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In various scientific fields it is important to find precise mathematical model for points randomly scattered in space (or time). Poisson point processes represent exactly this kind of model. Mathematical tools for their analysis are typically very advanced, but already relatively simple probabilistic methods yield relevant conclusions about the behaviour of randomly scattered points and their clustering in particular. The article illustrates this type of methods on practical problems in various settings. [ABSTRACT FROM AUTHOR]