This course is an opportunity for you to dive deeper into the world of statistics. The focus of the course will be model selection, validation, prediction, and control. Therefore, different types of data including time series data will be explored using statistical methods used in the analysis of environmental changes as a result of anthropogenic activities and natural events. This course covers the topics data distributions, experimental designs, linear models, generalized linear models, generalized linear mixed models, power analysis, model diagnostics, autoregressive integrated moving average model (ARIMA model), directed acyclic graphs, differences between frequentist and bayesian statistics. R software packages will be used for computation, and a gentle introduction to the R program for statistical programming will be given. Therefore, prior knowledge of R programming basics is a plus but not mandatory. The course will be more interactive, with short exercises and projects, where participants are encouraged to work on different problems. After this course, you will confidently choose and validate your statistical model(s) for your own research.
Frequency | Weekday | Time | Format / Place | Period | |
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weekly | Mo | 10-12 | W0-135 | 07.10.-31.12.2024 |
Module | Course | Requirements | |
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20-EB_5 Ergänzungsmodul Biologie | 2 std. Vorlesung mit Übungsanteil 1 | Study requirement
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Student information |
The binding module descriptions contain further information, including specifications on the "types of assignments" students need to complete. In cases where a module description mentions more than one kind of assignment, the respective member of the teaching staff will decide which task(s) they assign the students.
Degree programme/academic programme | Validity | Variant | Subdivision | Status | Semester | LP | |
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Biologie / Promotion | Lectures and Seminars | Wahl |