In order to present the differences and contrast the strengths and weaknesses between methods, the geospatial methods are grouped into three categories: simple, more complex, and advanced. Simple methods assume a conceptually uncomplicated relationship between sampled variables and the locations from which the data were collected. There is no provision for statistical error. More complex methods use the local average of the data and their relative locations in regression models. The variation between the regression model and the empirical data points support estimates of error. Advanced methods include a component for error not considered in the category of more complex methods. The choice between methods for a project depends on the character of the data and the goals of the analysis. Additional information about the categories is included in the Categories of Geospatial Interpolation Methods section.