| 08-27-GS-1 | Co-creating knowledge for ocean and coastal sustainability (in englischer Sprache)
Block Seminar: September 3rd-6th
Blockveranstaltung
ECTS: 3
VKey themes for the holistic assessment and sustainable governance and management of marine and coastal social-ecological systems in tropical regions will be introduced. With its inter- and transdisciplinary approach to the study of tropical coastal and marine systems, the Centre for Marine Tropical Research (ZMT) plays a leading role in linking and integrating social and natural science research approaches to as to generate actionable knowledge to support sustainable human-nature relations in coastal and marine regions of the tropical world. ZMT operates within the German marine research environment, in coastal science cooperation between Germany and partner countries in the tropics, and in international and intergovernmental global research and governance institutions.
Lernziele/Kompetenzen: 1) Understand and explain key concepts in ocean and coastal sustainability research. 2) Identify and critically assess key approaches/methods in inter- and transdisciplinary coastal and marine sustainability research at the ZMT 3) Suggest future pathways.
Studien- und Prüfungsleistungen,Prüfungsformen: During the 4-day Block Seminar I/we (there are other contributors) grade: 1) Individual participation; 2) a 10 min presentation of a short individual research/reading; 3) Group work
| Marion Glaser
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| 08-27-GS-2 | Introduction to R data analysis and visualization for geography and geosciences (in englischer Sprache)
Einführung in die Datenverarbeitung und -visualisierung mit R in Geographie und Geowissenschaften
Seminar
ECTS: 3
Termine:
wöchentlich Di 10:00 - 12:00 (2 SWS)
Veranstaltungsinhalte:
The lectures provide an introduction to the R programming language. The focus is on data processing and visualization with the following content:
1. Understand R language and navigate the RStudio software
2. R basics: manipulate different data structures: vectors, matrices, dataframes, lists; install code packages and use functions; manage the working directory and its environment
3. Data management: read in, edit, filter, merge and analyse data sets
4. Data visualization with most common graphs (scatterplot, boxplot, bar graph, time series plot); customize graph text and aesthetics.
5. Basic analyses: regression and ordination methods
6. Introduction to packages: ggplot, vegan, rioja.
All content is accompanied by practical exercises (during the course and as homework).
Lernziele/Kompetenzen:
The lectures aim is to teach students basic concepts, skills, and tools for working with the R software so that they can develop a basic understanding for working with R and basic analyses for upcoming student tasks. The lectures are designed for those interested in working with scientific data in R
| Maria Lujan Garcia
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