Environmental Statistics & data Analytics training - Part II
Tuesday 5th-Friday 8th January, 2016 Lab 110, Mathematics Building
The aim of this training is to provide environmental scientists with a thorough knowledge of and skills in three key areas of recent statistical development- flexible regression methods, spatio-temporal modelling and functional data analysis and to address the issues of quantification of risk and resilience in a linked workshop.
Building on the August 2015 training course, there will be a focus on key statistical methods, which are fundamental to Environmental science, namely exploring relationships (generalized additive mixed models, quantile regression, tipping points), spatio-temporal modeling, and functional data analysis (FDA) methods. Each topic will be covered at a sufficient level, to ensure that the students gain knowledge of the statistical techniques and the types of questions for which they would be appropriate. There will also be practical sessions associated with the topics. Sponsorship is available for NERC funded PhD students and post-doctoral researchers. This is a very popular course with places for a maximum of 30 students, so early registration is recommended.
The associated advanced workshop will focus on quantifying environmental risk, and resilience - how does the past (data) inform the present and the future (statistical models) . A key element of the workshop is to develop an awareness of: the interconnected effects of environmental hazards and vulnerabilities and uncertainty quantification. Sessions will cover the role of models and data in quantifying risk, precautionary approaches to policy making and the nature of evidence .
Contact details: Course organiser is Professor Marian Scott (email@example.com). You can view the draft programme for the course here. The registration form should be completed and returned to firstname.lastname@example.org no later than 27th November 2015.