The course is intended to give an overview of common statistical methods and concepts used within environmental sciences; with a focus on the applications, interpretation, and limitations of the methods. This format will provide a refresher of methods that students may have covered before, helping to contextualise them with practical examples within their areas of study, as well as extending beyond these methods and drawing the links between different methods that are often overlooked.
This course will not be going into depth on the underlying formulae, or on the programming/software skills required to conduct the analyses – but additional references and resources will be provided so students interested in those areas can explore them should they so wish.
Example data sets and questions will be related to environmental sciences topics. Each module will include pre-recorded videos, interactive workbooks, exercises & links to further resources – all of these can be accessed by the students at any time after the module is launched. A 1 hour webinar will be held at the end of each weekly module, working through the answers to the exercises and allowing for a Q&A about any of the content from within the module.
There will be 6 modules within the course:
1. Exploratory Data Analysis
2. Sampling, estimation & confidence intervals
3. Hypothesis testing & p-values
4. Introduction to Statistical Modelling – General Linear Models
5. Continuing Statistical Modelling – Generalised Linear Models & Other Extensions
6. Ecological diversity indices; & taking things further
- Profesor: Sam Dumble
- Profesor: Alex Riba
- Profesor: Alex Thomson