Areas of Expertise
- Movement ecology
- Population ecology
- Community ecology
- statistics
- spatial ecology
- Agroecology
- Biodiversity
- Applied ecology
- roe deer
- animal movements
- habitat use
- home range
- biodiversity
This module introduces students to the basics of analyzing ecological data, using the R Software Environment for Statistical Computing. The topics covered will be also broad enough to be equally applicable to basic data analysis across biology. Students will receive 8 computer-based workshops/practicals, complemented by 9 lectures before each workshop. Furthermore, a weekly drop-in stats help session will be provided, as well as help through a course Facebook page. The module will cover 5 key themes: 1). Data analysis and statistics, reproducibility and the R Software Environment; 2). Data management; 3). Data visualization; 4). Data analysis - The general linear model; 5). Data analysis - Presentation of results and outline of more advanced methods. The module will be subject to continuous assessment consisting of 3 pieces of computer-based work (60% of final mark), which will require the students to carefully complete all course work assigned on a weekly basis ('independent learning'), in order to be able to complete the assignments. A further 40% of the final mark will consist in a data analysis report, to be completed after the end of the course. Weekly readings and non-assessed computer-based exercises will be assigned, too.
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