The study of statistical methods for spatial data analysis presents challenges that are fairly unique within the statistical sciences. Like few other areas, spatial statistics draws on and brings together philosophies, methodologies, and techniques that are typically taught separately in statistical curricula. Understanding spatial statistics requires tools from applied statistics, mathematical statistics, linear model theory, regression, time series, and stochastic processes. It also requires a different mindset, one focused on the unique characteristics of spatial data, and additional analytical tools designed explicitly for spatial data analysis.

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