PG Dip / MSc Applied Statistics And Datamining

A  2.1 undergraduate Honours degree in mathematics, statistics or in an area with substantive mathematical or statistical content.

For fees and funding options, please visit website to find out more

Graduates from this programme typically seek employment as analysts within a company, research body, government, or as statistical consultants. 

Recent graduates have found employment in: 

• large consulting firms and major financial institutions including: American Express, Aviva, Capital One, Goldman Sachs, Lloyds, PwC, RBS, Scottish and Southern Energy, Tesco Bank, TSB and Vodafone
• biomedical research, clinical trials and pharmaceuticals 
• wildlife and conservation managers including the Wildlife Conservation Society (WCS)

The Careers Centre offers one-to-one advice to all students as well as a programme of events to assist students in building their employability skills.

Compulsory

• Advanced Data Analysis: covers modern modelling methods for situations where the data fails to meet the assumptions of common statistical models and simple remedies do not suffice.
• Applied Statistical Modelling using GLMs: covers the main aspects of linear models and generalised linear models, including model specification, various options for model selection, model assessment and tools for diagnosing model faults.
• Introductory Data Analysis: covers essential statistical concepts and analysis methods relevant for commercial analysis.
• Knowledge Discovery and Datamining: covers many of the methods found under the banner of datamining, building from a theoretical perspective but ultimately teaching practical application.
• Multivariate Analysis: introductory and advanced training in the applied analysis of multivariate data.
• Software for Data Analysis: covers the practical computing aspects of statistical data analysis focusing on widely used packages, including data-wrangling and visualisation.

Optional 

• Advanced Bayesian Inference
• Advanced Combinatorics
• Estimating Animal Abundance and Biodiversity
• Independent Study Module
• Mathematical Oncology
• Medical Statistics
• Modelling Wildlife population dynamics
• Spatial Models and Pattern Formation in Mathematical Biology

Computer Science modules 

In addition, students may take modules from the School of Computer Science that are consistent with the degree. Representative examples of these modules are:

• Data-Intensive Systems
• Database Management Systems

Optional modules are subject to change each year and require a minimum number of participants to be offered. Some may only allow limited numbers of students or assume prior knowledge before taking.

Dissertation

MSc students complete a dissertation during the final three months of the course to be submitted near the end of August. Dissertations are supervised by members of teaching staff who will advise on the choice of subject and provide guidance throughout the progress of the dissertation. Many topics are in collaboration with companies and other external bodies.

If students choose not to complete the dissertation requirement for the MSc, there is an exit award available that allows suitably qualified candidates to receive a Postgraduate Diploma. By choosing an exit award, you will finish your degree at the end of the second semester of study and receive a PGDip instead of an MSc