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|Application deadline:||as early as possible|
|Tuition fee:|| |
|Start date:||September 2013|
|Credits:|| 60 ECTS |
|Duration full-time:||12 months|
|Delivery mode:||On Campus|
This 12 month postgraduate statistics course aims to train professional statisticians for posts in industry, government, research and teaching. It also provides a suitable preparation for careers in other fields requiring a strong statistical background. The Royal Statistical Society (RSS), which has accredited the programme, has extensive information about career opportunities in statistics.
The statistics group at SMSAS is highly qualified to lead your advanced study in statistics and research in the field is thriving here. In the last Research Assessment Exercise (RAE), in 2008, we were ranked 8th in the UK for Statistics. Our research work informs our MSc teaching, through lectures, practical work and projects.
Both the RSS and Statisticians in the Pharmaceutical Society (PSI) offer prizes for students who perform exceptionally well on the MSc in Statistics.
* Duration: One year full-time.
* Start: September.
Modules taught in the autumn and spring terms contribute 120 credits with a project undertaken in the summer term contributing the remaining 60 credits. Details are shown below for the core modules, the project, and the optional modules (of which you choose 2).
* Probability and classical inference - This module lays the theoretical foundations for the course, providing a solid grounding in probability and covering all of the essential theory of classical statistics.
* Advanced regression modelling - Regression models seek to explain variation in one variable, the response variable, in terms of other variables, the explanatory variables. This module covers many important models of this type, including linear models for regression and the analysis of variance, and generalised linear models for the analysis of contingency tables and data that arise as counts or proportions.
* Computational statistics - This module revises and integrates material from other modules, and reveals the power of Statistics for analysing novel and challenging data sets. Theory is complemented by hands-on practical experience using computer programs written in Matlab and in R.
* Bayesian statistics - Bayesian inference has become central to modern statistical analysis by providing a very general way of tackling statistical problems. This module covers modern, simulation-based methods, and is illustrated by hands-on computing experience, using packages such as WinBUGS.
* Practical statistics and computing - This module is concerned with the practical analysis of real data, report writing, oral presentation and consultancy skills, all of which are essential tools for the modern Statistician. The main computer package used is R.
* Principles of data collection - This module explores the important roles that Statisticians play in planning how data are collected. The two main types of study considered are sample surveys and designed experiments. Especially important are topics such as questionnaire design and the design of clinical trials to study the performance of new drugs.
Optional modules (students chose two of the following)
* Stochastic Processes and Time Series - Time-dependent data play an important role in everyday life, enabling us to gauge changes to the climate, to analyse stock-market prices, to determine how to model waiting times, as in hospital, and so forth. This module covers the essentials of the analysis of stochastic processes and also the analysis of time-series data.
* Stochastic Models in Ecology and Medicine - The two topics of this module are of great current importance. For instance in ecology we might be interested in what drives populations of wild animals to change over time, and in medicine we need methods to determine how diseases develop and progress, which factors are important, and how effective are interventions.
* Analysis of Large Datasets - Huge data sets are now routinely collected in many applied areas such as economics, finance, biology and the social sciences. In this module techniques are presented to simplify such data sets, and uncover hidden, important structure
Students choose their project topic in consultation with members of staff, from a wide range covering both practical data analysis and more theoretical work. Students on the MSc in Statistics with Finance will work on topics in the appropriate subject area. Students working on their projects obtain regular supervision from their supervisor(s).
An applicant should hold a 2(ii) or better Honours Bachelor degree with the equivalent of at least one year of mathematics at undergraduate level from an accredited UK institution or equivalent. There are English language requirements for international students.
|CAE score:||75(Grade B)|
|TOEFL internet-based test score:||90|
Details of the School's bursary scheme to support taught postgraduate students are as follows:
* The school will award up to 35 bursaries of between £500 and £1500.
* All applicants who have accepted a place on one of the following courses will automatically be considered for a bursary. There is no need to make a separate application. * Postgraduate Diploma in Actuarial Science
* MSc in Applied Actuarial Science
* MSc in Finance, Investment and Risk
* MSc in Mathematics and its Applications
* MSc in Statistics/Statistics with Finance
* Overseas/home/EU fee paying students are all eligible.
* There is no formal closing date but we recommend you apply for your chosen course before the end of July 2012. The selection process continues until all bursaries are awarded.
You are normally required to take an English Proficiency Test.
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