have an element of continuous assessment through coursework, but the majority of modules assessed through written examinations in May and June or, for some modules, January.

The performance of MSc students in their core and optional modules combined is then examined by an examinations board consisting of academic staff plus an External Examiner appointed from another university.
Dissertations are examined in the Department and then by the External Examiner. The MSc degree is awarded subject to satisfactory standard in the dissertation. Students who do outstandingly well in both taught modules and the dissertation may be awarded the MSc with Distinction or Merit.