Course 10 Spatial Statistics

Spatial statistics is a branch of statistics that deals with analyzing and modeling data that are spatially referenced or geographically distributed. It focuses on understanding the patterns, relationships, and dependencies that arise when data points are associated with specific locations in space. Unlike traditional statistical methods that assume data points are independent, spatial statistics accounts for spatial autocorrelation, where observations near each other are often more similar than those further apart. This field has widespread applications across disciplines, including environmental science, epidemiology, geography, and urban planning, providing tools to analyze phenomena such as disease spread, resource distribution, and landscape patterns. Key methods in spatial statistics include point pattern analysis, geostatistics, and spatial regression models, offering powerful frameworks for uncovering spatial structures and making location-based predictions.