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Seminar - Statistical Methods in Environmental Science

Seminar Statistical Methods in Environmental Science

 

 Veranstaltung für den Master (T-Modul)

 

Serviceveranstaltung für Masterstudierende der Kultur- bzw. Rechtswissenschaften

Serviceveranstaltung für das Doktorandenprogramm

 

Die Veranstaltung findet im Sommersemester 2014 statt.

 

The subject of environmetrics is the statistical analysis of 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 the development 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 learn how these methods can be successfully applied to environmental data. The seminar is given in English.

  

Conditions for getting a credit:

 
Seminar paper with oral presentation

 

Schedule of the lectures 

Introductory lectures are planned. Besides that, a short revision of multiple linear regression theory and both a theoretical and practical introduction to Geostatistics will be provided. Moreover, other important information concerning seminar papers and presentations will be mentioned during the first meeting.

 

The First meeting will take place on April 10th, 2014, 12pm – 14pm in HG 104.

 

There will be Introductory lectures in the first block every Monday at 11pm to 13pm in room GD 06.

 

The binding registration is from 16.03.2014 till 24.04.2014.

 

Suggestions on seminar topics are also possible and could be accepted if they are fitting the orientation of the seminar.

 

Every seminar paper consists of a theoretical part and a practical part. Each participant should provide a detailed description of the methods used and give a short literature overview. In the application part each student is given a real environmental dataset, which shall be analyzed through fitting the appropriate model and by producing geographic prediction maps of the corresponding environmental variable.

 

Datasets included

  1. Air pollution data (eg. PM10, NO2, O3)

  2. Meteorological data (temperature, rainfall, sunshine)

 

For further information or if you have any questions please contact vetter[at]europa-uni.de.
 

Registration in Hisportal is required.

 

Literature:

Abdel H. El-Shaarawi and Walter W. Piegorsch: Encyclopedia of Environmetrics. Wiley, Chichester, 2002.

Bruno F. and Cocchi D. (2002). A unified strategy for building simple air quality indices.Environmetrics, 13, 243-261.

Bruno. F. and Cocchi D. (2007). Recovering information from synthetic air quality indexes.Environmetrics, 18, 345-359.

O. Bodnar, M. Cameletti, A. Fassò, and W. Schmid (2008) Comparing air quality in Italy, Germany and Poland using BC indexes. Atmospheric Environment, 42, 8412-8421.

Aitana Lertxundi-Manterola and Marc Saez (2009). Modelling of nitrogen dioxide (NO2) and fine particle matter (PM10) air pollution in the metropolitan areas of Barcelona and Bilbao, Spain. Environmetrics, 20, 477-493.

Johannes Staehelin, Christian Keller, Wernera Stahel, Kurt Schläpfer, Urs Steinemann, Toni Bürgin and Stefan Schneider (1997). Modelling emission of road traffic from a tunnel study. Environmetrics, 8, 219-239.

Francis W. Zwiers and Hans von Storch (2004). On the role of statistics in climate research.International Journal of climatology, 24, 665-680.

Gabriela Beblo and Wolfgang Schmid: Modeling High Frequency Wind Speed Data. January 2011,  Europa-Universität Viadrina: Discussion Papers.

C. A. Glasbey  and D. J. Allcroft (2008) A spatiotemporal auto-regressive moving average model for solar radiation. Journal of the Royal Statistical Society, 57, 343-355.