Postgraduate Biology 2014-2015

This course provides rigorous training for biologists in statistical modelling concepts and techniques as well as the design of field experiments. The course uses a combination of lectures, computer-based and field-based practical to introduce students to the flexible linear modelling framework to analyse biological data. In addition to linear and generalized linear modelling, the course also introduces generalized additive modelling and multivariate statistics. You will gain a robust understanding of concept, theory and practice in biostatistics thanks to a unique example-led teaching approach. You will be trained to implement biostatistical analyses in the programming environment R.

This highly regarded course will take your understanding of statistics to the next level and provide you with the skills and confidence to analyse your complex biological data. Through a combination of lectures, computer based practicals and group work you will gain an understanding of how to deal with pervasive issues in the analysis of real world biological data such as heterogeneity of variance, spatial and temporal non-independence. Hands on computer tutorials will allow you to apply statistical models using modern statistical software (R) to real data, collected by researchers to answer real biological questions.

This course is one of the few postgraduate courses in Europe to provide an introduction to Bayesian inference, which is increasingly used in advanced quantitative research. A combination of lectures and personal research will provide you with the core concepts necessary to understand recent research in your field and apply Bayesian approaches to your own research. Hands-on computer tutorials will also allow you to implement statistical models in a Bayesian context and provide you with the essential skills for taking it further.

·         Introduction to techniques used in environmental and ecological modelling.

·         Main course materials in two parts; model development and model evaluation.

·         Hands on practice in model development and evaluation in two 4 hour computer classes.

·         Guest lectures from people using modelling in research in a range of different areas in biology.

·         Course assessment is based on the write up of the two practical sessions and a final course essay on a modelling topic selected by each student.

·         The course provides students with the key skills required for environmental and ecological modelling.