This chapter deals with

• Calculating basic statistics for analyzing geographic distributions including mean center, median center, central feature, standard distance and standard deviational ellipse (centrographics)

• Explaining how these metrics can be used to describe spatial arrangements of different sets of point patterns

• Defining locational and spatial outliers

• Introducing the notions of complete spatial randomness, first-order effects and second-order effects

• Analyzing point patterns through average nearest neighbor analysis

• Ripley’s K function

• Kernel density estimation

• Randomness and the meaning of spatial process in creating point patterns

  After a thorough study of the theory and lab sections, you will be able to

• Use spatial statistics to describe the distribution of point patterns

• Identify locational and spatial outliers

• Use statistical tools and tests to identify if a spatial point pattern is random, clustered or dispersed

• Use Ripley’s K and L functions to define the appropriate scale of analysis

• Use kernel density functions to produce smooth surfaces of points’ intensity over space

• Apply centrographics, conduct point pattern analysis, apply jernel density estimator and trace locational outliers through ArcGIS