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Environmetrics *

Name of module: Environmetrics *

Exam number: 7001

Semester/Trimester: Semester

Duration of the module: Ein Semester

Form of the module (i.e. obligatory, elective course): Wahlpflicht

Frequency of module offer: Each winter semester

Prerequisites: Mathematical and statistical knowledge

Applicability of module for other modules and study programmes:
Serviceveranstaltung für Masterstudierende der Kultur- bzw. Rechtswissenschaften.

Person responsible for module: Prof. Dr. Wolfgang Schmid

Name of the professor: Prof. Dr. Wolfgang Schmid

Language of teaching: Englisch

ECTS-Credits (based on the workload): 6 (E-Modul)

Workload and its composition (self-study, contact time):
Kontaktzeit (Vorlesung, Übung, Seminar etc.) 37,5 Std.; Selbststudium: 142,5 Std.

Contact hours (per week in semester): 3

Methods and duration of examination:
Es kann ein Leistungsnachweis erworben werden. Voraussetzung hierfür ist die erfolgreiche Anfertigung einer Seminar-/Hausarbeit im Umfang von 15 Seiten / mit 30 000 Zeichen (sowie Präsentation der Ergebnisse der Arbeit)

Emphasis of the grade for the final grade: 1/29

Aim of the module (expected learning outcomes and competencies to be acquired):
Fachliche Kompetenzen:
Students understand and have knowledge of
- multiple linear regression
- time series analysis
- regression models
- spatial models
Students acquire the skills:
- analyzing of environmental data
- applying statistical methods to environmental data
Außerfachliche und überfachliche Kompetenzen:
- reading and understanding scientific texts
- writing of the seminar paper
- giving a presentation

Contents of the module:
The subject of environmetrics is the statistical analysis of the environmental processes. Environmetrics has close relationships with many other fields of science like natural sciences, engineering, medicine and economics. As environmental issues become more complex and environmental decision-making strives to be more precise, quantitative analysis becomes more important. New questions are requiring developing of new statistical methods and quantitative techniques to provide answers. The students should get familiar with statistical methods that are used to analyze environmental data and how this methods can be successfully applied to environmental data.

Teaching and learning methods:
Vorlesung, Projektarbeit, Präsentationen, Diskussionen

Additional feature:
Visit of a wind park and a measuring station of the air pollution.

Literature (compulsory reading, recommended literature):

Further information:
First meeting as announced on chair's web page. Further meetings will be appointed during the first meeting.
Registration in Moodle required.