Practical course: Time Series Analysis (M6b) (74054)
2023-02-13-2023-02-17 (several days), Block course, see announcement
Holger Lange, Michael Hauhs
P, 3 ECTS
Block course from 13 February, 2023 to 17 February, 2023
Prerequisites: Introductory course in statistics, basic knowledge in R
Learning Objectives: In this module, students should learn to evaluate, analyse and assess on their own typical environmental time series (climate and ecological data). In doing so, they will gain practice in using R.
Course content: In this module linear and non-linear time series analysis will be taught and practiced by using different data sets from various environmental monitoring. Along with the classic procedure (auto and cross correlation, trend analyse, Fourier analyse, ARIMA-models) a focus is on non-linear methods recurring analysis, singular system analysis, wavelets, dimension reduction, etc.). The selection of procedure can change and is based on the interests of the students and current research projects.
The second part of the module consists of a Block-Practicum. Students will choose appropriate methods to use for predetermined data sets and the results of the different procedures will be interpreted.
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