851311 Environmental statistics
- Type
- Lecture and exercise
- Semester hours
- 2
- Lecturer (assistant)
- Schlögl, Matthias , Laaha, Gregor
- Organisation
- Offered in
- Sommersemester 2025
- Languages of instruction
- Englisch
- Content
-
In this course statistical methods for the analysis of spatio-temporal environmental data are developed on the basis of practical tasks (data examples). These are divided into local tasks (e.g. statistical key figures, time series analyses) and regional tasks (multivariate and geostatistical regionalisation methods). In the lecture part, basic methods are presented, the exercise part is for practical application on the computer.
Lecture part
• Introduction (aim, data, explorative statistics)
• Local methods (environmental indices, homogeneity tests, time series analysis)
• Regional methods (multivariate methods, geostatistics, grouping methods)
Practical part
• Short introduction to statistics-software "R"
• Application of "R" to environmental data
• Elaboration of practical exercises
- Previous knowledge expected
-
This is an advanced lecture in applied statistics. A sound basis in statistical methods (introduction to statistics) and computer basics required!
- Participants without basic knowledge of R and R-Studio are recommended to attend the course "851016 First Steps with R" which is held in a block at the beginning of the semester (Rcmdr knowledge alone is not sufficient).
- Objective (expected results of study and acquired competences)
-
With the completion of the course, students should be able to analyse and present spatio-temporal environmental data using statistical methods. The students have acquired a repertoire of basic methods for solving local and regional environmental statistical problems, can define and describe them, understand their methodological requirements, and have the competence to apply them to concrete problems using statistical software and to interpret the results.
You can find more details like the schedule or information about exams on the course-page in BOKUonline.