In this digital and data-rich era the demand for statistics graduates from industry, the public sector and academia is high, yet the pool of such graduates is small. The recent growth of data science has increased the awareness of the importance of statistics, with the analysis of data and interpretation of the results firmly embedded within this newly recognised field.
This programme is designed to train the next generation of statisticians with a focus on the newly recognised field of data science. The syllabus combines rigorous statistical theory with wider hands-on practical experience of applying statistical models to data. In particular the programme includes:
Graduates will be in high demand. It is anticipated that the majority of students will be employed as statisticians within private and public institutions providing statistical advice/consultancy.
To be awarded the MSc degree you need to obtain a total of 180 credits. All students take courses during semester 1 and 2 to the value of 120 credits which will be a combination of compulsory and optional courses. Successful performance in these courses (assessed via coursework or examinations or both) permits you to start work on your dissertation (60 credits) for the award of the MSc degree. The dissertation will generally take the form of two consultancy-style case projects or an externally supervised project.
The set of courses available is subject to review in order to maintain a modern and relevant MSc programme.
Previous compulsory courses for 2016-17:
Previous optional courses for 2016-17 include:
At the end of this programme you will have:
Trained statisticians are in high demand both in public and private institutions. This programme will provide graduates with the necessary statistical skills, able to handle and analyse different forms of data, interpret the results and effectively communicate the conclusions obtained.
Graduates will have a deep knowledge of the underlying statistical principles coupled with practical experience of implementing the statistical techniques using standard software across a range of application areas, ensuring they are ideally placed for a range of different job opportunities.
The degree is also excellent preparation for further study in statistics or data science.
This programme trains you in the theory and methods of social statistics, exposing you to cutting-edge social statistical practice and preparing you for carrying out research in the social sciences. There is a particular focus on survey design and analysis, statistical modelling of complex data and demographic methods.
Compulsory modules: Quantitative Methods I & II or Generalised Linear Models; Survey Design; Demographic Methods I; Qualitative Methods I; Analysis of Hierarchical (Multilevel and Longitudinal) Data; Research Skills; Social Science Data: Sources and Measurement. Optional modules: Computer-intensive Statistical Methods; Critical Issues in Global Health: Concept and Case Studies; Methods and Analysis of Global Health Trends and Differentials; Philosophy of Social Science Research; Family Demography; Qualitative Methods II; Statistical Theory and Linear Models; Demographic Methods II; Design of Experiments; Epidemiological Methods; Migration and Development; Multivariate Analysis; Population, Poverty and Policy; Population and Reproductive Health; Methods for Researching in Ageing Societies; Statistical Computing; Statistical Genetics; Survey Methods I; Survival Analysis; Understanding Population Change Plus dissertation