ABSTRACT
The importance of geography and spatial analysis is increasingly being embraced by a wide variety of disciplines and so the need for effective ways to visualize the results has never been more paramount. Data analysis can employ straightforward or complex techniques and increasingly, with advances in technology and data availability more advanced approaches are being sought. The key to any successful map lies in the ability for it to efficiently capture the message and convey it to the reader but when dealing with the results of complex spatial analysis this can be challenging. Jeremy Mennis, in his paper on mapping the results of geographically weighted regression (GWR), recognized the importance of the cartographic approach when mapping the results. With reference to geographically weighted regression, Mennis states that parameter estimates should be represented in tangent with the distribution of significance to ensure that results are correctly interpreted.
