 Another straightforward way to visualize the points is a 2D histogram (sometimes called a quadrats) that bins the points into rectangular regions.A benefit of quadrat analysis is that it forces the analysis to take into account possible scales within which statistically significant inhomogeneities may be occurring.The null model for point patterns is complete spatial randomness (CSR), modeled as a Poisson process in R"n", which implies that the number of points in any arbitrary region "A" in "D" will be proportional to the area or volume of "A".