Course Structure - MSc in Statistics and Sustainability

Students will gain experience of the development and application of statistical techniques and models, and geographic information systems (GIS) and remote sensing technologies, to local and global sustainability problems. They will be exposed to the underlying theory of the statistical methodologies studied to deepen their statistical skills and their ability to promote statistical innovation.

Communication skills will be developed via individual and team project work embedded in the curriculum, and there will be an emphasis on translating statistical outcomes to broad audiences in multiple contexts. Graduates will be equipped with the quantitative skills needed to promote data-based decision making and 'green' innovation.

The course runs full-time over a twelve-month period commencing late September and completing early September of the following year. Formal teaching is divided into two twelve-week semesters, running from September to December and from January to April. By April, students will have chosen their Dissertation topic, picked and consulted in conjunction with their chosen supervisor, and be ready to develop substantial time researching and prototyping their work.

Module Information

Core Modules

Optional Modules
All modules unless otherwise stated are worth 5 ECTS and run for one semester.

The course comprises seven compulsory modules, and a Dissertation module. There are also 15 optional taught modules, from which students can choose modules worth a total of 20 ECTS. These options are split into two groups according to whether they are primarily statistics or sustainability modules. Students must choose at least one module from each group.

Statistics Modules: Time Series, Multivariate Analysis, Applied Statistical Modelling, Data Analytics (10 ECTS – runs over two semesters).

Sustainability Modules: Air Pollution, Transportation Modelling & Planning, Transport Data and Evaluation, Energy Policy and Building Energy Demand, Global Environmental Change, Environmental Policy, Human-Biodiversity Interactions, Earth System Science: Deep Time, Life Cycle Assessment for Engineering Practice, Engineering for the Environment, Advanced Spatial Analysis using GIS.