Personal and Key Transferable/ Employment Skills and Knowledge: 7 Statistical analysis skills;
8 Self-learning and making effective use of learning resources;
9 Effective use of learning resources;
10 Report writing and presentation.
SYLLABUS PLAN - summary of the structure and academic content of the module The syllabus will depend upon the module topic(s) offered and will be specified in detail by the lecturer(s) and agreed by the module coordinator for any particular year.
Examples of topics include time series modelling and forecasting, clustering, neural networks and Bayesian computation. Examples of topics include time series
modelling and forecasting; geostatistics; modelling of extreme values; hierarchical modelling; data fusion; multivariate analysis; computational statistics; data mining
methods; survival analysis; survey sampling and experimental design. Other suitable topics may also be offered.
LEARNING AND TEACHING LEARNING ACTIVITIES AND TEACHING METHODS (given in hours of study time) Scheduled Learning & Teaching Activities 30.00
Guided Independent Study 120.00
Placement / Study Abroad 0.00
DETAILS OF LEARNING ACTIVITIES AND TEACHING METHODS Category
Hours of study time
Description
Scheduled Learning and Teaching Activities
20
Lectures
Scheduled Learning and Teaching Activities
10
Problem-solving sessions
Guided Independent Study
56
Self-study & background reading
Guided Independent Study
64
Coursework
ASSESSMENT FORMATIVE ASSESSMENT - for feedback and development purposes; does not count towards module grade Form of Assessment Size of Assessment (e.g. duration/length) ILOs Assessed Feedback Method Feedback on unassessed problem sheets and data analyses
24
All
Oral
