Archaeologists spend a great amount of their time pondering maps of points, so-called distribution maps of sites or artefacts, and trying to make sense of them (Fig. 1; see also Fig. 2 and Fig. 8, upper left). The mapped points are, of course, manifestations of something much more complex and interesting. And these hidden processes behind the points are the real phenomena that are of academic interest. When attempting inference from indirect evidence, such as point distributions, the use of formal methods is of particular importance. A rigid analytical approach helps the human interpreter avoid jumping to premature conclusions or reading too much into the data. Indeed, the eagerness of the human brain to identify patterns, i.e., recurring regularities, in visual information seems hard to control and even harder to replace with a more objective approach. The following sections will discuss mathematical methods for the detection of clusters, a type of pattern that is characterised by locally increased densities. Such clusters are assumed to be indicative of higher frequencies of human activities, i.e., they represent “hotspots” of social processes (note that this deviates from the use of the term “cluster” within the context of multivariate clustering analysis as discussed by Mucha et al. in Chapter 9).