What term refers to the statistical methods specifically designed for analyzing spatial data?

The term that accurately describes the statistical methods specifically designed for analyzing spatial data is referred to as "Spatial Statistics." This field encompasses a variety of techniques that account for the unique characteristics of spatial data, such as spatial autocorrelation and variability, which are not typically addressed in traditional statistical methods.

Spatial Statistics provides tools to analyze spatial relationships, patterns, and distributions within datasets that have geographic references. For example, methodologies in this area include kriging, which is used for interpolation of geospatial data, and spatial regression techniques that assess relationships between dependent and independent variables while acknowledging their spatial properties.

Other terms such as "Geospatial Analysis" broadly refer to the use of geospatial data and methods, including but not limited to Spatial Statistics. "Standard Statistics" generally refers to statistical techniques applied without specific consideration for spatial data, making them less suitable for analyzing datasets where spatial relationships are important. "Statistic Inference" pertains to predictive modeling and conclusions drawn from sample data rather than the specialized techniques used for spatial data analysis, underscoring its lack of direct relation to the unique challenges presented by spatial datasets.