ABSTRACT
Readers interested in further motivational material might enjoy Griffith’s fine treatment of polyomino games and spatial autocorrelation. Maps and spatial statistics can work together to offer a visual understanding of the extent to which neighboring values of quantified information influence each other. When coupled with a positional understanding of where these values are in geographic space, visualization, the use of one’s imagination to try to understand information in a pictorial or graphic manner, occurs. The Moran Coefficient and the Geary Ratio are often used to index spatial autocorrelation: to understand the mathematical developement of the ratios. The visualization of spatial dependence is an extension of both cartography and spatial statistics. Spatial statistics help us to understand the nature and the extent of the effects that neighbors have on each other. Random spatial autocorrelation is difficult to detect visually because patches of areas display similar information while patches of areas contain fragmented locational information.
