This is a session of Topic 6: Statistics education, training and the workplace
(Monday 12th, 16:30-18:00)
- Jennifer Brown (New Zealand)
AbstractEnvironmental statistics can be a very challenging, but rewarding field of research. The challenge is because environmental data typically are very messy – nothing quite fits the perfect normal distribution, there are often many missing values, there is large variation, and measurement errors can confound results. Despite these challenges it is a tremendously rewarding field because the application area is fascinating – we all want to make the world a better place – and because of the level of passion and enthusiasm of environmental managers and researchers for their work.
Teaching statistics to this target audience of environmental managers and researchers needs to be focused on applications, use real-life case studies, and be convincing. Often excess quantities of data are collected with little regard for data-quality. Environmental statistics must be taught in such a way to convince the audience to design surveys and experiments carefully, analysis the data using modern tools, and restrict the report to inference only at the level appropriate given the data.
In this session we will hear from speakers who have experience teaching environmental statistics. Their expertise ranges from data collection and survey design through to complex data and computer-intensive simulation analysis methods.
|Paper||Title||Presenter(s) / Author(s)|
|6A1||The need for teaching weighted distribution theory: illustrated with applications in environmental statistics||Lyman McDonald (United States)|
|6A2||Amarillo by morning: data visualization in geostatistics||William Harper (United States)|
Isobel Clark (United Kingdom)
|6A3||Statistics education in a conservation organisation — towards evidence based management||Ian Westbrooke (New Zealand)|