Note: In the spring semester 2019 (107-2), I will teach this class in three weekend blocks: 2/23-24 (Saturday+Sunday), 3/23-24 (Saturday+Sunday) and 5/25 (Saturday).
Course focused on the analysis of community ecology data in R, organized by Institute of Ecology and Evolutionary Biology, College of Life Science, National Taiwan University
When: 2/23-24 (Saturday+Sunday), 3/23-24 (Saturday+Sunday) and 5/25 (Saturday). Every day we start at 9:00! (detailed schedule is in Calendar)
Where: 4A Life Science building, National Taiwan University
TA: Jia-Ang “Will” Ou
Language of the course: English
Course content: analysis of community ecology data, including ordination and cluster analysis, diversity analysis and analysis of species attributes. We will use real community ecology data (mostly vegetation and zoological datasets) and practice the analysis using the R project.
Link to CEIBA (NTU study system): https://ceiba.ntu.edu.tw/course/8ad85b/index.htm
Target audience: senior undergraduate and graduate ecology students focused on botany and zoology, who are planning to do a study at the community level (i.e. not on a single species, but on the multiple species occurring at multiple localities). The class may be useful also for other disciplines handling multivariate data (e.g. microbiology), but the main focus is on ecological data. If you study PhD and want to join, you are welcome, but expect that some of the teaching materials will cover rather basic things.
Teaching strategy: The class includes presentation of theory, application of methods using R program, solving individual exercise during the class, homework assignments, test of knowledge (analogy of midterm and final test) and preparation of individual projects and their presentation (in English).
Schedule: 5 days during 3 weekends. In selected weekend days, the course will start morning at 9 am and end evening around 6 pm. The first two weekends are focused on lectures and practice, the third weekend (including only Saturday) will be the final exam and presentations of individual projects.
Location: Life Science Building, National Taiwan University, Taipei.
Disclaimer: this is rather an intensive course, focused on a theory of community data analysis, and practical exercise using R on real community ecology datasets. Along to the lectures taught in the classroom, you need to also complete homework assignments, midterm quiz, final test and prepare (and present in English) the final project focused on analysis of community data. This is not an R course for advanced use of R program - I expect you have a basic knowledge of R before you enter the class, but the main focus is on learning the theory behind the methods and their use, not advanced R programming. If you want to learn basics of R, consider taking my other class Introduction to R for Ecologists (regular 3 credit class taught every winter semester).