Learning from Various Plants and Scenarios: Statistical Modeling

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.

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