This module provides students with an introduction to graduate-level approaches to biodiversity data analysis, and introduce two important software platforms for statistical exploration, simulation and spatial data analysis. The first half of this module uses R to teach data exploration and statistical analysis. The second half of this module introduces geographic information systems and their use in the analysis of spatially-explicit biological data, including raster and vector data.
At the end of this module students should be able to:
- Use the “R” computing environment to design experiments, statistically test and simulate patterns in biological systems
- Explain and use statistical analysis in the context of conservation biology including simple statistical tests, linear and non-linear regression and ordination.
- Demonstrate an ability to create, manage and manipulate spatial data through the ArcGIS computing platform;
- Transform vector and raster data into biologically relevant information;
- Interpret and manipulate remotely sensed spatially explicit data to elucidate underlying patterns and drivers of biodiversity distributions;
This module provides learners with a graduate-level overview of the following topics in biostatistics, geographic information systems (GIS) and remote sensing:
- Introduction to the “R” platform
- Basic statistical methods
- Experimental design and exploring biological data
- Advanced statistical methods – GLM and GLMM
- Introduction to spatial dataand its management
- Vector data analysis
- Raster data analysis