PuSH - Publication Server of Helmholtz Zentrum München

zu Castell, W. ; Matyssek, R.* ; Göttlein, A.* ; Fleischmann, F.* ; Staninska, A.

Learning from various plants and scenarios: Statistical modeling.

In: Growth and Defence in Plants. Berlin ; Heidelberg: Springer, 2012. 355-373 (Ecol. Stud. ; 220)
Open Access Green as soon as Postprint is submitted to ZB.
Experimental approaches studying complex phenomena in nature often show various answers to one question, depending on the experimental scale chosen, the experimental set-up and other types of restrictions chosen along the way. This difficulty does not only result from a lack of experimental technology, but also from our reductionist approach. While having been shown to be very powerful in experimental sciences, the approach also faces limitations dealing with complex systems. Being aware of such difficulties, statistical methodology has to provide answers for various levels of contingency. We discuss some of these questions and look at examples of statistical methods according to their power in addressing questions raised from complexity.
Additional Metrics?
Edit extra informations Login
Publication type Article: Edited volume or book chapter
ISSN (print) / ISBN 0070-8356
ISBN 978-3-642-30644-0
Book Volume Title Growth and Defence in Plants
Quellenangaben Volume: 220, Issue: , Pages: 355-373 Article Number: , Supplement: ,
Publisher Springer
Publishing Place Berlin ; Heidelberg
Reviewing status Peer reviewed